摘要
不同高粱品种直接决定其所酿酱香型白酒的品质高低,因此高粱品种的鉴别尤为重要。本研究利用便携式近红外光谱结合化学计量学方法建立高粱品种鉴别模型,采集了25、45、65 ms三个积分时间下的粳高粱和糯高粱在完整以及粉末两种状态的光谱数据,利用单一及组合光谱预处理方法消除光谱中存在的干扰,结合无监督识别方法主成分分析(principal component analysis,PCA)和3种有监督模式识别方法线性判别式分析(linear discriminant analysis,LDA)、偏最小二乘判别分析(partial least square discriminant analysis,PLS-DA)以及软独立模式识别法(soft independent mode classification analysis,SIMCA)分别构建了不同品种高粱的鉴别模型。结果表明,光谱预处理方法能够有效消除干扰;无监督方法无法实现不同品种高粱鉴别,有监督模式识别方法结果能实现高粱品种鉴别,其中LDA>PLS-DA>SIMCA;三个积分时间下,粉末高粱结果优于完整高粱;三个有监督鉴别模型的65 ms的结果较差,45 ms积分时间下的鉴别结果最佳,原始光谱均能达到100%鉴别。以上结果表明,便携式近红外光谱仪结合模式识别方法可以实现糯高粱和粳高粱的准确无损鉴别。
Different sorghum varieties directly determine the quality of Baijiu,so the identification of sorghum varieties is particularly important.This study used portable near-infrared(NIR)spectroscopy combined with chemometric methods to establish a sorghum varieties identification model.Spectra of japonica sorghum and glutinous sorghum in both intact and powdered states were collected at three integration times of 25,45 ms,and 65 ms.Single and combined spectral preprocessing methods were used to eliminate interference in the spectra.Unsupervised recognition methods,PCA,and three supervised pattern recognition methods,LDA,PLS-DA,and SIMCA,were used to construct identification models for different varieties of sorghum.The results indicated that spectral preprocessing methods could effectively eliminate interference.Unsupervised methods could not achieve the identification of different varieties of sorghum,while supervised pattern recognition methods could achieve the identification of sorghum varieties,where LDA>PLS-DA>SIMCA.Under three integration times,the results of powdered sorghum were better than those of intact sorghum.The results of the three supervised discrimination models at 65 ms were poor,the best discrimination result achieved at 45 ms integration time,and the original spectra were able to achieve 100%discrimination.The above results indicated that the combination of portable near-infrared spectrometer and pattern recognition method could achieve accurate and non-destructive identification of glutinous sorghum and japonica sorghum.
作者
杨理萍
邱熙文
杨清华
谌佳琪
唐辉
李跑
杜国荣
YANG Liping;QIU Xiwen;YANG Qinghua;ZHAN Jiaqi;TANG Hui;LI Pao;DU Guorong(College of Food Science and Technology,Hunan Agricultural University,Changsha 410128,China;China Certification&Inspection Group Hunan Co.,Ltd.,Changsha 410021,China;Guangdong Provincial Key Laboratory of Utilization and Conservation of Food and Medicinal Resources in Northern Region,Shaoguan 512005,China;Shanghai Tobacco Group Co.,Ltd.,Technical Center Beijing Workstation,Beijing 101121,China)
出处
《中国果菜》
2025年第1期1-7,共7页
China Fruit & Vegetable
基金
湖南省自然科学基金(2023JJ30290)
2024年度湖南省大学生创新训练计划一般项目(s202410537029)
广东省食药资源利用与保护重点实验室2023年度开放基金课题重点项目(FMR2023012Z)
湖南农业大学2024年学科交叉研究青年引导项目(2024XKJC10)。
关键词
糯高粱
粳高粱
近红外光谱
模式识别
无损鉴别
智能检测
Glutinous sorghum
japonica sorghum
near-infrared spectroscopy
nondestructive testing
nondestructive identification
intelligent detection
作者简介
第一作者:杨理萍(2000-),女,在读硕士,研究方向为食品无损检测;通信作者:李跑(1989-),男,副教授,博士,主要从事食品分析与化学计量学研究与教学工作;通信作者:杜国荣(1983-),男,高级工程师,博士,主要从事化学计量学研究工作。
