Deliverable Factsheet
Date: 15/11/2010
Deliverable
7.2
Working Package
7
Partner responsible
UWA (Aberystwyth University)
Other partners participating
UNWE, LEI
Nature
Economic analysis
Dissemination level
Project report publishable as review paper
Delivery date according to DoW
Month 22
Actual delivery date
Month 30
Finalization date
Month --
Relevant Task(s):
7.2 & 7.3
Brief description of the deliverable
The analysis includes the following aspects:

A preliminary analysis of FADN and national data, including accessibility, availability of
variables and access to the data.

Methodology for the classification of low-input conventional holdings.

Analysis of FADN whole farm data to highlight crop protection (CP) and other input
usage, output and overall profitability of organic, conventional and low-input classified
holdings at all-EU, EU region, country and FADN farm type level.

Analysis of national farm survey data to highlight crop protection (CP) and other input
usage, output and overall profitability of organic, conventional and low-input classified
holdings for various crop enterprises.

Modelling the profitability of typical farm types and enterprises at varying levels of crop
protection usage and potential levy/tax systems employed for the focus group participating
countries.

A summary of the financial and crop protection usage position of EU farms and the likely
effects of tax/levy systems.
Followed methodology / framework applied
The study is predominantly based on farm financial data from the Farm Accountancy Data Network and
national data from UK and NED, through peer reviewed journal articles, books and published reports and in
some cases, unpublished reports and personal communications have also been used to complement
published material.
1
Target group(s)
TEAMPEST partners and academic community
Key findings / results
The evidence presented in this report highlights the variability in Crop Protection (CP) usage both between
farm types and crop enterprises, but also the variation within these groups.









The highest CP product usage per hectare was by Horticulture, Orchard, wine and other Permanent
Crop farm types.
Within the limited crop enterprise data available; Potatoes, Onions and Sugar beet were identified
as requiring the highest CP product inputs.
Splitting the data into low, medium and high CP cost and organic groups helped to identify
variance in profitability and other factors between the different groups.
At whole farm level, conventional high CP use holdings were the most profitable and the largest
economically, with variable performance on organic holdings.
At crop enterprise level, results were more variable with organic enterprises achieving the highest
gross margins, but within conventional farming high CP use systems were generally (but not
exclusively) the most profitable.
A range of flat rate crop protection cost increases, simulating a tax or levy on crop protection
inputs, was applied to both whole farm and crop enterprise data to identify the effects this may have
on whole farm profitability and enterprise GM.
Although the tax/levy increased CP costs proportionally more for the highest CP users, the effect
on profitability was often proportionally lower due to CP costs being a small proportion of total
costs (e.g. at 25% CP tax/levy, Cereal farm type profitability would fall by 10%, but Horticulture
would only fall by 2%).
At enterprise level, cereal enterprise gross margins reduced more than higher CP intensity crops
such as potatoes or sugar beet.
The imposition of the tax/levy on crop protection inputs resulted in a reduced difference in
profitability between low, medium, high CP input and organic groups, but didn’t alter the overall
position that higher input systems resulted in higher profitability per hectare.
Therefore it can be concluded that a flat rate tax/levy would probably not achieve a potentially desirable
shift of farmers from high input to lower input or organic systems, due to the lower profitability of low input
systems and a lack of new organic markets.
Interactions with other WPs deliverables / joint outputs
WP no.
Relevant tasks
Partner(s) involved
Context of interaction
3
3.1, 3.2 & 3.3
SLU
Taxation/levy methods/rates
5
5.2 and 5.3
WU/UCY
Taxation/levy methods/rates
6
6.1, 6.2 and 6.3
UCY
Taxation/levy methods/rates
8
8.1
UNWE
Taxation/levy methods/rates
2
Project no. 212120
Project acronym: TEAMPEST
Project title:
Theoretical Developments and Empirical Measurement of the
External Costs of Pesticides
Collaborative Project
SEVENTH FRAMEWORK PROGRAMME
THEME 2
Food, Agriculture and Fisheries, and Biotechnology
Title of Deliverable:
D7.2 Results of FADN Data Analysis and Typical Farm Models from the
Participating Countries.
Due date of delivery: March 2010
Actual submission date: November 2010
Start date of project: 1st May 2008
Duration: 36 months
Lead contractor for this deliverable: Aberystwyth University
Version: Draft
Confidentiality status: Confidential
3
WP 7 - Results of FADN Data Analysis and Typical Farm Models
from the Participating Countries
Tasks 7.2, 7.3, and associated Deliverable 7.2 – Results of FADN Data
Analysis and Typical Farm Models from the Participating Countries
Authors: Moakes, S. and P. Nicholas*
Institute of Biological, Environmental and Rural Sciences, Aberystwyth University, Gogerddan Campus,
Aberystwyth SY23 3EB
*Communicating author
4
Executive Summary
TEAMPEST project Tasks 7.2 and 7.3 were to determine the level of Crop Protection (CP) product usage at
an EU and national level and to examine the effects of a potential CP tax/levy on farm profitability. This data
would then be used in farmer focus groups in Task 7.4, to illustrate the possible effects of a CP tax/levy and
their potential for encouraging movement towards lower crop protection, particularly pesticide and input
systems.
CP product usage was assessed through the analysis of FADN data for 151,313 farm holdings collected
between 2004 and 2007, and national farm accounts data for UK (2005-08) and Holland (2004-07). CP usage
is defined by FADN (2007) as “Plant protection products, traps, baits, bird scarers, anti-hail shells, frost
protection etc. (excluding those used for forests).” and were identified from farm expenditure and calculated
per hectare by dividing by the farm’s utilizable agricultural area (UAA).
Whole farm analysis of FADN data
To ensure the results reflected the true nature of EU agriculture, the data was proportionally weighted, which
maintained the correct statistical error whilst allowing for the correct relative representation of individual
farm data within the EU. The results were assessed as a whole dataset but also as sub-groups by country,
region, and farm type and by the intensity of CP usage compared to the average for that farm type. Farm CP
usage intensity differentiation was achieved through the use of quartiles (specific to farm type) to classify
holdings into low, medium and high CP cost groups (<Q1=low, Q1 to Q3=med, >Q3=high).
Average CP costs for all EU farms were €246/ ha, but the median was only €79/ha and a standard deviation
of €1161/ha, indicating a large variability in the data and that some very high CP cost holdings were
increasing the mean value. Differentiating into conventional and organic farm types highlighted the high
overall CP costs of conventional farms at €249/ha while organic holdings were at €93/ha. Organic holdings
are also severely limited in the range of chemicals approved for use by European organic certification
standards, so costs were not directly comparable. Table 1 below, highlights the average CP costs of the eight
farm types studied, split by CP cost level into low, med, high and organic groups.
Table 1 Average EU CP costs for farm type, split by CP cost level (€/ha)
CP Level
Farm type
Low (LCP)
mean
Cereals, oilseeds & pulses
Other Fieldcrops
Horticulture
Wine
Orchards
Olives
Other permanent crops
Mixed cropping
6
16
60
28
40
9
14
6
sd
5
12
47
21
29
8
11
6
Med (MCP)
n
6907
6426
4030
2386
3174
1710
1864
3282
mean
48
92
689
202
255
61
98
53
sd
20
36
440
93
112
27
45
27
High (HCP)
n
mean
18347
17387
8617
8203
6436
3309
3492
8728
142
345
5588
778
843
219
552
328
sd
80
2
7774
479
414
100
1006
335
Org (ORG)
n
10664
2542
4902
4740
4692
894
2972
5345
mean
10
25
494
179
242
38
85
25
sd
26
2
1140
181
272
47
134
66
n
887
856
296
336
553
420
231
642
Analysis of Variance (ANOVA) tests indicated that CP costs for all eight farm types were significantly
different at the 0.05 level. The profitability of most farm types was also significantly different though
Fieldcrops, Permanent crop and Mixed farms were similar, as were Wine, Orchard and Olive types with the
Other Permanent Crops farm type.
The FADN data was also assessed for correlations between CP and other variables, such as fertiliser costs
and profitability, which were all found to be significant at the 0.01 level. Fertiliser was found to be the most
closely correlated, particularly for Fieldcrops, Horticulture and Mixed farm types, which indicates that any
change to CP costs would probably result in changes to fertiliser usage as well. Profitability was strongly
correlated for Wine and Horticulture types and wheat yield strongly correlated for Cereal and Olive farm
types. Overall, higher CP costs were slightly negatively correlated to physical farm size, which points
5
towards smaller farms spending more on CP products, while economic size and labour input were weakly
positively correlated with greater CP costs.
National crop enterprise data analysis
Crop enterprise data was also utilised from UK and NED to assess CP usage by individual crop enterprises.
This data was also classified into differing CP cost groups, to assess variability in gross margin at different
levels of CP costs, as shown in Table 2 below. Potatoes, particularly seed potatoes, onions and sugar beet
have the highest CP costs for those crops investigated.
Table 2 Average CP costs for enterprise type, split by CP cost level (€/ha)
CP Input Level
Enterprise
Winter Wheat
UK
Wheat
NED
Potatoes (maincrop)
UK
Potatoes (maincrop)
Potatoes (seed)
NED
NED
Sugar Beet
UK
Sugar Beet
NED
Spring Barley
UK
Beans
UK
Winter Oilseed
UK
Onions
NED
Low (LCP)
mean
sd
100
31
77
45
273 123
340
85
376 102
102
26
134
37
23
16
45
24
97
22
283 116
Med (MCP)
mean
sd
168 19
174 24
552 77
555 67
629 85
182 23
235 34
78 19
103 19
156 21
554 95
High (HCP)
mean
sd
247
44
276
65
971 304
792 112
1004 206
265
26
389 101
157
48
179
38
241
47
883 164
Org (ORG)
mean
sd
3
16
2
12
56
70
12
72
5
21
49 107
1
5
1
4
17
41
n
646
729
61
416
388
66
890
326
183
220
320
Effect of applying a CP taxation/levy to farm data
In Task 7.3, various tax/levy scenarios were applied to the datasets described above. After consultation with
other WP, a tax/levy scenario document was received that outlined various tax/levy scenarios to be assessed
within the TEAMPEST project. The only variable available for analysis within Task 7.2/7.3 was CP
expenditure; therefore a tax/levy could only be applied on a flat-rate basis to conventional CP expenditure.
The tax/levy rates assessed were 10%, 15%, 20% and 25%, applied to the CP costs of individual farms.
Due to the nature of the data Task 7.3 was unable to differentiate by a tax or levy system, but Task 7.4 will
build on the results of Task 7.3 to examine both the direct financial effects of a CP tax/levy, but also illicit
how farmers perceive the application of a tax that would return funds to central government, or a CPindustry enforced levy system that could be used to encourage safer use of CP products for farmers and
society as a whole.
Applying a CP tax/levy to whole farm data resulted in varying levels of profitability reduction, as shown in
Table 3 below. Cereal and Orchard farm types were the worst affected, indicating their relatively high CP
costs in relation to their profitability. Although in monetary terms Horticulture was the worst affected, the
percentage reduction was smaller than many other farm types, a result of the high value of output compared
to CP costs.
The analyses of the effects of a CP tax/levy at enterprise level are presented in Table 4 below, and indicate
that some enterprise gross margins would fall by up to 10%. Reflecting the whole farm results above, cereal
and pulse crops appeared to be the hardest hit, whilst crops that used higher levels of CP products such as
potatoes and sugar beet would see a smaller percentage effect on gross margin from a tax/levy. This may
have policy implications as a tax/levy may not achieve a reduction in CP usage in the highest CP intensity
systems.
6
Table 3 Percentage change in profitability at 15 or 25% tax rates of EU farms by farm type and CP
cost level (Whole farm data, FADN)
Farm
type
COP
FIELD
HORT
WINE
ORCH
OLIVE
PERM
MIXED
CP
Tax/Levy
rate
15%
25%
15%
25%
15%
25%
15%
25%
15%
25%
15%
25%
15%
25%
15%
25%
% change in profit (FNVA)
Low CP
-0.2%
-0.4%
-0.3%
-0.5%
0.0%
-0.1%
-0.2%
-0.4%
-0.2%
-0.4%
-0.1%
-0.2%
-0.1%
-0.1%
-0.1%
-0.2%
Med CP
-1.4%
-2.4%
-1.1%
-1.8%
-0.4%
-0.7%
-1.1%
-1.9%
-0.9%
-1.5%
-0.4%
-0.7%
-0.6%
-0.9%
-0.5%
-0.9%
High CP
-3.0%
-5.0%
-1.2%
-2.0%
-0.9%
-1.6%
-0.9%
-1.5%
-2.2%
-3.7%
-1.3%
-2.2%
-0.6%
-1.1%
-1.2%
-2.0%
ORG
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
Table 4 Percentage change in profitability at 15% or 25% tax rates, split by farm type and CP cost
level (Enterprise data, UK & NED)
Crop type
Wheat
Country
UK
NED
Potatoes
(maincrop)
UK
NED
Sugar Beet
NED
Beans
UK
Winter OSR
UK
Onions
NED
CP
Tax/Levy
rate
Low CP
15%
25%
15%
25%
15%
25%
15%
25%
15%
25%
15%
25%
15%
25%
15%
25%
-2%
-3%
-2%
-3%
-1%
-1%
-1%
-2%
-1%
-1%
-2%
-3%
-1%
-2%
-2%
-3%
% change in gross margin per ha
Med CP
-3%
-5%
-3%
-5%
-2%
-4%
-2%
-4%
-1%
-2%
-4%
-7%
-2%
-4%
-2%
-4%
High CP
-5%
-8%
-6%
-9%
-4%
-6%
-4%
-6%
-3%
-4%
-6%
-10%
-4%
-6%
-5%
-8%
ORG
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
Conclusions and policy implications
Task 7.2 highlighted horticulture and permanent crop farm types as the most intense CP users, though there
was a large difference in conventional farm CP usage within these farm types. This indicates that lower input
management techniques are possible for these farm types and could be adopted, however, profitability was
also generally lower for low CP intensity systems (e.g. 44% lower for Cereal, 87% lower for Wine types),
which would inhibit its uptake.
7
An analysis of crop enterprise data from UK and NED indicated that the most CP intensive crops were
potatoes, onions and sugar beet, but that the highest crop gross margins were achieved by organic farms and
not necessarily by the high CP input systems.
Task 7.2 examined the effect of imposing a tax/levy to the data, with Cereal and Orchard farm types the most
severely affected, whilst the high CP intensity Horticulture farm type profitability fell by just 2%. This
reflects that relative to output, CP costs are higher for Cereal and Orchard farms, but a lesser percentage of
total costs on Horticulture holdings.
The imposition of a flat rate tax/levy would have a variable effect on the profitability of farms and crop
enterprises and may not reduce usage where it is intended. Due to the larger percentage effect on Cereal
farms, a tax/levy may reduce CP usage on high input Cereal farms, but not reduce CP usage to a large extent
within Horticulture holdings due to the smaller percentage effect. The data analysis also identified that some
organic farm types and enterprises performed well financially, but the organic market is limited in size and is
not suitable for all farms, so only a small proportion of farms could move in this direction. A move to lower
input systems, although desirable to reduce CP use would appear to result in lower profitability for the
farmer, compared to higher CP intensity systems.
Therefore, from this financial analysis it can be concluded that a CP tax/levy system would need to be a
“targeted” mechanism to ensure a reduction in usage on the most CP intense holdings, and that a tax/levy is
unlikely to result in the wider adoption of low input or organic techniques due to poorer financial
performance and a lack of new markets respectively. However, Task 7.1 identified that financial drivers are
not the only reasons for using CP products, and it is hoped that the farmer focus groups within Task 7.4 will
illicit other motivations for the use of CP products and determine how a tax or levy could be used to enable
more effective use of CP products.
8
Table of contents
Executive Summary................................................................................................................... 5
Effect of applying a CP taxation/levy to farm data ................................................................................... 6
Conclusions and policy implications ........................................................................................................ 7
1
Introduction..................................................................................................................... 15
2
Economic analysis of FADN data .................................................................................. 16
2.1
A preliminary analysis of FADN and national data, including accessibility and availability of
parameters ................................................................................................................................................... 16
2.1.1
Whole Farm Data..................................................................................................................... 16
2.1.2
Cropping Enterprise Data ........................................................................................................ 16
2.1.3
Conventional and organic data ................................................................................................ 17
2.1.4
Weighting of data .................................................................................................................... 17
2.1.5
ANOVA methodology ............................................................................................................. 17
2.1.6
Methodology for the classification of low-input conventional holdings ................................. 17
2.2
Analysis of FADN whole farm data............................................................................................... 19
2.2.1
Crop Protection usage .............................................................................................................. 19
2.2.2
ANOVA analysis of CP costs and profitability by farm type.................................................. 22
2.2.3
Correlations of CP costs and other factors by farm type ......................................................... 23
2.2.4
Cereals, Oilseeds and Pulses (COP) ........................................................................................ 23
2.2.5
Other fieldcrops (FIELD) ........................................................................................................ 28
2.2.6
Horticulture (HORT) ............................................................................................................... 31
2.2.7
Wine (WINE) .......................................................................................................................... 35
2.2.8
Orchards (ORCH) .................................................................................................................... 38
2.2.9
Olives (OLIVE) ....................................................................................................................... 42
2.2.10
Other Permanent Crops (PERM) ............................................................................................. 43
2.2.11
Mixed Cropping (MIXED) ...................................................................................................... 46
2.2.12
Whole farm data summary ...................................................................................................... 50
2.3
Analysis of national farm survey data for UK and Netherlands .................................................... 51
2.3.1
Winter Wheat (UK) ................................................................................................................. 51
2.3.2
Spring Barley (UK) ................................................................................................................. 52
2.3.3
Beans (UK) .............................................................................................................................. 52
2.3.4
Potatoes – Maincrop (UK) ....................................................................................................... 53
2.3.5
Sugar Beet (UK) ...................................................................................................................... 54
2.3.6
Winter Oilseed Rape (UK) ...................................................................................................... 55
2.3.7
Potatoes - Maincrop (NED) ..................................................................................................... 55
2.3.8
Potatoes - Seed (NED)............................................................................................................. 56
2.3.9
Sugar Beet (NED) .................................................................................................................... 57
9
2.3.10
Onions (NED) .......................................................................................................................... 57
2.3.11
Winter Wheat (NED) ............................................................................................................... 58
2.3.12
Crop enterprise data summary ................................................................................................. 59
2.4
Effect of applying CP taxation/levy ............................................................................................... 60
2.4.1
Effect of applying CP taxation/levy to whole farm data ......................................................... 60
2.4.2
Effect of applying CP taxation/levy to national crop enterprise data ...................................... 62
2.4.3
Summary of the effects of a CP tax/levy ................................................................................. 70
3
Conclusions and Policy Recommendations .................................................................... 71
4
Relevance to other work packages in TEAMPEST ........................................................ 73
5
References....................................................................................................................... 74
6
Appendix......................................................................................................................... 75
6.1
Appendix 1: FADN farm typologies .............................................................................................. 75
6.2
Appendix 2: FADN requested variable list .................................................................................... 76
6.3
Appendix 3: UN EU region classification...................................................................................... 79
6.4
Appendix 4: Additional data tables ................................................................................................ 81
10
List of tables and figures
Figure 1 CP costs across EU regions (FADN 2004-2007) .............................................................................. 20
Table 1 Average EU CP costs for farm type, split by CP cost level (€/ha) ....................................................... 5
Table 2 Average CP costs for enterprise type, split by CP cost level (€/ha) ..................................................... 6
Table 3 Percentage change in profitability at 15 or 25% tax rates of EU farms by farm type and CP cost level
(Whole farm data, FADN) ................................................................................................................................. 7
Table 4 Percentage change in profitability at 15% or 25% tax rates, split by farm type and CP cost level
(Enterprise data, UK & NED) ........................................................................................................................... 7
Table 5 Descriptive statistics for CP costs (€/ha) (2004-2007, TEAMPEST TF14 farm types only) ............. 18
Table 6 Quartile statistics for conventional farm CP costs (€/ha) (2004-2007) .............................................. 18
Table 7 CP/ha for General TF farm types (€/ha, un-weighted FADN EU27, 2004-2007).............................. 19
Table 8 CP/ha for selected FADN TF14 farm types (€/ha, FADN 2004-2007) .............................................. 19
Table 9 Mean cp/ha by EU region (2004-2007, TEAMPEST TF14 farm types only) .................................... 20
Table 10 Mean cp/ha by country (2004-2007, TEAMPEST TF14 farm types only) ...................................... 21
Table 11 Mean cp/ha by farm type and CP input level (2004-2007) .............................................................. 21
Table 12 Mean fnva/ha by farm type and CP input level (2004-2007) ........................................................... 22
Table 13 CP usage ANOVA analysis at farm type level ................................................................................. 22
Table 14 FNVA ANOVA analysis at farm type level ..................................................................................... 23
Table 15 Correlations of CP/ha with other variables by farm type ................................................................. 23
Table 16 COP crop inputs (€ per hectare) ....................................................................................................... 24
Table 17 COP profitability and wheat yield (€/ha and t/ha) ............................................................................ 24
Table 18 COP area, economic size and labour input (UAA ha, ESU/farm, AWU/farm) ............................... 25
Table 19 COP ANOVA analysis of inputs, profitability and fixed factors at different CP input levels ......... 27
Table 20 COP ANOVA analysis of differences in CP input and profitability at different CP input levels
across EU regions ............................................................................................................................................ 27
Table 21 COP correlations of CP/ha with other variables in EU regions........................................................ 28
Table 22 FIELD crop inputs (€ per hectare).................................................................................................... 28
Table 23 FIELD profitability and wheat yield (€/ha and t/ha) ........................................................................ 29
Table 24 FIELD area, economic size and labour input (UAA ha, ESU/farm, AWU/farm) ............................ 29
Table 25 FIELD ANOVA analysis of inputs, profitability and fixed factors at different CP input levels ...... 30
Table 26 FIELD ANOVA analysis of differences in CP input and profitability at different CP input levels
across EU regions ............................................................................................................................................ 30
Table 27 FIELD correlations of CP/ha with other variables in EU regions .................................................... 31
Table 28 HORT crop inputs (€ per hectare) .................................................................................................... 31
Table 29 HORT profitability and wheat yield (€/ha and t/ha)......................................................................... 32
Table 30 HORT area, economic size and labour input (UAA ha, ESU/farm, AWU/farm) ............................ 33
Table 31 HORT ANOVA analysis of inputs, profitability and fixed factors at different CP input levels ...... 33
11
Table 32 HORT ANOVA analysis of differences in CP input and profitability (FNVA) at different CP input
levels across EU regions .................................................................................................................................. 35
Table 33 HORT correlations of CP/ha with other variables in EU regions .................................................... 35
Table 34 WINE crop inputs (€ per hectare)..................................................................................................... 36
Table 35 WINE profitability and wheat yield (€/ha and t/ha) ......................................................................... 36
Table 36 WINE area, economic size and labour input (UAA ha, ESU/farm, AWU/farm) ............................. 37
Table 37 WINE ANOVA analysis of inputs, profitability and fixed factors at different CP input levels....... 37
Table 38 WINE ANOVA analysis of differences in CP input and profitability (FNVA) at different CP input
levels across EU regions .................................................................................................................................. 38
Table 39 WINE correlations of CP/ha with other variables in EU regions ..................................................... 38
Table 40 ORCH crop inputs (€ per hectare) .................................................................................................... 39
Table 41 ORCH profitability and wheat yield (€/ha and t/ha) ........................................................................ 39
Table 42 ORCH area, economic size and labour input (UAA ha, ESU/farm, AWU/farm) ............................ 40
Table 43 ORCH ANOVA analysis of inputs, profitability and fixed factors at different CP input levels ...... 40
Table 44 ORCH ANOVA analysis of differences in CP input and profitability (FNVA) at different CP input
levels across EU regions .................................................................................................................................. 41
Table 45 ORCH correlations of CP/ha with other variables in EU regions .................................................... 41
Table 46 OLIVE crop inputs (€ per hectare) ................................................................................................... 42
Table 47 OLIVE profitability and wheat yield (€/ha and t/ha) ....................................................................... 42
Table 48 OLIVE area, economic size and labour input (UAA ha, ESU/farm, AWU/farm) ........................... 42
Table 49 OLIVE ANOVA analysis of inputs, profitability and fixed factors at different CP input levels ..... 43
Table 50 PERM crop inputs (€ per hectare) .................................................................................................... 43
Table 51 PERM profitability and wheat yield (€/ha and t/ha)......................................................................... 44
Table 52 PERM area, economic size and labour input (UAA ha, ESU/farm, AWU/farm) ............................ 44
Table 53 PERM ANOVA analysis of inputs, profitability and fixed factors at different CP input levels ...... 45
Table 54 PERM ANOVA analysis of differences in CP input and profitability (FNVA) at different CP input
levels across EU regions .................................................................................................................................. 46
Table 55 PERM correlations of CP/ha with other variables in EU regions .................................................... 46
Table 56 MIXED crop inputs (€ per hectare) .................................................................................................. 47
Table 57 MIXED profitability and wheat yield (€/ha and t/ha) ...................................................................... 47
Table 58 MIXED area, economic size and labour input (UAA ha, ESU/farm, AWU/farm) .......................... 48
Table 59 MIXED ANOVA analysis of inputs, profitability and fixed factors at different CP input levels .... 48
Table 60 MIXED ANOVA analysis of differences in CP input and profitability (FNVA) at different CP input
levels across EU regions .................................................................................................................................. 49
Table 61 MIXED correlations of CP/ha with other variables in EU regions .................................................. 49
Table 62 UK Winter Wheat enterprise analysis at varying CP Level ............................................................. 51
Table 63 UK Winter Wheat ANOVA analysis at varying CP Level ............................................................... 51
Table 64 UK Spring Barley enterprise analysis at varying CP Level ............................................................. 52
Table 65 UK Spring Barley ANOVA analysis at varying CP Level ............................................................... 52
12
Table 66 UK Beans enterprise analysis at varying CP Level .......................................................................... 52
Table 67 UK Beans ANOVA analysis at varying CP Level ........................................................................... 53
Table 68 UK Potatoes enterprise analysis at varying CP Level ...................................................................... 53
Table 69 UK Potatoes ANOVA analysis at varying CP Level ....................................................................... 54
Table 70 UK Sugar Beet enterprise analysis at varying CP Level .................................................................. 54
Table 71 UK Sugar Beet ANOVA analysis at varying CP Level ................................................................... 54
Table 72 UK Winter Oilseed Rape enterprise analysis at varying CP Level .................................................. 55
Table 73 UK Winter Oilseed Rape ANOVA analysis at varying CP Level .................................................... 55
Table 74 NED Potatoes (Maincrop) enterprise analysis at varying CP Level................................................. 56
Table 75 NED Potatoes (Maincrop) ANOVA analysis at varying CP Level .................................................. 56
Table 76 NED Potatoes (seed) enterprise analysis at varying CP Level ......................................................... 56
Table 77 NED Potatoes (seed) ANOVA analysis at varying CP Level .......................................................... 57
Table 78 NED Sugar Beet enterprise analysis at varying CP Level ................................................................ 57
Table 79 NED Sugar Beet ANOVA analysis at varying CP Level ................................................................. 57
Table 80 NED Onion enterprise analysis at varying CP Level ....................................................................... 58
Table 81 NED Onions ANOVA analysis at varying CP Level ....................................................................... 58
Table 82 NED Winter Wheat enterprise analysis at varying CP Level ........................................................... 58
Table 83 NED Winter Wheat ANOVA analysis at varying CP Level ............................................................ 59
Table 84 COP Effects of taxation on CP and profitability (FNVA) by CP cost group ................................... 60
Table 85 FIELD Effects of taxation on CP and profitability (FNVA) by CP cost group ............................... 60
Table 86 HORT Effects of taxation on CP and profitability (FNVA) by CP cost group ................................ 60
Table 87 WINE Effects of taxation on CP and profitability (FNVA) by CP cost group ................................ 61
Table 88 ORCH Effects of taxation on CP and profitability (FNVA) by CP cost group ................................ 61
Table 89 OLIVE Effects of taxation on CP and profitability (FNVA) by CP cost group ............................... 61
Table 90 PERM Effects of taxation on CP and profitability (FNVA) by CP cost group ................................ 62
Table 91 MIXED Effects of taxation on CP and profitability (FNVA) by CP cost group .............................. 62
Table 92 UKI average enterprise GM at 0% CP tax and 25% CP tax rates, at varying CP Levels ................. 63
Table 93 UKI Winter Wheat GM at no tax and 25% CP tax rates (ANOVA analysis at varying CP Levels) 64
Table 94 UKI Spring Barley GM at no tax and 25% CP tax rates (ANOVA analysis at varying CP Levels) 65
Table 95 UKI Beans GM at no tax and 25% CP tax rates (ANOVA analysis at varying CP Levels) ............ 65
Table 96 UKI Potatoes GM at no tax and 25% CP tax rates (ANOVA analysis at varying CP Levels)......... 65
Table 97 UKI Sugar Beet GM at no tax and 25% CP tax rates (ANOVA analysis at varying CP Levels) .... 66
Table 98 UKI Winter Oilseed Rape GM at no tax and 25% CP tax rates (ANOVA analysis at varying CP
Levels) ............................................................................................................................................................. 66
Table 99 NED average enterprise GM at 0% CP tax and 25% CP tax rates at varying CP Levels ................ 68
Table 100 NED Potatoes (maincrop) GM at 0% tax and 25% CP tax rates (ANOVA analysis at varying CP
Levels) ............................................................................................................................................................. 68
13
Table 101 NED Potatoes (seed) GM at 0% tax and 25% CP tax rates (ANOVA analysis at varying CP Levels)
......................................................................................................................................................................... 68
Table 102 NED Sugar Beet GM at 0% tax and 25% CP tax rates (ANOVA analysis at varying CP Levels) 69
Table 103 NED Onions GM at 0% tax and 25% CP tax rates (ANOVA analysis at varying CP Levels) ...... 69
Table 104 NED Wheat GM at 0% tax and 25% CP tax rates (ANOVA analysis at varying CP Levels) ....... 70
Table 105 FADN - General TF farm typologies ............................................................................................. 75
Table 106 FADN – TF14 farm typologies ...................................................................................................... 75
Table 107 Mean cp/ha by country for each year 2004-2007, (TEAMPEST TF14 farm types only) .............. 81
14
1 Introduction
This report has been prepared to fulfil Tasks 7.2 and 7.3 of Work Package 7 of the TEAMPEST project.
Task 7.2 aimed to analyse full farm data sets of Farm Income Data (FADN) for low-pesticide input and
conventional farms with arable, horticulture and permanent crop enterprise, with more detailed assessments
carried out in UK, Bulgaria and the Netherlands. Only organic holdings could be identified specifically in the
FADN data but expenditure on pesticides could be used as a proxy to identify other low-pesticide input
systems. Task 7.2 led onto 7.3, modelling scenarios of different relative profitability for a number of typical
farm types (of varying arable, horticulture and permanent crop enterprise mixes) in UK, Bulgaria and the
Netherlands , with the identification of typical farms.
The process used to address the aims outlined above included:

