Winter Wheat Quality Inspection and Regionalization Based on NIR Network and Remote Sensing
In the crown of the year, inspection of wheat quality fast and accurate is very important for all of grain enterprises, farmers and governments. Governments would like to construct a fair and equitable market for grain transaction with explicit grain quality standard. Farmers would like to sell their highquality grain at a high unit price for they have paid more attention and in-vestment. Enterprises also would like to purchase high-quality grain with higher unit price for it can bring more profits. At the same time, generating regionali-zation map of wheat quality accuracy in time is very important on the grain enterprises purchase strategy formulating and purchase region choosing. The authors collected 1200 NIR samples in 240 points (in other words, 5 samples per point ) in 12 counties in the main wheat producing areas in China (Hebei, Henan, Jiangsu and Shandong), then analysis these samples by both GIS spatial interpolation method and RS inverse method. In contrast, RS inverse method can simulate the quality parameter more accuracy than GIS spatial interpolation method. In conclusion, RS inverse method is preferable to generate quality regionalization map with NIR network samples.
Winter Wheat Quality Inspection Quality Regionalization NIR Network Remote Sensing
Xiaodong Yang WenJiang Huang Cunjun Li Xingang Xu Hao Yang
National Engineering Research Center for Information Technology in Agriculture,Beijing 100097, China
国际会议
南昌
英文
280-288
2010-10-22（万方平台首次上网日期，不代表论文的发表时间）