[1] 孙永立. 我国食品安全形势总体稳中向好[J].中国食品工业, 2021(7):52-55.
SUN Y L.China′s food safety situation is generally stable and improving [J].China Food Industry, 2021(7):52-55.
[2] 丁卫平, 杨夕宇, 朱可滢, 等.分子生物学技术在检测机构食品微生物检测中的应用现状、技术制约因素与发展趋势[J].中国调味品, 2021, 46(3):198-200.
DING W P, YANG X Y, ZHU K Y, et al.The application status,technical constraints and development trend of molecular biology technology in the detection of food microorganisms by testing institutions[J].China Condiment, 2021, 46(3):198-200.
[3] 吕琳卿, 刘乐平, 陈跃华.浅析无损检测技术在食品质量安全检测中的应用[J].食品安全导刊, 2020(33):187.
LYU L Q, LIU L P, CHEN Y H.Analysis on the application of nondestructive testing technology in food quality and safety testing [J].China Food Safety Magazine, 2020(33):187.
[4] 黄宝莹, 佘之蕴, 王文敏, 等.近红外光谱技术在乳制品快速检测中的应用研究进展[J].中国酿造, 2020, 39(7):16-19.
HUANG B Y, SHE Z Y, WANG W M, et al.Research progress of near-infrared spectroscopy application in rapid detection of dairy products[J].China Brewing, 2020, 39(7):16-19.
[5] 曹玉栋, 祁伟彦, 李娴, 等.苹果无损检测和品质分级技术研究进展及展望[J].智慧农业, 2019, 1(3):29-45.
CAO Y D, QI W Y, LI X, et al.Research progress and prospect on non-destructive detection and quality grading technology of apple[J].Smart Agriculture, 2019, 1(3):29-45.
[6] 彭云发. 近红外光谱技术在南疆红枣品质快速无损检测中的应用研究[D].阿拉尔:塔里木大学, 2015.
PENG Y F.The application research of near infrared spectroscopy in the nondestructive detection of Nanjang jujubes internal quality[D].Alaer:Tarim University, 2015.
[7] 郝广. 基于多光谱成像技术的番茄酱品质与安全快速检测研究[D].合肥:合肥工业大学, 2018.
HAO G.Rapid detection of quality and safety of tomato paste by using multispectral imaging[D].Hefei:Hefei University of Technology, 2018.
[8] 闫思雨, 寇婕妤, 张茜, 等.冷藏鲜切猕猴桃片微生物污染的近红外检测[J].陕西科技大学学报, 2019, 37(5):46-52;62.
YAN S Y, KOU J Y, ZHANG Q, et al.Near infrared detection of microbial contamination in refrigeration fresh Kiwi slices[J].Journal of Shaanxi University of Science & Technology, 2019, 37(5):46-52;62.
[9] 熊来怡. 近红外光谱技术检测猪肉品质及其安全判别研究[D].杨凌:西北农林科技大学, 2012.
XIONG L Y.Quality detection and safety discrimination of pork with near-infrared spectroscopy[D].Yangling:Northwest A&F University, 2012.
[10] 蓝蔚青, 孙雨晴, 张楠楠, 等.基于近红外光谱建立大黄鱼新鲜度预测模型[J].包装工程, 2020, 41(17):1-6.
LAN W Q, SUN Y Q, ZHANG N N, et al.Prediction model for freshness of large yellow croaker based on near infrared spectroscopy[J].Packaging Engineering, 2020, 41(17):1-6.
[11] GRAU R, SÁNCHEZ A J,GIRÓN J, et al. J.Nondestructive assessment of freshness in packaged sliced chicken breasts using SW-NIR spectroscopy[J].Food Research International, 2011, 44(1):331-337.
[12] 何鸿举, 蒋圣启, 王洋洋, 等.在线近红外光谱系统快速检测整块鸡胸肉菌落总数含量[J].食品工业科技, 2020, 41(16):232-237.
HE H J, JIANG S Q, WANG Y Y, et al.Rapid detection of total viable count in whole chicken breast by an online near-infrared spectroscopy system[J].Science and Technology of Food Industry, 2020, 41(16):232-237.