A preliminary analysis of FADN and national data, including accessibility, availability of parameters
and application for access to data.

Methodology for the classification of low-input conventional holdings.

Analysis of FADN whole farm data to highlight crop protection (CP) and other input usage, output
and overall profitability of organic, conventional and low-input classified holdings at all-EU, EU
region, country and FADN farm type level.

Analysis of national farm survey data to highlight crop protection (CP) and other input usage, output
and overall profitability of organic, conventional and low-input classified holdings for various crop
enterprises.

Modelling the profitability of typical farm types and enterprises at varying levels of crop protection
usage and potential levy/tax systems employed for the focus group participating countries UK, BG
and NED.

A summary of the financial and crop protection usage position of EU farms and the likely effects of
tax/levy systems.
This study is predominantly based on the analysis of FADN and national farm economic data, but includes
reference to peer reviewed journal articles, books and published reports.
The study builds upon Task 7.1 that hypothesised that economic viability is a key driver to the uptake, or not,
of a farming system or practice, and investigated the role other factors might play in driving farmer decision
making. Tasks 7.2 and 7.3 aim to provide an economic analysis and tools to highlight the possible financial
advantages/disadvantages to producers of reducing pesticide usage by increasing the uptake of organic and
other low pesticide input farming systems. Task 7.3 specifically attempts to analyse the financial impacts of
the application of various tax/levy scenarios on typical farm types.
15
2 Economic analysis of FADN data
Task 7.2 commenced with a preliminary analysis of FADN and national data, including accessibility,
availability parameters and the possible classification of low-input conventional holdings. With the available
data, an analysis of FADN whole farm data was completed, including the calculation of a low-input
classification methodology, crop protection usage at EU, regional, country and FADN farm type levels
which were subsequently split by CP cost level.
2.1 A preliminary analysis of FADN and national data, including accessibility
and availability of parameters
Prior to data analysis an assessment of data availability was carried out, to clarify data variables collected
through various agencies and the accessibility of this data to the project for analysis and use within
TEAMPEST.
2.1.1
Whole Farm Data
The Farm Accountancy Data Network (FADN) was highlighted as the principle data source for whole farm
data for WP7 within the project Document of Work (DoW). The FADN was established in 1965 under
Council Regulation 79/65, is derived from national surveys, and is the only source of micro-economic data
that is harmonised, i.e. the bookkeeping principles are the same in all countries across the EU (FADN,
2009a). The FADN data is publicly available through an interactive database website
(http://ec.europa.eu/agriculture/rica/database/database_en.cfm) that provides average results by farm type,
country and other factors. However, the TEAMPEST task required the analysis of individual farm data as
farm holdings would be classified according to their level of CP costs (See Appendix 1: FADN farm
typologies for a full list).
A total of 66 variables (See Appendix 2: FADN requested variable list, page 75), were requested from
FADN in an application for individual farm data for the years 2004 through to 2007. The request was
submitted to FADN through the project co-ordinator in mid-December 2008, however due to some
communication delays the 2004 to 2006 data was not received until August 2009 and the 2007 data followed
in February 2010. In total, data for 229,073 individual farms was received from FADN, with 151,313 data
sets used for the TEAMPEST analysis due to the specific farm types studied. Data for 2004-2006 covered
the EU25 countries, with the addition of Romania and Bulgaria to form the EU27 in 2007.
As an initial step, data for all countries over the four years was compiled into a single data sheet in Microsoft
Excel 2007 and then imported into SPSS software (IBM, 2010) for analysis. To ensure data was more
comparable between groups of farms the main variables considered within TEAMPEST were re-calculated
on a per hectare basis by dividing the per farm cost by the Utilisable Agricultural Area (UAA).
To ensure confidentiality of FADN surveyed holdings, published average data must contain data from at
least 15 holdings. This ensures that no one holding is identifiable from the data and helps to balance out
extreme values. Due to the classification of holdings by farm type, whether they are conventional or organic,
EU region and CP expenditure level some groups were smaller than 15 farms and therefore data could not be
published and is marked by an “a” in data tables.
2.1.2 Cropping Enterprise Data
In addition to FADN data, the project anticipated the use of more detailed national data for analysis of CP
usage at a crop enterprise level, rather than at whole farm level. Aberystwyth University already had access
to detailed UK national data due to other farm economic analysis work carried out for the UK government,
but also required more detailed data for the Netherlands and Bulgaria as they were identified to carry out
farmer focus groups in Task 7.4. Negotiations with Dutch TEAMPEST partner LEI allowed remote access to
the detailed Dutch farm economic data, which became available to AU in spring 2010. Due to the remote
access system for accessing the Dutch data (to maintain data confidentiality), there were some difficulties in
analysing the data and reporting the results which slowed progress. However, both UK and Dutch data
included crop area, output and input data for a range of arable and horticultural enterprises, though data was
16
limited for some crops. Both systems employed a combination of manual and automatic allocation of costs
and outputs to an enterprise.
Detailed Bulgarian data was found to be not available, as Bulgaria had only joined the FADN system for the
2007 data year, so only the whole farm data could be utilised for their focus groups in Task 7.4.
2.1.3 Conventional and organic data
Due to the different farming methods and type of pesticides used, this report presents results split by
conventional and organic farming. CP costs for organic farming will be mainly for physical or biological pest
control, though a few, naturally occurring chemicals are permitted for use under EU organic farming rules
(COMMISSION REGULATION (EC) No 889/2008, 2008 ). Contrasts between organic and conventional farming
are of particular relevance to the profitability analysis as farmers are unlikely to adopt organic farming
methods without the prospect of similar or improved financial returns. Farm data from farms that were inconversion have been excluded from the results are they are in a transitional phase and will not accurately
reflect the true performance of established organic farms.
2.1.4 Weighting of data
The FADN database uses a special system of weighting. The FADN sample is a subset of the EUROSTAT
Farm Structure Survey (FSS) and farms are weighted according to their FADN region, farm type and
economic size to represent the full sample of FSS farms. To simply use the FADN weighting value would
however artificially inflate the confidence level of the data by creating a very large sample of replicated data
that would under-estimate the standard errors (Maletta, 2007). Therefore, for the FADN data analysis, each
holding was proportionally weighted to ensure that the FADN weighting of the holding was accounted for,
but that statistical tests for significance were calculated correctly by maintaining the original sample size. All
FADN data results have been calculated using proportional weighting according to the sample; national
enterprise data analysis was not weighted.
2.1.5 ANOVA methodology
Analysis of variance (ANOVA) techniques were used to ascertain the significance of differences between
different farm types and groups within these types. Based on techniques described within the SPSS statistics
program, (IBM, 2009), during exploratory analysis the Levene statistic was found to be significant indicating
that variance between the groups was not homogenous, and therefore “Tamhane” posthoc multiple
comparison methodology was used for the ANOVA analyses to identify differences between group means
via a robust test. ANOVA data tables are presented as posthoc results, to indicating differences between
groups, which were assumed to be significant at a P value of 0.05 or lower.
2.1.6 Methodology for the classification of low-input conventional holdings
To enable an assessment of the relative profitability of organic, conventional and low input farms it is
necessary to classify farms into these sub-groups. The FADN system identifies organic and conventional
farms and splits these into various general or more detailed farm typologies, but there is no classification
system for recognising low input farms. Therefore a method for identifying farms with lower usage of CP
products was necessary to achieve the aims of WP7. An analysis of existing low input classification systems
that had been applied to similar data sets was carried out through a review of existing literature.
Two possible systems were identified as potential methods; the IRENA (Indicator Reporting on the
Integration of Environmental Concerns into Agriculture Policy) project and the SEAMLESS (Systems for
Environmental and Agricultural Modelling; Linking European Science and Society) project.
The IRENA operation was launched in 2002, to further develop agri-environmental indicators for monitoring
the integration of environmental concerns into the common agricultural policy (CAP). A joint exercise
between DG Agriculture and Rural Development, DG Environment, Eurostat, DG Joint Research Centre,
and the European Environment Agency (EEA), (EEA, 2005). As part of the project a methodology to
classify farms in terms of intensity was developed: IRENA indicator 15 assessed; a) Trends in the share of
agricultural area managed by low-input, medium-input or high-input farm types (based on the average
expenditure on inputs per hectare). The agricultural intensity of holdings was defined as: Low-input farms
17
spend less than €80 per ha per year on fertilisers, crop protection and concentrated feedstuff. Medium-input
farms spend between €80 and €250 per ha per year and high-input farms more than €250 per ha per year on
these inputs.
The SEAMLESS project, an EU 6th Framework funded project’s main objective was to develop an
integrated framework (SEAMLESS-IF) to support ex-ante analysis of policies that enable analysis at the full
range of scales (Elbersen et al., 2006). As part of this work a system for allocating typology of farm holding
intensity was developed, based on farm output per hectare: Low < €500 per ha, medium €500-€3000 per ha,
high €3000+ per ha.
After some exploratory data analysis and due to the very specific nature of the TEAMPEST project it was
decided that rather than use an indirect measure, FADN crop protection costs (SE300) divided per hectare of
Utilizable Agricultural Area (UAA) would be utilised as the primary measure for intensity of CP usage. The
next stage was to determine the cut off values to determine low, medium and high CP usage.
The dataset comprised of a large number of holdings that used no CP products, but a small number that used
a very high level. With the IRENA and SEAMLESS low intensity figures in mind, quartiles or percentiles
were considered to be the best option for identifying holdings with low CP input. Table 5 indicates that
overall, for all conventional TEAMPEST farm types, a quartile 1 (Q1) figure of €28/ha and a quartile 3 (Q3)
figure of €194/ha. Holdings with a CP/ha value of less than Q1 were classed as low input, whilst holdings
with a CP/ha above Q3 were classed as high input holdings.
The EU25 data for each year shows slight variation, with the conventional farm mean highest in 2007, but
the median figure lowest in 2007, indicating that some producers spent more on CP in 2007 but that overall,
producers spent less.
Table 5 Descriptive statistics for CP costs (€/ha) (2004-2007, TEAMPEST TF14 farm types only)
All farms
Conv.
Org.
2004-07
Mean
Median
246
79
2004-07
2004
2005
2006
2007
2004-07
2004
2005
2006
2007
249
255
240
246
257
93
119
84
80
90
Q1
28
Q3
194
29
30
31
29
28
0
0
0
0
0
197
201
200
200
187
71
93
84
52
68
81
84
83
81
75
12
13
13
7
16
sd
n
1161 151313
1174
933
819
956
1679
297
345
219
328
280
147092
35477
36423
36492
38700
4221
897
925
1201
1198
Although useful for highlighting overall CP input levels, considerable variation between farm types indicated
that CP intensity values for each farm type should also be calculated. There for, analysis of the FADN
dataset as a whole utilises the overall Q1 and Q3 figures for intensity classification, but analysis of data split
by farm type utilises Q1 and Q3 figures specific to each farm type, (see Table 6, e.g. Low input Cereal
farms ).
Table 6 Quartile statistics for conventional farm CP costs (€/ha) (2004-2007)
Conventional farms
Q1 (low input)
Q3 (high input)
Cereals, oilseeds & pulses (COP)
Other fieldcrops (FIELD)
Horticulture (HORT)
Wine (WINE)
Orchards (ORCH)
Olives (OLIVE)
Perm. crops combined PERM)
Mixed crops (MIXED)
17
37
155
69
92
23
34
17
88
168
1771
395
478
120
196
116
n
35918
32398
17549
15329
14302
5913
8328
17355
18
2.2 Analysis of FADN whole farm data
Crop protection costs were identified within FADN datasets as variable SE300, and defined as:
“Plant protection products, traps, baits, bird scarers, anti-hail shells, frost protection etc. (excluding those
used for forests).” (FADN, 2007)
The definition presented some issues to the TEAMPEST project as the project is focused primarily on the
effects of the use of pesticides. Variable SE300 may contain a variety of crop protection costs, not
exclusively chemical pesticides. Only the Netherlands appeared to have some detailed data concerning the
breakdown of SE300 data, and a very detailed study would be required to identify the exact composition of
SE300 within varying farm types and in different countries or regions. Due to the difficulty in allocating
actual CP costs to these various items this analysis assumed that the majority of conventional farm/holding
CP costs identified within SE300 were CP chemical products.
2.2.1 Crop Protection usage
To ensure an in-depth analysis of CP usage, the FADN dataset was split by farm type. Initially the dataset
was sorted by EU FADN farm typology (General TF) and assessed for the mean value of crop protection (CP)
used per hectare. Table 7 shows that over the four year period 2004-07, the four (General TF) farm types
with the highest CP usage were Fieldcrops, Horticulture, Permanent Crops and Mixed Cropping. At this
point the livestock based farm types were excluded from any further analysis as their CP usage per hectare
was substantially lower.
Table 7 CP/ha for General TF farm types (€/ha, un-weighted FADN EU27, 2004-2007)
General TF farm type
Mean
Field crops
sd
Range
n
94
149
12913
70059
1733
4266
255650
17845
Permanent crops
222
461
24619
45412
Grazing livestock
17
34
1293
83003
Granivores
52
196
15790
15023
Mixed cropping
108
277
15113
17997
Mixed livestock
27
42
856
15296
Mixed crops-livestock
44
68
3420
35302
157
901
255650
299937
Horticulture
Total
To allow for more detailed analysis, the more comprehensive FADN (TF14) farm typology classifies
Fieldcrops and Permanent Crops into smaller sub-groups, so four farm types split into eight farm types.
Table 8 below highlights the variance in these sub-groups; in particular between Cereals, Oilseeds and Pulses
(COP) and Other fieldcrops (FIELD) farms, and with Olives (OLIVE) and Orchards (ORCH) compared to
other Permanent Crop (PERM) types.
Table 8 CP/ha for selected FADN TF14 farm types (€/ha, FADN 2004-2007)
TF14
Cereals, oilseeds & pulses (COP)
Other fieldcrops (FIELD)
Horticulture (HORT)
Wine (WINE)
Orchards (ORCH)
Olives (OLIVE)
Perm. crops combined (PERM)
Mixed crops (MIXED)
Mean
61
136
1756
303
347
88
190
110
Conventional
sd
range
66
2427
211
12913
4489 255650
377
5170
371
5024
95
1000
546
24619
211
15113
n
35918
32398
17549
15329
14302
5913
8328
17355
Mean
10
25
494
179
242
38
85
25
Organic
range
26
299
60
582
1140
14388
181
1112
272
1610
47
428
134
1085
66
1003
sd
n
887
856
296
336
553
420
231
642
19
Following farm type assessment, CP costs were assessed by EU region (classified by UN, 2010), to identify
how CP costs varied across the EU. Overall it can be seen that they were considerably higher in the Western
EU states than other areas. At farm type level this pattern was similar for all types except type 34 (Other
Permanent Crops), with Northern areas having higher CP usage.
Figure 1 CP costs across EU regions (FADN 2004-2007)
600
CP costs (€/ha)
500
400
300
200
100
0
East
North
South
Conv.
West
Org.
Table 9 Mean cp/ha by EU region (2004-2007, TEAMPEST TF14 farm types only)
EU Region
Farm
Type
All
types
COP
Eastern
Type
Conv
Org
Conv
Org
Conv
Org
Conv
Org
Conv
Org
Conv
Org
Conv
Org
Conv
Org
Conv
Org
Mean
sd
213
1949
19
115
43
33
6
12
84
102
FIELD
5
19
1499
6406
HORT
a
a
236
158
WINE
nd
nd
269
232
ORCH
51
107
nd
nd
OLIVE
nd
nd
167
199
PERM
a
a
57
135
MIXED
12
24
nd=no data, a=data excluded as n<15
Northern
Southern
Western
n
Mean
sd
n
Mean
sd
n
Mean
sd
n
24724
295
195
8
65
5
82
6
1960
109
nd
nd
236
1
nd
nd
1079
a
46
2
1381
149
51
14
87
25
5230
884
nd
nd
322
1
nd
nd
2626
a
115
6
13598
790
219
117
47
12
153
56
1516
628
228
189
348
253
88
38
166
87
140
39
691
225
74
24
230
83
2770
624
269
180
380
269
95
47
359
136
246
88
77305
2230
504
119
109
17
186
20
2699
485
518
170
566
282
a
nd
549
a
165
20
1711
579
51
42
280
60
4811
1582
538
183
439
352
a
nd
1620
a
171
55
31465
906
8732
54
6142
65
2117
14
559
nd
2417
19
nd
nd
346
5
4411
133
6586
307
3694
297
1719
65
nd
nd
386
34
nd
nd
355
2
858
85
12277
279
15974
283
8180
71
8834
187
9454
439
5909
420
6811
218
9866
333
8323
247
6588
211
5533
146
5936
144
2045
61
4
nd
816
6
2220
91
20
Overall CP usage in each EU state is shown in Table 10, spilt by conventional and organic farming methods.
The highest levels of CP costs were in Netherlands, Belgium and Bulgaria. The lowest levels were in the
Baltic states of Lithuania, Estonia and Latvia. The high level of CP usage on organic farms in Belgium
appears to be an anomaly within a small sample and does not reflect usage in similar countries such as the
Netherlands.
Table 10 Mean cp/ha by country (2004-2007, TEAMPEST TF14 farm types only)
Conventional
Country
mean
BEL
BGR
CYP
CZE
DAN
DEU
ELL
ESP
EST
FRA
HUN
IRE
ITA
LTU
LUX
LVA
MLT
NED
OST
POL
POR
ROU
SUO
SVE
SVK
SVN
UKI
873
1285
271
324
200
392
184
218
32
370
185
105
252
26
610
21
423
2211
134
197
64
70
317
128
65
111
265
sd
1899
8082
476
1137
1236
1095
736
726
148
855
644
64
661
44
448
94
1154
5151
155
1474
433
142
2654
759
73
144
963
Organic
mean
n
1941
a
a
40
7
41
131
213
0
178
84
a
73
0
a
2
a
151
23
16
88
a
2
25
31
14
4
1305
1141
1477
2566
3435
10942
13127
20229
790
14548
5459
185
37456
2454
152
1355
769
2558
1960
14042
3794
484
1263
976
1032
453
3140
sd
n
2706
a
a
59
251
116
198
337
0
381
129
a
146
3
a
11
a
1057
42
115
161
a
7
36
43
49
12
28
4
12
18
341
367
168
326
26
214
46
4
1572
106
1
70
3
74
222
207
110
3
73
134
17
39
36
a=data excluded as n<15
Following the data analysis by organic and conventional farming methods, the conventional data was subdivided by CP cost level, utilising quartiles as the cut-off values to define holdings as low (LCP) (quartile 1),
medium (MCP) (between quartile 1 and 3) and high (HCP) (above quartile 3) CP usage in addition to
organic (ORG) data, (as described previously). Data was also split by EU region to take account of the wide
variation in agricultural conditions across the EU, as identified in Table 9.
Table 11 Mean cp/ha by farm type and CP input level (2004-2007)
CP Level
Farm
type
Low (LCP)
mean
COP
FIELD
6
16
sd
5
12
Med (MCP)
n
6907
6426
mean
48
92
sd
20
36
High (HCP)
n
18347
17387
mean
142
345
sd
80
2
Org (ORG)
n
10664
2542
mean
10
25
sd
26
2
n
887
856
21
HORT
WINE
ORCH
OLIVE
PERM
MIXED
60
28
40
9
14
6
47
21
29
8
11
6
4030
2386
3174
1710
1864
3282
689
202
255
61
98
53
440
93
112
27
45
27
8617
8203
6436
3309
3492
8728
5588
778
843
219
552
328
7774
479
414
100
1006
335
4902
4740
4692
894
2972
5345
494
179
242
38
85
25
1140
181
272
47
134
66
296
336
553
420
231
642
TEAMPEST deliverable 7.1 identified that profitability was a significant factor in the farmer’s CP product
decision process. Table 12 displays the profitability (FNVA) of the various farm types at varying CP cost
levels. It can be seen that HORT holdings were by far the most profitable per hectare, whilst the permanent
crop types; PERM and WINE were the next most profitable and COP holdings the least profitable. Organic
holding profitability was lower than HCP holdings but often similar or superior to LCP and MCP holdings,
suggesting potential to move to this type of system. However, in terms of conventional systems, it appears
from this data that increasing CP costs result in increased profitability, and this is studied by farm type in
later sections.
Table 12 Mean fnva/ha by farm type and CP input level (2004-2007)
Farm
type
COP
FIELD
HORT
WINE
ORCH
OLIVE
PERM
MIXED
CP Level
Low
Mean
399
837
27074
1656
2630
1473
3357
1025
sd
962
1682
82310
4228
3544
1434
26444
14229
Med
n
6907
6426
4030
2386
3174
1710
1864
3282
Mean
493
1267
24771
2654
4174
2298
2575
1542
High
sd
2317
