PASTOR: A Technical
Coefficient Generator for
Pasture and Livestock
Systems in the Humid
Tropics; version 2.0
A User Guide
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PE
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PASTOR: A Technical
Coefficient Generator for
Pasture and Livestock
Systems in the Humid
Tropics; version 2.0
A User Guide
B.A.M Bouman, A. Nieuwenhuyse & H. Hengsdijk
REPOSA: Research Program on Sustainability in Agriculture
Apartado 224-7210, Guápiles, Costa Rica
PE
Quantitative Approaches
in Systems Analysis No. xxx
February 1998
ab-dlo
CIP-DATA KONINKLIJKE BIBLIOTHEEK, DEN HAAG
B.A.M Bouman, A. Nieuwenhuyse & H. Hengsdijk
PASTOR: A technical coefficient generator for pasture
and livestock systems in the humid tropics/ B.A.M Bouman,
A. Nieuwenhuyse & H. Hengsdijk.
- Wageningen : DLO Research Institute for
Agrobiology and Soil Fertility ; Wageningen : The C.T. de
Wit Graduate School for Production Ecology. (Quantitative approaches in systems analysis ; no. xx)
ISBN 90-73384-34-6
NUGI 835
Subject headings: technical coefficient / beef cattle ;
pasture / humid tropics / Costa Rica
Keywords
Technical Coefficient Generator, Expert System, beef cattle, pasture, sustainability, Costa Rica
Guidelines 'Quantitative Approaches in Systems Analysis'
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publication editor at AB-DLO, or from the PE office:
H. Terburg
Th.H. Jetten
AB-DLO
Secretariat C.T. de Wit Graduate School
for Production Ecology
P.O. Box 14
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NL-6701 AN Wageningen
Phone:
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Phone:
(+) 31 317.485116
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Fax:
(+) 31 317.484855
E-mail:
h.terburg@ab.dlo.nl
E-mail:
theo.jetten@beleid.spp.wau.nl
Preface
This document is a users guide to the system PASTOR (PASture and livestock technical coefficient
generatOR), version 2.0. PASTOR generates technical coefficients for pastures, herds and feed
supplementing in cattle systems in the humid tropics. The system was developed in the project
REPOSA (Research Programme on Sustainability in Agriculture) in Guápiles, Costa Rica. REPOSA
is a cooperation between Wageningen Agricultural University (WAU), the Centre for Research and
Education in Tropical Agriculture (CATIE), and the Ministry of Agriculture and Livestock, Costa Rica
(MAG). PASTOR is complementary to LUCTOR (Land Use Crop technical coefficient generaTOR;
Hengsdijk & Nieuwenhuyse, 1998), a system developed by REPOSA to generate technical
coefficients for cropping systems in the North Atlantic Zone of Costa Rica.
The primary goal of PASTOR is to generate technical coefficients for linear programming models to
explore sustainable land use options. The system has also been found to be useful as a standalone tool for simple cost-benefit analyses of proposed cattle livestock systems. PASTOR was
especially developed for cattle livestock systems in the humid tropics using the Northern Atlantic
Zone (NAZ) in Costa Rica as case-study. However, the system was set up in a generic manner so
that, by adapting input files, users can make PASTOR suitable to other environments as well.
A complete listing of all PASTOR data files as used by REPOSA in the NAZ of Costa Rica is
included as appendices to serve as documentation of current and possible alternative beef
production systems in the NAZ.
PASTOR 2.0 can be obtained from:
B.A.M Bouman
Until October 1998:
REPOSA: Research Program on Sustainability in Agriculture
Apartado 224-7210, Guápiles, Costa Rica; Tel (+506) 710 6595; Fax (+506) 710 2327;
Email: bbouman@sol.racsa.co.cr
After October 1998:
AB-DLO, P.O. Box 14, NL-6700 AA Wageningen, The Netherlands. Phone: (+) 31 317.475723;
Fax: (+) 31 317.423110 ; E-mail b.a.m.bouman@ab.dlo.nl
Table of Contents
page
Preface
Table of Contents
Summary
1
1 The PASTOR system
3
1.1 Animal Production Systems at a defined Technology
1.2 PAsture production Systems at a defined Technology
1.2.1 Fertilised pasture
1.2.2 Unfertilised pastures
1.2.3 Technical coefficients
1.3 Feed Acquisition Systems at a defined Technology
2 PASTOR structure and operation
2.1 File lay-out and model running
2.2 Input files
2.3 Output files
2.4 PASTOR language
3 Generating Animal Production Systems (APSTs)
3.1 CRIA model
3.1.1 Herd characteristics file
3.1.2 Herd management file
3.1.3 Site file
3.2 GORDO model
3.2.1 Herd characteristics file
3.2.2 Herd management and site file
3.3 Special case: reruns
5
6
6
9
11
12
13
13
13
16
18
19
19
20
23
27
27
28
30
30
4 Generating Pasture Production Systems (PASTs)
31
4.1 PASTOF model
4.1.1 Pasture data file
4.1.2 Soil data file
4.1.3 CAT_CHAR data file
4.1.4 Site file
4.2 PASTOU model
4.2.1 Pasture data file
4.2.2 Soil, CAT_CHAR and site data file
4.3 Special case: reruns
31
32
40
42
43
44
44
50
50
5 Generating Feed Acquisition Systems (FASTs)
52
6 Attribute files
54
7 Error and warning messages
55
References
57
Appendix I: PASTOR input files
I-1
I.1 APST input files
I.1.1 CRIAHRD.DAT
I.1.2 CRIAMAN.DAT
I.1.3 GORDHRD.DAT
I.1.4 GORDMAN.DAT
I.2 PAST input files
I.2.1 ESTREL.DAT
I.2.2 BBRIZAN.DAT
I.2.3 TANNER.DAT
I.2.4 NATURAL.DAT
I.2.5 BPINTOI.DAT
I.3 Other input files
I.3.1 SOIL.DAT
I.3.2 SITE.DAT
I.3.3 FEEDS.DAT
I-1
I-1
I-2
I-4
I-5
I-7
I-7
I-10
I-13
I-16
I-18
I-20
I-20
I-21
I-22
Appendix II: PASTOR attribute files
I-24
II.1 Materials
II.2 Equipment
II.3 Traction
II.4 Fertiliser
II.5 Pesticide
II.6 Cattle
II.7 Feed
I-24
I-24
I-25
I-25
I-25
I-26
I-27
1
Summary
This document is a users guide to the expert system PASTOR (PASture and livestock technical
coefficient generatOR), version 2.0. PASTOR generates technical coefficients (TCs) for cattle
systems in the humid tropics, using the target-oriented approach. Three components of a cattle
system are defined, for which TCs are generated separately by individual models: Animal
Production Systems at a defined Technology (APSTs), PASture systems at a defined Technology
(PASTs) and Feed Acquisition Systems at a defined Technology (FASTs; feed supplements). For
APSTs, separate models exist for cattle breeding and cattle fattening systems. For PASTs separate
models exists for fertilised pastures with a user-defined soil nutrient balance and for unfertilised
pastures with an ‘open’ soil nutrient balance. Technical coefficients are inputs and outputs of
production systems, such as production (pasture yield, meat, milk), costs, labour use, soil nutrient
balances, nutrient losses to the environment and pesticide use. PASTOR was especially developed
for cattle livestock systems in the humid tropics using the Northern Atlantic Zone (NAZ) in Costa
Rica as case-study. However, the system was set up in a generic manner so that, by adapting input
files, users can make PASTOR suitable to other environments. Listings of all PASTOR data files are
included in the appendices to document current and possible alternative beef production systems in
the NAZ of Costa Rica as described and developed by REPOSA.
2
3
1 The PASTOR system
PASTOR generates technical coefficients for beef cattle livestock systems in the humid tropics.
Technical coefficients are inputs and outputs of production systems (Van Ittersum & Rabbinge,
1997; Hengsdijk et al., 1996), and are used in Linear Programming models to explore or optimise
land use systems (e.g. Griffith & Zepeda, 1994; Jones, 1989; Nicholson et al., 1994; Hazel &
Norton, 1986). Examples of the use of PASTOR-generated technical coefficients in linear
programming models are given in Bouman & Nieuwenhuyse (1998) and Bouman et al. (1998).
PASTOR can also be used as a stand-alone tool for simple cost-benefit analyses of proposed
alternative livestock systems.
A beef cattle system consists of three main components:
1. The herd, generating the marketable products meat and milk, and characterised by certain feed
requirements. A herd system entails the management and maintenance of a collection of
animals. Since management is explicitly addressed in the form of technology used, the term
APST1 is used: Animal Production System at a defined Technology.
2. Pastures supplying feed. Pasture production system entails the growing and management of
pasture (i.e. grass, or grass-legume mixtures). Here, the term PAST is used: PASture
production system at a defined Technology.
3. Feed supplements providing an additional source of feed. Feed supplementing simply entails a
specification of feed supplement options, and is abbreviated here as FAST: Feed Acquisition
System at a defined Technology.
For each of these three sub-systems, PASTOR contains separate models that can be run
individually (Figure 1.1). Within PASTOR, there is no formal relationship between APSTs, PASTs
and FASTs. Generated technical coefficients can be analysed for each sub-system separately, or
be integrally analysed in linear programming models (e.g. by equating feed requirements of APSTs
to feed supplied by PASTs and FASTs; Bouman & Nieuwenhuyse, 1998).
Technical coefficients are generated using the so-called ‘target oriented’ approach (Van Ittersum &
Rabbinge, 1997). This approach entails that target production levels are predefined and that
subsequently the amount of required inputs is calculated by PASTOR. The calculation of inputs is
based – as far as possible - on knowledge of physical, chemical, physiological and ecological
processes involved. When process knowledge is incomplete/absent, calculations are based on
expert knowledge, literature data and field observations. In this sense, PASTOR might be called an
‘expert system’. Target production levels may vary from potential production levels to very low
levels. In the first case, high external input levels (e.g. in the case of pastures fertilisers, crop
protection) will be required, and in the second case, low external input levels are needed. Next to
desired production levels, the manner (technology) of production can be specified. For instance,
certain operations may be performed with machines or may alternatively be done manually (or
using a combination of both). By specifying a number of target production levels and a number of
different technologies, PASTOR can generate technical coefficients of a large number of alternative
production systems. ‘Classical’ input technical coefficients are the use of resources such as
fertilisers, pesticides, machines, labour, and - of course - the total costs of production (using all the
required resources). ‘Classical’ output technical coefficients are yields and the economic value of
1 APST, PAST and FAST names were suggested by D.M. Jansen, in analogy to the terminology developed earlier in
REPOSA (Jansen & Schipper, 1995; Stoorvogel et al., 1995).
4
the yield. Next to these classical technical coefficients, PASTOR also calculates a number of other
technical coefficients called ‘sustainability indicators’ (Bouman et al., 1998). Examples are the soil
nutrient balance, losses of nutrients to the environment, and pesticide use.
PASTOR
APST
(herd)
Breeding
CRIA
Fattening
GORDO
Unfertilized
PASTOU
PAST
(Pastures)
Fertilized
PASTOF
FAST
(Feed
supplement)
SUPP
Figure 1.1. Schematic presentation of the main components of PASTOR (APST, PAST, FAST) and its models
(CRIA and GORDO for APSTs, PASTOU and PASTOF for PASTs, and SUPP for FASTs).
In the following paragraphs, a summary of the scientific background of PASTOR is given for each of
the APSTs, PASTs and FASTs components separately. Chapter 2 gives the technical structure and
lay-out of PASTOR, explains how to run the models and introduces all input and output files.
Chapters 3-5 give detailed explanation on how to steer the generation of the technical coefficients
of APSTs (Chapter 3), PASTs (Chapter 4) and FASTs (Chapter 5) by model input parameter
values, and gives further explanation on how technical coefficients are calculated. Chapter 6
explains a special set of data files, called attribute files, that contain attribute characteristics of
inputs used in the production systems. Chapter 7 mentions some possible error messages that
might be obtained by incorrect running of PASTOR and gives some hints on how to remedy these.
Finally, the appendices list all input files (model data files and attribute files) that accompany
PASTOR 2.0, which serve as documentation of beef cattle production systems as described and
developed for the North Atlantic Zone of Costa Rica by REPOSA.
5
1.1 Animal Production Systems at a defined Technology
PASTOR contains two separate models for the calculation of technical coefficients of APSTs
(herds), one for cattle breeding, called CRIA (Spanish for ‘breeding’), and one for beef fattening,
called GORDO (Spanish for ‘fattening’). The calculated technical coefficients are:




Production, in terms of meat and milk
Feed requirements, in terms of metabolizable energy, crude protein and phosphorus
Costs of production
Labour required
The exact definitions and units of the technical coefficients are given in Table 2.3.1 (Paragraph 2.3).
A breeding system is defined here as a system where calves are bred and subsequently sold at a
certain age or live weight. No animals are bought externally. A fattening system is defined here as a
system where young animals are bought, fattened for a period of time, and then sold. No animals
are bred internally. For both types, the modelled herds are ‘stationary’, which means that there are
no dynamics in herd size and composition over the year(s), (Upton, 1989; 1993). Based on a
specification of herd structure characteristics, target growth of the animals and target buying/selling
strategy, total composition, production and feed requirements of the herd are computed. The
(stationary) composition of the herd, i.e. the number and type of animals per age class, is calculated
using the method presented by Hengsdijk et al. (1996). The production of the herd is simply
obtained by summing the user-specified target live weight gains and milk production over all
animals in the herd, using the user-defined buying/selling strategy. Because of market price
differentiation, four classes of live weight products are differentiated: i) male and female calves of a
breeding system, ii) old cows of breeding and double purpose systems, iii) male animals of fattening
system, and iv) male and female animals of double purpose system 2. Next to live weight of the herd
as ‘output’, the required ‘input’ of live weight is calculated as the weight of bought animals to
maintain the herd composition (relevant in fattening systems).
Computations of feed requirements are based on equations for beef cattle as presented by the
National Research Council (NRC, 1996), and on NRC (1989) for dairy cattle. Calculations were
performed for each animal in the herd according to sex and age group, and for females according to
stage of pregnancy and lactation, and then summed to get total herd requirements. The amount of
milk produced and consumed internally in the herd is subtracted from these amounts to obtain
‘external’ feed requirements (i.e. that should be met by pasture or feed supplement intake;
Hengsdijk et al., 1996). It is noted that in this approach, the source of feed (e.g. pasture, feed
supplement) is not taken into account; i.e. the total amounts of metabolizable energy, crude protein
and phosphorus are calculated that are needed to sustain the desired target growth without taking
efficiency effects of feed composition into account (NRC, 1989). In the current form of CRIA and
GORDO, there are no seasonal effects on animal growth and herd composition (stationary
approach). The target live weight gains specified by the user are average values for a whole year.
Therefore, the calculated feed requirements are uniformly distributed over the year, i.e. monthly
feed requirements are calculated that are the same each month of the year. Yearly feed
requirements are twelve times the monthly calculated values 3.
2 The double purpose system, although not yet implemented as a separate model (such as CRIA and GORDO), already
features as separate live weight class in anticipation of future developments in PASTOR.
3 If users want to apply CRIA or GORDO in an environment with seasonality, the models should be run with input data
characteristic for each season, and the generated monthly feed requirements should be interpreted as being characteristic
6
The costs and labour requirements of the simulated APSTs are calculated from maintenance and
operation specifications provided by the user (e.g. the use of corrals and troughs and the
application of inoculations). Costs are expressed as an annuity factor to take account of investment
costs in materials with a life span larger than one year. Annuity costs were calculated using the
capital recovery factor (Price Gittinger, 1973) with a discount rate as specified by the user. Labour
use is expressed in two units: physical labour, and ‘annuity’ labour. Physical labour is just the sum
of all labour activities, where labour used in investment activities, such as building a corral, is
divided by the life span of the investment activity. Annuity labour is based on the same calculation
procedure as for costs: labour used in investment activities is ‘discounted’ into an annuity using the
same capital recovery factor as used in the annuity cost calculation. This way, the price of labour
can be kept a constant in LP modelling when computing total costs of alternative land use activities
(Schipper, 1996).
1.2 PAsture production Systems at a defined Technology
PASTOR contains two separate models for the calculation of technical coefficients of PASTs
(pastures), one for fertilised pastures with a ‘user-defined soil nutrient balance, called PASTOF, and
one for unfertilised pastures, called PASTOU. The calculated technical coefficients are:





Production, in terms of dry matter, metabolizable energy, crude protein and phosphorus
Costs of production
Labour required
Sustainability indicators: soil nutrient balances, N losses to the environment, pesticide use
Some fertiliser use specifications
The exact definitions and units of the technical coefficients are given in Table 2.3.2 (Paragraph 2.3).
1.2.1 Fertilised pasture
For fertilised grasses, PASTOF calculates technical coefficients for production techniques with a
pre-defined soil nutrient balance, i.e. no more nitrogen (N), potassium (K) and phosphorus (P) are
allowed to be removed from the soil than a pre-defined quantity by the user. For true sustainable
and stable pasture systems, the soil nutrient balance should be zero (Hengsdijk et al., 1996).
Variables that define alternative pasture production systems are grass species, soil type, stocking
rate and fertiliser level. Stocking rate is explicitly taken into account because of its effect on pasture
production (Ibrahim, 1994; Hernandez et al, 1995) and on the soil nutrient balance. The procedure
for calculating the technical coefficients is quite complex but involves, schematically, the following
steps (Figure 1.2). First, for each grass species, upper and lower production boundaries should be
estimated for the soil types under study in terms of biomass and content of metabolizable energy,
crude protein and phosphorus (user defined input). The upper boundary is the maximum attainable
production with no nutrient constraints (Bouman et al., 1996), and the lower boundary is the
minimum production level supposedly attained on exhausted soils where the grass just manages to
for that season. The generated production, cost and labour use technical coefficients should be summed with a weighing
factor per season to get year totals.
7
Grass charact.
Climate
Attainable
production
on best soil
Soil charact.
Management:
stocking rate
Soil-limited
production
Attai nable biomass
on offer
Manure
Deposition
Fixation
Labour use
XXXXX : input data
: generated TC
: intermediae
variables
Costs
Nutrient loss
Nutrient
requirements
Actual biomass
and nutrients
provided
Fertilizer
requirements
Biocide use
: model
: flow of information
Management:
allowed mining
Management:
weed control
fert. application
Management:
fert. application
Soil charact.
(nutrient
loss fractions)
Figure 1.2. Schematic representation of calculation procedure of technical coefficients by PASTOF for fertilised
pastures.
survive. On the basis of the maximum attainable production, PASTOF calculates attainable feed on
offer as function of a range of (user-defined) stocking rates. With increasing stocking rate, less of
the pasture biomass is available for uptake because of trampling and deposition of faeces and urine
(Deenen, 1994; Van der Ven, 1992). For each feed level thus obtained (as function of grass
species, soil type and stocking rate), the attainable amount of biomass and nutrients that may be
removed by the grazing stock is calculated. The supposedly grazing stock associated with each
stocking rate has a certain feed requirement and manure and urine production (which may be
calculated by the CRIA or GORDO models, but not necessarily!), based on the assumption of a
fixed target growth rate. A soil nutrient balance is calculated using an adapted version of the model
presented by Stoorvogel (1993). This model determines the soil nutrient balance, where the user
can specify the amount of nutrient mining (depletion of soil nutrient stock) that is allowed. The
calculation of the soil nutrient balance is based on estimates/calculations for all inputs, namely
atmospheric deposition, fixation by micro-organisms, weathering, manure and urine (from the
grazing stock), and all outputs, namely the attainable amount that may be removed by grazing and
losses by erosion, leaching, volatalization, denitrification/nitrification, and fixation (for P). A negative
balance below the allowed mining level indicates the amount of fertiliser that is needed to sustain
the attainable amount of biomass that may be removed (Hengsdijk et al., 1996). Next, a userdefined range of fertiliser application levels is specified, ranging from 0-100% of the amount needed
to sustain attainable production. Gross fertiliser input is calculated from the required net amount, by
taking account of loss fractions specified by the user per nutrient type (Hengsdijk et al., 1996). Next,
nutrient concentrations in the biomass of the pasture are calculated for each fertiliser level by linear
interpolation between the minimum and maximum production points given earlier (Figure 1.3), using
the total amount of nutrients available for growth. With these concentrations, the soil nutrient
balance is again invoked for each fertiliser level, and new amounts of feed on offer are calculated
by matching all inputs with all outputs.
8
CP%
13.00
12.00
11.00
10.00
9.00
8.00
7.00
6.00
5.00
0
500
1000
1500
2000
N Application (kg/ha)
Figure 1.3. Crude protein content (CP%) as function of N applied (in form of fertiliser, manure and urinary N).
Drawn line is simulation by PASTOF for fertilised Cynodon nlemfuensis (Estrella) on fertile well
drained soil, points are observed data in humid tropical environments: circles are mean values of
Pangola grass and dots are observed mean values over a large number of species (source of
observed data: Vicente-Chandler, 1974, as reported by Crowder & Chenda, 1982.
ME (Mcal/ha)
60000
50000
40000
30000
II
I
20000
10000
0
0
2
4
6
8
10
Stocking rate (AU/ha)
Figure 1.4. Attainable feed on offer (black diamonds) and feed requirements (white diamonds) in terms of
metabolizable energy (ME) versus stocking rate, for fertilised Cynodon nlemfuensis (Estrella) on
fertile well drained soil. In section I, attainable feed on offer exceeds the intake requirements of
the stock. In grazing only systems, the actual feed intake is limited by the ‘white diamond line’ ; in
grazing plus mowing systems, the difference between the black and the white diamonds is
supposed to be removed by mowing. In section II, the feed requirements of the stock are higher
than what the pasture can offer, and supplements are supposed to be used to feed the stock.
9
E.g. in case of 0% fertiliser application, the amount of feed removed by grazing can not be higher
than the amount that is produced with external inputs from atmospheric deposition, fixation by
micro-organisms, weathering and faeces and urine only (minimum level). In case of 100% fertiliser
gift, the amount that can be removed by grazing equals the attainable production.
There are two options of pasture grazing implemented that are governed by the user, i) pure
grazing systems where pasture is only removed by the grazing stock, and ii) mixed grazing-mowing
systems, where pastures are also occasionally mown. In the grazing only system, no more biomass
can be removed than is eaten by the cattle, i.e. the actual amount of feed removed by the cattle is
the minimum of the amount of feed on offer and the cattle intake requirements of the grazing stock.
(Figure 1.4). In mixed grazing-mowing systems, there may exist a surplus of biomass on offer
compared to cattle intake requirements, which is supposed to be removed from the pasture by
mowing. In both systems, when cattle intake requirements exceed the amount on offer, the
shortage is supposed to be balanced by feed supplements, thus constituting an alternative source
of external nutrients to the pasture.
Costs and labour use involve material inputs such as fences, tools and herbicides, and operations
such as establishment, weeding, fertiliser application (if any) and maintenance.
Input data and simulated output of PASTOF were checked against well-established agronomic
knowledge (e.g. Figure 1.6) and field data from experiments in tropical humid climates reported in
literature (e.g. Figure 1.3 and 1.5), and were carefully reviewed by a number of outside experts (e.g.
CATIE and MAG experts).
1.2.2 Unfertilised pastures
For unfertilised pastures, the calculation procedures of PASTOU are relatively simple. Since no
fertiliser is applied by definition, actual feed on offer is simply specified by the user as function of a
range of feasible stocking rates. In the case of grass-legume mixtures, the soil nutrient balance
model takes account of the additional input of N by the legume. The soil nutrient balance is merely
the result of book-keeping of all nutrient inputs and outputs (Hengsdijk et al., 1996), and may be
zero or negative. Negative soil nutrient balances indicate that the modelled production is not
sustainable, i.e. the user-supplied yield levels can not be maintained on the long run. Many actual
production systems in humid tropical environments are unsustainable in this sense (Bouman &
Nieuwenhuyse, 1998). The calculation procedure for costs and labour requirements is the same as
for the fertilised pastures.
10
20
Dry matter (t/ha)
mmmattermatter
18
16
14
2
12
1
10
8
6
4
2
0
0
100
200
300
400
500
600
N fertilizer application (kg/ha)
Figure 1.5. PASTOF simulated (drawn lines) and observed (markers with dotted lines) yield of fertilised
Cynodon nlemfuensis (Estrella) on a fertile well-drained soil versus fertiliser-N application. Drawn
line 1 was simulated with 40% N uptake efficiency; line 2 with 50% (estimated range in actual
values). Experimental data were for a 14-day (diamonds), 21-day (squares) and 28-day
(pyramids) grazing rotation. Experimental data from Salazar, 1977.
Dry matter yield (*10 kg/ha)
2000
1500
1000
500
N application (kg/ha)
N yield (kg/ha)
0
-1000
-800
-600
-400
-200
0
200
400
600
-500
-1000
N application (kg/ha)
-1500
Figure 1.6. Three quadrant diagram of PASTOF-simulated yield, fertiliser-N application and N yield for fertilised
Cynodon nlemfuensis (Estrella) on a fertile well-drained soil. The solid line was simulated with a
stocking rate of 0.25 AU ha-1, the broken line with 1 AU ha-1, and the large dotted line with 3 AU
ha-1 .
11
1.2.3 Technical coefficients
Production
The calculated production technical coefficients are ‘removed’ amounts (yield) of dry matter,
metabolisable energy, crude protein and phosphorus, both on monthly and on yearly basis. The
’removed’ amount is either the amount eaten by the grazing stock, when pastures are grazed only,
or the combination of the amount eaten plus the amount removed by cutting. This choice is
governed by input control by the user (see Chapter 4). The pasture may not deliver sufficient
removable feed to feed the grazing stock (in which case it is assumed that feed supplements are
given to maintain the grazing stock at its fixed growth rate). Therefore, two coefficients express the
difference between ‘removable’ feed and feed demand by the stock in terms of metabolisable
energy (DMEHRD, Table 2.3.2) and crude protein (DCPHRD, Table 2.3.2), (these two being the
most limiting parameters in terms of animal feed requirement). In the case of grazed pastures only,
these parameters can be negative or zero only. In the case of the combination of grazing with
cutting, these parameters may take negative as well as positive values.
Sustainability.
Soil nutrient balances are given for nitrogen (N), phosphorus (P) and potassium (K). N losses to the
environment are expressed in terms of leaching losses, volatilisation losses and denitrification
losses. Volatilisation of N via ammoniac results in acid rain; leached N is a potential soil water
pollutant; and denitrification/nitrification losses of N via N 2O and NO add to the greenhouse gas
effect (Keller et al., 1993). Two indicators are related to pesticide use: an ordinal so-called Pesticide
Environmental Impact Index (PEII; Jansen et al., 1995 4), and the total amount of active ingredients
used (PAI). Even though the latter is relatively easy to monitor and much used, it is not a particularly
appropriate indicator as active ingredients differ considerably with regard to their environmental
impact (Van der Werf, 1996). The PEII takes into account not only active ingredients used but also
their degree of toxicity and their persistence in the environment. Both PEII and PAI are summed
over all pesticide inputs applied.
Fertiliser use
Some technical coefficients are generated that illustrate the use and some losses of N, P and K
fertiliser applied. These concern gross N, P and K input, the yearly application frequency, the gift
size per application, the fertiliser application time, and N, P and K leaching losses (see Table 2.3.2).
Labour use and costs
Labour use and costs of production are calculated the same way as explained for APSTs
(Paragraph 1.1).
4 Jansen et al., 1995, used the term Biocide Index (BILU).
12
1.3 Feed Acquisition Systems at a defined Technology
The model SUPP of PASTOR calculates technical coefficients for FASTs:



Feed provided, in terms of metabolizable energy, crude protein and phosphorus
Costs of application
Labour required
The exact definitions and units of the technical coefficients are given in Table 2.3.3 (Paragraph 2.3).
The SUPP model is very simple and merely ‘converts’ data supplied by the user in input files into
the same format as that used for the technical coefficients of the other systems (i.e. APSTs and
PASTs). Labour use and costs of application are calculated the same way as explained for APSTs
(Paragraph 1.1).
