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基于电子鼻技术的荆州鱼糕贮藏过程新鲜度预测

张欣 ,  陈双宜 ,  谷惠文 ,  尹小丽

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张欣, 陈双宜, 谷惠文, 等. 基于电子鼻技术的荆州鱼糕贮藏过程新鲜度预测[J]. 轻工学报, 2022, 37(3): 17-25. doi: 10.12187/2022.03.003
引用本文: 张欣, 陈双宜, 谷惠文, 等. 基于电子鼻技术的荆州鱼糕贮藏过程新鲜度预测[J]. 轻工学报, 2022, 37(3): 17-25. doi: 10.12187/2022.03.003
shu
ZHANG Xin, CHEN Shuangyi, GU Huiwen and et al. Prediction of freshness of Jingzhou fish cake during storage based on electronic nose technology[J]. Journal of Light Industry, 2022, 37(3): 17-25. doi: 10.12187/2022.03.003
Citation: ZHANG Xin, CHEN Shuangyi, GU Huiwen and et al. Prediction of freshness of Jingzhou fish cake during storage based on electronic nose technology[J]. Journal of Light Industry, 2022, 37(3): 17-25. doi: 10.12187/2022.03.003
shu

基于电子鼻技术的荆州鱼糕贮藏过程新鲜度预测

  • 1. 长江大学 生命科学学院, 湖北 荆州 434025;

  • 2. 长江大学 化学与环境工程学院, 湖北 荆州 434023

    • 作者简介: 张欣(1974—),男,湖北省荆州市人,长江大学讲师,主要研究方向为农产品加工与贮藏。E-mail:1934112@qq.com;

  • 基金项目: 32001790)
    国家自然科学基金项目(31701693

  • 中图分类号: TS254.4

Prediction of freshness of Jingzhou fish cake during storage based on electronic nose technology

  • 1. College of Life Sciences, Yangtze University, Jingzhou 434025, China;

  • 2. College of Chemistry and Environmental Engineering, Yangtze University, Jingzhou 434023, China

  • Received Date: 2021-09-14
    Accepted Date: 2022-03-25

    CLC number: TS254.4

  • 摘要: 以荆州鱼糕为研究对象,采用感官评定、挥发性盐基氮(TVB-N)检测和电子鼻技术分析不同贮藏条件下荆州鱼糕的新鲜度变化,并基于电子鼻检测数据,结合主成分分析(PCA)、层次聚类分析(HCA)、偏最小二乘判别分析(PLS-DA)和逐步多元线性回归分析(Stepwise-MLR)建立鱼糕新鲜度的判别和预测模型。结果表明:在4℃和室温条件下,电子鼻响应信号均能很好地区分鱼糕样品的新鲜度;鱼糕贮藏过程中产生的氮氧化物、硫化物、甲烷等是新鲜度下降的重要指标;基于电子鼻检测数据建立的多元线性回归预测模型的R2均大于0.932 5,预测集样品的预测均方根误差均小于1.22,即电子鼻技术结合多元统计分析可作为一种无损、简便和快速检测鱼糕新鲜度的方法。
    Abstract: At different storage conditions, the freshness of fish cake after storage was analyzed by sensory evaluation, volatile basic nitrogen (TVB-N) detection and electronic nose. Combining with principal component analysis (PCA), hierarchical cluster analysis (HCA), partial least square discriminant analysis (PLS-DA) and stepwise multiple linear regression analysis (Stepwise-MLR), freshness discriminant and predictionanalysis based on the electronic nose data were carried out.The research results show that the freshness of the fish cake samples was well distinguished at 4 ℃ and room temperature. Nitrogen oxide, sulfide and methane were the important indicatiors of freshness decrease. The correlation coefficients between measured and predicted TVB-N values based on stepwise-MLR were greater than 0.932 5. And the predicted root mean square errors of the prediction set samples were less than 1.22. It could be concluded that electronic nose combined with multivariate statistical analysis could provide a nondestructive, simple and rapid method for detecting the freshness of fish cake.
    1. [1]

      WELLS N,YUSUFU D,MILLS A.Colourimetric plastic film indicator for the detection of the volatile basic nitrogen compounds associated with fish spoilage[J].Talanta,2019,194:830-836.

    2. [2]

      KOSOWSKA M,MAJCHER M A,FORTUNA T,et al.Volatile compounds in meat and meat products[J].Food Science and Technology,2018,37(1):1-7.

    3. [3]

      ZHOU J J,WU X Y,CHEN Z,et al.Evaluation of freshness in freshwater fish based on near infrared reflectance spectroscopy and chemometrics[J].LWT-Food Science and Technology,2019,106:145-150.

    4. [4]

      吴海龙,龙婉君,谷惠文,等.高阶仪器多维校正理论及其在环境分析化学中的应用研究进展[J].长江大学学报(自然科学版),2021,18(3):74-86.

    5. [5]

      ALI M M,HASHIM N,ABD AZIZ S,et al.Principles and recent advances in electronic nose for quality inspection of agricultural and food products[J].Trends in Food Science&Technology,2020,99:1-10.

