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Winter Wheat Cropland Grain Protein Content Evaluation through Remote Sensing



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 R2003E0.521, RMSE00A0003C00A00.66%. 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.



Total Pages: 11
Pages: 599-609


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Volume: 20
Issue: 4
Year: 2014

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ISSN PRINT: 1079-8587
ISSN ONLINE: 2326-005X
DOI PREFIX: 10.31209
10.1080/10798587 with T&F
IMPACT FACTOR: 0.652 (2017/2018)

SJR: "The two years line is equivalent to journal impact factor ™ (Thomson Reuters) metric."

Journal: 1995-Present


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