Douglas J. Hunsaker

Free-air CO2 enrichment and soil nitrogen effects on energy balance and evapotranspiration of wheat

In order to determine the likely effects of the increasing atmospheric CO2 concentration on future evapotranspiration, ET, plots of field-grown wheat were exposed to concentrations of 550 µmol/mol CO2 (or 200 µmol/mol above current ambient levels of about 360 µmol/mol) using a free-air CO2 enrichment (FACE) facility. Data were collected for four growing seasons at ample water and fertilizer (high N) and for two seasons when soil nitrogen was limited (low N). Measurements were made of net radiation, Rn; soil heat flux; air and soil temperatures; canopy temperature, Ts; and wind speed. Sensible heat flux was calculated from the wind and temperature measurements. ET, that is, latent heat flux, was determined as a residual in the energy balance. The FACE treatment increased daytime Ts about 0.6° and 1.1°C at high and low N, respectively. Daily total Rn was reduced by 1.3% at both levels of N. Daily ET was consistently lower in the FACE plots, by about 6.7% and 19.5% for high and low N, respectively.

Estimating cotton evapotranspiration crop coefficients with a multispectral vegetation index

Crop coefficients are a widely used and universally accepted method for estimating the crop evapotranspiration (ETc) component in irrigation scheduling programs. However, uncertainties of generalized basal crop coefficient (Kcb) curves can contribute to ETc estimates that are substantially different from actual ETc. Limited research with corn has shown improvements to irrigation scheduling due to better water-use estimation and more appropriate timing of irrigations when Kcb estimates derived from remotely sensed multispectral vegetation indices (VIs) were incorporated into irrigation-scheduling algorithms. The purpose of this article was to develop and evaluate a Kcb estimation model based on observations of the normalized difference vegetation index (NDVI) for a full-season cotton grown in the desert southwestern USA. The Kcb data used in developing the relationship with NDVI were derived from back-calculations of the FAO-56 dual crop coefficient procedures using field data obtained during two cotton experiments conducted during 1990 and 1991 at a site in central Arizona. The estimation model consisted of two regression relations: a linear function of Kcb versus NDVI (r2=0.97, n=68) used to estimate Kcb from early vegetative growth to effective full cover, and a multiple regression of Kcb as a function of NDVI and cumulative growing-degree-days (GDD) (r2=0.82, n=64) used to estimate Kcb after effective full cover was attained. The NDVI for cotton at effective full cover was ~0.80; this value was used to mark the point at which the model transferred from the linear to the multiple regression function. An initial evaluation of the performance of the model was made by incorporating Kcb estimates, based on NDVI measurements and the developed regression functions, within the FAO-56 dual procedures and comparing the estimated ETc with field observations from two cotton plots collected during an experiment in central Arizona in 1998. Preliminary results indicate that the ETc based on the NDVI-Kcb model provided close estimates of actual ETc.

COTTON IRRIGATION SCHEDULING USING REMOTELY SENSED AND FAO-56 BASAL CROP COEFFICIENTS

Multispectral vegetation indices calculated from canopy reflectance measurements have been used to simulate real-time basal crop coefficients (Kcb), which have been validated to improve evapotranspiration (ETc) estimation for several crops. In this article, an application of the approach was evaluated for cotton using remote sensing observations of the normalized difference vegetation index (NDVI) to estimate Kcb as a function of NDVI. The dual crop coefficient procedures of FAO Paper 56 (FAO-56) were used to calculate ETc and determine irrigation scheduling using Kcb estimates from remote sensing (NDVI treatment) as well as from time-based Kcb curves (FAO treatment), which were developed locally for standard crop conditions using FAO-56 procedures. Two cotton experiments, conducted in 2002 and 2003 in central Arizona, included sub-treatments of three levels of plant density and two levels of nitrogen management to impose a wide range of crop development and water use. The NDVI-Kcb relationships used for 2002, developed from previous data for a different cotton cultivar, row orientation, and soil type, substantially underestimated ETc, resulting in significantly less irrigation water applied and lower lint yields for NDVI compared to the FAO treatment. The 2002 data were used to recalibrate the NDVI-Kcb relationships, which were then used for the NDVI treatments in 2003. The FAO Kcb curve used in 2002 described ETc and irrigation scheduling reasonably well for sparse plots, but consistently underestimated water use and soil water depletion for the higher plant densities during the first half of the season. Consequently, an adjusted FAO Kcb curve, based on 2002 results, was employed for the FAO treatment in 2003. For the 2003 experiment, estimated cotton ETc for the NDVI treatment resulted in a mean absolute error of 9% compared to 10% for the FAO treatment, where the difference was not significant between treatments. However, the NDVI-Kcb relations used in 2003 greatly improved estimates for ETc compared to the previous year, where the mean absolute error for the NDVI treatment in 2002 was 22%. Predicted ETc using the FAO Kcb curve of 2003 for typical planting density and high nitrogen conditions resulted in a mean absolute error of 10% compared to 15% in 2002. Final lint yields for 2003 were not significantly different between the two Kcb methods. Although additional research is needed to validate remote sensing Kcb estimation for other conditions than those in these experiments, this study did not show significant advantages for the NDVI approach over a carefully derived single FAO Kcb application. However, the NDVI approach has the potential to further extend our present crop coefficient estimation capabilities when weather, plant density, or other factors cause cotton canopy development and water use patterns to depart from typical conditions.

