基于近红外光谱技术的蔬菜农药残留种类检测
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摘要
该文基于近红外光谱技术,提出一种快速无损检测方法,以期实现蔬菜农药残留的分类检测。通过对喷洒了氰戊菊酯溶液、三唑磷溶液和未喷洒农药的生菜样本进行研究,比较不同预处理后的建模效果,选用SNV算法作为最优预处理方法。分别采用连续投影算法(SPA)、自主软收缩法(BOSS)和竞争性自适应重加权算法(CARS)对预处理后的光谱数据进行特征波段选择。采用支持向量机(SVM)和基于灰狼算法(GWO)优化的支持向量机(SVM)算法对特征波长变量分别建立分类模型。再通过对建立的模型进行比较得出:CARS-GWO-SVM模型取得了最佳的分类效果,模型的训练集精度和预测集精度均为100%。因此,利用近红外光谱技术对蔬菜上的农药残留进行分类检测是可行的。该研究为生菜中其他农药残留的快速无损检测分析提供参考。
Based on near-infrared spectroscopy,a non-destructive testing method to achieve rapid and non-destructive classification of pesticide residues on vegetables was proposed. It hope to realize the classification and detection of pesticide residues on vegetables. By studing the lettuce samples sprayed with cypermethrin solution,triazophos solution and unsprayed pesticide,the modeling effects of different pretreatments were compared,and SNV algorithm was chosen as the optimal pre-processing method for this study. In this study,the successive projection algorithm( SPA),the bootstrapping soft shrinkage( BOSS) and the competitive adaptive reweighted sampling( CARS) were used to select the characteristic bands of the preprocessed spectral data.A support vector machine( SVM) and the support vector machine( SVM) algorithm based on Grey wolf optimization( GWO)optimization were used to establish a classification model of characteristic wavelength variables. The results showed that the CARS-GWO-SVM model achieved the best classification influence,and the accuracy of training set and the accuracy of prediction set were both 100%. Therefore,it is feasible to use NIR spectroscopy to classify pesticide residues on vegetables. This study also provided a reference for the rapid,non-destructive analysis of other pesticide residues in lettuce.
Based on near-infrared spectroscopy,a non-destructive testing method to achieve rapid and non-destructive classification of pesticide residues on vegetables was proposed. It hope to realize the classification and detection of pesticide residues on vegetables. By studing the lettuce samples sprayed with cypermethrin solution,triazophos solution and unsprayed pesticide,the modeling effects of different pretreatments were compared,and SNV algorithm was chosen as the optimal pre-processing method for this study. In this study,the successive projection algorithm( SPA),the bootstrapping soft shrinkage( BOSS) and the competitive adaptive reweighted sampling( CARS) were used to select the characteristic bands of the preprocessed spectral data.A support vector machine( SVM) and the support vector machine( SVM) algorithm based on Grey wolf optimization( GWO)optimization were used to establish a classification model of characteristic wavelength variables. The results showed that the CARS-GWO-SVM model achieved the best classification influence,and the accuracy of training set and the accuracy of prediction set were both 100%. Therefore,it is feasible to use NIR spectroscopy to classify pesticide residues on vegetables. This study also provided a reference for the rapid,non-destructive analysis of other pesticide residues in lettuce.
引文
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[4]李爽,郭翔宇,钱巍.技术性贸易壁垒对我国蔬菜出口贸易影响的实证分析[J].农业技术经济,2008(6):79-85.LI Shuang,GUO Xiangyu,QIAN Wei. Empirical analysis on the impact of technical barriers to China's vegetable exports trade[J].Journal of Agrotechnical Economics,2008(6):79-85.
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[7]郭培源,刘硕,杨昆程,等.色谱技术、光谱分析法和生物检测技术在食品安全检测方面的应用进展[J].食品安全质量检测学报,2015(8):3 217-3 223.GUO Peiyuan, LIU Shuo, YANG Kuncheng, et al. Progress in food safety detection using chromatographic techniques,spectroscopic techniques,and biological detection technology[J]. Journal of Food Safety&Quality,2015(8):3 217-3 223.
