中国农业科学 ›› 2022, Vol. 55 ›› Issue (6): 1127-1138.doi: 10.3864/j.issn.0578-1752.2022.06.006

• 耕作栽培·生理生化·农业信息技术 • 上一篇    下一篇

基于PLS的不同水氮条件下带状套作玉米产量预测

谭先明(),张佳伟,王仲林,谌俊旭,杨峰(),杨文钰   

  1. 四川农业大学农学院/农业部西南作物生理生态与耕作重点实验室/四川省作物带状复合种植工程技术研究中心,成都 611130
  • 收稿日期:2021-05-17 接受日期:2021-10-08 出版日期:2022-03-16 发布日期:2022-03-25
  • 通讯作者: 杨峰
  • 作者简介:谭先明,E-mail: 2019301094@stu.sicau.edu.cn
  • 基金资助:
    国家重点研发计划(2016YFD0300602);成都市科技项目(2020-YF09-00033-SN)

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

TAN XianMing(),ZHANG JiaWei,WANG ZhongLin,CHEN JunXu,YANG Feng(),YANG WenYu   

  1. College of Agronomy, Sichuan Agricultural University/Key Laboratory of Crop Ecophysiology and Farming System in Southwest, Ministry of Agriculture/Sichuan Engineering Research Center for Crop Strip Intercropping System, Chengdu 611130
  • Received:2021-05-17 Accepted:2021-10-08 Online:2022-03-16 Published:2022-03-25
  • Contact: Feng YANG

摘要:

【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参数,基于线性函数、二次函数和偏最小二乘(partial least squares,PLS)回归法构建产量估测模型。【结果】光合色素-产量预测模型中,冠层类胡萝卜素密度的PLS产量估测模型效果最佳(R2=0.882,RMSE=0.669 t·hm-2)。光谱参数-光合色素分析中,抽雄期叶绿素含量与波段自由组合指数rRVI(534,546)相关性最好(r=0.927)。其余光合色素参数与对应光谱指数相关性均在0.797以上。在高光谱参数-光合色素-产量估测模型中,由叶绿素含量、类胡萝卜素含量、冠层叶绿素密度、冠层类胡萝卜素密度为连接点,并以光谱指数rNDVI(534,546),rRVI(531,555),rNDVI(532,546),rNDVI(531,555)为自变量构建的PLS产量预测模型效果较好(R2=0.509,RMSE=1.352 t·hm-2)。【结论】利用色素参数作为光谱数据和产量连接的桥梁,通过PLS回归法建立的预测模型,能够在带状套作玉米中,对玉米产量实现较好估测,为带状套作玉米的田间管理和生长监测提供理论和技术参考。

关键词: 套作, 玉米, 高光谱, 色素参数, 产量, 偏最小二乘回归

Abstract:

【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.

Key words: relay intercropping, maize, hyperspectral, pigment parameters, yield, partial least squares regression