[13] 王建明, 李颖, 李祥辉, 等.傅里叶变换近红外技术在乳制品微生物鉴别中的应用研究[J].光谱学与光谱分析, 2016, 36(S1):56-57.
WANG J M, LI Y, LI X H, et al.Study on the identification of microorganisms in milk and dairy products by fourier transform near-infrared spectroscopy[J].Spectroscopy and Spectral Analysis, 2016, 36(S1):56-57.
[14] CÁMARA-MARTOS F, LOPES J A, MORENO-ROJAS A, et al.Detection and quantification of Escherichia coli and Pseudomonas aeruginosa in cow milk by near-infrared spectroscopy[J].International Journal of Dairy Technology, 2015, 68(3):357-365.
[15] 刘建学, 马凯旋, 韩四海, 等.食源性致病菌近红外光谱改进贝叶斯判别模型的建立[J].农产品加工, 2018(12):22-26.
LIU J X, MA K X, HAN S H, et al.Improved Bayes discriminant analysis on near infrared spectroscopy of food pathogens[J].Farm Products Processing, 2018(12):22-26.
[16] 沈飞, 魏颖琪, 张斌, 等.稻谷有害霉菌侵染的近红外光谱快速检测[J].光谱学与光谱分析, 2018, 38(12):3 748-3 752.
SHEN F, WEI Y Q, ZHANG B, et al.Rapid detection of harmful mold infection in rice by near infrared spectroscopy[J].Spectroscopy and Spectral analysis, 2018, 38(12):3 748-3 752.
[17] ZHANG Q, LIU C H, SUN J K, et al.Rapid non-destructive detection for molds colony of paddy rice based on near infrared spectroscopy[J].Journal of Northeast Agricultural University, 2014, 21(4):54-60.
[18] 刘鹏, 蒋雪松, 沈飞, 等.近红外光谱技术的花生产毒霉菌侵染快速检测[J].光谱学与光谱分析, 2017, 37(5):1 397-1 402.
LIU P, JIANG X S, SHEN F, et al.Rapid detection of toxigenic fungal contamination in peanuts with near infrared spectroscopy technology[J].Spectroscopy and Spectral Analysis, 2017, 37(5):1 397-1 402.
[19] 张亮. 扩展青霉和展青霉素的近红外检测技术研究[D].杨凌:西北农林科技大学, 2010.
ZHANG L.Application of near infrared spectroscopy on detection of Penicillium expansoum and patulin[D].Yangling:Northwest A&F University, 2010.
[20] 邢政. 菜籽粕固态发酵制备多肽过程主要参数的近红外光谱快速检测方法研究[D].镇江:江苏大学, 2019.
XING Z.Study on the near infrared spectroscopy rapid detection methods for main parameters of rapeseed meal solid-state fermentation for polypeptides preparation[D].Zhenjiang:Jiangsu University, 2019.
[21] 刘世凯, 李子琦, 张新乐.高光谱成像技术在食品安全检测方面的应用[J].食品安全导刊, 2015(6):124-126.
LIU S K, LI Z Q, ZHANG X L.Application of hyperspectral imaging technology in food safety detection [J].China Food Safety Magazine, 2015(6):124-126
[22] 王慧, 何鸿举, 刘璐, 等.高光谱成像在鱼肉品质无损检测中的研究进展[J].食品科学, 2019, 40(5):329-338.
WANG H, HE H J, LIU L, et al.Recent progress in hyperspectral imaging for nondestructive evaluation of fish quality[J].Food Science, 2019, 40(5):329-338.
[23] 郑彩英. 基于高光谱成像技术的冷却羊肉表面微生物活细胞数量无损检测方法研究[D].银川:宁夏大学,2014.
ZHENG C Y.Study on non-destructive assessment of microbial viable cells on chilled mutton surface based on hyperspectral imaging technology[D].Yinchuan:Ningxia University, 2014.
[24] 成军虎. 基于高光谱成像鱼肉新鲜度无损快速检测方法研究[D].广州:华南理工大学,2016.
CHENG J H.Non-destructive and rapid detection of fish freshness using hyperspectral imaging technique[D].Guangzhou:South China University of Technology, 2016.