13
2 PASTOR structure and operation
2.1 File lay-out and model running
PASTOR 2.0 consists of models (executable Fortran files) with corresponding input files, organised
in a certain directory structure (Figure 2.1). There are five independent models to generate technical
coefficients for alternative APSTs, PASTs and FASTs separately:
APST:
 CRIA for cattle breeding systems
 GORDO for cattle fattening systems
PAST:
 PASTOF for fertilised pastures with a user-defined soil nutrient balance
 PASTOU for unfertilised pastures with an ‘open’ soil nutrient balance
FAST:
 SUPP for feed supplements
Each model is run by giving the command ‘MODEL.EXE’ (where MODEL stands for the name of the
model to be run, i.e. CRIA, GORDO,…, SUPP) in the appropiate sub-directory where the model is
located (Figure 2.1). Each model needs a set of input files as specified in the CONTROL.DAT file –
and optionally in the RERUNS.DAT file, see Paragraph 2.2 - that accompanies each model. The
PASTOR models create output files that contain the generated technical coefficients, and which are
stored in a separate sub-directory (PASTOR\FILE_OUT; Figure 2.1). The names of the output files
are specified in the CONTROL.DAT file accompanying each model. How to exactly run and control
each model of PASTOR is explained in detail in Chapters 3-5.
2.2 Input files
The input files given in Figure 2.1 accompany PASTOR 2.0. They characterise systems applicable
to the North Atlantic Zone of Costa Rica as collected in the REPOSA project (Bouman et al., 1998).
There are two types of input files: model data files (*.DAT files) and so-called attribute files (*.ATF
files), Table 2.1. In model data files, the user specifies characteristics and management of the
system to be modelled (APST, PAST or FAST). For instance, for the PAST models PASTOF and
PASTOU, the pasture input file contains data that characterise the type of pasture to be modelled
(e.g. attainable production level, content of nutrients and metabolizable energy) and the way the
pasture is managed (e.g. amount of fertiliser, manner of weeding). In model data files, reference is
made to inputs that are used in the management, such as materials, pesticides, equipments or
fertilisers. These inputs are listed with their characteristics (attributes) in the so-called attribute files.
Attributes are e.g. cost price (or rent price), unit of measure and toxicity (in the case of pesticides).
In principle, all model data and attribute files are self-explanatory, i.e. all parameters that need to be
14
PASTOR
MOD_CRIA
CRIA.EXE
CONTROL.DAT
(RERUNS.DAT)
MOD_GORD
GORDO.EXE
CONTROL.DAT
(RERUNS.DAT)
MOD_PASF
PASTOF.EXE
CONTROL.DAT
(RERUNS.DAT)
MOD_PASU
PASTOU.EXE
CONTROL.DAT
(RERUNS.DAT)
MOD_SUPP
SUPP.EXE
CONTROL.DAT
FILE_IN
HERD
CRIAHRD.DAT
GORDHRD.DAT
CRIAMAN.DAT
GORDMAN.DAT
PASTO
ESTREL.DAT
BBRIZAN.DAT
TANNER.DAT
NATURAL.DAT
BPINTOI.DAT
FEED
FEEDS.DAT
SOIL.DAT
SITE.DAT
CAT_CHAR.DAT
FILE_ATR
MATER.ATF
EQUIP.ATF
TRACTION.ATF
FERT.ATF
BIOCID.ATF
CATTLE.ATF
FEEDS.ATF
FILE_OUT
*.PRN
Figure 2.1. Directory structure and files of PASTOR. Names in boxes are sub-directories, others are
executable programs (*.EXE), run control files (CONTROL.DAT, RERUNS.DAT), input files
(*.DAT), attribute files (*ATF) and output files (*.PRN)
15
Table 2.1. Model data and attribute files used by PASTOR 2.0
Directory
File name
Explanation
FILE_IN\HERD
CRIAHRD.DAT
Herd characteristics for breeding herd
GORDHRD.DAT
Herd characteristics for fattening herd
CRIAMAN.DAT
Management characteristics for breeding herd
GORDMAN.DAT
Management characteristics for fattening herd
ESTREL.DAT
Characteristics and management of Estrella grass
BBRIZAN.DAT
Characteristics and management of Brachiaria brizanta grass
TANNER.DAT
Characteristics and management of Tanner grass
NATURAL.DAT
Characteristics and management of ‘Natural’ grass
BPINTOI.DAT
Characteristics and management of Brachiaria brizanta with
FILE_IN\PASTO
Arachis pintoi legume
FILE_IN\FEED
FEEDS.DAT
Selection of feed supplements
FILE_IN
SOIL.DAT
Soil characteristics
SITE.DAT
Site characteristics
CAT_CHAR.DAT
Properties of grazing stock on pasture (optionally produced by
APST model CRIA)
FILE_ATR
BIOCID.ATF
Properties of pesticides
CATTLE.ATF
Properties of specific inputs for cattle maintenance
EQUIP.ATF
Properties of equipments
FEEDS.ATF
Properties of feed supplements
FERT.ATF
Properties of fertilisers
MATER.ATF
Properties of materials
TRACTION.ATF
Properties of types of traction
supplied (quantified) are explained and their units given in the files themselves. All input files are in
ASCII and can be changed or updated by the user. The standard input files of PASTOR 2.0 are
listed in Table 2.1.
Other input files are the CONTROL.DAT and the optional RERUNS.DAT files that accompany each
of the PASTOR models. Thus, the sub-directories MOD_CRIA, MOD_GORD, MOD_PASF,
MOD_PASU and MOD_SUPP all contain an executable program (*.EXE) and their accompanying
CONTROL.DAT and (optional) RERUNS.DAT file. CONTROL.DAT is used to specify the various
model data and attribute files for the model. The names of these files in CONTROL.DAT may be
changed by the user. For instance, the user that runs the model PASTOF for fertilised grasslands
specifies the name of the grass file (e.g. ESTREL.DAT, TANNER.DAT or BBRIZAN.DAT) in the
CONTROL.DAT file in the same directory. Of course, a user can also make a completely new input
file, and specify this file name in CONTROL.DAT.
All models can make so-called reruns. In a rerun, the program is repeatedly executed with different
input files (or different parameter values). The name of the input file needs to be given in the
RERUNS.DAT file. For instance, the PASTOF model can be run for all three available grass types
by specifying ESTREL.DAT in the CONTROL.DAT file, and by specifying TANNER.DAT and
BBRIZAN.DAT in the RERUNS.DAT file. When the RERUNS.DAT file is not present, the model is
only executed one time (with the file specifications as in CONTROL.DAT). See Van Kraalingen
(1995) for more details on using the rerun facility, plus the relevant paragraphs in Chapters 3-5.
16
2.3 Output files
The PASTOR models produce a number of output files that contain the generated technical
coefficients. Table 2.3.1 lists and explains the files produced by the APST models CRIA and
GORDO, Table 2.3.2 those produced by the PAST models PASTOF and PASTOU, and Table 2.3.3
those by the FAST model SUPP.
Table 2.3.1 Output files produced by CRIA (CRIA*) and GORDO (GORD*) herd models with an explanation of
the technical coefficients (TCs) they contain. All TCs are on yearly basis unless otherwise specified.
File name
TC
Explanation
Unit
CRIAP, GORDP
LWCY
Live weight of sold male and female calves in breeding system
kg/herd/y
LWCO
Live weight of sold old cows in breeding and double-purpose
kg/herd/y
system
LWEY
Live weight of sold male calves in fattening system
kg/herd/y
LWDY
Live weight of sold male and female calves in double-purpose
kg/herd/y
system
MLK
Milk produced
kg/herd/y
HLABP
Total physical labour needed for herd, per year
d/herd/y
HLABA
Total ‘annuity’ labour needed for herd, per year
d/herd/y
HCOSTS
Total annuity costs for herd
colon/herd/y
HLABP
Total physical labour needed for herd, per month
d/herd/mnth
HLABA
Total ‘annuity’ labour needed for herd, per month
d/herd/mnth
HME
Monthly required metabolizable energy
Mcal/herd/mnth
HCP
Monthly required crude protein
kg/herd/mnth
HP
Monthly required phosphorus
kg/herd/mnth
HSIZE
Herd size in animals
no
HSAU
Herd size in animal units (1 AU = 400 kg)
no
CRIAIN, GORDIN
LWCINP
Inputted (bought) weight of animals (calves)
kg/herd/y
CAT_CHAR*
-
No TCs generated, but general information (CRIA model only)
-
CRIALC, GORDLC
CRIALM, GORDLM
CRIAR, GORDR
*: the file CAT_CHAR does not contain technical coefficients, but general information on the characteristics of the simulated
herd of a breeding system (thus produced by CRIA only). This file may optionally be used as input data file for the pasture
models PASTOF and PASTOU (see Chapter 4).
17
Table 2.3.2 Output files produced by PASTOF (PFER*) and PASTOU (PUNF*) pasture models with an
explanation of the technical coefficients (TCs) they contain. All TCs are on yearly basis unless otherwise
specified.
File
TC
Explanation
Unit
PFERPM, PUNFPM
SDMN
HME
HCP
HP
SR
DMEHRD
DCPHRD
Monthly supplied dry matter
Monthly supplied metabolizable Energy (ME)
Monthly supplied crude Protein
Monthly supplied phosphorus
Stocking rate
Supplied ME by pasture - eaten ME by herd
Supplied CP by pasture - eaten CP by herd
kg/ha/mnth
Mcal/ha/mnth
kg/ha/mnth
kg/ha/mnth
AU/ha
Mcal/ha/mnth
kg/ha/mnth
PFERPY, PUNFPY
SDMN
HME
HCP
HP
SR
DMEHRD
DCPHRD
Yearly supplied dry matter
Yearly supplied metabolizable Energy (ME)
Yearly supplied crude Protein
Yearly supplied phosphorus
Stocking rate
Yearly supplied ME by pasture - eaten ME by herd
Yearly supplied CP by pasture - eaten CP by herd
kg/ha/y
Mcal/ha/y
kg/ha/y
kg/ha/y
AU/ha
Mcal/ha/y
kg/ha/mnth
PFERLM, PUNFLM
GLABP
GLABA
Total monthly physical labour required by pasture
Total monthly ‘annuity’ labour required by pasture
d/mnth
d/mnth
PFERLC, PUNFLC
GLABP
GLABA
COST
COSTEST
COSTBIO
COSTFET
COSTOP
Total yearly physical labour required by pasture
Total yearly ‘annuity’ labour required by pasture
Total annuity costs for pasture production
Annuity costs for pasture establishment
Annuity costs for herbicides, pesticides etc.
Annuity costs for fertiliser
Annuity costs for various materials used in operations
d/y
d/y
colon/ha/y
colon/ha/y
colon/ha/y
colon/ha/y
colon/ha/y
PFERS, PUNFS
NBAL
PBAL
KBAL
NLEA
NVOL
NDEN
PEII
PAI
Soil N balance
Soil P balance
Soil K balance
N leached
N volatilised
N denitrified
Pesticide Environmental Impact Index
Amount of active ingredients of pesticides applied
kg/ha/y
kg/ha/y
kg/ha/y
kg/ha/y
kg/ha/y
kg/ha/y
kg/ha/y
PFERX, PUNFX
FIN
FIP
FIK
FFREQ
FSGIFT
FAPDRS
NLEA
PLEA
KLEA
Gross fertiliser N input
Gross fertiliser P input
Gross fertiliser K input
Fertiliser gift frequency
Fertiliser gift size
Fertiliser application duration
N leached
P leached
K leached
kg/ha/y
kg/ha/y
kg/ha/y
no/ha/y
kg/ha/y
h/ha
kg/ha/y
kg/ha/y
kg/ha/y
PFERCOM, PUNFCOM
-
A list of generated alternative PASTs
-
18
Table 2.3.3 Output files produced by SUPP feed supplement model with an explanation of the technical
coefficients (TCs) they contain. All TCs are per kilogram applied feed supplement.
File
TC
Explanation
Unit
FEEDP
HME
Supplied metabolizable Energy in feed supplement
Mcal/kg
HCP
Supplied crude Protein in feed supplement
kg/kg
HP
Supplied phosphorus in feed supplement
kg/kg
FLABP
Total physical labour needed for application of feed supplement
d/kg
FLABA
Labour ‘annuity’ labour needed for application of feed supplement
d/kg
FCOST
Annuity costs for application of feed supplement
colon/kg
FEEDLC
The format of all output files (except CAT_CAR.DAT; see Chapter 3) is designed for easy reading
by linear programming models programmed in GAMS (Brooke et al., 1992)5. The files are standard
ASCII, and data columns are space-separated. Each output file contains a header explaining the
technical coefficients in the columns. The lines of the headers begin with an asterix so that they are
skipped while reading by GAMS (and other Fortran) programs.
2.4 PASTOR language
PASTOR is programmed in the language FORTRAN77. Use was made of a special modelling
structure as developed for crop simulation, called FSE (Fortran simulation Environment; van
Kraalingen, 1995), and of a set of Fortran utilities called TTUTIL (Rappoldt & Van Kraalingen,
1990). During development, guidelines for software quality control as under development by ABDLO (Van Kraalingen, pers. comm.) have been applied as much as possible. This document
describes the use of the Fortran executable files; the source code of PASTOR is available on
request by the authors. PASTOR was compiled and linked on a 486 DOS Personal Computer, and
should run on any 486 PC - or higher - operating under DOS.
5 The PASTOF and PASTOU models may also produce output files suitable for reading by the Century and the DNDC
simulation models. This option, governed by the user in the CONTROL.DAT files, falls outside the scope of this manual.
19
3 Generating Animal Production Systems (APSTs)
The models to generate animal production systems (APSTs) are run by giving the *.EXE command
in the appropriate subdirectory, i.e. CRAI.EXE for breeding herds in the PASTOR\CRIA_MOD subdirectory, or GORDO.EXE in the PASTOR\GORD_MOD sub-directory. In the following paragraphs,
the control over executing the CRIA and GORDO models is explained in detail.
3.1 CRIA model
In CONTROL.DAT (in the sub-directory MOD_CRIA), the required model input and attribute files of
the CRIA model for breeding herds are specified:
*************************** CONTROL.DAT ***********************
* Control file for CRIA
model
* PASTOR 2.0
*
*
***************************************************************
* Detailed output control parameter:
* 'Y' means that detailed data are written to file RES.DAT
* 'N' means that no RES.DAT file is produced (for large reruns!)
OUTPUT = 'N'
* FILEI0
Input file with financial data
* FILEI1
Input file with herd data
* FILEI2
Input file with ..... data
* FILEI3
Input file with ..... data
* FILEI4-8
Attribute input files
FILEI0 = 'C:\PASTOR\FILE_IN\SITE.DAT'
FILEI1 = 'C:\PASTOR\FILE_IN\HERD\CRIAHRD.DAT'
FILEI2 = 'C:\PASTOR\FILE_IN\HERD\CRIAMAN.DAT'
FILEI3 = 'C:\PASTOR\FILE_ATR\MATER.ATF'
FILEI4 = 'C:\PASTOR\FILE_ATR\CATTLE.ATF'
FILEI5 = 'C:\PASTOR\FILE_ATR\FEEDS.ATF'
* Output files
* FILEO1
Monthly feed requirements
* FILEO2
Herd products ('yields')
* FILEO3
Yearly labour req. plus costs for herd
* FILEO4
Monthly labour req. for herd
* FILEO6
Various data
* FILEO8
Herd animal weight input
FILEO1 = 'C:\PASTOR\FILE_OUT\CRIAR.PRN'
FILEO2 = 'C:\PASTOR\FILE_OUT\CRIAP.PRN'
FILEO3 = 'C:\PASTOR\FILE_OUT\CRIALC.PRN'
FILEO4 = 'C:\PASTOR\FILE_OUT\CRIALM.PRN'
20
FILEO6 = 'C:\PASTOR\FILE_IN\CAT_CHAR.DAT'
FILEO8 = 'C:\PASTOR\FILE_OUT\CRIAIN.PRN'
The model input and attribute files needed are specified at the variables FILEI0-5. Note that, beside
the file name, the complete path of the sub-directory where the files are stored is given. Users may
change the names of the input files when they have created their own input files: FILEI0 contains
site-characteristics; FILEI1 specifies the name of a file that contains characteristics of the herd to be
modelled; FILEI2 contains the management of the herd. The site file contains so-called ‘site’ data, in
PASTOR 2.0 only rate of interest and work hours in a day, and is also used by the other models of
PASTOR. The herd characteristics, herd management and site file are explained in detail in the
following paragraphs
Attribute files (FILEI3-5) are explained in Chapter 6.The names of the attribute files should not be
changed by the user.
The names of the output files are given under the variables FILEO1-8. These names are the same
as given in Table 2.3.1, but may be changed by the user. Next to these ‘standard’ output files
indicated at the FILEO variables, CRIA provides an option to produce detailed output that specifies
the herd structure, e.g. animal numbers and weights per age class. This file is called RES.DAT, and
will be produced when the OUTPUT variable is put to ‘Y’. Be default, this variable is put to ‘N’
because RES.DAT can become quite large when making reruns. The output file specified under
FILEO6, CAT_CHAR.DAT, contains summary characteristics of the simulated herd (herd size, feed
requirements, outputs, manure production). This file may be used as input file for the pasture
models PASTOF and PASTOU, see Chapter 4.
3.1.1 Herd characteristics file
Input parameters that characterise the structure, target selling strategy and target growth of the
breeding herd to be modelled are specified in the so-called herd characteristics file. The parameters
of this file are explained here, using the file CRIAHRD.DAT for a breeding herd in the North Atlantic
Zone (NAZ) of Costa Rica as example. A complete listing of CRIAHRD.DAT is given in Appendix
1.1.1
The parameter MAINK specifies the manner in which the herd is supposedly fed, and entails
a correction factor for maintenance energy required to support grazing 6 (real). The following options
may be selected:
*MAINK = 1.0: for stable-fed
*MAINK = 1.1: for good pasture
*MAINK = 1.2: for sparse pasture
MAINK = 1.2
A one-letter code is given that serves to ‘recognise’ the herd type that was modelled in the output
files (character). E.g.:
HCODE = 'B'
6 In truth, MAINK is a management characteristic
21
The size of the herd is given in total number of animals (i.e. calves, steers and cows all count as
one animal), (integer):
HSIZE = 50
The herd size is combined in CRIA with the one-letter code HCODE to produce a unique
identification number for the herd under consideration. For this identification number, the actual
herd number is increased with 100 for ‘programming’ reasons. Thus, in this example, the herd
identification number will be B150 (HCODE followed by 100+HSIZE). The herd identification
number is written as first column in all output files.
The ‘breed’ - or type - of animals is specified by a size/weight indication for females and males
separately. This identification is used in the some of the calculation of feed requirements (NRC,
1989; p 74). The following options may be selected:
*ITYPEF = 1: female, large breed; max weight is 800 kg
*ITYPEF = 2: female, small breed; max weight is 600 kg
*ITYPEM = 3: male, large breed; max weight is 1000 kg
*ITYPEM = 4: male, small breed; max weight is 800 kg
ITYPEF = 1
ITYPEM = 3
For the calculation of maintenance energy requirements, three parameters relating to breed and
weight specifications should be given (NRC, 1996; p115-116):
A breed effect on maintenance energy requirements (NRC, 1996; p 115). E.g.
BE = 0.90; for Brahman and Nellore
Shrunk Relative Weight (NRC, 1996; p 116), e.g.:
*SRW = 435. ; kg for animals finishing at trace marbling (25.2% body fat)
*SRW = 462. ; kg for animals finishing at slight marbling (26.8% body fat)
*SRW = 478. ; kg for animals finishing at small marbling (28% body fat) and
replacement heifers
SRW = 435.
Final shrunk body weight at maturity (typically 0.96 times full final weight):
FSBW = 550.
The maximum age of the reproductive female animals is given in years: (year) (integer; bounded by
0 and 20):
IAMAX = 11
The live weight of animals at birth is given in kg (real):
LWB = 32.
The age of selling of calves (called ‘surplus’) is specified in months for male and female calves
separately (month) (real). The value of this parameter must lie between 0 (no negative ages!) and
12 times the maximum age IAMAX as specified above (calves can not be sold after their maximum
age). For male calves:
ASMS = 8.
For female calves:
ASFS = 8.
22
The target growth rates of the animals are specified per age class. These targets are set by the
user, and CRIA subsequently calculates the feed requirements necessary to accomplish these
targets. Of course, there is a relationship with the management of the herd. For instance, high
target growth rates should be accompanied by ‘good’ management as specified in the herd
management file (e.g. good care-taking, sufficient inoculations etc.), Paragraph 3.1.2. The target
growth rates for males are specified for age 0-1 years (LWGM0), age 1-2 years (LWGM1), age 2-4
years (LWGM2), and after 4 years of age (LWGM3). (kg/day) (real):
LWGM0 = 0.65
LWGM1 = 0.45
LWGM2 = 0.25
LWGM3 = 0.
The target growth rates for females are specified for age 0-1 years (LWGF0), age 1-2 years
(LWGF1), age 2-4 years (LWGF2), and after 4 years of age (LWGF3). (kg/day) (real):
LWGF0 = 0.52
LWGF1 = 0.36
LWGF2 = 0.135
LWGF3 = 0.
The mortality rate is specified as fraction for both males and females together, for age class 0-1
years (MRATE0), age class 1-2 years (MRATE1), and after age of 2 years (MRATE). (-) (real,
bounded by -0 and 0.99)
MRATE0 = 0.1
MRATE1 = 0.02
MRATE = 0.01
The abortion rate is specified for both males and female together (real, bounded by -0 and 0.99):
AR = 0.0
The first age at which reproductive female animals start calving, in months (month) (real; higher
than 12. and lower than 60. months):
AFC = 31.
The calving interval (from birth to birth) of reproductive females, in months (month) (real; higher
than 0):
CI = 14.
The duration of lactation is the period during and after pregnancy that the reproductive female gives
milk (month) (real; for reasons of calculation procedures given by NRC (1989), DLAC should be
smaller than the calving interval CI minus two months):
DLAC = 8.
The duration of the pregnancy in months (month) (real; should be smaller than the calving interval
CI):
DPREG = 9.
The daily amount of milk produced during lactation (kg/d) (real; bounded by 0. and 100.):
MILK = 3.5
23
A fraction of the daily milk production may be used for human consumption (selling, own
consumption), as for example in double purpose systems. For pure breeding systems, this value
should be set to 0. (-) (real; bounded by 0. and 1.):
FMLKH = 0.
Some characteristics of the milk:
Percentage milk fat (%) (real; bounded by 0. and 10.):
FAT = 4.5
Specific weight of milk (kg/l) (real; bounded by 1. and 1.1):
SWMILK = 1.03
Finally, a factor should be given that ‘scales’ the energy concentration of the diet fed according to
NRC (1989) assumptions, with a suggested range from 0.95 - 1.05. (real; bounded by 0.9-1.1). It is
suggested to leave this value at 1., unless strong evidence exists to change this value.
FEDNRC = 1.
3.1.2 Herd management file
Input parameters that characterise the management strategy of the herd are specified in a so-called
herd management file, and are used by CRIA to calculate costs and labour requirements. The
parameters of this file are explained here using the file CRIAMAN.DAT DAT for a breeding herd in
the North Atlantic Zone of Costa Rica as example. A complete listing of CRIAMAN.DAT is given in
Appendix 1.1.2. In the herd management file, reference is made to ‘items’ that are specified in socalled attribute files. Attribute files are explained in Chapter 6. A complete listing of all attribute files
is given in Appendix II.
HERD SIZE DEFINITION
For management and maintenance of a herd, necessary inputs are generally herd-size dependent.
Therefore, a generic method was developed in which management is specified for various herd size
classes (HRDCLAS) in the herd management file. The actual desired herd size (HSIZE) is inputted
by the user in the herd characteristics file (see above, Paragraph 3.1.1). The CRIA model reads this
actually desired herd size from the herd characteristics file, and retrieves the management and
maintenance data for the appropriate herd size class. The definition of the herd size classes in the
herd management file is as follows:
*HRDCLAS
Herd size class (number) (integer)
*HRDMIN
Minimum number of animals in the class (number) (INTEGER)
*HRDMAX
Maximum number of animals in the class (number) (INTEGER)
HRDCLAS
HRDMIN
HRDMAX
1
1
10
2
11
30
3
31
60
4
61
100
The CRIA model checks that the ranges of the herd size classes are ‘unique’ and do not overlap.
The user can change the values of HRDMIN and HRDMAX, and increase or decrease the number
of rows (minimum of one row, maximum of 10). However, whenever reference is made to herd
classes in the rest of the input file, these class references should be the same as given here (i.e.
24
the values of the parameters HRDCLAS, CRCLASS, MTCLASS, T1CLASS, T2CLASS, T3CLASS,
CHCLASS, CMCLASS and I2CLASS should all be the same).
MATERIALS USED
Next, for each defined herd size class, input materials should be given. There is a fixed input
section for a corral and for troughs, and one general section in which up to three types of inputs can
be defined. Each input item should be selected from the attribute file in which materials are
specified, i.e. the MATER.ATF file. When a user wants to input a material that is not (yet) present in
the MATER.ATF file, he/she can update this attribute file by supplying the required information (see
Chapter 6). If a name for a material is given that is not present in the MATER.ATF file, an error
message is obtained during execution of CRIA. In general, for each inputted material item, the
following information should be provided: the amount of labour used in its construction (if
appropriate), the amount of the materials used, and its depreciation time.
For corrals, the following inputs are required:
* CRDCLAS
Herd size class (number) (integer)
* CROLAB
Farm labour for corral construction (hour/corral) real)
* CRMAT
Name of corral material (name) (character),
*
Select from MATER.ATF attribute file.
* CRQUAN
Quantity of corrals (number) (real)
* CRDEP
Depreciation time of the corral (year) (real)
CRCLAS
CROLAB
CRMAT
1
0.
'corral1'
2
0.
'corral2r'
1.
30.
3
0.
'corral3r'
1.
30.
4
0.
'corral4r'
1.
30.
CRQUAN
CRDEP
1.
30.
Note that when no corral is to be used, the user can give ‘none’ in the column CRMAT. In this
example, CROLAB = 0 because in the costs of the corrals (in MATER.ATF), the labour for
construction is included.
For troughs, the following inputs are required:
* MTDCLAS
Herd size class (number) (integer)
* MTMAT
Name of trough (name) (character)
*
Select from MATER.ATF attribute file.
* MTQUAN
Quantity of troughs (number) (real)
* MTDEP
Depreciation time of trough (year) (real)
MTCLAS
MTMAT
MTQUAN
MTDEP
1
'trough'
1.
5.
2
'trough'
4.
5.
3
'trough'
5.
5.
4
'trough'
6.
5.
Note that when no troughs are to be used, the user can give ‘none’ in the column MTMAT.
For any other materials, up to three inputs can be supplied:
* T_CLAS
Herd size class (number) (integer)
* T_MAT
Name of used materials (name) (character)
*
Select from MATER.ATF attribute file.
* T_QUAN
Materials quantity, in same unit as in materials file! (name) (real)
* T_DEP
Depreciation time of used materials (years) (real).
*
Note: when T_DEP is 0, the tools are yearly acquired.
* Tool2 per herd size class
25
T1CLAS
T1MAT
T1QUAN
T1DEP
1
'stools'
10.
5.
2
'stools'
10.
5.
3
'stools'
10.
5.
4
'stools'
10.
5.
* Tool2 per herd size class
T2CLAS
T2MAT
T2QUAN
T2DEP
1
'ltools'
3.
3.
2
'ltools'
4.
3.
3
'ltools'
5.
3.
4
'ltools'
8.
3.
* Tool3 per herd size class
T3CLAS
T3MAT
T3QUAN
T3DEP
1
'none'
0.
0.
2
'none'
0.
0.
3
'none'
0.
0.
4
'none'
0.
0.
In this example, only ‘small tools’ and ‘large tools’ are used, and the option for input item number 3
is left unused by specifying ‘none’ under T3MAT.
OPERATIONS AND HEALTH CARE
Herd management entails the performance of various operations. There are ‘miscellaneous’
operations such as general inspection, and operations that are related to specific activities such as
assistance at calving, salt application or the inoculation of animals. These operations require time
and input materials that need to be specified by the user. Miscellaneous operations are such things
as general inspection, snakes chasing, general health care etc. The amount of time spent on these
miscellaneous operations should be provided. One input item can be given, to be selected from the
attribute file CATTLE.DAT (if necessary, this file may be updated to include the desired item). Note:
all inputs are on a yearly basis!
* CHCLAS
Herd size class (number) (integer)
* CHLAB
Own (farm) labour use (hours/year) (real)
* CHMAT
Health materials used (character).
*
Select from CATTLE.ATF attribute file.
* CHQUAN
Quantity of health materials used (unit)
CHCLAS
CHLAB
CHMAT
CHQUAN
1
180.
'emicina'
50.
2
240.
'emicina'
100.
3
300.
'emicina'
250.
4
360.
'emicina'
400.
Assistance at calving is independent of herd size and is expressed in labour hours per born animal:
* BRTLAB Own (farm) labour use for assistance at calving (hour/born
*
calve) (real)
BRTLAB = 3.
