An evaluation of plant drought stress parameters in spring wheat
by Katim Seringe Touray
A thesis submitted in partial fulfillment of the requirements for the degree of Master of Science in Soils
Montana State University
© Copyright by Katim Seringe Touray (1987)
Abstract:
Five spring wheat (Triticum aestivum L.) accessions were planted in the Sumner of 1986 near
Manhattan, Montana, to assess the relations between various plant drought stress parameters using a
line-source sprinkler irrigation system (Hanks et. al., 1976).
Soil moisture content, and soil moisture depletion, were measured and, from these parameters and
precipitation measurements, evapotranspiration was computed. In addition, leaf water potential, leaf
relative water content, stomatal mass flow resistance, crop canopy temperature, and canopy-air
temperature difference were measured.
Results from the analyses of variance did not show significant accession differences in soil moisture
content or in their relative water content, canopy temperature, canopy-air temperature difference and
stomatal mass flow resistance. However, significant accession differences were found in soil moisture
depletion, evapotranspiration, and leaf water potential.
Regression analysis gave good correlations (R^2 = 0.99) between canopy-air temperature difference
and canopy temperature. Also, canopy temperature was found to be a linear function of stomatal mass
flow resistance.
The results obtained suggest that the use of canopy temperature and canopy-air temperature difference
as plant drought stress indicators is justifiable in some instances. However, there were indications that
caution is warranted in the use of these parameters, especially as a means of screening crops for
drought tolerance. AN EVALUAHCN CF FUSNT DROUGHT STRESS PARAMETERS
IN SPRING WHEAT
by
Katie Seringe Touray
A thesis submitted in partial fulfillment
of the requirements for the degree
of
Master of Science
in
Soils
MONTANA STATE HHVERSITY
Bozeman# Montana
August# 1987
main ub
^ms
APPRWAL
of a thesis submitted by
Katim Seringe Touray
This thesis has been read by each member of the thesis committee
and has been found to be satisfactory regarding contentf English usage,
format, citations, bibliographic style, and consistency, and is ready
for submission to the College of Graduate Studies.
Approved for the Major Department
V/2//27
Date
Head, Major Department
Approved for the College of Graduate Studies
^
Date
F
7
Graduate Dean
iii
STATEMENT CF PERMISSION TO USE
In
presenting
this
thesis
in
partial
fulfillment
of
the
requirements for a masters' degree at Montana State University^ I agree
that the Library shall make it available to borrowers under rules of
the Library. Brief quotations from this thesis are allowable without
special permission/ provided that accurate acknowledgment of source is
made.
Permission for extensive quotation from or reproduction of this
thesis may be granted by my major professor/ or in his absence/ by the
Director of Libraries when/ in the opinion of either/ the proposed use
of the material is for scholarly purposes. Any copying or use of the
material in this thesis for financial gain shall not be allowed without
my written permission.
S i g n a t u r e - ^ ______
Date
V
ACKNOWLEDGMENTS
My graduate program has been made possible by a Fellowship from
The African-American Institute, through the cooperation of. The Gambia
government,
and Montana State University.
I am most grateful to all
three bodies and all the people through whom they provided their
support. In particular, Anita Johnson, and Jackie Allen, both of the
African-American Institute, deserve a special mention.
I
am particularly indebted to my major professor. Dr.
A.
Hayden
Ferguson, for his understanding and guidance, but above all, his faith
in me. My Graduate Committee members, Drs. Ron Lockerman, Jarvis Brownf
and Joseph Caprio, also contributed in no small way to the realization
of my objectives in graduate school. Dr. Lockerman, together with his
graduate student, Mr. Jim Bunker, allowed my use of their experiment to
obtain data for the thesis.
I am grateful to Carol Bittinger, Statistics/Graphics Consultant,
Computing
Services,
frustrating
for being of
analysis
of my
invaluable help in the frequently
data.
Chris Julson helped
type the
manuscript, and for that, I express my sincere thanks.
In the tin® I have been in Bozeman, I have made a lot of friends,
mostly under circumstances totally unrelated to Soil science. Though
they are too numerous to list,
I thank all of them for being what
everybody wants: good friends.
Finally, Marie Chantale Damas has been a friend special enough to
warrant mentioning her by name. Thanks a lot.
vi
TABLE OF CONTENTS
Page
LIST OF TABLES
.................................................. viii
LIST OF F I G U R E S ............................... ................. x
LIST OF ABBREVIATIONS AND SYMBOLS........ .......................Xl
ABSTRACT ........................................................ xiv
INTRODUCTION
.................
I
LITERATURE R E V I E W ...........................................
MATERIALS AND METHODS
11
16
............................
Measurement of Soil Moisture Content and
Evapotranspiration.............................
Measurement of Plant Drought Stress
Parameters.................................
Leaf Water Potential ...................................
Leaf Relative Water Content ...........................
Stomatal Mass Flow Resistance ..........................
Canopy Temperature and CanopyAir Temperature Difference ..........................
RESULTS AND DISCUSSION
LD CO (Tl
Soil Water Content .......
Leaf Water Potential .....
Leaf Relative Water Content
Leaf Diffusive Resistance
. and Stomatal Mass Flow Resistance...... ...................
Canopy Temperature ..........................
Canopy-Air Temperature Difference..........................
3
........................................
2
24
24
24
25
27
Analysis of Variance Resu l t s ....................
Soil Moisture C o n t e n t ..................................
28
Soil Moisture Depletion.... ............................ 29
Evapotranspir a t i o n ........................ -........... 30
Seasonal Evapotranspiration ............................
31
Relative Water C o n t e n t .........................
Canopy Temperature and CanopyAir Temperature Difference ...........................
34
Stomatal Mass Flow Resistance.... ..................... 36
Leaf Water Potential......................
28
33
.
vii
TABLE OF CONTENTS - CONTINUED
Relationships Between Plant Drought Stress
Parameters.................................................
Stomatal Mass Flow Resistance and
Leaf Relative Water C o n t e n t ..... .....................
Canopy Temperature and Leaf
Relative Water C o n t e n t .........
Canopy Temperature and Stomatal
Mass Flow Resistance......................
Canopy-Air Teiperature Difference
and Canopy Temperature .......................
44
Fluctuations of the Drought Stress
Parameters.........................................
44
SUMMARY AND CONCLUSIONS
BIBLIOGRAPHY
APPENDICES
...........
...........
................. ...........................:.... .
39
39
41
41
55
58
65
Appendix I ........
68
Appendix 2 .......................
70
Appendix 3 ................................................
71
viii
LIST OF.TABLES
Table
Page
1. Soil Moisture Content measurement
and Irrigation E v e n t s ............................
2. Analysis of Variance for Soil
Moisture C o n t e n t .......... .................................
21
28
3. Analysis of Variance for Soil Moisture
Depletion between successive Soil Moisture
Content measurements .........................................
29
4. Tukeys1 HSD Test for cultivar differences
in mean soil moisture depletion ..............................
30
5. Analysis of Variance forEvapotranspiration .*.................
31
6. Tukeys1 HSD Test for cultivar differences
in mean Evapotranspiration..................
32
7. Analysis of Variance for Seasonal
Evapotranspiration ..........................................
32
8. Tukeys1 HSD Test for cultivar differences
in mean Seasonal Evapotranspiration......................
33
9. Analysis of Variance for Leaf
Relative Water C o n t e n t ......................................
33
10. Analysis of Variance for Canopy Tenperature .................
34
11. Analysis of Variance for Canopy-Air
Temperature Difference......................................
35
12. Analysis of Variance for Stomatal
Mass Flow Resistance........
37
13. Analysis of Variance for Leaf Water
Potential...........
38
14. Tukeys1 HSD Test for cultivar differences
in mean Leaf Water Potential..........
38
15. Precipitation recored on different days
after planting ................................
66
ix
. LIST OF TABLES (CONTINUED)
Table
16. Accession drought stress parameter means
for different irrigation treament levels .....................
17. Drought stress parameter means at
different days after planting ............................
Page
68
69
X
LIST OF FIGURES
Figure
Page
1. Experimental L a y o u t ......................................
20
2. Irrigation water applied (in mm) at
different days after planting......................
22
3. Plot of Stomatal Mass Flow Resistance versus
Leaf Relative Water C o n t e n t ..............................
40
4. Plot of Canopy Terrperature versus
Leaf Relative Water C o n t e n t ..........................
42
5. Plot of Canopy Tenperature versus
Stomatal Mass Flow Resistance......................
43
6. Cubic plot of Canopy-Air Tenperature Difference
versus Canopy Tenperature........................
7. Plot of Leaf Water Potential and Stomatal
Mass Flow Resistance at different days
after planting ...............................................
45
46
8. Canopy-Air Tenperature Difference and
Canopy Tenperature at different
days after planting................................
48
9. Leaf Relative Water Content and Leaf
Water Potential at different days
after planting ..............................................
50
10. Soil Moisture Content and Canopy
Tenperature at different days
after planting.........................................
51
11. Soil Moisture Content and Canopy-Air
Tenperature Difference at different
days after planting .........................................
53
12. Soil Moisture Content and
Stomatal Mass Flow Resistance at different
days after planting ............
