Agronomy Journal Journal of Natural Resources and Life Sciences Education
HOME HELP FEEDBACK SUBSCRIPTIONS ARCHIVE SEARCH TABLE OF CONTENTS
QUICK SEARCH:   [advanced]


     

Published online 4 April 2007
Published in Agron J 99:637-644 (2007)
DOI: 10.2134/agronj2006.0062
© 2007 American Society of Agronomy
677 S. Segoe Rd., Madison, WI 53711 USA
This Article
Right arrow Abstract Freely available
Right arrow Figures Only
Right arrow Full Text (PDF) Free
Right arrow Alert me when this article is cited
Right arrow Alert me if a correction is posted
Services
Right arrow Similar articles in this journal
Right arrow Alert me to new issues of the journal
Right arrow Download to citation manager
Right arrow reprints & permissions
Citing Articles
Right arrow Citing Articles via HighWire
Right arrow Citing Articles via Google Scholar
Google Scholar
Right arrow Articles by Baker, J. T.
Right arrow Articles by Upchurch, D. R.
Right arrow Search for Related Content
PubMed
Right arrow Articles by Baker, J. T.
Right arrow Articles by Upchurch, D. R.
Agricola
Right arrow Articles by Baker, J. T.
Right arrow Articles by Upchurch, D. R.
Related Collections
Right arrow Agroclimatology
Right arrow Water Stress

Drought

Using Leaf Gas Exchange to Quantify Drought in Cotton Irrigated Based on Canopy Temperature Measurements

J. T. Bakera,*, D. C. Gitzb, P. Paytonb, D. F. Wanjurab and D. R. Upchurchc

a USDA-ARS, Plant Stress and Water Conservation Laboratory, 302 West I-20, Big Spring, TX, 79720
b USDA-ARS, Plant Stress and Water Conservation Laboratory, 3810 4th Street, Lubbock, TX 79415
c USDA-ARS, 1001 Holleman Drive East, College Station, TX 77840

* Corresponding author (jtbaker{at}lbk.ars.usda.gov)

Received for publication February 24, 2006.

   ABSTRACT
TOP
 ABSTRACT
INTRODUCTION
 MATERIALS AND METHODS
 NOTES
 RESULTS
 DISCUSSION
 SUMMARY
 REFERENCES
 
Plant gas exchange provides a highly sensitive measure of the degree of drought stress to which a crop is exposed. However, equipment costs and time requirements for gas exchange measurements are major obstacles to the use of gas exchange measurements in real-time irrigation scheduling systems. Canopy temperature (Tc) provides a much easier to acquire indication of crop water deficit that has been used in irrigation scheduling systems, but interpretation of this measurement has proven difficult. Our goal was to test the ability of Tc to quantify the degree of crop water deficit by comparing Tc with simultaneous measurements of leaf-level gas exchange parameters, which were viewed as alternative indicators of water deficit. To provide a wide range of plant water deficit conditions for the comparison of Tc with leaf-level gas exchange parameters, cotton (Gossypium hirsutum L.) was subsurface drip irrigated using Tc according to the stress-time index method of irrigation scheduling during two growing seasons. Comparisons between Tc and leaf-level gas exchange were accomplished by measuring Tc diurnally with hand-held infrared thermometers and controlling cuvette leaf temperature (TL) equal to Tc and then measuring leaf level net assimilation (A) and stomatal conductance (g) at a photosynthetically active radiation (PAR) level of 1500 µmol (photons) m–2 s–1. In general, as plant water deficit became more severe, leaf level gas exchange tended to decline with rising TL. However, we found that A and g could vary by more than twofold at a given TL, indicating that Tc was not a particularly robust indicator of the degree of drought stress. Furthermore, we found the leaf minus air temperature differential (TL – Ta) and vapor pressure deficit calculated based on leaf temperature (VPDL) were better predictors of the degree of drought stress, as indicated by gas exchange parameters, than TL alone. Regression of A and g against (TL – Ta) and VPDL indicated that the combination of these two variables accounted for >79% of the variability in A and g. We conclude that the term (Tc – Ta) either alone or in combination with VPD should provide a better predictor of the degree of drought stress in cotton than Tc alone.