The application of (mineral) salt is specified by the type of salt applied, the amount applied per
animal unit per day and the amount of (yearly) labour hours needed to fill the troughs with salt. One
Animal unit is defined as an animal of 400 kg. The type of salt should be selected from the
26
FEED.ATF attribute file (if necessary, this file may be updated to include the desired type of salt).
The unit of the quantity of (mineral) salt should be the same as that in the FEED.ATF attribute file.
* MSNAME
Name of salt (name) (character). Select from FEED.ATF attribute file
* MSQUAN
Quantity of salt application (kg/day/AU) (real)
MSNAME
MSQUAN
'salt'
0.05
Note that in the example given here, only one type of salt given. The user may increase the number
of salts (lines) up to a maximum of five. When no salt is to be supplied, ‘none’ can be entered.
Labour use for salt application is entered as follows:
* CMCLAS
Herd size class (number) (integer)
* MSLAB
Labour use to supply all mineral salt (hour/year) (real)
CMCLAS
MSLAB
1
26.
2
30.
3
40.
4
50.
Born animals may be given one-time-only health care treatments such as specific inoculations. For
these treatments, the name and quantity of the supplied materials (inoculations) have to be selected
from the attribute file CATTLE.ATF. The unit of the quantity of inoculation (I1QUAN) should be the
same as that of the selected item in the CATTLE.ATF file. The amount of labour for these
treatments/inoculations should include possible round-up of the animal tot a corral or the time
needed to administer the treatment. All data are specified per animal:
* I1NAME
Name of (inoculation) material (name) (character)
*
Select from CATTLE.ATF attribute file.
* I1QUAN
Quantity (of inoculation) per application (unit) (real)
* I1LAB
Labour use per inoculation, including round-up to corral (hour/animal)
I1NAME
I1QUAN
I1LAB
'brucel'
1.
0.15
'dectomax'
6.
0.30
'bacterine'
5.
0.10
The example given here is three rows long; the user may increase/decrease the number of rows
(minimum of one, maximum of five). One row should always be present, but the user may give
‘none’ for the material used.
Beside one-time-only treatments/inoculations of animals, other treatments/inoculations may be
administered with a certain yearly frequency. For these treatments, the name and quantity of the
supplied materials (inoculations) have to be supplied (again selected from the attribute file
CATTLE.ATF), the amount of labour required for the administration of these
treatments/inoculations, and – separately! - the amount of yearly labour for round-up of the animals
tot a corral. The unit of the quantity of inoculation (I2QUAN) should be the same as that of the
selected item in the CATTLE.ATF file. The data on type and amount of treatment, and the labour
hours for administration are specified per animal or per animal unit:
* I2NAME
Name of inoculation material (name) (character)
*
Select from CATTLE.ATF attribute file.
* I2UNIT
Herd unit for application, either 'animal' (per animal) or
*
'aunit' (per animal unit)
* I2FREQ
Frequency of application (times per year per I2UNIT) (real)
* I2QUAN
Quantity of inoculation per application (unit) (real)
* I2LAB
Labour use for inoculation, without round-up time to corral
27
*
(hour/I2UNIT) (real)
I2NAME
I2UNIT
I2FREQ
I2QUAN
I2LAB
'ripercol'
'aunit'
2.
20.
0.1
'bacterine'
'animal'
2.
5.
0.1
'anthrax'
'animal'
2.
5.
0.1
'neguvon'
'aunit'
5.
0.005
0.07
The example given here is four rows long; the user may increase/decrease the number of rows
(minimum of one, maximum of 10). One row should always be present, but the user may give ‘none’
for the material used. The amount of labour required for round-up to the corral (for
treatment/inoculations) is specified for the whole herd: number of yearly round-ups and labour hours
per round-up:
* I2CLAS
Herd size class (number) (integer)
* I2RNO
Number of round-ups per year for inoculation (number) (real)
* I2RLAB
Round-up time to corral for inoculation (hour/round up)
*
(real)
I2CLAS
I2RNO
I2RLAB
1
6.
0.15
2
6.
0.30
3
6.
0.67
4
6.
1.00
3.1.3 Site file
The site file contains two parameters that are used by all PASTOR models: interest rate and the
number of work hours in a day. The interest rate is used in the calculations of annuity costs of
items/inputs that have a lifetime (renewal period) of more than one year.
* Interest rate for cost calculations (%/year) (real)
RINT = 7.
All labour specifications in the input files are given in hours. However, all PASTOR models compute
total labour requirements on a daily basis, Therefore, the number of hours in a work-day is specified
under DAYHR.
* Hours of labour in one day (real) (h/d)
DAYHR = 8.
3.2 GORDO model
Input and output file names for the GORDO model are specified in the file CONTROL.DAT the
same way as for the CRIA model, Paragraph 3.1. The only differences are the names of the herd
characteristics and the herd management data files:
FILEI1 = 'C:\PASTOR\FILE_IN\HERD\GORDHRD.DAT'
FILEI2 = 'C:\PASTOR\FILE_IN\HERD\GORDMAN.DAT'
28
3.2.1 Herd characteristics file
Input parameters that characterise the structure, target selling strategy and target growth of the
breeding herd to be modelled are specified in the so-called herd characteristics file. The parameters
of this file are explained here, using the file GORDHRD.DAT DAT for a fattening herd in the North
Atlantic Zone of Costa Rica as example. A complete listing of GORDHRD.DAT is given in Appendix
1.1.3.
The parameter MAINK specifies the manner in which the herd is supposedly fed, and entails
a correction factor for maintenance energy required to support grazing 7 (real). The following options
may be selected:
*MAINK = 1.0: for stable-fed
*MAINK = 1.1: for good pasture
*MAINK = 1.2: for sparse pasture
MAINK = 1.2
A one-letter code is given that serves to ‘recognise’ the herd type that was modelled in the output
files (character). E.g.:
HCODE = 'F'
The size of the herd is given in total number of animals (i.e. calves, steers and cows all count as
one animal), (integer):
HSIZE = 50
The herd size is combined in GORDO with the one-letter code HCODE to produce a unique
identification number for the herd under consideration. For this identification number, the actual
herd number is increased with 100 for ‘programming’ reasons. Thus, in this example, the herd
identification number will be F150 (HCODE followed by 100+HSIZE). The herd identification
number is written as first column in all output files.
The ‘breed’ - or type - of animals is specified by a size/weight indication for females and males
separately. This identification is used in the some of the calculation of feed requirements (NRC,
1989; p 74). The following options may be selected:
*ITYPEF = 1: female, large breed; max weight is 800 kg
*ITYPEF = 2: female, small breed; max weight is 600 kg
*ITYPEM = 3: male, large breed; max weight is 1000 kg
*ITYPEM = 4: male, small breed; max weight is 800 kg
ITYPEF = 1
ITYPEM = 3
For the calculation of maintenance energy requirements, three parameters relating to breed and
weight specifications should be given (NRC, 1996; p115-116):
A breed effect on maintenance energy requirements (NRC, 1996; p 115). E.g.
BE = 0.90; for Brahman and Nellore
Shrunk Relative Weight (NRC, 1996; p 116), e.g.:
*SRW = 435. ; kg for animals finishing at trace marbling (25.2% body fat)
*SRW = 462. ; kg for animals finishing at slight marbling (26.8% body fat)
7 In truth, MAINK is a management characteristic
29
*SRW = 478. ; kg for animals finishing at small marbling (28% body fat) and
replacement heifers
SRW = 435.
Final shrunk body weight at maturity (typically 0.96 times full final weight):
FSBW = 550.
The ratio of male to female animals in the herd should be supplied:
* Herd male/female animal ration:
RATIOMF = 1.5
The live weight of young animals that are bought is specified separately for males (WBUYM) and
females (WBUYF), (kg) (real).
* Live weight of animal at buying (kg) (real); for male calves
* (WBUYM) and female calves (WBUYF)
WBUYM = 190.
WBUYF = 160.
The live weight of the animals at selling is specified separately for males (WSELLM) and females
(WSELLF), (kg) (real). GORDO assumes that animals are kept at least one complete month in the
herd for fattening. Therefore, it computes the duration time of animals in the herd by dividing the
‘selling weight’ minus the ‘buying weight’ by the daily live weight gain (LWG, specified below). When
this value is larger than 31 days, the user gets an error message from the program.
* Live weight of animal at selling (kg) (real); for males (WSELLM)
* and for females (WSELLF)
WSELLM = 450.
WSELLF = 400.
The target growth rates of the animals are specified for males (LWGM) and females (LWGF)
separately (kg/day) (real). These target growths are set by the user, and GORDO subsequently
calculates the feed requirements necessary to accomplish these targets. Of course, there is a
relationship with the management of the herd. For instance, high target growth rates should be
accompanied by ‘good’ management as specified in the herd management file (e.g. good caretaking, sufficient inoculations etc.), Paragraph 3.2.2.
* Live weight gain of animals (kg/day) (real); for males (LWGM)
* and for females (LWGF)
LWGM = 0.5
LWGF = 0.4
The mortality rate is specified as fraction for both males and females together, (-) (real). Bounded
by -0 and 0.99:
* Mortality rate (real). Bounded by -0 and 0.99.
MRATE = 0.01
Finally, a factor should be given that ‘scales’ the energy concentration of the diet fed according to
NRC (1989) assumptions, with a suggested range from 0.95 - 1.05. (real; bounded by 0.9-1.1). It is
suggested to put this value at 1., unless strong evidence exists to change this value.
FEDNRC = 1.
30
3.2.2 Herd management and site file
The management data file for GORDO is very similar to that for CRIA in terms of structure and data
input; see Paragraph 3.1.2. A complete listing of the data file GORDMAN.DAT is given in Appendix
1.1.4. There are only two differences with the management file for CRIA herds:
1. There is no specification of the labour use for assistance at calving (BRTLAB), since no calves
are born in a fattening herd.
2. The inoculations given once to born animals in the CRIA model (I1NAME, I1QUAN, I1LAB) are
inoculations given once for bought animals in the GORDO model. The inoculations that are
regularly given (I2NAME, I2UNIT, I2FREQ, I2QUAN, I2LAB) are supplied with an indication of
frequency per year (I2FREQ). GORDO automatically computes the correct number of
inoculations applied when the duration time of animals in the herd is shorter than one year.
The information needed for the GORDO model in the site file is exactly the same as that for the
CRIA model; see Paragraph 3.1.3.
3.3 Special case: reruns
The models CRIA and GORDO generate technical coefficients for alternative herds, i.e. Animal
Production Systems (APSTs), as specified by the herd characteristics and herd management input
files given in the CONTROL.DAT files. However, it could be interesting to generate various breeding
and/or fattening APSTs. The rerun option of PASTOR allows that CRIA and GORDO are
automatically executed several times by reading and using subsequent input data files. The
following example explains the procedure for CRIA; the same applies to GORDO. A RERUNS.DAT
file should be created and put in the CRIA or GORDO sub-directory. This RERUNS.DAT file should
contain the names of alternative herd characteristics and/or herd management input files that
should be used. This is done by repeating the name and path of the FILEI1 parameter in the
CONTROL.DAT file, but using different data file names. For example, the following RERUNS.DAT
file causes CRIA first to generate technical coefficients for an APST as specified by input files as in
CONTROL.DAT, and than subsequently for an APST as specified by the herd characteristics file
CALTHRD.DAT:
FILEI1 = 'C:\PASTOR\FILE_IN\HERD\CALTHRD.DAT'
The file CALTHRD could, for instance, be a herd with a different selling strategy, or a herd with a
different target growth rate from the herd as specified in CRIAHRD.DAT.
Note: remember that each herd characteristics file should have a unique one-letter code to
recognise the herd type (HCODE) in the generated output files.
When no reruns are wished, the RERUNS.DAT file should be removed from the sub-directory, or an
asterix may be put in front of each line in the file.
31
4 Generating Pasture Production Systems (PASTs)
The models to generate pasture production systems (PASTs) are run by giving the *.EXE command
in the appropriate subdirectory, i.e. PASTOF.EXE for fertilised pastures in the
PASTOR\PASF_MOD sub-directory, or PASTOU.EXE for unfertilised pastures in the
PASTOR\PASU_MOD sub-directory. In the following paragraphs, the control over executing the
PASTOF and PASTOU models is explained in detail.
4.1 PASTOF model
In CONTROL.DAT (in the sub-directory MOD_PASF), the required model input, attribute and output
files of PASTOF are specified:
*************************** CONTROL.DAT ***********************
* Control file for PASTOF model
*
* PASTOR 2.0
*
***************************************************************
* RUNMOD Select mode of model running: PASTOR or CENTURY
RUNMOD = 'PASTOR'
* PASMAN select type of pasture use: SILAGE for silage (pasture
* may produce more biomass than animals can eat, surplus is removed),
* or GRAZING for truly grazed pastures.
PASMAN = 'GRAZING'
***************************************************************
* INPUT FILES
***************************************************************
* FILEI0
Input file with site data
* FILEI1
Input file with grass data
* FILEI2
Input file with soil data
* FILEI3
Input file with herd data
* FILEI4-8
Attribute input files
FILEI0 = 'C:\PASTOR\FILE_IN\SITE.DAT'
FILEI1 = 'C:\PASTOR\FILE_IN\PASTO\ESTREL.DAT'
FILEI2 = 'C:\PASTOR\FILE_IN\SOIL.DAT'
FILEI3 = 'C:\PASTOR\FILE_IN\CAT_CHAR.DAT'
FILEI4 = 'C:\PASTOR\FILE_ATR\MATER.ATF'
FILEI5 = 'C:\PASTOR\FILE_ATR\BIOCID.ATF'
FILEI6 = 'C:\PASTOR\FILE_ATR\EQUIP.ATF'
FILEI7 = 'C:\PASTOR\FILE_ATR\FERT.ATF'
FILEI8 = 'C:\PASTOR\FILE_ATR\TRACTION.ATF'
***************************************************************
32
* PASTOR Output files
***************************************************************
* FILEO1
Monthly yield data
* FILEO2
Yearly yield data
* FILEO3
'Extra' data (not directly for LP model)
* FILEO4
Yearly sustainability indicators
* FILEO5
Yearly labour use plus costs data
* FILEO6
Monthly labour use data
* FILEO8
Combination definition
FILEO1 = 'C:\PASTOR\FILE_OUT\PFERPM.PRN'
FILEO2 = 'C:\PASTOR\FILE_OUT\PFERPY.PRN'
FILEO3 = 'C:\PASTOR\FILE_OUT\PFERX.PRN'
FILEO4 = 'C:\PASTOR\FILE_OUT\PFERS.PRN'
FILEO5 = 'C:\PASTOR\FILE_OUT\PFERLC.PRN'
FILEO6 = 'C:\PASTOR\FILE_OUT\PFERLM.PRN'
FILEO8 = 'C:\PASTOR\FILE_OUT\PFERCOM.PRN'
First, it should be specified that PASTOF should produce technical coefficient outputs, always set:
RUNMOD= ‘PASTOR’8
Next, it should be specified whether computations should be performed for a grazing system only
(PASMAN=’GRAZING’), or for a system where the pasture is grazed and mown
(PASMAN=’SILAGE’). See Paragraph 1.2.1 for further explanation.
The model data files needed are specified at the variables FILEI0-3. Note that, beside the file name,
the complete path of the sub-directory where the files are stored is given. Users may change the
names of the input files when they have created their own input files. FILEI0 contains sitecharacteristics; FILEI1 specifies the name of the file that contains characteristics and management
of the pasture to be modelled; FILEI2 contains soil characteristics; and FILEI3 contains data on
(a.o.) manure produced and feed requirements of the stocked herd on the pasture. The site file
contains so-called ‘site’ data, of which some are also used by the other models of PASTOR. In the
following paragraphs, the model data files are explained in detail.
Attribute files (FILEI4-8) are explained in Chapter 6. The names of the attribute files should not be
changed by the user.
The names of the output files are given under the variables FILEO1-8. These names are the same
as given in Table 2.3.1, but may be changed by the user.
4.1.1 Pasture data file
Input parameters that characterise species, production levels and management of the pasture to be
modelled are specified in the pasture file. The parameters of this file are explained here, using the
8 If RUNMOD=’CENTURY’, PASTOF produces output for Century and DNDC simulation model. Not further explained. Also,
some more FILEO files should then be specified, which is not shown here.
33
file ESTREL.DAT for fertilised Estrella (Cynodon nlemfuensis) in the North Atlantic Zone (NAZ) of
Costa Rica as example. A complete listing of ESTREL.DAT is given in Appendix 1.2.1
PRODUCTION CHARACTERISTICS
First, the name and a one-letter code for the pasture type is given. The one-letter code will appear
in the output files in the complete code that characterises the pasture being modelled (see below).
Note: each pasture file should have a unique one-letter code (e.g. ‘E’ for Estrella).
* GNAME : Grass name (character)
* GCODE : Grass code (one letter only!) (character)
* -------------------------------------------------GNAME = 'Estrella'
GCODE = 'E'
Next, two pasture production levels need to be supplied: the ‘highest possible’, called ‘attainable’,
and the ‘worst possible’, called ‘minimum’. These two levels are the maximum and minimum
production levels between which target production of the pasture can be realised. Attainable
production is defined here as the highest (total above-ground) production with the best quality in
terms of energy, crude protein and phosphorus content, that can be obtained on the best soil type
in the area under the prevailing climatic conditions, with optimum supply of nutrients and with
optimum pest, disease and weed control (Bouman et al., 1996). The only growth-limiting factors are
climatic, i.e. radiation, temperature and rainfall, and the physical soil properties of the best soil
available. Attainable production values can be derived from well-calibrated crop growth simulation
models, well-controlled field experiments, expert knowledge or literature (Van Ittersum & Rabbinge,
1997; Bouman et al., 1996). Differences among months can result from seasonal variation in
weather (e.g. cold spells, droughts) and/or physiological development of the pasture (e.g. flowering
period). The minimum pasture production is assumed to take place on poor soils (completely
exhausted; hardly any nutrient stock available) with only natural input of nutrients, such as N
deposition in rain and N fixation by micro-organisms, and P and K from weathering. The minimum
production is also the production level, with corresponding N, P and K content, below which the
pasture can no longer survive.
The attainable production characteristics of the pasture under consideration have to be supplied per
month. To characterise the minimum production, only the nutrient and energy content have to
supplied as yearly value; PASTOF calculates the corresponding biomass level.
* Pasture data at level of attainable production (PER MONTH):
* MONTH: Name of month (character)
* DMP:
(above-ground total) Dry matter attainable production
*
on best soils (kg/month) (real)
* CP:
Crude Protein content (%)
* ME:
Metabolizable energy content (Mcal/kg) (real)
* P:
Phosphorus content (%) (real)
* K:
Potassium content (%) (real)
(real)
* -------------------------------------------------MONTH
DMP
CP
ME
P
K
'JAN'
1928.
11.0
2.3
0.35
3.7
! Literature, expert knowledge
'FEB'
1928.
11.0
2.3
0.35
3.7
! Total PP: 28 t/ha
'MAR'
1928.
11.0
2.3
0.35
3.7
'APR'
2468.
12.0
2.5
0.30
3.5
34
'MAY'
2468.
12.0
2.5
0.30
3.5
'JUN'
2468.
12.0
2.5
0.30
3.5
'JUL'
2468.
12.0
2.5
0.30
3.5
'AUG'
2468.
12.0
2.5
0.30
3.5
'SEP'
2468.
12.0
2.5
0.30
3.5
'OCT'
2468.
12.0
2.5
0.30
3.5
'NOV'
2468.
12.0
2.5
0.30
3.5
'DEC'
2468.
12.0
2.5
0.30
3.5
There is no distinction among months for the minimum production characteristics:
* Minimum nutrient and energy concentrations when no external (manure,
* fertiliser) nutrients are supplied. (minimum production level).
* CPMIN: Minimum Crude Protein content (%) (real)
* MEMIN: Minimum Metabolizable energy content (Mcal/kg) (real)
* PMIN:
Minimum Phosphorus content (%) (real)
* KMIN:
Minimum Potassium content (%) (real)
*-----------------------------------------------------------------* From variety of literature and expert knowledge
CPMIN = 6.
MEMIN = 1.5
PMIN
= 0.12
KMIN
= 1.4
EFFECT OF SOIL TYPE AND STOCKING RATE
The attainable production level applies to the best possible soil. In an area under study, there may
exist a variety of soils characterised by physical and chemical properties. The influence of soil type
on the attainable production level is expressed by two reduction factors, RDMP and RDMUSE.
RDMP quantifies the reduction in attainable pasture production due to soil limitations such as
acidity, poor drainage or low water holding capacity. Note that, on this level, it is still assumed that
nutrients are in ample supply! RDMP values need to be supplied for each soil type in the area under
study for which PASTs have to be generated. Soil types are indicated by a three letter code, in our
example SFW (Soil Fertile Well drained), SIW (Soil Infertile Well drained) and SFP (Soil Fertile
Poorly drained), Bouman et al. (1998). The soil name supplied here should correspond to the list of
soil names given in the soil data file (SOIL.DAT; see Paragraph 4.1.2), and to the list of soil names
given in the site data file (SITE.DAT; see Paragraph 4.1.4), because PASTOF calculates soil
nutrient balances based on the soil properties supplied in these files. In the example below, it is
specified that there is no reduction in attainable yield on SFW soils, since these soils are the best in
the NAZ with no limitations to pasture growth. SIW are acid soils, and attainable yields are 80% of
those on the best soils. SFP have excess water problems, and attainable yields are only 40% of
those on the best soils. RDMUSE quantifies the effect of soil type on the potential use fraction of the
total above-ground biomass as function of stocking rate. Not all above-ground production can be
eaten by grazing animals because i) parts such as stubble are ‘unreachable’ and should be left for
regrowth, ii) parts are trampled under the hooves of the animals, and iii) parts are (temporarily)
unavailable because they are covered by manure or urine patches (Deenen, 1994; Van der Ven,
1992). The potential fraction of total above-ground biomass ‘on offer’ for consumption is called
DMUSE, and depends on the amount of animals per surface unit (stocking rate). The factor DMUSE
is - as standard - specified for the best soil type available in the area. The reduction factor RDMUSE
adapts DMUSE to the conditions of the actual soil types to be studied. In our example, there is no
35
extra reduction in dry matter use on the soils SFW and SIW. The soil type SFP is poorly drained,
however, and trampling on this soil causes an 80% reduction in potential dry matter use as
compared to the potential dry matter use on the best soil.
* Yield reduction factors
* SOILP:
Soil name (character)
* RDMP:
Reduction fraction of attainable production (DMP as above)
*
due to soil limitations (-) (real)
* RDMUSE: Reduction fraction of potential dry matter use (DMUSE as below) due to
*
soil limitations. (-) (real)
* ---------------------------------------------------------------SOILP
RDMP
RDMUSE
'SFW'
1.0
1.0
'SIW'
0.7
1.0
'SFP'
0.4
0.8
Note: in this example, three soil types are supplied. This list can be shortened (with a minimum of
one soil type) or extended (up to a maximum of 10). The soil names will appear in the complete
code that characterises the pasture(s) being modelled (see below).
The factor DMUSE specifies the fraction of the total-above ground matter potentially on offer for
consumption as function of stocking rate, on the best soil type available in the area. Information on
this relationship can be derived from experiments, expert knowledge or literature. The user is
completely free to fill-in this table: the value of the stocking rates provided and the number of
stocking rates can be adapted according to local conditions and wishes of the user (a minimum of
one relationship should be provided; the maximum is 50). In our example, stocking rate varies from
one to three.
***********************************************************************
* SRATE: Stocking rate (animal units per ha) (real)
* DMUSE: Potential fraction dry matter on offer (fraction of total above* ground biomass), as function of stocking rate (-) (real)
* ---------------------------------------------------------------SRATE
1.
DMUSE ! Expert knowledge
0.55
1.5
0.525
2.
0.50
2.5
0.475
3.
0.45
The stocking rates will appear (preceded by the letter ‘R’) in the complete code that characterises
the pasture(s) being modelled (see below).
TECHNOLOGY: FERTILIZER AND WEEDING
At this moment, PASTOF has all the necessary information to calculate maximum attainable
production levels (quantity and quality) for all combinations of given soil types and stocking rates.
Based on the soil properties provided in the soil data file (SOIL.DAT; see Paragraph 4.1.2),
PASTOF calculates the soil nutrient balance for all combinations of soil types and stocking rates.
The amount of nutrients in manure and urine that is inputted into the system by the herd at each
stocking rate is also taken into account. Characteristics of the manure are read from a file as
36
specified in CONTROL.DAT, in our example the file CAT_CHAR.DAT (see Paragraph 4.1.3).
PASTOF next calculates the amount of extra (fertiliser) N, P and K nutrients that are required to
obtain the attainable production levels for all combinations of soil types and stocking rates, under a
user-specified soil nutrient balance. The maximum allowable soil nutrient mining (negative soil
nutrient balance) is read from the site file, in our example SITE.DAT (Paragraph 4.1.4). Now, the
user can specify options for management of the pasture related to i) actual amounts of fertiliser
application, and ii) manner of weeding. The target amount of fertiliser applied, FGIFT, is expressed
as fraction of the amount needed to realise the maximum attainable production for the specified
soil-stocking rate combinations. Thus, the highest possible FGIFT is 1.0 (leading to maximum
attainable production), and the lowest is 0.0 (leading to the lowest production level). The manner in
which fertiliser is applied is specified under FERTAP. PASTOR is highly generic in the sense that
the user can ‘build’ his own options for the manner in which fertiliser is applied at the end of the file.
From these own-build options, a selection can be made and used as input under FERTAP. The
same applies to the manner of weeding. At the end of the file, a number of alternatives can be
‘build’ from which a selection can be inputted under WEED. All three management input parameters
(FGIFT, FERTAP and WEED) are preceded by a column that encodes the technology level as a
two-digit number. This two-digit number will appear (preceded by the one-letter code that indicates
the type of pasture, see above) in the complete code that characterises the pasture(s) being
modelled (see below).
* PLEVEL: Code for technology level (2 numbers only!) (integer)
* FGIFT:
Fraction of fertiliser N gift to realise maximum
*
attainable production (-) (real)
* FERTAP: Manner of fertiliser application (name) (real)
*
Select from options given below under 4. OPERATIONS)
* WEED:
Manner of weeding (name) (character)
*
Select from options given below under 4. OPERATIONS)
* ---------------------------------------------------------------PLEVEL
FGIFT
FERTAP
WEED
11
0.00
'manual'
'mixed'
20
0.20
'manual'
'mixed'
40
0.40
'manual'
'mixed'
60
0.60
'manual'
'mixed'
80
0.80
'manual'
'mixed'
99
1.00
'manual'
'mixed'
! User defined
In our example, there are six technology levels that will be modelled by PASTOF. However, this list
can be shortened or expanded to include as many combinations of FGIFT, FERTAP and WEED
desired (up to a maximum of 50). PASTOF will calculate technical coefficients for all combinations
of soil types, stocking rates and technology levels so far specified (in our example three soil types,
five stocking rates and six technology levels, leading to 90 PASTs).
ESTABLISHMENT AND MAINTENANCE OPERATIONS
The pasture specified so far has to be established by sowing or planting, and maintained and
managed by operations. First, pasture establishment operations are specified by listing labour and
material inputs required for two specific actions: i) application of herbicides to kill existing crops or
natural vegetation, and ii) the application of a basic fertiliser gift. For herbicide application, the
names of the herbicides, the amount of herbicides, the amount of labour used, the equipment and
the type of traction used need to be specified. The herbicides used have to be selected from the
attribute file BIOCID.ATF, the equipments from the attribute file EQUIP.ATF file, and the tractions
37
from the attribute file EQUIP.ATF. The units of the quantities of the herbicides, equipments and
tractions have to be the same as those in these *.ATF files. When a desired
herbicide/equipment/traction is not present in these files, they can be added by the user and then
selected here. Several herbicides can be applied by listing these products in different rows. For the
application of each herbicide, the amount of labour used is specified under EWLAB. Alternatively, a
separate line can be used to enter all labour used for the application of all herbicides, and then a ‘0’
can be entered for each herbicide separately. For instance, in the example below, the first line is
used to enter all labour, equipment and traction used for all herbicides together, and the herbicides
are listed separately on the following lines. The number of entries (lines) is flexible and can be
shortened or expanded by the user (minimum is one; maximum is five).
Separate lines are used to enter the fertilisers applied at establishment. This follows the same
scheme as for the herbicides, with the difference that the fertilisers are selected from the FERT.DAT
attribute file. Since all these data are used by PASTOF to calculate costs and total labour use for
the pasture, the duration of the pasture has to be supplied at EDEP (needed to calculate annuities
of costs).