Carbon Dioxide Enrichment and Irrigation Effects on Wheat Evapotranspiration and Water Use Efficiency

Evapotranspiration (ET) and water use efficiency were evaluated for two spring wheat crops, grown in a drip-irrigated field under ambient (about 370 mmol mol–1) and enriched (550 mmol mol–1) carbon dioxide (CO2) concentrations during the 1992-1993, and 1993-1994, Free-Air CO2 Enrichment (FACE) experiments in central Arizona. CO2-enriched (FACE) and ambient CO2 (CONTROL) treatments were replicated in four circular plots, 25 m in diameter, and well-watered (WET) and water-stressed (DRY) irrigation treatments were imposed on one-half of each plot. Wheat ET, measured over discrete time periods of several days by a soil water balance, was significantly higher for WET than DRY irrigation treatments after the first week in March in both years. Differences in ET between CO2 treatments during the season were generally small, although there was a consistent trend towards decreased ET for the FACE over CONTROL under the well-watered irrigation regime.

Acclimation response of spring wheat in a free-air CO2 enrichment (FACE) atmosphere with variable soil nitrogen regimes. 2. Net assimilation and stomatal conductance of leaves.

Atmospheric CO2 concentration continues to rise. It is important, therefore, to determine what acclimatory changes will occur within the photosynthetic apparatus of wheat (Triticum aestivum L. cv. Yecora Rojo) grown in a future high-CO2 world at ample and limited soil N contents. Wheat was grown in an open field exposed to the CO2 concentration of ambient air [370 μmol (CO2) mol−1; Control] and air enriched to ∼200 μmol (CO2) mol−1 above ambient using a Free-Air CO2 Enrichment (FACE) apparatus (main plot). A High (35 g m−2) or Low (7 and 1.5 g m−2 for 1996 and 1997, respectfully) level of N was applied to each half of the main CO2 treatment plots (split-plot). Under High-N, FACE reduced stomatal conductance (gs) by 30% at mid-morning (2 h prior to solar noon), 36% at midday (solar noon) and 27% at mid-afternoon (2.5 h after solar noon), whereas under Low-N, gs was reduced by as much as 31% at mid-morning, 44% at midday and 28% at mid-afternoon compared with Control. But, no significant CO2 × N interaction effects occurred. Across seasons and growth stages, daily accumulation of carbon (A′) was 27% greater in FACE than Control. High-N increased A′ by 18% compared with Low-N. In contrast to results for gs, however, significant CO2 × N interaction effects occurred because FACE increased A′ by 30% at High-N, but by only 23% at Low-N. FACE enhanced the seasonal accumulation of carbon (A′′) by 29% during 1996 (moderate N-stress), but by only 21% during 1997 (severe N-stress). These results support the premise that in a future high-CO2 world an acclimatory (down-regulation) response in the photosynthetic apparatus of field-grown wheat is anticipated. They also demonstrate, however, that the stimulatory effect of a rise in atmospheric CO2 on carbon gain in wheat can be maintained if nutrients such as nitrogen are in ample supply.