Abbreviations: A, leaf level net assimilation • g, light saturated stomatal conductance • CWSI, crop water stress index • PAR, photosynthetically active radiation • PFD, photosynthetic photon flux density • SDD, stress degree day • ST, stress time • Ta, air temperature • Tc, canopy temperature • TL, leaf temperature • VPDL, vapor pressure deficit calculated based on leaf temperature


   INTRODUCTION
TOP
 ABSTRACT
 INTRODUCTION
MATERIALS AND METHODS
 NOTES
 RESULTS
 DISCUSSION
 SUMMARY
 REFERENCES
 
LIMITED SOIL WATER AVAILABILITY reduces crop growth more than all other environmental factors combined (Mauney et al., 1979; Boyer, 1982). In arid and semiarid regions where water resources for irrigation are being depleted, methods for more efficient irrigation scheduling are needed for commercial growers.

In the 1970s and 1980s, the advent of relatively affordable infrared thermometers for remotely monitoring Tc spurred research into the use of Tc as a real-time measure of crop water status for irrigation scheduling. The central idea here is that as drought stress progresses in severity, stomata close and the resulting reduction in latent energy loss by the canopy causes Tc to rise. However, because a number of environmental and plant factors combine to determine Tc at any given point in time, interpretation of this measurement is difficult (Idso et al., 1966). Idso et al. (1977) and Jackson et al. (1977) developed the stress degree day (SDD) index, which they defined as the cumulative difference between Tc and Ta. Here, it was assumed that if the (Tc – Ta) differential was negative, the plants were well watered, but a positive (Tc – Ta) differential indicated a drought stress. Improving on this concept, Idso et al. (1981a) empirically, and Jackson et al. (1981) theoretically, developed the crop water stress index (CWSI). Use of this index requires the development of a nonwaterstressed baseline, which is the linear relationship between the (Tc – Ta) differential vs. air vapor pressure deficit under nonlimiting soil water conditions, where the crop is transpiring at the potential rate. The CSWI has subsequently been related to other physical and physiological measures of drought stress, including soil water content (Jackson et al., 1981), plant water potential (Idso et al., 1981b,c), and net photosynthesis (Idso et al., 1982; O'Toole et al., 1984).

In another approach for scheduling irrigation based on Tc, Wanjura et al. (1992) developed a stress time (ST) index that accumulates the amount of daily time that Tc exceeds a specified optimum or threshold Tc for a crop. Underlying the ST index and the concept of an optimum or threshold Tc are the findings of Burke (1993) and Burke and Oliver (1993), who showed that leaf enzymes operate most productively in a narrow temperature range called the thermal kinetic window. Under the ST index criteria, an irrigation is triggered when Tc exceeds a specific threshold temperature for a specified duration of time, called the time threshold, during a given day. Using the ST method for irrigation scheduling, a wide range of temperature thresholds, daily accumulated STs, and irrigation amounts were empirically evaluated against yield and water use criteria in a series of experiments conducted at Lubbock, TX (Wanjura et al., 1993, 1995, 2002). Wanjura and Upchurch (2000) compared irrigation scheduling using the CWSI and ST and concluded that the CWSI was a potentially superior method for comparing water stress levels across environments, but noted that application of the CWSI was difficult to implement because of the need to measure or calculate several environmental factors.