[25] ACHATA E M, OLIVEIRA M, ESQUERRE C A, et al.Visible and NIR hyperspectral imaging and chemometrics for prediction of microbial quality of beef Longissimus dorsi muscle under simulated normal and abuse storage conditions[J].LWT,2020, 128:109463.
[26] TAO F F, PENG Y K.A method for nondestructive prediction of pork meat quality and safety attributes by hyperspectral imaging technique[J].Journal of Food Engineering, 2014, 126:98-106.
[27] 赵楠, 刘强, 魏康丽, 等.基于近红外高光谱成像技术的鸡蛋污染过程中菌落总数可视化研究[J].南京农业大学学报, 2019, 42(3):543-550.
ZHAO N, LIU Q, WEI K L, et al.Visualization of the total viable count of bacteria during the polluted process of eggs based on near infrared hyperspectral imaging technology[J].Journal of Nanjing Agricultural University, 2019, 42(3):543-550.
[28] 唐凯. 基于高光谱图像技术的茶叶霉菌菌落总数检测研究[D].镇江:江苏大学, 2018.
TANG K.Research on detection of total number of mold colonies in tea based on hyperspectral imaging technology[D].Zhenjiang:Jiangsu University, 2018.
[29] ZHAO X, WANG W, CHU X, et al.Early detection of Aspergillus parasiticus infection in maize kernels using near-infrared hyperspectral imaging and multivariate data analysis[J].Applied Sciences, 2017, 7(1):90.
[30] 王振杰. 计算机视觉对稻谷储藏霉变真菌的识别研究[D].南京:南京农业大学,2016.
WANG Z J.Identification of mildew fungi of storage paddy based on computer vision[D].Nanjing:Nanjing Agricultural University, 2016.
[31] MARTYNENKO A.Computer vision for real-time control in drying[J].Food Engineering Reviews,2017, 9(2):91-111.
[32] 殷涌光, 丁筠.基于计算机视觉的食品中大肠杆菌快速定量检测[J].吉林大学学报(工学版), 2009,39(S2):344-348.
YIN Y G, DING J.Rapid method for enumeration of Escherichia coli in food based on computer vision[J].Journal of Jilin University(Engineering and Technology Edition), 2009, 39(S2):344-348.
[33] 丁筠. 基于生物技术与计算机视觉的食品微生物快速检测研究[D].长春:吉林大学,2010.
DING J.Rapid detection research for microorganisms in food based on biotechnology and computer vision.[D].Changchun:Jilin University, 2010.
[34] 丁筠, 殷涌光, 王旻.蔬菜中大肠杆菌的机器视觉快速检测[J].农业机械学报, 2012,43(2):134-139;145.
DING J, YIN Y G, WANG M.Rapid detection based on machine vision for Escherichia coli in vegetables[J].Transactions of the Chinese Society for Agricultural Machinery, 2012,43(2):134-139;145.
[35] WANG Y, YIN Y G, ZHANG C N.Selective cultivation and rapid detection of staphylococcus aureus by Computer Vision[J].Journal of Food Science, 2014, 79(3):M399-M406.
[36] 王慧莹. 基于计算机视觉技术快速检测食品中蜡样芽孢杆菌的研究[D].长春:吉林大学, 2011.
WANG H Y.Research on rapid detection of Bacillus cereus in food by computer vision[D].Changchun:Jilin University, 2011.
[37] 王勇. 食品中三种致病菌的快速检测方法研究[D].长春:吉林大学, 2014.
WANG Y.Research on rapid detection method of three pathogenic bacteria in food[D].Changchun:Jilin University, 2014.
[38] SHEN F, HUANG Y, JIANG X S, et al.On-line prediction of hazardous fungal contamination in stored maize by integrating Vis/NIR spectroscopy and computer vision[J].Spectrochimica Acta Part A:Molecular and Biomolecular Spectroscopy, 2020,229:118012.
[39] 张楠楠, 刘伟, 王伟, 等.玉米霉变及黄曲霉毒素的图像处理检测方法[J].中国粮油学报, 2014, 29(2):82-88.