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[9]蒋雪松,王维琴,许林云,等.农产品/食品中农药残留快速检测方法研究进展[J].农业工程学报,2016,32(20):267-274.JIANG Xuesong,WANG Weiqin,XU Yunlin, et al. Review on rapid detection of pesticide residues in agricultural and food products[J]. Transactions of the Chinese Society of Agricultural Engineering,2016,32(20):267-274.
[10] TIONG Gim Aw,SAMANTHA Wengert,JOAN B Rose. Metagenomic analysis of viruses associated with field-grown and retail lettuce identifies human and animal viruses[J]. International Journal of Food Microbiology,2016,223:50-56.
[11]李志刚,贾策,王晓闻,等.牛肉质构特性的近红外光谱无损检测[J].农业工程学报,2016,32(16):286-292.LI Zhigang,JIA Ce,WANG Xiaowen,et al. Nondestructive determination of beef textural properties by near infrared spectroscopy[J]. Transactions of the Chinese Society of Agricultural Engineering,2016,32(16):286-292.
[12] PRACHI Sharma,SUSHEEL Sharma,JASVIR Singh,et al. Incidence of lettuce mosaic virus in lettuce and its detection by polyclonal antibodies produced against recombinant coat protein expressed in Escherichia coli[J]. Journal of Virological Methods,2016,230:53-58.
[13]胡耀华,李清宇,唐翊.基于高光谱的晚疫病胁迫下马铃薯叶片的过氧化物酶活性检测[J].江苏大学学报(自然科学版),2018,39(6):683-688.HU Yaohua,LI Qingyu,TANG Xu. Detection of peroxidase activity in potato leaves under stress of late blight using hyperspectral imaging[J]. Journal of Jiangsu University(Natural Science Edition),2018,39(6):683-688.
[14]徐广通,袁洪福,陆婉珍.现代近红外光谱技术及应用进展[J].光谱学与光谱分析,2000,20(2):134-142.XU Guangtong, YUAN Hongfu, LU Wanzheng. Development of modern near infrared spectroscopic techniques and its applications[J]. Spectroscopy and Spectral Analysis,2000,20(2):134-142.
[15]陈蕊,张骏,李晓龙.蔬菜表面农药残留可见-近红外光谱探测与分类识别研究[J].光谱学与光谱分析,2012,32(5):1 230-1 233.CHEN Rui,ZHANG Jun,LI Xiaolong. Study on the detection and pattern classification of pesticide residual on vegetable surface by using visible/near-infrared spectroscopy[J]. Spectroscopy and Spectral Analysis,2012,32(5):1 230-1 233.
[16]张令标,何建国,刘贵珊,等.基于可见/近红外高光谱成像技术的番茄表面农药残留无损检测[J].食品与机械,2014,30(1):82-85.ZHANG Lingbiao,HE Jianguo,LIU Guishan,et al. Detection of pesticide residue on cherry tomatoes by hyperspectral image technology[J]. Food&Machinery,2014,30(1):82-85.
[17]李建东,杨薇,贾晶霞,等.基于近红外光谱扫描的马铃薯内部品质检测装置设计[J].农业工程,2015,5(1):74-75.LI Jiandong,YANG Wei,JIA Jingxia,et al. Design on checking device of potato inside quality based on near-infrared light spectrum scanning[J]. Agricultural Engineering,2015,5(1):74-75.
[18]虞轶俊,吴声敢,于国光,等.新版食品中农药最大残留限量国家标准研究[J].农产品质量与安全,2014(4):37-40.
[19] LONG Qian,LI Haitao, ZHANG Youyu, et al. Upconversion nanoparticle-based fluorescence resonance energy transfer assay for organophosphorus pesticides[J]. Biosensors and Bioelectronics,2015(68):168-174.
