Paper
2 October 2008 Prediction of winter wheat grain protein content by ASTER image
Author Affiliations +
Proceedings Volume 7104, Remote Sensing for Agriculture, Ecosystems, and Hydrology X; 71040Y (2008) https://doi.org/10.1117/12.800440
Event: SPIE Remote Sensing, 2008, Cardiff, Wales, United Kingdom
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.
© (2008) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Wenjiang Huang, Xiaoyu Song, Jihua Wang, Zhijie Wang, and Chunjiang Zhao "Prediction of winter wheat grain protein content by ASTER image", Proc. SPIE 7104, Remote Sensing for Agriculture, Ecosystems, and Hydrology X, 71040Y (2 October 2008); https://doi.org/10.1117/12.800440
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KEYWORDS
Proteins

Image quality

Nitrogen

Reflectivity

Remote sensing

Vegetation

Agriculture

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