Spectral vegetation indices as nondestructive tools for determining durum wheat yield

Remote sensing measurements may be a useful tool for quantifying crop devel opment and yield. Our objective was to study the potential of using spectra l reflectance indices to provide accurate and nondestructive estimates of p hysiological traits determining yield in durum wheat [Triticum turgidum L. subsp. durum (Desf.) Husn.]. Twenty-five genotypes were grown under rainfed and irrigated conditions in northeastern Spain. Reflectance from the veget ation at different growth stages was measured and the following spectral in dices calculated: simple ratio (SR), normalized difference vegetation index (NDVI), and photochemical reflectance index (PRI). Crop dry mass (CDM), le af area index (LAI), and green area index (GAI) were measured. All the indi ces and grain yield were greater under irrigated than rainfed conditions. L AI was the crop growth trait that most closely correlated with the spectral reflectance indices, with SR and PRI being the best and the worst indices, respectively, for the assessment of crop growth and yield. In rainfed cond itions, the spectral reflectance indices measured at any crop stage were po sitively correlated (P < 0.05) with LAI and yield. Under irrigation, correl ations were only significant during the second half of the grain filling. T he integration of either NDVI, SR, or PRI from heading to maturity explaine d 52, 59, and 39% of the variability in yield within genotypes in rainfed c onditions and 39, 28, and 26% under irrigation. Our results suggest that fo r durum wheat, the usefulness of the SR and NDVI for calculating green area and grain yield is limited to LAI values < 3.