Monitoring spatial variance of winter wheat growth and grain quality under variable-rate fertilization conditions by remote sensing data

Remote sensing images acquired by satellite-based sensors have the potential for monitoring crop growth variation because they can provide an area global view for entire field within the crop growth season with scathelessness. This study aimed to use Quickbird image to evaluate the spatial variabilities of winter wheat growth and grain quality under different fertilization levels. The variable-rate fertilization experiment was carried out on National Experimental Station for Precision Agriculture during 2005-2006 the wheat growing season. The results indicated that the spectrum parameters of Quickbird image could reflect the spatial variabilities of winter wheat growth in different fertilization study areas. Meanwhile the spatial variabilities of wheat growth at early stage could reflect the variance of yield and grain quality. The wheat growth information at the booting stage had strong positive correlations with yield, and strong negative correlations with grain protein and wet gluten. The correlation coefficient between OSAVI (optimized soil adjusted vegetation index) and wheat yield was 0.536. It was -0.531 for GNDVI (greenness-normalized difference vegetation index) and grain protein content, and -0.535 for GNDVI and wet gluten, respectively. The study also indicated that diverse spectrum parameters had different sensitivities to the wheat growth spatial variance. So it is feasible to use remote sensing data to investigate the crop growth and quality spatial variance.