现代食品科技2026，Vol.42Issue(4)：313-326,14.DOI:10.13982/j.mfst.1673-9078.2026.4.0130
基于近红外光谱技术快速预测菊芋主要理化指标
Rapid Prediction of the Main Physicochemical Indicators in Jerusalem Artichoke by Using Near-infrared Spectroscopy
摘要
Abstract
Inulin,protein,total polyphenols,and ash are important physicochemical components of the Jerusalem artichoke.They have an impact on Jerusalem artichoke's processing and nutritional characteristics.Traditional detection methods for these components often require a large number of chemical reagents and high-standard equipment.To achieve rapid prediction of the main physicochemical indicators in the Jerusalem artichoke,56 Jerusalem artichoke samples were examined in this study.Spectral data were collected in the range of 900～2 500 nm by using a near-infrared(NIR)spectrometer,and partial least squares regression prediction models were established in combination with the measured contents of inulin,protein,total polyphenols,and ash.The results showed that,after outlier elimination,spectral preprocessing,and characteristic band screening,prediction correlation coefficients(R2p)for the optimal quantitative models of inulin,protein,total polyphenols,and ash were 0.869 5,0.930 7,0.943 3,and 0.920 6,respectively.The corresponding root mean square errors of prediction were 2.237 2 g/100 g,0.363 4 g/100 g,0.107 7 mg.g-1,and 0.158 1 g/100 g,respectively,indicating good predictive ability of the models.External validation showed no significant difference(P＞0.05)between the detection results obtained using NIR spectroscopy and standard chemical methods.This study provides a theoretical basis for the application of NIR in the rapid prediction of physicochemical components in the Jerusalem artichoke.关键词
菊芋/近红外漫反射法/含量预测/特征波段筛选/偏最小二乘回归Key words
Jerusalem artichoke/near-infrared diffuse reflectance spectrometry/content prediction/characteristic band screening/partial least squares regression引用本文复制引用
李心怡,肖苏尧,宋明月,段杉,曹庸,徐小航,韩少钦,阚启鑫,谭悦,王祺皓,刘果,李院平,韩勇军..基于近红外光谱技术快速预测菊芋主要理化指标[J].现代食品科技,2026,42(4):313-326,14.基金项目
贵威生物营养与健康研究院项目(5100-PH23004) （5100-PH23004）
广东省功能食品活性物重点实验室(2018B030322010) （2018B030322010）
广东省引进创新创业团队项目(2019ZT08N291) （2019ZT08N291）