Previous studies have utilized a number of different measurements to quantify the degree of drought stress including plant (Comstock and Mencuccini, 1998) or soil water potential (Lamhamedi et al., 1992), fraction of extractable soil water (Ray et al., 2002; Sinclair, 2005), relative plant tissue water content (Ritchie et al., 1990) and leaf (Faver et al., 1996) and whole-canopy gas exchanges (Marani et al., 1985; Baker et al., 1997). A problem with thermodynamic measures of drought stress is that there are no unique functions that describe plant responses to either plant or soil water potential (Sinclair and Ludlow, 1985; Lawlor, 1995; Sinclair, 2005). Because of interspecific differences in the relationships between photosynthesis and leaf water potential or relative water content, Flexas and Medrano (2002) successfully utilized g as an indicator of the degree of drought induced inhibition of different photosynthetic subprocesses for a wide range of published studies in the literature. Medrano et al. (2002) and Flexas and Medrano (2002) divided g into four broad ranges according to the effect of g on various photosynthetic subprocesses: g > 150 mmol H2O m–2 s–1 (unstressed to mild drought); 150 mmol H2O m–2 s–1 > g > 100 mmol H2O m–2 s–1 (moderate drought); 100 mmol H2O m–2 s–1 > g > 50 mmol H2O m–2 s–1(severe drought), and g < 50 mmol H2O m–2 s–1 (very severe drought). Plant gas exchange is clearly a sensitive measure of the degree of drought stress with only leaf tissue expansion (Sadras and Milroy, 1996), being one of the few physiological responses that is more sensitive to plant water deficit than gas exchange.

For automated irrigation scheduling systems, two desirable characteristics of a sensor or an indicator of plant water deficit are clearly, first, an ability to detect whether or not a crop is in fact under a drought stress and, further, an ability to determine the severity or degree of that drought stress. In the current study, our goal was to test the ability of Tc to quantify the degree of drought stress by comparing Tc with simultaneous measurements of leaf-level gas exchange parameters in an experiment on cotton where subsurface drip irrigation was scheduled with the ST method.


   MATERIALS AND METHODS
TOP
 ABSTRACT
 INTRODUCTION
 MATERIALS AND METHODS
NOTES
 RESULTS
 DISCUSSION
 SUMMARY
 REFERENCES
 
‘Paymaster 2326BGRR’ cotton was planted on 13 May 2003, while Fibermax, FM 959 was planted on 7 June 2005 at the Plant Stress and Water Conservation Laboratory in Lubbock, TX (33°40' N, 101°49' W) into rows 1.02 m apart. After emergence, plant population was 119 000 and 137 000 plants ha–1 in 2003 and 2005, respectively. Drip irrigation laterals had been previously installed 0.35 m below the soil surface in each row. Row spacing was 1 m with drip lines placed in alternate furrows or 2 m between drip lines. The soil was an Olton clay loam (fine, mixed, thermic, Aridic Paleustolls).

In both years, Tc was monitored with infrared thermometers (IRt/c) (Model IRt/c-K-80F/27C, Exergen, Corp, 51 Water Street, Watertown, MA)1 with a 28° field of view. The IRt/c were wrapped with insulation, encased in PVC pipe, and attached to vertical poles in each plot above the plant canopy. The Tc was monitored at 6-s intervals and data were averaged and recorded every 15 min using a Campbell Scientific CR23X data logger.

Irrigation events were based on daily accumulated ST, where ST was the accumulation of time (h) that Tc exceeded an optimum critical temperature threshold of 28°C (Burke et al., 1988). Treatments in 2003 consisted of time thresholds, where a time threshold is the number of hours in a day Tc must exceed 28°C in order for an irrigation event to be triggered. Time thresholds evaluated were 5.5, 6.5, 7.5, and 8.5 h. Each irrigation event for a given day delivered 5 mm of water. Additionally, for comparison purposes, in single unreplicated plots, irrigation treatments of 4, 5, and 6 mm per irrigation event were maintained using 5.5 h as a time threshold. In 2005, treatments consisted of irrigation amounts per irrigation event: 0 (dryland), 2.5, 5, and 7.5 mm. Here, irrigations in all plots were based on the ST accumulated in the 5-mm treatment with a time threshold of 5.5 h. These ST irrigation treatments provided a wide range of plant water deficit treatments for the comparison of Tc with leaf-level gas exchange measurements.

On 8 May and 6 Aug. 2003, 61.6 kg N ha–1 was injected into the irrigation system. In 2005, preplant fertilizer was applied at a rate of 54 kg N ha–1 and 27 kg P ha–1. Also in 2005, additional N was added through the irrigation system from 13 July to 25 August. This additional N amounted to 17.7, 35.4, and 53.5 kg N ha–1 for the 2.5, 5, and 7.5 mm irrigation amount treatments, respectively.

