不同算法红边位置监测小麦冠层氮素营养指标的比较

【目的】红边位置常被用于监测作物叶片氮素营养状况。本文旨在通过不同算法提取红边位置,分析并比较不同算法提取的红边位置对氮素营养监测模型的准确性和可靠性差异,确定监测小麦叶片氮素营养的最佳红边位置算法及定量模型。【方法】基于不同施氮水平、播种密度、品种类型和生育时期的小麦田间试验,系统分析不同算法的红边位置(一阶微分、倒高斯法、多项式拟合法、四点内插法、拉格朗日法、线性外推法)与冠层叶片氮素营养指标的定量关系,比较不同算法红边位置对氮素营养监测的准确性和可靠性。【结果】线性外推法为计算小麦红边位置的最佳算法,并建立了基于线性外推法的小麦冠层叶片氮素营养定量监测模型。【结论】研究结果为小麦冠层叶片氮素营养指标的可靠监测提供了有效途径。

Comparative Study on Monitorin Canopy Leaf Nitrogen Status on Red Edge Position with Different Algorithms in Wheat

【Objective】 Red edge position (REP, 680-780 nm) has been used for evaluating crop leaves nitrogen status. The objectives of this paper were to extract REP with different algorithms, to analyze the precision and stability of the monitoring model, to ascertain the optimum REP algorithm and relevant quantitative model for nitrogen status. 【Method】 On the basis of hyperspectral reflectance and leaf nitrogen status at different growth stages under varied nitrogen rates, planting densities and wheat cultivars, this study systematically analyzed the quantitative relationships and statistical characters between red edge position on various algorithms and canopy leaf nitrogen status, and then developed the monitoring models by comparing accuracy and reliability of nitrogen estimation. 【Result】 The results showed that the monitoring models developed from the linear extrapolation method (LEM) could stably indicate canopy leaf nitrogen content (LNC) and leaf nitrogen accumulation (LNA) in wheat. 【Conclusion】 The results have provided a stable and effective approach for monitoring canopy leaf nitrogen status in wheat.