Ren Xiao, Lao Cai-lian, Xu Zhao-li, Jin Yan, Guo Yan, Li Jun-hui, Yang Yu-hong
Guang Pu Xue Yu Guang Pu Fen Xi. 2015 Jun;35(6):1654-9.
Fast and non-destructive measurements of tobacco leaf pigment contents by spectroscopy in situ in the field has great significance in production guidance for nutrient diagnosis and growth monitoring of tobacco in vegetative growth stage, and it is also very important for the quality evaluation of tobacco leaves in mature stage. The purpose of this study is to estimate the chlorophyll and carotenoid contents of tobacco leaves using tobacco leaf spectrum collected in the field. Reflectance spectrum of tobacco leaves in vegetative growth stage and mature stage were collected in situ in the field and the pigment contents of tobacco leaf samples were measured in this study, taking the tobacco leaf samples collected in each and both stages as modeling sets respectively, and using the methods of support vector machine (SVM) and spectral indice to establish the pigment content estimation models, and then compare the prediction performance of the models built by different methods. The study results indicated that the difference of estimation performance by each stage or mixed stages is not significant. For chlorophyll content, SVM and spectral indice modeling methods can both have a well estimation performance, while for carotenoid content, SVM modeling method has a better estimation performance than spectral indice. The coefficient of determination and the root mean square error of SVM model for estimating tobacco leaf chlorophyll content by each stage were 0.867 6 and 0.014 7, while the coefficient of determination and the root mean square error of SVM model for estimating tobacco leaf chlorophyll content by mixed stages were 0.898 6 and 0.012 3; The coefficient of determination and the root mean square error for estimating tobacco leaf carotenoid content by each stage were 0.861 4 and 0.002 5, while the coefficient of determination and the root mean square error of SVM model for estimating tobacco leaf carotenoid content by mixed stages were 0.839 9 and 0.002 5. The innovation point of this study is that on the basis of support vector machine and spectral indice, models established by each stage and mixed stages for estimating the pigment contents of tobacco leaf samples can provide scientific basis and technical support for quality control of tobacco leaf production in field and the ensurance of tobacco leaf recovery quality.
利用光谱法在田间原位快速无损测量烟草叶片色素含量，对于烟草营养生长阶段的养分诊断和生长监测生产指导具有重要意义，对成熟阶段烟叶品质评价也非常重要。本研究的目的是利用田间采集的烟草叶片光谱估算烟草叶片叶绿素和类胡萝卜素含量。本研究在田间原位采集了烟草营养生长阶段和成熟阶段的叶片反射光谱，并测定了烟草叶片样本的色素含量，分别以各阶段及两个阶段采集的烟草叶片样本作为建模集，采用支持向量机（SVM）和光谱指数方法建立色素含量估算模型，然后比较不同方法建立的模型的预测性能。研究结果表明，各阶段或混合阶段的估算性能差异不显著。对于叶绿素含量，SVM和光谱指数建模方法均具有良好的估算性能，而对于类胡萝卜素含量，SVM建模方法的估算性能优于光谱指数。各阶段SVM模型估算烟草叶片叶绿素含量的决定系数和均方根误差分别为0.867 6和0.014 7，混合阶段SVM模型估算烟草叶片叶绿素含量的决定系数和均方根误差分别为0.898 6和0.012 3；各阶段估算烟草叶片类胡萝卜素含量的决定系数和均方根误差分别为0.861 4和0.002 5，混合阶段SVM模型估算烟草叶片类胡萝卜素含量的决定系数和均方根误差分别为0.839 9和0.002 5。本研究的创新点在于，基于支持向量机和光谱指数，各阶段及混合阶段建立的估算烟草叶片样本色素含量的模型，可为田间烟叶生产质量控制和烟叶采收质量保障提供科学依据和技术支持。
