利用光谱反射特征预测柑橘叶片冻害

相对电导率是反映植物膜系统状况的一个重要的生理生化指标,与树体营养状况密切相关,越冬前的树体营养状态对果树抵御极端低温和顺利越冬是一个重要的影响因素,而果树受冻时细胞液渗出量和降解量也是冻害发生程度的指标。该研究对不同冻害处理下的柑橘叶片进行光谱扫描,采用了逐步回归法分析了叶片光谱反射率和叶片电导率之间的关系,构建了2种光谱反射预测柑橘叶片电导率模型,其决定系数分别为0.8201、0.8013。结果表明,柑橘叶片电导率与反射光谱之间有较强的相关性,且2种模型所得预测值与实测值的相对误差都小于10%,说明模型具有良好的预测结果。该模型可以为采用空间遥感监测果园生长状况和冻害情况提供参考。

Forecast of citrus leaves frozen injury based on spectral signature

Electrical conductivity is an important physiological and biochemical index which reflects the situation of plant biomembrane system and also reflects the nutrient condition of trees. The nutrition of the tree before winter is an important factor which resists extreme low temperature for surviving through the winter, the exudation or degradation of cell sap is an index of freezing degree when freezing injury happened. The research was to scan the different leaves in different freezing levels with a spectrometer, and the stepwise regression method was used to analyze the relation between spectral reflectivity and leaf conductivity, and then constructing the leaf conductivity and spectral reflection model. The results showed that there was a close relationship between citrus leaf electrical conductivity and spectral reflectance, the errors of predicted values by the two models were both less than 10% compared to measured values, which proved the two models had good predicted accuracy. The results can provide a reference for remote sensing to monitor the growth status and cold injury situation of orchards.