现代食品科技2017，Vol.33Issue(5)：247-252,297,7.DOI:10.13982/j.mfst.1673-9078.2017.5.039
基于计算机视觉和嗅觉的菠菜叶绿素含量检测方法研究
Study on Spinach Chlorophyll Detection Method Using Computer Vision and Artificial Olfactory Sensor
摘要
Abstract
Developing a rapid and nondestructive detection method for evaluating the quality of post-harvest spinach is essential for spinach producers and retailers.Typically,chlorophyll content was used as a reference index for spinach freshness,and the samples used in this study were stored at 4 ℃ for 12 d before being assessed by computer vision (for sample images) and electronic nose (for sample odors).Feature variables extracted from image and odor information were analyzed by principal component analysis (PCA) method.A chlorophyll content prediction model was established with back propagation artificial neural network (BPANN).The principal components (PCs) were used as the input parameters for the prediction model,and the chlorophyll content was used as the output.Experiments showed that the optimal prediction model of BPANN based on computer vision was obtained with four PCs.The root-mean-square error (RMSE) was 0.1978 mg/g and 0.2147 mg/g,and the correlation coefficient (R) was 0.8457 and 0.7995 for training and prediction sets,respectively.The results of the prediction model using BPANN based on the electronic nose showed that the RMSE was 0.3119 mg/g and 0.3032 mg/g,and R was 0.7013 and 0.7493 for training and prediction sets,respectively.The results of the BPANN model based on the fusion technique showed that the RMSE was 0.1759 mg/g and 0.2121 mg/g,while R was 0.8888 and 0.8736 for training and prediction sets,respectively.The prediction accuracy of the fusion technique was improved compared with that of either of the single detection methods.Overall,the results showed that it is feasible to predict the chlorophyll content of spinach during storage using computer vision and electronic nose,and the fusion technology is helpful in improving the prediction accuracy.关键词
菠菜/计算机视觉/电子鼻/融合技术/人工神经网络/叶绿素Key words
spinach/computer vision/electronic nose/fusion technology/artificial neural network/chlorophyll引用本文复制引用
黄星奕,徐海霞,王顺,潘思慧,田潇瑜..基于计算机视觉和嗅觉的菠菜叶绿素含量检测方法研究[J].现代食品科技,2017,33(5):247-252,297,7.基金项目
江苏省重点研发计划(现代农业)项目(BE2015308) （现代农业）
江苏省高校自然科学研究重大项目(14KJA550001) （14KJA550001）
江苏高校优势学科建设工程资助项目 （）
国家自然基金项目(31671932) （31671932）
江苏省第四期“333工程”资助项目(BRA2015320) （BRA2015320）