1976
54229
4135
4037
1767
4977
2979
n
18347
17387
8617
8203
6436
3309
3492
8728
Mean
712
4238
89683
12649
5767
2522
12943
4072
sd
2648
2
201004
20336
5161
1663
229011
9227
Org
n
10664
2542
4902
4740
4692
894
2972
5345
Mean
375
1012
13149
3134
3510
2364
5181
1235
sd
393
2
29133
4035
3679
1596
45600
2541
2.2.2 ANOVA analysis of CP costs and profitability by farm type
Farm types were briefly assessed for CP costs and profitability (Farm Net Value Added) factors to provide a
simple comparison between farm types. The results of the CP costs analysis indicate that most farm types
were significantly different to each other. COP and OLIVE farms had significantly lower CP costs than
nearly all other types and HORT farms had significantly higher CP costs.
Table 13 CP usage ANOVA analysis at farm type level
COP
COP
FIELD
HORT
WINE
ORCH
OLIVE
PERM
MIXED
n/a
74*
1674*
241*
284*
26*
128*
48*
FIELD
-74*
n/a
1600*
167*
210*
-47*
55*
-26*
HORT
-1674*
-1600*
n/a
-1433*
-1390*
-1647*
-1545*
-1626*
WINE
-241*
-167*
1433*
n/a
43*
-214*
-112*
-193*
ORCH
-284*
-210*
1390*
-43*
n/a
-258*
-156*
-236*
OLIVE
-26*
47*
1647*
214*
258*
n/a
102*
22*
PERM
-128*
-55*
1545*
112*
156*
-102*
n/a
-80*
MIXED
-48*
26*
1626*
193*
236*
-22*
80*
n/a
*. The mean difference is significant at the 0.05 level.
HORT farms were statistically the most profitable, whilst COP farms were the least profitable. More detailed
ANOVA analysis is presented in the separate farm type sections subsequently.
22
n
887
856
296
336
553
420
231
642
Table 14 FNVA ANOVA analysis at farm type level
COP
COP
FIELD
HORT
WINE
ORCH
OLIVE
PERM
MIXED
n/a
1362*
40541*
4355*
3641*
1633*
4832*
1502*
FIELD
-1362*
n/a
39179*
2994*
2280*
271*
3471
140
HORT
-40541*
-39179*
n/a
-36185*
-36899*
-38908*
-35709*
-39039*
WINE
ORCH
-4355*
-2994*
36185*
n/a
-714*
-2723*
477
-2853*
-3641*
-2280*
36899*
714*
n/a
-2009*
1191
-2139*
OLIVE
PERM
-1633*
-271*
38908*
2723*
2009*
n/a
3200
-131
MIXED
-4832*
-3471
35709*
-477
-1191
-3200
n/a
-3330
-1502*
-140
39039*
2853*
2139*
131
3330
n/a
*. The mean difference is significant at the 0.05 level.
2.2.3 Correlations of CP costs and other factors by farm type
CP costs were then assessed by splitting the data into farm type, with various parameters assessed including
CP, fertiliser and other crop cost inputs, profitability indicated by FNVA and Family Farm Income and
wheat yield as a physical output, and fixed factors such as farm physical size, economic size and labour input.
Bi-variate correlations identified fertiliser as the most closely correlated variable, though the profitability
measures and wheat yield were also closely correlated in some farm types. Most variables were positively
correlated, though farm area was negatively correlated for many farm types indicating an increase in CP
costs per hectare with smaller farm area. More detailed correlations for each farm type are presented
subsequently.
Table 15 Correlations of CP/ha with other variables by farm type
Fert
CP level
Other
crop
costs
Net
value
added
Gross
farm inc.
All types
COP
FIELD
HORT
WINE
ORCH
OLIVE
PERM
MIXED
.654**
.303**
.334**
.374**
.205**
.240**
.737**
.478**
.272**
.637**
.261**
.411**
.469**
.072**
.624**
.442**
.169**
.311**
.375**
.030*
.188**
.427**
.512**
.081**
.614**
.210**
.286**
**. Correlation is significant at the 0.01 level (2-tailed)
*. Correlation is significant at the 0.05 level (2-tailed)
a. Data not shown as sample <15 farms
.381**
.265**
.300**
.441**
.651**
.380**
.206**
.103**
.311**
Wheat
Yield
(t/ha)
.289**
.495**
.342**
.204**
.308**
.356**
.587**
.337**
.264**
Land
area
Econ.
Size
-.036**
.082**
-.023**
-.049**
-.146**
-.061**
-.082**
-.052**
-.030**
.100**
.240**
.066**
.087**
.210**
.133**
-.034**
.065**
.059**
Labour
.137**
.071**
.112**
.175**
.111**
.175**
.133**
.154**
.043**
2.2.4 Cereals, Oilseeds and Pulses (COP)
COP farms exhibited a wide range of CP usage within the same farm type, which was reflected in other crop
inputs. CP usage ranged from a LCP average of €6/ha through to €142/ha in the HCP group. Southern
Europe had the highest overall CP usage in the HCP group, though the standard deviation was large
indicating variability. Fertiliser costs were higher overall for all farms, the average for each group ranging
from €55/ha to €160/ha. It could be possible that crop yield is more dependent on fertiliser usage at lower
levels of intensity, but as fertiliser costs increase CP costs increase rapidly to reach a similar cost level per
hectare.
23
Table 16 COP crop inputs (€ per hectare)
CP
level
LCP
MCP
HCP
ORG
EU
region
All EU
East
North
South
West
All EU
East
North
South
West
All EU
East
North
South
West
All EU
East
North
South
West
CP
mean
6
8
9
5
7
48
44
48
45
62
142
117
133
158
138
10
6
5
12
17
Fert.
sd
5
6
5
5
6
20
18
20
19
18
80
38
37
132
40
26
12
14
24
42
mean
55
48
54
57
50
102
82
91
118
105
160
135
118
214
143
33
20
19
50
35
Other Crop Costs
sd
40
39
40
40
50
63
44
42
77
48
279
59
41
497
47
50
26
37
53
58
mean
4
3
12
3
2
11
5
19
14
3
36
7
29
100
3
13
3
22
4
14
sd
n
18
9
23
18
8
33
17
30
43
12
564
21
47
1021
13
29
11
35
13
36
6907
1021
1110
4646
130
18347
6369
3866
5507
2605
10664
1342
1610
2124
5588
887
54
307
279
247
COP farm profitability, indicated by GFI and FNVA per hectare increases with increased level of CP costs.
Profitability was highest in Southern Europe (despite a lower wheat yield), as were CP costs, possibly
reflecting a difference in farm type in that region (possibly cereals and permanent crops resulting in a higher
profit). Organic farm profitability was highest in the Western region at a higher level than Western
conventional COP farms, though organic profitability was lower than conventional farms in other regions.
Wheat yields were highest on Northern HCP cost farms; the lowest conventional yields were in Southern and
Eastern Europe. The high CP costs group’s wheat yield was 109% higher than the LCP cost group, though
CP costs were 2267% higher. Organic farm yields were similar to LCP yields at 3.5t/ha.
Table 17 COP profitability and wheat yield (€/ha and t/ha)
CP
level
LCP
MCP
HCP
EU
region
All EU
East
North
South
West
All EU
East
North
South
West
All EU
East
North
Gross Farm Inc.
Net Value Added
mean
mean
520
342
568
554
448
698
381
610
966
569
967
444
630
sd
1078
318
2696
860
375
2378
261
1509
3433
405
2816
297
1073
399
208
389
443
269
493
260
387
710
372
712
282
433
sd
962
249
2333
791
403
2317
250
1287
3378
349
2648
317
924
Wheat yield (t)
n
6907
1021
1110
4646
130
18347
6369
3866
5507
2605
10664
1342
1610
mean
3.3
3.2
3.5
3.3
4.9
4.9
4.2
5.5
4.7
5.9
6.9
5.4
7.7
sd
n
1.5
1.6
1.7
1.4
2.0
1.9
1.6
1.9
1.9
1.5
1.7
1.3
1.7
3215
836
839
1449
91
12906
5629
3274
1823
2180
8613
1262
1536
24
ORG
South
West
All EU
East
North
South
West
1753
648
564
340
402
598
821
4955
327
407
203
309
417
419
1363
447
375
220
224
445
545
4684
321
393
220
333
407
396
5.4
7.2
3.5
2.9
3.6
2.4
3.8
2124
5588
887
54
307
279
247
1.7
1.5
1.6
1.1
1.6
1.2
1.7
523
5292
514
43
196
55
220
The HCP cost farms were the largest for all regions except the South which had the smallest farms (tending
to indicate that Southern COP farms may be different in nature to other regions). Northern and Western
region farms within the HCP cost group were the largest economically, but Eastern region farms had the
highest labour input.
Table 18 COP area, economic size and labour input (UAA ha, ESU/farm, AWU/farm)
CP
level
LCP
MCP
HCP
ORG
EU
region
All EU
East
North
South
West
All EU
East
North
South
West
All EU
East
North
South
West
All EU
East
North
South
West
Land area
mean
61
54
69
62
59
57
67
91
27
97
102
138
156
20
132
80
81
83
59
104
sd
116
170
91
105
47
142
215
132
40
160
175
344
181
38
173
110
213
92
77
129
Econ. Size
mean
17
10
15
18
27
24
16
38
15
55
67
41
102
20
89
29
15
28
21
46
sd
27
30
18
28
22
49
49
50
24
80
101
106
124
43
106
40
43
30
39
49
Labour
mean
1.0
1.7
1.2
0.9
1.3
1.2
1.7
1.1
0.9
1.4
1.5
2.7
1.5
1.0
1.6
1.3
2.3
1.1
1.0
1.6
sd
n
1.6
3.6
1.4
0.5
0.6
2.4
4.2
1.7
0.6
1.5
2.3
7.0
1.6
1.2
1.6
1.8
5.4
1.5
0.8
1.4
6907
1021
1110
4646
130
18347
6369
3866
5507
2605
10664
1342
1610
2124
5588
887
54
307
279
247
25
Table 19 indicates differences between CP cost levels for various factors listed on the left of the table. CP
input differences indicated significantly different levels of CP costs between each group, which was the same
for fertiliser and similar for other crop costs. Profitability was significantly different between MCP, HCP and
ORG farms, but not significantly different between organic and LCP farms.
Farm physical size was significantly different for both HCP and ORG farms, but not significantly different
between LCP and MCP farms. The economic sizes of all farm types were significantly different, with the
high input farms the largest. Labour input was also significantly different for most farm types, though MCP
and ORG farms were identical.
26
Table 19 COP ANOVA analysis of inputs, profitability and fixed factors at different CP input levels
CP Level comparison
Factor
Low
Med
High
Med
Org
Low
High
High
Org
-41*
-136*
-4*
41*
-94*
37*
CP
-47*
-105*
22*
47*
-58*
69*
FERT
-7*
-32*
-9*
7*
-26*
-2
OCC
-178*
-447*
-44
178*
-269*
134*
GFI
-94*
-313*
23
94*
-219*
118*
FNVA
5
-41*
-18*
-5
-45*
-23*
UAA
-7*
-50*
-12*
7*
-43*
-5*
ESU
-.15*
-.42*
-.21*
.15*
-.27*
0
AWU
*. The mean difference is significant at the 0.05 level.
Org
Low
Med
Org
Low
Med
High
136*
105*
32*
447*
313*
41*
50*
.42*
94*
58*
26*
269*
219*
45*
43*
.27*
132*
127*
24*
403*
336*
22*
38*
.20*
4*
-22*
9*
44
-23
18*
12*
.21*
-37*
-69*
2
-134*
-118*
23*
5*
0
-132*
-127*
-24*
-403*
-336*
-22*
-38*
-.20*
Table 20 highlights differences in CP costs and profitability of farms differing by CP cost level and EU
region. Although there was little difference between LCP holdings, average CP cost per hectare was
significantly lower for Southern region farms. All but Eastern and Southern region holdings were
significantly different for MCP farms and all HCP EU regions were different. For the organic holdings CP
costs were similar in the North and East and in the South and West.
For profitability (FNVA), the greatest range in profitability for conventional farms was between Southern
and other regions within the HCP group, though smaller, often significant differences were also seen
between other regions. The Western region farms were the most profitable for the organic farms, being
significantly higher than other regions.
Table 20 COP ANOVA analysis of differences in CP input and profitability at different CP input
levels across EU regions
EU region comparison
CP
Variable
level
East
North
West
East
South
West
South
West
East
North
West
East
North
South
LCP
0
3*
1
0
3*
MCP
-3*
-1
-17*
3*
2*
HCP
-16*
-41*
-20*
16*
-25*
ORG
0
-6*
-11*
0
-6*
Net
LCP
-181
-235*
-61
181
-54
value
MCP -127*
-450* -112* 127* -323*
added
HCP
-151* -1080* -165* 151* -930*
ORG
-4
-225* -325*
4 -221*
*. The mean difference is significant at the 0.05 level.
1
-14*
-5*
-12*
120
15
-14
-321*
-3*
1
41*
6*
235*
450*
1080*
225*
-3*
-2*
25*
6*
54
323*
930*
221*
-2*
-17*
20*
-5
174*
338*
916*
-100*
-1
17*
20*
11*
61
112*
165*
325*
-1
14*
5*
12*
-120
-15
14
321*
2*
17*
-20*
5
-174*
-338*
-916*
100*
CP per
ha
South
North
It can be seen from Table 21 that fertiliser and wheat showed the best correlation with CP costs, as would be
expected from data in
27
Table 16 and Table 17. In general, the correlation with profitability was poor and insignificant. Land area,
economic size and labour were significantly correlated for some groups, and in particular for Northern region
holdings.
Table 21 COP correlations of CP/ha with other variables in EU regions
Fert
CP level
EU reg
Other
crop
costs
Net
value
added
LCP
East
0.02
0.06
0.02
North
.212**
0.06
-0.01
South
.232**
0.00
-.064**
West
.176*
0.07
.215*
MCP
East
.397**
0.01
.091**
North
.174**
.130**
.035*
South
.318**
.117**
0.02
West
.294**
-0.03
0.03
HCP
East
.111**
0.01
0.01
North
.204**
-0.01
0.03
South
.306**
.303**
.573**
West
.231**
.075**
.076**
ORG
East
.359**
0.22
0.16
North
.758**
.213**
0.09
South
.427**
0.07
.139*
West
.777**
-0.04
0.09
**. Correlation is significant at the 0.01 level (2-tailed)
*. Correlation is significant at the 0.05 level (2-tailed)
a. Data not shown as sample <15
Gross
farm
inc.
Wheat
Yield
(t/ha)
.113**
0.00
-.034*
0.09
.119**
0.03
.036**
0.03
.082**
0.01
.594**
.114**
0.12
.127*
.362**
0.06
.198**
.152**
.152**
0.00
.177**
.464**
.254**
.289**
.058*
.213**
-.096*
.284**
0.21
.585**
.345**
.673**
Land
area
Econ.
Size
0.00
0.02
-.070**
.224*
.039**
.080**
-.105**
.073**
-0.02
.143**
-0.01
0.00
0.27
.324**
-.141*
-0.06
0.02
.089**
-0.03
0.10
.076**
.254**
.038**
.150**
-0.02
.185**
0.02
.029*
.355**
.298**
0.04
0.08
Labour
-.062*
-0.02
-.072**
0.11
.033**
.038*
.061**
.053**
-0.01
.125**
.245**
0.01
0.22
0.06
0.03
0.07
2.2.5 Other fieldcrops (FIELD)
FIELD farms exhibited a wider range of CP usage within the same farm type than COP farms; CP usage
ranging from a low average of €16/ha through to €345/ha in the HCP group. As with COP farms, Southern
Europe had the highest overall CP usage in the HCP group, though the standard deviation was large
indicating variability. Fertiliser costs were higher than CP costs for LCP groups but lower than CP costs for
the HCP groups, the average ranging from €68/ha to €289/ha. Other crop costs were also higher for FIELD
type farms, reflecting the greater importance of CP and other crop costs for FIELD farms.
Table 22 FIELD crop inputs (€ per hectare)
CP
level
LCP
MCP
HCP
EU
region
All EU
East
North
South
West
All EU
East
North
South
West
All EU
East
North
South
CP
mean
16
19
12
16
17
92
79
91
92
110
345
286
258
372
Fert.
sd
12
11
12
12
13
36
32
34
36
34
92
178
129
333
mean
68
61
57
74
75
139
126
118
153
131
289
299
159
320
Other Crop Costs
sd
66
47
55
76
59
86
84
56
95
59
340
269
74
283
mean
18
16
19
17
57
42
43
50
45
25
144
102
155
148
sd
66
44
48
65
194
159
97
65
188
179
697
172
270
543
n
6426
1422
1107
3649
248
17387
4196
2239
7348
3604
8585
524
348
4977
28
ORG
West
All EU
East
North
South
West
312
25
5
6
56
20
411
60
19
25
83
60
217
61
15
18
121
71
489
115
23
38
162
107
153
51
88
20
35
96
1134
112
134
26
107
156
2736
856
65
297
283
211
Profitability, indicated by GFI and FNVA per hectare increased with higher levels of CP costs, and organic
farm profitability between LCP and MCP conventional holdings. Profitability of FIELD farms was also
highest in Southern Europe (despite a lower wheat yield), again indicating a possible difference in farm type
in that region. Overall, Northern region farms were the least profitable, despite wheat yields being higher
than average and equalling the Western region average yield of 8.1t/ha.
Table 23 FIELD profitability and wheat yield (€/ha and t/ha)
CP level
CP level
LCP
Low
MCP
Med
HCP
High
ORG
Organic
EU region
All EU
East
North
South
West
All EU
East
North
South
West
All EU
East
North
South
West
All EU
East
North
South
West
Gross Farm Inc.
Net Value Added
mean
mean
sd
1093
825
649
1309
1121
1604
1235
730
2095
1184
4914
3409
1353
6234
2524
1345
1429
500
1551
2273
1766
1307
2099
1873
1643
2068
1270
876
2543
1546
16654
2526
1344
20609
5321
1621
996
423
1544
2379
837
628
435
1019
819
1267
966
491
1689
894
4238
2891
1015
5480
1937
1012
1142
297
1153
1806
Wheat yield (t)
sd
n
1682
1280
1820
1818
1444
1976
1207
742
2468
1407
16337
2531
1236
20280
4611
1464
901
406
1390
2189
6426
1422
1107
3649
248
1766
4196
2239
7348
3604
8585
524
348
4977
2736
856
65
297
283
211
mean
3.9
3.8
4.2
3.7
5.7
5.6
4.6
7.0
4.4
7.3
7.0
4.6
8.1
4.7
8.1
3.7
2.9
3.5
3.9
4.1
sd
1.6
1.2
2.0
1.7
2.1
2.7
1.4
1.9
4.2
1.8
2.3
1.7
1.9
1.8
1.6
1.6
1.3
1.5
1.8
1.6
n
2670
1042
607
846
175
10331
3487
1792
1896
3156
3397
249
260
703
2185
421
40
141
62
178
The organic farms were the largest in terms of land area, though the HCP group were the largest
economically. In particular, Northern HCP farms were larger physically, economically and in labour
requirement per farm than other regions.
Table 24 FIELD area, economic size and labour input (UAA ha, ESU/farm, AWU/farm)
CP
level
LCP
MCP
EU
region
All EU
East
North
South
West
All EU
East
North
South
Land area
mean
29
21
53
27
57
44
33
122
17
sd
64
76
80
47
116
134
159
191
38
Econ. Size
mean
17
8
18
20
44
39
15
98
23
sd
38
34
28
36
92
106
76
150
59
Labour
mean
1.3
1.7
1.3
1.0
1.5
1.7
2.4
1.7
1.2
sd
n
1.7
2.5
1.9
0.9
1.7
3.1
4.7
3.3
1.3
6426
1422
1107
3649
248
17387
4196
2239
7348
29
HCP
ORG
West
All EU
East
North
South
West
All EU
East
North
South
West
101
35
16
207
11
87
52
18
66
47
61
195
89
87
294
31
82
87
36
92
107
58
97
58
11
278
30
124
42
7
35
42
73
177
135
63
423
95
111
76
22
57
89
90
1.9
2.1
3.5
4.0
1.6
2.4
1.6
2.5
1.1
1.4
2.1
3.5
2.9
5.1
4.6
2.1
2.6
1.9
3.2
1.7
1.2
1.6
3604
8585
524
348
4977
2736
856
65
297
283
211
Table 25 indicates differences between CP cost levels for various factors listed on the left of the table. As
expected, CP input was significantly different between each group. Fertiliser costs were similar for LCP and
ORG farms, but MCP and HCP fertiliser use was significantly higher. ORG farm other crop costs were
significantly higher than LCP farms, similar to MCP but significantly less than HCP holdings. Profitability
was significantly different between all farm groups; LCP the lowest and HCP the highest.
Farm physical size was significantly different for all groups, the ORG farms being the largest and LCP farms
the smallest. Both economic size and labour input were similar for MCP and ORG groups, but LCP farms
were significantly lower and HCP farms were significantly larger.
Table 25 FIELD ANOVA analysis of inputs, profitability and fixed factors at different CP input levels
CP Level comparison
Factor
Low
Med
High
Med
Org
Low
High
High
Org
-75*
-329*
-8*
75*
-254*
67*
CP
-71*
-220*
7
71*
-150*
78*
Fert
-24*
-127*
-33*
24*
-103*
-9
OCC
-511* -3822* -252* 511* -3311* 259*
GFI
-430* -3401* -174* 430* -2971* 255*
FNVA
-15*
-7*
-24*
15*
8*
-9*
UAA
-22*
-41*
-25*
22*
-19*
-3
ESU
AWU
-.39*
-.83* -.33*
.39*
-.44*
0
*. The mean difference is significant at the 0.05 level.
Org
Low
Med
Org
Low
Med
High
329*
220*
127*
3822*
3401*
7*
41*
.83*
254*
150*
103*
3311*
2971*
-8*
19*
.44*
320*
228*
94*
3570*
3227*
-17*
16*
.50*
8*
-7
33*
252*
174*
24*
25*
.33*
-67*
-78*
9
-259*
-255*
9*
3
0
-320*
-228*
-94*
-3570*
-3227*
17*
-16*
-.50*
Table 26 highlights differences in CP costs and profitability of farms differing by CP cost level and EU
region. Although there was little difference between LCP cost holdings, average CP cost per hectare was
higher for Eastern region farms and lower for Northern farms. Within the MCP group, Western region
holding CP costs were significantly higher than other regions, though within the HCP and ORG groups
Southern EU holdings had significantly higher CP costs.
For profitability (FNVA), the greatest range in profitability for conventional farms was between Southern
and other regions, though smaller but significant differences were also seen between other regions. As with
COP farms, the Western region FIELD farms were the most profitable for the organic farms, being
significantly higher than other regions, and Northern farms being the least profitable.
Table 26 FIELD ANOVA analysis of differences in CP input and profitability at different CP input
levels across EU regions
EU region comparison
CP
Variable
level
CP per
LCP
East
North
North
South
West
7*
4*
2
East
-7*
South
West
South
West
East
North
West
East
North
South
-3*
-5*
-4*
3*
-2
-2
5*
2
30
ha
-12*
-13*
-31*
12*
-1
MCP
28*
-86*
-25
-28*
-114*
HCP
-1
-51*
-15*
1
-50*
ORG
193*
-390*
-191
-193*
-584*
Net
LCP
value
475*
-723*
72
-475* -1198*
MCP
added
1876*
-2590*
953*
-1876*
-4465*
HCP
845*
-11 -664*
-845*
-856*
ORG
*. The mean difference is significant at the 0.05 level.
-19*
-54*
-14*
-384*
-403*
-922*
-1509*
13*
86*
51*
390*
723*
2590*
11
1
114*
50*
584*
1198*
4465*
856*
-17*
60*
36*
200
795*
3543*
-653*
31*
25
15*
191
-72
-953*
664*
19*
54*
14*
384*
403*
922*
1509*
17*
-60*
-36*
-200
-795*
-3543*
653*
Correlations in Table 27 show that fertiliser and wheat showed the best correlation with CP costs,
particularly for ORG farms and Western region HCP farms. Correlation with profitability was generally poor
for most groups, but Western and Northern HCP correlation with CP costs was high and significant. Other
factors had poor correlation though some groups were significant.
Table 27 FIELD correlations of CP/ha with other variables in EU regions
Other
crop
costs
Fert
CP level
EU reg
Net
value
added
LCP
East
.331**
.056*
-0.02
North
.259**
.164**
0.01
South
.146**
.066**
-0.01
West
0.10
-.180**
-.160*
MCP
East
.392**
.232**
.185**
North
.158**
.159**
.089**
South
.254**
.084**
.119**
West
.310**
0.00
.036*
HCP
East
.346**
-0.03
.133**
North
.254**
.313**
.588**
South
.632**
.256**
.194**
West
.916**
.895**
.823**
ORG
East
.788**
-0.03
-0.10
North
.768**
.170**
.177**
South
.762**
0.10
-0.06
West
.421**
0.04
.173*
**. Correlation is significant at the 0.01 level (2-tailed)
*. Correlation is significant at the 0.05 level (2-tailed)
a. Data not shown as sample <15
Gross
farm
inc.
0.01
0.02
0.01
-.141*
.224**
.089**
.128**
0.03
.147**
.607**
.215**
.830**
-0.09
.232**
0.06
.182**
Wheat
Yield
(t/ha)
.158**
.292**
.131**
-0.02
.188**
.358**
.051*
.396**
0.12
.219**
-0.05
0.00
.369*
.526**
0.15
.443**
Land
area
Econ.
Size
0.00
.126**
-.054**
0.09
.054**
.129**
-.040**
.058**
-0.05
-0.03
-.055**
-.137**
0.18
.315**
-.117*
-0.05
0.02
.208**
-0.01
0.06
.067**
.265**
.049**
.117**
-0.03
0.04
0.01
-.075**
.362**
.345**
0.01
0.08
Labour
0.01
.074*
-.039*
0.04
.105**
.043*
.091**
0.03
.192**
.149**
.167**
.181**
0.22
.281**
0.10
0.09
2.2.6 Horticulture (HORT)
HORT farms had the widest range of CP usage within the same farm type, ranging from a LCP average of
€60/ha through to €5588/ha for the HCP group. Northern and Eastern Europe had the highest overall CP