ZHANG N N, LIU W, WANG W, et al.Image processing method of corn kernels mildew infection and aflatoxin levels[J].Journal of the Chinese Cereals and Oils Association, 2014, 29(2):82-88.
[40] 顾欣哲.基于电子鼻响应信息的猪肉假单胞菌生长预测模型的构建[D].南京:南京农业大学, 2017.
GU X Z.Constructing the predictive growth model of Pseudomonas in pork based on electronic nose[D].Nanjing:Nanjing Agricultural University, 2017.
[41] 韩方凯. 基于味觉传感的鱼类食用安全性检测新技术研究[D].镇江:江苏大学, 2015.
HAN F K.Research on novel detection techniques for fish edible safety based on taste sensors[D].Zhenjiang:Jiangsu University, 2015.
[42] WANG D F, WANG X C, LIU T A, et al.Prediction of total viable counts on chilled pork using an electronic nose combined with support vector machine.[J].Meat Science, 2012, 90(2):373-377.
[43] CHEN Q S, HU W W, SU J, et al.Nondestructively sensing of total viable count (TVC) in chicken using an artificial olfaction system based colorimetric sensor array[J].Journal of Food Engineering, 2016,168:259-266.
[44] 贾哲, 陈晓婷, 潘南, 等.基于电子舌快速检测冷藏双斑东方鲀的新鲜度[J].现代食品科技, 2021, 37(5):220-229.
JIA Z, CHEN X T, PAN N, et al.The freshness of frozen fugu bimaculatus was detected by electronic tongu[J].Modern Food Science and Technology, 2021, 37(5):220-229.
[45] 陈丽萍,徐茂琴,何红萍,等.应用PEN3型电子鼻传感器快速检测食源性致病菌[J].食品科学,2014, 35(8):187-192.
CHEN L P, XU M Q, HE H P, et al.Application of PEN3 electronic nose sensor for rapid detection of food-borne pathogenic bacteria[J].Food Science, 2014, 35(8):187-192.
[46] GOBBI E, FALASCONI M, ZAMBOTTI G, et al.Rapid diagnosis of Enterobacteriaceae in vegetable soups by a metal oxide sensor based electronic nose[J].Sensors & Actuators:B.Chemical, 2015, 207:1 104-1 113.
[47] ABDALLAH S A, AL-SHATTI L A, ALHAJRAF A F, et al.The detection of foodborne bacteria on beef:the application of the electronic nose[J].SpringerPlus, 2013, 2:687.
[48] 吴启芳. 稻米黄曲霉毒素污染的电子鼻和红外光谱快速无损检测方法研究[D].南京:南京财经大学,2016.
WU Q F.Rapid non-destructive inspection of aflatoxins in rice based on electronic nose and infrared spectroscopy[D].Nanjing:Nanjing University of Finance and Economics, 2016.
[49] 沈飞, 刘鹏, 蒋雪松, 等.基于电子鼻的花生有害霉菌种类识别及侵染程度定量检测[J].农业工程学报,2016,32(24):297-302.
SHEN F, LIU P, JIANG X S, et al.Recognition of harmful fungal species and quantitative detection of fungal contamination in peanuts based on electronic nose technology[J].Transactions of the Chinese Society of Agricultural Engineering, 2016, 32(24):297-302.
[50] 郑飞翔, 李剑, 楼雄伟, 等.基于电子鼻的霉变黄豆和白芸豆检测方法[J].中国食品学报,2016, 16(3):190-197.
ZHENG F X, LI J, LOU X W, et al.Detection methods of moldy soybean and white kidney bean using electronic nose[J].Journal of Chinese Institute of Food Science and Technology,2016, 16(3):190-197.
[51] 朱娜, 毛淑波, 潘磊庆, 等.电子鼻对草莓采后贮藏早期霉菌感染的检测[J].农业工程学报, 2013, 29(5):266-273.
ZHU N, MAO S B, PAN L Q, et al.Early detection of fungal disease infection in strawberry fruits by e-nose during postharvest storage[J].Transactions of the Chinese Society of Agricultural Engineering,2013, 29(5):266-273.
