CAJ | 학술논문

暗箱环境下采集柑橘叶片高光谱图像，采用阈值法提取整叶有效光谱信息区域的平均光谱，比对分析了柑橘叶片光谱信息不同预处理方法和光谱PLS、BPNN和LS-SVM预测模型对叶绿素a、叶绿素b和类胡萝卜素等光合色素含量的预测精度。结果显示，采用MSC对原始光谱进行预处理和LS-SVM建模对叶绿素a含量的预测效果较好，Rp 达0.8983，RMSEP为0.1404；采用SNV光谱预处理和LS-SVM 模型对叶绿素b含量的预测其Rp 为0.9123，RMSEP为0.0426；采用MAS预处理和PLS模型对于类胡萝卜素含量预测的 Rp 和RMSEP分别为0.7128和0.0624。结果表明：采用高光谱图像信息可较好地进行柑橘叶片叶绿素a，叶绿素b和类胡萝卜素等光合色素含量的预测，为进一步研究柑橘叶片光合色素含量与组分构成的非损伤实时检测提供了依据。
암상배경하채집감귤협편고광보도상，채용역치법제취정협유효광보신식구역적평균광보，비대분석료감귤협편광보신식불동예처리방법화광보PLS、BPNN화LS-SVM예측모형대협록소a、협록소b화류호라복소등광합색소함량적예측정도。결과현시，채용MSC대원시광보진행예처리화LS-SVM건모대협록소a함량적예측효과교호，Rp 체0.8983，RMSEP위0.1404；채용SNV광보예처리화LS-SVM 모형대협록소b함량적예측기Rp 위0.9123，RMSEP위0.0426；채용MAS예처리화PLS모형대우류호라복소함량예측적 Rp 화RMSEP분별위0.7128화0.0624。결과표명：채용고광보도상신식가교호지진행감귤협편협록소a，협록소b화류호라복소등광합색소함량적예측，위진일보연구감귤협편광합색소함량여조분구성적비손상실시검측제공료의거。
The effective region was segmented from the hyperspectral image of citrus leaf by threshold method with the average spectrum extracted and used to describe the corresponding leaf .Based on the different spectral pre-processing methods ,the pre-diction models of three photosynthetic pigments (i .e .,chlorophyll a ,chlorophyll b ,and carotenoid) were calibrated by partial least squares (PLS) ,BP neural network (BPNN) and least square support vector machine (LS-SVM) .The LS-SVM model for chlorophyll a was established based on multiplicative scatter correction (MSC) ,and the correlation coefficient (Rp ) and the root mean square error of prediction (RMSEP) were 0.898 3 and 0.140 4 ,respectively .The LS-SVM model for chlorophyll b with Rp=0.912 3 and RMSEP=0.042 6 ,was established based on standard normal variable (SNV) .The PLS model for carotenoid was established with Rp =0.712 8 and RMSEP=0.062 4 based on moving average smoothing (MAS) ,but the result was no bet-ter than the other two .The results illustrated that these three photosynthetic pigments could be nondestructively and real time estimated by hyperspectral image .