[20]侯培国,李宁,常江,等. SG平滑和IBPLS联合优化水中油分析方法的研究[J].光谱学与光谱分析,2015,35(6):1 529-1 533.HOU Peiguo,LI Ning,CHANG Jiang,et al. Research on analysis of oil in water based on the joint optimization of Savitzky-Golay smoothing and IBPLS models[J]. Spectroscopy and Spectral Analysis,2015,35(6):1 529-1 533.
[21] GUO Ying,NI Yongnian,SERGE Kokot. Evaluation of chemical components and properties of the jujube fruit using near infrared spectroscopy and chemometrics[J]. Spectrochimica Acta Part A:Molecular and Biomolecular Spectroscopy,2016(153):79-86.
[22] TOM Fearn,CECILIA Riccioli,ANA Garrido-Varo,et al. On the geometry of SNV and MSC[J]. Chemometrics and Intelligent Laboratory Systems,2008,96(1):22-26.
[23]王动民,纪俊敏,高洪智.多元散射校正预处理波段对近红外光谱定标模型的影响[J].光谱学与光谱分析,2014,34(9):2 387-2 390.WANG Dongmin,JI Junming,GAO Hongzhi. The effect of MSC spectral pretreatment regions on near infrared spectroscopy calibration results[J]. Spectroscopy and Spectral Analysis,2014,34(9):2 387-2 390.
[24]高洪智,卢启鹏,丁海泉,等.基于连续投影算法的土壤总氮近红外特征波长的选取[J].光谱学与光谱分析,2009,29(11):2 951-2 954.GAO Hongzhi, LU Qipeng, DING Haiquan, et al. Choice of characteristic near-infrared wavelengths for soil Total nitrogen based on successive projection algorithm[J]. Spectroscopy and Spectral Analysis,2009,29(11):2 951-2 954.
[25] DENG Baichuan,YUN Yonghuan,CAO Dongsheng, et al. A bootstrapping soft shrinkage approach for variable selection in chemical modeling[J]. Analytica Chimica Acta,2016(908):63-74.
[26]于雷,洪永胜,周勇,等.高光谱估算土壤有机质含量的波长变量筛选方法[J].农业工程学报,2016,32(13):95-102.YU Lei,HONG Yongsheng,ZHOU Yong,et al. Wavelength variable selection methods for estimation of soil organic matter content using hyperspectral technique[J]. Transactions of the Chinese Society of Agricultural Engineering,2016,32(13):95-102.
[27]王璨,李志伟.利用融合高度与单目图像特征的支持向量机模型识别杂草[J].农业工程学报,2016,32(15):165-174.WANG Can,LI Zhiwei. Weed recognition using SVM model with fusion height and monocular image features[J]. Transactions of the Chinese Society of Agricultural Engineering,2016,32(15):165-174.
[28]唐美丽,张劲松,李璐,等.基于GPU的SVM参数优化并行算法[J].江苏大学学报(自然科学版),2017,38(5):576-581.TANG Meili,ZHANG Jinsong,LI Lu, et al. Optimization algorithm of SVM parallel parameters based on GPU[J]. Journal of Jiangsu University(Natural Science Edition), 2017, 38(5):576-581.
[29] SEYEDALI Mirjalili,SEYED Mohammad Mirjalili,ANDREW Lewis. Grey wolf optimizer[J]. Advances in Engineering Software,2014,69(3):46-61.
[2]王洁莲,张琳.山西省叶菜类蔬菜农残检测结果及治理对策[J].农业工程,2017,7(4):84-86.WANG Jielian,ZHANG Lin. Results and countermeasures of leaft vegetables pesticide residue testing in Shanxi province[J]. Agricultural Engineering,2017,7(4):84-86.
[3]惠媛,张丽.蔬菜中农药残留的危害及预防措施[J].农业科技与信息,2017(18):45-46.
[4]李爽,郭翔宇,钱巍.技术性贸易壁垒对我国蔬菜出口贸易影响的实证分析[J].农业技术经济,2008(6):79-85.LI Shuang,GUO Xiangyu,QIAN Wei. Empirical analysis on the impact of technical barriers to China's vegetable exports trade[J].Journal of Agrotechnical Economics,2008(6):79-85.