54
xi
LIST OF ABBREVIATIONS AND SYMBOLS
Abbreviation or Symbol
B
cP
Meaning
A composite constant
Volumetric heat capacity, of air
cs
Stomatal conductance (cm/sec)
CWSI
Crop Water Stress Index (dimensionless)
D
Soil moisture depletion (cm)
E
Transpiratiai (mm)
Et
Evapotranspiration (mm)
f(u)
A function of wind speed, u
G
Soil heat flux (W m”^ sec-*)
I
Irrigation (imO
IR
Infrared
LAI
Leaf Area Index (dimensionless)
LWP
Leaf Water Potential (MPa)
P
Precipitation (irm)
Boundary layer resistance (sec/cm)
Leaf, cuticular
(sec/cm)
diffusive
resistance
r^
Leaf inter c e l l u l a r
resistance (sec/cm)
s p a c e dif f u s i v e
rL
Leaf internal diffusive resistance
(sec/cm)
r ITif (SM FR)
Stcanatal mass flow resistance (sec/cm)
rs
Stcanatal diffusive resistance (sec/cm)
xii
Abbreviation or Syntool
Meaning
r„
Cell, wall diffusive resistance in the
leaf (sec/cm)
R
Radiation
emitted
canopy (W m 2 sec-1)
from
the
crop
Rainfall (excluding run-off) (mm)
Bn
Net solar radiation (W m-2 sec-1)
rP
Resistance to water flow from the roots
to the evaporating surface in the leaves
rTS
Mean resistance to water flow within
the roots
RWC
Relative Water Content (%)
SDD
Stress Degree Day (0C)
SMC
Soil Moisture Content (cm)
SPD
Saturation Pressure Deficit (MPa)
Ta
Air temperature (0C)
Tc
Tc"Ta
U
wd
"
*L
Canopy temperature (0C)
Canopy-air temperature difference (0C)
Wind speed (m sec-1)
Drainage from the root zone (mm)
Mean leaf water potential (MPa)
Matrix potential (MPa)
%
V
Pressure potential (MPa)
*
Whole-plant water potential (MPa)
plant
Solute (osmotic) potential (MPa)
^soil
Mean Soil Water potential (MPa)
xiii
Abbreviation or Synfcol
Meaning
e
Eknissivity of crop canopy (dimensionless)
a
Stefan-Boltzmann constant (5.674 x
10-8 w m"2 K"4)
xiv
ABSTRACT
Five spring wheat (Triticum aestivum L.) accessions were planted
in the Sumner of 1986 near Manhattanr Montana/ to assess the. relations
between various plant drought stress parameters using a line-source
sprinkler irrigation system (Hanks et. al., 1976).
Soil moisture content/ and soil moisture depletion/ were measured
and/ f r o m t hese p a r a m e t e r s and p r e c i p i t a t i o n measurements/
evapotranspiration was computed. In addition/ leaf water potential/
leaf relative water content/ stomatal mass flow resistance/ crop canopy
temperature/ and canopy-air temperature difference were measured.
Results from the analyses of variance did not show significant
accession differences in soil moisture content or in their relative
water content/ canopy temperature/ canopy-air temperature difference
and stomatal mass flow resistance. However/, significant accession
differences were found in soil moisture depletion/ evapotranspiration/
and leaf water potential.
.
Regression analysis gave good correlations (Rr = 0.99) between
canopy-air temperature difference and canopy temperature. Also/ canopy
temperature was found to be a linear function of stomatal mass flow
resistance.
The results obtained suggest that the use of canopy temperature
and canopy-air temperature difference as plant drought stress
indicators is justifiable in some instances. However/ there were
indications that caution is warranted in the use of these parameters/
especially as a means of screening crops for drought tolerance.
I
INTRCDUCTION
Water is a major component of all plants and, is essential for the
production of crops. Unfortunately, the importance of water is seldom
matched by its availability for agriculture.
As a consequence, modern agriculture has come to rely significantly
on the judicious use of limited water resources.
In this connection,
the quest for efficient means of harnessing, conveying, and applying
irrigation water has received considerable time and effort in the last
few decades. In areas where irrigation is not common, the maximization
of the crop production from.available precipitation has been of
paramount importance.
Increased efficiency in water use for crop production is beneficial
in reducing the amounts of water that would otherwise have been wasted.
It is also beneficial in reducing the hazards to the environment posed
by the increased use of fertilizers under irrigated agriculture has
posed.
Contaminated
ground water,
increased
salinity,
and toxicity
levels in soils are all testimonies to the problems attendant to the
inefficient use of irrigation water.
For these reasons, various methods and techniques have been devised
to aid in the achievement of better irrigation management practices.
The various methods have aimed, with varying degrees of success and
acceptance, at finding convenient and economic means of detecting crop
water stress,
estimating crop water
efficient irrigation scheduling.
requirements,
and achieving
Most of the methods developed for
2
estimation
water
of
evapotranspiration,
and hence the prediction of crop
requirementsr are not very suitable for use by an individual
farmer.
This is because of the scale (in both time and space)
and
instrumentation factors entailed in the use of these techniques.
Therefore/^there has been an increased effort recently to develop
methods of crop water stress detection that are fast/ economical/ and
reliable enough to assure that crops would neither be unduly stressed
nor would irrigation water requirements be overestimated.
For these
reasons/ crop water parameters that are easily measurable and correlate
well
with more
difficult
to measure but
reliable water
stress
indicators/ have been used.
Two such parameters/ crop canopy temperature and its' difference
from
air
temperature
researchers.
have
received
enthusiastic
support
from sane
These parameters have been studied in conjunction with
other crop water stress parameters such as leaf water potential/ leaf
relative
water
content/
stomatatal
mass
flow
resistance/
and
soil
moisture depletion.
This study aimed to investigate the relation between these drought
parameters
in five varieties of spring wheat under
four levels of
irrigation. Also/ the study aimed to assess the efficacy of the use of
these parameters in the detection of crop water stress and/ explore the
potential use of these parameters for irrigation scheduling.
3
LITERATURE REVIEW
Moisture uptake and use by plants is determined by a wide variety
of factors. The factors governing evaporative flux from crops can be
grouped into three classes (Reggief 1971):
a) soil factors;
b) micrometeorological factors;
c) plant factors.
These
factors
consequently influence various aspects of soil water
management/ including irrigation scheduling.
Various methods for scheduling, irrigation have been proposed/ and
they can be grouped into three broad classes (Jackson/ 1982):
a) soil based;
b) meteorologically based;
c) plant based.
Quite
commonly/
combinations
of
the
three
are used for
irrigation
scheduling.
Soil
based
irrigation
scheduling
techniques
rely
on
the
measurement or monitoring of soil moisture content (Gear et al./ 1977).
The information thus obtained is used with a pre-defined refill point
(the point at which irrigation should occur)
and a full point to
schedule irrigations. The full point is defined as the total soil water
holding capacity of a specified depth expressed as depth of water per
unit depth of soil after
water.
initial drainage has removed some of the
'4Meteorological
nethods
of
irrigation
scheduling
(e.g.
pierce,
1960; Jensen and Haise, 1963) make use of meteorological factors such
as air temperature, net radiation, relative humidity and windspeed as
inputs in models used for the calculation of evapotranspiration in a
given time.
Plant-based
evaluation
methods
of
of plant drought
scheduling
irrigation
stress parameters,
rely
e.g.
on
the
leaf water
potential (Scholander et al., 1965), leaf or canopy temperatures (Stone
and Horton, 1974), or leaf diffusive resistance (Kanemasu and Tanner,
1969). These techniques are particularly attractive because they
provide a diagnostic tool for detecting impending or actual plant water
stress from the plant itself.
precise
information
distribution
and
on
This obviates the need for gathering
available
atmospheric
soil
evaporative
moisture
demand
content,
(Pinter,
root
Jr.,
and
Reginato, 1982). However, the problem encountered in using plant
parameters for scheduling irrigations is that it is a time-consuming
method,
requiring numerous measurements for the characterization of a
field (Jackson, 1982).
The foregoing discussion indicates the complex nature of the
interactions between the various factors involved in soil water
management
moisture
for
efficient plant production.
content,
evapotranspiration,
These factors viz:
and plant
drought
soil
stress
parameters have received the attention of researchers during the past
couple of decades.
5
Soil Water Content
Soil water has both direct and indirect influences on plant
growth. Soil water directly affects plant growth through its effect on
plant water status.
For exampler soil water potential influences leaf
water potential (Campbell and Campbell, 1982) in a manner given by the
relationship:
1^L
^soil
“ E ^ Rrs + Bp)
........ ..................
(I)
where:
=
^soil =
E
rTS
rP
mean leaf water potential;
mean soil water potential;
transpiration;
mean resistance to water flew in the roots;
resistance
to water
flow from the
.
roots to the
evaporation surface in the leaves.
Ehrler et al.
(1978)
have also found changes in
!(Jpjant
(potential
Treasured on the whole plant) to be determined by changes in volumetric
soil moisture content.
Indirectly^ soil water acts on other plant growth factors such as
soil
temperaturef
soil
aeration,
and
nutrient
availability.
Consequently, soil moisture conditions that lead to the minimization of
plant water stress may result in unfavorable soil temperature or
aeration, or may leach nutrients required for plant growth (Campbell,
and Canpbellr 1982).
Often, it is the rate of movement of water within the. soil, not
water content or potential, which determines the availability of water
6
for plant user and hencer the need for irrigation (Hillelr 1972). The
rate of movement of water within the soil-plant-atmosphere continum has
been explained with the aid of electrical resistance analogs
Cowanr
1965);
continum.
(e.g.
which assign resistances to various components of the
The
significance
of
eac h
of c o m p o n e n t
toward
the
determination of.the rate of water movement depends on its contribution
to the total resistance of the system.
Soil water content is a dynamic parameterr in that it is not
constant.
One of the factors contributing to changes in soil water
content is soil water depletionr which in turn is dependent on a
variety of soilr environmental and management factors.
For exampler
Jensen et al. (1971) have expressed soil moisture depletion (D) as:
n
D = .^1 (Et - Be - I + Wd) ..... ...........
(2)
where:
Et = evapotranspiration;
Ee = rainfall (excluding run-off);
I
= irrigation water applied;
= drainage from the root zone.
In the above relation/ D=O/ and i=l
after a thorough irrigation/ and
the terms on the right are daily totals.
Equations
(I)
evapotranspiration
in
and
(2)
both
indicate
soil-plant-atmosphere
related to its water economy.
the
continum/
impo r t a n c e
of
especially
as
Evapotranspiration has very intimate/
complex and frequently recursive relationships with other plant water
7
stress parameters.
For example, Millar et al.
(1970)
found that
transpiration rates of barley decreased with decreasing leaf relative
water content ( K C ) . When EWC reached about 85%, there was a reduction
of approximately 50% in actual transpiration recorded.
Yang and de
Jong (1972) found a similar pattern in the relationship between the two
parameters.