Photosynthesis meters (LI-6400, LICOR, Inc., Lincoln Nebraska) were used to measure single-leaf gas exchange characteristics from 5 to 21 Aug. 2003 and 8 Aug. to 9 Sept. 2005. Equations for calculating A [µmol (CO2) m–2 s–1], g [mol (H2O) m–2 s–1], substomatal carbon dioxide concentration [Ci, µmol (CO2) mol–1 (air)], and VPDL (kPa) are given in the LI-6400 users manual (LI-COR Biosciences, 2002) after von Caemmerer and Farquhar (1981).Typically, measurements were made from about 0900 to 1500 h during the day. Cuvette relative humidity was controlled to 50% in 2003 and 30% in 2005, while carbon dioxide concentration was maintained at 350 µmol (CO2) mol–1 air in both years.

Before making leaf-level gas exchange measurements, a hand-held infrared thermometer (Infrared Ag Multimeter, Model 510B, Everest Interscience, Inc., Fullerton, CA) was used to obtain an average TL of several sunlit leaves in a particular treatment. Once this average TL was obtained, this value was entered into the LI-6400 as a set point for controlling cuvette TL to that predetermined value. Automated photosynthetic light response curves were then generated by controlling the cuvette red/blue LED (6400–02B, LICOR, Inc., Lincoln Nebraska) to PAR values of 2000, 1500, 1000, 500, 200, 100, 50, and 0 µmol (photons) m–2 s–1. Leaves selected for gas exchange measurement were the fourth leaf, counting nodes with leaves longer than 3 cm from the top of the mainstem. Light response curves were obtained for two to eight individual leaves at a particular TL. Typically these measurements at a given TL required 40 min to 1 h to complete. This process was then repeated by measuring another average TL on a different set of leaves and generating another set of light response curves. As each day progressed, TL generally increased primarily due to increasing solar radiation and increasing Ta. Differences in set point TL between sets of measured leaves typically ranged from 1 to 3°C depending on weather conditions and irrigation treatment. A single LI-6400 instrument was available in 2003, while three LI-6400 photosynthesis meters were used in 2005. In all cases, a single photosynthesis meter was assigned to one treatment for a given day.

In 2003, data were grouped as either wet or dry data sets, depending on whether that particular plot had received an irrigation on the previous day (Table 1). To simplify the analysis, we chose a common PAR level of 1500 µmol (photons) m–2 s–1 to compare measured leaf gas exchange parameters. Leaf-level gas exchange parameters used to quantify the degree of drought stress in these experiments were A [µmol (CO2) m–2 s–1] and g [mol (H2O) m–2 s–1]. Trends in gas exchange measurements vs. measured environmental parameters were determined by regression analysis using the GLM and REG procedures provided by the SAS Institute (SAS Institute, 1990).


View this table:
[in this window]
[in a new window]

  		Table 1. Summary of treatment conditions in a drip irrigated cotton experiment at Lubbock, TX, in 2003 on selected days when diurnal leaf-level gas exchange measurements were made. All irrigations occurred after 1700 h, after that day's leaf-level gas exchange measurements had been completed.

 

   RESULTS
TOP
 ABSTRACT
 INTRODUCTION
 MATERIALS AND METHODS
 NOTES
 RESULTS
DISCUSSION
 SUMMARY
 REFERENCES
 
Shown in Fig. 1 are two examples of the light response curves for TL of 27.9 and 40.1°C for the wet and dry data sets in 2003, respectively. In this example, the combination of high TL and drought stress sharply reduced A in the dry data set and induced complete photosynthetic light saturation at much lower photosynthetic photon flux density (PFD) compared with the wet data set.


