利用冠层光谱监测小麦籽粒蛋白质积累动态

于2003-2006年连续3个生长季, 利用不同小麦品种在不同施氮水平下进行大田试验，在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、生物量和籽粒蛋白质积累量(GPA)。通过定量分析小麦籽粒蛋白质积累量、冠层氮素营养指标及高光谱参数的相互关系，确立了能够准确预测小麦籽粒蛋白质积累动态的敏感光谱参数及定量模型。结果表明，在籽粒灌浆期间冠层氮素营养指标(CNNI)自开花期随时间进程的积分累积值与对应时期籽粒蛋白质积累状况存在显著的定量关系，其中植株氮积累量(PNA)表现最好。对冠层氮素营养指标的光谱估算，在不同品种、氮素水平、生育时期和年度间可以使用统一的光谱模型。根据特征光谱参数-冠层氮素营养指标-籽粒蛋白质积累量这一技术路径，以冠层氮素营养指标为交接点将两部分模型链接，建立高光谱参数与籽粒蛋白质积累量间定量方程。经不同年际独立数据的检验，基于SDr/SDb–PNA–GPA技术路径建立模型可以估算小麦籽粒生长过程中蛋白质积累动态，预测精度和相对误差分别为0.954和13.1%。因此，利用关键特征光谱参数可以实时监测小麦籽粒生长进程中蛋白质积累状况。

Monitoring Grain Protein Accumulation Dynamics with Canopy Reflectance Spectra in Wheat

Grain protein is an important index indicating wheat quality status, and nondestructive and quick assessments of grain protein accumulationdynamics is necessary for cultural regulation and quality classification in wheat (Triticum aestivum L.) production. The objectives of this study were to determine the relationships between plant nitrogen nutrition status, grain protein accumulation, and canopy reflectance spectra in winter wheat, therefore, to derive regression equations for monitoring grain protein accumulation with canopy hyper-spectral remote sensing. Three types of cultivars, i.e., high protein content (Xuzhou 26 and Yumai 34), medium protein content (Yangmai 10, Yangmai 12, and Huaimai 20), and low protein content (Ningmai 9) were used in three field experiments under different nitrogen levels in the growing seasons of 2003–2006. Time-course measurements were taken on canopy hyperspectral reflectance, plant weight, nitrogen content and grain protein accumulation (GPA) during the experimental periods. The results showed that the cumulative value of canopy nitrogen nutrition index (CNNI) from anthesis to specific day were highly correlated with grain protein accumulation at corresponding day across grain filling with the best predictor of plant N accumulation (PNA). According to the regression analyses between vegetation indices and canopy nitrogen nutrition index,several key spectral parameters could accurately estimate the changes in plant N status across different growth stages, nitrogen levels, and growing seasons with the same spectral parameters for each wheat cultivar. According to the technical route of key spectral parameters-canopy N nutrition index-grain protein accumulation, estimating models on grain protein accumulation were constructed on the basis of canopy hyper-spectral parameters by linking the above two models with canopy N nutrition index as intersection in wheat. Tests with other independent dataset showed that the key spectral index SDr/SDb on the basis of the technical route of SDr/SDb-PNA-GNA could be used to predict grain protein accumulation from 7d after anthesis to maturity, with the predictive precision (R²) of 0.954 and the relative error (RE) of 13.1%, respectively. It can be concluded that dynamic change of grain protein accumulation in wheat could be monitored directly with key vegetation spectral index.