沈阳农业大学学报2024，Vol.55Issue(2)：231-239,9.DOI:10.3969/j.issn.1000-1700.2024.02.011
基于高光谱成像技术的南果梨酸度无损检测方法
Non-destructive Testing Method for Acidity of Nanguo Pear Based on Hyperspectral Imaging Technology
摘要
Abstract
Nanguo pear is an important fruit variety,and its acidity is one of the important indicators for evaluating fruit quality.However,traditional methods for detecting acidity in Nanguo pear often require destructive sampling and chemical analysis,which is not only time-consuming and laborious,but also prone to sample contamination and waste.Therefore,a non-destructive testing method based on hyperspectral imaging technology was explored to achieve rapid,accurate,and non-destructive detection of acidity in Nanguo pear.Firstly,the hyperspectral data of Nanguo pear stored for different days at room temperature of 20℃was collected,the wavelength range is 400-1 000 nm,and the titratable acid of Nanguo pear samples was measured through physical and chemical experiments;secondly,multiple methods such as multiple scatter correction(MSC),standard normal variation(SNV),Savitzky Golay smoothing filtering were used to preprocess spectral data.A partial least squares regression(PLSR)model was established,and the best preprocessing method was selected.The results showed that the MSC method had the best performance;then,combined with the continuous projection algorithm(SPA),feature bands are extracted,and 9 feature spectral variables are determined in the range of 700-900 nm;finally,using the extracted 9 feature spectral variables as input vectors,a PLSR model,an extreme learning machine(ELM)model,and a BP neural network model optimized by genetic algorithm(GA)and particle swarm optimization(PSO)were established respectively.The research results indicate that the PSO-BP model based on MSC preprocessing and SPA algorithm feature extraction has the highest prediction accuracy and the best performance,with a prediction set determination coefficient R2p=0.911 and RMSEP=0.032.It can be seen that the SPA-PSO-BP model based on hyperspectral imaging technology can be used for the detection of acidity in Nanguo pear,providing reference for the quality evaluation of Nanguo pear.关键词
高光谱成像技术/南果梨/酸度/BP神经网络/PSO-BP模型Key words
hyperspectral imaging technology/Nanguo pear/acidity/BP neural network/PSO-BP model分类
轻工业引用本文复制引用
张芳,邓照龙,田有文,高鑫,王开田,徐正玉..基于高光谱成像技术的南果梨酸度无损检测方法[J].沈阳农业大学学报,2024,55(2):231-239,9.基金项目
辽宁省教育厅基础研究项目(JYTMS20231285) （JYTMS20231285）