usage within the HCP group, but with large standard deviations indicating variability. Fertiliser costs were
higher than CP costs for all groups, the average ranging from €707/ha to €7625/ha, with extremely high costs
for Northern region farms. Other crop costs were also extremely high for HORT type farms, the average for
Northern region farms at €66,998/ha within the HCP group. ORG farm costs were most similar to MCP
farms and varied considerably between regions.
Table 28 HORT crop inputs (€ per hectare)
CP
level
LCP
EU
reg
All EU
East
North
CP
mean
60
68
27
Fert.
sd
47
40
41
mean
707
240
2076
Other Crop Costs
sd
mean
sd
n
4871
572
8454
8137
622
63258
52996
4726
151942
4030
737
624
31
South
62
48
West
54
54
MCP
All EU
689
440
East
611
440
North
598
431
South
701
428
West
765
456
HCP
All EU
5588
7774
East
7098 14432
North
7962
8547
South
4556
4259
West
6183
6481
ORG
All EU
494
1140
East
a
a
North
109
884
South
628
624
West
485
1582
a. Data not shown as sample <15
464
2040
1571
1657
4781
1084
2557
7625
9981
21506
5758
7502
1265
a
192
1560
1287
1976
11839
4044
2732
10107
1595
7541
17001
32425
20068
10490
10083
2489
a
868
1256
3574
1266
9193
3938
2822
20523
2049
9202
17252
14713
66998
6566
30503
2175
a
742
884
4058
7128
29086
17091
6167
54769
14098
23194
49330
32655
107906
26081
65374
10649
a
2585
4847
15700
1892
777
8617
985
479
4385
2768
4902
395
616
1903
1988
296
14
65
71
146
Profitability (GFI and FNVA) per hectare was highest within the HCP group at €112,994/ha and lowest for
the ORG group. Northern and Western region HORT holdings were the most profitable, but also had the
highest costs seen in Table 28 above. Wheat yield was a less clear indicator of farm performance for HORT
holdings as the majority of holdings did not grow wheat, particularly within the HCP group.
Table 29 HORT profitability and wheat yield (€/ha and t/ha)
CP
level
LCP
EU
region
Gross Farm Inc.
Net Value Added
mean
mean
sd
n
27074
3214
97828
18207
78902
24771
12470
45280
19153
55308
89683
72130
228041
53735
143912
13149
a
6706
12790
16748
82310
9163
165608
38136
150966
54229
25775
73463
30245
101986
201004
150970
221508
101051
308841
29133
a
32733
20024
37469
4030
737
624
1892
777
8617
985
479
4385
2768
4902
395
616
1903
1988
296
14
65
71
146
sd
All EU
32419
95362
East
4227
9998
North
119942 192999
South
20872
45095
West
94366 168641
MCP
All EU
30644
61597
East
18326
33210
North
53547
83386
South
22592
32134
West
68167 115415
HCP
All EU
112994 228159
East
94466 174888
North
274903 246468
South
62585 106099
West
190167 349283
ORG
All EU
16668
36558
East
a
a
North
8191
38488
South
15230
23244
West
22014
48388
a. Data not shown as sample <15
Wheat yield (t)
mean
3.7
3.4
4.4
3.8
5.1
4.6
3.6
7.5
3.9
6.3
4.8
a
a
a
a
3.4
a
2.5
a
4.1
sd
n
1.6
1.4
2.2
1.4
1.7
2.2
1.8
1.3
1.4
2.2
2.3
a
a
a
a
1.6
a
1.3
a
1.5
549
237
61
132
119
587
143
71
63
310
10
4
2
1
3
45
3
15
2
25
The LCP and ORG farms were the largest in terms of land area, though the HCP group were the largest
economically. Overall, Northern and Western HCP farms were larger physically, economically and had
greater labour input than other regions. ORG farms had a similar area to LCP but were economically more
equivalent to MCP farms.
32
Table 30 HORT area, economic size and labour input (UAA ha, ESU/farm, AWU/farm)
CP
level
EU
reg
Land area
mean
sd
Econ. Size
mean
LCP
All EU
8
33
East
7
46
North
11
23
South
8
21
West
10
25
MCP
All EU
5
26
East
3
21
North
31 151
South
4
9
West
9
18
HCP
All EU
2
5
East
1
1
North
1
2
South
2
5
West
2
6
ORG
All EU
8
22
East
a
a
North
17
21
South
3
29
West
11
14
a. Data not shown as sample <15
42
16
68
36
135
69
18
364
45
171
109
19
298
46
247
62
a
48
30
108
Labour
sd
mean
127
70
135
84
283
233
67
1036
118
320
251
25
473
161
327
208
a
71
258
178
2.4
2.2
3.4
2.2
3.6
2.9
2.8
9.8
2.3
4.3
4.4
4.1
9.8
2.9
6.6
2.7
a
2.6
1.7
3.8
sd
n
4.3
5.9
4.2
2.5
3.7
5.6
6.6
21.2
3.5
4.5
7.1
5.7
15.9
4.5
8.4
3.6
a
2.1
2.9
4.4
4030
737
624
1892
777
8617
985
479
4385
2768
4902
395
616
1903
1988
296
14
65
71
146
An ANOVA analysis of CP cost levels for various factors is shown in Table 31 below, which indicates that
CP input was significantly different between each group. Fertiliser costs were significantly different between
all groups except for MCP and ORG farms and other crop costs were all significantly different. Profitability
of HCP farms was significantly higher than other groups and ORG profitability was significantly lower than
other groups, with no significant difference between LCP and MCP farms. HCP farms were significantly
physically smaller but larger economically and for labour input. Although LCP and MCP farms were
significantly different for the three size measures, neither was statistically different to the ORG farms.
Table 31 HORT ANOVA analysis of inputs, profitability and fixed factors at different CP input levels
CP Level comparison
Factor
Low
Med
High
Med
Org
Low
High
High
Org
CP
-629*
-5529*
-434*
629*
-4899*
195*
Fert
-864*
-6918*
-558*
864*
-6053*
307
OCC
4199*
-9115*
5962* -4199*
-13314*
1763*
GFI
1775
-80575* 15750*
-1775
-82350* 13975*
FNVA
2302
-62609* 13925*
-2302
-64911* 11622*
UAA
3*
6*
1
-3*
3*
-2
ESU
-26*
-67*
-20
26*
-40*
6
AWU
-.48*
-1.99*
-0.21
.48*
-1.51*
0.27
*. The mean difference is significant at the 0.05 level.
Org
Low
Med
Org
Low
5529*
6918*
4899*
6053*
5095*
6360*
434*
558*
9115*
80575*
62609*
-6*
67*
1.99*
13314*
82350*
64911*
-3*
40*
1.51*
15077*
96326*
76534*
-6*
47*
1.78*
-5962*
-15750*
-13925*
0
20
0.21
Med
High
-195*
-307
-5095*
-6360*
-1763*
-15077*
-96326*
-76534*
6*
-47*
-1.78*
-13975*
-11622*
2
-6
-0.27
33
Table 32 highlights differences in CP by cost level and EU region, and indicates that CP use on LCP
holdings significantly varied across the EU, with the highest use in the Eastern region. For MCP holdings the
Western region average CP cost per hectare was higher than other areas and lowest for Northern farms.
Within the MCP group, Western region holding CP costs were significantly higher than other regions,
though for the HCP group, Southern holdings used significantly less than other areas and ORG groups
showed insignificant differences in CP costs except CP for Northern and Southern regions.
In general, conventional Northern region holdings were significantly more profitable (FNVA) than other
regions, with large differences to Southern and Eastern regions. Western ORG farms were the most
profitable, but only significantly with Eastern ORG farms.
34
Table 32 HORT ANOVA analysis of differences in CP input and profitability (FNVA) at different CP
input levels across EU regions
EU region comparison
CP
level
East
North
South
North
West
East
CP
South
41*
5*
14*
-41*
LCP
13
-90*
-155*
-13
MCP
-864
2542*
915
864
HCP
78
-442
-298
-78
ORG
-94614*
-14993*
-75688*
94614*
FNVA LCP
-32810*
-6683*
-42838*
32810*
MCP
-155911*
18395
-71782*
155911*
HCP
-4030
-10114*
-14071*
4030
ORG
*. The mean difference is significant at the 0.05 level.
South
West
East
-27*
-168*
1779*
-376
-5*
90*
-2542*
442
79621*
18926
26128*
-10027
174306*
-6084
-35*
-103*
3406*
-520*
North
West
West
East
North
South
35*
103*
-3406*
520*
8*
-64*
-1627*
144
-14*
155*
-915
298
27*
168*
-1779*
376
-8*
64*
1627*
-144
14993*
-79621*
-60695*
75688*
-18926
60695*
6683*
-26128*
-36155*
42838*
10027
36155*
84130*
-18395
-174306*
-90176*
71782*
-84130*
90176*
-10042
10114*
6084
-3957
14071*
10042
3957
Correlations below show that fertiliser and profitability showed the best correlation with CP costs. HCP
regions showed a significant level of correlation, in part due to the high level of CP costs as a percentage of
total costs. Correlations were significant but less important at lower CP level groups and variable for the
ORG group due to small samples. Weak correlations with land area may indicate an increase in CP costs per
hectare on smaller holdings.
Table 33 HORT correlations of CP/ha with other variables in EU regions
Fert
CP level
EU reg
LCP
Other
crop
costs
Net
value
added
East
.110**
-0.01
0.07
North
-.135**
-.268**
-.360**
South
-.123**
-.191**
-.168**
West
-0.07
-.182**
-.328**
MCP
East
.436**
.375**
.359**
North
.307**
.176**
.379**
South
.310**
.086**
.202**
West
.124**
.190**
.214**
HCP
East
.816**
.530**
.565**
North
.112**
.191**
.303**
South
.590**
.307**
.392**
West
.232**
.465**
.470**
ORG
East
a
a
a
North
.973**
.879**
.980**
South
.642**
-0.09
0.18
West
.558**
0.16
.460**
**. Correlation is significant at the 0.01 level (2-tailed)
*. Correlation is significant at the 0.05 level (2-tailed)
a. Data not shown as sample <15
Gross
farm
inc.
Wheat
Yield
(t/ha)
Land
area
0.06
-.380**
-.177**
-.351**
.398**
.387**
.228**
.239**
.571**
.315**
.420**
.519**
a
.982**
0.12
.512**
.223**
.741**
.192*
0.13
.274**
-0.06
0.12
0.18
0.51
-1.000**
.a
0.12
0.88
0.38
1.000**
0.10
0.04
.304**
-0.04
.303**
-.067*
-.093*
-.126**
-.201**
-.133**
-.125**
-.076**
-.077**
a
-0.08
-0.02
-0.14
Econ.
Size
0.05
0.03
-0.01
.115**
0.01
.120**
0.01
.047*
-.106*
-0.01
-0.03
.165**
a
.439**
0.03
.311**
Labour
0.03
.129*
0.03
0.16
.063**
.388**
.065**
.064*
-0.03
0.01
0.02
0.00
0.06
0.07
.384**
.451**
2.2.7 Wine (WINE)
There was a large range in CP costs between LCP and HCP holdings, with ORG CP costs similar to MCP
costs. Fertiliser and other crop costs were very varied though generally increasing with CP costs. (Please
note there were no wine holdings in the Northern region).
35
Table 34 WINE crop inputs (€ per hectare)
CP
level
EU
region
CP
mean
Fert.
sd
All
28
21
East
29
22
South
27
20
West
33
25
All
MCP
202
93
East
184
88
South
194
93
West
228
89
All
HCP
778 479
East
496 116
South
660 311
West
940 600
All
ORG
179 181
East
a
a
South
189 180
West
170 183
a. Data not shown as sample <15
LCP
mean
78
34
75
131
121
44
141
82
275
56
257
309
82
a
104
59
Other Crop Costs
sd
96
58
84
203
120
126
122
93
384
82
235
517
107
a
107
103
mean
41
33
31
197
253
1188
151
349
930
275
1214
609
511
a
364
684
sd
n
297
151
256
661
1539
5681
851
1010
9429
952
12706
1567
1357
a
996
1685
2386
47
2073
266
8203
383
4684
3136
4740
129
2077
2534
336
5
187
144
Profitability was highest for HCP holdings in the Western region, though large variability existed as
indicated by the high standard deviation value. Interestingly Western LCP holdings achieved a higher
profitability than MCP holdings. ORG holding performance was similar to the conventional MCP group.
Table 35 WINE profitability and wheat yield (€/ha and t/ha)
CP
level
LCP
EU
region
Gross Farm Inc.
mean
sd
All
2108
4886
East
2891
8186
South
1680
3025
West
8847 14376
MCP
All
3529
4444
East
2964
6563
South
3353
3273
West
4089
6210
HCP
All
15141 21915
East
2184
3294
South
6965
8297
West
26090 28440
ORG
All
4123
4544
East
a
a
South
4084
4005
West
4113
5135
a. Data not shown as sample <15
Net Value
Added
Wheat yield (t)
mean
sd
n
1656
1121
1320
7046
2654
2279
2484
3164
12649
1332
5171
22636
3134
a
3136
3072
4228
8586
2865
11685
4135
6360
3124
5619
20336
3048
8310
26281
4035
a
3855
4259
2386
47
2073
266
8203
383
4684
3136
4740
129
2077
2534
336
5
187
144
mean
3.8
3.0
3.7
4.0
5.1
3.2
4.7
5.5
6.0
a
6.4
5.9
3.3
nd
a
3.3
sd
n
1.9
1.4
2.3
1.3
1.8
1.9
1.6
1.8
1.9
a
1.9
1.8
1.5
nd
a
1.3
192
14
91
87
1104
38
393
673
112
1
33
78
52
0
8
44
The area of WINE holdings was largest for LCP and ORG holdings, whilst the HCP group were the largest
economically and for labour requirements.
36
Table 36 WINE area, economic size and labour input (UAA ha, ESU/farm, AWU/farm)
CP
level
EU
region
Land area
mean
sd
Econ. Size
mean
All
16
22
East
30 101
South
16
20
West
24
28
All
MCP
13
22
East
12
49
South
9
14
West
26
24
All
HCP
8
14
East
8
15
South
6
12
West
12
14
All
ORG
16
21
East
a
a
South
12
11
West
23
27
a. Data not shown as sample <15
LCP
19
20
17
60
36
12
19
86
59
11
22
109
45
a
29
66
Labour
sd
mean
40
57
37
59
61
50
30
90
92
17
47
112
56
a
30
72
1.3
6.2
1.3
1.7
1.7
3.5
1.3
2.2
2.2
2.2
1.6
2.9
2.0
a
1.9
2.1
sd
n
2.0
22.2
1.1
1.3
2.5
8.5
1.5
1.7
2.7
7.2
2.2
2.5
2.3
a
1.7
2.9
2386
47
2073
266
8203
383
4684
3136
4740
129
2077
2534
336
5
187
144
ANOVA tests indicated differences in most groups though ORG and MCP CP costs were not significantly
different. Fertiliser costs were similar for ORG and LCP holdings but significantly different for other groups,
and other crop costs were statistically different for all groups.
HCP and LCP groups were statistically more and less profitable, respectively, than other groups, with no
difference between MCP and ORG holdings. LCP holdings were the largest and significantly larger than
MCP and HCP holdings, though similar to ORG holdings, whilst the HCP group was the largest
economically and the LCP group was significantly smaller than others. ORG holdings were smaller than the
HCP group but larger than LCP and MCP group averages. Labour requirements were highest for ORG and
HCP holdings and significantly the lowest for the LCP group.
Table 37 WINE ANOVA analysis of inputs, profitability and fixed factors at different CP input levels
CP Level comparison
Factor
Low
Med
High
Med
Org
Low
High
High
Org
-175*
-750*
-151*
175*
-575*
24
CP
-43*
-197*
-4
43*
-154*
39*
Fert
-212*
-889*
-470*
212*
-677*
-258*
OCC
-1421* -13033* -2015*
1421* -11612*
-594
GFI
-999* -10994* -1478*
999*
-9995*
-479
FNVA
3*
8*
0
-3*
5*
-3*
UAA
-17*
-40*
-26*
17*
-23*
-9*
ESU
-.35*
-.84*
-.68*
.35*
-.49*
0
AWU
*. The mean difference is significant at the 0.05 level.
Org
Low
Med
Org
Low
Med
High
750*
197*
889*
13033*
10994*
-8*
40*
.84*
575*
154*
677*
11612*
9995*
-5*
23*
.49*
599*
193*
419*
11018*
9516*
-8*
14*
0
151*
4
470*
2015*
1478*
0
26*
.68*
-24
-39*
258*
594
479
3*
9*
0
-599*
-193*
-419*
-11018*
-9516*
8*
-14*
0
Categorising CP cost level groups into EU regions showed that Western region conventional holdings had
significantly higher CP costs than other regions, but that ORG regional differences were not significant.
Profitability (FNVA) for conventional farms was highest in the Western region for all CP cost levels. The
difference was largest for the HCP group, but also large for the LCP group, whilst Eastern ORG farms were
more profitable but not significantly, probably due to a smaller sample and large variability.
37
Table 38 WINE ANOVA analysis of differences in CP input and profitability (FNVA) at different CP
input levels across EU regions
EU region comparison
Variable
CP level
East
South
CP per ha
South
West
LCP
MCP
HCP
ORG
LCP
MCP
HCP
ORG
2
-4
-10
-44*
-164*
-443*
-120
-101
-199
-5925*
Net value
-206
-885*
added
-3839*
-21304*
1922
1985
*. The mean difference is significant at the 0.05 level.
East
-2
10
164*
120
199
206
3839*
-1922
West
West
East
-5*
-34*
-279*
18
-5727*
-680*
-17465*
63
4
44*
443*
101
5925*
885*
21304*
-1985
South
5*
34*
279*
-18
5727*
680*
17465*
-63
Correlations shown below, indicate that fertiliser, other crop costs and profitability were correlated with CP
costs in Southern and Western regions but poorly correlated in Eastern areas (possibly due to a smaller
sample size). Land area, economic size and labour input were poorly correlated except for the Western
region.
Table 39 WINE correlations of CP/ha with other variables in EU regions
Fert
CP level
EU reg
LCP
Other
crop
costs
Net
value
added
East
.433**
0.04
0.14
North
nd
nd
nd
South
.109**
.076**
.146**
West
-.521**
-.133*
-.598**
MCP
East
.126*
-0.05
-0.06
North
nd
nd
nd
South
.200**
.104**
.166**
West
.076**
.142**
.124**
HCP
East
.293**
0.11
0.09
North
nd
nd
nd
South
.126**
.098**
.184**
West
.468**
-.108**
.641**
ORG
East
a
a
a
North
nd
nd
nd
South
.512**
0.01
.232**
West
.592**
.370**
.423**
**. Correlation is significant at the 0.01 level (2-tailed)
*. Correlation is significant at the 0.05 level (2-tailed)
a. Data not shown as sample <15
Gross
farm
inc.
-0.08
nd
.201**
-.603**
-0.06
nd
.220**
.147**
0.08
nd
.228**
.654**
a
nd
.251**
.445**
Wheat
Yield
(t/ha)
a
nd
.617**
-0.04
.479**
nd
.197**
.221**
nd
nd
-0.04
-0.14
nd
nd
a
0.05
Land
area
Econ.
Size
0.05
nd
-.198**
.265**
0.00
nd
-.100**
-.144**
-0.01
nd
-0.04
-.359**
0.32
nd
-0.10
-0.14
0.09
nd
0.00
0.08
0.03
nd
0.02
.073**
0.03
nd
0.00
-.052**
0.34
nd
0.08
0.06
Labour
0.01
nd
0.00
0.03
-0.03
nd
.040**
.099**
0.05
nd
0.03
-.059**
0.46
nd
0.05
0.16
2.2.8 Orchards (ORCH)
ORCH CP costs varied substantially between an average of €40/ha on LCP holdings and €843/ha on HCP
farms, with ORG and MCP holdings at €242/ha and €255/ha respectively. As with some other farm type’s
fertiliser costs were higher than CP costs on LCP holdings but lower than CP costs on HCP holdings. Other
crop costs varied considerably both between and within ORCH holding groups. Northern holdings within
MCP and HCP groups had particularly high other crop costs.
38
Table 40 ORCH crop inputs (€ per hectare)
CP
level
LCP
MCP
HCP
ORG
EU
region
CP
mean
Fert.
sd
mean
Other Crop Costs
sd
mean
sd
n
All EU
East
40
29
140
200
30
161
3174
49
26
66
54
27
195
532
North
26
24
31
32
39
98
115
South
39
30
153
214
21
106
2419
West
36
33
109
95
384
645
108
All EU
East
255
112
251
210
72
226
6436
251
106
123
94
59
179
1538
North
255
111
73
86
1310
1978
167
South
255
113
284
219
65
166
4030
West
279
115
140
106
172
359
701
All EU
East
843
414
412
530
236
785
4692
708
221
175
170
84
188
347
North
812
269
126
138
4167
4445
104
South
849
431
461
569
163
566
3005
West
906
364
203
149
773
1224
1236
All EU
East
242
272
368
457
94
422
553
51
107
28
46
14
43
19
North
1
1
3
16
12
23
34
South
253
269
406
470
64
332
439
West
282
352
155
241
651
1054
61
ORCH holding profitability, indicated by GFI and FNVA per hectare generally increased with higher levels
of CP costs, though there was considerable variation within each CP cost group. The highest average
profitability group was Western ORG holdings, though the ORG average farm profitability was between
LCP and MCP conventional holding averages.
Table 41 ORCH profitability and wheat yield (€/ha and t/ha)
CP
level
LCP
MCP
HCP
EU
region
All EU
East
North
South
West
All EU
East
North
South
West
All EU
East
North
South
West
Gross Farm
Inc.
mean
3150
1134
892
3452
4777
4948
2039
2727
5598
3986
7157
2775
5181
7434
8455
sd
3607
1130
1033
3703
5473
3951
1611
3793
4015
3808
5545
2545
3522
5530
5886
Net Value
Added
mean
2630
676
678
2925
4020
4174
1139
2259
4862
2918
5767
1542
4134
6087
6558
Wheat yield (t)
sd
n
3544
1076
987
3655
5129
4037
1548
3735
4117
3322
5161
2326
3460
5138
5525
3174
532
115
2419
108
6436
1538
167
4030
701
4692
347
104
3005
1236
mean
3.9
4.0
a
3.8
4.1
4.3
3.9
7.3
4.1
5.5
6.2
a
a
6.3
6.2
sd
n
2.5
1.2
a
4.0
1.5
1.6
1.0
2.0
1.5
2.1
1.8
a
a
1.6
2.3
238
141
11
60
26
545
192
25
178
150
245
8
2
144
91
39
ORG
All EU
4147 4091
East
1394 1290
North
521
543
South
4066 3386
West
8721 9257
a. Data not shown as sample <15
3510
982
239
3475
7078
3679
1357
511
3148
7939
553
19
34
439
61
4.1
a
a
4.4
3.8
1.4
a
a
1.7
1.0
39
2
3
18
16
The ORG holdings were again the largest in terms of land area, though the HCP group were the largest
economically. Northern and Western HCP farms were larger physically, economically and in labour
requirement per farm than other regions.
Table 42 ORCH area, economic size and labour input (UAA ha, ESU/farm, AWU/farm)
CP
level
LCP
MCP
HCP
ORG
EU
region
Land area
mean
All EU
East
North
South
West
All EU
East
North
South
West
All EU
East
North
South
West
All EU
East
North
South
West
Econ. Size
sd
11
10
25
10
23
6
9
40
4
25
6
8
34
5
20
12
9
27
10
33
mean
26
23
34
26
34
12
14
61
8
28
11
12
51
8
17
22
17
36
15
63
17
7
18
18
41
17
8
83
15
83
33
9
129
25
122
27
8
24
24
81
Labour
sd
mean
65
15
27
70
42
39
15
130
30
113
61
16
210
46
98
49
14
28
40
119
1.1
1.5
1.3
1.1
1.7
1.4
2.2
4.1
1.1
3.3
1.9
2.5
7.5
1.5
5.2
1.5
1.0
1.6
1.4
3.2
sd
n
1.0
1.8
2.2
0.8
1.1
1.5
2.4
7.6
0.8
3.4
2.4
2.4
11.4
1.2
4.8
1.8
0.9
2.0
1.5
4.4
3174
532
115
2419
108
6436
1538
167
4030
701
4692
347
104
3005
1236
553
19
34
439
61
ANOVA analysis tested for differences between CP cost groups, confirming that the HCP group had
significantly higher CP costs and the LCP group had significantly lower costs, whilst the MCP and ORG
groups were similar. Fertiliser and other crop costs followed a similar pattern though ORG and HCP fertiliser
costs were not significantly different. The profitability of all groups was significantly different.
The analysis of farm physical size identified LCP and ORG to be similar and MCP and HCP holdings to be
similar but the two groups being significantly different to each other. Economically LCP and MCP groups
were of similar size but HCP and ORG were significantly greater. Labour input was similar for ORG and
MCP holdings but significantly different for LCP and HCP holdings.
Table 43 ORCH ANOVA analysis of inputs, profitability and fixed factors at different CP input levels
CP Level comparison
Factor
CP
Fert
OCC
Low
Med
Med
High
Org
-216*
-112*
-42*
-803*
-272*
-206*
-202*
-228*
-64*
Low
216*
112*
42*
High
High
Org
-588*
-160*
-164*
14
-116*
-22
Low
803*
272*
206*
Med
588*
160*
164*
Org
Org
602*
44
142*
Low
Med
High
202*
228*
64*
-14
116*
22
-602*
-44
-142*
40
-1798*
-4007* -998*
1798*
-2209*
801*
GFI
-1543*
-3137* -879*
1543*
-1593*
664*
FNVA
5*
4*
-1
-5*
0
-6*
UAA
1
-16*
-9*
0
-17*
-10*
ESU
-.25*
-.80*
-.37*
.25*
-.55*
0
AWU
*. The mean difference is significant at the 0.05 level.
4007*
3137*
-4*
16*
.80*
2209*
1593*
0
17*
.55*
3009*
2257*
-5*
7*
.42*
998*
879*
1
9*
.37*
-801*
-664*
6*
10*
0
-3009*
-2257*
5*
-7*
-.42*
Table 44 indicates differences in CP costs and profitability of farms differing by CP cost level and EU region.
CP costs varied across regions with the Eastern region significantly lower than most other regions and
Western region holdings having significantly higher CP costs than others. Profitability for LCP and HCP
holdings was significantly higher in Western and Southern regions, whilst for MCP holdings Southern
holdings were significantly more profitable, and the Western ORG group was significantly more profitable