* EDEP
Depreciation time of pasture (year) (real).
* EWLAB/EFLAB
Farm labour use for weeding/fertilising (hours) (real)
* EWNAME/EFNAME Herbicide/fertiliser name (name) (character);
*
to select from BIOCID.ATF and FERT attribute files.
* EWQUAN/EFQUAN Herbicide/fertiliser quantity (unit) (real)
* EWEQ/EFEQ
Herbicide/fertiliser equipment name (name) (character);
*
to select from EQUIP.ATF attribute file.
* EWQUSE/EFQUSE Herbicide/fertiliser equipment use (hours) (real)
* EWTRAC/EFTRAC Herbicide/fertiliser traction for equipment (name) (character)
*
to select from TRACTION.ATF attribute file.
* Input data: Andre Nieuwenhuyse, based on farmer inquiries in the AZ (96-97)
EDEP = 10.
EWLAB
EWNAME
24.0
'None'
EWQUAN
0.0
'Tordon-101'
1.
'ksspray'
0.
'none'
0.0
'24D'
3.
'ksspray'
0.
'none'
0.0
'Round-up'
4.
'ksspray'
0.
'none'
EFLAB
EFNAME
EFQUAN
EFEQ
EFQUSE
EFTRAC
4.0
'P'
4.
'none'
0.
'none'
0.
EWEQ
'ksspray'
EWQUSE
24.
EWTRAC
'none'
Next, the input of labour and other materials for the establishment and maintenance of the pasture
have to be supplied. Under OPER, a brief description of the operation can be supplied. The list then
follows the same principle as above: materials have to be selected from the MATER.ATF attribute
file, equipments from the EQUIP.ATF file, and tractions from the EQUIP.ATF file. The units of the
quantities of the materials, equipments and tractions have to be the same as those in the *.ATF
files. When a desired material/equipment/traction is not present in these files, they can be added by
the user and then selected here. The duration/lifetime can vary per material and therefore the
depreciation time DEPRET has to be specified per material input. When materials are inputted each
year, DEPRET should be set to ‘0’. In the example file below, there are lines that specify the input of
the Estrella grass stolons (line 1), lines for the establishment of fences (lines 2-5), lines for the
maintenance of the fences (line 6) and for the use of five small tools in general (e.g. a saw, a
machete, a hammer, a bucket, a knife) (line 7). The grass stolons are inputted every 10 years,
which is the duration of the pasture; the fences (and the used fence materials) have a lifetime of six
38
years and need to be replaced; the fences are maintained every year (DEPRET = 0), and the small
tools have a lifetime of five years. The user can decrease or increase the list according to own
specifications (minimum is one; maximum is 25).
* OPER
Name of operation (name) (character)
* OWNLAB
Own (farm) labour use (hours) (real)
* MATER
Name of used materials (name) (character)
*
to select from MATER.ATF attribute file.
* MQUANT
Materials quantity, in same unit as in materials file! (name)(real)
* DEPRET
Depreciation time of used materials (years) (real).
*
Note: when DEPRET is 0, the operation/inputs are yearly recurrent.
* EQUIP
Name of equipment used (name) (character),
*
to select from EQUIP.ATF attribute file.
* EQUSE
Equipment use time (real) (hour)
* TRAC
Traction used to 'pull' equipment (name) (character)
*
to select from TRACTION.ATF attribute file.
* Input data: Andre Nieuwenhuyse, based on farmer inquiries in the AZ (96-97)
OPER
OWNLAB
MATER
MQUANT
DEPRET
EQUIP
EQUSE
'Grass sowing'
30.
'gstolE'
1.5
10.
'none'
0.
'none'
'Labour fence estab.' 12.
'none'
0.
6.
'none'
0.
'none'
'Fences barbed wire'
0.
'bwire-Cai'
350.
6.
'none'
0.
'none'
'Fences dead'
0.
'dposts-sl'
33.
6.
'none'
0.
'none'
'Fences nails'
0.
'cramp-l'
0.5
6.
'none'
0.
'none'
'Fence maintenance'
2.
'none'
0.
0.
'none'
0.
'none'
'stools'
5.
5.
'none'
0.
'none'
'Various small tools' 0.
TRAC
WEEDING AND FERTILISING MANNER SPECIFICATION
The last section of the data file is meant to ‘build’ own specifications of i) recurrent weeding and ii)
manner of fertiliser application. The amount of time and materials (herbicides) required for weeding
depends on the cover - and thus production level - of the pasture. A high production with a good soil
cover suppresses weeds, and therefore the amount of time and inputs spent on weeding can be
relative low. On the contrary, a low producing pasture with a poor soil cover encourages weed
infestation and more time and inputs need to be spent in controlling weeds. Since the actual
production level varies for the various combinations of soil type, stocking rate and technology level
as specified earlier, a whole range of weeding inputs would need to be specified. This problem is
solved in PASTOF by specifying two input levels of weeding inputs: one for the maximum attainable
production level and one for the minimum (extensive) production level. PASTOF calculates for each
realised actual production level the amount of labour and herbicides needed by interpolation
between the maximum and minimum amounts. The labour and herbicide inputs for the attainable
level are recognised by the suffix ‘PP’, and those for the extensive level by the suffix ‘EX’. For each
manner of weeding that the user wants to ‘build’, the following inputs need to be specified for both
levels: labour use, type and amount of herbicides applied, and equipment and traction used in the
application of the herbicides. All inputs are yearly totals (per hectare). Because more than one type
of herbicide may be applied, there is provision to enter data for up to three herbicide types. The
labour use, and the use of equipment and traction on each line are the totals of all labour,
equipment and traction used in the whole year (summed over all manual weeding and the
application of all the herbicides). On each line, manual weeding - in the form of labour hours
invested - and chemical weeding may be combined by summing all labour used under OL. The
user is free to ‘build’ any number of alternative weed control manners, as long as the manners are
39
quantified at both the PP and the EX technology level (a minimum of one, up to a maximum of five).
The name of the manner should be entered under WEEDPP/WEEDEX. This name can then be
used earlier in the file to select the manner of weeding that is to be modelled (under WEED; see
above). In the example below, three weeding manners have been build; a strict manual weeding, a
strict chemical weeding, and a mixed manner with both manual and chemical weeding. Quantitative
data on labour hours and chemical inputs have to be obtained from field enquiries and from expert
knowledge.
* Input data: Andre Nieuwenhuyse, based on farmer inquiries in the AZ (96-97)
* Note that all inputs are totals over the year.
* All inputs/activities are specified for the level of potential production
* (extension PP) and for the level of zero external inputs (extension EX)
* WEED
Name of weeding manner (name) (character)
* OL
(total) Own (farm) labour use (hour/year) (real)
* C1N
Name of first herbicide input (name) (character)
*
to select from BIOCIDE.ATF attribute file.
* C1Q
Quantity of first herbicide input (amount/year) (real)
*
Units of quantity should match those in biocide file!
* C2N
Name of second herbicide input (name) (character)
*
to select from BIOCIDE.ATF attribute file.
* C2Q
Quantity of second herbicide input (amount/year) (real)
*
Units of quantity should match those in biocide file!
* C3N
Name of third herbicide input (name) (character)
*
to select from BIOCIDE.ATF attribute file.
* C3Q
Quantity of third herbicide input (amount/year) (real)
*
Units of quantity should match those in biocide file!
* WEQ
Equipment used for weeding (name) (character)
*
to select from EQUIPMENT.ATF attribute file.
* WEQU
Use time of equipment (hours/year) (real)
* WTRA
Traction used to 'pull' equipment (name) (character)
*
to select from TRACTION.ATF attribute file.
WEEDPP
OLPP
C1NPP
C1QPP
C2NPP
C2QPP
C3NPP
C3QPP
WEQPP
'manual'
7.0
'None'
0.
'None'
0.
'None'
0.
'none'
WEQUPP
0.
'none'
'chemic'
3.5
'24D'
1.5
'Tordon-101'
0.5
'Combo'
0.035
'ksspray'
3.5
'none'
'mixed'
5.0
'24D'
1.5
'Tordon-101'
0.5
'None'
0.
'ksspray'
2.0
'none'
WEEDEX
OLEX
C1NEX
C1QEX
C2NEX
C2QEX
C3NEX
C3QEX
WEQEX
'manual'
20.
'None'
0.
'None'
0.
'None'
0.
'none'
0.
'none'
'chemic'
11.5
'24D'
4.5
'Tordon-101'
1.5
'Combo'
0.105
'ksspray'
10.5
'none'
'mixed'
14.
'24D'
3.0
'Tordon-101'
1.0
'Combo'
0.035
'ksspray'
6.
'none'
WEQUEX
WTRAPP
WTRAEX
In the same way as ‘building’ weeding manners, manners of fertiliser application can be ‘build’. A
notable difference, however, is that here the labour required for fertiliser application is calculated by
PASTOF and is not explicitized by the user. This is because the amount of fertiliser to be applied is
calculated by PASTOF on the basis of the nutrient balance and the relative fraction inputted by the
user under FGIFT (see above). For this calculation, two parameters need to be supplied: FSSIZE
that quantifies the gross amount of fertiliser that can be applied on one hectare pasture in
application time FSADUR. For instance in our example, 150 kg of fertiliser can be manually applied
on one hectare in three hours. The parameter FOLAB can be used to specify whether own labour is
used in the fertiliser application, or not (e.g. in the case of contract labour using tractors). No type of
40
fertiliser has to be indicated since PASTOF automatically takes average properties for N, P and K
fertiliser from the FERT.ATF attribute file. The name of the fertiliser application manner should be
entered under FERTIL. This name can then be used earlier in the file to select the manner of
fertiliser application that is to be modelled (under FERTAP; see above).
* FERTIL Manner of fertiliser application (name) (character)
* FOLAB
Fertiliser own (farm) labour (whether own labour is used in
*
application)
*
options: 'yes' or 'no' (e.g. when contract labour is used)
* FEQUIP Fertiliser equipment (name) (character)
*
to select from EQUIP.ATF attribute file.
* FSSIZE Fertiliser amount that can be applied in FSADUR time (kg)
*
(real)
* FSADUR Fertiliser application duration for FSSIZE (hour) (real)
* FTRAC
Traction used to 'pull' equipment (name) (character)
*
to select from TRACTION.ATF attribute file.
FERTIL
FOLAB
FEQUIP
FSSIZE
FSADUR
FTRAC
'manual'
'yes'
'none'
150.
3.
'none'
In this example, only one fertiliser application manner is specified. However, the list can be
extended to include more manners (a minimum of one, up to a maximum of five).
CODING OF GENERATED PASTS
PASTOF produces output files that contain technical coefficients of all modelled alternative pasture
production systems (PAST). Many PASTs may be generated in one run of PASTOF for a single
pasture type because the model is repeatedly executed with different combinations of soil type,
stocking rate and technology level as specified in the pasture data file. Each PAST is recognised by
a code, written in the first column of each output file. The explanation of this code is given for an
example generated by PASTOF for one of the alternatives specified in the example pasture data file
ESTREL.DAT
SFW.E20.R1.JAN
where:
 SFW is the soil type (SOILP)
 E20 is a combination of the one-letter code for the pasture name (GCODE) with the technology
level (PLEVEL)
 R1 indicates the stocking rate (SRATE)
 JAN indicates the month for which the particular technical coefficient in the file is valid (MONTH;
not used in all files)
4.1.2 Soil data file
The soil file contains characteristics of various soil types which are used by PASTOF in the
calculation of the soil nutrient balances. Soil types used in the pasture data file should also be
present in the soil data file. The example file presented here, SOIL.DAT, contains characteristics for
three soil types in the Atlantic Zone of Costa Rica (Bouman et al., 1998; Nieuwenhuyse, 1996):
41
SFW (Soil Fertile Well drained), SIW (Soil Infertile Well drained) and SFP (Soil Fertile Poorly
drained).
First, some non-soil specific amounts of natural input of nutrients to all soil types are given:
* Atmospheric nitrogen deposition (kg/ha/y) (real)
AND = 1.7
* Atmospheric phosphorus deposition (kg/ha/y) (real)
APD = 0.2
* Atmospheric potassium deposition (kg/ha/y) (real)
AKD = 5.4
* Annual input of phosphorus by weathering (kg/ha/y) (real)
WP = 0.
* Annual input of potassium by weathering (kg/ha/y) (real)
WK = 0.
Next, soil properties are given that characterise loss fractions of fertiliser and manure (urine and
faeces separately) nutrients. These loss fractions are specified for each type of loss (such as
leaching or volatilisation) and for each nutrient N, P and K separately. For urine, a distinction is
made for leaching losses through macropores and through the soil matrix (‘normal’ type of leaching
loss). For phosphorus, a fixation fraction is to be supplied as well. When inputting the loss fractions,
it should be checked that the sum of some loss fractions cannot be greater than 1:
ULLMP + ULL + UVL + UDL <= 1
FLL + FVL + FDL <= 1
FELLN + FEVLN + FEDLN <= 1
Of course, single loss fractions are physically bounded by 0. and 1.
The first column of the table gives the three-letter code for the soils. Users can shorten, extend or
edit the list of soil names and properties presented here (with a minimum of one, and a maximum of
10).
* SOILS = soil type (name) (character)
* NFIX
= Nitrogen fixation by micro-organisms (kg/ha/y) (real)
* ULLMP = Urinary leaching loss fraction through macropores (-) (real)
* ULL
= Urinary leaching loss fraction (-) (real)
* UVL
= Urinary volatalization loss fraction (-) (real)
* UDL
= Urinary (de)nitrification loss fraction (-) (real)
*
i.e.: NO, N2O and N2 loss
* FLL
= Faecal leaching loss fraction (-) (real)
* FVL
= Faecal volatalization loss fraction (-) (real)
* FDL
= Faecal denitrification loss fraction (-) (real)
* FELLN = Fertiliser leaching loss fraction nitrogen (-) (real)
* FELLK = Fertiliser leaching loss fraction potassium (-) (real)
* FEVLN = Fertiliser volatalization loss fraction nitrogen (-) (real)
* FEDLN = Fertiliser denitrification loss fraction nitrogen (-) (real)
* FPXL
*
= Phosphorus fixation fraction, for faeces, urine and
fertiliser (-) (real)
42
SOILS
NFIX
ULLMP
ULL
UVL
UDL
FLL
FVL
FDL
'SFW'
6.0
0.30
0.20
0.15
0.05
0.60
0.05
0.05
'SIW'
3.0
0.30
0.20
0.15
0.05
0.60
0.05
0.05
'SFP'
1.0
0.30
0.15
0.25
0.15
0.40
0.15
0.15
FELLN
FEVLN
FEDLN
FELLK
FPXL
0.40
0.13
0.02
0.40
0.0
0.45
0.13
0.02
0.45
0.0
0.40
0.15
0.10
0.40
0.0
PASTOF calculates the soil nutrient balance with fixed loss fractions of fertiliser, manure and urine
(Stoorvogel, 1993; Hengsdijk et al., 1996). However, loss fractions are in reality not constant: with
increasing fertiliser application, the ‘holding capacity’ of the soil steadily becomes saturated and
increasing portions of additional fertiliser are lost by leaching, denitrification etc. Therefore, an extra
‘fertiliser loss factor’ can be specified, that is a multiplication factor on the calculated amount of
needed gross fertiliser (with losses as specified above) as function of applied net (without losses)
fertiliser. This fraction is an empirical parameter that can be derived from field experiments. The
data values below are derived from Vicente-Chandler et al. (1974), who found that fertiliser use
efficiency (losses) in tropical humid environments are constant up to a gross application rate of
about 800-1000 kg ha-1, which coincides in our example with some 400 kg ha-1 net application rate.
* 'Extra loss of fertiliser nitrogen (to be divided over leaching and
* denitrification), as multiplication factor on calculated gross
* N fertiliser gift (from loss fractions as above).
* Give list as function of net fertiliser gifts (kg/ha)-fraction
EXLOST =
0.0
1.0
250.
1.0
275.
1.0
300.
1.0
400.
1.0
425.
1.1
450.
1.2
475.
1.3
1000.
1.5
The extra losses are distributed over leaching and denitrification:
* Fraction of 'extra' loss distribution over leaching and denitrification
* LLEX = fraction to extra leaching loss (1-LLEX goes to denitr. loss)
LLEX = 0.5
4.1.3 CAT_CHAR data file
The herd ‘manure’ file contains some characteristics of the stock that is supposed to graze the
pasture. This file can be made by the user according to own insights, or be made by the CRIA
model (see Chapter 3.1). The data in this file are used by PASTOF to calculate daily amounts of
consumed nutrients and energy per animal unit, and in the calculation of the soil nutrient balance
via inputs of nutrients by manure and urine per animal unit.
43
**************************************************
* This file was created by CRIA.FOR
* in its first run (no reruns used)
* Contains characteristics of simulated herd.
**************************************************
* Herd size (number)
HSIZE =
50
* Herd size (animal unit)
HSAU =
41.33
* Live weight of sold male calve (kg)
SLWMS =
190.60
* Number of sold male calves (no)
NSMS_HRD =
12.50
* Live weight of sold female calve (kg)
SLWFS =
158.88
* Number of sold female calves (no)
NSFS_HRD =
8.38
* Live weight of sold female cow (kg)
SLWF =
452.90
* Metabolizable energy req. (Mcal/mth/herd
MEHRD =
20419.71
* Crude protein required (kg/mth/herd)
CPHRD =
943.64
* Phosphorus required (kg/mth/herd)
PHRD =
20.97
* Crude protein in manure (kg/mth/herd)
FCPHRD =
587.14
* Crude protein in urine (kg/mth/herd)
UCPHRD =
275.96
4.1.4 Site file
The site file contains two parameters that are used by all PASTOR models: interest rate and the
number of work hours in a day. The interest rate is used in the calculations of annuity costs of
items/inputs that have a lifetime (renewal period) of more than one year.
* Interest rate for cost calculations (%/year) (real)
44
RINT = 7.
All labour specifications in the input files are given in hours. However, all PASTOR models compute
total labour requirements on a daily basis, Therefore, the number of hours in a work-day is specified
under DAYHR.
* Hours of labour in one day (real) (h/d)
DAYHR = 8.
Next, the maximum allowable level of soil mining has to be supplied, per nutrient type and per soil
type. For truly sustainable and stable production systems, the allowable mining is zero (Van
Ittersum & Rabbinge, 1997).
* ANMINE allowable nitrogen mining (kg/ha) (real) ( 0)
* AKMINE allowable potassium mining (kg/ha) (real) ( 0)
* APMINE: allowable phosphorus mining (kg/ha) (real) ( 0)
SOIL
ANMINE
AKMINE
APMINE
'SFW'
0.
0.
0.
'SIW'
0.
0.
0.
'SFP'
0.
0.
0.
4.2 PASTOU model
Input and output files are specified in CONTROL.DAT the same way is for the PASTOF model
(Paragraph 4.1).
4.2.1 Pasture data file
As for PASTOF, input parameters that characterise pasture species, production levels and
management of the pasture to be modelled are specified in the pasture file. The standard example
files are NATURAL.DAT for non-fertilised natural pastures and BPINTOI for a grass-legume mixture
(Brachiaria brizantha + Arachis pintoi), see Appendices 1.2.4 and 1.2.5. The parameters of the
pasture file are explained here using NATURAL.DAT DAT for natural pasture in the North Atlantic
Zone (NAZ) of Costa Rica as example.
PRODUCTION CHARACTERISTICS
First, the name and a one-letter code for the pasture type is given. The one-letter code will appear
in the output files in the complete code that characterises the pasture being modelled (see below).
Note: each pasture file should have a unique one-letter code (e.g. ‘N’ for Natural, ‘P’ for B.
Brizantha + A. pintoi mixture etc.).
* GNAME : Grass name (character)
* GCODE : Grass code (one letter only!) (character)
* -------------------------------------------------GNAME = 'Natural'
GCODE = 'N'
45
Next, the (target) production level needs to be specified in terms of above-ground dry biomass and
contents of metabolisable energy, crude protein and phosphorus, on the best soil available in the
area under study. This is different from the input for the PASTOF model; there is no quantification of
‘maximum attainable’ and ‘minimum’ production levels, but the desired target production is directly
inputted.
* Grass data at level of attainable production (PER MONTH):
* MONTH: Name of month (character)
* DMP:
(above-ground total) Dry matter attainable production
*
(kg/month) (real)
* CP:
Crude Protein content (%)
* ME:
Metabolizable energy content (Mcal/kg) (real)
* P:
Phosphorus content (%) (real)
* K:
Potassium content (%) (real)
(real)
* -------------------------------------------------* Data for attainable production estimated as two times that of current
MONTH
DMP
CP
ME
P
K
! data from various sources
'JAN'
1087.
10.0
2.1
'FEB'
1087.
10.0
2.1
0.15
1.5
! literature, expert-knowledge
0.15
1.5
! Total attain. prod: 15 t/ha/y!
'MAR'
1087.
10.0
'APR'
1304.
10.0
2.1
0.15
1.5
! Villareal pers. com.
2.1
0.15
1.5
'MAY'
1304.
10.0
2.1
0.15
1.5
'JUN'
1304.
10.0
2.1
0.15
1.5
'JUL'
1304.
10.0
2.1
0.15
1.5
'AUG'
1304.
10.0
2.1
0.15
1.5
'SEP'
1304.
10.0
2.1
0.15
1.5
'OCT'
1304.
10.0
2.1
0.15
1.5
'NOV'
1304.
10.0
2.1
0.15
1.5
'DEC'
1304.
10.0
2.1
0.15
1.5
EFFECT OF SOIL TYPE AND STOCKING RATE
Next, effects of soil type on pasture production and nitrogen supply are given. The production
specified above, DMP, applies to the best soil type in the area. For other soil types, two reduction
factors linearly reduce these productions according to soil limitations: RDMP and RDMUSE. A third
factor is needed per soil type to calculate the soil nitrogen balance: NSUPL (explained below).
These tree parameters need to be supplied for all soil types under study. Soil types are indicated by
a three letter code, in our example SFW (Soil Fertile Well drained), SIW (Soil Infertile Well drained)
and SFP (Soil Fertile Poorly drained). The soil names given here should correspond to the list of
soil names available in the soil data file (SOIL.DAT; see Paragraph 4.1.2).
RDMP quantifies the reduction in pasture production due to soil limitations such as acidity, poor
drainage, nutrient shortage or low water holding capacity. In the example below, it is specified that
there is no reduction in production on SFW soils since these soils are the best soils in the NAZ. SIW
are acid soils, and target production levels are 80% of those on the best soils. SFP has drainage
problems, but the natural grasses assumed to grow here are supposed to be species adapted to
water excesses. Therefore, the yields on SFP soils are the same as on SFW soils, and the
reduction factor is 1.
RDMUSE quantifies the effect of soil type on the potential use fraction of the total above-ground
biomass as function of stocking rate. Not all above-ground production can be eaten by grazing
animals because i) parts such as stubble are ‘unreachable’ and should be left for regrowth, ii) parts
46
are trampled under the hooves of the animals, and iii) parts are (temporarily) unavailable because
they are covered by manure or urine patches (Deenen, 1994; Van der Ven, 1992). The potential
fraction of total above-ground biomass ‘on offer’ for consumption is called DMUSE, and depends on
the amount of animals per surface unit (stocking rate). The factor DMUSE is - as standard specified for the best soil type available in the area. The reduction factor RDMUSE adapts DMUSE
to the conditions of the actual soil types to be studied. In our example, there is no extra reduction in
fraction dry matter on offer on the soils SFW and SIW. The soil type SFP is poorly drained,
however, and trampling on this soil causes an extra 80% reduction in fraction dry matter on offer.
NSUPL quantifies the amount of nitrogen supplied by the pasture to ‘itself’. NSUPL is meant for
grass-legume mixtures where the legume supplies nitrogen to the grass. In our example of natural
pasture, there are no leguminous species and NSUPL is 0 on all soils. For the example of the
B.brizantha + A. pintoi mixture in the file BPINTOI.DAT (Appendix 1.2.5), NSUPL is 150 kg/ha.
Note: NSUPL is not to be confused with the parameter NFIX in the soil file that quantifies the
amount of nitrogen fixed in the soil by free-living micro-organisms (Paragraph 4.1.2).
* Yield reduction factors
* SOILP:
Soil name (character)
* RDMP:
Reduction fraction of attainable production (DMP as above)
*
due to soil limitations (-) (real)
* RDMUSE: Reduction fraction of potential dry matter on offer (DMUSE
*
see below), due to soil limitations. (-) (real)
* NSUPL: Supply of nitrogen from legumes that may be present
*
e.g. as in grass-legume mixtures. (kg/ha) (real)
* ---------------------------------------------------------------SOILP
RDMP
RDMUSE
NSUPL
'SFW'
1.0
1.0
0.
'SIW'
0.8
1.0
0.
'SFP'
1.0
0.8
0.
! Estimates from expert knowledge
Note: in this example, three soil types are supplied. This list can be shortened or extended (with a
minimum of one soil type, and a maximum of 10). The soil names will appear in the complete code
that characterises the pasture being modelled (see below).
The factor DMUSE specifies the fraction of the total-above ground matter potentially on offer for
consumption as function of stocking rate, on the best soil type available in the area. Information on
this relationship can be derived from experiments, expert knowledge or literature. The user is
completely free to fill-in this table: the value of the stocking rates provided and the number of
stocking rates can be adapted according to local conditions and wishes of the user (a minimum of
one relationship should be provided; the maximum is 50). In our example, stocking rate varies from
one to three.
* SRATE: Stocking rate (animal units per ha) (real)
* DMUSE: Potential fraction above-ground dry matter on offer
*
on best soils, as function of stocking rate (-) (real)
* ---------------------------------------------------------------SRATE
DMUSE ! estimated from expert knowledge
1.
0.55
1.5
0.525
2.
0.50
2.5
0.475
3.
0.45
47
The stocking rates will appear (preceded by the letter ‘R’) in the complete code that characterises
the pasture being modelled (see below).
TECHNOLOGY: WEEDING
At his moment, PASTOU calculates the amount of (target) above-ground production that is
available for consumption by the herd, for each soil and for each stocking rate. Unlike as in
PASTOF, no production levels are set by manipulating fertiliser application. Different technologies
are only defined by specification of the manner of weeding. The system is generic in the sense that
the user can ‘build’ his own options for the manner in which weeds are controlled at the end of the
file. From these own-build options, a selection can be made and used as input under WEED. This
management input parameter (WEED) is preceded by a column that encodes the ‘technology’ level
as a two-digit number. This two-digit number will appear (preceded by the one-letter code that
indicates the type of pasture, see above) in the complete code that characterises the pasture(s)
being modelled (see below).
* PLEVEL: Code for technology level (2 numbers only!) (integer)
* WEED:
Manner of weeding (name) (character)
*
Select from options given below under 4.OPERATIONS)
* ---------------------------------------------------------------PLEVEL
WEED
20
'mixed'
In our example, there is only one technology level that will be modelled by PASTOU. However, this
list can be shortened or expanded to include various manners of weed control desired (a minimum
of one, and a maximum of 50). PASTOU will calculate technical coefficients for all combinations of
soil type, stocking rate and technology level so far specified (in our example three soil types, five
stocking rates and one technology level, leading to 15 PASTs).
ESTABLISHMENT AND MAINTENANCE OPERATIONS
The pasture specified so far has to be established by sowing or planting (the only exception being
‘natural’ grass), and maintained and managed by operations. First, pasture establishment
operations are specified by listing labour and material inputs required for two specific actions: i)
application of herbicides to kill existing crops or natural vegetation, and ii) the application of a basic
fertiliser gift. For the application of herbicides, the names of the herbicides, the amount of
herbicides, the amount of labour used, and the equipment type of traction used need to be
specified. The herbicides used have to be selected from the attribute file BIOCID.ATF, the
equipments from the attribute file EQUIP.ATF file, and the tractions from the attribute file
EQUIP.ATF. The units of the quantities of the herbicides, equipments and tractions have to be the
same as those in these *.ATF files. When a desired herbicide/equipment/traction is not present in
these files, they can be added by the user and then selected here. Several herbicides can be
applied by listing these products in different rows. For the application of each herbicide, the amount
of labour used is specified under EWLAB. Alternatively, a separate line can be used to enter all
labour used for the application of all herbicides, and then a ‘0’ can be entered for each herbicide
separately. For instance, in the example below, the first line is used to enter all labour, equipment
and traction used for all herbicides together, and the herbicides are listed separately on the
following lines. The number of entries (lines) is flexible and can be shortened or expanded by the
user (minimum is one; maximum is five).