    6. [6]

      SANAEIFAR A,ZAKIDIZAJI H,JAFARI A,et al.Early detection of contamination and defect in foodstuffs by electronic nose:A review[J].TRAC-Trends in Analytical Chemistry,2017,97:257-271.

    7. [7]

      KODOGIANNIS V. Application of an electronic nose coupled with fuzzy-wavelet network for the detection of meat spoilage[J].Food and Bioprocess Technology,2017,10(4):730-749.

    8. [8]

      GAMBOA J C R,ALBARRACIN E E S,DA SILVA A J,et al.Wine quality rapid detection using a compact electronic nose system:Application focused on spoilage thresholds by acetic acid[J].LWT-Food Science and Technology,2019,108:377-384.

    9. [9]

      HUI G H,WANG L Y,MO Y H,et al.Study of grass carp (Ctenopharyngodon idellus) quality predictive model based on electronic nose[J]. Sensors and Actuators B:Chemical,2012,166:301-308.

    10. [10]

      QIU S S,WANG J.The prediction of food additives in the fruit juice based on electronic nose with chemometrics[J].Food Chemistry,2017,230:208-214.

    11. [11]

      XU J Y,LIU K W,ZHANG C.Electronic nose for volatile organic compounds analysis in rice aging[J].Trends in Food Science&Techno-logy,2021,109:83-93.

    12. [12]

      GUNEY S,ATASOY A.Freshness classification of horse mackerels with E-nose system using hybrid binary decision tree structure[J].International Journal of Pattern Recognition and Artificial Intelligence,2020,34(3):2050003.

    13. [13]

      沈秋霞,朱克永,李明元,等.低场核磁结合电子鼻判定复合保鲜剂对冷藏虹鳟鱼片品质变化的影响[J].食品与机械,2019,35(12):130-136.

    14. [14]

      曲映红,王锋,施文正.感官评定在鱼糜制品工艺优化中的应用[J].山东化工,2018,47(22):122-124.

    15. [15]

      王丹,姜启兴,许艳顺,等.鱼糕质构的仪器分析与感官评定间的相关性[J].食品与机械,2016,32(4):24-27
      ,210.

    16. [16]

      国家卫生和计划生育委员会.食品安全国家标准食品中挥发性盐基氮的测定:GB 5009.228-2016[S].北京:中国标准出版社,2016.

    17. [17]

      刘明,潘磊庆,屠康,等.电子鼻检测鸡蛋货架期新鲜度变化[J].农业工程学报,2010,26(4):317-321.

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  • 收稿日期:  2021-09-14
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张欣, 陈双宜, 谷惠文, 等. 基于电子鼻技术的荆州鱼糕贮藏过程新鲜度预测[J]. 轻工学报, 2022, 37(3): 17-25. doi: 10.12187/2022.03.003
引用本文: 张欣, 陈双宜, 谷惠文, 等. 基于电子鼻技术的荆州鱼糕贮藏过程新鲜度预测[J]. 轻工学报, 2022, 37(3): 17-25. doi: 10.12187/2022.03.003
shu
ZHANG Xin, CHEN Shuangyi, GU Huiwen and et al. Prediction of freshness of Jingzhou fish cake during storage based on electronic nose technology[J]. Journal of Light Industry, 2022, 37(3): 17-25. doi: 10.12187/2022.03.003
Citation: ZHANG Xin, CHEN Shuangyi, GU Huiwen and et al. Prediction of freshness of Jingzhou fish cake during storage based on electronic nose technology[J]. Journal of Light Industry, 2022, 37(3): 17-25. doi: 10.12187/2022.03.003
shu

基于电子鼻技术的荆州鱼糕贮藏过程新鲜度预测

    作者简介:张欣(1974—),男,湖北省荆州市人,长江大学讲师,主要研究方向为农产品加工与贮藏。E-mail:1934112@qq.com
  • 1. 长江大学 生命科学学院, 湖北 荆州 434025;
  • 2. 长江大学 化学与环境工程学院, 湖北 荆州 434023
  • 收稿日期: 2021-09-14
  • 录用日期: 2022-03-25
基金项目:  32001790)国家自然科学基金项目(31701693

摘要: 以荆州鱼糕为研究对象,采用感官评定、挥发性盐基氮(TVB-N)检测和电子鼻技术分析不同贮藏条件下荆州鱼糕的新鲜度变化,并基于电子鼻检测数据,结合主成分分析(PCA)、层次聚类分析(HCA)、偏最小二乘判别分析(PLS-DA)和逐步多元线性回归分析(Stepwise-MLR)建立鱼糕新鲜度的判别和预测模型。结果表明:在4℃和室温条件下,电子鼻响应信号均能很好地区分鱼糕样品的新鲜度;鱼糕贮藏过程中产生的氮氧化物、硫化物、甲烷等是新鲜度下降的重要指标;基于电子鼻检测数据建立的多元线性回归预测模型的R2均大于0.932 5,预测集样品的预测均方根误差均小于1.22,即电子鼻技术结合多元统计分析可作为一种无损、简便和快速检测鱼糕新鲜度的方法。

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