Figure 1
View larger version (16K):
[in this window]
[in a new window]

  		Fig. 1. An example of leaf net assimilation (A) vs. photosynthetic photon flux density (PFD) for experimental plots that were either irrigated the previous day (wet) or that were not irrigated the previous day (dry). Wet and dry data sets were collected on three or four leaves on 8 and 11 Aug. 2003, respectively. Error bars are ± standard error. Regression curves are of the form y = y0 + a[1 – exp(–bx)] with R2 > 0.99 for both curves.

 
In Fig. 2 , A and g measured at a PFD of 1500 µmol (photons) m–2 s–1, is plotted against TL for the data collected in 2003. Although most well watered, temperate C3 plants exhibit a broad photosynthetic temperature optimum between 20° and 35°C with peak A near 30°C, it must be emphasized here that TL in this experiment was measured under a wide range of drought stress conditions. In Fig. 2, A declined with increasing TL with a much sharper decline for the dry data set, where the crop did not receive an irrigation the previous day, compared with the wet data set, which did receive an irrigation the previous day. The g for the wet data set varied considerably with TL, while g was comparatively low in the dry data set. The large variability in A and g across the wet and dry data sets at a given TL indicates that TL was not a particularly robust indicator of the degree of drought stress as quantified by these gas exchange parameters. For example, at a TL of 30°C, A varied from about 10 to >20 µmol m–2 s–1, while g varied from {approx}0.1 to >1.0 m–2 s–1. Theoretically, one wouldn't expect Tc to be an ideal indicator of crop water status since it responds to several physiological and environmental parameters; however, research on the linkages between Tc and yield continue (Wanjura et al., 2002).


Figure 2
View larger version (14K):
[in this window]
[in a new window]

  		Fig. 2. Leaf net assimilation (A) and stomatal conductance (g) measured at a photosynthetic photon flux density (PFD) of 1500 µmoles (photons) m–2 s–1 vs. leaf temperature (TL) for wet and dry data sets collected in 2003.

 
In Fig. 3 , A and g measured at a PFD of 1500 µmol (photons) m–2 s–1 are plotted against TL for the 7.5-mm irrigation amount treatment in 2005. Before 1 September, both A and g were high, apparently due to frequent irrigations. The data collected on 8 September (open triangle symbols) showed a pronounced reduction in both A and g which corresponds to a 6-d time span without an irrigation. Following the irrigation on the evening of 8 September, the data on 9 September displayed an increase in A and a much smaller increase in g compared with the previous day. However, here again, the data in Fig. 3 illustrate that wide ranges in A and g and thus the degree of drought stress were possible at a given TL.


Figure 3
View larger version (19K):
[in this window]
[in a new window]

  		Fig. 3. Leaf net assimilation (A) and stomatal conductance (g) measured at a photosynthetic photon flux density (PFD) of 1500 µmoles (photons) m–2 s–1 vs. leaf temperature (TL) for the 7.5 mm irrigation amount treatment in 2005. Numbers in parentheses are the number of days since the last irrigation or significant rainfall.

 
In Fig. 4 , A is plotted against g for all data collected in these experiments. This relationship indicates that, as plant water deficit increases from low to moderate levels, g is reduced far more than A until g reaches about 0.4 mol m–2 s–1. After this point, as plant water deficit became more severe, A declined rapidly. Also shown in Fig. 4 is the relationship between calculated substomatal or intercellular CO2 concentration (Ci) and g. Here, the decline in Ci with increasing plant water deficit and reductions in g were more gradual than that for A and reached an apparent CO2 compensation point of about 116 µmol mol–1 at zero g.


Figure 4
View larger version (25K):
[in this window]
[in a new window]

  		Fig. 4. Leaf net assimilation (A) and intercellular CO2 concentration (Ci) measured at a photosynthetic photon flux density (PFD) of 1500 µmoles (photons) m–2 s–1 vs. stomatal conductance (g). Different symbols represent different operators with different photosynthesis meters or different years.

