title: [The prediction of barley grain protein content based on hyperspectral data].
abstract: The prediction of crop grain protein by hyperspectral data has the nondestructive and quick advantages. At present, there are only a few reports about the prediction of barley grain protein by remote sensing. The present research focuses on the malt barley of Northeast China. Firstly, we analyzed the sensitive band area, compared many vegetation indexes related with the plant nitrogen. According to the mechanism of nitrogen transfer, the authors built the prediction model based on the hyperspectral vegetation indexes. Finally, we validated the results. It can meet the standard. The outcome shows that (1) the sensitive band region of barley plant nitrogen is 550-590 nm and 670-710 nm. (2) GRVI was significantly correlated with plant nitrogen. The relationship between GRVI and barley plant nitrogen had a coefficient of determination of R2 = 0.665 1. The results indicated that the prediction of barley grain protein by hyperspectral data is feasible. This research will be a strong scientific support for barley purchase.
authors.affiliation: School of Geography and Remote Sensing Science, Beijing Normal University, State Key Laboratory of Remote Sensing Science, Beijing 100875, China. guzhihong@gmail.com
authors.forename: Zhi-hong
authors.initials: ZH
authors.lastname: Gu
mesh_terms: D002523:Edible Grain; D001467:Hordeum; D008962:Models, Theoretical; D009584:Nitrogen; D010940:Plant Proteins
chemical_list: D010940:Plant Proteins; D009584:Nitrogen