Wheat Irrigation Management Using Multispectral Crop Coefficients: I. Crop Evapotranspiration Prediction

A method widely used for irrigation management determines crop evapotranspiration (ETc) from reference evapotranspiration (ETo) calculations and estimated crop coefficients. However, standard time-based crop coefficients may fail to represent the actual crop water use, for example, when deviations in weather or agronomic constraints appreciably change crop development patterns from typical conditions. In this study, the FAO-56 dual crop coefficient procedures were applied during experiments with wheat to calculate the estimated ETc for irrigation scheduling. The objective of this research was to determine whether basal crop coefficients (Kcb) determined from a normalized difference vegetation index (NDVI treatment) improve the prediction of ETc over a standard application with a locally developed time-based Kcb curve (FAO treatment). The experiments conducted for two seasons in central Arizona included subtreatments, equally replicated within the NDVI and FAO treatments, of three plant densities (typical, dense, and sparse) and two nitrogen levels (high and low) to provide a range of crop development and water use conditions. The effects of plant density and N level resulted in significant differences in measured seasonal ETc. Large variations that occurred in the observed Kcb and ETc trends between subtreatments were better correlated with the NDVI than the FAO treatment. The mean absolute percent difference for predicted ETc was significantly smaller for NDVI than FAO during both seasons. The treatment difference was 5% for the first season, but 10% for the second season when an unexpected early decline in ETc and Kcb was effectively predicted by the NDVI treatment but not by the FAO treatment. NDVI appears to be a robust approach for Kcb estimation of wheat, able to reliably predict actual ETc for both typical and abnormal water use conditions.

Acclimation response of spring wheat in a free-air CO2 enrichment (FACE) atmosphere with variable soil nitrogen regimes. 3. Canopy architecture and gas exchange.

The response of whole-canopy net CO2 exchange rate (CER) and canopy architecture to CO2 enrichment and N stress during 1996 and 1997 for open-field-grown wheat ecosystem (Triticum aestivum L. cv. Yecora Rojo) are described. Every Control (C) and FACE (F) CO2 treatment (defined as ambient and ambient +200 μmol mol−1, respectively) contained a Low- and High-N treatment. Low-N treatments constituted initial soil content amended with supplemental nitrogen applied at a rate of 70 kg N ha−1 (1996) and 15 kg N ha−1 (1997), whereas High-N treatments were supplemented with 350 kg N ha−1 (1996 and 1997). Elevated CO2 enhanced season-long carbon accumulation by 8% and 16% under Low-N and High-N, respectively. N-stress reduced season-long carbon accumulation 14% under ambient CO2, but by as much as 22% under CO2 enrichment. Averaging both years, green plant area index (GPAI) peaked approximately 76 days after planting at 7.13 for FH, 6.00 for CH, 3.89 for FL, and 3.89 for CL treatments. Leaf tip angle distribution (LTA) indicated that Low-N canopies were more erectophile than those of High-N canopies: 48° for FH, 52° for CH, and 58° for both FL and CL treatments. Temporal trends in canopy greenness indicated a decrease in leaf chlorophyll content from the flag to flag-2 leaves of 25% for FH, 28% for CH, 17% for CL, and 33% for FL during 1997. These results indicate that significant modifications of canopy architecture occurs in response to both CO2 and N-stress. Optimization of canopy architecture may serve as a mechanism to diminish CO2 and N-stress effects on CER.

Acclimation response of spring wheat in a free-air CO2 enrichment (FACE) atmosphere with variable soil nitrogen regimes. 1. Leaf position and phenology determine acclimation response

We have examined the photosynthetic acclimation of wheat leaves grown at an elevated CO2 concentration, and ample and limiting N supplies, within a field experiment using free-air CO2 enrichment (FACE). To understand how leaf age and developmental stage affected any acclimation response, measurements were made on a vertical profile of leaves every week from tillering until maturity. The response of assimilation (A) to internal CO2 concentration (Ci) was used to estimate the in vivo carboxylation capacity (Vcmax) and maximum rate of ribulose-1,5-bisphosphate limited photosynthesis (Asat). The total activity of ribulose-1,5-bisphosphate carboxylase/oxygenase (Rubisco), and leaf content of Rubisco and the Light Harvesting Chlorophyll a/b protein associated with Photosystem II (LHC II), were determined. Elevated CO2 did not alter Vcmax in the flag leaf at either low or high N. In the older shaded leaves lower in the canopy, acclimatory decline in Vcmax and Asat was observed, and was found to correlate with reduced Rubisco activity and content. The dependency of acclimation on N supply was different at each developmental stage. With adequate N supply, acclimation to elevated CO2 was also accompanied by an increased LHC II/Rubisco ratio. At low N supply, contents of Rubisco and LHC II were reduced in all leaves, although an increased LHC II/Rubisco ratio under elevated CO2 was still observed. These results underscore the importance of leaf position, leaf age and crop developmental stage in understanding the acclimation of photosynthesis to elevated CO2 and nutrient stress.