48
Separate lines are used to enter the fertilisers applied at establishment. This follows the same
scheme as for the herbicides, with the difference that the fertilisers are selected from the FERT.DAT
attribute file. Since all these data are used by PASTOF to calculate costs and total labour use for
the pasture, the duration of the pasture has to be supplied at EDEP (needed to calculate annuities
of costs).
* EDEP
Depreciation time of pasture (year) (real).
* EWLAB/EFLAB
Farm labour use for weeding/fertilising (hours) (real)
* EWNAME/EFNAME Herbicide/fertiliser name (name) (character);
*
to select from BIOCID.ATF and FERT attribute files.
* EWQUAN/EFQUAN Herbicide/fertiliser quantity (unit) (real)
* EWEQ/EFEQ
Herbicide/fertiliser equipment name (name) (character);
*
to select from EQUIP.ATF attribute file.
* EWQUSE/EFQUSE Herbicide/fertiliser equipment use (hours) (real)
* EWTRAC/EFTRAC Herbicide/fertiliser traction for equipment (name)
*
(character) to select from TRACTION.ATF attribute file.
EDEP = 100.
EWLAB
0.0
EWNAME
'None'
EWQUAN
EWEQ
0.
'none'
EWQUSE
0.
EWTRAC
'none'
EFLAB
EFNAME
EFQUAN
EFEQ
EFQUSE
EFTRAC
0.0
'none'
0.
'none'
0.
'none'
Natural grasses are a special case because the pasture is not truly ‘established’ since, by definition,
a natural pasture already exists. In our example above, therefore, entries ‘0’ and ‘none’ are given to
indicate that no labour nor any inputs are used in the ‘establishment’ of natural pasture. The
depreciation period is set to an arbitrary high value of 100 years. An example for the establishment
of a grass-clover mixture is found in Appendix 1.2.5.
Next, the input of labour and other materials for the establishment and maintenance of the pasture
have to be supplied. Under OPER, a brief description of the operation can be supplied. The list then
follows the same principle as above: materials have to be selected from the MATER.ATF attribute
file, equipments from the EQUIP.ATF file and tractions from the EQUIP.ATF file. The units of the
quantities of the materials, equipments and tractions have to be the same as those in the *.ATF
files. When a desired material/equipment/traction is not present in these files, they can be added by
the user and then selected here. The duration/lifetime can vary per material and therefore the
depreciation time DEPRET has to be specified per material input. When materials are inputted each
year, DEPRET should be set to ‘0’. In the example for natural pastures below, there are lines that
specify the establishment of fences (lines 1-4), lines for the maintenance of the fences (line 5) and
for the use of 5 small tools in general (e.g. a saw, a machete, a hammer, a bucket, a knife) (line 6).
Sine natural grass is existent, there is no input of seeds or stolons (see Appendix 1.2.5. for an
example of inputs for a grass-legume mixture). The fences (and the used fence materials) have a
lifetime of six years and need to be replaced; the fences are maintained every year (DEPRET = 0),
and the small tools have a lifetime of five years. The user can decrease or increase the list
according to own specifications (with a minimum of one, a maximum of five).
* OPER
Name of operation (name) (character)
* OWNLAB
Own (farm) labour use (hours) (real)
* MATER
Name of used materials (name) (character)
*
to select from MATER.ATF attribute file.
* MQUANT
Materials quantity, in same unit as in materials file! (name)
*
(real)
49
* DEPRET
Depreciation time of used materials (years) (real).
*
Note: when DEPRET is 0, the operation/inputs are yearly recurrent.
* EQUIP
Name of equipment used (name) (character),
*
to select from EQUIP.ATF attribute file.
* EUSE
Equipment use time (real) (hour)
* TRAC
Traction used to 'pull' equipment (name) (character)
*
to select from TRACTION.ATF attribute file.
* Input data: Andre Nieuwenhuyse, based on farmer inquiries in the AZ (96-97)
OPER
OWNLAB
MATER
MQUANT
'Labour fence estab.' 12.
'none'
0.
'Fences barbed wire'
0.
'bwire-Cai'
350.
'Fences dead'
0.
'dposts-sl'
'Fences nails'
0.
'cramp-l'
'Fence maintenance'
2.
'Various small tools' 0.
DEPRET
EQUIP
EQUSE
TRAC
6.
'none'
0.
'none'
6.
'none'
0.
'none'
33.
6.
'none'
0.
'none'
0.5
6.
'none'
0.
'none'
'none'
0.
0.
'none'
0.
'none'
'stools'
5.
5.
'none'
0.
'none'
WEEDING APPLICATION MANNER
The last section of the data file is meant to ‘build’ own specifications of recurrent weeding practices.
Unlike as for PASTOF, the amount of labour and amount of herbicides can be entered directly,
since the above-ground biomass (and hence the soil cover) are not calculated by the model but are
entered directly by the user. The input for weeding operations follows the same structure as for
PASTOF (Paragraph 4.1.1). For each manner of weeding that the user wants to ‘build’, the following
inputs need to be specified: labour use, type and amount of herbicides applied, and equipment and
traction used in the application of the herbicides. All inputs are yearly totals (per hectare). Because
more than one type of herbicide may be applied, there is provision to enter data for up to three
herbicides. The labour use, and the use of equipment and traction on each line are the totals of all
labour, equipment and traction used in the whole year (summed over all manual weeding and the
application of all the herbicides). On each line, manual weeding - in the from of labour hours
invested - and chemical weeding may be combined by summing all labour used under OL. The
name of the manner should be entered under WEEDN. This name can then be used earlier in the
file to select the manner of weeding that is to be modelled (under WEED; see above). In the
example below, three weeding manners have been build; a strict manual weeding, a strict chemical
weeding, and a mixed manner with both manual and chemical weeding. The user is free to ‘build’
any number of alternative weed control manners (with a minimum of one, a maximum of five).
Quantitative data on labour hours and chemical inputs have to be obtained from field enquiries and
from expert knowledge.
* WEEDN
Name of weeding manner (name) (character)
* OL
(total) Own (farm) labour use (hour/year) (real)
* C1N
Name of first herbicide input (name) (character)
*
to select from BIOCIDE.ATF attribute file.
* C1Q
Quantity of first herbicide input (amount/year) (real)
*
Units of quantity should match those in biocide file!
* C2N
Name of second herbicide input (name) (character)
*
to select from BIOCIDE.ATF attribute file.
* C2Q
Quantity of second herbicide input (amount/year) (real)
*
Units of quantity should match those in biocide file!
* C3N
Name of third herbicide input (name) (character)
*
to select from BIOCIDE.ATF attribute file.
50
* C3Q
Quantity of third herbicide input (amount/year) (real)
*
Units of quantity should match those in biocide file!
* WEQ
Equipment used for weeding (name) (character)
*
to select from EQUIPMENT.ATF attribute file.
* WEQU
Use time of equipment (hours/year) (real)
* WTRA
Traction used to 'pull' equipment (name) (character)
*
to select from TRACTION.ATF attribute file.
* Input data: Andre Nieuwenhuyse, based on farmer inquiries in the AZ (96-97)
WEEDN
OLWEED
C1N
C1Q
C2N
C2Q
C3N
C3Q
WEQ
WEQU
WTRA
'manual' 10.
'None'
0.
'None'
0.
'None'
0.
'none'
0.
'none'
'chemic' 6.0
'24D'
3.0
'Tordon-101'
1.0
'Combo'
0.035
'ksspray'
6.0
'none'
'mixed'
'24D'
1.5
'Tordon-101'
0.5
'Combo'
0.035
'ksspray'
3.5
'none'
7.0
CODING OF GENERATED PASTS
PASTOU produces output files that contain technical coefficients of all modelled alternative pasture
production systems (PAST). Many PASTs may be generated in one run of PASTOF for a single
pasture type because the model is repeatedly executed with different combinations of soil type,
stocking rate and technology level as specified in the pasture data file. Each PAST is recognised by
a code, written in the first column of each output file. The explanation of this code is given for an
example generated by PASTOU for one of the alternatives specified in the example pasture data
file NATURAL.DAT.
SFW.N20.R1.JAN
where:
 SFW is the soil type (SOILP)
 N20 is a combination of the one-letter code for the pasture name (GCODE) with the technology
level (PLEVEL)
 R1 indicates the stocking rate (SRATE)
 JAN indicates the month for which the particular TC in the file is valid (MONTH; not used in all
files)
4.2.2 Soil, CAT_CHAR and site data file
The soil, CAT_CHAR and site data files used by PASTOU are exactly the same as those used by
PASTOF (Paragraphs 4.1.2-4.1.4).
4.3 Special case: reruns
PASTOF and PASTOU calculate technical coefficients for all alternative pasture production systems
(PASTs) as specified in the pasture data files. One pasture data file may lead to different PASTs for
one pasture type (botanical composition, e.g. Estrella grass). However, it could be interesting to
generate PASTs for a number of different pasture types. The rerun option of PASTOR allows that
51
PASTOF and PASTOU are automatically executed several times by reading and using subsequent
pasture data files. A RERUNS.DAT file should be created and put in the PASTOF or PASTOU subdirectory. This RERUNS.DAT file should contain the names of alternative pasture input files that
should be used. This is done by repeating the name and path of the FILEI1 parameter in the
CONTROL.DAT file, but using different data file names. For example, the following RERUNS.DAT
file causes PASTOF first to generate PASTs for the pasture Estrella (as ESTREL.DAT was
specified in CONTROL.DAT; see Paragraph 4.1.1), and then subsequently PASTs for the pastures
Brachiaria brizantha (as specified in BBRIZAN.DAT) and Tanner (as specified in TANNER.DAT)
FILEI1 = 'C:\PASTOR\FILE_IN\PASTO\BBRIZAN.DAT'
FILEI1 = 'C:\PASTOR\FILE_IN\PASTO\TANNER.DAT'
Note: remember that each pasture file should have a unique one-letter code to indicate the pasture
type (e.g. ‘E’ for Estrella, ‘T’ for Tanner etc.).
When no reruns are wished, the RERUNS.DAT file should be removed from the sub-directory, or an
asterix may be put in front of each line in the file.
52
5 Generating Feed Acquisition Systems (FASTs)
The model to generate feed acquisition systems (FASTs) is run by giving the SUPP.EXE command
in the PASTOR\PASF_SUPP sub-directory. In this chapter, the control over SUPP is explained.
SUPP is a very simple model that merely selects a number of supplementary feed options and
‘transforms’ the data format of the file that contains the feed attributes to the standard output format.
In CONTROL.DAT (in the sub-directory MOD_SUPP), the required model input, attribute and output
files of SUPP are specified:
*************************** CONTROL.DAT ***********************
* Control file for SUPP
model
* PASTOR 2.0
*
*
***************************************************************
* FILEI1
Attribute file with supplementary feed attribute data
* FILEI2
Input file with supplementary feed input data
* FILEI3
Input file with site data
* FILEO2
Output file with labour and costs data
* FILEO3
Output file with nutrition value data
FILEI1 = 'C:\PASTOR\FILE_ATR\FEEDS.ATF'
FILEI2 = 'C:\PASTOR\FILE_IN\FEED\FEEDS.DAT'
FILEI3 = 'C:\PASTOR\FILE_IN\SITE.DAT'
FILEO2 = 'C:\PASTOR\FILE_OUT\FEEDLC.PRN'
FILEO3 = 'C:\PASTOR\FILE_OUT\FEEDP.PRN'
The input and attribute files needed are specified at the variables FILEI1-3. Note that, beside the file
name, the complete path is given. Users may change the names of the data files when they have
created their own input files: FILEI1 contains the attribute file of all feed supplements available;
FILEI2 contains the names of the supplementary feeds selected, and FILEI3 lists the site file that
contains so-called ‘site’ data, such as rate of interest and work-hours in a day, that are also used by
the other models of PASTOR. The input file FEEDS.DAT is explained in detail below.
Attribute files (FILEI1) are explained in Chapter 6. The name of the attribute file should not be
changed by the user.
The names of the output files are given under the variables FILEO2-3. These names are the same
as given in Table 2.3.1, but may be changed by the user.
In the file FEEDS.DAT, a number of supplementary feed types should be supplied under SFNAME.
Feed types are to be selected from the FEEDS.ATF file. If required, the FEEDS.ATF file can be
updated to include the supplementary feed types of interest. Each selected supplementary feed
type in FEEDS.DAT should be accompanied by a number of parameters that specify the labour and
equipments involved in distributing the feed supplement to the cattle. The labour use (LABUSE; in
hour per kg of product) typically involves carrying the feed supplement to a trough or to a common
eating-place of the cattle. Equipments to carry the feed on the farm (EQUIP) can be selected from
the EQUIP.ATF attribute file (e.g. wheel-barrow). Some equipments need ‘traction’ for pulling (e.g. a
tractor to pull a chart), (TRAC), which may be selected from the TRACTION.ATF attribute file. All
53
entries for LABUSE, EQUIP, EQUSE and TRAC refer to activities in carrying and distributing the
feed supplement on-farm to the animals. In the example below, four feed supplements have been
selected from the FEEDS.ATF attribute file. It takes 0.01 hour to carry and distribute 1 kg of
molasse to the animals; 0.003 hours for 1 kg of bananas; 0.007 hours for 1 kg of concentrate type
number 2; and 0 hours for phosphorus concentrate p20 (because this product is mixed with salt,
and the distribution time for salt to the animals is already included under MSLAB in the herd
management data file; Paragraph 3.1.2!). All feed supplements are distributed by hand and by
generally available tools on the farm (e.g. a spade as included under T3MAT in the herd
management data file; Paragraph 3.1.2).
* SFNAME
Supplementary feed name (name) (character)
* LABUSE
Labour use to deliver supplementary feed on farm (hr/kg) (real)
* EQUIP
Equipment used to deliver suppl. feed on farm (name) (character)
* EQUSE
Time use of equipment (hr/kg)
* TRAC
Traction used to 'pull' equipment (name) (character)
SFNAME
LABUSE
EQUIP
EQUSE
TRAC
'molasse'
0.01
'none'
'none'
'none'
'banana'
0.003
'none'
'none'
'none'
'conc2'
0.007
'none'
'none'
'none'
'p20'
0.0
'none'
'none'
'none'
The list presented here contains four feed supplements. This list can be shortened (with a minimum
of one) or extended (up to a maximum of 25). A complete FEEDS.DAT data file is given in Appendix
1.3.3.
54
6 Attribute files
There are seven so-called attribute files (Figure 2.1) that list attributes (characteristics) of items that
can be referred to in input files of PASTOR. For example, in the pasture data and herd
management input files, reference can be made to materials that are listed in the MATER.ATF
attribute file. Wherever attribute files are used in the input data files, the name of these attribute files
are explicitly mentioned in the input files. Having attributes of inputs of production systems stored in
separate files facilitates the use of these attributes in various model input data files (Stoorvogel,
1995; Jansen & Schipper, 1995).
Common attributes of items in the attribute files are:
CODE
a numerical code (obsolete)
NAME
name of the item
DESCR
brief description of the item
UNIT
unit of measure of item
PRICE
price of the item
PY
year that price information was collected
PM
month that price information was collected
The above names are generally preceded by a letter that indicates the type of the item, such as ‘M’
for ‘materials’, ‘E’ for ‘equipments’, ‘T’ for ‘traction types’, etc. Furthermore, different attribute files
may hold additional attributes, such as nutrition data in the FEEDS.ATF file and pesticide data in
the BIOC.ATF file. These data are all explained in the headers of the files. Attribute information is
used by PASTOR in the computation of cost prices, labour requirement and some environmental
indicators (namely the PEII, Paragraph1.2.3). Appendix II lists all attribute files currently present in
PASTOR 2.0. Users may update these files according to own wishes and insights by editing the
existing attributes (such as price updates) and/or by adding new lines with new items. The only
restriction for adding new lines is that all columns must be filled-in. The CODE column is currently
obsolete and any ‘dummy’ number can be filled-in.
In PASTOR, there is a fixed maximum number of the rows for each attribute file. When users make
the number of rows too large, the file can not be read by the PASTOR programs and a Fortran error
message occurs. This problem can be solved by removing some lines with items that are not used
in the data input files.
55
7 Error and warning messages
Care has been taken to ‘safeguard’ the user from making errors - or getting model run time errors when executing PASTOR. However, errors may still occur when running PASTOR models, and
here are some solutions to possibly occurring problems. Some error and warning messages have
been programmed by the authors of PASTOR (and by the subroutines that it uses), while other
errors may come from Fortran itself in the form of run-time errors.
Input data error
 All data in the input data files and in the attribute files are checked during model execution on
impossible and/or unlikely values. For example, negative prices or negative growth rates of
animals are not allowed, and the user gets an error message when PASTOR reads these data.
In general, this error message is accompanied with a brief text explaining the nature of the
problem. Refer to the corresponding section of this manual when the explanation for the
particular error insufficiently clear to solve the problem.
 The models of PASTOR are written in the Fortran language. This means that all input
parameters must have a certain ‘format’. The format of each parameter is indicated in the
example files: Integer: whole number (numeric) without a ‘dot’; e.g. 1, 50 or 100; Real: any
number (numeric) with a ‘dot’; e.g. 0.23, 1. or 100.; Character: characters (words or
abbreviations) put between ‘ ‘; e.g. ‘H’. When parameters are specified in the wrong format, the
models give error messages when trying to read these data.
 Some data in input and attribute files are supplied in columns (e.g. all attribute file data, the
attainable production data in the pasture input files). In PASTOR, a maximum array-size is
defined for each of these ‘column-variables’. When the column size (i.e. number of rows) has
been made larger (by entering too many lines) than this pre-defined array-size, Fortran run-time
errors are returned during execution of PASTOR. This problem can be solved by removing
(condensing) some lines in the input files.
 When required input data have been omitted in a data input file, an error message is returned
when PASTOR tries to read this data from file. Generally, a good indication is given about
which data element is lacking in which file.
File name/location error
When files are not present under the name and in the directory as specified in the CONTROL.DAT
files, PASTOR returns an error message on the file name that it is unable to find. Remedy: check
thoroughly names and paths of the input/output files in CONTROL.DAT files.
Runtime error
 Despite careful checking on impossible/unlikely input data, runtime errors during execution of
PASTOR might still happen. Such errors are generally caused by execution of ‘impossible’
equations, such as division by zero. Another error might be the writing of output data to files
with ‘insufficient’ space allocated (e.g. trying to write a seven digit number to a space for a six
digit number only). Such errors are inherent in scientific programs and can not be avoided for
100%. The only solution is to double-check all data entries and look for unlikely combinations of
input data.
 A number of runtime checks have been build-in by the developers of PASTOR, and concern
mass and nutrient balance checking. These checks are to safeguard against erroneous model
results.
56
57
References
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growth simulation models: pedigree and historical overview. Agricultural Systems 52: 171-198.
Bouman, B.A.M. & A. Nieuwenhuyse, 1998. Exploring sustainable beef cattle farming options in the
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Bouman, B.A.M., R. A. Schipper, A. Nieuwenhuyse, H. Hengsdijk & H.G.P. Jansen, 1998.
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Deenen, P.J.A.G., 1994. Nitrogen use efficiency in intensivel grassland farming. PhD Thesis.
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Griffith, K. & L. Zepeda, 1994. Farm level trade-offs of intensifying tropical milk production.
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generator for land use activities in the Koutiala region of south Mali. DLV report no. 6, ABDLO/Department of Development Economics, Wageningen, The Netherlands. 40 pp. + appendices.
Hernandez, M., P.J. Argel, M.A. Ibrahim & L. ‘t Mannetje, 1995. Pasture production, diet selection
and liveweight gains of cattle grazing Brachiaria brizantha with or without Arachis pintoi at two
stocking rates in the Atlantic Zone of Costa Rica. . Tropical Grasslands 29: 134-141.
Ibrahim, M.A., 1994. Compatibility, persistence and productivity of grass-legume mixtures for
sustainable animal production in the Atlantic Zone of Costa Rica. Ph.D. thesis, Wageningen
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Jansen, D.M. & R.A. Schipper, 1995. A static, descriptive approach to quantify land use systems.
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land use analysis: an example from Costa Rica. Netherlands Journal of Agricultural Science, 43:
61-82.
Jones, M.R., 1989. A generic planning model for use in the livestock feed sector of developing
countries. Agricultural Systems 29: 267-286.
Keller, M., E. Veldkamp, A.M. Weitz & W.A. Reiners, 1993. Effect of pasture age on soil trace-gas
emissions from a deforested area of Costa Rica. Nature 365: 244-246.
Nicholson, C.F., D.R. Lee, R.N. Boisvert, R.W. Blake & C.I. Urbina, 1994. An optimization model of
the dual-purpose cattle production system in the humid lowlands of Venezuela. Agricultural
Systems, 46: 311-334.
Nieuwenhuyse, A., 1996. Soils, geology and soil-related sustainability aspects of the perhumid
tropical Limon basin, Costa Rica. Serie Tecnica. Informe Tecnico 272. CATIE, Turialbla, Costa
Rica. 85 pp.
NRC, 1989. Nutrient requirements of dairy cattle, Sixth revised edition update 1989. National
Academy Press, Washington D.C. 157 pp.
NRC, 1996. Nutrient requirements of beef cattle. National Academy Press, Washington D.C. 242
pp.
Price Gittinger, J., (Editor), 1973. Compounding and discounting tables for project evaluation. John
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Rappoldt, C. & D.W.G. van Kraalingen, 1990. FORTRAN utility library TTUTIL. Simulation Report
CABO-TT. AB-DLO, Wageningen, The Netherlands. 54 pp.
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nitrogenado sobre el rendimiento y valor nutritivo del pasto estrella (Cnynodon nlemfuensis). San
Pedro de Montes de Oca. Costa Rica. 66 pp.
Schipper, R.A., 1996. Farming in a fragile future. Economics of land use with applications in the
Atlantic Zone of Costa Rica. Ph.D thesis, Wageningen Agricultural University, The Netherlands. 282
pp.
Stoorvogel, J.J., 1993. Optimizing land use distribution to minimize nutrient depletion: a case study
for the Atlantic Zone of Costa Rica. Geoderma 60: 277-292.
Stoorvogel, J.J., 1995. Geographic information systems as a tool to explore land characteristics and
land use, with reference to Costa Rica. PhD thesis, Wageningen Agricultural University,
Wageningen, The Netherlands. 151 pp.
Stoorvogel, J.J., Schipper, R.A., and Jansen, D.M., 1995. USTED: a methodology for quantitative
analysis of land use scenarios. Netherlands Journal of Agricultural Science (43): 5-18.
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29: 149-164
59
Upton, M., 1993. Livestock productivity assessment and modelling. Agricultural Systems, 43: 459472.
Van der Ven, G.W.J., 1992. Grasmod, a grassland management model to calculate nitrogen losses
from grassland. CABO-DLO report 158. CABO-DLO, Wageningen, The Netherlands. 108 pp.
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Experiment Station Rio Piedras, Puerto Rico.
I-1
Appendix I: PASTOR input files
I.1 APST input files
I.1.1 CRIAHRD.DAT
************************** CRIAHRD.DAT****************************
* Data file for CRIA.FOR, as in PASTOR version 2.0
*
******************************************************************
* Correction factor for maintenace energy required to support grazing
* (NRC, 1989; page 7):
* MAINK = 1.0: for stable-fed
* MAINK = 1.1: for good pasture
* MAINK = 1.2; for sparse pasture and long walking distance
* Bounded by 1.0 - 1.2
MAINK = 1.2
* One-letter code for herd (B from breeding)
HCODE = 'B'
* Herd size (no) (INTEGER); bounded by 1 and 900
HSIZE = 50
* ITYPEF/M: Type of DAIRY cattle (-) (integer)
* ITYPEF = 1: female, large breed (max weight is 800 kg)
* ITYPEF = 2: female, small breed (max weight is 600 kg)
* ITYPEM = 3: male, large breed (max weight is 1000 kg)
* ITYPEM = 4: male, small breed (max weight is 800 kg)
ITYPEF = 1
ITYPEM = 3
* Breed effect on maintenace requirements (NRC, 1996, p 115)
BE = 0.90
* SRW: see page 116 (NRC, 1996);
* FSBW = actual final shrunk body weight at maturity
SRW = 435.
FSBW = 550.
* Maximum age of reproductive female animal (year) (integer)
* bounded by 0 and 20.
IAMAX = 11
* Live weight of animal at birth (kg) (real)
LWB = 32.
* Age of selling of male surplus (month) (real), bounded by 0
* and 12 * IAMAX
ASMS = 8.
* Age of selling of female surplus (month) (real), bounded by 0
* and 12 * IAMAX
ASFS = 8.
* Live weight gain of males in year 0-1 (LWGM0), year 1-2 (LWGM1),
* year 2-4 (LWGM2), and after year 4 (LWGM3). (kg/day) (real)
LWGM0 = 0.65
LWGM1 = 0.45
LWGM2 = 0.25
LWGM3 = 0.
* Live weight gain of females in year 0-1 (LWGF0), year 1-2 (LWGF1),
* year 2-4 (LWGF2), and after year 4 (LWGF3). (kg/day) (real)
LWGF0 = 0.52
LWGF1 = 0.36
LWGF2 = 0.135
LWGF3 = 0.
I-2
* Mortality rate in age class 0 (0-1 years), age class 1 (1-2 years),
* and after age class 1 (-) (real). Bounded by -0 and 0.99.
MRATE0 = 0.1
MRATE1 = 0.02
MRATE = 0.01
* Abortion rate (-) (real), bounded by -0 and 0.99
AR = 0.0
* Age at first calving of reproductive female (month) (real)
* Should be higher than 12 and lower than 60 months
AFC = 31.
* Calving interval (month) (real), bounded by -0.
CI = 14.
* Duration of lactation (month) (real). Should be <= CI - 2.
DLAC = 8.
* Duration of pregnancy (month) (real). Should be <= CI
DPREG = 9.
* MILKKG: Milk production during lactation, bounded by 0 and
* 100 (kg/d) (real)
MILK = 3.5
* Fraction of milk produced by herd that is used for human consumption
* bounded by 0. and 1. (-) (real)
FMLKH = 0.
* Percentage milk fat, bounded by 0 and 10 (%) (real)
FAT = 4.5
* Specific weight of milk (kg/l)
SWMILK = 1.03
* Energy concentration of diet fed/NRC (1988) assumption (FEDNRC) with
* suggested range from 0.95 - 1.05. (bounded by 0.9-1.1) (-) (real)
FEDNRC = 1.
I.1.2 CRIAMAN.DAT
************************** CRIAMAN.DAT****************************
* Data file for CRIA.FOR; as in PASTOR 2.0
*
* Management data of cria herd
*
* THESE DATA FOR CRIA HERDS IN AZ; A. NIEUWENHUYSE, APRIL 97
*
******************************************************************
******************************************************************
* 1. Definition of herd sizes that have scale-specific requirements
******************************************************************
* HRDCLAS Herd size class (number) (integer)
* HRDMIN
Minimum number of animals in herd (number) (INTEGER)
* HRDMAX
Maximum number of animals in herd (number) (INTEGER)
HRDCLAS
1
2
3
4
HRDMIN
1
11
31
61
HRDMAX
10
30
60
100
******************************************************************
* 2. Materials and tools
* 2.1 Corral construction per herd size class
******************************************************************
* CRDCLAS Herd size class (number) (integer)
* CROLAB
Own (farm) labour for corral construction (hour/corral) (real)
* CRMAT
Name of corral material (name) (character)
*
Select from MATER.ATF attribute file.
I-3
* CRQUAN
* CRDEP
Quantity of corrals (number) (real)
Depreciation time of the corral (year) (real)
CRCLAS
1
2
3
4
CROLAB
0.
0.
0.
0.
CRMAT
CRQUAN
'corral1'
1.
'corral2r'
1.
'corral3r'
1.
'corral4r'
1.
CRDEP
30.
30.
30.
30.
******************************************************************
* 2. Materials and tools
* 2.2 Mineral salt troughs per herd size class
******************************************************************
* MTDCLAS Herd size class (number) (integer)
* MTMAT
Name of trough (name) (character)
*
Select from MATER.ATF attribute file.
* MTQUAN
Quantity of troughs (number) (real)
* MTDEP
Depreciation time of trough (year) (real)
MTCLAS
1
2
3
4
MTMAT
'trough'
'trough'
'trough'
'trough'
MTQUAN
1.
4.
5.
6.
MTDEP
5.
5.
5.
5.
******************************************************************
* 2. Materials and tools
* 2.3 Tools 1 to 3 used.
******************************************************************
* T_CLAS Herd size class (number) (integer)
* T_MAT
Name of used materials (name) (character)
*
Select from MATER.ATF attribute file.