than other ORG regions.
Table 44 ORCH ANOVA analysis of differences in CP input and profitability (FNVA) at different CP
input levels across EU regions
EU region comparison
Variable
CP per
ha
Net
value
added
CP
level
LCP
MCP
HCP
ORG
LCP
MCP
HCP
ORG
East
North
South
22*
-4
North
West
East
South
10*
13*
-22*
-4
-28*
4
-103*
-141*
-198*
103*
50
-203*
-231*
-50
-3
-2249*
-3344*
3
-2246*
-1120*
-3724*
-1779*
1120*
-2592*
-4545*
-5016*
2592*
743
-2493*
-6097*
-743
South
West
East
North
-12*
-9
-10*
0
-24
4
-37
-94*
-253*
-281*
West
West
East
North
South
12*
3
-13*
9
-3
0
-24*
28*
24
24*
141*
37
-57*
198*
94*
57*
203*
253*
-28
231*
281*
28
-3341*
2249*
2246*
-1095
3344*
3341*
1095
-2603*
-659
3724*
2603*
1945*
1779*
659
-1945*
-1953*
-2424*
4545*
1953*
-471
5016*
2424*
471
-3236*
-6840*
2493*
3236*
-3604*
6097*
6840*
3604*
*. The mean difference is significant at the 0.05 level.
Correlations in Table 45 were variable, but strongest for fertiliser and other crop costs. Profitability
correlations identified a general increase as CP costs increased, but a strong negative correlation with
profitability was identified in Western region LCP holdings. Land area and economic size were poorly
correlated but labour input was strongly correlated for a few regions.
Table 45 ORCH correlations of CP/ha with other variables in EU regions
CP level
EU reg
LCP
East
North
South
West
East
North
South
West
East
North
South
West
East
North
South
MCP
HCP
ORG
Fert
Other
crop
costs
Net
value
added
Gross
farm
inc.
0.06
.378**
0.03
-0.08
.096**
.233**
.201**
0.02
0.07
.262**
.472**
.291**
.598**
0.06
.628**
0.00
.224*
.059**
-.475**
.050*
.429**
.128**
.195**
0.06
.357**
-0.02
.230**
.507*
-0.18
0.04
-0.06
-0.04
.312**
-.527**
.184**
.234**
.042**
.292**
-0.01
.285**
.320**
.186**
0.06
0.11
.482**
0.00
-0.02
.329**
-.519**
.258**
.255**
.050**
.308**
0.04
.301**
.372**
.241**
0.09
-0.01
.448**
Wheat
Yield
(t/ha)
0.07
a
0.04
0.24
0.07
0.09
0.02
.290**
a
a
-0.16
-0.01
a
.a
0.36
Land
area
-0.04
0.07
-.112**
.213*
-0.05
0.08
-0.03
-0.03
0.02
-0.14
-0.03
-.075**
0.19
0.09
-.242**
Econ.
Size
0.01
.311**
-0.02
0.02
0.00
.198*
0.01
.165**
0.06
-0.12
.081**
.096**
0.39
-0.30
0.05
Labour
-0.02
0.04
.057**
0.06
.077**
.224**
.102**
.291**
0.07
-0.06
.096**
.091**
0.26
.554**
.197**
41
West
.519**
-0.08
.274*
**. Correlation is significant at the 0.01 level (2-tailed)
*. Correlation is significant at the 0.05 level (2-tailed)
a. Data not shown as sample <15
.313*
0.49
-0.24
-0.06
0.18
2.2.9 Olives (OLIVE)
OLIVE farms were nearly all situated in the Southern EU region, so comparisons between regions were
impossible, however within the Southern region there was a wide range of CP costs. CP usage ranged from a
LCP average of €9/ha through to €219/ha in the HCP group. Fertiliser and other crop costs were less variable,
though the ORG group had high average other crop costs.
Table 46 OLIVE crop inputs (€ per hectare)
CP
level
EU
region
CP
mean
Other Crop
Costs
Fert.
mean
sd
LCP
All EU
9
8
South
9
8
West
a
a
MCP
All EU
61
27
South
61
27
West
a
a
HCP
South
219 100
ORG
South
38
47
a. Data not shown as sample <15
sd
72
72
a
116
116
a
189
103
mean
73
73
a
90
90
a
130
106
39
39
a
80
80
a
62
148
sd
n
94
94
a
176
176
a
190
192
1710
1708
2
3309
3307
2
894
420
OLIVE farm type profitability increased with higher expenditure on CP, but ORG was as profitable as MCP
and HCP groups but had lower CP costs.
Table 47 OLIVE profitability and wheat yield (€/ha and t/ha)
CP
level
EU
region
Gross Farm Inc.
mean
Net Value
Added
mean
sd
LCP
All EU
1766 1495
South
1766 1495
West
a
a
MCP
All EU
2632 1842
South
2632 1842
West
a
a
HCP
South
2893 1730
ORG
South
2902 1792
a. Data not shown as sample <15
1473
1473
a
2298
2298
a
2522
2364
Wheat yield (t)
sd
n
mean
1434
1434
a
1767
1767
a
1663
1596
1710
1708
2
3309
3307
2
894
420
sd
3.4
3.4
nd
5.4
5.4
nd
a
a
1.3
1.3
nd
2.5
2.5
nd
a
a
n
39
39
0
41
41
0
6
3
The ORG farms were the largest physically and economically, though HCP farms required more labour.
Table 48 OLIVE area, economic size and labour input (UAA ha, ESU/farm, AWU/farm)
CP
level
LCP
MCP
EU
region
All EU
South
West
All EU
Land area
mean
10
10
a
9
Econ. Size
sd
22
22
a
22
mean
10
10
a
16
Labour
sd
27
27
a
37
mean
1.0
1.0
a
1.2
sd
0.6
0.6
a
0.7
n
1710
1708
2
3309
42
South
9
22
West
a
a
HCP
South
6
14
ORG
South
12
21
a. Data not shown as sample <15
16
a
11
19
37
a
19
33
1.2
a
1.4
1.2
0.7
a
0.7
1.1
3307
2
894
420
ANOVA analysis of OLIVE farms confirmed CP costs of the different groups to be statistically different.
Fertiliser costs were similar for MCP and ORG groups, whilst ORG other crop costs were significantly
higher than all other groups. Gross Farm Income was significantly higher for ORG and HCP farms though
Farm Net Value Added was similar for MCP, HCP and ORG farms. HCP farms were significantly smaller
physically than other groups and smaller economically than ORG and MCP holdings, but had significantly
higher labour requirements than other groups.
Table 49 OLIVE ANOVA analysis of inputs, profitability and fixed factors at different CP
input levels
CP Level comparison
Factor
Low
Med
Med
High
Org
Low
High
High
Org
CP
-52*
-210*
-30*
52* -158*
23*
Fert
-44*
-117*
-31*
44*
-73*
13
OCC
-41*
-23*
-109*
41*
18
-68*
GFI
-866*
-1127*
-1136* 866* -261* -270*
FNVA
-825*
-1049*
-891* 825* -224*
-66
UAA
1
4*
-2
0
3*
-3
ESU
-5*
0
-9*
5*
5*
-3
AWU
-.16*
-.36*
-.19* .16*
-.19*
0
*. The mean difference is significant at the 0.05 level.
Org
Low
Med
Org
Low
Med
High
210*
117*
23*
1127*
1049*
-4*
1
.36*
158*
73*
-18
261*
224*
-3*
-5*
.19*
180*
86*
-86*
-9
158
-6*
-8*
.17*
30*
31*
109*
1136*
891*
2
9*
.19*
-23*
-13
68*
270*
66
3
3
0
-180*
-86*
86*
9
-158
6*
8*
-.17*
2.2.10 Other Permanent Crops (PERM)
PERM type holdings exhibited a wide range in CP costs per hectare, possibly reflecting the nonspecialisation of this sector that was mainly situated with the Southern EU region. Average PERM holding
CP costs ranged from €14/ha for LCP holdings to €552/ha for HCP holdings and were highest at €1953/ha
for Northern HCP holdings. Fertiliser costs were also wide ranging and very high for Northern HCP farms,
as were other crop costs too. ORG holding data indicates that their costs were similar to the MCP group.
Table 50 PERM crop inputs (€ per hectare)
CP
level
LCP
MCP
HCP
EU
region
All EU
East
North
South
West
All EU
East
North
South
West
All EU
East
CP
mean
14
15
6
15
4
98
104
84
97
120
552
474
Fert.
sd
11
13
9
11
8
45
45
41
44
45
1006
276
mean
128
73
489
108
1082
169
123
370
158
654
698
724
Other Crop Costs
sd
1734
68
1651
1728
2388
362
102
790
141
2078
2277
845
mean
236
103
1451
140
4972
156
167
1774
113
1559
2311
1625
sd
n
2974
514
3708
2766
7361
1029
689
4913
755
4012
10665
2301
1864
55
88
1639
82
3492
185
107
2964
236
2972
106
43
North
1953 3324
South
494
641
West
811 1981
ORG
All EU
85
134
East
a
a
North
a
a
South
87
136
West
a
a
a. Data not shown as sample <15
7487
464
1507
273
a
a
280
a
10207
1380
3224
3438
a
a
3501
a
19977
1245
7833
416
a
a
418
a
22827
9431
13712
4330
a
a
4409
a
160
2208
498
231
5
2
218
6
There was a large range in profitability though in general, profitability increased with CP expenditure. The
Northern and Western HCP holdings had the highest profit reflecting their higher expenditure on CP and
other crop costs.
Table 51 PERM profitability and wheat yield (€/ha and t/ha)
CP
level
EU
region
Gross Farm Inc.
mean
sd
LCP
All EU
3819
28235
East
2590
4658
North
13145
40222
South
3125
27642
West
37914
40654
MCP
All EU
3178
5611
East
1962
2474
North
8473
16512
South
2979
3074
West
12763
28278
HCP
All EU
15458 229805
East
9362
14243
North
86491 104758
South
11753 249573
West
34346
48873
ORG
All EU
5830
46206
East
a
a
North
a
a
South
5985
47055
West
a
a
a. Data not shown as sample <15
Net Value
Added
Wheat yield
(t)
mean
sd
n
mean
3357
1814
11756
2761
32887
2575
1417
7607
2413
10623
12943
7592
76761
9849
28216
5181
a
a
5354
a
26444
3986
38823
25961
36990
4977
2436
15915
2920
24242
229011
13741
98808
249008
41660
45600
a
a
46436
a
1864
55
88
1639
82
3492
185
107
2964
236
2972
106
160
2208
498
231
5
2
218
6
3.2
4.0
a
3.1
a
3.9
4.2
6.2
3.5
5.2
6.0
a
a
5.9
6.7
1.6
nd
a
nd
a
sd
n
1.8
1.1
a
1.8
a
1.3
1.1
1.1
1.3
1.4
1.8
a
a
1.6
2.2
1.5
nd
a
nd
a
131
21
2
104
4
337
82
17
193
45
240
8
2
188
42
12
0
1
0
11
ORG farms were the largest physically but Northern MCP holdings were the largest regional group at 93ha.
These farms were also the largest economically, though between CP cost groups the HCP farms were the
largest. Labour requirements were highest on the Northern HCP and MCP holdings.
Table 52 PERM area, economic size and labour input (UAA ha, ESU/farm, AWU/farm)
CP
level
LCP
EU
region
All EU
East
North
South
West
Land area
mean
13
15
23
13
10
Econ. Size
sd
19
51
24
17
31
mean
15
22
69
13
119
sd
38
56
107
19
201
Labour
mean
1.3
2.1
3.4
1.2
3.7
sd
1.7
3.7
4.5
1.5
4.1
n
1864
55
88
1639
82
44
MCP
HCP
ORG
All EU
East
North
South
West
All EU
East
North
South
West
All EU
East
North
South
West
8
10
93
7
19
6
8
8
5
11
15
a
a
15
a
20
37
233
13
21
13
20
16
13
16
26
a
a
22
a
19
15
749
15
133
39
19
125
26
125
23
a
a
23
a
106
69
1646
35
195
133
35
221
115
202
38
a
a
38
a
1.3
2.2
4.8
1.2
2.8
2.0
3.6
9.8
1.6
3.6
1.7
a
a
1.7
a
2.3
8.4
7.3
1.0
2.8
3.3
10.5
11.5
1.9
3.3
2.8
a
a
2.8
a
3492
185
107
2964
236
2972
106
160
2208
498
231
5
2
218
6
a. Data not shown as sample <15
ANOVA analysis identified that HCP holdings had significantly higher CP and other crop costs, whilst ORG
and MCP groups had similar costs. HCP fertiliser costs were also significantly higher than LCP and MCP
groups but not statistically different to ORG holdings. HCP Gross Farm Income was significantly higher
than LCP and MCP groups but Farm Added Net Value was not statistically different to others. HCP farms
were significantly smaller physically but also larger economically than others.
Table 53 PERM ANOVA analysis of inputs, profitability and fixed factors at different CP
input levels
CP Level comparison
Factor
Low
Med
High
Med
Org
Low
High
CP
-83*
-538*
-71*
83*
-455*
Fert
-41
-570*
-145
41
-529*
OCC
81
-2074*
-180
-81
-2155*
GFI
641
-11639* -2011
-641
-12280*
FNVA
783
-9586 -1824
-783
-10369
UAA
5*
7*
-2
-5*
2*
ESU
-4
-24*
-8*
4
-20*
AWU
-0.02
-0.66*
-0.35
0.02
-0.64*
*. The mean difference is significant at the 0.05 level.
High
Org
Org
Low
Med
Org
Low
Med
High
12
-104
-261
-2652
-2607
-7*
-4
-0.33
538*
570*
2074*
11639*
9586
-7*
24*
0.66*
455*
529*
2155*
12280*
10369
-2*
20*
0.64*
467*
426
1895*
9628
7762
-9*
16*
0.32
71*
145
180
2011
1824
2
8*
0.35
-12
104
261
2652
2607
7*
4
0.33
-467*
-426
-1895*
-9628
-7762
9*
-16*
-0.32
ANOVA analysis identified significant regional variations in CP costs and profitability. Within the LCP
group, Western region holding CP costs were significantly lower and profitability was significantly higher
than other areas. For the MCP group the Western region group CP costs were significantly higher and
profitability was higher than other regions. Within the HCP group the Northern region had significantly
higher CP costs and profitability than other regions. The Southern and Eastern ORG groups had the highest
CP costs but there were no significant differences between profitability of regions despite a large variation in
average figures.
45
Table 54 PERM ANOVA analysis of differences in CP input and profitability (FNVA) at
different CP input levels across EU regions
EU region comparison
Variable
CP per
ha
Net
value
added
CP
level
LCP
MCP
HCP
ORG
LCP
MCP
HCP
ORG
East
North
North
South
West
9*
0
11*
East
South
-9*
-9*
South
West
2
West
East
North
West
0
9*
10*
East
North
South
-2
-10*
-11*
20*
7
-16*
-20*
-13*
-36*
-7
13*
-23*
16*
36*
23*
-1479*
-19
-337*
1479*
1460*
1143*
19
-1460*
-317*
337*
-1143*
317*
86
2
85
-86
-84*
-1
-2
84*
83*
-85
1
-83*
-9942
-946
-31073*
9942
8996
-21131*
946
-8996
-30127*
31073*
21131*
30127*
-6190*
-996*
-9205*
6190*
5194*
-3015
996*
-5194*
-8209*
9205*
3015
8209*
-69168*
-2256
-20623*
69168*
66912*
48545*
2256
-66912*
-18367*
20623*
-48545*
18367*
174
-5008
-321
-174
-5181
-495
5008
5181
4686
321
495
-4686
*. The mean difference is significant at the 0.05 level.
Correlations between CP costs and other variables are shown in Table 55 below. The best correlations were
found to be within the HCP group for fertiliser, other crop costs and profitability measures, confirming the
strong link between CP costs and profitability for the highest users of CP products. The ORG Southern group
also showed strong correlations between CP costs and profitability indicating their greater use to increase
profits, even though ORG farms would only be using organic approved CP products.
Table 55 PERM correlations of CP/ha with other variables in EU regions
Fert
CP level
EU reg
LCP
East
North
South
West
East
North
South
West
East
North
South
West
East
North
South
West
MCP
HCP
ORG
.303*
-0.11
-0.02
-0.10
0.14
0.14
.292**
-0.08
.743**
.632**
.636**
.348**
a
a
.312**
a
Other
crop
costs
-0.05
-0.11
-0.05
-.266*
0.05
0.08
0.01
-0.03
.794**
.568**
.537**
.508**
a
a
.403**
a
Net
value
added
Gross
farm
inc.
Wheat
Yield
(t/ha)
Land
area
-0.16
-0.14
-.050*
-.287**
0.12
0.11
0.03
-0.05
.627**
.642**
.065**
.296**
a
a
.413**
a
-0.17
-0.14
-0.05
-.291**
0.08
0.12
.054**
-0.06
.657**
.646**
.081**
.457**
a
a
.415**
a
.518*
1.000**
.360**
.983*
0.17
0.13
.208**
0.03
0.01
-1.000**
.144*
0.00
a
a
nd
nd
0.07
0.16
-.243**
-0.02
0.00
-.204*
-.040*
0.01
-0.17
-0.15
0.00
-.127**
a
a
-0.09
a
Econ.
Size
0.01
.257*
-0.02
-0.05
0.02
-0.15
0.03
0.01
-0.04
-0.12
.098**
-0.07
a
a
.256**
a
Labour
0.12
0.12
-.087**
-0.18
0.03
0.17
-.038*
-0.03
0.04
0.10
.248**
0.07
a
a
.400**
a
**. Correlation is significant at the 0.01 level (2-tailed)
*. Correlation is significant at the 0.05 level (2-tailed)
a. Data not shown as sample <15
2.2.11 Mixed Cropping (MIXED)
MIXED farm type holding CP costs were less variable than some of the other types but still varied between
€6/ha and €328/ha. Fertiliser and other crop costs also varied considerably both between and within CP cost
groups. The Western region LCP group had low CP costs but high fertiliser and other crop costs compared to
the other regions.
46
Table 56 MIXED crop inputs (€ per hectare)
CP
level
LCP
MCP
HCP
ORG
EU
region
All EU
East
North
South
West
All EU
East
North
South
West
All EU
East
North
South
West
All EU
East
North
South
West
CP
mean
6
7
6
5
5
53
48
48
55
76
328
271
252
351
252
25
12
2
39
20
Fert.
sd
6
6
5
5
5
27
25
30
27
26
335
366
260
343
199
66
24
6
88
55
mean
52
38
23
65
179
99
79
82
115
108
295
157
214
331
231
65
41
10
97
43
Other Crop Costs
sd
mean
183
33
26
218
1089
83
46
57
102
67
436
152
753
413
675
212
62
20
297
70
46
4
6
80
414
35
26
30
43
37
214
237
436
209
203
39
12
21
56
60
sd
n
2125
25
22
2914
4522
214
110
59
271
246
1385
1042
1782
1467
1102
135
35
65
176
143
3282
737
342
2150
53
8728
3193
345
4145
1045
5345
481
171
3571
1122
642
133
85
333
91
Profitability was over four times higher for HCP than LCP holdings, though there was considerable variation
within each group, particularly within the Western region. Overall, Southern HCP MIXED farms were the
most profitable, though Northern region HCP farms achieved the highest wheat yield at 7.4t/ha. ORG farm
profitability was between LCP and MCP levels with an average wheat yield of 3.2t/ha.
Table 57 MIXED profitability and wheat yield (€/ha and t/ha)
CP
level
LCP
MCP
HCP
ORG
EU
region
All EU
East
North
South
West
All EU
East
North
South
West
All EU
East
North
South
West
All EU
East
North
Gross Farm
Inc.
Net Value
Added
Wheat yield
(t)
mean
sd
mean
sd
n
1259
464
326
1989
2898
1924
811
855
2941
1146
4941
3376
2857
5518
3129
1569
1150
636
14913
473
421
20702
12556
3132
870
827
3997
1789
10085
5069
10081
10690
10032
2927
1058
734
1025
264
234
1716
2320
1542
505
605
2489
813
4072
2823
2399
4584
2275
1235
911
391
14229
503
410
19764
10325
2979
660
749
3845
1566
9227
4904
9246
10018
7031
2541
950
709
3282
737
342
2150
53
8728
3193
345
4145
1045
5345
481
171
3571
1122
642
133
85
mean
2.9
2.8
2.9
3.1
4.2
4.1
3.9
5.2
4.3
5.8
5.4
3.6
7.4
5.4
6.6
3.2
2.8
2.7
sd
n
1.8
1.3
1.2
2.9
1.6
1.5
1.3
2.1
1.6
1.6
2.1
1.4
1.6
2.0
1.8
1.6
1.2
1.7
1238
468
207
529
34
4562
2595
226
879
862
1866
254
109
663
840
234
62
38
47
South
West
2017
1578
4007
1633
1611
1199
3466
1505
333
91
4.0
3.7
2.1
1.6
62
72
The average ORG farm was physically larger than the other groups, though Northern HCP and Western
MCP farms were the largest individual groups. Economically, Northern and Western farms were the largest
and also had the greatest labour requirements.
Table 58 MIXED area, economic size and labour input (UAA ha, ESU/farm, AWU/farm)
CP
level
LCP
MCP
HCP
ORG
EU
region
Land area
mean
All EU
East
North
South
West
All EU
East
North
South
West
All EU
East
North
South
West
All EU
East
North
South
West
21
10
33
27
49
21
21
59
14
84
16
16
89
8
63
30
13
40
37
44
sd
37
29
44
41
38
126
173
103
31
221
67
134
200
25
88
67
81
44
57
67
Econ. Size
mean
10
4
6
15
32
16
10
42
15
80
29
11
138
21
98
21
5
21
28
42
Labour
sd
mean
20
16
11
23
25
78
93
78
31
185
109
85
225
108
97
54
12
37
70
47
1.5
1.6
1.7
1.3
1.7
1.7
2.0
2.0
1.4
2.3
1.9
2.6
3.8
1.6
2.6
1.8
2.1
1.7
1.7
1.8
sd
n
1.6
1.7
1.4
1.5
0.9
5.0
7.2
7.7
1.0
5.1
5.3
6.6
7.5
5.3
2.9
1.7
1.9
1.1
1.7
1.3
3282
737
342
2150
53
8728
3193
345
4145
1045
5345
481
171
3571
1122
642
133
85
333
91
ANOVA analysis highlighted that CP costs were significantly different between CP cost groups and that the
HCP group had significantly higher fertiliser and other crop costs that other groups. LCP and ORG groups
were similar for fertiliser costs and LCP, MCP and ORG groups were similar for other crop costs.
Profitability was significantly higher for the HCP group, but statistically similar for LCP and ORG groups
and MCP and LCP groups. Physically, ORG farms were significantly larger and HCP holdings were
significantly smaller, but HCP farms were significantly larger economically. MCP, HCP and ORG farms
required significantly more labour input than LCP farms.
Table 59 MIXED ANOVA analysis of inputs, profitability and fixed factors at different CP
input levels
CP Level comparison
Factor
Low
Med
CP
Fert
OCC
GFI
FNVA
UAA
ESU
-47*
-47*
11
-665
-518
0
-7*
High
-322*
-243*
-168*
-3683*
-3047*
5*
-20*
Med
Org
-19*
-13
7
-310
-210
-9*
-12*
Low
47*
47*
-11
665
518
0
7*
High
Org
High
Org
Low
Med
Org
-275*
-196*
-179*
-3017*
-2529*
5*
-13*
28*
34*
-4
355*
308*
-9*
-5
322*
243*
168*
3683*
3047*
-5*
20*
275*
196*
179*
3017*
2529*
-5*
13*
303*
230*
175*
3372*
2837*
-14*
8*
Low
19*
13
-7
310
210
9*
12*
Med
High
-28*
-34*
4
-355*
-308*
9*
5
-303*
-230*
-175*
-3372*
-2837*
14*
-8*
48
AWU
-0.21*
-0.42*
-0.37* 0.21*
*. The mean difference is significant at the 0.05 level.
-0.21
-0.15
0.42*
0.21
0.05
0.37*
0.15
-0.05
ANOVA analysis of regional variations in CP costs identified a mixed pattern. Within the LCP group
Eastern farms had significantly higher CP costs, but with the MCP group the Western region CP costs were
higher and the within the HCP group Southern farms had significantly higher CP costs. Northern ORG farms
had significantly lower CP costs.
Profitability was highest for Western region LCP farms, but not significantly, but Southern MCP and HCP
farms were significantly more profitable than other regions. Low CP costs for Northern ORG farms are
reflected in significantly lower profitability, with Southern ORG farms the most profitable.
Table 60 MIXED ANOVA analysis of differences in CP input and profitability (FNVA) at
different CP input levels across EU regions
EU region comparison
Variable
CP per
ha
Net
value
added
CP
level
East
North
South
West
North
South
West
East
South
West
East
North
West
East
North
South
2*
0
18
9*
30
-100
424
519*
2*
-7*
-80*
-27*
-1453*
-1983*
-1760*
-700*
3*
-28*
19
-9
-2056
-308*
548
-288
-2*
0
-18
-9*
-30
100
-424
-519*
0
-7*
-98*
-36*
-1482*
-1883*
-2185*
-1220*
1
-28*
1
-18*
-2086
-208*
124
-808*
-2*
7*
80*
27*
1453*
1983*
1760*
700*
0
7*
98*
36*
1482*
1883*
2185*
1220*
1
-21*
99*
18
-603
1676*
2309*
412
-3*
28*
-19
9
2056
308*
-548
288
-1
28*
-1
18*
2086
208*
-124
808*
-1
21*
-99*
-18
603
-1676*
-2309*
-412
LCP
MCP
HCP
ORG
LCP
MCP
HCP
ORG
*. The mean difference is significant at the 0.05 level.
MIXED farm type fertiliser and other crop costs were closely correlated to CP costs. Due to greater
expenditure on inputs, profitability was also closely correlated for the HCP group. Wheat yield was
correlated for some groups, but generally wheat yield, land area, economic size and labour input were poorly
correlated.
Table 61 MIXED correlations of CP/ha with other variables in EU regions
Fert
CP level
EU reg
LCP
East
North
South
West
East
North
South
West
East
North
South
West
East
North
South
MCP
HCP
ORG
Other
crop
costs
Net
value
added
Gross
farm
inc.
Wheat
Yield
(t/ha)
Land
area
Econ.
Size
Labour
.451**
.381**
-.058**
-0.12
.084*
.115*
-0.02
-0.08
.254**
-0.02
-.043*
-0.14
.160**
0.07
-0.04
-0.14
.326**
.265**
0.01
.401*
0.05
0.05
-.047*
0.15
0.03
.129*
0.03
0.16
0.06
0.00
-.081**
0.15
.479**
.288**
.254**
.135**
.185**
.361**
.087**
0.03
.179**
.129*
.057**
0.04
.328**
.160**
.072**
0.02
.102**
.631**
.115**
.238**
.054**
.132*
-0.01
0.01
.063**
.388**
.065**
.064*
.073**
0.02
.084**
0.02
.398**
.236**
.717**
.389**
.622**
.356**
.393**
.329**
.637**
.352**
.483**
.509**
.707**
.357**
.506**
.498**
0.03
0.13
-.160**
.133**
-0.03
-0.09
-.065**
-.193**
-0.03
0.01
0.02
0.00
0.02
0.14
.060**
.144**
.548**
.693**
.272**
0.12
0.02
.191**
.186*
0.03
.250**
0.16
0.14
.244**
0.17
-0.25
.388**
0.01
-0.03
0.00
0.06
0.07
.384**
0.09
-0.14
.305**
49
West
.417**
0.09
0.02
0.01
.616**
0.15
.451**
-0.04
**. Correlation is significant at the 0.01 level (2-tailed)
*. Correlation is significant at the 0.05 level (2-tailed)
a. Data not shown as sample <15
2.2.12 Whole farm data summary
To summarise the findings of this section:





Horticulture CP costs were much higher than any other farm type, as was profitability
Permanent crop types such as Wine and Orchards also had high CP costs and farm profitability,
Cereal farms had the lowest CP cost and profitability
Across the EU, Western EU holdings had the highest CP costs
Fertiliser costs were the most closely correlated to CP costs across all farm types
Profitability of the high CP cost holdings was higher than lower input groups
50
2.3 Analysis of national farm survey data for UK and Netherlands
National farm survey data was available to the TEAMPEST project in the UK and the Netherlands. There
was sufficient data available to allow for analysis to be carried out on a number of different crop enterprises
in each country, whilst ensuring groups were large enough for data publication after splitting into varying CP
cost level groups. The national data was also used for the Farmer Focus groups carried out within Task 7.4.
UK data, originally in Pounds (£) was converted to Euros (€) at the official EU (2010) currency conversion
for each year to make data easier to understand in the European context, though differences in data collection
techniques mean that enterprise data is not directly comparable between countries.
2.3.1 Winter Wheat (UK)
UK Winter Wheat crop data indicated a significant variation in conventional CP costs, whilst fertiliser and
other crop costs showed less variability. Organic seed costs were approximately twice as high as
conventional costs, reflecting the higher output price of organic cereals. Overall, total variable costs and
yields, (shown in Table 63) were significantly different between groups, with HCP farms the highest and
organic farms the lowest. However, due to the high price of organic grains, the organic holdings had the
highest Gross Margin (GM, enterprise output minus direct enterprise variable costs) and Net Margin (NM,
enterprise output minus direct and indirect enterprise costs), despite the highest fixed costs. ANOVA
analysis highlighted ORG farm profitability to be significantly higher than HCP farms but no different to
LCP and MCP holdings.
Table 62 UK Winter Wheat enterprise analysis at varying CP Level
CP Input Level
Parameter
(per hectare)
LCP
mean
CP
Fertiliser
Seeds
Other Crop Costs
Yield
Gross Margin
Fixed Costs
Net Margin
n
100
138
59
36
6.9
852
894
-117
MCP
sd
31
67
27
62
1.8
366
294
413
142
mean
168
154
64
30
7.8
883
856
-83
HCP
sd
19
69
23
47
1.5
368
279
403
mean
247
177
73
47
8.2
814
898
-184
286
ORG
sd
mean
sd
44
71
30
78
1.6
369
366
514
3
14
120
23
4.1
1125
1029
12
16
42
57
39
1.6
540
349
451
142
76
Table 63 UK Winter Wheat ANOVA analysis at varying CP Level
CP Level
LCP
Indicator
MCP
HCP
MCP
ORG
LCP
CP
-68*
-147*
96*
68*
Fertiliser
-16
-39*
123*
16
Seeds
-6
-14*
-61*
6
Other Crops Costs
6
-12
13
-6
Total Variable Costs
-89*
-219*
168*
89*
Yield
0*
-1*
3*
1*
GM
-31
38
-273*
31
Mach & Cont.
31
-1
-113*
-31
Total Fixed Costs
38
-4
-135*
-38
Net Margin
-35
67
-130
35
*. The mean difference is significant at the 0.05 level.
HCP
ORG
HCP
ORG
LCP
MCP
ORG
LCP
MCP
HCP
-79*
-23*
-8*
-18
-130*
0*
69
-31
-41
102
165*
139*
-56*
6
257*
4*
-242*
-144*
-173*
-95
147*
39*
14*
12
219*
1*
-38
1
4
-67
79*
23*
8*
18
130*
0*
-69
31
41
-102
243*
163*
-48*
24*
387*
4*
-311*
-112*
-131
-197*
-96*
-123*
61*
-13
-168*
-3*
273*
113*
135*
130
-165*
-139*
56*
-6
-257*
-4*
242*
144*
173*
95
-243*
-163*
48*
-24*
-387*
-4*
311*
112*
131
197*
51
2.3.2 Spring Barley (UK)
UK Spring Barley data also indicated a significant variation in conventional CP costs. Conventional farm
fertiliser and seed costs showed less variability, with no difference in other crop costs between groups.
Organic seed costs were significantly higher than conventional costs, whilst fertiliser and CP costs were
significantly lower. Yield differences were less marked than for Winter Wheat, but were still significant,
whilst GM was highest for ORG and MCP farms. Overall, ORG NM was significantly higher than HCP
farms but not statistically higher than LCP and MCP holdings.
Table 64 UK Spring Barley enterprise analysis at varying CP Level
CP Input Level
Parameter
(per hectare)
LCP
mean
CP
Fert
Seeds
Other Crop Costs
Yield
Gross Margin
Fixed Costs
Net Margin
n
MCP
sd
23
102
72
14
4.5
554
697
-190
69
mean
16
70
39
23
1.3
305
219
289
HCP
sd
78
100
68
19
5.2
648
742
-175
139
19
49
27
34
1.3
324
243
318
mean
157
148
78
30
5.7
557
793
-337
69
ORG
sd
48
94
27
47
1.5
344
316
417
mean
1
34
110
27
3.1
760
810
-108
49
sd
5
69
70
49
1.0
344
313
321
Table 65 UK Spring Barley ANOVA analysis at varying CP Level
CP Level
Indicator
LCP
MCP
HCP
MCP
ORG
LCP
CP
-55*
-135*
22*
55*
Fert
2
-46*
68*
-2
Seeds
4
-5
-38*
-4
Other Crops Costs
-5
-16
-13
5
Total Variable Costs
-55*
-207*
36
55*
Yield
0*
-1*
1*
1*
GM
-94
-3
-206*
94
Mach & Cont.
-13
-44
-70
13
Total Fixed Costs
-45
-96
-113
45
Net Margin
-15
147
-82
15
*. The mean difference is significant at the 0.05 level.
HCP
ORG
HCP
ORG
LCP
MCP
ORG
LCP
MCP
HCP
-80*
-48*
-10
-11
-152*
-0.5
91
-31
-51
162*
77*
66*
-42*
-8
90*
2*
-112
-57
-68
-67
135*
46*
5
16
207*
1*
3
44
96
-147
80*
48*
10
11
152*
0.5
-91
31
51
-162*
156*
114*
-33*
3
242*
3*
-203*
-26
-17
-229*
-22*
-68*
38*
13
-36
-1*
206*
70
113
82
-77*
-66*
42*
8
-90*
-2*
112
57
68
67
-156*
-114*
33*
-3
-242*
-3*
203*
26
17
229*
2.3.3 Beans (UK)
CP costs for beans were significantly different between groups, though fertiliser and other crop costs were
similar. ORG seed costs were however significantly higher than the conventional holdings. Overall, ORG
and LCP holdings had similar variable costs whilst MCP and HCP farms were significantly higher. Yields
were similar between ORG and LCP holdings and LCP and MCP farms but statistically different between
other groups. Fixed costs, including machinery and contracting charges were significantly higher for ORG
holdings than conventional farms. Overall, there was no significant difference in UK Bean NM between the
groups.
Table 66 UK Beans enterprise analysis at varying CP Level
Parameter
(per hectare)
CP Input Level
LCP
MCP
HCP
ORG
52
mean
CP
Fert
Seeds
Other Crop Costs
Yield
Gross Margin
Fixed Costs
Net Margin
n
sd
45
28
65
18
2.8
347
566
-254
32
mean
24
31
41
28
1.4
231
194
231
sd
103
33
62
13
3.4
387
595
-253
64
19
30
37
23
1.3
240
123
190
mean
179
26
81
40
4.2
469
622
-201
32
sd
38
34
40
76
1.6
350
213
364
mean
sd
1
11
116
18
2.4
629
805
-241
55
4
44
54
33
1.2
439
284
346
Table 67 UK Beans ANOVA analysis at varying CP Level
CP Level
LCP
Indicator
MCP
MCP
HCP
ORG
LCP
CP
-59*
-134*
44*
59*
Fert
-5
2
17
5
Seeds
3
-16
-51*
-3
Other Crops Costs
5
-22
0
-5
Total Variable Costs
-57*
-172*
10
57*
Yield
-0.6
-1*
0.4
0.6
GM
-40
-122
-282*
40
Mach & Cont.
-3
-42
-207*
3
Total Fixed Costs
-29
-57
-239*
29
Net Margin
-1
-53
-13
1
*. The mean difference is significant at the 0.05 level.
HCP
ORG
HCP
ORG
LCP
MCP
ORG
LCP
MCP
HCP
-76*
7
-19
-27
-114*
-0.8
-82
-39
-27
-52
103*
22*
-54*
-5
68*
1*
-242*
-204*
-210*
-12
134*
-2
16
22
172*
1*
122
42
57
53
76*
-7
19
27
114*
0.8
82
39
27
52
178*
15
-35*
22
182*
2*
-160
-165*
-183*
40
-44*
-17
51*
0
-10
-0.4
282*
207*
239*
13
-103*
-22*
54*
5
-68*
0*
242*
204*
210*
12
-178*
-15
35*
-22
-182*
-2*
160
165*
183*
-40
2.3.4 Potatoes – Maincrop (UK)
UK Potato CP costs varied significantly between groups, the HCP group costs over 3 times higher than the
LCP group. Fertiliser costs were significantly lower for ORG holdings, whilst other variable costs were not
significant (probably due to a small sample and large variability). ORG potato yield was significantly lower
with no difference between the conventional groups, and overall, there was no significant difference in NM
between the groups.
Table 68 UK Potatoes enterprise analysis at varying CP Level
CP Input Level
Parameter
(per hectare)
LCP
mean
CP
Fert
Seeds
Other Crop Costs
Yield
Gross Margin
Fixed Costs
Net Margin
n
273
341
596
382
35.4
4702
2068
2282
10
MCP
sd
123
102
207
247
9.6
1573
1056
1250
mean
552
528
766
240
31.6
3921
1962
1067
21
HCP
sd
77
322
272
213
11.9
2169
1066
1561
mean
971
560
727
304
35.9
3948
2446
476
10
ORG
sd
304
201
346
194
14.5
3047
1466
2646
mean
56
47
1723
301
15.1
4044
2570
291
20
sd
70
77
2282
309
10.0
5048
1579
3742
53
Table 69 UK Potatoes ANOVA analysis at varying CP Level
CP Level
Indicator
LCP
MCP
MCP
HCP
ORG
LCP
CP
-279* -698*
217*
279*
Fert
-187
-220
294*
187
Seeds
-171
-131 -1128
171
Other Crops Costs
142
79
82
-142
Total Variable Costs
-495* -970*
-539
495*
Yield
3.7
-0.5
20*
-3.7
GM
780
754
658
-780
Mach & Cont.
277
8
-260
-277
Total Fixed Costs
106
-378
-502
-106
Net Margin
1215
1806
1991 -1215
*. The mean difference is significant at the 0.05 level.
HCP
ORG
HCP
ORG
LCP
MCP
ORG
LCP
MCP
HCP
-419*
-33
40
-63
-476
-4.3
-27
-268
-484
591
496*
481*
-957
-60
-45
17*
-122
-537*
-608
776
698*
220
131
-79
970*
0.5
-754
-8
378
-1806
419*
33
-40
63
476
4.3
27
268
484
-591
915*
513*
-997
3
431
21*
-96
-268
-123
185
-217*
-294*
1128
-82
539
-20*
-658
260
502
-1991
-496*
-481*
957
60
45
-17*
122
537*
608
-776
-915*
-513*
997
-3
-431
-21*
96
268
123
-185
2.3.5 Sugar Beet (UK)
CP costs for sugar beet were significantly different between groups, but other costs were statistically similar.
LCP total variable costs were significantly lower than the HCP group but overall, yield and NM was similar
between conventional farm groups (no ORG data was available).
Table 70 UK Sugar Beet enterprise analysis at varying CP Level
CP Input Level
Parameter
(per hectare)
LCP
mean
CP
Fert
Seeds
Other Crop Costs
Yield
Gross Margin
Fixed Costs
Net Margin
n
MCP
sd
mean
102
26
232 115
233
91
285 175
58.6 14.6
1185 543
780 246
28 509
HCP
sd
mean
182
23
165
97
202
58
373 208
58.5 12.9
1114 496
807 352
4 811
16
sd
265
192
208
411
59.6
1103
760
32
34
26
102
68
186
9.2
340
278
531
16
Table 71 UK Sugar Beet ANOVA analysis at varying CP Level
CP Level
Indicator
LCP
MCP
CP
Fert
Seeds
Other Crops Costs
Total Variable Costs
Yield
GM
Mach & Cont.
Total Fixed Costs
-80*
67
31
-88
-71
0.04
72
-41
-27
LCP
MCP
-163*
40
25
-126
-224*
-0.98
83
-38
20
MCP
80*
-67
-31
88
71
-0.04
-72
41
27
LCP
MCP
-83*
-26
-6
-38
-153
-1.02
11
3
47
MCP
163*
-40
-25
126
224*
0.98
-83
38
-20
MCP
83*
26
6
38
153
1.02
-11
-3
-47
54
Net Margin
24
-4
*. The mean difference is significant at the 0.05 level.
-24
-28
4
28
2.3.6 Winter Oilseed Rape (UK)
CP and total variable costs varied significantly between the groups, whilst fertiliser costs were significantly
higher for the HCP group but similar for LCP and MCP groups. LCP and HCP yield and GM were
significantly different, but overall NM was not statistically different between groups.
Table 72 UK Winter Oilseed Rape enterprise analysis at varying CP Level
CP Input Level
Parameter
(per hectare)
Low
mean
CP
Fert
Seeds
Other Crop Costs
Yield
Gross Margin
Fixed Costs
Net Margin
n
97
160
50
33
2.9
543
759
-310
55
Med
sd
22
71
20
39
0.8
242
250
284
mean
156
161
50
22
3.2
604
745
-239
110
High
sd
mean
21
43
19
26
0.8
311
184
281
241
200
56
28
3.3
681
783
-227
55
sd
47
82
25
30
0.6
344
223
376
Table 73 UK Winter Oilseed Rape ANOVA analysis at varying CP Level
CP Level
Indicator
LCP
MCP
MCP
HCP
LCP
CP
-58*
-143*
58*
Fert
-1
-40*
1
Seeds
0
-6
0
Other Crops Costs
10
5
-10
Total Variable Costs
-51*
-187*
51*
Yield
-0.27
0*
0.27
GM
-61
-139*
61
Mach & Cont.
21
-32
-21
Total Fixed Costs
14
-24
-14
Net Margin
-72
-83
72
*. The mean difference is significant at the 0.05 level.
HCP
HCP
LCP
MCP
-85*
-39*
-7
-5
-136*
-0.17
-78
-53
-38
-12
143*
40*
6
-5
187*
0*
139*
32
24
83
85*
39*
7
5
136*
0.17
78
53
38
12
2.3.7 Potatoes - Maincrop (NED)
NED main crop potato CP, fertiliser and seed costs were significantly different between all groups. Other
crop costs were significantly higher for ORG and HCP farms. Yield was similar for conventional farm types
but significantly lower for ORG holdings, but HCP and MCP holding GMs were significantly lower than
ORG farms.
55
Table 74 NED Potatoes (Maincrop) enterprise analysis at varying CP Level
CP Input Level
Parameter
(per hectare)
LCP
mean
CP
Fert
Seeds
Other Crop Costs
Yield
Gross Margin
MCP
sd
mean
340
85
198 121
647 277
94 144
46.0 13.0
3765 2870
n
HCP
sd
555
67
232 114
786 342
141 254
47.0 11.0
3453 2761
88
mean
ORG
sd
792 112
266 125
844 350
193 266
49.0 11.0
3314 2783
176
mean
sd
12
72
79 110
1152 454
350 422
22.0 10.0
5247 3861
88
64
Table 75 NED Potatoes (Maincrop) ANOVA analysis at varying CP Level
CP Level
Parameter
LCP
MCP
HCP
MCP
ORG
LCP
CP
-215* -452*
328* 215*
Fert
-35*
-68*
119*
35*
Seeds
-140* -197* -505* 140*
Other Crops Costs
-46
-98* -256*
46
Yield
-1.9
-3.7
23.4*
1.9
GM
312
451 -1482
-312
*. The mean difference is significant at the 0.05 level.
HCP
ORG
HCP
ORG
LCP
MCP
ORG
LCP
MCP
HCP
-238*
-34*
-58*
-52
-1.8
139
543*
153*
-366*
-209*
25.3*
-1794*
452*
68*
197*
98*
3.7
-451
237*
34*
58*
52
1.8
-139
781*
187*
-308*
-157
27.0*
-1933*
-328*
-119*
505*
256*
-23.4*
1482
-543*
-153*
366*
209*
-25.3*
1794*
-781*
-187*
308*
157
-27.0*
1933*
2.3.8 Potatoes - Seed (NED)
NED seed potato enterprises had higher CP costs than the main crop type, with significant differences
between the CP groups. Fertiliser costs were similar for LCP and ORG holdings, which were significantly
lower than MCP and HCP holdings. Other crop and seed costs varied significantly between conventional
farms, but not ORG holdings, but yield was statistically different between all groups, varying between 25
and 35t/ha. LCP GM was lower than all other groups whilst MCP, HCP and ORG GM were statistically
similar.
Table 76 NED Potatoes (seed) enterprise analysis at varying CP Level
CP Input Level
Parameter
(per hectare)
LCP
mean
CP
Fert
Seeds
Other Crop Costs
Yield
Gross Margin
n
MCP
sd
376 102
139
96
878 416
156 336
27
6.2
3105 1880
91
mean
HCP
sd
629
85
207
93
1259 482
319 317
32
6.6
4593 2690
183
mean
ORG
sd
1004 206
231 122
1577 606
504 541
35
6.2
5301 2709
91
mean
sd
5
21
111 159
1717 1496
676 996
25
9.0
6627 5642
23
56
Table 77 NED Potatoes (seed) ANOVA analysis at varying CP Level
CP Level
Parameter
LCP
MCP
HCP
MCP
ORG
LCP
CP
-253*
-628*
372*
253*
Fert
-68*
-92*
28
68*
Seeds
-380*
-699*
-838
380*
Other Crops Costs
-163*
-348*
-519
163*
Yield
-5.5*
-8.3*
2
5.5*
GM
-1488* -2196* -3522* 1488*
*. The mean difference is significant at the 0.05 level.
HCP
ORG
HCP
ORG
LCP
MCP
ORG
LCP
MCP
HCP
-375*
-24
-318*
-185*
-2.9*
-708
624*
97
-458
-356
7.6*
-2034
628*
92*
699*
348*
8.3*
2196*
375*
24
318*
185*
2.9*
708
999*
120*
-140
-172
10.4*
-1325
-372*
-28
838
519
-2.1
3522*
-624*
-97
458
356
-7.6*
2034
-999*
-120*
140
172
-10.4*
1325
2.3.9 Sugar Beet (NED)
NED sugar beet CP costs were significantly different but other costs were similar between groups. ORG
yields were significantly lower but ORG GM was significantly higher than conventional groups and HCP
was significantly lower than other groups.
Table 78 NED Sugar Beet enterprise analysis at varying CP Level
CP Input Level
Parameter
(per hectare)
LCP
mean
CP
Fert
Seeds
Other Crop Costs
Yield
Gross Margin
n
MCP
sd
134
37
112
74
217
48
11
17
68.0 11.0
2585 626
218
mean
HCP
sd
235
34
116
76
226
52
10
18
69.0 12.0
2504 578
437
mean
ORG
sd
mean
389 101
110
99
235
50
14
26
66.0 11.0
2205 595
218
sd
49 107
91
88
278
99
3
5
65.0 14.0
3426 1293
17
Table 79 NED Sugar Beet ANOVA analysis at varying CP Level
CP Level
Parameter
LCP
MCP
HCP
MCP
ORG
LCP
CP
-101* -256*
85* 101*
Fert
-4
2
21
4
Seeds
-8
-17*
-61
8
Other Crops Costs
1
-2
9*
-1
Yield
-0.9
1.6
3.2
0.9
GM
81
380* -841
-81
*. The mean difference is significant at the 0.05 level.
HCP
ORG
HCP
ORG
LCP
MCP
ORG
LCP
MCP
HCP
-154*
6
-9
-3
2.5
299*
186*
25
-52
8*
4.1
-922
256*
-2
17*
2
-1.6
-380*
154*
-6
9
3
-2.5
-299*
341*
19
-43
11*
1.6
-1221*
-85*
-21
60
-9*
-3.2
841
-186*
-25
52
-8*
-4.1
922
-341*
-19
43
-11*
-1.6
1221*
2.3.10 Onions (NED)
CP costs varied significantly between CP groups for NED onions. Fertiliser costs were lowest for ORG and
LCP farms, but seed and other crop costs were significantly higher for ORG farms but similar for
conventional farms. Yield was significantly higher for HCP than ORG and LCP holdings, but GM was only
significantly higher for ORG farms.
57
Table 80 NED Onion enterprise analysis at varying CP Level
CP Input Level
Parameter
(per hectare)
LCP
mean
CP
Fert
Seeds
Other Crop Costs
Yield
Gross Margin
MCP
sd
283 116
161 103
676 398
113 280
47.0 13.0
2715 3003
n
71
mean
HCP
sd
554
95
192
99
625 200
102 177
54.0 14.0
3801 3734
mean
ORG
sd
mean
883 164
222
97
642 368
219 463
57.0 14.0
2795 3513
145
sd
17
41
110 116
1220 1193
854 876
27.0 13.0
6786 5498
71
33
Table 81 NED Onions ANOVA analysis at varying CP Level
CP Level
Parameter
LCP
MCP
HCP
MCP
ORG
LCP
CP
-271* -601*
265* 271*
Fert
-31
-61*
51
31
Seeds
51
35
-544
-51
Other Crops Costs
11
-107
741*
-11
Yield
-6.2* -10.1*
20.2* 6.2*
GM
-1085
-79 -4070* 1085
*. The mean difference is significant at the 0.05 level.
HCP
ORG
HCP
ORG
LCP
MCP
ORG
LCP
MCP
HCP
-329*
-30
-17
-118
-3.9
1006
537*
82*
-596*
-752*
26.4*
-2985*
601*
61*
-35
107
10.1*
79
329*
30
17
118
3.9
-1006
866*
112*
-579
-634*
30.2*
-3991
-265*
-51
544
741*
-20.2*
4070*
-537*
-82*
596*
752*
-26.4*
2985*
-866*
-112*
579
634*
-30.2*
3991*
2.3.11 Winter Wheat (NED)
NED Winter Wheat CP costs were significantly different for all groups, whilst fertiliser costs were
significantly higher for MCP and HCP farms but similar for ORG and LCP holdings. Seed and other crop
costs were statistically higher for ORG farms, but yields were lower. MCP and HCP yields were similar, but
higher than LCP and ORG holdings. Overall, GM was significantly higher for ORG and MCP compared to
LCP holdings.
Table 82 NED Winter Wheat enterprise analysis at varying CP Level
CP Input Level
Parameter
(per hectare)
LCP
mean
CP
Fert
Seeds
Other Crop Costs
Yield
Gross Margin
n
MCP
sd
77 45
83 64
86 40
49 58
6.5 2.2
711 476
168
mean
HCP
sd
174 24
125 53
79 24
43 56
8.3 4.0
856 676
338
mean
ORG
sd
276 65
134 58
84 25
40 49
8.7 1.7
762 353
168
mean
sd
2 12
92 109
118 83
97 54
5.0 1.6
946 477
55
58
Table 83 NED Winter Wheat ANOVA analysis at varying CP Level
CP Level
Parameter
LCP
MCP
HCP
MCP
ORG
LCP
CP
-97* -199*
-76*
97*
Fert
-42*
-51*
-9
42*
Seeds
7
2
-33*
-7
Other Crops Costs
6
9
-48*
-6
Yield
-1.8*
-2.1*
1.5*
1.8*
GM
-145*
-51 -235* 145*
*. The mean difference is significant at the 0.05 level.
HCP
-102*
-9
-5
3
-0.4
94
HCP
ORG
172*
33
-39*
-54*
3.3*
-90
LCP
MCP
199*
51*
-2
-9
2.1*
51
102*
9
5
-3
0.4
-94
ORG
ORG
275*
42
-34
-56*
3.7*
-184
LCP
MCP
HCP
-76*
9
33*
48*
-1.5*
235*
-172*
-33
39*
54*
-3.3*
90
-275*
-42
34*
56*
-3.7*
184
2.3.12 Crop enterprise data summary
To summarise the findings of this section:



Potato, sugar beet and onion crops had the highest gross margins.
Organic gross margins significantly higher than most conventional margins, despite lower yields.
Most conventional CP cost level group gross margins were not significantly different, indicating that
producers may not be adversely affected financially by moving to lower CP use.
59
2.4 Effect of applying CP taxation/levy
The aim of this analysis was to discover the direct financial effect of the application of a CP tax/levy to the
historical farm accounts data. A CP tax/levy was therefore applied at four different rates on a flat rate basis
to the CP costs identified in the data. In reality a CP tax/levy system would probably differentiate by the
toxicity of the product, but due to the nature of the data the tax could only be applied at a flat rate for all
conventional CP expenditure. It is also likely that with the application of a CP tax/levy farmers may adjust
their CP usage, which is studied in Task 7.4 and will be presented in TEAMPEST Deliverable 7.3.
2.4.1 Effect of applying CP taxation/levy to whole farm data
The following tables show the effects of a flat rate tax applied to conventional whole farm CP expenditure on
CP costs and profitability (Farm Net Value Added) variables. The difference between the average FADN
figure (2004-2007) and the calculated figure (+25% CP tax) is shown to indicate the overall effect on
profitability.
COP farms have relatively low levels of CP expenditure, but in relation to profitability a potential 5% drop in
profitability for HCP farms is quite substantial.
Table 84 COP Effects of taxation on CP and profitability (FNVA) by CP cost group
CP Tax Rate
Net Value Added €/ha
CP €/ha
LCP
MCP
HCP
Standard CP
6
48
142
+10% tax
7
52
156
+15% tax
7
55
163
+20% tax
7
57
170
+25% tax
8
59
177
% Difference (standard and 25% tax)
ORG
10
10
10
10
10
LCP
MCP
399
398
398
397
397
0%
493
488
486
483
481
-2%
HCP
ORG
712
698
690
683
676
-5%
375
375
375
375
375
0%
FIELD farms had higher CP costs than COP farms but the overall effect is smaller on profitability due to the
smaller percentage of CP costs as a proportion of total costs, with the HCP group only losing 2% profitability.
Table 85 FIELD Effects of taxation on CP and profitability (FNVA) by CP cost group
CP Tax Rate
Standard CP
+10% tax
Net Value Added €/ha
CP €/ha
LCP
16
18
MCP
92
101
HCP
ORG
LCP
MCP
HCP
ORG
345
380
25
25
837
836
1267
1258
4238
4204
1012
1012
+15% tax
19
105
397
+20% tax
20
110
414
+25% tax
20
114
431
% Difference (standard and 25% tax)
25
25
25
835
834
833
0%
1253
1249
1244
-2%
4187
4169
4152
-2%
1012
1012
1012
0%
HORT holdings were the highest users of CP products so would be expected to be adversely affected by a
CP tax/levy but similarly to FIELD farms their turnover is far superior to their crop costs so there was only a
2% reduction in the HCP group’s profit, despite a substantial €1400 increase in CP costs.
Table 86 HORT Effects of taxation on CP and profitability (FNVA) by CP cost group
CP Tax Rate
Standard CP
+10% tax
Net Value Added €/ha
CP €/ha
LCP
60
66
MCP
689
758
HCP
5588
6147
ORG
LCP
MCP
HCP
ORG
494 27074 24771 89683 13149
494 27068 24702 89124 13149
60
+15% tax
+20% tax
+25% tax
69
72
75
792
827
861
6427
6706
6985
494 27065 24668 88844 13149
494 27062 24633 88565 13149
494 27059 24599 88286 13149
% Difference (standard and 25% tax)
0%
-1%
-2%
0%
The effect on WINE holdings was similar to HORT units as turnover was far higher than CP costs, so only a
2% reduction in profit was expected for HCP holdings.
Table 87 WINE Effects of taxation on CP and profitability (FNVA) by CP cost group
CP Tax Rate
Net Value Added €/ha
CP €/ha
LCP
MCP
HCP
Standard CP
28
202
778
+10% tax
30
223
855
+15% tax
32
233
894
+20% tax
33
243
933
+25% tax
34
253
972
% Difference (standard and 25% tax)
ORG
179
179
179
179
179
LCP
MCP
HCP
ORG
1656
1653
1651
1650
1649
0%
2654
2634
2624
2614
2604
-2%
12649
12571
12533
12494
12455
-2%
3134
3134
3134
3134
3134
0%
ORCH holdings were slightly more severely affected than other permanent crop type holdings due to a
higher CP expenditure relative to profitability, and may be affected by up to 4% reduction in profit.
Table 88 ORCH Effects of taxation on CP and profitability (FNVA) by CP cost group
CP Tax Rate
Net Value Added €/ha
CP €/ha
LCP
MCP
HCP
ORG
LCP
MCP
HCP
ORG
Standard CP
40
255
843
242
2630
4174
5767
3510
+10% tax
+15% tax
44
46
281
294
927
970
242
242
2626
2624
4148
4135
5683
5641
3510
3510
+20% tax
48
307
1012
+25% tax
50
319
1054
% Difference (standard and 25% tax)
242
242
2622
2620
0%
4123
4110
-2%
5598
5556
-4%
3510
3510
0%
OLIVE holdings were less reliant on CP expenditure to achieve profitability so profitability was only
predicted to fall by 2%.
Table 89 OLIVE Effects of taxation on CP and profitability (FNVA) by CP cost group
CP Tax Rate
Standard CP
Net Value Added €/ha
CP €/ha
LCP
9
MCP
61
HCP
ORG
LCP
MCP
HCP
ORG
219
38
1473
2298
2522
2364
+10% tax
10
67
241
+15% tax
10
70
252
+20% tax
11
73
263
+25% tax
11
76
274
% Difference (standard and 25% tax)
38
38
38
38
1472
1471
1471
1470
0%
2292
2289
2286
2283
-1%
2500
2489
2478
2467
-2%
2364
2364
2364
2364
0%
PERM holdings were the least affected by the application of a CP tax/levy. Despite the addition of the 25%
tax, profitability was only reduced by 1% in MCP and HCP groups.
61
Table 90 PERM Effects of taxation on CP and profitability (FNVA) by CP cost group
CP Tax Rate
Standard CP
+10% tax
+15% tax
+20% tax
Net Value Added €/ha
CP €/ha
LCP
14
16
16
17
MCP
98
107
112
117
HCP
ORG
LCP
MCP
HCP
ORG
552
607
635
663
85
85
85
85
3357
3356
3355
3354
2575
2565
2560
2555
12943
12888
12861
12833
5181
5181
5181
5181
+25% tax
18
122
690
% Difference (standard and 25% tax)
85
3354
0%
2550
-1%
12805
-1%
5181
0%
MIXED farms had a similar relationship between CP expenditure and profitability to FIELD farms which
resulted in a similar 2% reduction in profit.
Table 91 MIXED Effects of taxation on CP and profitability (FNVA) by CP cost group
CP Tax Rate
Net Value Added €/ha
CP €/ha
LCP
MCP
HCP
ORG
LCP
MCP
HCP
ORG
Standard CP
+10% tax
6
7
53
58
328
361
25
25
1025
1024
1542
1537
4072
4039
1235
1235
+15% tax
+20% tax
7
7
61
64
377
394
25
25
1024
1023
1534
1532
4023
4006
1235
1235
+25% tax
8
66
410
% Difference (standard and 25% tax)
25
1023
0%
1529
-1%
3990
-2%
1235
0%
2.4.2 Effect of applying CP taxation/levy to national crop enterprise data
The same tax/levy rates were applied to enterprise data from UK and NED to highlight potential changes in
gross margins of various crops. To obtain a better view of the likely effects of a tax/levy scheme, the
conventional farm data was split into 5 groups, split by their CP costs, using 20% percentiles as the cut-off
values, rather than Q1 and Q3 used earlier to determine groups. This resulted in five approximately equal
sized conventional holding groups; Very Low CP costs (VLCP), Low CP costs (LCP), Medium CP costs
(MCP), High CP costs (HCP) and Very High CP costs (VHCP), in addition to the group of organic farms
(where available).
2.4.2.1
UKI Enterprise Data
Table 92 indicates the effect of a 25% tax/levy applied to CP costs for the various CP cost groups. For all
crops, the greatest effect was found in the highest CP usage group, but the percentage effect varied between
crops, depending on the level of CP expenditure compared to output. Beans and oilseed rape were the worst
affected even though potatoes saw the largest actual increase in CP costs.
62
Table 92 UKI average enterprise GM at 0% CP tax and 25% CP tax rates, at varying CP Levels
Crop
GM/ha
Winter Wheat
Standard CP
CP+25% tax
Spring Barley
Beans
Potatoes
867
844
Low
857
822
Med
838
796
High
936
887
V High
792
728
Org
1125
1125
Difference
-3%
-4%
-5%
-5%
-8%
0%
Standard CP
CP+25% tax
570
565
652
639
604
585
623
597
559
517
760
760
Difference
-1%
-2%
-3%
-4%
-7%
0%
Standard CP
CP+25% tax
365
356
327
307
350
324
477
444
470
423
629
629
Difference
-3%
-6%
-7%
-7%
-10%
0%
4841
4780
3721
3612
4023
3882
4460
4298
3558
3298
4044
4044
Standard CP
CP+25% tax
Difference
Sugar Beet
V Low
Standard CP
CP+25% tax
Difference
Winter Oilseed Rape Standard CP
CP+25% tax
Difference
-1%
-3%
-4%
-4%
-7%
0%
1235
1212
1076
1038
1101
1056
1182
1129
1050
982
nd
nd
-2%
-4%
-4%
-5%
-6%
551
528
521
489
564
526
741
694
661
598
-4%
-6%
-7%
-6%
-9%
nd
nd
The ANOVA analysis of enterprise CP costs groups before and after applying a 25% CP tax/levy for the UK
and NED enterprises is presented as post-hoc mean differences in Table 93 to
63
Table 104, with significant differences at the 0.05 level indicated by a *.
Table 93 indicates that for most Winter Wheat CP cost groups their relationship did not change, but that with
the addition of the tax/levy the ORG group GM became significantly higher than the HCP group
Table 93 UKI Winter Wheat GM at no tax and 25% CP tax rates (ANOVA analysis at varying CP
Levels)
VLCP
LCP
MCP
HCP
VHCP
ORG
GM/ha
Standard CP
CP+25% tax
Standard CP
CP+25% tax
Standard CP
CP+25% tax
Standard CP
CP+25% tax
Standard CP
CP+25% tax
Standard CP
CP+25% tax
VLCP
LCP
MCP
n/a
n/a
10
22
-10
-22
-29
-48
69
43
-75
-116
258*
281*
n/a
n/a
-19
-26
79
65
-65
-94
268*
303*
HCP
29
48
19
26
n/a
n/a
98
91
-46
-68
287*
329*
VHCP
-69
-43
-79
-65
-98
-91
n/a
n/a
-144*
-159*
189
238*
n/a
n/a
ORG
-258*
-281*
-268*
-303*
-287*
-329*
-189
-238*
-333*
-397*
333*
397*
n/a
n/a
75
116
65
94
46
68
144*
159*
*. The mean difference is significant at the 0.05 level.
The tax/levy did not have any significant effects on the differences in GM of Spring Barley enterprises.
64
Table 94 UKI Spring Barley GM at no tax and 25% CP tax rates (ANOVA analysis at varying CP
Levels)
GM/ha
VLCP
LCP
MCP
HCP
VHCP
ORG
Standard CP
CP+25% tax
Standard CP
CP+25% tax
Standard CP
CP+25% tax
Standard CP
CP+25% tax
Standard CP
CP+25% tax
Standard CP
CP+25% tax
VLCP
LCP
MCP
n/a
n/a
-82
-74
82
74
35
20
54
32
-11
-48
190
195
n/a
n/a
-47
-54
-28
-42
-93
-122
108
121
HCP
-35
-20
47
54
-54
-32
28
42
-19
-12
n/a
n/a
19
12
-46
-68
156
175
VHCP
n/a
n/a
-65
-80
137
163
11
48
93
122
46
68
65
80
ORG
n/a
n/a
-190
-195
-108
-121
-156
-175
-137
-163
-201*
-243*
201*
243*
n/a
n/a
*. The mean difference is significant at the 0.05 level.
The tax/levy did not have any significant effects on the differences in GM of UK Bean enterprises.
Table 95 UKI Beans GM at no tax and 25% CP tax rates (ANOVA analysis at varying CP Levels)
GM/ha
VLCP
LCP
MCP
HCP
VHCP
ORG
Standard CP
CP+25% tax
Standard CP
CP+25% tax
Standard CP
CP+25% tax
Standard CP
CP+25% tax
Standard CP
CP+25% tax
Standard CP
CP+25% tax
VLCP
LCP
MCP
n/a
n/a
39
49
-39
-49
-15
-32
111
88
105
67
264*
273*
n/a
n/a
23
17
150
137
144
115
303*
322*
HCP
15
32
-23
-17
n/a
n/a
127
120
120
99
279*
305*
VHCP
-111
-88
-150
-137
-127
-120
n/a
n/a
-7
-22
152
185
-105
-67
-144
-115
-120
-99
7
22
ORG
n/a
n/a
-264*
-273*
-303*
-322*
-279*
-305*
-152
-185
-159
-206
159
206
n/a
n/a
*. The mean difference is significant at the 0.05 level.
Despite large differences between CP cost groups none of the groups were found to differ significantly
before or after applying a tax/levy.
Table 96 UKI Potatoes GM at no tax and 25% CP tax rates (ANOVA analysis at varying CP Levels)
GM/ha
VLCP
LCP
MCP
HCP
VHCP
Standard CP
CP+25% tax
Standard CP
CP+25% tax
Standard CP
CP+25% tax
Standard CP
CP+25% tax
Standard CP
CP+25% tax
VLCP
LCP
MCP
n/a
n/a
1121
1168
-1121
-1168
-818
-898
-381
-482
-1283
-1481
n/a
n/a
302
270
740
686
-162
-313
HCP
818
898
-302
-270
n/a
n/a
437
417
-464
-583
VHCP
381
482
-740
-686
-437
-417
n/a
n/a
1283
1481
162
313
464
583
902
1000
-902
-1000
n/a
n/a
ORG
798
736
-323
-432
-21
-162
417
254
-485
-745
65
ORG
Standard CP
CP+25% tax
-798
-736
323
432
21
162
-417
-254
485
745
n/a
n/a
*. The mean difference is significant at the 0.05 level.
Similar to potatoes, despite large differences between CP cost groups none of the groups were found to differ
significantly before or after applying a tax/levy.
Table 97 UKI Sugar Beet GM at no tax and 25% CP tax rates (ANOVA analysis at varying CP Levels)
GM/ha
VLCP
LCP
MCP
HCP
VHCP
Standard CP
CP+25% tax
Standard CP
CP+25% tax
Standard CP
CP+25% tax
Standard CP
CP+25% tax
Standard CP
CP+25% tax
VLCP
LCP
MCP
n/a
n/a
160
174
-160
-174
-135
-156
-53
-83
-185
-230
n/a
n/a
HCP
135
156
-25
-18
25
18
107
91
-26
-56
n/a
n/a
82
73
-51
-74
VHCP
53
83
-107
-91
-82
-73
n/a
n/a
185
230
26
56
51
74
132
147
-132
-147
n/a
n/a
*. The mean difference is significant at the 0.05 level.
Applying the tax/levy resulted in only one change in statistical differences, with HCP and MCP holdings
becoming non-significantly different, indicating that a medium level of CP costs would achieve a similar
GM to a higher CP input.
Table 98 UKI Winter Oilseed Rape GM at no tax and 25% CP tax rates (ANOVA analysis at varying
CP Levels)
GM/ha
VLCP
LCP
MCP
HCP
VHCP
Standard CP
CP+25% tax
Standard CP
CP+25% tax
Standard CP
CP+25% tax
Standard CP
CP+25% tax
Standard CP
CP+25% tax
VLCP
LCP
MCP
n/a
n/a
30
39
-30
-39
13
-3
190*
166*
110
70
n/a
n/a
43
36
220*
205*
140
109
HCP
-13
3
-43
-36
n/a
n/a
177*
169
96
73
VHCP
-190*
-166*
-220*
-205*
-177*
-169
n/a
n/a
-110
-70
-140
-109
-96
-73
80
96
-80
-96
n/a
n/a
*. The mean difference is significant at the 0.05 level.
2.4.2.2
NED Enterprise Data
66
Table 99 indicates the effect of a 25% tax/levy applied to CP costs for the various NED CP cost groups. For
all crops, the greatest effect was found in the highest CP usage group, but the percentage effect varied
between crops, depending on the level of CP expenditure compared to output. Wheat and onion enterprises
were the worst affected even though potatoes saw the largest actual increase in CP costs.
67
Table 99 NED average enterprise GM at 0% CP tax and 25% CP tax rates at varying CP Levels
Crop
GM/ha
Potatoes
(cons.)
Standard CP
CP+25% tax
VLCP
3706
3626
Difference
Potatoes
(seed)
Standard CP
CP+25% tax
Standard CP
CP+25% tax
Wheat
HCP
3578
3439
VHCP
2943
2782
ORG
3512
3307
5247
5247
-2%
-3%
-4%
-5%
-6%
0%
3833
3704
4629
4473
5113
4925
5385
5122
6627
6627
-3%
-3%
-3%
-4%
-5%
0%
2587
2556
2575
2528
2559
2501
2346
2275
2181
2078
3426
3426
Difference
Onions
3748
3633
MCP
3034
2947
Difference
Sugar Beet
LCP
-1%
-2%
-2%
-3%
-5%
0%
2706
2642
3651
3544
3679
3542
3859
3687
2505
2275
6786
6786
Difference
-2%
-3%
-4%
-4%
-9%
0%
Standard CP
CP+25% tax
714
697
741
707
867
823
910
858
752
680
946
946
Difference
-2%
-5%
-5%
-6%
-10%
0%
Standard CP
CP+25% tax
Although there were few significant differences between CP cost groups for NED maincrop potatoes,
applying the tax resulted in the VHCP and MCP groups GM becoming significantly lower than the ORG
group, as was the HCP group.
Table 100 NED Potatoes (maincrop) GM at 0% tax and 25% CP tax rates (ANOVA analysis at
varying CP Levels)
GM/ha
VLCP
LCP
MCP
HCP
VHCP
ORG
Standard CP
CP+25% tax
Standard CP
CP+25% tax
Standard CP
CP+25% tax
Standard CP
CP+25% tax
Standard CP
CP+25% tax
Standard CP
CP+25% tax
VLCP
LCP
MCP
n/a
n/a
-42
-7
42
7
-127
-187
-762
-844
-193
-319
1542
1621
n/a
n/a
-170
-194
-805
-851
-236
-326
1499
1615
HCP
127
187
170
194
n/a
n/a
-635
-657
-66
-132
1669
1809*
VHCP
762
844
805
851
635
657
n/a
n/a
569
525
2304*
2465*
193
319
236
326
66
132
-569
-525
ORG
n/a
n/a
-1542
-1621
-1499
-1615
-1699
-1809*
-2304*
-2465*
-1735
-1941*
1735
1941*
n/a
n/a
*. The mean difference is significant at the 0.05 level.
Through applying the tax/levy the CP costs groups became statistically more similar with the only significant
difference remaining between the VLCP/LCP and VHCP groups.
Table 101 NED Potatoes (seed) GM at 0% tax and 25% CP tax rates (ANOVA analysis at varying CP
Levels)
GM/ha
VLCP
LCP
MCP
Standard CP
CP+25% tax
Standard CP
CP+25% tax
Standard CP
VLCP
LCP
MCP
HCP
n/a
n/a
-799
-757
799
757
1595*
n/a
n/a
-1595*
-1526*
-796
-769
796
n/a
-2079*
-1978*
-1280*
-1221
-484
VHCP
-2351*
-2176*
-1552*
-1419*
-756
ORG
-3593
-3681
-2794
-2924
-1999
68
HCP
VHCP
ORG
CP+25% tax
Standard CP
CP+25% tax
Standard CP
CP+25% tax
Standard CP
CP+25% tax
1526*
2079*
1978*
2351*
2176*
3593
3681
769
1280*
1221
1552*
1419*
2794
2924
n/a
-452
484
452
756
649
1999
2155
n/a
n/a
272
197
1515
1703
-649
-272
-197
n/a
n/a
-2155
-1515
-1703
-1242
-1505
1242
1505
n/a
n/a
*. The mean difference is significant at the 0.05 level.
By applying the tax/levy the ORG group achieved a significantly higher GM than the HCP and VHCP
groups that were non-significant with no CP tax/levy.
Table 102 NED Sugar Beet GM at 0% tax and 25% CP tax rates (ANOVA analysis at varying CP
Levels)
GM/ha
VLCP
LCP
MCP
HCP
VHCP
ORG
Standard CP
CP+25% tax
Standard CP
CP+25% tax
Standard CP
CP+25% tax
Standard CP
CP+25% tax
Standard CP
CP+25% tax
Standard CP
CP+25% tax
VLCP
LCP
MCP
n/a
n/a
12
28
-12
-28
-28
-56
-241*
-281*
-406*
-478*
839
870
n/a
n/a
-16
-27
-229*
-253*
-394*
-450*
851
898
HCP
28
56
16
27
n/a
n/a
-213*
-225
-378*
-422*
867
925
VHCP
241*
281*
229*
253*
213*
225*
n/a
n/a
-165
-197*
1080
1151*
406*
478*
394*
450*
378*
422*
165
197*
ORG
n/a
n/a
-839
-870
-851
-898
-867
-925
-1080
-1151*
-1245
-1348*
1245*
1348*
n/a
n/a
*. The mean difference is significant at the 0.05 level.
The only difference after applying the tax was a significance difference between the ORG and MCP groups.
Table 103 NED Onions GM at 0% tax and 25% CP tax rates (ANOVA analysis at varying CP Levels)
GM/ha
VLCP
LCP
MCP
HCP
VHCP
ORG
Standard CP
CP+25% tax
Standard CP
CP+25% tax
Standard CP
CP+25% tax
Standard CP
CP+25% tax
Standard CP
CP+25% tax
Standard CP
CP+25% tax
VLCP
LCP
MCP
n/a
n/a
-945
-902
945
902
973
900
1153
1046
-201
-367
4080*
4144*
n/a
n/a
28
-2
208
144
-1146
-1269
3135
3242
HCP
-973
-900
-28
2
n/a
n/a
180
146
-1175
-1267
3106
3244*
VHCP
-1153
-1046
-208
-144
-180
-146
n/a
n/a
-1354
-1413
2927
3098
201
367
1146
1269
1175
1267
1354
1413
ORG
n/a
n/a
-4080*
-4144*
-3135
-3242
-3106
-3244*
-2927
-3098
-4281*
-4511*
4281*
4511*
n/a
n/a
*. The mean difference is significant at the 0.05 level.
The large percentage change in NED Wheat GM was highlighted by the VHCP group GM becoming
significantly lower than both the MCP and ORG groups GM.
69
Table 104 NED Wheat GM at 0% tax and 25% CP tax rates (ANOVA analysis at varying CP Levels)
GM/ha
VLCP
LCP
MCP
HCP
VHCP
ORG
Standard CP
CP+25% tax
Standard CP
