EVALUATING THE ASSOCIATION BETWEEN WHEAT YIELD AND REMOTELY-SENSED DATA

Analysis of data from aerial infrared photographs has recently been pr oposed as a supplemental tool to evaluate and improve the-efficiency o f the classical ANOVA for variety trial experiments. Our objective was to establish the relationships between spring wheat grain yield and r emotely-sensed data from a variety trial. Infrared photographs of a va riety trial were taken at six field-sites during the 1990 growing seas on. Significant (P less-than-or-equal-to 0.05) regressions between gra in yield and remotely-sensed data were detected at five out of six fie ld-sites. However, the low r2 values for remotely-sensed versus grain yield data suggested that much of the sample variability was not expla ined by these models. Spring wheats with high yields showed correspond ingly high estimates of a normalized difference vegetative index. Anal ysis of covariance using near infrared and red values as covariates, w as successfully used to reduce the variance of errors in grain yield. This method resulted in significant genotype effects detected at four of six field-sites compared to one with the classical analysis. Future research must develop more accurate methods of remotely-sensed analys is, including the need to take the infrared photographs at the correct growth stage and time with regard to environmental stresses.