Thus, transpiration rate dropped rapidly as FWC decreased
from 98 to 90%.
The decline of transpiration rate became more gradual
after EWC reached 90% until a constant transpiration rate of 0.05 g cm”
^ day ”1 was reached at about 50%
Etc.
Leaf water potential (IWP) has also been found by Yang and de Jong
(1972), to decrease with increased evaporative demand (which determines
the potential
water
evapotranspiration
deficits,
which
rate).
determines
This is only because leaf
L W P , are
caused
by
temporary
imbalances in the rates of transpiration and water absorption.
These
imbalances can be caused by either a sudden increase in evaporative
demand or by a lowering of water absorption (Ehrler et al., 1966).
Furthermore,
temperature,
reduced evapotranspiration rate, by increasing leaf
leads to increased leaf resistance to evaporation
(van
Bavel et al., 1965).
The transpiration of water from plant leaves leads to a lowering
of leaf temperatures by virtue of the latent heat of vaporization of
water relative to the heat capacity of plant tissue (Brown and Escombe,
1905).
For given conditions, this depression of temperature should be
proportional to the transpiration rate (Martin, 1943).
(1964a)
found
that
for bur
oak,
Thus, Gates
Quercus macrocorpa, the effective
radiation load on the leaf decreased by 0.10 cal cm”2 min”1 for each
8
1.7 x IO"4 g CirT^ min"-*- increase in transpiration rate.
This increase
in transpiration rate was calculated to drop leaf temperature below
that which would occur in the absence of transpiration.
Leaf Water Potential
Leaf water potential (IWP) has come to be a standard parameter for
quantifying plant water stress.
LWP
is the chemical potential
of
waterf defined as the algebraic sum of the potential components due to
the pressure
r solutes
(
(Hsiao, 1973).
(ijjg) and matrix
(^m ) of the plant leaf
The importance of these components in determining LWP
depends on the leaf water status.
For example, in fully turgid tissue
■
(Hsiao, 1973), large decreases in IWP are due mainly to changes imjj p.
Furthermore,
leaf age also has a significant influence on
LWP
irrespective of the plant water status (Rippling, 1967).
Given the complex nature of the interactions within a plant, LWP
also influences other plant water stress parameters.
Thus,
the
stomatal resistance of soy beans (Glycine max ) has been reported by
Kanemasu and Tanner (1969) to increase rapidly as LWP drops below -1.11
MPa.
Duniway
(1971)
and Jordan and Ritchie (1971)
found that leaf
resistance increased sharply, beyond the threshold LWP for stomatal
closure; increasing 20- to 30-fold for a drop in LWP of less than 0.5
MPa.
LWP has a significant bearing on evapotranspiration by its' direct
influence on the moisture concentration gradient between the leaf and
the ambient air.
(1985),
This is illustrated by the findings of Kirkham et al.
which show that
potentials.
Sunflower
had
a high ET at high water
9
Ehrlerf et al.f
(1978) have reported ^plant to influence the
difference between canopy temperature and air temperature (Tc-Ta). Thus
when 1Ijplant decreased to -1.9 MPa/ (Tc-Ta) was zero and when ^piant was
-4.8 MPaf
(Tc-Ta) rose to 4.8°C. Data from Kirkham et al. (1985) also
indicate there is a tendency for crops with high potentials to have low
(Tc-Ta) values and vice versa.
Leaf Relative Water Contait
Leaf relative water content (ESflC) is another commonly used index
of plant water
stress.
Sometimes
called water saturation deficit
(WSD) f ESflC is used as an indicator of the state of water balance of a
plant because it expresses the amount of water which the plant leaf
requires to reach full saturation (Catskyf 1974).
For this reasonf ESflC
has some bearingf direct or indirectlyf on other plant water stress
indices.
•
ThuSf Wiegland and Namken (1966.) found that a decrease in ESflC from
83% to 59% resulted in a 3.6°C increase in leaf temperature.
leaf reflectance in the 1.45 and 1.93y
AlsOf
water absorption bands have
been found to be significantly (p = 0.01) related to the relative water
content
in an inverse manner
(Thomas et al. 1971).
For cotton
(Gossvpium hiisutum L .)t the changes in reflectance were found to occur
when EWC fell below 70%.
Carlson et al. (1971) also found significant
relationships between ESflC and the spectral properties of leaves of c o m
(Zea mays) t soybean (Glycine max) t and sorghum (Sorghum biocolor) t over
the wavelength region 800-2600 ny . For examplef for sorghum leavesf
reflectivity decreased with increasing ESflC at both 2200 ny and 1950 my
wavelengths. In addition at a given ESflCf reflectivity at 2200 m y was
10
higher than at 1950
.
' EWC has also been found to influence IMP.
de Jong
(1972)
For example, Yang and
found that as. the EMC dropped in wheat plants,
LWP
dropped also, with a drastic change in the slope of the curve when EMC
was between 93 and 97%.
Millar et al. (1970) found a similar change in
the slope of the curve for barley and observed that the change
coincided with a change in the elasticity of the leaves.
However,
because variations in the environment can cause changes in EMC, the
usefulness of EMC as on index of LWP is significantly reduced (Yang and
de Jong, 1972).
Also,
a change of a few MPa of LWP in nearly saturated tissue
corresponds to a change of several percentage points in EMC (Hsiao,
1973).
This is about the size of the random measurement error for EMC
in many studies (Barrs, 1968).
It is perhaps for this reason that EMC
did not show significant changes in some studies even when other
physiological processes were affected by mild stress (Hsiao, 1970, and
Huffaker et al., 1970).
In studies where FMC was used as an index of leaf water status,
the
threshold
value
above
which
leaf diffusive
resistance
remains
constant (i.e. open stomata) was found to be about 80 to 85% EMC
cotton
(Troughton, 1969)
suggesting that
and
beans
(Duniway and Durbin,
for
1971);
EMC is a poor indicator of mild stress. However, this
conclusion probably cannot be generalized
since there are some
indications to the sensitivity of stomata of other species to mild
stress (Boyer, 1970; El-Sharkany and Heskelt, 1964).
11
Leaf Diffusive Resistance and Stomata! Mass Flow Resistance
Leaf diffusive resistance is a measure of the resistance to the
movement of water from the inside of the leaf to the ambient air.
It
is a single but important component in the network of resistances along
the path of water in the soil-plant atmosphere continum.
The total internal leaf resistance rL is given (Milthorpef 1961)
by:
1
=
rL
1 +
I
rc
................. .
(3)
rs + ri + rw
where:
rc f rg f r^f and rw are the resistances to diffusion of water
vapor through the cuticle, stomata,
intercellular spaces in the
leaf, and the cell walls of the leaf, respectively.
Different components of rL have varying significances, depending on a
host of leaf and environmental conditions
(Slatyer, 1967).
In most
cases, rc far exceeds rg when the stomata is open.
Since stomata control only one part of the total resistance, the
magnitude of the effect of this change will depend on the importance of
rs
relative to that of the boundary layer resistance
(Hsiao, 1970).
(ra), and rc
Stomatal aperture in plant leaves is dependent to a
large extent on the water
(Slatyer, 1967).
status of and light intensity on plants
In well watered plants,
stomatal
aperture is
determined by the illumination (Ehrler and van Bavel, 1967).
Various theories have been advanced to give the sequence of events
leading to the closing of stomata in the event of water stress.
presumed
sequence
of
events
begins
with
the
Cne
disparity between
12
transpiration and absorption of water, which causes the development of
a leaf water deficit and, subsequently, stomatal closure (van Bavel,
1965).
The effect of water stress on stomatal closure is probably similar
to that of most other inhibitors; acting partly by causing changes in
internal
COg
co n c e n t r a t i o n ,
thus
mediating
respir a t i o n
and
photosynthetic processes, and partly by influencing processes concerned
with energy flow and guard cell turgor (Slatyer, 1967).
Of
all
the
fact o r s
involved
in
plant
water
dynamics,
evapotranspiration is perhaps the factor which is most influenced by
stomatal closure.
Thus, Holmgren et al., (1965); and Rijtema,
(1965)
found that transpiration rate is increased by increased evaporative
demand (which determines transpiration)
irrespective of LWP, probably
due to stomatal and cuticular resistance to water movement.
However,
the
inf l u e n c e
of
rs on
transpiration
significantly tempered by environmental factors.
air with the stomata open, (i.e. rc (or rs) «
is often
For example, in still
ra }, Bange (1953) found
little stomatal control of transpiration until stomatal aperture was
significantly
reduced.
Under moving
air conditions
though,
ra
is
substantially reduced and, hence, stomatal control of transpiration is
effective throughout the entire range of apertures.
One other drawback of using rg as an index of plant water stress
lies in the lack of
leaves
and
those
for
correlation between values obtained on single
crop
canopies, . since
there
is
no
simple
relationship between crop and single leaf values of rL (Slatyer, 1967).
Further, given that leaf area index (LM)
for a good canopy normally
13
exceeds If effective rL values for crop canopies can be expected to be
less than for a single leaf;
declining as L M
decreases.
This is
because the resistances due to the individual leaves are connected in
parallel.
The
relationship between
stomatal mass flow
(Shimshif
porometers
(or viscous)
1977; Waggonerf
amphistomatous
stomatal
resistance
1965).
leavesf the
diffusive
resistance
rs and
is somewhat complicated
One reason for this is that in
resistance measured by viscous
flow
is the sum of the resistances of both epidermises with
stomata and that of the intercellular system of the mesophyll (Slavik r
1974).
'
Howeverf various power functions have been proposed to describe
the relationship. For examplef Darwin (1916)r has related r ^ to rs by:
4t
where y = 0.50.
A similar relationship was obtained empirically by Milthorpe and Penman
(1965; cited in Waggonerf 1965)r with y having a value of 0.44.
Canopy Temperature
Surface temperature data have been used in the study of many and
varied natural processes.
