基于无人机多光谱影像的寒地水稻品质估测  

Rapid and accurate estimation of rice quality in northeast China based on UAV multispectral images

作　　者：彭显龙[1,2] 武文宇 董强 李鹏飞 朱美瑞[1] 刘东晖 刘智蕾 于彩莲[3] PENG Xian-long;WU Wen-yu;DONG Qiang;LI Peng-fei;ZHU Mei-rui;LIU Dong-hui;LIU Zhi-lei;YU Cai-lian(College of Resources and Environment,Northeast Agricultural University,Harbin,Heilongjiang 150030,China;Key Laboratory of Germplasm Enhancement,Physiology and Ecology of Food Crops in Cold Region,Ministry of Education,Northeast Agricultural University,Harbin,Heilongjiang 150030,China;The School of Material Science and Chemical Engineering,Harbin University of Science and Technology,Harbin,Heilongjiang 150040,China)

机构地区：[1]东北农业大学资源与环境学院,黑龙江哈尔滨150030 [2]东北农业大学寒地粮食作物种质创新与生理生态教育部重点实验室,黑龙江哈尔滨150030 [3]哈尔滨理工大学化工与环境工程学院,黑龙江哈尔滨150040

出　　处：《植物营养与肥料学报》2024年第1期12-26,共15页Journal of Plant Nutrition and Fertilizers

基　　金：黑土地保护与利用科技创新工程专项(XDA28100302);现代农业产业技术体系建设专项(CARS-1-29);国家重点研发计划项目(2023YFD2300403)。

摘　　要：【目的】在稻谷收获前准确估测稻米品质,为改善水稻养分管理、实现优质优价提供参考。【方法】试验在黑龙江省佳木斯市大兴农场和青龙山农场进行,两个地点土壤肥力具有较大差异。每个农场选择一块稻田,以20 m×20 m间隔采集土壤样品分析碱解氮含量,通过变量施氮形成产量水平、长势差异明显的水稻群体。利用大疆精灵4四旋翼多光谱无人机获取水稻分蘖期、拔节期、抽穗期和成熟期冠层多光谱数据。成熟期采集长势具有明显差异的水稻样品和对应的土壤样品,测定土壤有机质和速效氮、磷、钾含量,水稻籽粒蛋白质和直链淀粉含量,产量和食味值,随机选择其中67%的数据通过逐步多元线性回归构建不同生育时期的品质估算模型,其余33%的数据用于模型的验证。【结果】大兴农场水稻成熟期土壤有机质、碱解氮、有效磷和速效钾含量的变异系数分别为11.65%、14.44%、37.66%和11.60%,青龙山农场分别为14.45%、14.32%、36.37%和28.51%。成熟期两个地点水稻产量和食味值的变异系数均大于10%,青龙山农场水稻蛋白质含量变异系数也超过10%,而两地稻米直链淀粉含量的变异系数仅为1.11%~1.83%,因此,水稻直链淀粉含量不适合用于后续的品质估测分析。分蘖期至抽穗期,大兴农场和青龙山农场水稻蛋白质多元回归模型的R~2和RMSE分别为0.262~0.794和0.259~0.686,食味值多元回归模型的R~2和RMSE分别为0.240~0.755和4.211~7.588,估测效果不理想。成熟期,大兴农场和青龙山农场水稻蛋白质多元回归模型的R~2和RMSE分别为0.791~0.874和0.166~0.365,食味值多元回归模型的R~2和RMSE分别为0.786~0.852和2.836~4.039。成熟期基于植被指数的蛋白质和食味值估测精确度优于抽穗期。在抽穗期,将土壤pH、有机质、碱解氮、有效磷、速效钾等指标与植被指数一起建立与蛋白质和食味值的多元回归模型,大兴农场【Objectives】Accurate assessment of rice quality before harvesting is required for improving rice nutrient management and achieving both superior quality and market value.【Methods】Two paddy fields,where soil fertility was different from each other,were selected for the research in Daxing and Qinglongshan farms of Jiamusi City,Heilongjiang Province.Soil samples were collected in every 20 m×20 m area for determination of available N content,then nitrogen fertilizer amounts were calculated for reaching five target rice yield levels,and the distinct rice populations were created through machine interpolation and variable nitrogen application.The DJI Phantom 4 quadrotor multispectral UAV was used to obtain the canopy multi-spectral data of rice at tillering,jointing,heading and maturity stages,respectively,and the data were transferred into five type of normalized vegetation indexes.At maturity,rice grain samples were collected from notably different rice populations for determination of protein,amylose content,yield,and taste quality,and corresponding soil samples were collected afterwards for analysis of organic matter,available N,P,and K contents.67%of the acquired data at each growth stage were used to construct the multiple linear regression models between the quality indices and each of the vegetation index,using the determination coefficient(R2)and the square root of the variance(RMSE)to assess the accuracy of estimated quality.And the left 33%of data were used for the testify of the assessment.【Results】At maturity stage of rice,the coefficients of variation(CV)of soil organic matter,available N,P and K contents were 11.65%,14.44%,37.66%and 11.60%in Daxing farm,and the CVs were 14.45%,14.32%,36.37%and 28.51%in Qinglongshan farm,respectively.At maturity,the CVs of rice yield and taste value were all>10%in the two sites,the CV of protein was>10%in Qinglongshan,while the CVs of amylose varied in range of 1.11%-1.83%in the two sites,indicating that the taste value and protein content of rice were suitab

关 键 词：水稻 多光谱影像 植被指数 食味值 蛋白质 直链淀粉 

分 类 号：S511[农业科学—作物学]