 
In an effort to search for a better predictor of the degree of drought stress than TL, A and g were regressed against several parameters that were either measured and/or controlled by the photosynthesis meters using the MAXR option of the REG procedure provided by the SAS Institute (SAS Institute, 1990). Results of this analysis are presented in Table 2. The single most important predictor of both A and g was (TL – Ta), followed by VPDL calculated based on TL. Although relative humidity was controlled in these experiments, the typical rise in TL with time during the day resulted in concomitant increases in VPDL with increasing TL. The TL described about 24 and 13% of the variability in A and g, respectively (Table 2). The best two-variable model was the combination of (TL – Ta) and VPDL, which described >79% of the variability in A and g (Table 2).


View this table:
[in this window]
[in a new window]

  		Table 2. R2 values for the linear regression of leaf level net assimilation (A) and light saturated stomatal conductance (g) against several environmental parameters either measured or controlled by the LI-6400 photosynthesis meter.{dagger}

 
Shown in Fig. 5 are the relationships between A and g vs. (TL – Ta). Here, a second order polynomial appeared to improve the fit (R2 = 0.66) of A vs. (TL – Ta) compared with the linear fit given in Table 2 (R2 = 0.61). Comparison of the two relationships in Fig. 5 indicate that, as in Fig. 4, g appeared more sensitive initially to plant water deficit than A. Examination of these two regression equations also indicate that drought stress was detectable via reductions in A and g at (TL – Ta) values < 0. Regression of A and g against both (TL – Ta) differential and VPDL are shown in Fig. 6 and 7 , respectively. Not unexpectedly, the addition of this second independent variable (e.g., VPDL) improved the regression fit compared with (TL – Ta) differential or other single variable parameters.


Figure 5
View larger version (27K):
[in this window]
[in a new window]

  		Fig. 5. Leaf net assimilation (A) and stomatal conductance (g) measured at a photosynthetic photon flux density (PFD) of 1500 µmoles (photons) m–2 s–1 vs. leaf minus air temperature differential (TL – Ta).

 

Figure 6
View larger version (61K):
[in this window]
[in a new window]

  		Fig. 6. Three dimensional plot of leaf net assimilation (A) measured at a photosynthetic photon flux density (PFD) of 1500 µmoles (photons) m–2 s–1 vs. leaf minus air temperature differential (TL – Ta) vapor pressure deficit (VPDL). Equation for the fitted plane is y = 33.93 – 2.05(TL – Ta) – 5.24(VPDL) with R2 = 0.79, Sy.x = 3.64, and n = 166.

 

Figure 7
View larger version (60K):
[in this window]
[in a new window]

  		Fig. 7. Three dimensional plot of stomatal conductance (g) measured at a photosynthetic photon flux density (PFD) of 1500 µmoles (photons) m–2 s–1 vs. leaf minus air temperature differential (TL – Ta) and vapor pressure deficit (VPDL). Equation for the fitted plane is y = 1.08 – 0.09(TL – Ta) – 0.26(VPDL), with R2 = 0.80, Sy.x = 0.17, and n = 166.

 

   DISCUSSION
TOP
 ABSTRACT
 INTRODUCTION
 MATERIALS AND METHODS
 NOTES
 RESULTS
 DISCUSSION
SUMMARY
 REFERENCES
 
In our view, two desirable characteristics of a sensor or an indicator of plant water deficit for use in an irrigation management strategy are, first, an ability to detect whether or not a crop is in fact under a drought stress, and further, an ability to determine the severity or degree of that drought stress. Our data (Fig. 2, 3) indicate that substantial plant water deficit can occur in situations where TL is below the temperature threshold of 28°C, presumably when there is insufficient energy in the environment to drive TL above 28°C. From the wide range of A and g at a given TL in Fig. 2 and 3, it is clear that TL by itself is not a particularly robust indicator of the degree of drought stress, at least as quantified by A and g. The question then arises, how well do A and g perform as indicators of the degree of drought stress?