For example surface temperatures have been
used as a means of estimating evaporative losses from large bodies of
water (Richards and Irbef 1969; Webbf 1970)f bare soil (Conway and van
Bavelf 1966f 1967)r as well as vegetation (Blad and Rosenbergf 1975;
Stone and Hortonf
1974).
photographyf surface
variations
in
Furthermore through the use. of
infrared
temperatures have been used to detect genetic
sorghum drought
avoidance
(Blum et al. t 1978;
Blumf
14
1975).
Canopy temperatures,
in particular, have been found to be useful
indicators of both matric and osmotic stress in cotton plants (Howell
et al., 1984).
Both contact and non-contact methods of measuring plant
temperatures are in use.
infrared thermometry)
thermocouples)
For large areas, non-contact methods (e.g.
are more convenient than contact methods (e.g.
since thermocouples are limited to ground use and
individual leaves
(Ehrler et al., 1978).
Also, since thermocouples
must be attached to or inserted in the plant (generally the leaf), they
can cause changes in the condition of the plant part whose temperatures
are to be measured (Blad and Rosenberg, 1976).
Monteith and Szeicz (1962) and Tanner (1963) were among the first
researchers to use infrared
plant, temperatures.
Tanner
(IR)
radiometers for the measurement of
(1963)
used
IR thermometers to detect
moisture stress, in plants under different water regimes. He pointed out
that
Even though the temperature measurements so obtained are weighted
toward the upper part of the plant, it is these portions of the plant
canopy which participate most actively in transpiration, heat exchange
and assimilation.
The principle behind the IR measurement of canopy temperature is
the well-known Stephan-Boltzinan law:
R =
CGT^;
.......................
where:
R = the radiation emitted from the canopy (
e = the emissivity of the canopy
o = Stefan-Boltzman constant (5.674 x IO""** WnT^ K-^).
Tc = Canopy temperature (K)
(5)
15
IR thermometers measure the factor R in the Equation (4) above and
relate this to Tc .
In the 8-14 y m band (where most hand-held IR thermometers operate)
water vapor can have a significant influence on canopy temperature
measurementSf especially when distances between the target and sensor
are great.
However/ Lorenz (1968) found that this effect is negligible
when the distance to the target is less than 154m.
Emissivities of most plant surfaces have been reported (Jackson/
1982) to be in the range 0.95 to 1.00. Gates (1964b) found most plant
leaves to have a long-wave emittance of 0.97 to 0.98.
Canopy temperatures have been found to vary both between and
within plant species.
For example/ c o m was found
during one growing
season to have a consistently warmer canopy than alfalfa
Rosenberg/
1976).
Ehrler
(1973)
found
significant
(Blad and
and consistent
differences in leaf temperatures of different cotton varieties.
particular/
the differences observed were more pronounced in stands
growing
in dry soil/
warmer
varieties were
and explained by the fact that the leaves of
positioned nearly normal
to sunlight.
contrasted with the drooping leaves of the cooler variety;
position
In
that
leads
to
absorption
of
comparatively less
This
a leaf
shortwave
energy.
In contrast to the findings of Ehrler (1973) / Singh and Kanemasu
(1983)/ working with pearl millet found greater differences in leaf
temperatures of different genotypes when they were growing under
irrigated conditions than under non-irrigated conditions; a difference
attributed to differences in genetic make-up with a bearing on the
16
energy transfer characteristics of the plants.
Howeverf Idso et al. t
(1984) found no significant differences among the canopy temperatures
of six wheat (Triticum aestivum L.) cultures.
The differences in the results obtained in the above-mentioned
experiments
demonstrate
the complexity
of
the
relationship between
various factors affecting leaf and canopy temperatures.
Among these
factors are the sensible heat exchange as dictated by the wind and crop
geometryf
net
radiant energy absorbed/
and the evaporative cooling
which is dependent on wind and vapor pressure gradient (Ehrler and van
Bavelf 1967).
Leaf temperature is determined by changes in any or all of these
factors/ as
leaves.
Raschke
(1962)/ has shown quantitatively for single
These factors influence canopy temperatures by virtue of their
influence on the balance of sensitive and latent heat exchanges between
the crop canopy and the atmosphere (Hatfield et al./ 1985).
Canopy-Air Temperature Difference
Closely related to crop canopy temperature (Tc) is its difference
from air temperature (Ta) / i.e. the quantity (Tc-Ta).
This parameter
has been found to be a promising technique for monitoring plant water
stress
in wheat/ given its significant response to changes in plant
water potential occasioned by changes in soil moisture content (Ehrler
et al./ 1978).
Also/ Ehrler (1973) has found (Tlj-Ta) (the difference between leaf
and air temperatures)
Furthermore/
even
to be a sensitive indicator of changes in rg .
under
conditions
of
severe
drought/
(T^-Ta)
correlated well with leaf diffusive resistance despite changes in the
17
saturation deficit of the air.
The ability of (Tc-Ta) to indicate plant water stress has led to
the development of models relating it to evapotranspiration.
One such
model (Brown and Rosenberg/ 1973) is:
Et = Rn - G - f(u) Cp (Tc-Ta)
.............
(6)
where:
Et = evapotranspiration
Rn = net solar radiation
G = soil heat flux
f(u) = a function of wind speed
Cp = volumetric heat capacity of air.
Subsequent publications have discussed equation (6) in detail and have
found it to be a reliable predictor of Et (Stone and Horton/ 1974; Blad
and Rosenberg/ 1976).However/ for practical situations/ equation (6) is not easy to use
since f(u) is rather tedious to determine and dependent upon crop type
and
location.
Consequently/
Jackson
et
al.
(1977)
made
some
simplifying assumptions:
a)
for 24-hour periods/ G is negligible
b)
f(u) = I/ under still air conditions
Thus/ equation (6) becomes reduced to:
Et = Rn - B (Tc-Ta)
.......................
(7)
where:
B
experimentally.
is a composite constant
that can be determined
18
Ehrler et.al./
(1978)
found an inverse relationship between the
stress degree day parameter (Tc-Ta) and xylem water potential of wheat.
Later (1981 a) t the stress degree day parameter (£DD) was refined by
Idso et al., by taking the evaporative demand of the atmosphere into
account.
The transformed parameter was termed the crop water stress
index (OfSI) and was found to correlate well with the xylem pressure
potential of alfalfa plants subject to varying degrees of water stress
(Idso et al., 1981 b).
Pinter and Reginato (1982), Hatfield (1982) and
Reginato (1983) have all proposed the use of the CWSI as a tool for
irrigation scheduling.
19
MATERIALS AND METHODS
The
experiment was carried out in the summer of 19.86 on a
Manhattan sandy loam (coarse-loamy, mixed, Typic calciborolls) located
in the Gallatin Valley about 32 Km west of Bozeman, Montana.
The
experiment used
a line source sprinkler
irrigation system
along the lines of those proposed by Hanks et al., (1976); with the
sprinkler line running down the middle of the experiment (Fig. I). This
way,
a continuous gradient of soil water content is achieved in a
direction perpendicular to the direction of the sprinkler line.
Five accessions {Nfewana, Fortune, MT 7819 (Glenmann), MT 7836, and
MT 8182)} of spring wheat (Triticum aestivum L.) were planted on May
15, 1986 in plots of 3.66 x 3.66m with a 30cm spacing between the rows.
The accessions were randomized within four replications with rows
running perpendicular to the sprinkler line.
Thus, each replication
was split into two equal halves by the sprinkler line with irrigation
treatments being high, medium, low and "dry", progressing away from the
sprinkler line.
At the emergence stage of the plants, polyvinyl chloride (FVC)
pipes were installed to a depth of about 2m for use as access tubes for
neutron probe measurements of soil moisture.
Also,
a catch cup was
installed in the center of each plot about 60cm above the ground on a
wire frame to provide a means of measuring the amount of irrigation
water applied on each plot.
7320m
3.66 m
>
Replications
Half = 2
3«66 m
29.28m
Half = I
M
O
Accessions
Irrigation Treatment Levels:
3 High
2 Medium
I Low
0 Dry-
Sprinkler Heads:
Figure I
Experimental Layout
21
The plots were irrigated on the 28th, 42nd and 82nd days after
planting. The amounts of irrigation water applied on the different days
and on each of the irrigation treatment levels is as shown in Figure 2.
The plots were harvested at different dates, depending on how early the
crop matured, beginning H O days and ending 132 days after planting.
Measurement of Soil Moisture Content and Evapotransoiration
Soil moisture content determinations were made
at 20cm intervals
from a depth of 20cm to 140cm using a Campbell neutron probe. Days of
moisture content measurements and irrigation events are as Shown in
Table I.
Using a previously constructed calibration curve, the neutron
probe readings were converted to cm of water per cm of soil depth.
The
profile soil moisture content was obtained by summing the soil moisture
content for each depth.
Table I:
Days After
Planting
18
26
28
29
40
42
44
58
74
79
82
83
88 .
102
Y = Yes
N = NO
Soil Moisture Content Measurements and Irrigation Events.
Soil Moisture Content
Measurement
Y
Y
N
Y
Y
N
.Y
Y
Y
Y
N
Y
Y
Y
Irrigation
Event
N
N
Y
N
N
Y
N
N
N
N
Y
N
N
N
DAYS - 42
DAYS - 28
DAYS - 82
I----- Low
54
2 3 . 38%
M o d i urn
73
3 4 . 76%
K>
N>
I-- High
90
4 2 . 86%
Figure 2.
Irrigation water applied
(in mm)
at different days after planting
23
Meteorological
parameters
used
were
precipitation
and pan
evaporationf both of which were recorded o n .a daily basis.
For pan
evaporation measurementsf data obtained from two pans placed within the
experiment were averaged to obtain a daily value.
The
evapotranspiration
from each plot between
successive
soil
moisture content measurements was calculated using the following water
balance formula:
Et = I + P - D
............. .
(8)
where:
Et = evapotranspiration (mm)
I = amount of irrigation water applied (mm)
P = amount of precipitation (mm)
D = change in soil moisture between successive neutron
probe measurements (mm).
measurement of Plant Drought Stress Parameters
The plant drought stress parameters were measured from the 54th to
the 93rd day after planting; after the attainment of practically full
canopy. All parameter measurements on the plants were done between 1200
and
1600
hours
(Mountain Daylight Time)
to ensure maximum drought
stress on the plants.
