基于PLS的不同水氮条件下带状套作玉米产量预测

目的]利用高光谱数据构建一种"高光谱参数-光合色素-产量"模型间接估测套作玉米产量,为带状套作玉米产量无损预测提供技术手段.方法]以不同年份、地点、品种、处理(氮肥、水分)的田间试验为基础,综合分析带状套作玉米各生育时期及全生育期光合色素参数与冠层高光谱参数和玉米产量的关系,明确玉米产量预测的最佳生育时期及光合色素...

Prediction of Maize Yield in Relay Strip Intercropping Under Different Water and Nitrogen Conditions Based on PLS

【Objective】 This study was designed mainly to provide technical means for non-destructive prediction of intercropped maize yield. The prime objective of our study was to construct a “hyperspectral parameter-photosynthetic pigment-yield” model from the hyperspectral data. 【Method】 Based on field trials of different years, locations, varieties, and treatments (nitrogen fertilizer, moisture), the relationships among photosynthetic pigment parameters, canopy hyperspectral parameters, and maize yield at each growth period and the entire growth period of intercropping maize were comprehensively analyzed. In addition, the optimal growth period and photosynthetic pigment parameters for maize yield prediction were also clarified. Then, the prediction model of yield was constructed based on linear function, quadratic function and partial least squares regression (PLS). 【Result】 Among the photosynthetic pigment-yield prediction models, the PLS prediction model of yield based on canopy carotenoid density had the best effect (R ²=0.882, RMSE=0.669 t·hm ^-2). In the spectral parameter-photosynthetic pigment analysis, the chlorophyll content during the tasseling stage had the best correlation with the band free combination index rRVI (534, 546) (r=0.927). The correlation between the other photosynthetic pigment parameters and the corresponding spectral index was above 0.797. In the hyperspectral parameter- photosynthetic pigment-yield prediction model, the chlorophyll content, carotenoid content, canopy chlorophyll density, and canopy carotenoid density were used as connection points, and using the spectral indices of rNDVI (534, 546), rRVI (531, 555), rNDVI (532, 546), and rNDVI (531, 555) as independent variables, the PLS output prediction model had better effect (R²=0.509, RMSE=1.352 t·hm ^-2). 【Conclusion】 In intercropping maize, the pigment parameters were used as a bridge between spectral data and yield. A prediction model was established through PLS regression, which could achieve a better estimation of maize yield and provide the theoretical and technical reference for field management and growth monitoring of maize in intercropping.