Diagnosis alfalfa salt stress based on UAV multispectral image texture and vegetation index

Abstract

Abstract Aims This study aimed to explore the effects of increasing image texture features and removing soil background on the alfalfa salt stress diagnosis accuracy. Methods This study extracted spectral reflectance to construct 15 vegetation indexes, and used gray level co-occurrence matrix to calculate eight image texture features. The Canny edge detection algorithm was used to remove the soil background, and set T1 (vegetation index non-removed soil background), T2 (vegetation index + image texture features non-removed soil background), T3 (vegetation index removed soil background), T4 (vegetation index + image texture features removed soil background), as independent variables to construct salt stress diagnosis model based on the support vector regression algorithm, and determined the best salt stress diagnosis model. Results Compared with the T1, the modeling and validation accuracies of salt stress diagnosis model constructed based on the T2 increased by 13.39% and 13.36%, respectively, and those of salt stress diagnosis model constructed based on the T3 increased by 6.30% and 5.33%. The salt stress diagnosis accuracy constructed based on T4 was the highest, with the modeling set R 2 , RMSE, and RPD of 0.675, 0.2143, and 1.7735, respectively, and the validation set R 2 , RMSE, and RPD of 0.652, 0.2349, and 15749, respectively. The modeling and validation accuracies of the salt stress diagnosis model constructed based on crop salt stress index (CSSI) reached more than 0.564 and 0.549, respectively, which can be used as a new indicator for diagnosing salt stress. Conclusions Both increasing image texture features and removing soil background can significantly improve the accuracy of alfalfa salt stress diagnosis.

Plant phenotyping relevance

UAVマルチスペクトル画像から植生指数・テクスチャ特徴を抽出し、土壌背景除去とモデル検証を通じてアルファルファの塩ストレス状態を診断する方法が研究の中心である。

Code and data availability

The paper reports UAV multispectral imagery, soil salinity, and alfalfa biomass measurements used for salt stress diagnosis, but provides no public repository, dataset, image, or code deposit. The Data Availability statement only offers further details from the corresponding author upon reasonable request, so any paper

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