Irrigation applications were made on the 42nd and 82nd day after
planting/
allowing
the monitoring
drying and wetting cycle.
were:
of
the parameters within both a
The plant drought stress parameters measured
leaf water potential/ canopy temperature/ canopy-air temperature
difference/
content.
stomatal mass
flow resistance/
and leaf
relative water
24
T.eaf Water Potential
.
Plant leaf water potentials (IMP) were measured using the pressure
chamber method
(Scholander et al., 1965)
using the flag leaf of the
plant to avoid the disruptive effect of leaf aging on EWP (Millar et
al., 1970).
Leaf Relative Water Content
Leaf relative water content (RWC) was determined on the flag leafobtained for the LWP measurement. The method used for the determination
of RWC was
a modified version of that proposed by Stocker
(1928).
After determining LWP, the flag leaf was weighed and then placed in a
test tube three quarters filled with distilled water.
The test tube
rack was then covered with a plastic sheet to prevent the drying of the
exposed parts of the leaves.
The leaves were left in the water to
saturate overnight and then saturated weights measured.
The leaves were then oven-dried to a constant weight and FWC was
then calculated according to the formula (Catsky, 1974):
. RWC(%) = Field Weight - Dry Weight - x
Saturated Weight - Dry Weight
100 .........
(9)
Stomatal Mass Flow Resistance
The stomatal mass flow resistances
(SMFR) were measured (again,
using flag leaves) using a porometer designed by Shimshi (1977).
The
porpmeter is essentially a portable version of that developed by
Gregory and Pierce (1934).
Porometer readings which were in ran Hg were converted to stomatal
conductances by using the calibration equations (Brown, 1987):
25
Cs = 117.7 - 0.8672*^ + 0 . 0 0 1 3 9 4 * ^ ........
(10)
when
102 < Mm I 200; and:
Cs = 295.5 - 4.936*Mm + 0.02419*Mm2
......... (11)
when
Mm <102;
where:
Cs = stomatal conductance (cm sec-*)
Mm = porometer reading (mm Hg)
Frcm the Cs values obtained/ the EMFR (r^)
were computed using t h e .
inverse relationship:
Given the complications in relating r ^ to rg pointed out earlier, the
tjpf values obtained were not converted to rg values. In addition, since
the objective of the "experiment was more toward using r ^ as an index
of drought stress than measuring transpirational activity, the values
obtained were used for the statistical analyses carried out.
Canopy Temperature and Canony^Air Tenperature Difference
Crop
canopy
differences
temperatures
(Tc- T a) were
(Tc )
measured
and
using
canopy-air
temperature
a hand-held
infra-red
thermometer with a 3° field of view and an 8-14 y m spectral band-pass
filter.
For the measurement of Tc , the thermometer was pointed
obliquely to the crop canopy to avoid interference by exposed ground
surface,
and direct
solar
Chandhuri et al., 1986) .
radiation
(Singh and Kanemasu, 1983;
The emmisivity setting used for all canopy
26
temperature measurements was 0.98 (Gates? 1964b).
made
No corrections were
for humidity effects due to the short sensor-target distances
involved
(Lorenz? 1968)
or for the sky radiant emittance since the
thermometer was operating in the 8-14 urn bandwidth (Jackson? 1982).
27
RESULTS AND DISCUSSION
The data obtained were analyzed using the SAS Software package (SAS
Institute Inc., 1982). Analysis of variance was done for soil moisture
content/
soil
moisture
depletion/
evapotranspirationz and
seasonal
evapotranspiration. Data on plant water stress parameters were also
analyzed using the analysis of variance procedure.
Hanks et al.
statistical
(1980) have discussed the principles behind the
analysis of data obtained from a line source sprinkler
experimental design.
randomized/
effect.
Because the
irrigation treatments were not
there is no valid estimate of error for the irrigation
However/
the analysis of variance does provide valid error
terms for testing the effects of other randomized variables as well as
the effects of their interactions with irrigation treatment.
Varieties
replication
(factor C) were considered the main plots within each
(R)
and since the irrigation levels increase as the
sprinkler line is approached from either side/ the two halves of the
experiment are mirror images of each other and as such are considered
sub-plots (HA). Within these sub-plots/ the irrigation treatment levels
(T)/ were considered the sub-subplots.
Since measurements were done
over time/ the weeks after an irrigation (WEEK) or days after planting
(DAYS) were introduced as other factors in the analysis.
Regression, analyses were also done to find the relationships
between the plant water stress parameters and soil moisture content/
evapotranspiratibn
(both.seasonal
and periodic) / and
soil moisture
28
depletion.
Relationships between
the plant water
stress parameters
themselves were also investigated using regression techniques.
Analysis of Variance Results
Soil Moisture Content
Results obtained from the analysis of variance of data on soil
moisture content are shown in Table 2.
Table 2: Analysis of variance for soil moisture content (cm).
SOURCE
D.F.
SUM OF SQUARES
R
3
4
C
12
Error (C)
I
HA
C*HA
4
Error (HA) 15
T
3 .
'12
C*T
T*HA
3
12
C*T*HA
90
Error (T)
10
DAYS
40
C*DAYS
10
HA*DAYS
30
T*DAYS
C*T*HA*DAYS 310
Error (DAYS) 1200
670.514
. 256.817
371.224
8.828
22.705
176.199
8197.627
152.124
71.895
62.958
1254.533
53266.672
82.986
52.626
2433.335
297.427
1149.199
F-VALUE
SIGNIFICANCE*
7.22
2.08
NS
0.75
0.48
NV
NS
196.03
0.91
1.72
0.38
NV
NS
NV
NS
5562.14
2.17
5.50
84.70
1.00
* *
* *
* *
* *
NS
Note:
* *
*
implies significance at the 1% level of significance;
implies significance at the 5% level of significance;
NS
denotes
non-significance;
NV
signifies the non-validity of an F-test.
29
Cultivar (C) differences are not significant nor are the cultivar
by irrigation treatment (C*T), and the (C*T*HA) interactions. Only days
after planting (DAYS) and its interactions are significant.
Soil Moisture Depletion
Table 3 shows the analysis of variance results obtained for the
depletion of soil moisture between successive neutron probe reading
dates.
Table 3: Analysis of variance for soil moisture depletion (cm) between
successive soil moisture content measurements.
SOURCE
D.F.
R
3
4
C
Error (c)
12
HA
I
C*HA
4
Error (HA) 15
T
3
C*T
12
T*HA
3
C*T*HA
12
Error (T)
90
DAYS
9
36
C*DAYS
HAfDAYS
9
27
T*DAYS
C*T*HA*DAYS 279
Error (DAYS) 1080
SUM
OF SQUARES
0.844
2.889
2.303
0.646
0.813
4.969
36.550
2.318
5.278
3.834
19.465
10440.933
58.904
110.599
2234.686
301.116
1457.488
F-VALUE
SIGNIFICANCE
1.46
3.76
*
1.95
0.61
NV
NS
56.33
0.89
8.14
1.48
NV
NS
NV
NS
859.64
1.24
9.11
61.33
0.80
* *
NS
* *
* *
NS
The cultivar factor is significant at the 5 % level and all interaction
terms are non-significant except for the T*DAYS, and HAfDAYS terms.
Table 4 shows the results of the Tukeys1 highest significant
difference
depletion.
(HSD)
test for cultivar differences in soil moisture
30
Table 4: Tukeys1 HSD Test for cultivar differences in soil moisture
depletion between successive soil moisture content measurements.
CULTIVAR
MEAN
DEPLETION (cm)
1.22
1.18
1.17
1.11
1.10
MT 8182
NEWANA
FORTUNA
MT 7836
MT 7819 (Glenmann)
GRtXJPING
A*
A B
. A B
A B
B
* Cultivars followed by the same letter are not significantly different.
Note:
probability (alpha)
degrees of freedom (d.f)
minimum significant difference (msd)
mean square error (mse)
= 0.05
=12
= 0.11
= 0.19
As can be seen from Table 4, MT 8182 had a mean soil moisture
depletion significantly higher than that of MT 7819
(Glenmann). The
fact that there are significant cultivar differences in soil moisture
depletionf even though there are no significant cultivar differences in
soil
moisture
content
is
very
interesting f primarily because
soil
moisture depletion is a function of soil moisture content.
Evapotranspiration
Table 5 shows the analysis of variance for the periodic
between
successive
evapotranspiration.
soil
moisture
content
(i.e.
-measurements)
31
Table 5: Analysis of variance for evapotranspiration (mm)
SOURCE
D.F.
R
3
4
C
Error (c)
12
I
HA
C*HA
4
Error (ha) 15
T
3
C*T
12
T*HA
3
C*T*HA
12
Error (t)
90
10
DAYS
40
C fcDAYS
10
HA*DAYS
30
T fcDAYS
C*T*HA*DAYS .310
Error (D) 1200
SUM
CF SQUARES
48.011
356.713
117.619
10214.545
9v608
940.801
58919.193
249.233
4064.523
492.210
2065.295
3122363.628
-3961.525
140188.067
112481.194
49731.176
92320.772
P-VALUE
SIGNIFICANCE
1.63
9.10
* *
162.86
0.04
NV
NS
855.64
0.90
59.03
1.79
NV
NS
NV
NS
4058.50
1.29
182.22
48.73
2.09
* *
NS
* *
* *
* *
Cultivar differences in evapotranspiration are highly significant.
Also highly significant are the interaction terms HA*DAYSr T*DAYSr and
C*T*HA*DA3fS. Table 6 shows the results of the Tuk eys'
cultivar differences in evapotranspiration.
HSD test for
The cultivars Newana and
MT 8182 have higher evapotranspiration than MT 7836 and MT 783.9
(Glenmann).
Seasonal Evapotranspiration
The analysis of variance for the seasonal evapotranspiration data
is shown in Table 7.
