一种电子鼻识别模型应用于多味酱油酿造分析
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摘要
为进一步提高对酱油酿造过程效率及成品质量的把控,设计一种电子鼻智能识别系统对酱油酿造多种风味进行分析和研究。在重点掌握多味酱油酿造工艺、过程监测指标及关键环节控制的基础上,从电子鼻对食品调味品气味识别机理入手,建立该系统的识别模型,从软件控制算法与硬件模块设置两方面形成完整的电子鼻多味酱油酿造识别模型进行识别试验,得到:该电子鼻识别系统的识别准确率可达90%以上,对酱油多味的识别时间控制在60 s内,整体运行稳定可靠。基于电子鼻识别技术应用于酱油酿造的多味判定适用性广,且可为类似调味品风味识别与生产指标监控系统的设计开发提供参考思路。
In order to further improve the efficiency of soy sauce brewing process and the quality control of finished product, an electronic nose intelligent recognition system is designed to analyze and study the various flavors of soy sauce brewing. On the basis of mastering the brewing technology, process monitoring indexes and key link control of multi-flavor soy sauce, the recognition model of the system is established from the mechanism of electronic nose for identifying the flavor of food condiments. A complete recognition model of multi-flavor soy sauce brewing by electronic nose is formed from two aspects of software control algorithm and hardware module setting. The recognition accuracy rate of electronic nose recognition system could reach more than 90%, the recognition time of multi-flavor soy sauce could be controlled within 60 s, and the overall operation is stable and reliable. The application of electronic nose recognition technology in multi-flavor determination of soy sauce brewing has wide applicability, and would provide some references for the design and development of similar condiment flavor recognition and production index monitoring system.
In order to further improve the efficiency of soy sauce brewing process and the quality control of finished product, an electronic nose intelligent recognition system is designed to analyze and study the various flavors of soy sauce brewing. On the basis of mastering the brewing technology, process monitoring indexes and key link control of multi-flavor soy sauce, the recognition model of the system is established from the mechanism of electronic nose for identifying the flavor of food condiments. A complete recognition model of multi-flavor soy sauce brewing by electronic nose is formed from two aspects of software control algorithm and hardware module setting. The recognition accuracy rate of electronic nose recognition system could reach more than 90%, the recognition time of multi-flavor soy sauce could be controlled within 60 s, and the overall operation is stable and reliable. The application of electronic nose recognition technology in multi-flavor determination of soy sauce brewing has wide applicability, and would provide some references for the design and development of similar condiment flavor recognition and production index monitoring system.
引文
[1]万萍,周琳,孙杰,等.酱油选育菌种制曲条件的优化研究[J].中国调味品,2018,43(10):43-45.
[2]段松林,彭荣,殷钟意,等.基于综合酶活力优化的豆渣酱油曲制备工艺[J].大豆科学,2018,37(6):955-960,974.
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[4]殷勇,赵玉珍,于慧春.基于多种变量分析方法鉴别食醋种类电子鼻信号特征筛选[J].农业工程学报,2018,34(15):290-297.
[5]张振,柏韵,郭雪松,等.基于电子鼻技术研究壳聚糖/ε-聚赖氨酸复合膜对中国对虾的保鲜效果[J].食品工业科技,2018,39(15):285-290,297.
[6]邢梦珂,孙柯,赵楠,等.基于电子鼻技术的草莓损伤检测系统的开发[J].南京农业大学学报,2018,41(3):555-561.
[7]王彬.基于电子鼻及可见-近红外光谱的鸡蛋品种及产地鉴别研究[D].武汉:华中农业大学,2018.
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[14]刘燕.电子鼻系统中传感器漂移补偿方法研究[D].重庆:重庆大学,2017.
[15]胡梁斌,黎家奇,朱琳,等.基于模糊数学综合评价法研制鮰鱼辣椒酱配方的研究[J].中国调味品,2018,43(10):26-29.
[16]高竟.模块化电子鼻系统平台构建及其优化设计[D].吉林:东北电力大学,2018.
[17]徐克明.电子鼻优化设计及其在坚果品质检测中的应用[D].杭州:浙江大学,2017.
[18]朱新贵,李学伟,王颖.酿造酱油回收油脂的酶法脱酸工艺研究[J].中国酿造,2018,37(12):40-45.
[19]王晴晴.基于电子鼻/舌融合的感官鉴评模型构建及应用[D].吉林:东北电力大学,2018.
[20]雷锦成,常煦,宋焕禄,等.酱油活性干酵母在酱油中的应用效果研究[J].中国调味品,2013,38(2):1-3,8.
[2]段松林,彭荣,殷钟意,等.基于综合酶活力优化的豆渣酱油曲制备工艺[J].大豆科学,2018,37(6):955-960,974.
[3]王夫杰,鲁绯,赵俊平,等.酱油风味及其检测方法的研究进展[J].中国酿造,2010(8):1-5.
[4]殷勇,赵玉珍,于慧春.基于多种变量分析方法鉴别食醋种类电子鼻信号特征筛选[J].农业工程学报,2018,34(15):290-297.
[5]张振,柏韵,郭雪松,等.基于电子鼻技术研究壳聚糖/ε-聚赖氨酸复合膜对中国对虾的保鲜效果[J].食品工业科技,2018,39(15):285-290,297.
[6]邢梦珂,孙柯,赵楠,等.基于电子鼻技术的草莓损伤检测系统的开发[J].南京农业大学学报,2018,41(3):555-561.
[7]王彬.基于电子鼻及可见-近红外光谱的鸡蛋品种及产地鉴别研究[D].武汉:华中农业大学,2018.
[8]李伟丽,伍小宇,王庆慧,等.发芽青稞的营养加工特性及电子鼻快速识别[J].食品与发酵工业,2018,44(6):195-199.
[9]孙莹,彭子宁.电子鼻在调味料工业的应用研究进展[J].中国调味品,2018,43(7):170-172,177.
[10]邓平聆.基于表达学习的电子鼻干扰检测算法研究[D].重庆:重庆大学,2018.
[11]殷勇,申晓鹏,于慧春.基于KECA+FDA的白酒电子鼻多特征鉴别方法[J].农业机械学报,2018,49(4):374-380.
[12]信文平.基于电子鼻的香油精快速检测模式识别及算法研究[D].保定:河北大学,2012.
[13]杨成聪,舒娜,张亦舒,等.基于电子鼻和GC-MS技术对市售酱油风味品质的评价[J].中国调味品,2018,43(10):151-155.
[14]刘燕.电子鼻系统中传感器漂移补偿方法研究[D].重庆:重庆大学,2017.
[15]胡梁斌,黎家奇,朱琳,等.基于模糊数学综合评价法研制鮰鱼辣椒酱配方的研究[J].中国调味品,2018,43(10):26-29.
[16]高竟.模块化电子鼻系统平台构建及其优化设计[D].吉林:东北电力大学,2018.
[17]徐克明.电子鼻优化设计及其在坚果品质检测中的应用[D].杭州:浙江大学,2017.
[18]朱新贵,李学伟,王颖.酿造酱油回收油脂的酶法脱酸工艺研究[J].中国酿造,2018,37(12):40-45.
[19]王晴晴.基于电子鼻/舌融合的感官鉴评模型构建及应用[D].吉林:东北电力大学,2018.
[20]雷锦成,常煦,宋焕禄,等.酱油活性干酵母在酱油中的应用效果研究[J].中国调味品,2013,38(2):1-3,8.