A number of studies have shown that plant water uptake rates and/or transpiration generally proceeds at a maximum rate until about two-thirds of the available soil water is used, followed by a decline in gas exchange until all available water is exhausted (Ritchie, 1981; Sinclair and Ludlow, 1986; Ray et al., 2002; Sinclair, 2005). However, the fraction of available soil water threshold where plant gas exchange begins to decline can be affected by species or cultivar, atmospheric evaporative demand, and soil characteristics (Sadras and Milroy, 1996). In their review of the literature, Medrano et al. (2002) note that stomata respond to a wide range of internal and external factors related to plant water deficit, and often begin to close in response to drought before any change in leaf water potential or leaf water content is detectable. Because of this, Medrano et al. (2002) suggest that g represents a more integrated basis for assessing the effects of plant water deficit than leaf water potential or leaf water content. Our results in Fig. 4 indicate that g is initially more sensitive to the onset of plant water deficit than A, while A is quickly reduced as plant water deficit becomes more severe below g values of {approx}0.4 mol m–2 s–1.

Analysis of plant water deficit effects on leaf gas exchange often involves partitioning the effects of drought stress into either stomatal or nonstomatal effects. Stomatal effects involve gas diffusion processes through the stomata, while nonstomatal effects are biochemical in nature and are often analyzed in terms of ribulose bisphosphate carboxylase oxygenase (RuBP) activity and the regeneration of RuBP. For example, Faver et al. (1996), working with cotton, concluded that nonstomatal factors were largely responsible for small reductions in A under mild drought stress, but stomatal factors became more important than nonstomatal factors as drought stress became more severe. Similarly, even under mild drought stress, reduced ATP synthesis has been cited as the primary limitation of A (Tezara et al., 1999). In contrast with these reports, but supportive of the trends we show in Fig. 4 and 5, Flexas and Medrano (2002) concluded that stomatal closure was the earliest plant response to mild drought stress and that with increasing drought stress, the progressive downregulation or inhibition of metabolic processes, or nonstomatal effects, lead to decreased RuBP regeneration and inhibition of A. Thus, the relative importance of stomatal vs. nonstomatal limitations remain unclear and the discussion has become polarized (Lawlor, 2002). This issue is further complicated by TL in this experiment because leaf gas exchange processes are affected by TL, and here TL is in turn affected by the degree of drought stress.

Clearly, measurement of A and g, at least at present, is far too cumbersome and slow to be utilized directly as an indicator of the degree of drought stress in an automated irrigation management strategy. However, using A and g as proxies for the degree of drought stress, our results indicate that either (Tc – Ta) or the combination of (Tc – Ta) and VPD should provide a better estimation of the degree of drought stress than Tc alone (Table 2, Fig. 5Go–7). Interestingly, and as noted previously, quite similar approaches using either (Tc – Ta) or the combination of (Tc – Ta) and VPD have been used in the past for irrigation scheduling with the SDD index (Idso et al., 1977; Jackson et al., 1977) and the CWSI (Idso et al., 1981a; Jackson et al., 1981), respectively. Also as previously noted, the SSD index assumes that if the (Tc – Ta) differential was negative, the plants were well watered. Heermann and Duke (1978) found that average (Tc – Ta) > 1.5°C was correlated with grain yield reduction. Our data (Fig. 5) indicate that the onset of a response to plant water deficit (e.g., reductions in A or g) can be detected even at small negative (Tc – Ta) differentials below zero. Clearly, further research is needed to elucidate the relationships between A, g, (Tc – Ta), and final yield.

While it is generally agreed that g usually decreases as VPD increases (Massman and Kaufmann, 1991; Oren et al., 1999) the precise plant sensing mechanism for this effect is unknown. In some studies, increased transpiration rate and associated changes in leaf water potential rather than VPD per se is cited as the cue for stomatal closure (Mott and Parkhurst, 1991; Monteith, 1995; Oren et al., 1999), while other studies (Bunce, 1997, 1998) point to an abscisic acid mediated response. Considering the complex feedback and feed forward mechanisms associated with stomatal regulation, Jones (1998) concluded that it is difficult to decide whether stomata are controlling gas exchange or vice versa. In any event, our results (Table 2; Fig. 6, 7) suggest that the combination of (Tc – Ta) and VPD as formally described by the CWSI should provide even greater precision in detecting and quantifying the degree of plant water deficit than either TL or (Tc – Ta) differential. Indeed, the CWSI has been successfully used to schedule irrigation in several studies (Howell et al., 1984; Reginato 1983; Jackson, 1991; Irmak et al., 2000). The CWSI has also been shown to be correlated with both yield (Walker and Hatfield, 1983; Smith et al., 1985) and net photosynthesis (Idso et al., 1982; O'Toole et al., 1984).