32
Table 6: Tukeys1 HSD Test for cultivar differences in evapotranspiration
CULTIVAR
MEAN
EVAPOTRANSPIRAHON (mm)
NEWANA
MT 8182
FORTUNA
MT 7836
MT 7819 (Glenmann)
37.96
37.91
37.45
36.97
36.89
GROUPING
A
A
A
B
B
B
Note:
alpha = 0.05
d.f
= 12
msd
= 0.75
mse
= 9.80
Table It Analysis of variance for seasonal evapotranspiration.
SOURCE
D.F.
R
C
Error (C)
HA
C*HA
Error (HA)
T
C*T
T*HA
C*T*HA
Error (T)
3
4
12
I
4
15
3
12
3
12
90
Cultivar
significant.
effects.
SUM
590.450
9312.350
1561.300
125104.225
232.900
6552.875
1040366.450
3775.050
44384.425
2662.700
18524.375
differences
F-VALUE
OF SQUARES
in
SIGNIFICANCE
1.51
17.89
* *
286.37
0.13
NV
NS
1684.86
1.53
71.88
1.08
NV
NS
NV
NS
seasonal
evapotranspiration
is
highly
However, there are no significant C*HAr C*T, and C*T*HA
Results
of the Tukeys' BSD naans separation procedure for
cultivar seasonal evapotranspiration are shown in Table 8.
Newana and MT 8182 had higher seasonal evapotranspiration than MT
7819, Fortune, and MT 7836.
33
Table 8: Tukeys1
HSD test for cultivar differences
evapotranspiration.
CULTIVAR
MEAN
EVAPOTRANSPIRATION (ran)
NEMANA
MT 8182
MT 7819 (Glenmann)
FORTUNA
MP 7836
456.91
456.84
442.28
441.78
440.06
in seasonal
GROUPING
A
A
B
B
B
Note:
alpha
d.f
msd
mse
=
0.05
= 12
=
9.09
= 130.11
Relative Water Content
Results of the analysis of variance for leaf relative water
content are tabulated in Table 9:
Table 9: Analysis of variance for leaf relative water content (%).
SOURCE
D.F.
R
I
4
C
Error (C)
4
T
3
12
C*T
15
Error (T)
I
WEEK
4
C*WEEK
3
T*WEEK
MCDEL ERROR 19
SUM
OF SQUARES
189.308
357.804
91.318
84.149
243.290
334.804
12.038
290.871
88.972
1832.736
F-VALUE
SIGNIFICANCE
8.29
3.92
NS
1.26
0.91
NV
NS
0.12
0.75
0.31
NS
NS
NS
The model Error term was used for the F-test of the C*WEEK and
T*WEEK terms due to the fact that the R*C*T*WEEK term had zero degrees
of freedom.
In any eventf these interaction terms turned out to be
34
nonsignificant.
Results obtained from this analysis confirm the insensitivity of
RSTC as an index of plant moisture stress/ as has been pointed out by
Hsiao
(1973).
This
is mostly
due
to variations
in
leaf water
characteristics (including relative water content) which can be caused
by
changes
in meteorological
conditions
(Yang
and de Jong/
1972).
Furthermore/ given the fact tiiat the H C values obtained (Appendix I)
were
relatively high
(greater than 81%) / the plants were not that
stressed by the moisture regimes maintained for the duration of
measurements of RPC.
Canopy Temperature and Canopy-Air Temperature Difference
Table 10 shows the analysis of variance results for the canopy
temperature data.
Table 10: Analysis of variance for crop canopy temperature (0C).
SOURCE
D.F.
R
3
4
C
Error (C)
12
I
HA
C*HA
4
Error (HA) 15
T
3
C*T
12
T*HA
3
C*T*HA
12
Error (T)
90
3
WEEK
C fcWEEK
12
HAfcWEEK
I
T fcWEEK
6
C fcT fcHAfcWEEK 32
Error (WEEK) 115
SUM
OF SQUARES
14.990
18.269
72.076
17.539
9.399
39.443
438.089
5.667
248.463
17.911
126.334
2072.812
4.848
283.831
0.000
0.000
125.007
F-VALUE
SIGNIFICANCE
0.83
0.76
NS
6.67
0.89
NV
NS
104.03
0.34
59.00
1.06
635.63
0.37
261.11
0.00
0.00
.
NV
NS
NV
NS
* *
NS
* *
NS
NS
.
35
The C
factor proved
to be
insignificant,
and the only significant
interaction term is HA*WEEK.
The analysis of variance for the canopy^air temperature difference
(Tc - Ta) is shown in Table 11.
Table 11: Analysis of variance
difference (0C).
SOURCE
D.F.
R
3
C
4
Error (C)
12
HA
I
C*HA
4
Error (HA) 15
T
3
C*T
12
T*HA
3
C*T*HA
12
Error (T)
90
WEEK
3
C*WEEK
12
I
HAaWEEK
6
TaWEEK
C a T a HAaWEEK 32
Error (WEEK) 115
Again,
SUM
for
OF SQUARES
27.199
46.421
58.639
0.123
2.847
54.705
147.201
20.483
38.763
18.830
180.944
288.867
12.713
10.823
92.267
48.597
132.750
canopy-air
P-VALUE
1.86
3.27
0.03
0.20
24.41
0.85
6.43
0.78
47.58
0.52
5.35
7.60
0.75
there is no significant C effect,
temperature
SIGNIFICANCE
NS
NV
NS
NV
NS ■
NV
NS
* *
NS
*
* *
NS
though there are very
significant effects due to the WEEK term, and T*WEEK interaction term.
The HA*WEEK
interaction term is significant albeit only at the 5%
level. All other terms are not significant.
Also, the significance of the interaction terms involving the WEEK
factor point t ^ t h e importance of the time lag between the measurement
of Tc and
Pinter,
(Tc - Ta). This is supported by the results obtained by
and
Reginato
(1982).
Their
research indicated that the
parameter, crop water stress index (CWSI), which is based on (Tc - Ta),
36
and hence/ Tc / falls to a minimum value following an irrigation/ and
rises slowly again as the crop exhausts its supply of water.
The fact that there were no significant cultivar differences in
canopy temperature-based drought stress parameters/
as
Tables 10
of significant
and
11 could
also be due to the lack
indicated in
differences in the soil water content of the irrigation treatments.
Hatfield et al. (1984) have found Tc to be a useful indicator of crop
water
stress
in cotton so it should not be unreasonable to expect
cultivar differences in Tc and (Tc - Ta) under conditions of adequate
moisture stress. Indeed/ Blum et al.
infra-red
photography
to
(1978) and Blum (1975) have used
successfully
detect
genotype-caused
differences in sorghum drought tolerance.
Stonatal Mass Flow Resistance
Analysis of variance of stomatal mass flow resistance (SMFR)
shown
in
Table
12.
Except
for WEEK/
all
the main
effects
is
and
interaction terms that can be validly tested are insignificant. These
results are not surprising.
Appendix I shows the mean SMFR for
different cultivars at each irrigation treatment level. The resistances
are all very low/ even for the "dry" irrigation treatment levels. This
implies that the stomata of the plants were open most of the time/
indicating unstressed conditions. This/ more than anything/ explains
why all the resistances obtained were below 1.0 sec cirT^.
The effect of mild water stress on SMFR is probably mediated by
other plant water stress parameters/ like HWC/ O 1
JP/ and Tc . AS pointed
out earlier/ measured RWC values were relatively high/
and Tc mean
values obtained (Appendix I) were relatively low. In fact/ mean canopy
37
Table 12: Analysis of variance for stomatal mass flow resistance
(sec cm
.
SOURCE
D.F.
R
3
4
C
Error (C)
12
HA
I
C*HA
4
Error (HA) 15
T
3 '
C*T
12
T*HA
3
C*T*HA
12
Error (T)
90
WEEK
3
12
C fcWEEK
I
HA*WEEK
T fcWEEK
8
C*T*HA*WEEK 40
Error (WEEK) 75 '
SUM
OF SQUARES
0.184
0.005
0.137
0.193
0.004
0.108
0.375
0.055
0.325
0.096
0.583
1.433
0.101
0.000
0.000
0.164
0.748
F-VALUE
SIGNIFICANCE
5.35
0.10
NS
26.76
0.15
NV
NS
19.34
0.70
16.72
1.24
NV
NS
NV
NS
47.89
0.84
0.00
0.00
0.41
* *
NS
NS
NS
NS
temperatures for all the cultivars and treatments were less than air
temperature with (Tc-Ta) ranging from -4.7 to -2.1°C. This indicates
significant transpirational activity (Gates, 1964; Wiegland and Namken,
1966).
Leaf Water Potential
Table 13 shows the results of the analysis of variance on the data
for the plant leaf water potentials.
There were significant Cp = 0.05) differences in accession leaf
water potential. Other significant
terms were the WEEK and the C*T*HA
effects. Results of the Tukeys' HSD test for cultivar differences in
LWP are as shown in Table 14.
38
Table 13: Analysis of variance for Leaf Water Potential (MPa)?
SOURCE
D.F.
R
3
C
4 .
Error (C)
12
HA
I
C*HA
4
Error (HA) 15
T
3
C*T
12
T*HA
3
C*T*HA
12
Error (T)
90
WEEK
4
16
C*WEEK
T*WEEK
11
C*T*HA*WEEK 25
Error (WEEK) 35
SUM
OF SQUARES
6.183
1.561
1.095
0.906
0.253
1.018
1.675
1.252
0.365
1.956
5.964
5.218
3.164
2.147
6.437
15.162
F-VALUE
SIGNIFICANCE
22.59
4.28
*
13.36
0.93
NV
NS
8.42
1.57
1.84
2.46
.
NV
NS
NS
* *
*
NS
NS
NS
3.01 .
0.46
0.45
0.59
Table 14: Tukeys1 HSD Test for cultivar differences absolute values of
leaf water potential (MPa):
CULTIVAR
MEAN
IMP
MT 8182
FORTUNA
MT 7819 (Glenmann)
MT 7836
NEWANA
1.76
1.64
1.63
1.60
1.55
GROUPING
A
A
A
A
B
B
B
B
Note:
alpha = 0.05
d.f
= 12
msd
= 0.17
mse = 0.09
DOT 8182 had a mean IMP (-1.76 MPa) significantly lower than that
of Newana (-1.55 MPa). This is riot explained by the results obtained
from the analysis of/
for exampler the accession differences in
39
seasonal evapotranspiration (Table 8). From Table Sr it is seen that
there are no significant differences between these accessions in their
seasonal evapotranspiration means.
