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Digital image correlation (DIC) is a noncontact technique used to track full-field displacements on the surface of an object during mechanical testing. Optical DIC was originally developed in the 1980s [...]

Realizing the potential of agricultural genomics into practical applications requires quantitative predictions for complex traits and different genotypes and environmental conditions. The objective of this study was to develop and test a procedure for quantitative prediction of phenotypes as a function of environment and specific genetic loci in soybean [Glycine max (L.) Merrill]. We combined the ecophysiological model CROPGRO-Soybean with linear models that predict cultivar-specific parameters as functions of E loci. The procedure involved three steps: (i) a field experiment was conducted in Florida in 2001 to obtain phenotypic data for a set of near-isogenic lines (NILs) with known genotypes at six E loci; (ii) we used these data to estimate cultivar-specific parameters for CROPGRO-Soybean, minimizing root mean square error (RMSE) between observed and simulated values; (iii) these parameters were then expressed as linear functions of the (known) E loci. CROPGRO-Soybean predicted various phenological stages for the same NILs grown in 2002 in Florida with a RMSE of about 5 d using the E loci--derived parameters. A second evaluation of the approach used phenotypic data from cultivar trials conducted in Illinois. Cultivars were genotyped at the E loci using microsatellites. The model predicted time to maturity in the Illinois variety trials with RMSE around 7.5 d; it also explained 75% of the time-to-maturity variance and 54% of the yield variance. Our results suggest that gene-based approaches can effectively use agricultural genomics data for cultivar performance prediction. This technology may have multiple uses in plant breeding., RECENT ADVANCES in agricultural genomics promise a new era of yield maximization through genetic improvement and optimized crop management (Somerville and Somerville, 1999; Huang et al., 2002). The realization of [...]

Two equations for estimating grass reference evapotranspiration (E[T.sub.0]) were derived using the Food and Agriculture Organization Penman--Monteith (FAO56-PM) method as an index. The first equation, solar radiation ([R.sub.s]) based, estimates E[T.sub.0] from incoming [R.sub.s] and maximum and minimum air temperature, and the second equation, net radiation ([R.sub.n]) based, uses [R.sub.n] and maximum and minimum air temperature. The equations were derived using 15 years (1980-1994) of daily E[T.sub.0] values estimated from the FAO56-PM method using the measured and carefully screened weather data from near Gainesville, Florida. The performance of the derived equations was evaluated for 6 validation years (1995-2000), including dry and wet years, for the same site and for other humid locations in the Southeast United States. Comparisons of the performance of the derived equations with the other commonly used methods indicated that they estimate E[T.sub.0] as good or better than those other E[T.sub.0] methods. The [R.sub.s]- and [R.sub.n]-based equations resulted in the lowest 6 year average standard error of estimate (SEE) of daily E[T.sub.0] (0.44 and 0.41 mm [day.sup.-1], respectively). Both equations performed quite well for estimating peak month E[T.sub.0] and had the lowest 6 year average daily SEE for the peak month E[T.sub.0] (0.24 mm [day.sup.-1] for both equations). Estimates for annual total E[T.sub.0] were very close to those obtained from the FAO56-PM method. The 6 year average ratio of E[T.sub.0 method] to E[T.sub.0 FAO56-PM] were 1.05 and 1.03 for the [R.sub.s]- and [R.sub.n]-based equations, respectively. The derived equations were further evaluated in other humid locations in the Southeast United States, including two locations in coastal regions in Florida, one location in Georgia, and another location in Alabama. The comparisons showed that both equations are likely to provide good estimates of E[T.sub.0] in humid locations of the Southeast United States. When the required input variables are considered, the Priestley--Taylor (PT) method was the closest method to the second derived equation ([R.sub.n] based). Therefore, it was necessary to evaluate how the PT method would perform compared to the [R.sub.n]-based equation relative to the FAO56-PM method after it is calibrated locally. Although the performance of the PT method improved slightly after the calibration, its performances for estimating daily and peak month E[T.sub.0] remained poorer than the [R.sub.n]-based equation in all cases. Considering the limitations associated with the availability and reliability of the climatological data, especially in developing countries, the derived equations presented in this study are suggested as practical methods for estimating E[T.sub.0] if the standard FAO56-PM equation cannot be used because of the above-mentioned limitations. These equations are recommended over the other commonly used simplified temperature and radiation-based methods evaluated in this study for humid climates in the Southeast United States. CE Database subject headings: Radiation; Evapotranspiration; Humid areas; Predictions.

