CAJ | 학술논문

为解决传统理化法检测柑橘树叶片受红蜘蛛为害后色素含量变化时存在的工作量大、效率低等问题，该文研究应用高光谱成像技术检测柑橘红蜘蛛为害叶片色素含量的方法。研究中对比了正常叶片与受害叶片的原始光谱以及原始光谱一阶微分曲线的差异，寻找反映叶片色素含量变化的特征波段；分析了特征波段反射率比值与叶片色素间相关性；采用单变量线性回归法分析了常用植被指数预测叶片色素含量的效果；采用逐步回归分析法建立了叶片色素含量预测模型，并对模型预测效果进行了F检验。结果表明：常用植被指数预测叶片色素含量结果不理想；选取的667/522、667/647和522/647 nm等3个特征波段反射率比值与叶片3种色素含量间具有较高的相关性；用于建立叶片色素含量预测模型的最佳特征波段反射率比值为667/522和667/647 nm，所建立的模型可较好地预测健康及受害叶片的叶绿素a、叶绿素b和类胡萝卜素含量。
위해결전통이화법검측감귤수협편수홍지주위해후색소함량변화시존재적공작량대、효솔저등문제，해문연구응용고광보성상기술검측감귤홍지주위해협편색소함량적방법。연구중대비료정상협편여수해협편적원시광보이급원시광보일계미분곡선적차이，심조반영협편색소함량변화적특정파단；분석료특정파단반사솔비치여협편색소간상관성；채용단변량선성회귀법분석료상용식피지수예측협편색소함량적효과；채용축보회귀분석법건립료협편색소함량예측모형，병대모형예측효과진행료F검험。결과표명：상용식피지수예측협편색소함량결과불이상；선취적667/522、667/647화522/647 nm등3개특정파단반사솔비치여협편3충색소함량간구유교고적상관성；용우건립협편색소함량예측모형적최가특정파단반사솔비치위667/522화667/647 nm，소건립적모형가교호지예측건강급수해협편적협록소a、협록소b화류호라복소함량。
In order to solve the high workload and low efficiency problems while measuring the pigment content variation of citrus red mite infested leaves using the traditional physical and chemical methods, a novel pigment content measurement method for citrus red mite infested leaf using the hyper-spectral imaging technology was studied in this paper. In the research, 400 healthy leaves and 400 sick leaves were included as the test samples in which 350 healthy leaves and 350 sick leaves were utilized for model establishment and the other 50 leaves of each type were used for a model test. Each leaf’s original spectrum and its first order deviation in its particular healthy and sick area were acquired to investigate the characteristic spectrum bands which could mostly reflect the variation of leaf pigment content. The correlation between characteristic spectrum band ratios and pigment content was analyzed. An univariate linear regression method was applied to analyze the pigment content prediction effect using the common vegetation indexes. A leaf pigment content prediction model was established, using the stepwise regression method, and the model’s prediction ability was tested using the F test. Experimental results indicated that it is not satisfactory using the common vegetation indexes to predict leaf pigment content since they are not specially selected for citrus trees. The selected three characteristic spectrum band ratios of 667/522, 667/647, and 522/647 nm, each of which has a high correlation with a leaf’s three types of pigment content, were applied in the stepwise regression method to establish pigment content prediction models. Two out of three of the characteristic spectrum band ratios of 667/522 and 667/647 nm, which gave the best performance, were used as independent values for model establishment. The F test results indicated that the established models could preferably predict both healthy and sick leaves chlorophyll a, chlorophyll b, and carotenoid content. The selected characteristic bands, as well as the established prediction models, could be used as the foundation to further study the citrus red mite infestation fast detection methods and techniques.