* T_QUAN Materials quantity, in same unit as in materials file! (name) (real)
* T_DEP
Depreciation time of used materials (years) (real).
*
Note: when T_DEP is 0, the tools are yearly acquired.
* Tool1 per herd size class
T1CLAS
T1MAT
T1QUAN
1
'stools'
10.
2
'stools'
10.
3
'stools'
10.
4
'stools'
10.
* Tool2 per herd size class
T2CLAS
T2MAT
T2QUAN
1
'ltools'
3.
2
'ltools'
4.
3
'ltools'
5.
4
'ltools'
8.
* Tool3 per herd size class
T3CLAS
T3MAT
T3QUAN
1
'none'
0.
2
'none'
0.
3
'none'
0.
4
'none'
0.
T1DEP
5.
5.
5.
5.
T2DEP
3.
3.
3.
3.
T3DEP
0.
0.
0.
0.
******************************************************************
* 3. Operations
* 3.1 Miscellaneous operations on the herd (general health care,
* presence, snakes chasing,..) per herd size class
******************************************************************
* CHCLAS Herd size class (number) (integer)
* CHLAB
Own (farm) labour use (hours/year) (real)
* CHMAT
Health materials used (character)
*
Select from CATTLE.ATF attribute file.
* CHQUAN Quantity of healht materials used (unit)
CHCLAS
CHLAB
CHMAT
CHQUAN
1
180.
'emicina'
50.
2
240.
'emicina'
100.
3
300.
'emicina'
250.
4
360.
'emicina'
400.
******************************************************************
* 3. Operations
* 3.2. Assistance at birth
I-4
******************************************************************
* BRTLAB Own (farm) labour use for assistence at calving (hour/born calve) (real)
BRTLAB = 3.
******************************************************************
* 3. Operations
* 3.3. Salt application
******************************************************************
* MSNAME
Name of salt (name) (character)
*
Select from FEED.ATF attribute file.
* MSQUAN
Quantity of salt application (kg/day/AU) (real)
MSNAME
'salt'
* Labour
* CMCLAS
* MSLAB
CMCLAS
1
2
3
4
MSQUAN
0.05
Labour needed for application of minerals and salts
Herd size class (number) (integer)
Labour use to supply all mineral salt (hour/year) (real)
MSLAB
26.
30.
40.
50.
******************************************************************
* 3. Operations
* 3.4. One-time inocculation/protection of born animals
******************************************************************
* I1NAME
Name of (inocculation) material (name) (character)
*
Select from CATTLE.ATF attribute file.
* I1QUAN
Quantity (of inocculation) per application (unit) (real)
* I1LAB
Labour use per inocculation, including round-up to corral (hour/animal) (real)
I1NAME
I1QUAN
I1LAB
'brucel'
1.
0.15
'dectomax'
6.
0.30
'bacterine'
5.
0.10
******************************************************************
* 3. Operations
* 3.5. Recurrent inocculation (I2) of all animals
******************************************************************
* I2NAME
Name of inocculation material (name) (character)
*
Select from CATTLE.ATF attribute file.
* I2UNIT
Herd unit for application, either 'animal' (per animal) or 'aunit' (per an. unit)
* I2FREQ
Frequency of application (times per year per I2UNIT) (real)
* I2QUAN
Quantity of inocculation per application (unit) (real)
* I2LAB
Labour use for inocculation, without round-up time to corral (hour/I2UNIT) (real)
I2NAME
I2UNIT
I2FREQ
I2QUAN
I2LAB
'ripercol'
'aunit'
2.
20.
0.1
'bacterine' 'animal'
2.
5.
0.1
'anthrax'
'animal'
2.
5.
0.1
'neguvon'
'aunit'
5.
0.005
0.07
* I2CLAS
* I2RNO
* I2RLAB
I2CLAS
1
2
3
4
Herd size class (number) (integer)
Number of round-ups per year for inocculation (number) (real)
Round-up time to corral for inocculation (hour/round up) (real)
I2RNO
I2RLAB
6.
0.15
6.
0.30
6.
0.67
6.
1.00
I.1.3 GORDHRD.DAT
************************** GORDHRD.DAT****************************
* Data file for GORDO.FOR, as in PASTOR version 2.0.
*
******************************************************************
* Correction factor for maintenace energy required to support grazing
* (NRC, 1989; page 7):
* MAINK = 1.0: for stable-fed
* MAINK = 1.1: for good pasture
* MAINK = 1.2; for sparse pasture
I-5
* Bounded by 1.0 - 1.2
MAINK = 1.2
* One-letter code for herd (F from fattening)
HCODE = 'F'
* Herd size (no) (INTEGER); bounded by 1 and 900
HSIZE = 50
* ITYPEF/M: Type of cattle (-) (integer)
* ITYPEF = 1: female, large breed (max weight is 800 kg)
* ITYPEF = 2: female, small breed (max weight is 600 kg)
* ITYPEM = 3: male, large breed (max weight is 1000 kg)
* ITYPEM = 4: male, small breed (max weight is 800 kg)
ITYPEF = 1
ITYPEM = 3
* Breed effect on maintenace requirements (NRC, 1996, p 115)
BE = 0.90
* Herd male/female animal ration:
RATIOMF = 1.5
* SRW: see page 116 (NRC, 1996);
* FSBW = actual final shrunk body weight at maturity
SRW = 435.
FSBW = 550.
*******************************************************************
* WBUY, WSELL and LWG: make sure that animals are at least 1 month
* on the farm, i.e.: (WSELL-WBUY)/LWG should be larger than 31 days.
*******************************************************************
* Live weight of animal at buying (kg) (real); for male calves
* (WBUYM) and female calves (WBUYF)
WBUYM = 190.
WBUYF = 160.
* Live weight of animal at selling (kg) (real); for males (WSELLM)
* and for females (WSELLF)
WSELLM = 450.
WSELLF = 400.
* Live weight gain of animals (kg/day) (real); for males (LWGM)
* and for females (LWGF)
LWGM = 0.5
LWGF = 0.4
* Mortality rate (real). Bounded by -0 and 0.99.
MRATE = 0.01
* Energy concentration of diet fed/NRC (1988) assumption (FEDNRC) with
* suggested range from 0.95 - 1.05. (bounded by 0.9-1.1) (-) (real)
FEDNRC = 1.
I.1.4 GORDMAN.DAT
************************** GORDMAN.DAT****************************
* Data file for GORDO.FOR, as in PASTOR version 2.0.
*
* Management data of engorde herd
*
* THESE DATA FOR ENGORDE HERDS IN AZ; A. NIEUWENHUYSE, APRIL 97 *
******************************************************************
******************************************************************
* 1. Definition of herd sizes that have scale-specific requirements
******************************************************************
* HRDCLAS Herd size class (number) (integer)
* HRDMIN
Minimum number of animals in herd (number) (INTEGER)
* HRDMAX
Maximum number of animals in herd (number) (INTEGER)
HRDCLAS
1
2
HRDMIN
11
31
HRDMAX
30
60
I-6
3
61
100
******************************************************************
* 2. Materials and tools
* 2.1 Corral construction per herd size class
******************************************************************
* CRDCLAS Herd size class (number) (integer)
* CROLAB
Own (farm) labour for corral construction (hour/corral) (real)
* CRMAT
Name of corral material (name) (character)
*
Select from MATER.ATF attribute file.
* CRQUAN
Quantity of corrals (number) (real)
* CRDEP
Depreciation time of the corral (year) (real)
CRCLAS
1
2
3
CROLAB
0.
0.
0.
CRMAT
'corral2'
'corral3'
'corral4'
CRQUAN
1.
1.
1.
CRDEP
25.
25.
25.
******************************************************************
* 2. Materials and tools
* 2.2 Mineral salt troughs per herd size class
******************************************************************
* MTDCLAS Herd size class (number) (integer)
* MTMAT
Name of trough (name) (character)
*
Select from MATER.ATF attribute file.
* MTQUAN
Quantity of troughs (number) (real)
* MTDEP
Depreciation time of trough (year) (real)
MTCLAS
1
2
3
MTMAT
'trough'
'trough'
'trough'
MTQUAN
4.
5.
6.
MTDEP
5.
5.
5.
******************************************************************
* 2. Materials and tools
* 2.3 Tools 1 to 3 used.
******************************************************************
* T_CLAS Herd size class (number) (integer)
* T_MAT
Name of used materials (name) (character)
*
Select from MATER.ATF attribute file.
* T_QUAN Materials quantity, in same unit as in materials file! (name) (real)
* T_DEP
Depreciation time of used materials (years) (real).
*
Note: when T_DEP is 0, the tools are yearly acquired.
* Tool1 per herd size class
T1CLAS
T1MAT
T1QUAN
1
'stools'
10.
2
'stools'
10.
3
'stools'
10.
* Tool2 per herd size class
T2CLAS
T2MAT
T2QUAN
1
'ltools'
4.
2
'ltools'
5.
3
'ltools'
8.
* Tool3 per herd size class
T3CLAS
T3MAT
T3QUAN
1
'none'
0.
2
'none'
0.
3
'none'
0.
T1DEP
5.
5.
5.
T2DEP
3.
3.
3.
T3DEP
0.
0.
0.
******************************************************************
* 3. Operations
* 3.1 Miscellaneous operations on the herd (general health care,
* presence, snakes chasing,..) per herd size class
******************************************************************
* CHCLAS Herd size class (number) (integer)
* CHLAB
Own (farm) labour use (hours/year) (real) (Put to
*
70% of cria herd)
* CHMAT
Materials used in health care (character)
*
Select from CATTLE.ATF attribute file.
* CHQUAN Quantity of materials used in health care (in same unit as in
*
CATTLE.ATF file)
CHCLAS
CHLAB
CHMAT
CHQUAN
1
168.
'emicina' 100.
I-7
2
3
210.
252.
'emicina'
'emicina'
250.
400.
******************************************************************
* 3. Operations
* 3.3. Salt application
******************************************************************
* MSNAME
Name of salt (name) (character)
*
Select from FEED.ATF attribute file.
* MSQUAN
Quantity of salt application (kg/day/AU) (real)
MSNAME
'salt'
* Labour
* CMCLAS
* MSLAB
CMCLAS
1
2
3
MSQUAN
0.05
Labour needed for application of minerals and salts
Herd size class (number) (integer)
Labour use to supply all mineral salt (hour/year) (real)
MSLAB
30.
40.
50.
******************************************************************
* 3. Operations
* 3.4. One-time inocculation/protection of bought animals
******************************************************************
* I1NAME
Name of (inocculation) material (name) (character)
*
Select from CATTLE.ATF attribute file.
* I1QUAN
Quantity (of inocculation) per application (unit) (real)
* I1LAB
Labour use per inocculation, including round-up to corral (hour/animal) (real)
I1NAME
I1QUAN
I1LAB
'none'
0.
0.
******************************************************************
* 3. Operations
* 3.5. Recurrent inocculation (I2) of all animals
******************************************************************
* I2NAME
Name of inocculation material (name) (character)
*
Select from CATTLE.ATF attribute file.
* I2UNIT
Herd unit for application, either 'animal' (per animal) or 'aunit' (animal unit)
* I2FREQ
Frequency of application (times per year per I2UNIT) (real)
* I2QUAN
Quantity of inocculation per application (unit per I2UNIT) (real)
* I2LAB
Labour use for inocculation, without round-up time to corral (hour/I2UNIT) (real)
I2NAME
I2UNIT
I2FREQ
I2QUAN
I2LAB
'dectomax'
'aunit'
3.
8.
0.1
'bacterine' 'animal'
2.
5.
0.1
'anthrax'
'animal'
2.
5.
0.1
'neguvon'
'aunit'
5.
0.005
0.07
* I2CLAS
* I2RNO
* I2RLAB
I2CLAS
1
2
3
Herd size class (number) (integer)
Number of round-ups per year for inocculation (number) (real)
Round-up time to corral for inocculation (hour/round up) (real)
I2RNO
I2RLAB
6.
0.30
6.
0.67
6.
1.00
I.2 PAST input files
I.2.1 ESTREL.DAT
******************************* ESTREL.DAT ***************************
* Pasto input data file for program PASTOF, as in PASTOR version 2.0 *
* All data are per hectare
*
* Date: 09-09-1997; Author: B.A.M. Bouman, REPOSA.
*
* Data for grass: Estrella (Cynodon nlemfuensis)
*
* Most data are based on expert knowledge, an interpretation of
*
* various literature sources, and data collected by REPOSA.
*
* Experts: A. Nieuwenhuyse, M. Ibrahim, M. Villareal Castro.
*
* Literature: separate list available.
*
***********************************************************************
I-8
* GNAME : Pasture name (character)
* GCODE : Pasture code (one letter only!) (character)
* -------------------------------------------------GNAME = 'Estrella'
GCODE = 'E'
*****************************************************************
* 1. PASTURE CHARACTERISTICS
*
*****************************************************************
* Pasture data at level of attainable production (PER MONTH):
* MONTH: Name of month (character)
* DMP:
(above-ground total) Dry matter attainable production
*
on best soils (kg/month) (real)
* CP:
Crude Protein content (%) (real)
* ME:
Metabolizable energy content (Mcal/kg) (real)
* P:
Phosphorus content (%) (real)
* K:
Potassium content (%) (real)
* -------------------------------------------------MONTH
DMP
CP
ME
P
K
'JAN'
1928.
11.0
2.3
0.35
3.7 ! Literature, expert knowledge
'FEB'
1928.
11.0
2.3
0.35
3.7 ! Total PP: 28 t/ha
'MAR'
1928.
11.0
2.3
0.35
3.7
'APR'
2468.
12.0
2.5
0.30
3.5
'MAY'
2468.
12.0
2.5
0.30
3.5
'JUN'
2468.
12.0
2.5
0.30
3.5
'JUL'
2468.
12.0
2.5
0.30
3.5
'AUG'
2468.
12.0
2.5
0.30
3.5
'SEP'
2468.
12.0
2.5
0.30
3.5
'OCT'
2468.
12.0
2.5
0.30
3.5
'NOV'
2468.
12.0
2.5
0.30
3.5
'DEC'
2468.
12.0
2.5
0.30
3.5
* Minimum nutrient and energy concentrations when no external (manure,
* fertilizer) nutrients are supplied. (minimum production level).
* CPMIN: Minimum Crude Protein content (%) (real)
* MEMIN: Minimum Metabolizable energy content (Mcal/kg) (real)
* PMIN: Minimum Phosphorus content (%) (real)
* KMIN: Minimum Potassium content (%) (real)
*-----------------------------------------------------------------* From variety of literature and expert knowledge
CPMIN = 6.
MEMIN = 1.5
PMIN = 0.12
KMIN = 1.4
*******************************************************************
* 2. PASTURE RESPONSES TO SOIL TYPES: ATTAINABLE PRODUCTION
*
********************************************************************
* Yield reduction factors
* SOILP: Soil name (character)
* RDMP:
Reduction fraction of attainable production (DMP as above)
*
due to soil limitations (-) (real)
* RDMUSE: Reduction fraction of potential dry matter on offer (DMUSE
*
see below), due to soil limitations. (-) (real)
* ---------------------------------------------------------------SOILP
RDMP
RDMUSE ! literature, expert knowledge
'SFW'
1.0
1.0
'SIW'
0.7
1.0
'SFP'
0.4
0.8
**********************************************************************
* 3. MANAGEMENT CHARACTERISTICS
*
***********************************************************************
* SRATE: Stocking rate (animal units per ha) (real)
* DMUSE: Potential fraction above-ground dry matter on offer
*
on best soils, as function of stocking rate (-) (real)
* ---------------------------------------------------------------* Note: keep 'definition' the same in all files:
SRATE
DMUSE ! Expert knowledge
1.
0.55
1.5
0.525
2.
0.50
2.5
0.475
3.
0.45
* Data for target Production level
I-9
*
*
*
*
*
*
*
*
PLEVEL: Code for technology level (2 numbers only!) (integer)
FGIFT: Fraction of fertilizer N gift to realize maximum
attainable production (-) (real)
FERTAP: Manner of fertilizer application (name) (real)
Select from options given below under 4.OPERATIONS)
WEED:
Manner of weeding (name) (character)
Select from options given below under 4.OPERATIONS)
---------------------------------------------------------------PLEVEL
FGIFT
FERTAP
WEED
! User defined
11
0.00
'manual'
'mixed'
20
0.20
'manual'
'mixed'
40
0.40
'manual'
'mixed'
60
0.60
'manual'
'mixed'
80
0.80
'manual'
'mixed'
99
1.00
'manual'
'mixed'
***********************************************************************
* 4.OPERATIONS
*
***********************************************************************
* 4.0 establishment of pasto: herbicides and fertilizer application
* Note: land preparation and sowing/planting are specified in
* section 4.1 below
* EDEP
Depreciation time of pasto (year) (real). Note: see also 4.1 below
* EWLAB/EFLAB
Farm labour use for weeding/fertilizing (hours) (real)
* EWNAME/EFNAME Herbicide/fertilizer name (name) (character);
*
to select from BIOCID.ATF and FERT attribute files.
* EWQUAN/EFQUAN Herbicide/fertilizer quantity (unit) (real)
* EWEQ/EFEQ
Herbicide/fertilizer equipment name (name) (character);
*
to select from EQUIP.ATF attribute file.
* EWQUSE/EFQUSE Herbicide/fertilizer equipment use (hours) (real)
* EWTRAC/EFTRAC Herbicide/fertilizer traction for equipment (name) (character)
*
to select from TRACTION.ATF attribute file.
* Input data: Andre Nieuwenhuyse, based on farmer inquiries in the AZ (96-97)
EDEP = 10.
EWLAB
24.0
0.0
0.0
0.0
EWNAME
'None'
'Tordon-101'
'24D'
'Round-up'
EWQUAN
0.
1.
3.
4.
EWEQ
'ksspray'
'ksspray'
'ksspray'
'ksspray'
EWQUSE
24.
0.
0.
0.
EWTRAC
'none'
'none'
'none'
'none'
EFLAB
4.0
EFNAME
'P'
EFQUAN
4.
EFEQ
'none'
EFQUSE
0.
EFTRAC
'none'
*
*
*
*
*
*
*
*
*
*
*
*
*
*
*
*
4.1 Operations that are investments and recurrent variables independent
of production level (all entries per ha)
OPER
Name of operation (name) (character)
OWNLAB Own (farm) labour use (hours) (real)
MATER
Name of used materials (name) (character)
to select from MATER.ATF attribute file.
MQUANT Materials quantity, in same unit as in materials file! (name) (real)
DEPRET Depreciation time of used materials (years) (real).
Note: when DEPRET is 0, the operation/inputs are yearly recurrent.
EQUIP
Name of equipment used (name) (character)
to select from EQUIP.ATF attribute file.
EUSE
Equipment use time (real) (hour)
TRAC
Traction used to 'pull' equipment (name) (character)
to select from TRACTION.ATF attribute file.
Input data: Andre Nieuwenhuyse, based on farmer inquiries in the AZ (96-97)
Fences: 2. Short lasting fences; dead posts
OPER
'Grass sowing'
'Labour fence estab.'
'Fences barbed wire'
'Fences dead'
'Fences nails'
'Fence maintenance'
'Various small tools'
*
*
*
*
*
OWNLAB
30.
12.
0.
0.
0.
2.
0.
MATER
'gstolE'
'none'
'bwire-Cai'
'dposts-sl'
'cramp-l'
'none'
'stools'
MQUANT
1.5
0.
350.
33.
0.5
0.
5.
DEPRET
10.
6.
6.
6.
6.
0.
5.
EQUIP
'none'
'none'
'none'
'none'
'none'
'none'
'none'
EQUSE
0.
0.
0.
0.
0.
0.
0.
4.2 Description of options for special activities: recurrent weeding.
Note that all inputs are totals over the year.
4.2.1 Weeding at attainable production level of pasture
All inputs/activities are specified for the level ofattainable production
(extension PP) and for the level of zero external inputs (extension EX)
TRAC
'none'
'none'
'none'
'none'
'none'
'none'
'none'
I-10
*
*
*
*
*
*
*
*
*
*
*
*
*
*
*
*
*
*
*
WEED
OL
C1N
C1Q
C2N
C2Q
C3N
C3Q
WEQ
WEQU
WTRA
Name of weeding manner (name) (character)
(total) Own (farm) labour use (hour/year) (real)
Name of first herbicide input (name) (character)
to select from BIOCIDE.ATF attribute file.
Quantity of first herbicide input (amount/year) (real)
Units of quantity should match those in biocide file!
Name of second herbicide input (name) (character)
to select from BIOCIDE.ATF attribute file.
Quantity of second herbicide input (amount/year) (real)
Units of quantity should match those in biocide file!
Name of third herbicide input (name) (character)
to select from BIOCIDE.ATF attribute file.
Quantity of third herbicide input (amount/year) (real)
Units of quantity should match those in biocide file!
Equipment used for weeding (name) (character)
to select from EQUIPMENT.ATF attribute file.
Use time of equipment (hours/year) (real)
Traction used to 'pull' equipment (name) (character)
to select from TRACTION.ATF attribute file.
* Input data: Andre Nieuwenhuyse, based on farmer inquiries in the AZ (96-97)
WEEDPP
'manual'
'chemic'
'mixed'
OLPP
7.0
3.5
5.0
C1NPP
'None'
'24D'
'24D'
C1QPP
0.
1.5
1.5
C2NPP
'None'
'Tordon-101'
'Tordon-101'
C2QPP
0.
0.5
0.5
C3NPP
'None'
'Combo'
'None'
C3QPP
0.
0.035
0.
WEQPP
WEQUPP
'none'
0.
'ksspray' 3.5
'ksspray' 2.0
WTRAPP
'none'
'none'
'none'
WEEDEX
'manual'
'chemic'
'mixed'
OLEX
20.
11.5
14.
C1NEX
'None'
'24D'
'24D'
C1QEX
0.
4.5
3.0
C2NEX
'None'
'Tordon-101'
'Tordon-101'
C2QEX
0.
1.5
1.0
C3NEX
'None'
'Combo'
'Combo'
C3QEX
0.
0.105
0.035
WEQEX
WEQUEX
'none'
0.
'ksspray' 10.5
'ksspray' 6.
WTRAEX
'none'
'none'
'none'
*
*
*
*
*
*
*
*
*
*
4.3 Description of options for special activities: fertilizer application.
FERTIL Manner of fertilizer application (name) (character)
FOLAB Fertilizer own (farm) labor (whether own labor is used in application)
options: 'yes' or 'no' (eg when contract labor is used)
FEQUIP Fertilizer equipment (name) (character)
to select from EQUIP.ATF attribute file.
FSSIZE Fertilizer amount that can be applied in FSADUR time (kg) (real)
FSADUR Fertilizer application duration for FSSIZE (hour) (real)
FTRAC Traction used to 'pull' equipment (name) (character)
to select from TRACTION.ATF attribute file.
* Input data: Andre Nieuwenhuyse, based on farmer inquiries in the AZ (96-97)
FERTIL
FOLAB
FEQUIP
FSSIZE
FSADUR FTRAC
'manual'
'yes'
'none'
150.
3.
'none'
I.2.2 BBRIZAN.DAT
******************************* BBRIZAN.DAT ***************************
* Pasto input data file for program PASTOF, as in PASTOR version 2.0. *
* All data are per hectare
*
* Date: 09-09-1997; Author: B.A.M. Bouman, REPOSA.
*
* Data for grass: Brachiaria brizantha
*
* Most data are based on expert knowledge, an interpretation of
*
* various literature sources, and data collected by REPOSA.
*
* Experts: A. Nieuwenhuyse, M. Ibrahim, M. Villareal Castro.
*
* Literature: separate list available.
*
***********************************************************************
* GNAME : Pasture name (character)
* GCODE : Pasture code (one letter only!) (character)
* -------------------------------------------------GNAME = 'Bbrizantha'
GCODE = 'B'
*****************************************************************
* 1. PASTURE CHARACTERISTICS
*
******************************************************************
* Pasture data at level of attainable production (PER MONTH):
* MONTH: Name of month (character)
* DMP:
(above-ground total) Dry matter attainable production
*
on the best soil (kg/month) (real)
I-11
* CP:
Crude Protein content (%) (real)
* ME:
Metabolizable energy content (Mcal/kg) (real)
* P:
Phosphorus content (%) (real)
* K:
Potassium content (%) (real)
* -------------------------------------------------MONTH
DMP
CP
ME
P
K
! data from thesis Ibrahim (1994)
'JAN'
1806.
11.0
2.3
0.35
3.7 ! Total PP: 35 t/ha
'FEB'
1806.
11.0
2.3
0.35
3.7
'MAR'
1806.
11.0
2.3
0.35
3.7
'APR'
3287.
12.0
2.5
0.3
3.5
'MAY'
3287.
12.0
2.5
0.3
3.5
'JUN'
3287.
12.0
2.5
0.3
3.5
'JUL'
3287.
12.0
2.5
0.3
3.5
'AUG'
3287.
12.0
2.5
0.3
3.5
'SEP'
3287.
12.0
2.5
0.3
3.5
'OCT'
3287.
12.0
2.5
0.3
3.5
'NOV'
3287.
12.0
2.5
0.3
3.5
'DEC'
3287.
12.0
2.5
0.3
3.5
* Minimum nutrient and energy concentrations when no external (manure,
* fertilizer) nutrients are applied (minimum production level)
* CPMIN: Minimum Crude Protein content (%) (real)
* MEMIN: Minimum Metabolizable energy content (Mcal/kg) (real)
* PMIN: Minimum Phosphorus content (%) (real)
* KMIN: Minimum Potassium content (%) (real)
*-----------------------------------------------------------------CPMIN = 6.
MEMIN = 1.5
PMIN = 0.12
KMIN = 1.4
***********************************************************************
* 2. PASTURE RESPONSES TO SOIL TYPES: ATTAINABLE PRODUCTION
*
***********************************************************************
* Yield reduction factors
* SOILP: Soil name (character)
* RDMP:
Reduction fraction of attainable production (DMP as above)
*
due to soil limitations (-) (real)
* RDMUSE: Reduction fraction of potential dry matter on offer (DMUSE
*
see below), due to soil limitations. (-) (real)
* ---------------------------------------------------------------SOILP
RDMP
RDMUSE ! Expert knowledge, various literature
'SFW'
1.0
1.0
'SIW'
0.7
1.0
**********************************************************************
* 3. MANAGEMENT CHARACTERISTICS
*
***********************************************************************
* SRATE: Stocking rate (animal units per ha) (real)
* DMUSE: Potential fraction above-ground dry matter on offer
*
on best soils, as function of stocking rate (-) (real)
* ---------------------------------------------------------------SRATE
DMUSE ! Expert knowledge
1.
0.55
1.5
0.525
2.
0.50
2.5
0.475
3.
0.45
*
*
*
*
*
*
*
*
*
Data for target Production level
PLEVEL: Code for technology level (2 numbers only!) (I)
FGIFT: Fraction of fertilizer N gift to realize maximum
attainable production (-) (real)
FERTAP: Manner of fertilizer application (name) (real)
Select from options given below under 4.OPERATIONS)
WEED:
Manner of weeding (name) (character)
Select from options given below under 4.OPERATIONS)
---------------------------------------------------------------PLEVEL
FGIFT
FERTAP
WEED
! User defined
11
0.00
'manual'
'mixed'
20
0.20
'manual'
'mixed'
40
0.40
'manual'
'mixed'
60
0.60
'manual'
'mixed'
80
0.80
'manual'
'mixed'
99
1.00
'manual'
'mixed'
I-12
***********************************************************************
* 4.OPERATIONS
*
***********************************************************************
* 4.0 establishment of pasto: herbicides and fertilizer application
* Note: land preparation and sowing/planting are specified in
* section 4.1 below
* EDEP
Depreciation time of pasto (year) (real). Note: see also 4.1 below
* EWLAB/EFLAB
Farm labour use for weeding/fertilizing (hours) (real)
* EWNAME/EFNAME Herbicide/fertilizer name (name) (character);
*
to select from BIOCID.ATF and FERT attribute files.
* EWQUAN/EFQUAN Herbicide/fertilizer quantity (unit) (real)
* EWEQ/EFEQ
Herbicide/fertilizer equipment name (name) (character);
*
to select from EQUIP.ATF attribute file.
* EWQUSE/EFQUSE Herbicide/fertilizer equipment use (hours) (real)
* EWTRAC/EFTRAC Herbicide/fertilizer traction for equipment (name) (character)
*
to select from TRACTION.ATF attribute file.
* Input data: Andre Nieuwenhuyse, based on farmer inquiries in the AZ (96-97)
EDEP = 10.
