基于反射光谱技术的植物叶片SPAD值预测建模方法研究

植物叶片SPAD值反映了植物叶绿素含量，对特定的植物也反映了氮含量。为了实现植物叶绿素含量的快速无损检测，利用光纤反射光谱技术对植物叶片SPAD值进行了预测建模研究。实验中选取70个样本作为建模集，50个样本作为校验集。通过叶片光谱比对，发现光谱红边段650～750 nm对SPAD预测建模有直接关系。实验确定了光强调节因子和叶片厚度影响因子。首先通过待定系数法构造出SPAD预测公式，然后用Visual Basic6.0设计的遗传算法进行参数寻优，最后确定最佳敏感波段为683.24～733.91 nm。分析表明，叶片厚度对SPAD反射光谱模型精度有显著影响。经过叶片厚度修正后的建模集拟合因子R2为0.865 8, 校验集拟合因子R2为0.916 1。结果表明, 利用反射光谱技术建立的SPAD预测模型是成功的, 从而可为仪器开发提供方法指导。

SPAD Prediction of Leave Based on Reflection Spectroscopy

Handheld SPAD meter is often used to measure chlorophyll content of plant and nitrogen level for some species.For plant production automation,however,it loses its popularity due to its point-by-point checking.The authors need to monitor the growing conditions of plant remotely,instantly and nondestructively.In the test,we examined optical fiber reflection spectroscopy used to measure chlorophyll content of some plant leaves,or for their SPAD prediction.The authors picked 120 leaves randomly from our campus ...