Relationships Between the Plant Drought Stress Parameters
The means of the plant drought stress parameters by accessions for
each irrigation treatment are shown in Table 16. These values were used
to carry out regressions on the parameters to find out relationships
between them.
Stomata] Masa Flow Resistance and Leaf Relative Water Content
In plants not suffering from any drought stress, stcmatal aperture
is determined by illumination.
However, once water supply to the
plant becomes limited, stomatal aperture is determined by the degree of
leaf water deficit developed in the plant tissue (Ehrler and van Bavel,
1967; Slatyer, 1967).
Consequently, the SMFR of plant leaves should be expected to be
reduced with decreasing
relationship
1973)
is
EWC, all
not that simple,
things being equal.
However,
since most investigations
the
(Hsiao,
show a threshold value of EWC above which stomatal opening is
constant.
Figure 3 shows a plot of SMFR versus FWC.. NO equation was fitted
to the points but it is reasonable to conclude, on the basis.of a
visual inspection of the points, that there is a trend indicating a
decrease in SMFR with an increase in FMC.
0.20
E
omatal Mass Flow Resistance (sec
o
*
0.15 "
*
*
*
I
*
*
*
*
*
0.10 1
*
*
*
*
*
o
*
0.05 -
(Z)
0.00
80
85
90
Leaf Relative Water Content (%)
Figure 3.
Plot of Stomatal Mass Flow Resistance versus Leaf Relative Water Content.
95
41
Canopy Tenperature and Leaf Relative Water Content
Figure 4 shows a plot of Tc versus KtvCr with no equation fitted to
the points. Despite a lack of a fitted liner there is a trend in the
points showing a decrease in Tc caused by increasing E$C. This is as
expected since Weigland and Namken (1966) reported a 3.6°C increase in
cotton leaf temperature, when relative turgidity decreased from 83 to
59%.
Canopy Temperature and Stomatal Mass Flow Resistance
Canopy temperature depends to a large extent on transpiration rate.
This is due to the large latent heat of vaporization of water. Thusr
for
a given
set
of
conditionsr canopy temperature should decrease
proportionately to the increase in transpiration (Martinf 1943). Since
transpiration rate is directly proportional to stomatal aperture/ it is
to be expected that canopy temperature should be related to stomatal
aperture.
This is clearly indicated in Fig. 5/ which shows a plot of canopy
temperature versus
stomatal mass flow resistance.
When SMFR increases
from 0.10 to 0.15 sec/cm/ canopy temperature increases from 22.3 to
23.7°C.
The intercept of the plot is at 19.5°C which indicates the
temperature of the canopy under conditions of full stomatal opening
and/ by implication/ no water stress. This is not necessarily a stable
condition and most probably Tc / under conditions of no water stress/
will be significantly dependent bn environmental factors/ e.g. solar
radiation (Weigland and Namken/ 1966).
26
O
O
CD
O
O
24
O
3
O
O
O
®
Q-
E
O
O
CD
O
O
O
o 22
c
O
O
U
O
O
O
O
20
80
T
T
85
90
Leaf Relative Water Content (%)
Figure 4.
Plot of Canopy Temperature versus Leaf Relative Water Content.
95
Canopy Temperature ( C)
0.00
0.05
0.10
.
0.15
Stomatal Mass Flow Resistance (sec/cm )
Figure
5.
Plot of Canopy Temperature versus Stomatal Mass Flow Resistance.
0.20
44
Canopy-Air Teirperature Difference and Canopy Teirperature
The cubic plot of Tc-Ta versus Tc is as shown in Fig. 6. Even
though the model fitted has a high correlation coefficient of 0.99 (R^r
—
adjusted for the degrees of freedom), and the curve fits the points
relatively well, as indicated by a coefficient of variation of - 10.3%.
Figure 6 has a point of inflection at a canopy temperature of about
22°C and a (Tc-Ta) value of - 4.3°C. Beyond a canopy temperature of
22°C,
(Tc-Ta) increases with increasing Tc indicating a decrease in
transpiration
rate
caused
by
stomatal
closure
(Ehrler, 1973).
The
decrease in (Tc-Ta ) with increasing Tc below a Tc of 22°C could
probably be due to the fact that
(Tc-Ta) is influenced more by
environmental factors than by transpiration rate (and hence, Tc) under
conditions of low moisture stress.
Fluctuations of the Drought Stress Parameters
One unfortunate aspect of the experiment was that, due to the lack
of manpower and time, most of the plant drought stress parameters could
not
measured
simultaneously.
Consequently,
meaningful
regressions
could not be obtained for, say, SMFR versus IM*, EWC versus LWP, and Tc
versus LWP. To skirt this problem,
plots of the parameter means at
different days after planting (Table 17) were constructed, as shown in
Figs. 7 through 9.
Figure 7. shows a plot of LWP and SMFR versus the days after
planting. Since there were irrigations on the 42nd and 82nd days, the
plot shows the LWP changes within both a drying and wetting cycle. .As
can be seen from the plot, LWP fluctuates during the drying cycle (i.e
between the 42nd and 82nd days),
and this is without doubt due to
Y = 6 . 3 9 X - 0 . 6 1 X +0 .0 1 X
R - 0 -9 9
Canopy Temperature ( C)
Figure
6. Cubic plot of Canopy-Air Temperature Difference versus Canopy Temperature.
LWP
0.3 '
0.2
"
Leaf Water Potential (MPo)
omatol Mass Flow Resistance (sec
Irrigation Event on Day 82
Days After Planting
Figure 7. Plot of Etomatal Mass Flow and Leaf Water Potential Resistance at different days after planting.
47
extraneous
events
precipitation.
a f f ecting
soil
moisture
c o n t e n t r namely,
Worth noting is the fact that after an irrigation on
the 82nd day, the LWP takes about 6 days to respond to the increase in
moisture supply. This probably has more to do with the soil moisturetransport characteristics than any plant factor.
The stomatal mass flow resistances shown in Fig. 7
more than LWP.
fluctuate even
In addition to the precipitation factor, SMFR is also
dependent on a gamut of environmental factors which act both singly and
in concert.
For this reason, changes in SMFR are hard to relate to
soil moisture content alone. Furthermore, SMFR readings were no t .taken
after the 78th day and as such, nothing can be said about its response
to an irrigation.
Figure 8 shows the plots of the means of canopy temperature (Tc)
and the canopy-air temperature difference
(Tc-Tg) on different days
after planting. Both curves show some relative stability between the
59th and 76th days.
This is probably due more to the lack of data
points between these days than to an expression of physical reality.
This is indicated by the almost abrupt increase in Tc between the 76th
and the 78th days.
Between the 59th and the 76th days, both curves have a slight
positive slope indicating an increase in Tc with the drying of the soil
profile (Figure 10). It is noteworthy that the (Tc-Tg) is shown to be
increasing with increasing Tc .
Both canopy temperature and its difference from air temperature
decreased after the irrigation on the 82nd day. However, the rate of
decline of the parameters is not the same; canopy temperature declining
Irrigation Event on Day 82
Canopy Temperature (°C)
Days After Planting
Figure 8.
Canopy-Air Temperature Difference and
Canopy Tenperature at different days after planting.
49
at
a
faster
rate than
the canopy-air temperature difference.
suggests that in this case at least,
This
the canopy-air temperature
difference is not solely dependent on the canopy temperature.
Plots of the leaf EWC and IMP at different days after planting are
as shown in Fig. 9. EMC was measured only within the period of 63 and
70 days after planting. The mean values obtained Were variable, and
further, changes in these values roughly reflect changes in LWP. For
example, when EWC decreases from 91.7% on the 65th day to 78.8% on the
68th day, LWP decreased from -1.40 MPa to -1.77 MPa. When EWC increases
from 78.8
to 90.6 % between the 68th and 70th days, IWP increases from
-1.77 to -1.57 MPa.
These small changes in IWP in conjunction with large changes in
EWC are in line with the conclusions of HSiao (1973) since with nearly,
saturated tissue (as indicated by high EWC values), a small change.in
water content can significantly affect
^
(the pressure component of
IWP).
Since soil moisture content was not measured simultaneously with
the plant drought stress parameters, no regressions could be done to
determine the relationships between soil moisture content and these
parameters.
However, as is shown in Figures 10 and 11 some of these
parameters change in a manner roughly dependent on changes in soil
moisture content.
Thus,
from Fig.
10, which shows the soil moisture content and
canopy temperature at different days after planting,
that as soil moisture content decreases from 20.8
it can be seen
to 18.6 cm from the
74th to the 79th day, canopy temperature increases from 22.10C bn the
Irrigation Event on Day 82
Leaf Water Potential (MPa)
LWR
Days After Planting
Figure 9.
Leaf Relative Water Content and Leaf Water Potential at different days after planting.
Irrigation Event on Days 42 and 82
30
20
15
Days After Planting
Figure 10.
Soil Moisture Content and Canopy Temperature at different days after planting.
Canopy Temperature ( C)
25
52
76th day to 27.2°C on the 78th day. After the irrigation on the 82nd
dayr
canopy temperature declines with an increase in soil moisture
content.
Since
small
changes
in soil moisture
content lead
to
relatively large changes in canopy temperature, this is an indication
of the sensitivity of canopy temperature as an index of soil moisture
■
content.
Figure 11 shows the variation of (Tc-Ta) and soil moisture content
during the growing season. Here again, the pattern of changes in (TcTa) approximate the changes in soil moisture content. Thus, when soil
moisture content decreased from 20.8 cm on the 74th day after planting
to 18.6 cm on the 79th day, (Tq -Tq) decreased from -3.2°C on the 76th
day to -6.I0C on the 83rd day.
However, between the period from the 58th to the 74th days, soil
moisture content decreased by 5.7 cm and (Tq -Tq) actually increased in
this period.
