中文摘要：

应用可见/近红外高光谱对细菌性角斑病早期胁迫下的黄瓜叶片中所含过氧化物酶（peroxidase，POD）活性进行检测。在380~1 030 nm光谱范围获取120个样本（健康，病害轻微感染1级和2级）的光谱曲线，并使用分光光度计法测量感染病害样本中的过氧化物酶活性值。采用单因素方差分析（analysis of variance，ANOVA）对三种不同程度早期病害胁迫下过氧化物酶活性值进行统计分析，结果表明不同程度病害胁迫下黄瓜叶片中的过氧化物活性存在显著性差异（p=0.05）。采用SPXY方法将样本分为建模集（80个样本）与预测集（40个样本）。采用random frog（RF）和回归系数法（regression coefficient，RC）方法提取特征波段，并建立过氧化物酶活性值的偏最小二乘回归（partial least square regression，PLSR）预测模型。最终得到RF-PLSR具有最佳的预测效果，预测集相关系数为0.816，预测均方根误差为11.235。研究结果表明高光谱结合化学计量学方法可以实现细菌性角斑病早期胁迫下黄瓜叶片中过氧化物酶活性的测定，为植物病害的早期无损诊断提供参考。

英文摘要：

Visible/near-infrared hyper-spectra technique was applied to detect peroxidase （POD） content in cucumber leaves with early bacterial angular leaf-spot disease （BALD） stress. A total of 120 samples with three BALD infection stages were used to acquire with hyper-spectra with in the range of 380~1 030 nm （512 wavelengths） and corresponding POD content in the leaves were measured with spectrophotometer method. Analysis of variance （ANOVA） were applied to process statistical analysis of the measured POD content and results showed that there was significant difference （p=0.05） about the POD content in the cucumber leaves with the three stages of BALD stress. SPXY method was employed to divide the samples into a calibration set （n=80） and a prediction set （n=40）. Random Frog （RF） and regression coefficient （RC） were used to select the characteristic wavelengths to reduce data dimensions. Partial least square regression （PLSR） was applied to develop the quantitative relationship between spectra and POD content. RF-PLSR was the optimal model to predict POD content with correlation coefficient （r） of 0.816 with root mean squared error of prediction （RMSEP） of 11.235. The result showed that hyper-spectra technique combined with chemometrics method was promising for detecting POD content in the cucumber leaves with different BALD developments. This study provided a theoretical reference for early detecting disease infection in non-destructive way.