Net radiation ([R.sub.n]) is a key variable for computing reference evapotranspiration and is a driving force in many other physical and biological processes. The procedures outlined in the Food and Agriculture Organization Irrigation and Drainage Paper No. 56 [FAO56 (reported by Allen et al. in 1998)] for predicting daily [R.sub.n] have been widely used. However, when the paucity of detailed climatological data in the United States and around the world is considered, it appears that there is a need for methods that can predict daily [R.sub.n] with fewer input and computation. The objective of this study was to develop two alternative equations to reduce the input and computation intensity of the FAO56-[R.sub.n] procedures to predict daily [R.sub.n] and evaluate the performance of these equations in the humid regions of the southeast and two arid regions in the United States. Two equations were developed. The first equation [measured-[R.sub.s]-based ([R.sub.s-M])] requires measured maximum and minimum air temperatures ([T.sub.max] and [T.sub.min]), measured solar radiation ([R.sub.s]), and inverse relative distance from Earth to sun ([d.sub.r]). The second equation [predicted-[R.sub.s]-based ([R.sub.s-P])] requires [T.sub.max], [T.sub.min], mean relative humidity (R[H.sub.mean]), and predicted [R.sub.s]. The performance of both equations was evaluated in different locations including humid and arid, and coastal and inland regions (Gainesville, Fla.; Miami, Fla.; Tampa, Fla.; Tifton, Ga.; Watkinsville, Ga.; Mobile, Ala.; Logan, Utah; and Bushland, Tex.) in the United States. The daily [R.sub.n] values predicted by the [R.sub.s-M] equation were in close agreement with those obtained from the FAO56-[R.sub.n] in all locations and for all years evaluated. In general, the standard error of daily [R.sub.n] predictions (SEP) were relatively small, ranging from 0.35 to 0.73 MJ [m.sup.-2] [d.sup.-1] with coastal regions having lower SEP values. The coefficients of determination were high, ranging from 0.96 for Gainesville to 0.99 for Miami and Tampa. Similar results, with approximately 30% lower SEP values, were obtained when daily predictions were averaged over a three-day period. Comparisons of [R.sup.s-M] equation and FAO56-[R.sub.n] predictions with the measured [R.sub.n] values showed that the [R.sub.s-M] equations' predictions were as good or better than the FAO56-[R.sub.n] in most cases. The performance of the [R.sub.s-P] equation was quite good when compared with the measured [R.sub.n] in Gainesville, Watkinsville, Logan, and Bushland locations and provided similar or better daily [R.sub.n] predictions than the FAO56-[R.sub.n] procedures. The [R.sub.s-P] equation was able to explain at least 79% of the variability in [R.sub.n] predictions using only [T.sub.max], [T.sub.min], and RH data for all locations. It was concluded that both proposed equations are simple, reliable, and practical to predict daily [R.sub.n]. The significant advantage of the [R.sub.s-P] equation is that it can be used to predict daily [R.sub.n] with a reasonable precision when measured [R.sub.s] is not available. This is a significant improvement and contribution for engineers, agronomists, climatologists, and others when working with National Weather Service climatological datasets that only record [T.sub.max] and [T.sub.min] on a regular basis. CE Database subject headings: Radiation; Solar radiation; Evapotranspiration; Climatology; Predictions.

