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Proceedings Paper

Prediction of winter wheat grain protein content by ASTER image
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Paper Abstract

The Advanced technology in space-borne determination of grain crude protein content (CP) by remote sensing can help optimize the strategies for buyers in aiding purchasing decisions, and help farmers to maximize the grain output by adjusting field nitrogen (N) fertilizer inputs. We performed field experiments to study the relationship between grain quality indicators and foliar nitrogen concentration (FNC). FNC at anthesis stage was significantly correlated with CP, while spectral vegetation index was significantly correlated to FNC. Based on the relationships among nitrogen reflectance index (NRI), FNC and CP, a model for CP prediction was developed. NRI was able to evaluate FNC with a higher coefficient of determination of R2=0.7302. The method developed in this study could contribute towards developing optimal procedures for evaluating wheat grain quality by ASTER image at anthesis stage. The RMSE was 0.893 % for ASTER image model, and the R2 was 0.7194. It is thus feasible to forecast grain quality by NRI derived from ASTER image.

Paper Details

Date Published: 2 October 2008
PDF: 8 pages
Proc. SPIE 7104, Remote Sensing for Agriculture, Ecosystems, and Hydrology X, 71040Y (2 October 2008); doi: 10.1117/12.800440
Show Author Affiliations
Wenjiang Huang, National Engineering Research Ctr. for Information Technology in Agriculture (China)
Xiaoyu Song, National Engineering Research Ctr. for Information Technology in Agriculture (China)
Jihua Wang, National Engineering Research Ctr. for Information Technology in Agriculture (China)
Zhijie Wang, Agriculture and Agri-Food Canada (Canada)
Chunjiang Zhao, National Engineering Research Ctr. for Information Technology in Agriculture (China)


Published in SPIE Proceedings Vol. 7104:
Remote Sensing for Agriculture, Ecosystems, and Hydrology X
Christopher M. U. Neale; Manfred Owe; Guido D'Urso, Editor(s)

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