CP+25% tax
Standard CP
CP+25% tax
Standard CP
CP+25% tax
Standard CP
CP+25% tax
Standard CP
CP+25% tax
VLCP
LCP
MCP
n/a
n/a
-28
-10
28
10
153
126
197
161
39
-17
233*
249*
n/a
n/a
125
116
169
152
11
-27
205
240*
HCP
-153
-126
-125
-116
n/a
n/a
44
35
-114
-143*
80
123
VHCP
-197
-161
-169
-152
-44
-35
n/a
n/a
-158
-178
36
88
-39
17
-11
27
114
143*
158
178
ORG
n/a
n/a
-233*
-249*
-205
-240*
-80
-123
-36
-88
-194
-266*
194
266*
n/a
n/a
*. The mean difference is significant at the 0.05 level.
2.4.3 Summary of the effects of a CP tax/levy
To summarise this section:
 Cereal, Oilseed & Pulse and Orchard type holdings saw the greatest percentage reduction in
profitability when the tax/levy was applied, whilst Permanent Crops had the least effect.
 Other farm types saw a 2% profit decrease at a flat rate of 25% CP tax/levy.
 Cereal and oilseed crop enterprise gross margins were more severely affected than potato and sugar
beet enterprises, reflecting their lower relative output compared to CP costs.
 The CP tax/levy had the effect of reducing the gross margin of NED potato and sugar beet
enterprises by enough to result in the organic gross margin being significantly higher, and for the
very high input CP group GM to become significantly lower than the high CP group.
70
3 Conclusions and Policy Recommendations
Results of FADN data analysis in Task 7.2 highlighted HORT and some permanent crop farm types (e.g.
WINE and ORCH) as the most intensive CP product users, but there was a large difference in CP use on
conventional farms within these farm types. Overall, the Western EU CP costs were more than double that of
the other EU regions, whilst Holland, Bulgaria and Belgium had the highest CP costs by country, reflecting
their predominant types of agriculture.
The analysis of available crop enterprise data from UK and NED indicated that the most CP intensive crops
were potatoes, onions and sugar beet, but that the highest crop gross margins were often achieved by organic
farms and that within the conventional farming groups the high CP input systems did not necessarily achieve
the highest gross margins (e.g. the medium CP cost group achieved the highest conventional GM for UK
Spring Barley, the NED LCP maincrop potato group GM was 7% higher than the VHCP group).
In Task 7.3, the application of a tax/levy to the CP cost data resulted in COP and ORCH farm type
profitability being the most severely affected, whilst the CP intensive HORT farm type profitability fell by
less than 2%. This reflects how high COP and ORCH farm CP costs are relative to their output, and how CP
costs are of less importance on HORT holdings, despite being far higher in monetary value. The CP tax/levy
did have the effect of reducing the high and very high CP input potato enterprise GM by enough for the
organic enterprises to become significantly more profitable.
Due to the nature of the data available a flat rate tax/levy was applied, but had a variable effect on the
profitability of farms and crop enterprises, which may not reduce CP usage where it was intended. For
example, due to the larger percentage effect on profitability of COP farms, a tax/levy may reduce CP usage
on high input COP farms, but not reduce CP usage significantly within HORT type holdings due to the
smaller percentage effect on profitability.
The data analysis identified that financially, some organic farm types performed well in many farm types,
especially for the permanent crop types with profitability at or above the level of conventional LCP and MCP
holdings. At enterprise level, many organic holding gross margins were above conventional levels e.g. UK
winter wheat and NED maincrop potatoes. However, due to the limited size of the organic market it would
not be expected that a significant number of farms would be able to convert to organic farming and receive
the premium prices necessary for reduced yield levels.
The variability in CP use on conventional farms potentially indicated that lower input management
techniques do exist and could be adopted more widely, but the analysis highlighted that profitability was also
generally lower for low CP intensity systems (e.g. 44% lower for COP, 87% lower for WINE farm types),
which would be likely to inhibit its wider uptake. Therefore, although desirable to reduce CP use, a move to
lower input systems, would appear to result in lower profitability for the farmer (at whole farm level),
compared to higher CP intensity systems.
Therefore, from this financial analysis it can be concluded that a CP tax/levy system would have some affect
on the profitability of conventional EU cropping holdings, but that this effect is variable. It cannot be
assumed that the most intensive users per hectare will be the most severely affected as this depends on the
relationship of CP costs to overall output. Whilst at crop enterprise level a CP tax/levy had the effect of
reducing differences between CP input groups and organic holdings, at whole farm level the high CP input
group remained the most profitable.
A flat rate type of tax on all CP products is unlikely to achieve a significant reduction in CP usage, and a
tax/levy system would need to be a “targeted” mechanism to ensure a reduction in usage on the most CP
intense holdings (if this was desired from a policy perspective). However, based on this economic analysis
alone a tax/levy is unlikely to result in the wider adoption of low input or organic techniques due to poorer
overall farm profitability than high input conventional systems and a lack of large-scale new organic market
potential, particularly within the current economic climate within the EU.
In conclusion, although this analysis has shown that a CP tax/levy is unlikely to drastically change EU CP
usage through economics alone, TEAMPEST Deliverable 7.1 (Little et al. 2009), identified that although
important, profitability was not the only driver to CP product use. TEAMPEST Task 7.4 will illicit farmer
71
responses to a tax or levy to ascertain what other drivers may be influencing their choice of system now and
in the future, which may identify more successful methods to reduce the intensity of CP usage.
72
4 Relevance to other work packages in TEAMPEST
This work will be relevant to other aspects of the TEAMPEST project. Work package 5 will evaluate the
impacts of tax and levy schemes on farm level decision making to gauge the micro-foundations of the
alternative macro-level solutions. This is directly relevant to WP7 in that any tax or levy schemes on
pesticide use will influence the economic viability of farming systems and is, therefore, likely to influence
farmer decision making regarding the uptake of alternative lower pesticide input systems. Similarly, work
package 6 aims to design agricultural support policies and optimum tax and levy schemes on pesticides
which will again directly influence the economic performance of farm systems and the likely uptake of
alternative low input farming practices. The outputs from work package 7 will be directly applied in work
package 8 to case studies in Bulgaria and Portugal.
73
5 References
Elbersen B., Kempen, M., van Diepen K., Andersen E., Hazeu G., Verhoog D. (2006) Protocols for spatial
allocation of farm types, SEAMLESS Report No.19, SEAMLESS integrated project, EU 6th Framework
Programme, contract no. 010036-2, www.SEAMLESS-IP.org, 107 pp, ISBN no. 90-8585-046-0.
EC (2008) COMMISSION REGULATION (EC) No 889/2008
EU (2010) InforEuro, official EU currency conversion for GBP:Euro
FADN (2007), Definitions of variables used in FADN standard results
FADN (2009a) http://ec.europa.eu/agriculture/rica/index_en.cfm
FADN (2009b) Weighting system of EU-FADN results
http://ec.europa.eu/agriculture/rica/methodology3_en.cfm
http://eur-lex.europa.eu/LexUriServ/LexUriServ.do?uri=OJ:L:2008:250:0001:0084:EN:PDF
http://ec.europa.eu/budget/inforeuro/index.cfm?fuseaction=currency_historique&currency=72&Language=e
n
IBM (2008) SPSS Statistics 16 software
Little, A. and Nicholas, P. (2009) Socio-Economic Factors Influencing the Adoption of Organic Farming
and Other Low Input Pesticide Systems: A Literature Review, TEAMPEST Deliverable D7.1, Theoretical
Developments and Empirical Measurement of the External Costs of Pesticides project, EU 7th Framework
Programme, contract no. 212120, http://www.eng.auth.gr/mattas/teampest/project.htm, 48 pp,
Maletta, H. (2007) Weighting within SPSS http://www.spsstools.net/Tutorials/WEIGHTING.pdf
74
6 Appendix
6.1 Appendix 1: FADN farm typologies
Table 105 FADN - General TF farm typologies
General TF
1
Specialist field crops
2
Specialist horticulture
3
Specialist permanent Crops
4
Specialist grazing livestock
5
Specialist granivore
6
Mixed cropping
7
Mixed livestock
8
Mixed crops-livestock
9
Non classifiable
Table 106 FADN – TF14 farm typologies
TF14
13
Specialist COP
14
Specialist other fieldcrops
20
Specialist horticulture
31
Specialist wine
32
Specialist orchards - fruits
33
Specialist olives
34
Permanent crops combined
41
Specialist milk
44
Specialist sheep and goats
45
Specialist cattle
50
Specialist granivores
60
Mixed crops
70
Mixed livestock
80
Mixed crops and livestock
75
6.2 Appendix 2: FADN requested variable list
selected
NAME
DESCRIPTION
prefix
suffix1
y
A1
Region
A
1
A
y
A2
Sub-region
A
2
A
y
A24
Country
A
24
A
y
A27
Econ.size in EUR
A
27
y
y
A28
A29
General TF
A
Principal TF
A
28
29
y
A3
Farm Number
A
3
y
A32
Organic farming
A
32
y
A39
Less
Area
A
39
favoured
suffix2
comment
Related
table
Calculated by DG
AGRI (cf Typology
Regulation)
A
1-digit Calculated by
DG
AGRI
(cf
Typology
Regulation)
A
2-digit Calculated by
DG
AGRI
(cf
Typology
Regulation)
A
A
From 2000
A
The Netherlands do
no provide data on
LFA
classification
(use of code 4) and
LFA payments. They
considere LFA not
significant for the
country. In Germany
all the LFA farms
have been classified
under code 2 (LFAOther
than
Mountain).
This
should not be the
case any more for
2007 and following
accounting years.
A
y
A40
UAA
irrigation
under
A
40
A
y
A41
Altitude zone
A
41
y
A43
Area under glass
or plastic
A
43
A
A
76
y
y
y
y
y
y
A45
B48
C01YR
JC74
JC75
JC76
Environmental
constraints Area
(EC no 1257/1999
and 1698/2005)
A
UAA in owner
occupation
B
Unpaid-Reg
Holder/Mgr 1 Y/B
C
Subs.for fertilizers
and soil
J
Subs.for
crop
protection produ
J
Subs.for
other
specific crop c
J
45
e.g.: the majority of
the UAA of the farm
is located in a 'Natura
2000' area or in an
area linked to the
Directive
2000/60/EC (water).
A
48
B
01
YR
Year of birth
C
C74
J
C75
J
C76
J
y
SE005
Economic size
SE
005
in ESU
A
y
SE010
Total labour input
SE
010
in AWU
B
y
SE011
Labour input
SE
011
in hours
B
y
SE025
Total
Utilised
Agricultural Area
SE
025
Cereals
SE
y
y
y
y
SE035
SE041
SE042
SE046
Other field crops
Energy crops
Vegetables
flowers
SE
SE
and
SE
035
041
042
046
area in ha
B
area in ha - including
crops
grown
to
produce energy
B
area in ha - including
crops
grown
to
produce energy
B
area in ha - type of
crop = 10
B
area in ha
B
y
SE050
Vineyards
SE
050
area in ha
B
y
SE054
Permanent crops
SE
054
area in ha
B
y
SE055
Orchards
SE
055
area in ha
B
y
SE060
Olive groves
SE
060
area in ha
B
y
SE065
Other
crops
SE
065
permanent
area in ha
B
y
SE071
Forage crops
SE
071
area in ha
B
y
SE110
Yield of wheat
SE
110
in q/ha - global ratio
B
y
SE115
Yield of maize
SE
115
in q/ha - global ratio
B
y
SE131
Total output
SE
131
K
77
y
SE135
Total output crops
& crop production
SE
135
K
y
SE140
Cereals
SE
140
K
y
SE145
Protein crops
SE
145
K
y
SE146
Energy crops
SE
146
K
y
SE150
Potatoes
SE
150
K
y
SE155
Sugar beet
SE
155
K
y
SE160
Oil-seed crops
SE
160
K
y
SE165
Industrial crops
SE
165
K
y
SE170
Vegetables
flowers
SE
170
&
K
y
SE175
Fruit
SE
175
K
y
SE180
Citrus fruit
SE
180
K
y
SE185
Wine and grapes
SE
185
K
y
SE190
Olives & olive oil
SE
190
K
y
SE200
Other crop output
SE
200
K
y
SE270
Total Inputs
SE
270
F
y
SE281
Total
costs
SE
281
specific
F
y
SE295
Fertilisers
SE
295
F
y
SE300
Crop protection
SE
300
F
y
SE305
Other
crop
specific costs
SE
305
Gross
Income
SE
y
y
y
y
y
y
SE410
SE415
SE420
SE425
SE425D
SE631
Farm
F
S
Farm Net Value
Added
SE
Family
Income
SE
Farm
SE
AWU
SE
Farm
415
S
Farm Net Value
Added / AWU
Single
payment
410
SE
420
425
425D
This indicator is
calculated for the
whole
farms
including
those
without
family
labour
Global ratio
FNVA/AWU
denominator
SE010)
S
S
(=
S
631
J
78
y
SE632
Single
payment
Area
SE
632
J
y
SYS02
Farms represented
SYS
02
A
y
SYS03
Sample farms
SYS
03
A
y
SYS04
Exchange rate
SYS
04
A
y
TF14
TF14 Grouping
class
A
y
YEAR
Year
class
A
6.3 Appendix 3: UN EU region classification
(http://unstats.un.org/unsd/methods/m49/m49regin.htm)
150
Europe
151
Eastern Europe
112
Belarus
100
Bulgaria
203
Czech Republic
348
Hungary
616
Poland
498
Republic of Moldova
642
Romania
643
Russian Federation
703
Slovakia
804
Ukraine
154
Northern Europe
248
Åland Islands
830
Channel Islands
208
Denmark
233
Estonia
234
Faeroe Islands
246
Finland
831
Guernsey
352
Iceland
372
Ireland
833
Isle of Man
832
Jersey
428
Latvia
440
Lithuania
578
Norway
744
Svalbard and Jan Mayen Islands
752
Sweden
826
United Kingdom of Great Britain and Northern Ireland
039
Southern Europe
008
Albania
020
Andorra
070
Bosnia and Herzegovina
191
Croatia
79
292
Gibraltar
300
Greece
336
Holy See
380
Italy
470
Malta
499
Montenegro
620
Portugal
674
San Marino
688
Serbia
705
Slovenia
724
Spain
807
The former Yugoslav Republic of Macedonia
196
Cyprus*
155
Western Europe
040
Austria
056
Belgium
250
France
276
Germany
438
Liechtenstein
442
Luxembourg
492
Monaco
528
Netherlands
756
Switzerland
* Cyprus classed as Western Asia by UN, but classed as Southern Europe for FADN analysis
80
6.4 Appendix 4: Additional data tables
Table 107 Mean cp/ha by country for each year 2004-2007, (TEAMPEST TF14 farm types only)
Type
Country
CONVENTIONAL
BEL
BGR
CYP
CZE
DAN
DEU
ELL
ESP
EST
FRA
HUN
Year
2004
2005
2006
2007
2004
2005
2006
2007
2004
2005
2006
2007
2004
2005
2006
2007
2004
2005
2006
2007
2004
2005
2006
2007
2004
2005
2006
2007
2004
2005
2006
2007
2004
2005
2006
2007
2004
2005
2006
2007
2004
CP/ha
768
754
768
1161
1285
322
206
257
322
206
257
312
288
314
386
306
225
187
203
186
380
384
406
398
186
192
181
178
288
207
204
177
37
43
28
23
365
347
382
385
129
sd
n
range
1871
25185
1538
13283
1703
13808
2298
28058
8079
255650
597
7675
350
2881
398
2297
597
7675
350
2881
398
2297
502
5024
1184
23507
1248
15215
1215
15811
858
8365
1362
36414
1234
47181
1288
26278
1038
19743
991
25093
1072
23173
1219
28659
1097
33176
735
30000
706
26000
722
27820
777
30324
1175
35046
521
14173
526
11734
464
14524
177
2019
217
2498
102
1098
54
705
813
23818
950
36641
819
23187
832
21058
407
5640
321
301
319
364
1141
376
380
354
376
380
354
367
647
597
647
675
845
848
855
887
2535
2686
2844
2877
3530
3315
3176
3106
4674
5267
5170
5118
200
196
195
199
3633
3626
3630
3659
1355
81
IRE
ITA
LTU
LUX
LVA
MLT
NED
OST
POL
POR
ROU
2005
2006
2007
2004
2005
2006
2007
2004
2005
2006
2007
2004
2005
2006
2007
2004
2005
2006
2007
2004
2005
2006
2007
2004
2005
2006
2007
2004
2005
2006
2007
2004
2005
2006
2007
2004
2005
2006
2007
2004
2005
2006
2007
2004
2005
2006
170
192
247
116
103
87
112
249
246
252
262
29
26
23
26
490
558
687
735
17
21
21
25
462
374
385
473
1657
1903
2539
2807
134
122
136
143
168
202
172
244
168
171
165
186
70
301
220
621
8970
667
10311
807
16869
59
368
68
333
55
303
69
412
641
33214
612
46078
648
55563
737
51536
73
771
31
504
25
631
31
756
383
1472
455
1433
462
1629
450
1275
36
392
126
5736
73
1943
115
4560
1465
12651
1059
13334
995
13659
1006
22518
3432
36027
3975
40240
6348
88669
6259
68206
159
1384
145
1442
162
1455
153
990
542
11128
837
22005
687
18517
2619
104734
370
13213
442
14953
483
16533
446
14296
142
3601
3039
76414
2114
49418
1367
1338
1399
50
40
43
52
9173
9483
9312
9488
608
614
628
604
42
39
35
36
325
346
346
338
180
181
198
210
603
617
651
687
483
485
503
489
3239
3340
3620
3843
968
946
907
973
484
307
310
82
SUO
SVE
SVK
SVN
UKI
2007
2004
2005
2006
2007
2004
2005
2006
2007
2004
2005
2006
2007
2004
2005
2006
2007
2004
2005
2006
2007
412
301
220
412
339
94
92
138
199
51
59
68
80
114
104
115
114
277
248
266
269
3045
36556
3039
76414
2114
49418
3045
36556
2276
50704
533
12500
544
16820
694
11899
1149
19099
54
429
83
669
71
530
75
584
178
1442
116
895
134
1138
146
1642
1022
18663
940
24619
926
14377
959
15394
320
307
310
320
326
252
258
226
240
244
255
295
238
77
111
123
142
810
815
757
758
ORGANIC
BEL
BGR
CYP
CZE
DAN
DEU
ELL
2004
2005
2006
2007
2007
2004
2005
2006
2007
2004
2005
2006
a
a
a
a
a
a
a
a
a
a
a
a
a
a
11
7
7
3
4
2
1
2
7
6
6
3
a
a
a
a
a
a
a
a
a
a
a
a
a
a
a
a
a
a
a
a
a
a
2007 a
2004
2005
2006
a
a
4
4
11
139
4517
97
2217
382
13780
2007
2004
2005
2006
16
27
25
40
279
4834
74
399
76
490
96
656
2007
2004
74
229
182
1498
227
985
3
131
45
129
36
82
89
97
99
16
83
ESP
EST
FRA
HUN
IRE
ITA
LTU
LUX
LVA
MLT
NED
2005
2006
138
109
177
788
200
788
2007
2004
2005
2006
123
340
188
141
193
847
342
1997
279
2222
363
3038
2007
2004 a
2005 a
2006 a
171
324
3134
2007 a
2004
2005
2006
a
a
a
a
a
a
a
a
115
145
228
184
1184
206
1132
612
8132
2007
2004 a
2005 a
2006
201
281
1577
75
178
725
2007
2005 a
2006 a
2007 a
2004
2005
2006
52
59
139
80
68
61
157
3105
125
933
122
1042
2007
2004 a
2005
2006
84
173
1610
0
0
0
4
1
4
2007
2004 a
2004 a
2005 a
2006
0
1
9
1
1
5
2007
2005 a
2006 a
2007 a
2004
2005
2006
4
17
136
a
a
a
a
a
a
a
a
a
a
a
a
a
a
a
a
a
83
53
275
a
a
a
a
a
a
a
476
4133
503
5667
1342
10538
24
53
75
53
75
97
101
2
5
9
10
37
52
56
69
8
8
15
15
1
2
1
323
356
442
451
8
17
38
43
1
12
13
19
26
1
1
1
18
18
19
84
OST
POL
POR
ROU
SUO
SVE
SVK
SVN
UKI
2007
2004
2005
2006
240
28
21
30
1555
14388
48
199
43
182
51
208
2007
2004
2005
2006
15
35
12
8
22
131
248
3335
47
432
23
161
2007
2004
2005
2006
12
38
90
137
25
120
2007
2007 a
2004
2005
2006
119
80
484
178
1192
181
1056
192
1050
a
a
3
2
2
9
35
7
25
4
14
2007
2004
2005
2006
2
18
23
28
4
13
28
127
44
314
33
143
2007
2004 a
2005 a
2006 a
32
33
145
a
a
a
a
a
a
2007
2004
2005
2006
a
a
a
a
a
a
a
a
a
a
a
a
2007
2004
2005
2006
a
a
a
a
a
a
a
a
a
a
a
a
2007
2
4
19
42
56
62
62
48
47
52
60
34
25
23
28
3
19
18
18
18
32
39
32
31
2
4
4
7
5
13
10
11
5
5
11
17
15
a. Data not shown as sample <15
85