REMOTE SENSING OF COTTON NITROGEN STATUS USING THE CANOPY CHLOROPHYLL CONTENT INDEX (CCCI)

Various remote sensing indices have been used to infer crop nitrogen (N) status for field-scale nutrient management. However, such indices may indicate erroneous N status if there is a decrease in crop canopy density influenced by other factors, such as water stress. The Canopy Chlorophyll Content Index (CCCI) is a two-dimensional remote sensing index that has been proposed for inferring cotton N status. The CCCI uses reflectances in the near-infrared (NIR) and red spectral regions to account for seasonal changes in canopy density, while reflectances in the NIR and far-red regions are used to detect relative changes in canopy chlorophyll, a surrogate for N content. The primary objective of this study was to evaluate the CCCI and several other remote sensing indices for detecting the N status for cotton during the growing season. A secondary objective was to evaluate the ability of the indices to appropriately detect N in the presence of variable water status. Remote sensing data were collected during the 1998 (day of year [DOY] 114 to 310) and 1999 (DOY 106 to 316) cotton seasons in Arizona, in which treatments of optimal and low levels of N and water were imposed. In the 1998 season, water treatments were not imposed until late in the season (DOY 261), well after full cover. Following an early season N application in 1998 for the optimal (DOY 154) but not the low N treatment, the CCCI detected significant differences in crop N status between the N treatments starting on DOY 173, when canopy cover was about 30%. A common vegetation index, the ratio of NIR to red (RVI), also detected significant separation between N treatments, but RVI detection occurred 16 days after the CCCI response. After an equal amount of N was applied to both optimal and low N treatments on DOY 190 in 1998, the CCCI indicated comparable N status for the N treatments on DOY 198, a trend not detected by RVI. In the 1999 season, both N and water treatments were imposed early and frequently during the season. The N status was poorly described by both the CCCI and RVI under partial canopy conditions when water status differed among treatments. However, once full canopy was obtained in 1999, the CCCI provided reliable N status information regardless of water status. At full cotton cover, the CCCI was significantly correlated with measured parameters of N status, including petiole NO 3 -N (r = 0.74), SPAD chlorophyll (r = 0.65), and total leaf N contents (r = 0.86). For well-watered cotton, the CCCI shows promise as a useful indicator of cotton N status after the canopy reaches about 30% cover. However, further study is needed to develop the CCCI as a robust N detection tool independent of water stress.

Field-Based High-Throughput Plant Phenotyping Reveals the Temporal Patterns of Quantitative Trait Loci Associated with Stress-Responsive Traits in Cotton

The application of high-throughput plant phenotyping (HTPP) to continuously study plant populations under relevant growing conditions creates the possibility to more efficiently dissect the genetic basis of dynamic adaptive traits. Toward this end, we employed a field-based HTPP system that deployed sets of sensors to simultaneously measure canopy temperature, reflectance, and height on a cotton (Gossypium hirsutum L.) recombinant inbred line mapping population. The evaluation trials were conducted under well-watered and water-limited conditions in a replicated field experiment at a hot, arid location in central Arizona, with trait measurements taken at different times on multiple days across 2010–2012. Canopy temperature, normalized difference vegetation index (NDVI), height, and leaf area index (LAI) displayed moderate-to-high broad-sense heritabilities, as well as varied interactions among genotypes with water regime and time of day. Distinct temporal patterns of quantitative trait loci (QTL) expression were mostly observed for canopy temperature and NDVI, and varied across plant developmental stages. In addition, the strength of correlation between HTPP canopy traits and agronomic traits, such as lint yield, displayed a time-dependent relationship. We also found that the genomic position of some QTL controlling HTPP canopy traits were shared with those of QTL identified for agronomic and physiological traits. This work demonstrates the novel use of a field-based HTPP system to study the genetic basis of stress-adaptive traits in cotton, and these results have the potential to facilitate the development of stress-resilient cotton cultivars.