22 October 2010 Winter wheat growth and grain protein uniformity monitoring through remotely sensed data
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An uneven growing winter wheat will be slower to reach full ground cover and will be lead to uneven yield and quality for cropland. The traditional investigation of crop uniformity is mainly depends on manpower. Remote sensing technique is a potentially useful tool for monitoring the crop uniformity status for it can provide an area global view for entire field within the crop growth season with scathelessness. The objective of this study was to use remote sensing imagery to evaluate the crop growth uniformity, as well as the yield and grain quality variation for a winter wheat study area. One Quickbird image on winter wheat booting stage was collected and processed to monitoring the uniformity of wheat growth. The results indicated that the spectrum parameters of Quickbird image can reflect the spatial uniformity of winter wheat growth in the study areas. Meanwhile the spatial uniformity of wheat growth in early stage can reflect the uniformity of yield and grain quality. The wheat growth information at the booting stage has strong positive correlations with yield, and strong negative correlation with grain protein. The correlation coefficient between OSAVI (optimized soil adjusted vegetation index) and wheat yield was 0.536. It was -0.531 for GNDVI (Greeness-normalized difference vegetation index) and grain protein content. The study also indicated that diverse spectrum parameters had different sensitivity to the wheat growth spatial variance. So it is feasible to use remote sensing data to investigate the crop growth and quality spatial uniformity.
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Xiaoyu Song, Xiaoyu Song, Jihua Wang, Jihua Wang, Wenjiang Huang, Wenjiang Huang, } "Winter wheat growth and grain protein uniformity monitoring through remotely sensed data", Proc. SPIE 7824, Remote Sensing for Agriculture, Ecosystems, and Hydrology XII, 78242G (22 October 2010); doi: 10.1117/12.865162; https://doi.org/10.1117/12.865162

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