中国烟草学报2018，Vol.24Issue(1)：6-13,8.DOI:10.16472/j.chinatobacco.2017.210
基于近红外光谱分析技术结合化学计量学方法的初烤烟叶霉变预测研究
Prediction model for flue-cured tobacco leaf mildew based on NIR spectroscopy combined with chemometrics
摘要
Abstract
A near infrared spectroscopy (NIR) prediction model was built for tobacco mildew early warning based on content of ergosterol. Twenty leaf tobacco samples of two grades (B2F and C3F) in 2015 and 2016, from five regions in Yunnan province, were collected as research material. Mildew tests were conducted under artificial conditions (28℃, 80% relative humidity, and 18% of leaf water content). Tobacco leaves were sampled every 3 days, and ergosterol content was determined. Based on principal component analysis (PCA) and Hotelling T2parameter, a prediction model was established. Early warning of tobacco mildew was compared between model prediction and unaided eye observation. Results indicated that (1) when mildew became macrosopic, ergosterol content of tobacco leaf increased by 4.66-23.38 folds compared with initial value. (2) Among the 20 samples, nine confirmed mildew pre-warning by 3-6 days, and four warned at the same day when mildew was macrosopic, while no mildew was found in the rest seven samples. It was concluded that the model can be used to predict flue-cured tobacco leaf mildew.关键词
初烤烟叶/近红外光谱分析技术/麦角甾醇/霉变/HotellingT2Key words
flue-cured tobacco/near infrared spectroscopy (NIR)/ergosterol/mildew/hotelling T2引用本文复制引用
周继月,杨盼盼,刘磊,尹晓东,侯英,杨式华..基于近红外光谱分析技术结合化学计量学方法的初烤烟叶霉变预测研究[J].中国烟草学报,2018,24(1):6-13,8.基金项目
中国烟草总公司云南省公司科技计划项目"云南初烟存储过程霉变规律研究及预防控制"(合同编号:2015YN29) （合同编号:2015YN29）