In many crop species, drought stress impacts on final yield depend on the duration and severity of drought stress as well as the particular growth stage at which the stress occurs. Typically, reproductive growth is more sensitive to plant water deficit than vegetative growth. With an adequate quantification of the degree of drought stress, it should be possible to develop deficit irrigation strategies that control the degree of drought stress based on crop developmental stage, with less severe plant water deficit during sensitive reproductive phases of development for example. It would appear that this type of approach should have the potential for increasing water use efficiency.


   SUMMARY
TOP
 ABSTRACT
 INTRODUCTION
 MATERIALS AND METHODS
 NOTES
 RESULTS
 DISCUSSION
 SUMMARY
REFERENCES
 
In these experiments, we utilized diurnal leaf level measurements of A and g as proxies for the degree of drought stress in cotton subsurface drip irrigated according to the stress-time index method of irrigation scheduling. We found that TL, and by extension Tc, was not a particularly relevant predictor of the degree of drought stress in cotton, while the (TL – Ta) differential and the combination of (TL – Ta) and VPDL provided greater predictive utility than TL alone. Our results indicate that g is more sensitive than A to mild drought stress, while A is severely reduced as plant water deficit becomes more acute at g values below {approx}0.4 mol m–2 s–1. We conclude that greater accuracy in the quantification of the degree of drought stress should improve the economic efficiency of water use, particularly in situations where deficit irrigation is practiced.


   NOTES
TOP
 ABSTRACT
 INTRODUCTION
 MATERIALS AND METHODS
 NOTES
RESULTS
 DISCUSSION
 SUMMARY
 REFERENCES
 
1 Mention of this or other proprietary products is for the convenience of the readers only, and does not constitute endorsement or preferential treatment of these products by USDA-ARS. Back


   REFERENCES
TOP
 ABSTRACT
 INTRODUCTION
 MATERIALS AND METHODS
 NOTES
 RESULTS
 DISCUSSION
 SUMMARY
 REFERENCES
 




This article has been cited by other articles:


Home page
 Agron. J.Home page
J. T. Baker, S. Van Pelt, D. C. Gitz, P. Payton, R. J. Lascano, and B. McMichael
Canopy Gas Exchange Measurements of Cotton in an Open System
Agron. J., January 8, 2009; 101(1): 52 - 59.
[Abstract] [Full Text] [PDF]

This Article
Right arrow Abstract Freely available
Right arrow Figures Only
Right arrow Full Text (PDF) Free
Right arrow Alert me when this article is cited
Right arrow Alert me if a correction is posted
Services
Right arrow Similar articles in this journal
Right arrow Alert me to new issues of the journal
Right arrow Download to citation manager
Right arrow reprints & permissions
Citing Articles
Right arrow Citing Articles via HighWire
Right arrow Citing Articles via Google Scholar
Google Scholar
Right arrow Articles by Baker, J. T.
Right arrow Articles by Upchurch, D. R.
Right arrow Search for Related Content
PubMed
Right arrow Articles by Baker, J. T.
Right arrow Articles by Upchurch, D. R.
Agricola
Right arrow Articles by Baker, J. T.
Right arrow Articles by Upchurch, D. R.
Related Collections
Right arrow Agroclimatology
Right arrow Water Stress

HOME HELP FEEDBACK SUBSCRIPTIONS ARCHIVE SEARCH TABLE OF CONTENTS
The SCI Journals Crop Science Vadose Zone Journal
Journal of Natural Resources
and Life Sciences Education		 Soil Science Society of America Journal
Journal of Plant Registrations Journal of
Environmental Quality		 The Plant Genome