EWLAB
24.0
0.0
0.0
0.0
EWNAME
'None'
'Tordon-101'
'24D'
'Round-up'
EWQUAN
0.
1.
3.
4.
EWEQ
'ksspray'
'ksspray'
'ksspray'
'ksspray'
EWQUSE
24.
0.
0.
0.
EWTRAC
'none'
'none'
'none'
'none'
EFLAB
4.0
EFNAME
'P'
EFQUAN
4.
EFEQ
'none'
EFQUSE
0.
EFTRAC
'none'
*
*
*
*
*
*
*
*
*
*
*
*
*
*
*
*
4.1 Operations that are investments and recurrent variables independent
of production level (all entries per ha)
OPER
Name of operation (name) (character)
OWNLAB Own (farm) labour use (hours) (real)
MATER
Name of used materials (name) (character)
to select from MATER.ATF attribute file.
MQUANT Materials quantity, in same unit as in materials file! (name) (real)
DEPRET Depreciation time of used materials (years) (real).
Note: when DEPRET is 0, the operation/inputs are yearly recurrent.
EQUIP
Name of equipment used (name) (character)
to select from EQUIP.ATF attribute file.
EUSE
Equipment use time (real) (hour)
TRAC
Traction used to 'pull' equipment (name) (character)
to select from TRACTION.ATF attribute file.
Fences: 2. Short lasting fences; dead posts
land preparation by contract removed; compensated by 1.5 times seed use
* Input data: Andre Nieuwenhuyse, based on farmer inquiries in the AZ (96-97)
OPER
OWNLAB
MATER
MQUANT DEPRET
EQUIP
EQUSE
TRAC
'Grass sowing'
27.
'seedBB'
7.5
10.
'none'
0.
'none'
'Labour fence estab.' 12.
'none'
0.
6.
'none'
0.
'none'
'Fences barbed wire' 0.
'bwire-Cai' 350.
6.
'none'
0.
'none'
'Fences dead'
0.
'dposts-sl' 33.
6.
'none'
0.
'none'
'Fences nails'
0.
'cramp-l'
0.5
6.
'none'
0.
'none'
'Fence maintenance'
2.
'none'
0.
0.
'none'
0.
'none'
'Various small tools' 0.
'stools'
5.
5.
'none'
0.
'none'
*
*
*
*
*
*
*
*
*
*
*
*
*
*
*
*
*
*
*
4.2 Description of options for special activities: recurrent weeding.
Note that all inputs are totals over the year.
4.2.1 Weeding at attainable production level of pasture
All inputs/activities are specified for the level ofattainable production
(extension PP) and for the level of zero external inputs (extension EX)
WEED
Name of weeding manner (name) (character)
OL
(total) Own (farm) labour use (hour/year) (real)
C1N
Name of first herbicide input (name) (character)
to select from BIOCIDE.ATF attribute file.
C1Q
Quantity of first herbicide input (amount/year) (real)
Units of quantity should match those in biocide file!
C2N
Name of second herbicide input (name) (character)
to select from BIOCIDE.ATF attribute file.
C2Q
Quantity of second herbicide input (amount/year) (real)
Units of quantity should match those in biocide file!
C3N
Name of third herbicide input (name) (character)
to select from BIOCIDE.ATF attribute file.
C3Q
Quantity of third herbicide input (amount/year) (real)
Units of quantity should match those in biocide file!
I-13
* WEQ
*
* WEQU
* WTRA
*
Equipment used for weeding (name) (character)
to select from EQUIPMENT.ATF attribute file.
Use time of equipment (hours/year) (real)
Traction used to 'pull' equipment (name) (character)
to select from TRACTION.ATF attribute file.
* Input data: Andre Nieuwenhuyse, based on farmer inquiries in the AZ (96-97)
WEEDPP
'manual'
'chemic'
'mixed'
OLPP
3.5
1.75
2.5
C1NPP
'None'
'24D'
'24D'
C1QPP
0.
0.75
0.75
C2NPP
'None'
'Tordon-101'
'Tordon-101'
C2QPP
0.
0.25
0.25
C3NPP
'None'
'Combo'
'None'
C3QPP
0.
0.018
0.
WEQPP
WEQUPP
'none'
0.
'ksspray' 1.75
'ksspray' 1.0
WTRAPP
'none'
'none'
'none'
WEEDEX
'manual'
'chemic'
'mixed'
OLEX
20.
11.5
14.
C1NEX
'None'
'24D'
'24D'
C1QEX
0.
4.5
3.0
C2NEX
'None'
'Tordon-101'
'Tordon-101'
C2QEX
0.
1.5
1.0
C3NEX
'None'
'Combo'
'Combo'
C3QEX
0.
0.105
0.035
WEQEX
WEQUEX
'none'
0.
'ksspray' 10.5
'ksspray' 6.
WTRAEX
'none'
'none'
'none'
*
*
*
*
*
*
*
*
*
*
4.3 Description of options for special activities: fertilizer application.
FERTIL Manner of fertilizer application (name) (character)
FOLAB Fertilizer own (farm) labor (whether own labor is used in application)
options: 'yes' or 'no' (eg when contract labor is used)
FEQUIP Fertilizer equipment (name) (character)
to select from EQUIP.ATF attribute file.
FSSIZE Fertilizer amount that can be applied in FSADUR time (kg) (real)
FSADUR Fertilizer application duration for FSSIZE (hour) (real)
FTRAC Traction used to 'pull' equipment (name) (character)
to select from TRACTION.ATF attribute file.
FERTIL
'manual'
FOLAB
'yes'
FEQUIP
'none'
FSSIZE
150.
FSADUR
3.
FTRAC
'none'
I.2.3 TANNER.DAT
******************************* TANNER.DAT ****************************
* Pasto input data file for program PASTOF, as in PASTOR version 2.0 *
* All data are per hectare
*
* Date: 09-09-1997; Author: B.A.M. Bouman, REPOSA.
*
* Data for grass: Tanner (Brachiaria radicans)
*
* These grass data only for poorly drained soils!
*
* Most data are based on expert knowledge, an interpretation of
*
* various literature sources, and data collected by REPOSA.
*
* Experts: A. Nieuwenhuyse, M. Ibrahim, M. Villareal Castro.
*
* Literature: separate list available.
*
***********************************************************************
* GNAME : Pasture name (character)
* GCODE : Pasture code (one letter only!) (character)
* -------------------------------------------------GNAME = 'Tanner'
GCODE = 'T'
*******************************************************************
* 1. PASTURE CHARACTERISTICS
*
*******************************************************************
* Grass data at level of attainable production (PER MONTH):
* MONTH: Name of month (character)
* DMP:
(above-ground total) Dry matter attainable production
*
on best soils (kg/month) (real)
* CP:
Crude Protein content (%) (real)
* ME:
Metabolizable energy content (Mcal/kg) (real)
* P:
Phosphorus content (%) (real)
* K:
Potassium content (%) (real)
* -------------------------------------------------MONTH
DMP
CP
ME
P
K
! Estimated expert knowledge
'JAN'
1583.
11.0
2.3
0.35
3.7 ! various literature
'FEB'
1583.
11.0
2.3
0.35
3.7 ! Total dry matter is 19 t/ha
'MAR'
1583.
11.0
2.3
0.35
3.7
'APR'
1583.
11.0
2.3
0.35
3.7
'MAY'
1583.
11.0
2.3
0.35
3.7
'JUN'
1583.
11.0
2.3
0.35
3.7
'JUL'
1583.
11.0
2.3
0.35
3.7
'AUG'
1583.
11.0
2.3
0.35
3.7
'SEP'
1583.
11.0
2.3
0.35
3.7
I-14
'OCT'
'NOV'
'DEC'
1583.
1583.
1583.
11.0
11.0
11.0
2.3
2.3
2.3
0.35
0.35
0.35
3.7
3.7
3.7
* Minimum nutrient and energy concentrations when no external (manure,
* fertilizer) nutrients are applied (minimum production level).
* CPMIN: Minimum Crude Protein content (%) (real)
* MEMIN: Minimum Metabolizable energy content (Mcal/kg) (real)
* PMIN: Minimum Phosphorus content (%) (real)
* KMIN: Minimum Potassium content (%) (real)
*-----------------------------------------------------------------* Expert knowledge, various literature
CPMIN = 6.
MEMIN = 1.5
PMIN = 0.12
KMIN = 1.4
***********************************************************************
* 2. PASTURE RESPONSES TO SOIL TYPES: ATTAINABLE PRODUCTION
*
***********************************************************************
* Yield reduction factors
* SOILP: Soil name (character)
* RDMP:
Reduction fraction of attainable production (DMP as above)
*
due to soil limitations (-) (real)
* RDMUSE: Reduction fraction of potential dry matter on offer (DMUSE
*
see below), due to soil limitations. (-) (real)
* ---------------------------------------------------------------SOILP
RDMP
RDMUSE ! Tanner does only apply to SFP soils!
'SFP'
1.0
1.0
**********************************************************************
* 3. MANAGEMENT CHARACTERISTICS
*
***********************************************************************
* SRATE: Stocking rate (animal units per ha) (real)
* DMUSE: Potential fraction above-ground dry matter on offer
*
on best soils, as function of stocking rate (-) (real)
* ---------------------------------------------------------------SRATE
DMUSE ! Estimated expert knowledge
1.
0.55
1.5
0.525
2.
0.50
2.5
0.475
3.
0.45
*
*
*
*
*
*
*
*
*
Data for target Production level
PLEVEL: Code for technology level (2 numbers only!) (I)
FGIFT: Fraction of fertilizer N gift to realize maximum
attainable production (-) (real)
FERTAP: Manner of fertilizer application (name) (real)
Select from options given below under 4.OPERATIONS)
WEED:
Manner of weeding (name) (character)
Select from options given below under 4.OPERATIONS)
---------------------------------------------------------------PLEVEL
FGIFT
FERTAP
WEED
! User defined
11
0.00
'manual'
'mixed'
20
0.20
'manual'
'mixed'
40
0.40
'manual'
'mixed'
60
0.60
'manual'
'mixed'
80
0.80
'manual'
'mixed'
99
1.00
'manual'
'mixed'
***********************************************************************
* 4.OPERATIONS
*
***********************************************************************
* 4.0 establishment of pasto: herbicides and fertilizer application
* Note: land preparation and sowing/planting are specified in
* section 4.1 below
* EDEP
Depreciation time of pasto (year) (real). Note: see also 4.1 below
* EWLAB/EFLAB
Farm labour use for weeding/fertilizing (hours) (real)
* EWNAME/EFNAME Herbicide/fertilizer name (name) (character);
*
to select from BIOCID.ATF and FERT attribute file.
* EWQUAN/EFQUAN Herbicide/fertilizer quantity (unit) (real)
* EWEQ/EFEQ
Herbicide/fertilizer equipment name (name) (character);
*
to select from EQUIP.ATF attribute file.
* EWQUSE/EFQUSE Herbicide/fertilizer equipment use (hours) (real)
* EWTRAC/EFTRAC Herbicide/fertilizer traction for equipment (name) (character)
I-15
*
to select from TRACTION.ATF attribute file.
EDEP = 10.
* Input data: Andre Nieuwenhuyse, based on farmer inquiries in the AZ (96-97)
EWLAB EWNAME
EWQUAN
EWEQ
EWQUSE EWTRAC
24.0
'None'
0.
'ksspray'
24.
'none'
0.0
'Tordon-101'
1.
'ksspray'
0.
'none'
0.0
'24D'
3.
'ksspray'
0.
'none'
0.0
'Round-up'
4.
'ksspray'
0.
'none'
EFLAB
0.0
*
*
*
*
*
*
*
*
*
*
*
*
*
*
*
*
EFNAME
'none'
EFQUAN
0.
EFEQ
'none'
EFQUSE
0.
EFTRAC
'none'
4.1 Operations that are investments and recurrent variables independent
of production level (all entries per ha)
OPER
Name of operation (name) (character)
OWNLAB Own (farm) labour use (hours) (real)
MATER
Name of used materials (name) (character)
to select from MATER.ATF attribute file.
MQUANT Materials quantity, in same unit as in materials file! (name) (real)
DEPRET Depreciation time of used materials (years) (real).
Note: when DEPRET is 0, the operation/inputs are yearly recurrent.
EQUIP
Name of equipment used (name) (character)
to select from EQUIP.ATF attribute file.
EUSE
Equipment use time (real) (hour)
TRAC
Traction used to 'pull' equipment (name) (character)
to select from TRACTION.ATF attribute file.
Fences: 2. Short lasting fences; dead posts
land preparation by contract removed; compensated with 1.5 times stolon use
* Input data: Andre Nieuwenhuyse, based on farmer inquiries in the AZ (96-97)
* Fences: 2. Short lasting fences; dead posts
OPER
OWNLAB
MATER
MQUANT DEPRET
EQUIP
EQUSE
TRAC
'Grass sowing'
30.
'gstolT'
1.5
10.
'none'
0.
'none'
'Labour fence estab.' 12.
'none'
0.
6.
'none'
0.
'none'
'Fences barbed wire' 0.
'bwire-Cai' 350.
6.
'none'
0.
'none'
'Fences dead'
0.
'dposts-sl' 33.
6.
'none'
0.
'none'
'Fences nails'
0.
'cramp-l'
0.5
6.
'none'
0.
'none'
'Fence maintenance'
2.
'none'
0.
0.
'none'
0.
'none'
'Various small tools' 0.
'stools'
5.
5.
'none'
0.
'none'
*
*
*
*
*
*
*
*
*
*
*
*
*
*
*
*
*
*
*
*
*
*
*
*
4.2 Description of options for special activities: recurrent weeding.
Note that all inputs are totals over the year.
4.2.1 Weeding at attainable production level of pasture
All inputs/activities are specified for the level ofattainable production
(extension PP) and for the level of zero external inputs (extension EX)
WEED
Name of weeding manner (name) (character)
OL
(total) Own (farm) labour use (hour/year) (real)
C1N
Name of first herbicide input (name) (character)
to select from BIOCIDE.ATF attribute file.
C1Q
Quantity of first herbicide input (amount/year) (real)
Units of quantity should match those in biocide file!
C2N
Name of second herbicide input (name) (character)
to select from BIOCIDE.ATF attribute file.
C2Q
Quantity of second herbicide input (amount/year) (real)
Units of quantity should match those in biocide file!
C3N
Name of third herbicide input (name) (character)
to select from BIOCIDE.ATF attribute file.
C3Q
Quantity of third herbicide input (amount/year) (real)
Units of quantity should match those in biocide file!
WEQ
Equipment used for weeding (name) (character)
to select from EQUIPMENT.ATF attribute file.
WEQU
Use time of equipment (hours/year) (real)
WTRA
Traction used to 'pull' equipment (name) (character)
to select from TRACTION.ATF attribute file.
* Input data: Andre Nieuwenhuyse, based on farmer inquiries in the AZ (96-97)
WEEDPP
'manual'
'chemic'
'mixed'
OLPP
7.0
3.5
5.0
C1NPP
'None'
'24D'
'24D'
C1QPP
0.
1.5
1.5
C2NPP
'None'
'Tordon-101'
'Tordon-101'
C2QPP
0.
0.5
0.5
C3NPP
'None'
'Combo'
'Combo'
C3QPP
0.
0.035
0.
WEQPP
WEQUPP
'none'
0.
'ksspray' 3.5
'ksspray' 2.0
WTRAPP
'none'
'none'
'none'
WEEDEX
'manual'
'chemic'
'mixed'
OLEX
15.
7.0
11.5
C1NEX
'None'
'24D'
'24D'
C1QEX
0.
3.0
1.5
C2NEX
'None'
'Tordon-101'
'Tordon-101'
C2QEX
0.
1.0
0.5
C3NEX
'None'
'Combo'
'Combo'
C3QEX
0.
0.070
0.035
WEQEX
WEQUEX
'none'
0.
'ksspray' 7.0
'ksspray' 3.5
WTRAEX
'none'
'none'
'none'
I-16
*
*
*
*
*
*
*
*
*
*
4.3 Description of options for special activities: fertilizer application.
FERTIL Manner of fertilizer application (name) (character)
FOLAB Fertilizer own (farm) labor (whether own labor is used in application)
options: 'yes' or 'no' (eg when contract labor is used)
FEQUIP Fertilizer equipment (name) (character)
to select from EQUIP.ATF attribute file.
FSSIZE Fertilizer amount that can be applied in FSADUR time (kg) (real)
FSADUR Fertilizer application duration for FSSIZE (hour) (real)
FTRAC Traction used to 'pull' equipment (name) (character)
to select from TRACTION.ATF attribute file.
* Input data: Andre Nieuwenhuyse, based on farmer inquiries in the AZ (96-97)
FERTIL
FOLAB
FEQUIP
FSSIZE
FSADUR FTRAC
'manual'
'yes'
'none'
150.
3.
'none'
I.2.4 NATURAL.DAT
******************************* NATURAL.DAT ***************************
* Pasto input data file for program PASTOU, as in PASTOR version 2.0 *
* All data are per hectare
*
* Date: 09-09-1997; Author: B.A.M. Bouman, REPOSA.
*
* Data for grass: Some kind of 'natural/improved grass' mixture that *
*
is representative for the various soil types.
*
* Most data are based on expert knowledge, an interpretation of
*
* various literature sources, and data collected by REPOSA.
*
* Experts: A. Nieuwenhuyse, M. Ibrahim, M. Villareal Castro.
*
* Literature: separate list available.
*
***********************************************************************
* GNAME : Pasture name (character)
* GCODE : Pasture code (one letter only!) (character)
* -------------------------------------------------GNAME = 'Natural'
GCODE = 'N'
***********************************************************************
* 1. PASTURE CHARACTERISTICS
*
***********************************************************************
* Grass data at level of attainable production (PER MONTH):
* MONTH: Name of month (character)
* DMP:
(above-ground total) Dry matter attainable production
*
(kg/month) (real)
* CP:
Crude Protein content (%) (real)
* ME:
Metabolizable energy content (Mcal/kg) (real)
* P:
Phosphorus content (%) (real)
* K:
Potassium content (%) (real)
* -------------------------------------------------* Data for attainable production estimated as two times that of current
MONTH
DMP
CP
ME
P
K
! data from various sources
'JAN'
1087.
10.0
2.1
0.15
1.5 ! literature, expert-knowledge
'FEB'
1087.
10.0
2.1
0.15
1.5 ! Total attain. prod: 15 t/ha/y!
'MAR'
1087.
10.0
2.1
0.15
1.5 ! Villareal pers. com.
'APR'
1304.
10.0
2.1
0.15
1.5
'MAY'
1304.
10.0
2.1
0.15
1.5
'JUN'
1304.
10.0
2.1
0.15
1.5
'JUL'
1304.
10.0
2.1
0.15
1.5
'AUG'
1304.
10.0
2.1
0.15
1.5
'SEP'
1304.
10.0
2.1
0.15
1.5
'OCT'
1304.
10.0
2.1
0.15
1.5
'NOV'
1304.
10.0
2.1
0.15
1.5
'DEC'
1304.
10.0
2.1
0.15
1.5
***********************************************************************
* 2. PASTURE RESPONSES TO SOIL TYPES: ATTAINABLE PRODUCTION
*
***********************************************************************
* Yield reduction factors
* SOILP: Soil name (character)
* RDMP:
Reduction fraction of attainable production (DMP as above)
*
due to soil limitations (-) (real)
* RDMUSE: Reduction fraction of potential dry matter on offer (DMUSE
*
see below), due to soil limitations. (-) (real)
I-17
* NSUPL: Supply of nitrogen from legumes that may be present
*
e.g. as in grass-legume mixtures. (kg/ha) (real)
* ---------------------------------------------------------------SOILP
RDMP
RDMUSE NSUPL ! Estimates from expert knowledge
'SFW'
1.0
1.0
0.
'SIW'
0.8
1.0
0.
'SFP'
1.0
0.8
0.
**********************************************************************
* 3. MANAGEMENT CHARACTERISTICS
*
***********************************************************************
* SRATE: Stocking rate (animal units per ha) (real)
* DMUSE: Potential fraction above-ground dry matter on offer
*
on best soils, as function of stocking rate (-) (real)
* ---------------------------------------------------------------SRATE
DMUSE ! estimated from expert knowledge
1.
0.55
1.5
0.525
2.
0.50
2.5
0.475
3.
0.45
*
*
*
*
*
Data for manner of herbicide control (parallel to production level)
PLEVEL: Code for technology level (2 numbers only!) (I)
WEED:
Manner of weeding (name) (character)
Select from options given below under 4.OPERATIONS)
---------------------------------------------------------------PLEVEL
WEED ! User supplied
11
'mixed'
***********************************************************************
* 4.OPERATIONS
*
***********************************************************************
* 4.0 establishment of pasto: herbicides and fertilizer application
* Note: land preparation and sowing/planting are specified in
* section 4.1 below
* EDEP
Depreciation time of pasto (year) (real). Note: see also 4.1 below
* EWLAB/EFLAB
Farm labour use for weeding/fertilizing (hours) (real)
* EWNAME/EFNAME Herbicide/fertilizer name (name) (character);
*
to select from BIOCID.ATF and FERT attribute files.
* EWQUAN/EFQUAN Herbicide/fertilizer quantity (unit) (real)
* EWEQ/EFEQ
Herbicide/fertilizer equipment name (name) (character);
*
to select from EQUIP.ATF attribute file.
* EWQUSE/EFQUSE Herbicide/fertilizer equipment use (hours) (real)
* EWTRAC/EFTRAC Herbicide/fertilizer traction for equipment (name) (character)
*
to select from TRACTION.ATF attribute file.
EDEP = 100.
! natural grass is 'forever'
EWLAB EWNAME
0.0
'None'
EWQUAN
0.
EFLAB
0.0
EFQUAN
0.
*
*
*
*
*
*
*
*
*
*
*
*
*
*
EFNAME
'none'
EWEQ
'none'
EFEQ
'none'
EWQUSE
0.
EWTRAC
'none'
EFQUSE
0.
EFTRAC
'none'
4.1 Operations that are investments and recurrent variables independent
of production level (all entries per ha)
OPER
Name of operation (name) (character)
OWNLAB Own (farm) labour use (hours) (real)
MATER
Name of used materials (name) (character)
to select from MATER.ATF attribute file.
MQUANT Materials quantity, in same unit as in materials file! (name) (real)
DEPRET Depreciation time of used materials (years) (real).
Note: when DEPRET is 0, the operation/inputs are yearly recurrent.
EQUIP
Name of equipment used (name) (character)
to select from EQUIP.ATF attribute file.
EUSE
Equipment use time (real) (hour)
TRAC
Traction used to 'pull' equipment (name) (character)
to select from TRACTION.ATF attribute file.
* Input data: Andre Nieuwenhuyse, based on farmer inquiries in the AZ (96-97)
* Fences: 2. Short lasting fences; dead posts
OPER
OWNLAB
MATER
MQUANT DEPRET
EQUIP
EQUSE
TRAC
'Labour fence estab.' 12.
'none'
0.
6.
'none'
0.
'none'
'Fences barbed wire' 0.
'bwire-Cai' 350.
6.
'none'
0.
'none'
'Fences dead'
0.
'dposts-sl' 33.
6.
'none'
0.
'none'
I-18
'Fences nails'
0.
'Fence maintenance'
2.
'Various small tools' 0.
*
*
*
*
*
*
*
*
*
*
*
*
*
*
*
*
*
*
*
*
*
*
'cramp-l'
'none'
'stools'
0.5
0.
5.
6.
0.
5.
'none'
'none'
'none'
0.
0.
0.
'none'
'none'
'none'
4.2 Description of options for special activities: recurrent weeding.
Note that all inputs are totals over the year.
4.2.1 Weeding of pasture
WEED
Name of weeding manner (name) (character)
OL
(total) Own (farm) labour use (hour/year) (real)
C1N
Name of first herbicide input (name) (character)
to select from BIOCIDE.ATF attribute file.
C1Q
Quantity of first herbicide input (amount/year) (real)
Units of quantity should match those in biocide file!
C2N
Name of second herbicide input (name) (character)
to select from BIOCIDE.ATF attribute file.
C2Q
Quantity of second herbicide input (amount/year) (real)
Units of quantity should match those in biocide file!
C3N
Name of third herbicide input (name) (character)
to select from BIOCIDE.ATF attribute file.
C3Q
Quantity of third herbicide input (amount/year) (real)
Units of quantity should match those in biocide file!
WEQ
Equipment used for weeding (name) (character)
to select from EQUIPMENT.ATF attribute file.
WEQU
Use time of equipment (hours/year) (real)
WTRA
Traction used to 'pull' equipment (name) (character)
to select from TRACTION.ATF attribute file.
* Input data: Andre Nieuwenhuyse, based on farmer inquiries in the AZ (96-97)
WEEDN
'manual'
'chemic'
'mixed'
OLWEED C1N
10.
'None'
6.0
'24D'
7.0
'24D'
C1Q
0.
3.0
1.5
C2N
'None'
'Tordon-101'
'Tordon-101'
C2Q
0.
1.0
0.5
C3N
'None'
'Combo'
'Combo'
C3Q
0.
0.035
0.035
WEQ
WEQU
'none'
0.
'ksspray' 6.0
'ksspray' 3.5
WTRA
'none'
'none'
'none'
I.2.5 BPINTOI.DAT
******************************* BPINTOI.DAT ***************************
* Pasto input data file for program PASTO, as in PASTOR version 2.0
*
* All data are per hectare
*
* Date: 09-09-1997; Author: B.A.M. Bouman, REPOSA.
*
* Data for grass: Mixture of Brachiaria brizantha with Arachis pintoi *
*
Data taken from Ibrahim, 1994.
*
* Most data are based on expert knowledge, an interpretation of
*
* various literature sources, and data collected by REPOSA.
*
* Experts: A. Nieuwenhuyse, M. Ibrahim, M. Villareal Castro.
*
* Literature: separate list available.
*
***********************************************************************
* GNAME : Pasture name (character)
* GCODE : Pasture code (one letter only!) (character)
* -------------------------------------------------GNAME = 'Bpintoi'
GCODE = 'I'
***********************************************************************
* 1. PASTURE CHARACTERISTICS
*
***********************************************************************
* Grass data at level of attainable production (PER MONTH):
* MONTH: Name of month (character)
* DMP:
(above-ground total) Dry matter attainable production
*
on best soils (kg/month) (real)
* CP:
Crude Protein content (%) (real)
* ME:
Metabolizable energy content (Mcal/kg) (real)
* P:
Phosphorus content (%) (real)
* K:
Potassium content (%) (real)
* -------------------------------------------------MONTH
DMP
CP
ME
P
K
'JAN'
1024.
9.0
2.0
0.20
2.5 ! Data M. Ibrahim thesis, 1994
'FEB'
1024.
9.0
2.0
0.20
2.5 ! Total production 20 t/ha
'MAR'
1024.
9.0
2.0
0.20
2.5 ! Data 'CIAT's contribution'
'APR'
1862.
11.0
2.1
0.20
2.5
'MAY'
1862.
11.0
2.1
0.20
2.5
'JUN'
1862.
11.0
2.1
0.20
2.5
'JUL'
1862.
11.0
2.1
0.20
2.5
I-19
'AUG'
'SEP'
'OCT'
'NOV'
'DEC'
1862.
1862.
1862.
1862.
1862.
11.0
11.0
11.0
11.0
11.0
2.1
2.1
2.1
2.1
2.1
0.20
0.20
0.20
0.20
0.20
2.5
2.5
2.5
2.5
2.5
***********************************************************************
* 2. PASTURE RESPONSES TO SOIL TYPES: ATTAINABLE PRODUCTION
*
***********************************************************************
* Yield reduction factors
* SOILP: Soil name (character)
* RDMP:
Reduction fraction of attainable production (DMP as above)
*
due to soil limitations (-) (real)
* RDMUSE: Reduction fraction of potential dry matter on offer (DMUSE
*
see below), due to soil limitations. (-) (real)
* NSUPL: Supply of nitrogen from legumes that may be present
*
e.g. as in grass-legume mixtures. (kg/ha) (real)
* ---------------------------------------------------------------SOILP
RDMP
RDMUSE NSUPL ! Expert knowledge, Ibrahim thesis 1994
'SFW'
1.0
1.0
150. ! 'CIAT's contribution' for NSUPL, p.124
'SIW'
0.66
1.0
100.
**********************************************************************
* 3. MANAGEMENT CHARACTERISTICS
*
***********************************************************************
* SRATE: Stocking rate (animal units per ha) (real)
* DMUSE: Potential fraction above-ground dry matter on offer
*
on best soils, as function of stocking rate (-) (real)
* ---------------------------------------------------------------SRATE
DMUSE ! Expert estimates
1.
