中国农业大学学报2024，Vol.29Issue(12)：12-22,11.DOI:10.11841/j.issn.1007-4333.2024.12.02
基于不同传感器的叶色信息对上海崇明区水稻氮营养诊断的研究
Study on the diagnosis of rice nitrogen nutrition in Chongming District,Shanghai based on leaf color information of different sensors
摘要
Abstract
In order to construct a non-destructive diagnostic model of leaf color for hybrid rice and conventional rice based on the critical nitrogen dilution curve and explore the appropriate nitrogen nutrition diagnosis method for different leaf color sensors in Chongming District,Shanghai.This study conducted field experiments with different nitrogen application rates(0～375 kg/hm2)by taking two hybrid rice varieties('Shenyou 26'and'Shenyou 28'),and two conventional rice varieties('Nanjing 46'and'Chongshang 2022')as materials in 2023.The experiments were carried out from the tillering stage to the heading stage to obtain the above-ground dry matters weight and nitrogen concentration of rice,calculate the agronomic parameters such as rice above-ground biomass and nitrogen uptake of rice,and calculate the critical nitrogen concentration and nitrogen nutrient index of different varieties at different stages with the critical nitrogen concentration curves of hybrid rice and conventional rice respectively.Simultaneously,the SPAD-502 Plus(Soil plant analysis development-502 Plus)and DJI Phantom 4 RTK drone which equipped with multi-spectral cameras were used to obtain rice leaf color information,and constructed a nitrogen nutrient diagnosis model based on the critical nitrogen concentration curve of SPAD index and multi-spectral canopy vegetation index.The results showed that:1)During the key growth stages of rice,the nitrogen nutrient index model were established by SPAD index,the optimal index for hybrid rice was Normalized SPAD Index for Top 2 Leaves(NSI2),while the optimal index for conventional rice was Normalized SPAD Index for Top 1 Leaves(NSI1),respectively.2)In the nitrogen nutrient index model established by Unmanned Aerial Vehicle(UAV)with multi-spectral camera,the optimal vegetation index for hybrid rice and conventional rice was Normalized Green Blue Difference Index(NGBDI).3)Estimated the NNI model using the SPAD index simulated by SPAD-502 Plus,the model can explain over 50％of the variables with accuracy.Estimated the NNI model using the NGBDI index simulated by multi-spectral canopy vegetation data,the model can explain over 56％of the variables with accuracy.In conclusion,both SPAD index and vegetation index can be used to establish nitrogen nutrition estimation model at booting stage,but the accuracy of using multi-spectral diagnostic model is stronger.关键词
氮营养诊断/多光谱数据/SPAD/植被指数Key words
nitrogen nutrient diagnosis/multi-spectral data/SPAD/vegetation index分类
农业科技引用本文复制引用
李月帅,姚银坤,郝祝霞,周圆,张卫峰,祝松蔚,宋轶辉,沈春晓..基于不同传感器的叶色信息对上海崇明区水稻氮营养诊断的研究[J].中国农业大学学报,2024,29(12):12-22,11.基金项目
崇明区农业科创项目(2021CNKC-05-03) （2021CNKC-05-03）
