WINTER WHEAT CROPLAND GRAIN PROTEIN CONTENT EVALUATION THROUGH REMOTE SENSING

文献类型： 外文期刊

第一作者： Song, Xiaoyu

作者： Song, Xiaoyu;Yang, Guijun;Feng, Haikuan;Wang, Jihua

作者机构：

关键词： Winter wheat;Grain protein content (GPC);Remote sensing;Multi linear regression (MLR) analysis

期刊名称：INTELLIGENT AUTOMATION AND SOFT COMPUTING （ 影响因子：1.647； 五年影响因子：1.469 ）

ISSN： 1079-8587

年卷期： 2014 年 20 卷 4 期

页码：

收录情况： SCI

摘要： Grain protein content (GPC) is generally not uniform across cropland due to changes in landscape position, nutrient availability, soil chemical, physical properties, cropping history and soil type. It is necessary to determine the winter wheat GPC quality for different croplands in a collecting area in order to optimize the grading process. GPC quality evaluation refers not only the GPC value, but also the GPC uniformity across a cropland. The objective of this study was to develop a method to evaluate the GPC quality for different croplands through remote sensing technique. Three Landsat5 TM images were acquired on March 27, April 28 and May 30, 2008, corresponding to erecting stage, booting stage and grain filling stage of wheat. The wheat GPC was determined after harvest. Then multi linear regression (MLR) analysis with the enter method was calculated using the TM spectral parameters and the measured GPC data. The GPC MLR model was established based on multi-temporal spectral parameters. The accuracy of the model was R-2 > 0.521, RMSE < 0.66%. The GPC mean value and standard deviation value for each cropland was calculated based on the ancillary cropland boundary data and the grain protein monitoring map. Winter wheat filed GPC quality was evaluated by the GPC mean value and GPC uniformity parameter - coefficients of variation (CV). The evaluation result indicated that the super or good level winter wheat croplands mainly lie in Tongzhou, Daxing and Shunyi County, while the middle or low GPC level croplands are mainly distributed on the Fangshang county. This study indicates that the remote sensing technique provides valuable opportunities to monitor and evaluate grain protein quality.

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