0.55
1.5
0.525
2.
0.50
2.5
0.475
3.
0.45
*
*
*
*
*
Data for manner of herbicide control (parallel to production level)
PLEVEL: Code for technology level (2 numbers only!) (I)
WEED:
Manner of weeding (name) (character)
Select from options given below under 4.OPERATIONS)
---------------------------------------------------------------PLEVEL
WEED
11
'manual'
***********************************************************************
* 4.OPERATIONS
*
***********************************************************************
* 4.0 establishment of pasto: herbicides and fertilizer application
* Note: land preparation and sowing/planting are specified in
* section 4.1 below
* EDEP
Depreciation time of pasto (year) (real). Note: see also 4.1 below
* EWLAB/EFLAB
Farm labour use for weeding/fertilizing (hours) (real)
* EWNAME/EFNAME Herbicide/fertilizer name (name) (character)
* EWQUAN/EFQUAN Herbicide/fertilizer quantity (unit) (real)
* EWEQ/EFEQ
Herbicide/fertilizer equipment name (name) (character)
* EWQUSE/EFQUSE Herbicide/fertilizer equipment use (hours) (real)
* EWTRAC/EFTRAC Herbicide/fertilizer traction for equipment (name) (character)
EDEP = 10.
* Input data: Andre Nieuwenhuyse, based on farmer inquiries in the AZ (96-97)
EWLAB EWNAME
EWQUAN
EWEQ
EWQUSE EWTRAC
24.0
'None'
0.
'ksspray'
24.
'none'
0.0
'Tordon-101'
1.
'ksspray'
0.
'none'
0.0
'24D'
3.
'ksspray'
0.
'none'
0.0
'Round-up'
4.
'ksspray'
0.
'none'
EFLAB
4.0
*
*
*
*
*
*
EFNAME
'P'
EFQUAN
4.
EFEQ
'none'
EFQUSE
0.
EFTRAC
'none'
4.1 Operations that are investments and recurrent variables independent
of production level (all entries per ha)
OPER
Name of operation (name) (character)
OWNLAB Own (farm) labour use (hours) (real)
MATER
Name of used materials (name) (character)
MQUANT Materials quantity, in same unit as in materials file! (name) (real)
I-20
*
*
*
*
*
DEPRET
EQUIP
EUSE
TRAC
Depreciation time of used materials (years) (real).
Note: when DEPRET is 0, the operation/inputs are yearly recurrent.
Name of equipment used (name) (character)
Equipment use time (real) (hour)
Traction used to 'pull' equipment (name) (character)
* Input data: Andre Nieuwenhuyse, based on farmer inquiries in the AZ (96-97)
* Fences: 2. Short lasting fences; dead posts
OPER
OWNLAB
MATER
MQUANT DEPRET
EQUIP
EQUSE
TRAC
'Grass sowing'
27.
'seedBB'
7.5
10.
'none'
0.
'none'
'Arachis planting'
18.
'stolAP'
1.5
10.
'none'
0.
'none'
'Labour fence estab.' 12.
'none'
0.
6.
'none'
0.
'none'
'Fences barbed wire' 0.
'bwire-Cai' 350.
6.
'none'
0.
'none'
'Fences dead'
0.
'dposts-sl' 33.
6.
'none'
0.
'none'
'Fences nails'
0.
'cramp-l'
0.5
6.
'none'
0.
'none'
'Fence maintenance'
2.
'none'
0.
0.
'none'
0.
'none'
'Various small tools' 0.
'stools'
5.
5.
'none'
0.
'none'
* Original:
*'Land preparation'
*'Grass sowing'
*
*
*
*
*
*
*
*
*
*
*
*
*
*
*
*
*
0.
18.
'contract1'
'seedBB'
1.
5.
10.
10.
'none'
'none'
0.
0.
'none'
'none'
4.2 Description of options for special activities: recurrent weeding.
Note that all inputs are totals over the year.
4.2.1 Weeding of pasture
WEEDN Name of weeding manner (name) (character)
OL
(total) Own (farm) labour use (hour/year) (real)
C1N
Name of first herbicide input (name) (character)
C1Q
Quantity of first herbicide input (amount/year) (real)
Units of quantity should match those in biocide file!
C2N
Name of second herbicide input (name) (character)
C2Q
Quantity of second herbicide input (amount/year) (real)
Units of quantity should match those in biocide file!
C3N
Name of third herbicide input (name) (character)
C3Q
Quantity of third herbicide input (amount/year) (real)
Units of quantity should match those in biocide file!
WEQ
Equipment used for weeding (name) (character)
WEQU
Use time of equipment (hours/year) (real)
WTRA
Traction used to 'pull' equipment (name) (character)
* Input data: Andre Nieuwenhuyse, based on farmer inquiries in the AZ (96-97)
* Three times a year, five hours chapia
WEEDN
'manual'
OLWEED
15.
C1N
'None'
C1Q
0.
C2N
'None'
C2Q
0.
C3N
'None'
C3Q
0.
WEQ
'none'
I.3 Other input files
I.3.1 SOIL.DAT
*************************** SOIL.DAT *****************************
* Soil input data file, for PASTOR version 2.0
*
******************************************************************
******************************************************************
* NON SOIL TYPE SPECIFIC
*
******************************************************************
* Atmospheric nitrogen deposition (kg/ha/y) (real)
AND = 1.7
* Atmospheric phosphorus deposition (kg/ha/y) (real)
APD = 0.2
* Atmospheric potassium deposition (kg/ha/y) (real)
AKD = 5.4
* Annual input of phosphorus by weathering (kg/ha/y) (real)
WP = 0.
* Annual input of potassium by weathering (kg/ha/y) (real)
WEQU
0.
WTRA
'none'
I-21
WK = 0.
******************************************************************
* SOIL TYPE SPECIFIC
*
******************************************************************
* SOILS = soil type (name) (character)
* NFIX = Nitrogen fixation by micro-organisms (kg/ha/y) (real)
* ULLMP = Urinary leaching loss fraction through macropores (-) (real)
* ULL
= Urinary leaching loss fraction (-) (real)
* UVL
= Urinary volatalization loss fraction (-) (real)
* UDL
= Urinary (de)nitrification loss fraction (-) (real)
*
i.e.: NO, N2O and N2 loss
* FLL
= Fecal leaching loss fraction (-) (real)
* FVL
= Fecal volatalization loss fraction (-) (real)
* FDL
= Fecal denitrification loss fraction (-) (real)
* FELLN = Fertilizer leaching loss fraction nitrogen (-) (real)
* FELLK = Fertilizer leaching loss fraction potassium (-) (real)
* FEVLN = Fertilizer volatalization loss fraction nitrogen (-) (real)
* FEDLN = Fertilizer denitrification loss fraction nitrogen (-) (real)
* FPXL = Phosphorus fixation fraction, for feces, urine and
*
fertilizer (-) (real)
SOILS
'SFW'
'SIW'
'SFP'
NFIX
6.0
3.0
1.0
ULLMP
0.30
0.30
0.30
ULL
0.20
0.20
0.15
FELLN
0.40
0.45
0.40
FEVLN
0.13
0.13
0.15
FEDLN
0.02
0.02
0.10
FELLK
0.40
0.45
0.40
UVL
0.15
0.15
0.25
UDL
0.05
0.05
0.15
FLL
0.60
0.60
0.40
FVL
0.05
0.05
0.15
FDL
0.05
0.05
0.15
FPXL
0.0
0.0
0.0
* 'Extra'loss of fertizer nitrogen (to be divided over leaching and
* denitrification), as multiplication factor on calculated gross
* N fertilizer gift (from loss fractions as above).
* Give list as function of nett fertilizer gifts (kg/ha)-fraction
EXLOST =
0.0
1.0
250. 1.0
275. 1.0
300. 1.0
400. 1.0
425. 1.1
450. 1.2
475. 1.3
1000. 1.5
* Fraction of 'extra' loss distribution over leaching and denitrification
* LLEX = fraction to extra leaching loss (1-LLEX goes to denitr. loss)
LLEX = 0.5
I.3.2 SITE.DAT
*************************** SITE.DAT ****************************
* Site information; for PASTOR version 2.0
*
*****************************************************************
* Interest rate for cost calculations (%/year) (real)
* Real interest rate (mean bank interest rate corrected for inflation),
* mean of 1991-1996. Note RINT should be ò 0.
RINT = 7.
* Hours of labour in one day (real) (h/d) Should be: 0 < DAYHR < 24.
DAYHR = 8.
******************************************************************
* Characteristics per soil type
******************************************************************
* ANMINE allowable nitrogen mining (kg/ha) (real) (ò 0)
* AKMINE allowable potassium mining (kg/ha) (real) (ò 0)
* APMINE: allowable phophorus mining (kg/ha) (real) (ò 0)
I-22
SOIL
'SFW'
'SIW'
'SFP'
ANMINE
0.
0.
0.
AKMINE
0.
0.
0.
APMINE
0.
0.
0.
I.3.3 FEEDS.DAT
**************************** FEEDS.DAT ********************************
* Feed supplement input file
* Labour use calculated bu Nieuwenhuyse, april 1997.
* For PASTOR version 2.0
***********************************************************************
* SFNAME Supplementary feed name (name) (character)
* LABUSE Labor use to deliver supplementary feed on farm (hr/kg) (real)
* EQUIP
Equipment used to deliver suppl. feed on farm (name) (character)
* EQUSE
Time use of equipment (hr/kg)
* TRAC
Traction used to 'pull' equipment (name) (character)
SFNAME
'molasse'
'banana'
'conc1'
'conc2'
'p20'
LABUSE
0.01
0.003
0.007
0.007
0.0
EQUIP
'none'
'none'
'none'
'none'
'none'
EQUSE
'none'
'none'
'none'
'none'
'none'
TRAC
'none'
'none'
'none'
'none'
'none'
I-23
I-24
Appendix II: PASTOR attribute files
II.1 Materials
**************************** MATER.ATF *****************************
* Material attribute file, for PASTOR version 2.0
* Updated by A.Nieuwenhuyse April 1997
********************************************************************
* MCODE
Material code (number) (real)
* MDESCR Material description (name) (character)
* MNAME
Material name (name) (character)
* MUNIT
Materials unit for MPRICE (name) (character)
*
('kg', 'li', 'no', 'm')
* MPRICE Materials price, per unit as in MUNIT (colon) (real)
* MPY
Year of material price (number) (real)
* MPM
Month of material price (number) (real)
MCODE
0000.00
0000.00
0000.00
0000.00
0000.00
0000.00
0000.00
0000.00
0000.00
0000.00
0000.00
0000.00
0000.00
0000.00
0000.00
0000.00
0000.00
0000.00
0000.00
0000.00
0000.00
0000.00
0000.00
0000.00
0000.00
0000.00
0000.00
0000.00
MDESCR
'No material'
'Contract land prep pasto'
'Grass stolons Estrella'
'Grass stolons Tanner'
'Stolons Arachis pintoi'
'Stumps Poro'
'Grass seed Brachiaria br.'
'Grass seed Ratana'
'Living fence posts'
'Short-living dead fence post'
'Long-living dead fence post'
'Barbed wire Caiman'
'Barbed wire Cabra'
'Barbed wire Moto'
'Cramps-small'
'Cramps-large'
'Small tools (saw,mach,..)'
'Medium tools'
'Large tools (spade, ..)'
'Contr. corral 1-10 animals roof'
'Contr. corral 10-30 animals'
'Contr. corral 10-30 animals roof'
'Contr. corral 30-60 animals'
'Contr. corral 30-60 animals roof'
'Contr. corral 60-100 animals'
'Contr. corral 60-100 animals roof'
'Salt trough'
'Salt trough roof'
MNAME
'none'
'contract1'
'gstolE'
'gstolT'
'stolAP'
'stumP'
'seedBB'
'seedR'
'lposts'
'dposts-sl'
'dposts-ll'
'bwire-Cai'
'bwire-Cab'
'bwire-Mot'
'cramp-s'
'cramp-l'
'stools'
'mtools'
'ltools'
'corral1'
'corral2'
'corral2r'
'corral3'
'corral3r'
'corral4'
'corral4r'
'trough'
'troughr'
MUNIT
'no'
'no'
'ha'
'ha'
'ha'
'no'
'kg'
'kg'
'no'
'no'
'no'
'm'
'm'
'm'
'kg'
'kg'
'no'
'no'
'no'
'no'
'no'
'no'
'no'
'no'
'no'
'no'
'no'
'no'
MPRICE
0.
20000.
3000.
3000.
6000.
25.
3500.
500.
25.
300.
800.
12.1
21.7
14.1
425.
230.
500.
750.
1500.
77000.
193900.
353150.
338250.
661880.
463500.
907500.
2300.
6000.
II.2 Equipment
********************** EQUIP.ATF ********************************
* Equipment attribute file, for PASTOR version 2.0
*****************************************************************
* ECODE
Equipment code (number) (real)
* EDESCR Equipment description (name) (character)
* ENAME
Equipment name (name) (character)
* EPRICE Equipments depreciation plus use, or rental price, per hour
*
(colon/hour) (real)
* EPY
Year of equipment price date (number) (real)
* EPM
Month of equipment price date (number) (real)
ECODE
0000.00
0000.00
7020.00
7030.00
EDESCR
'No equipment'
'Fertilizer spreader'
'Moulboard plough'
'Disc plough, one way'
ENAME
'none'
'spreader'
'mplough'
'dplough'
EPRICE
0.
0.
1500.
1500.
EPY
EPM
1997. 03.
1997. 03.
1991. 06.
1991. 06.
MPY
1991.
1997.
1997.
1997.
1997.
1997.
1997.
1997.
1996.
1996.
1996.
1997.
1997.
1997.
1997.
1997.
1996.
1996.
1996.
1997.
1997.
1997.
1997.
1997.
1997.
1997.
1996.
1997.
MPM
06.
04.
04.
04.
04.
04.
04.
04.
06.
06.
06.
04.
04.
04.
04.
04.
06.
06.
06.
04.
03.
03.
03.
03.
04.
04.
06.
06.
I-25
7040.00
7210.00
7320.00
0000.00
7330.00
8810.00
0000.00
'Disc harrow'
'Row seeder'
'Motor sprayer rental'
'Motor sprayer own'
'Knapsack sprayer'
'Chainsaw rental'
'Chainsaw own'
'dharrow'
'rseeder'
'mspray-r'
'mspray-o'
'ksspray'
'csaw-r'
'csaw-o'
1500.
1500.
1200.
800.
30.
1500.
900.
1991.
1991.
1997.
1997.
1997.
1997.
1997.
06.
06.
03.
03.
03.
03.
03.
II.3 Traction
************************* TRACTION.ATF ***************************
* Traction attribute file, fpr PASTOR version 2.0
*
******************************************************************
* TCODE
Traction code (number) (real)
* TDESCR Traction description (name) (character)
* TNAME
Traction name (name) (character)
* TPRICE Traction depreciation or rental price, per hour
*
(colon/hour) (real)
* TPY
Year of traction price (number) (real)
* TPM
Month of traction price (number) (real)
TCODE
0000.00
5011.00
6100.00
6200.00
6300.00
6310.00
6910.00
TDESCR
'No traction'
'Draugh cattle span'
'Field tractor 15-40 hp'
'Field tractor 40-100 hp'
'Field tractor > 100 hp'
'Crawler tractor'
'Airplane'
TNAME
'none'
'draught1'
'tractor1'
'tractor2'
'tractor3'
'tractor4'
'plane'
TPRICE
0.
500.
1700.
2300.
3000.
4000.
5080.
TPY
1997.
1991.
1991.
1991.
1991.
1991.
1991.
TPM
03.
06.
06.
06.
06.
06.
06.
II.4 Fertiliser
**************************** FERT.ATF *****************************
* Fertilizer attribute file, for PASTOR version 2.0
*
* Note: Nirtogen, Phosphorus and Potassium are obligated entries *
*
MNGIFT is obligated entry
*
*******************************************************************
* MNGIFT = Maximum nutrient gift in one application (kg) (real)
*
(note: nutrient, and not gross fertilizer product)
MNGIFT = 50.
*
*
*
*
*
*
*
FCODE
FDESCR
NNAME
NCNT
NPRICE
NPY
NPM
FCODE
0000.00
0000.00
0000.00
0000.00
Fertilizer code (number) (real)
Fertilizer description (name) (character)
Nutrient name in fertilizer (name) (character)
(mean) Nutrient concentration in fertilizer (-) (real)
(mean) Nutrient price (colon) (real)
Year of nutrient price (number) (real)
Month of nurteint price (number) (real)
FDESCR
'none'
'N-mean'
'P-mean'
'K-mean'
NNAME
'none'
'N'
'P'
'K'
NCNT
1.00
0.33
0.33
0.33
NPRICE
000.
180.
390.
128.
NPY
1997.
1997.
1997.
1997.
NPM
03.
03.
03.
03.
II.5 Pesticide
******************************* BIOCID.ATF *********************************
* Biocide attribute file, for PASTOR version 2.0
* Date updated by A. Nieuwenhuyse March 1997 (toxic data for combo have to be checked)
****************************************************************************
* BCODE
Biocide code (number) (real)
I-26
*
*
*
*
*
*
*
*
*
*
BNAME
BPRICE
BPY
BPM
BUNIT
AI
WHO
DUR
SOL
COMNAME
BCODE
0000.000
0000.000
0000.000
1600.000
1609.904
1600.202
1600.202
1600.204
1600.204
1601.001
1601.201
1601.201
1600.206
1600.208
1600.209
1601.002
1600.212
1600.215
1601.005
1600.217
1601.006
1611.000
1610.000
1611.001
1614.200
1614.201
1610.001
1610.006
1610.904
1610.905
1610.007
1621.000
1620.001
1620.302
1621.401
1620.004
1620.005
1620.006
1620.007
1621.001
1623.003
1621.003
1623.004
1621.100
1621.402
Biocide name (name) (character)
Biocide price per unit as in BUNIT (colon) (real)
Year of biocide price (number) (real)
Month of biocide price (number) (real)
Biocide unit (name) (character] [kg' or 'li')
Active ingredient fraction of main biocide (-) (real)
WHO code for severity of main biocide (name) (character)
Duration of main biocide in days of residual action (d) (real)
Solubility of main biocide (g/l) (real)
Common name of biocide in product (name) (character)
BNAME
'None'
'none'
'Combo'
'Basagram'
'Banvel-S'
'Diuron-kg'
'Diuron-li'
'Karmex'
'Karmex-kg'
'Gardoprim'
'Gesaprim'
'Gesaprim-kg'
'Goal-2EC'
'Gramoxone'
'Gramuron'
'Hedonal'
'Lazo-EC(=Lasso)'
'Prowl-500E'
'24D'
'Round-up'
'Tordon-101'
'Afungil-50PM'
'Antracol'
'Benlate'
'Daconil-500'
'Daconil-2787W75'
'Dithane-M-45'
'Manzate-200'
'Orthocide'
'Poliram-combi'
'Ridomil-MZ58'
'Counter'
'Diazinon'
'Furadan'
'Lannate'
'Lorsban'
'Malathion-li'
'Malathion-kg'
'Methil-parathion'
'Mocap'
'Orthene'
'Perfektion'
'Tamaron'
'Thiodan'
'Vydate-L'
BPRICE
0.
0.
10468.0
4635.0
2250.0
1095.0
1600.0
1183.0
2875.0
2000.0
628.0
2100.0
5950.0
1127.0
1630.0
1180.0
1835.0
3060.0
744.0
2040.0
2800.0
4000.0
1773.0
8080.0
2915.0
3915.0
1278.0
1350.2
1040.0
1439.0
5180.0
575.0
2150.0
1030.0
11800.0
2700.0
1435.0
390.0
2600.0
1058.0
5033.0
2860.0
2570.0
2800.0
4720.0
BPY
BPM
1997. 03.
1997. 03.
1997. 03.
1997. 03.
1997. 03.
1991. 06.
1997. 03.
1991. 06.
1997. 03.
1997. 03.
1991. 06.
1997. 03.
1997. 03.
1997. 03.
1997. 03.
1997. 03.
1997. 03.
1997. 03.
1997. 03.
1997. 03.
1997. 03.
1997. 03.
1997. 03.
1997. 03.
1997. 03.
1997. 03.
1997. 03.
1997. 03.
1997. 03.
1997. 03.
1997. 03.
1997. 03.
1997. 03.
1997. 03.
1997. 03.
1997. 03.
1997. 03.
1997. 03.
1997. 03.
1997. 03.
1997. 03.
1997. 03.
1997. 03.
1997. 03.
1997. 03.
BUNIT AI
'kg'
0.
'kg'
0.
'li'
0.24
'li'
0.04
'li'
0.48
'kg'
0.8
'li'
0.8
'li'
0.9
'kg'
0.9
'li'
0.5
'li'
0.5
'kg'
0.5
'li'
0.02
'li'
0.2
'li'
0.2
'li'
0.48
'li'
0.04
'li'
0.5
'li' 0.414
'li'
0.41
'li'
0.24
'kg'
0.5
'kg'
0.7
'kg'
0.5
'li'
0.75
'kg'
0.75
'kg'
0.8
'kg'
0.8
'kg'
0.5
'kg'
0.8
'kg'
0.1
'kg'
0.1
'li'
0.6
'kg'
0.1
'kg'
0.9
'li'
0.04
'li'
0.57
'kg'
0.05
'li'
0.46
'kg'
0.05
'kg'
0.95
'li'
0.5
'li'
0.6
'li'
0.35
'li'
0.24
WHO
DUR
'Ia'
0.
'Ia'
0.
'II'
8.
'III'
48.
'III'
48.
'III'
64.
'III'
64.
'III'
64.
'III'
64.
'III'
70.
'III'
50.
'III'
50.
'III'
35.
'II' 1000000.
'II' 1000000.
'II'
8.
'III'
84.
'III'
171.
'II'
8.
'III'
30.
'II'
8.
'III'
225.
'III' 1000000.
'III'
225.
'III'
24.
'III'
24.
'III'
5.
'III'
5.
'II'
3650.
'III'
0.
'III'
5.
'Ia'
15.
'II'
23.
'Ib'
37.
'Ib'
6.
'II'
89.
'III'
30.
'III'
30.
'Ia'
19.
'Ia'
32.
'III'
2.
'II'
14.
'Ib'
3.
'II'
70.
'Ib'
18.
SOL
0.
0.
0.61
0.5
4.5
0.042
0.042
0.042
0.042
0.0085
0.03
0.03
0.0001
700.
700.
0.61
0.24
0.0003
0.61
12.
0.61
0.003
0.
0.003
0.006
0.006
0.
0.
0.003
0.01
0.
0.0125
0.04
0.
58.
0.32
0.145
0.145
0.0575
0.
0.0005
25.
500.
0.00032
280.
II.6 Cattle
********************** CATTLE.ATF *******************************
* Cattle data attribute file, for PASTOR version 2.0
*****************************************************************
* CCODE
Cattle input code (number) (real)
* CDESCR Cattle input description (name) (character)
* CNAME
Cattle input name (name) (character)
* CUNIT
cattle input unit (measure unity) (character)
* CPRICE Cattle input depreciation or rental price, per unit
*
(colon/unit) (real)
* CPY
Year of cattle input price date (number) (real)
* CPM
Month of cattle input price date (number) (real)
CCODE
0000.00
0000.00
0000.00
CDESCR
'No cattle input'
'Dectomax antiparasite'
'Panacur inocculation'
CNAME
'none'
'dectomax'
'panacur'
CUNIT
'no'
'ml'
'ml'
CPRICE
0.
92.
9.9
CPY
CPM
1997. 03.
1997. 02.
1996. 06.
COMNAM
'Zero input'
'Zero input'
'Bentazone'
'Dicamba'
'Diuron'
'Diuron'
'Diuron'
'Diuron'
'Atrazine'
'Atrazine'
'Oxyfluorfen'
'Paraquat'
'Paraquat
'2,4D'
'Alachlor'
'2,4D'
'Glyphosate'
'Picloram +
'Benomyl'
'Propineb'
'Benomyl'
'Mancozeb'
'Mancozeb'
'Captan'
'Metiram'
'Mancozeb
'Terbufos'
'Diazinon'
'Carbofuran'
'Methomyl'
'Chlorpyrifos'
'Malathion'
'Malathion'
'Parathion'Ethoprophos'
'Acephate'
'Dimetoate'
'Endosulfan'
'Oxamyl'
I-27
0000.00
0000.00
0000.00
0000.00
0000.00
0000.00
0000.00
0000.00
0000.00
0000.00
'Ripercol inocculation'
'Neguvon external par.'
'Nuvan external par.'
'Butox external par.'
'Bacterine Doble vaccine'
'Bacterine Triple vaccine'
'Anthrax vaccine'
'Leptopsirosis vaccine'
'Brucellosis vaccine'
'Emicine antibiotics'
'ripercol'
'neguvon'
'nuvan'
'butox'
'bacterine'
'bacterine'
'anthrax'
'lepto'
'brucel'
'emicina'
'ml'
'kg'
'l'
'l'
'ml'
'ml'
'ml'
'ml'
'ml'
'ml'
7.7
4660.
9750.
21690.
5.1
5.3
4.
39.
250.
15.
1996.
1996.
1996.
1997.
1996.
1996.
1996.
1996.
1996.
1996.
06.
06.
06.
04.
06.
06.
06.
08.
06.
06.
II.7 Feed
********************** FEED.ATF *******************************
* Supplementary feed data attribute file, for PASTOR version 2.0
* Updated by A.Nieuwenhuyse April 1997
*****************************************************************
* FCODE
Suppl. feed input code (number) (real)
* FDESCR Suppl. feed input description (name) (character)
* FNAME
Suppl. feed input name (name) (character)
* FUNIT
Suppl. feed input unit (measure unity) (character)
* FCOD
Suppl. feed input three-letter code (name) (character)
* FPRICE Suppl. feed input price, per unit (colon/unit) (real)
* FPY
Year of Suppl. feed input price date (number) (real)
* FPM
Month of Suppl. feed input price date (number) (real)
* FDM
dry matter content of fresh suppl. feed (%) (real)
* FCP
Crude protein content of fresh material (%) (real)
* FME
Metabolizable energy content of fresh material (Mcal/kg) (real)
* FP
Phosphorus content of fresh material (%) (real)
* FK
Potassium content of fresh material (%) (real)
FCODE
0000.00
0000.00
0000.00
0000.00
0000.00
0000.00
0000.00
0000.00
0000.00
0000.00
0000.00
0000.00
FDESCR
'No supl. feed'
'Molasse of cana'
'Green banana'
'Gallinaz.engorde'
'Gallinaz.engorde'
'Gallinaz.leche'
'Gallinaz.leche'
'Mineral salt'
'Pecutrin salt'
'Common salt'
'P20 phosphorus'
'MG micronutrients'
FNAME
'none'
'molasse'
'banana'
'conc1'
'conc2'
'conc3'
'conc4'
'minsalt'
'pecutrin'
'salt'
'p20'
'MG'
FUNIT FCOD
'no'
'NON'
'kg'
'MOL'
'kg'
'BAN'
'kg'
'CN1'
'kg'
'CN2'
'kg'
'CN3'
'kg'
'CN4'
'kg'
'MNS'
'kg'
'PEC'
'kg'
'SAL'
'kg'
'P20'
'kg'
'MG0'
FPRICE FPY
0.
1997.
21.7
1997.
2.9
1997.
21.7
1997.
19.6
1997.
26.1
1997.
34.8
1997.
69.
1996.
222.
1996.
20.
1997.
178.
1996.
117.
1996.
FPM
04.
04.
04.
04.
04.
04.
04.
06.
06.
04.
06.
06.
FDM
0.
77.
17.
87.
87.
87.
87.
100.
100.
100.
100.
100.
FCP
0.
7.44
0.74
17.0
16.0
17.0
13.0
0.
0.
0.
0.
0.
FME
0.
2.7
0.41
2.5
2.25
2.55
3.04
0.
0.
0.
0.
0.
FP
0.
0.054
0.017
0.8
1.3
0.9
0.8
0.
19.
0.
19.
0.
FK
0.
1.94
0.48
0.
0.
0.
0.
0.
0.
0.
0.
0.
I-28
(Sectie 5) Appendix II: titel
Deze sectie en de sectie hieronder zijn alleen nodig als men een programmalisting in twee
kolommen geprint wil hebben. Hier worden twee secties voor gebruikt omdat er anders geen
normale kop boven de listing geplaats kan worden. Vergeet niet om de stijl Listing 2 voor Sectie 6
gebruiken. Voor de paginanummering zie Sectie 4 hierboven.
(Sectie 6)
deze sectie is bedoeld
voor een programmalisting in
twee kolommen.