This can only be due to either the predominance of other
environmental factors in the determination of (Tq -Tq) or undetermined
increases in soil moisture content caused by precipitation.
Indeed,
18.2 mm of precipitation was recorded during this period (Table 15).
Changes in stomatal mass flow resistance (SMFR) and soil moisture
content at different days after planting are shown in Fig. 12. Changes
in SMFR do not, in this case, seem to be related to changes in soil
moisture
content.
Almost
all
the determinations
of
SMFR were done
between the 58th and the 70th days. Since only two measurements of soil
moisture content were carried out in this period (on the 58th and the
74th days), transient changes in soil moisture content that could have
affected SMFR might have gone un-detected.
Irrigation Event on Days 42 and 82
-2
—
6
—8
Canopy—Air Temperature Difference ( C)
- -4
100
Days After Planting
Figure 11.
Soil Moisture Content and Canopy-Air Temperature Difference at different days after planting.
Irrigation Event on Days 42 and 82
omatal Mass Flow Resistance (sec/cm
50
60
70
Days After Planting
Figure 12.
Soil Moisture Content and Stomatal Mass Flow Resistance at different days after planting
55
SUMMARY AND CONCLUSIONS
The results of this experiment show the hazards involved in the
application of theoretical deductions to field conditions. For the most
part/ the theoretical basis for the relationships between plant drought
stress parameters is very sound. However/ the complex inter-play of all
these factors under field conditions makes it very difficult/ at best/
to discern the nature of these relationships.
Thus/ as has been shown in Tables 2 through 14/ very few of the
drought stress parameters studied indicated any cultivar differences.
In fact/ of all the drought stress parameters studied/ it was only in
the case of leaf water potential that cultivar differences were found.
Although the soil moisture use parameters
evapotranspiration/
and
seasonal
(soil moisture depletion/
evapotranspiration)/
showed
significant cultivar differences (Tables 3/ 5/ and 7) / there were no
consistent trends in these differences (Tables 4/ 6/ and 8).
Disappointing
as the above
results are/
the drought stress
parameters regressions show that even under the variable environmental
conditions obtained in the field during the study period/ significant
correlations between some of the parameters could be obtained. Thus;/ in
Fig. 5/ canopy temperature is shown to be linearly related to stomatal
mass
flow resistance and
in Figure 6
the dependence of canopy-air
temperature difference on canopy temperature is indicated.
These results indicate that there is some basis for further study
of the use of easily determined drought stress parameters (e.g. canopy
56
temperature and/or canopy-air temperature difference) for the detection
of plant drought stress and, ultimately, irrigation scheduling. The use
of canopy temperatures as an indicator of plant drought stress is now
fairly well accepted (Jackson et. al, 1977; Jackson, 1982; Singh and
Kanemasu, 1983).
That canopy-air temperature difference is significantly dependent
on canopy temperature (Fig. 6) suggests an alternative method for the
fast detection of plant drought stress. In this regard, the development
of models that incorporate meteorological factors (i.e., SPD) in the
equations based o n .canopy temperature or canopy-air temperature
difference
(Reginato,
1983;
Idso et.
al.
1984)
should imply an
improvement in the reliability of the use of these parameters in plant
drought stress detection.
The means of the drought stress parameters at different days after
planting are plotted in Figs. 7 through 12. Even though most of the
results obtained in this vein were inconclusive, there is enough trend
in the variations to warrant further investigations into changes in
these parameters both with irrigation events as well as plant aging. If
anything,
such
effort might
yield
valuable
information
on
the
reliability of the use of these parameters at different stages of plant
growth.
•
In conclusion, the results obtained from this experiment proved to
be both inconclusive in some respects and promising in others. On one
hand, there were no cultivar differences in most of the plant drought
stress parameters. On the other hand, there were indications of some
good correlations between some of the parameters. In a way, the results
57
reflect the fact that due to relatively high precipitation (Table 15)
the water supply gradient between the irrigation treatments could not
be consistently maintained for the duration of the trial.
Furthermorez
the precipitation also prevented the imposition of
severe drought stress on the plants as shown by the means obtained for
the parameters (Tables 16, and 17). For the benefit of future research
efforts,
it might be worth noting that the success or failure of an
experiment like this depends
in no small way on the extent to which
reasonable levels of water stress are imposed on the plants.
BIBLIOGRAPHY
59
Astonf A.R. f and van Bavelz C.H.M. 1972. Soil surface water depletion
and Ieat temperature. Agron. J. 64:368-373.
Bangez G.G.J. 1953. On the quantitative explanation of stomatal
transpiration. Acta bot. neerl. 2:255-297.
Barrsz H.D. 1968. Determination of water deficits in plants. In: Water
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Press. New York. pp. 235-268.
Boyerz J.S. 1970. Leaf enlargement and metabolic rates in cornz
soybeanz and sunflower at various leaf water potentials. Plant
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Bladz B. and Rosenbergz N. 1976. Measurement of crop temperature
by leaf thermocouplez infrared thermometryz and remotely sensed
thermal imagery. Agron. J. 68:635-641. .
Bladz B.L.z and N.J. Rosenberg. 1975. Evaluation of a resistance
model for estimating evapotranspiration in the east central Great
Plains. Agric. Meteorol. Progr. Rep. 75-1. Uhiv. of Nebraskaz
Lincoln. Chap. 3.
Blumz A. 1974. Infra-red photography for selection of dehydration
avoidant Sorghum genotypes. Z. Pflanzenzuecht. 75:339-345.
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APPENDICES
66
Table 15: Precipitation recorded on
different
Days after planting
after planting.
Precipitation (ran)
3
0.2
5
1.0
6
2.0
7
10.0
17
1.0
18
2.0
19
2.0
20
2.0
21
12.0
22
10.0
24
6.0
25
3.0
26
8.0
30
2.0
35
0.2
43
9.0
45
5.0
Note: Continuation on pp. 67
days
67
Table 15: (continued).
Days after planting
Precipitation (mm)
45
1.0
50
4.0
51
20.0
56
4.0
57
5.0
58
6.0
63
16.0
64
0.2
73
.
2.0
86
6.0
89
6.0
97
23.0
105
4.0
106
0.2
68
Table
16:
Accession
Accession drought stress parameter means
irrigation treatment levels.
Irrigation
Treatment
Soil
FWC
Moisture
Content
(cm)
(mm).
LWP
Tc
(MPa)
( °C)
ET
for different
Tc-Ta
SMFR
( 0C) (see/cm)
Newana
"Dry"
Low"
Medium
High
27.4
35.7
43.7
45.4
22.7
24.1
26.3
28.3
92.2
90.6
90.9
92.3
-1.76
-1.41
-1.40
-1.71
21.1
23.8
22.8
22.1
-4.4
-3.4
-4.5
-4.7
0.07
0.15
0.14
0.09
Fortuna
"Dry"
Low
Medium
High
27.3
35.4
41.8
42.7
22.6
23.4
25.2
27.5
91.2
89.7
81.0
87.3
-1.76
-1.55
-1.66
-1.64
21.3
24.3
23.4
22.6
-4.3
-2.6
-3.3
-3.8
0.08
0.14
0.15
0.09
"Dry"
Low
Medium
High
27.1
34.7
41.8
43.8
22.5
24.1
26.6
27.9
88.0
88.4
83.5
89.7
-1.67
-1.67
-1.57
-1.62
21.5
24.5
23.1
22.3
-3.2
-2.1
-3.6
-4.1
0.09
0.14
0.12
0.07
MT 7836
"Dry"
Low
Medium
High
26.6
34.8
42.0
43.3
21.9
24.1
25.4
27.0
91.4
87.7
90.9
92.9
-1.78
-1.56
-1.51
-1.61
21.1
24.3
23.3
22.7
-3.5
-2.4
-3.7
—4.6
0.06
0.16
0.14
0.10
MT 8182
"Dry"
Low
Medium
High
27.4
36.3
43.5
45.2
21.4
23.2
25.2
27.6
92.4
92.5
94.3
92.8
-1.81
-1.69
-1.73
-1.82
20.8
24.1
22.6
22.2
-4.1
-3.0
—4.4
-4.4
0.05
0.14
0.16
0.12
MT 7819
(Glenmann)
69
Table 17: Drought stress parameter means at different days after
planting.
Days
After
Planting
Tc
. RWC
Tc-?a
( °C) ( 0C).
(%)
18 .
-
-
-
26
-
-
-
29
-
-
-
40
-
.-
44
-
54
-
55
LWP
(MPa)
-
SMFR
(sec/cm)
SMC
(cm)
-
30.5
-
32.2
-
-
33.4
-
-
-
29.0
-
-
-
29.7
-
-
-1.55
—
-
-
-
-1.85
—
56
-
-
-
-1.84
-
58
19.7
-3.5
-
-1.62
0.06
26.5
59
21.6
-4.1
-
-
0.03
-
.- •
-
63
-
-
. 92.8
-2.11
0.35
' -
65
-
-
91.7
-1.48
0.17
-
-
-1.78.
0.02
-
.-
66
68
-
-
78.8
-1.77
0.15
-
69
-
-
93.9
-1.77
0.31
- ■
70
-
-
90.6
-1.57
0.09
-
74
-
■ -
-
-
■
Note: Continuation in pp. 70
* Soil moisture content
■ -
20.8
70
Table 17: (continued).
Days
After
Planting
Tc"Ta
EWC
LWP
( °C) ( °C)
(%)
(MPa)
Tc
SMFR
(see/cm)
SMC
(cm)
76
22.1
-3.2
-
-
-
-
77
25.0
-3.1
—
-
0.15
-
78
27.2
-3.0
-
-
0.17
-
79
-
83
24.2
-6.1
86
21.0
—6.6
-
-
88
89
90
-
-
92
-
-
93
-
-
102
M.
—'
-
■-
-1.85
-1.86
-
-
18.6
20.8
-
■-
19.6
-
-0.66
-
- ’
-
-1.02
-
-
-1.47
-
-
-1.74
-
-
—
—
18.9
.—
3
»