臭氧胁迫冬小麦叶片高光谱特征和叶绿素含量估算

为无损、快速监测臭氧胁迫下冬小麦叶片叶绿素含量,建立叶绿素含量与光谱指标的定量关系,基于自由式臭氧浓度增加系统平台观测了臭氧浓度升高下拔节期、开花期及灌浆期冬小麦叶片的叶绿素含量和光谱特征。通过线性回归、人工神经网络(ANN)以及偏最小二乘回归(PLSR)模型对臭氧胁迫下叶片高光谱特征进行了叶绿素含量的估算。结果表明：臭氧胁迫冬小麦叶片的光谱曲线特征出现绿峰“红移”和红边位置“蓝移”现象。相比于拔节期和开花期,小麦叶片在灌浆期受到臭氧的影响更大。臭氧胁迫下叶绿素含量与部分光谱特征参数及遥感植被指数存在显著相关关系,所有模型均取得了较高的估算精度(R²>0.8),其中以光谱特征参数为建模参量的偏最小二乘回归模型精度最高。该方法可用于臭氧胁迫下冬小麦叶片叶绿素含量的估测,动态监测作物的臭氧胁迫。

Hyperspectral characteristics and chlorophyll content estimation of winter wheat under ozone stress

To quantify the O₃-induced damage non-destructively and rapidly, it is important to build up the relationship between the chlorophyll content and spectral characteristics. In this study, the winter wheat leaves under ozone stress were measured at the jointing, flowering and grain filling stages, respectively. The field experiment was conducted through the free-air ozone concentration elevation system (O₃-FACE) platform located at Jiangdu, Yangzhou, Jiangsu Province. Hyperspectral estimation of chlorophyll content under ozone stress was made using linear regression model, artificial neural network (ANN) model and partial least squares regression (PLSR) model, respectively. The results showed that the green peak of the leaf spectrum under ozone stress showed a "red shift", while the red edge of the leaves spectrum showed a "blue shift". Elevated ozone affected wheat leaves more at grain filling stage than jointing and flowering stages. There was a significant correlation between chlorophyll content and most spectral characteristics or vegetation spectral indexes under ozone stress with high estimation accuracy (R²>0.8). Among all models, the highest accuracy was achieved by the PLSR model based on spectral characteristics. The PLSR model can be used to estimate the chlorophyll content of winter wheat exposed to high ozone concentration and thus quantify the damage induced by ozone stress.