Evaporation pans [Class A pan, U.S. Weather Bureau (USWB)] are used extensively throughout the world to measure free-water evaporation and to estimate reference evapotranspiration (E[T.sub.0]). However, reliable estimation of E[T.sub.0] using pan evaporation ([E.sub.pan]) depends on the accurate determination of pan coefficients ([K.sub.pan]). Two equations developed by Frevert et al. in 1983 and Snyder in 1992 to estimate daily [K.sub.pan] values were evaluated using a 23-year climate dataset in a humid location (Gainesville, Florida). The E[T.sub.0] data, calculated using daily [K.sub.pan] values from these equations, were compared to the Food and Agricultural Organization (FAO)-Penman-Monteith (FAO56-PM) method. The two equations resulted in significantly different daily [K.sub.pan] values that produced different daily, monthly, and annual total E[T.sub.0] estimates. The E[T.sub.0] values calculated using Frevert et al.'s 1983 [K.sub.pan] coefficients were in very good agreement with the FAO56-PM method with daily, monthly, and annual mean percent errors (PE) of 5.8, 5.5, and 5.7%, respectively. The daily and annual mean-root-mean-square error (RMSE) of the estimates using this method were as low as 0.33 and 7.3 mm, respectively. Snyder's 1992 equation overestimated FAO56-PM E[T.sub.0] with daily, monthly, and annual mean PEs of 16.3, 13.8, and 13.2%, respectively. The daily and annual mean RMSEs for this method were higher (0.6 and 18 mm) than those obtained with Frevert et al.'s 1983 coefficients. The overestimations with Snyder's 1992 method were highest in the peak E[T.sub.0] month of May and in summer months. The performances of the [K.sub.pan] equations were also evaluated using randomly selected individual years (1979, 1988, 1990, and 1994) of climate data that had different climate characteristics than the 23-year average dataset. Frevert et al.'s 1983 coefficients resulted in good E[T.sub.0] estimates with lower annual mean PEs of 7.0, 0.1, 15.7, and 1.3% for 1979, 1988, 1990, and 1994, respectively, compared to Snyder's 1992 equation, which resulted in considerably higher PEs of 17.6, 9.1, 26.2, and 14.3% in 1979, 1988, 1990, and 1994, respectively. It was concluded that using Frevert et al.'s 1983 equation to calculate daily [K.sub.pan] provided more accurate E[T.sub.0] estimates, relative to the FAO56-PM method, from [E.sub.pan] data compared to Snyder's 1992 equation under the humid-region climatic conditions in this study. The method is very useful in computer calculations of E[T.sub.0] since it does not require 'table lookup' for [K.sub.pan] values. CE Database keywords: Evapotranspiration; Humidity; Evaporation.

Crop model testing in diverse environments is essential if modelers wish to make applications or extrapolations to those environments. A recent study demonstrated the effectiveness of optimization techniques for deriving cultivar coefficients for the CROPGRO-Soybean model from typical information provided by soybean performance tests. The objectives of this study were (i) to explore the extent to which cultivar coefficients developed by these approaches from crop performance tests are stable across different regions, (ii) to test the CROPGRO-Soybean model's ability to predict phenology and seed yield using cultivar coefficients that were developed in different regions, and (iii) to investigate whether 3 yr of crop performance data are adequate for developing stable genetic coefficients. A stepwise procedure was applied to derive cultivar coefficients for 10 common cultivars grown in different environments in Georgia and North Carolina. Regarding the transportability of cultivar coefficients across states, we found that the critical daylength coefficients were the most reliable cultivar traits. We found less stability of the cultivar traits that control genetic differences in seed yield potential. The estimated cultivar coefficients developed in Georgia enabled CROPGRO to predict yield and harvest maturity in North Carolina within 3.8% and 3.5 d, respectively, from the observed averages. Using the cultivar coefficients developed from North Carolina environments allowed us to simulate the actual mean yield and harvest maturity in Georgia to within 2.5% and 2.0 d. Furthermore, the model's ability to predict seed yield and maturity with cultivar coefficients developed from 3 yr of data was nearly as good as that derived from much larger data sets., DYNAMIC, PROCESS-LEVEL crop models are playing an increasing role in analyzing the interactions and contributions of environmental factors (such as temperature, daylength, and water supply), genetics, and physiology on seed [...]