小麦籽粒蛋白质含量高光谱预测模型研究

为定量分析小麦籽粒蛋白质含量、叶片氮素营养指标、冠层高光谱参数的相互关系，确立能够准确预测小麦籽粒蛋白质含量的敏感光谱参数和定量模型，2003—2006年在连续3个生长季不同小麦品种和不同施氮水平的4个大田试验条件下，于小麦不同生育期采集田间冠层高光谱数据并测定植株氮素含量和籽粒蛋白质含量。试验1以低蛋白质含量的宁麦9号和高蛋白质含量的豫麦34为材料，试验2以低、中、高蛋白质含量的宁麦9号、扬麦12和豫麦34为材料，试验3以低蛋白质含量的宁麦9号、中蛋白质含量的扬麦10号和淮麦20以及高蛋白质含量的徐州26为材料，试验4以低蛋白质含量的宁麦9号和中蛋白质含量的扬麦10号为材料。结果显示，不同品种小麦的籽粒蛋白质含量随施氮水平的提高而增加，可以通过开花期叶片氮含量和氮积累量进行可靠的估测。而不同试验条件下的叶片氮含量和氮积累量可以基于统一的光谱参数进行定量反演，其中基于REPle和mND705的叶片氮含量监测模型及基于SDr/SDb和FD742的叶片氮积累量监测模型，具有可靠的预测性和适用性。根据特征光谱参数—叶片氮素营养—籽粒蛋白质含量这一技术路径，以叶片氮素营养为交接点将两部分模型链接，建立了基于开花期高光谱参数的小麦籽粒蛋白质含量预测模型，经独立资料检验表明，以参数mND705、REPle、SDr/SDb和FD742为变量建立成熟期籽粒蛋白质含量预报模型均给出较好的检验结果。因此，利用开花期关键特征光谱指数可以直接评价小麦成熟期籽粒蛋白质含量状况，其中基于mND705参数的预测模型更为准确可靠。

Predicting Grain Protein Content with Canopy Hyperspectral Remote Sensing in Wheat

Grain protein content is an important index indicating wheat quality status,and non-destructive and quick assessment of grain protein content is necessary for cultural regulation and quality classification in wheat production. The objectives of this study were to determine the relationships of grain protein content to ground-based canopy hyper-spectral reflectance and spectral parameters,and to derive regression equations for predicting grain protein content in winter wheat(Triticum aestivum L.) with canopy hyper-spectral remote sensing,by four field experiments with different wheat cultivars and nitrogen levels across three growing seasons,and by time-course measurements on canopy hyperspectral reflectance,plant dry weight,nitrogen content and grain protein content during the experiment periods in 20032006.In experiment one and four,two cultivars of Ningmai 9 and Yumai 34 were used as low and high protein types respectively.In experiment two,Yangmai 12 was added as medium protein type cultivar.In experiment three,the high protein type cultivar altered for Xuzhou 26,and medium type cultivar for Yangmai 10 and Huaimai 20.The results showed that the grain protein content at maturity in wheat increased with nitrogen rate promotion,and could be well estimated by plant nitrogen nutrition status such as leaf N content and leaf N accumulation at anthesis.The regression analyses between vegetation indices developed and leaf N nutrition indices such as leaf N content and leaf N accumulation indicated that several key spectral parameters could be accurately used to estimate the changes in leaf N status across different growth stages,nitrogen levels and growing seasons,e.g.,REPle and mND705 could be used to leaf nitrogen content,and SDr/SDb and FD742 to leaf nitrogen accumulation.The total predicting models on grain protein content at maturity were constructed based on canopy hyper-spectral parameters at anthesis by linking the above two models with leaf N nutrition as intersection in wheat.Testing of the predicting models with independent datasets indicated that the spectral indices of REPle,mND705,SDr/SDb,and FD742 could be used to accurately estimate grain protein contents in wheat.It can be concluded that the grain protein content at maturity in wheat could be predicted directly by key vegetation indices at anthesis,with more reliable estimation from mND705.