[5]谢一凡,刘慧中,杨若林,等.高效液相色谱法在仪器分析实验教学中的应用[J].化学教育(中英文),2017,38(2):52-54.XIE Yifan,LIU Huizhong,YANG Ruolin, et al. Application of HPLC in teachingof instrumental analysis experiment[J]. Chinese Journal of Chemical Education,2017,38(2):52-54.
[6]张伟国,储晓刚,李重九.气相色谱/离子阱质谱-选择离子方法同时检测大米中百种农药残留[J].分析化学,2006,34(4):484-488.ZHANG Weiguo, CHU Xiaogang, LI Chongjiu. Multi-residue method for simultaneous analysis of 107 pesticides in rice by gas chromatography/mass spectrometry[J]. Chinese Journal of Analytical Chemistry,2006,34(4):484-488.
[7]郭培源,刘硕,杨昆程,等.色谱技术、光谱分析法和生物检测技术在食品安全检测方面的应用进展[J].食品安全质量检测学报,2015(8):3 217-3 223.GUO Peiyuan, LIU Shuo, YANG Kuncheng, et al. Progress in food safety detection using chromatographic techniques,spectroscopic techniques,and biological detection technology[J]. Journal of Food Safety&Quality,2015(8):3 217-3 223.
[8]李岩.食品检验中生物检测技术应用的分析[J].中国医药指南,2012,10(13):369-370.
[9]蒋雪松,王维琴,许林云,等.农产品/食品中农药残留快速检测方法研究进展[J].农业工程学报,2016,32(20):267-274.JIANG Xuesong,WANG Weiqin,XU Yunlin, et al. Review on rapid detection of pesticide residues in agricultural and food products[J]. Transactions of the Chinese Society of Agricultural Engineering,2016,32(20):267-274.
[10] TIONG Gim Aw,SAMANTHA Wengert,JOAN B Rose. Metagenomic analysis of viruses associated with field-grown and retail lettuce identifies human and animal viruses[J]. International Journal of Food Microbiology,2016,223:50-56.
[11]李志刚,贾策,王晓闻,等.牛肉质构特性的近红外光谱无损检测[J].农业工程学报,2016,32(16):286-292.LI Zhigang,JIA Ce,WANG Xiaowen,et al. Nondestructive determination of beef textural properties by near infrared spectroscopy[J]. Transactions of the Chinese Society of Agricultural Engineering,2016,32(16):286-292.
[12] PRACHI Sharma,SUSHEEL Sharma,JASVIR Singh,et al. Incidence of lettuce mosaic virus in lettuce and its detection by polyclonal antibodies produced against recombinant coat protein expressed in Escherichia coli[J]. Journal of Virological Methods,2016,230:53-58.
[13]胡耀华,李清宇,唐翊.基于高光谱的晚疫病胁迫下马铃薯叶片的过氧化物酶活性检测[J].江苏大学学报(自然科学版),2018,39(6):683-688.HU Yaohua,LI Qingyu,TANG Xu. Detection of peroxidase activity in potato leaves under stress of late blight using hyperspectral imaging[J]. Journal of Jiangsu University(Natural Science Edition),2018,39(6):683-688.
[14]徐广通,袁洪福,陆婉珍.现代近红外光谱技术及应用进展[J].光谱学与光谱分析,2000,20(2):134-142.XU Guangtong, YUAN Hongfu, LU Wanzheng. Development of modern near infrared spectroscopic techniques and its applications[J]. Spectroscopy and Spectral Analysis,2000,20(2):134-142.
[15]陈蕊,张骏,李晓龙.蔬菜表面农药残留可见-近红外光谱探测与分类识别研究[J].光谱学与光谱分析,2012,32(5):1 230-1 233.CHEN Rui,ZHANG Jun,LI Xiaolong. Study on the detection and pattern classification of pesticide residual on vegetable surface by using visible/near-infrared spectroscopy[J]. Spectroscopy and Spectral Analysis,2012,32(5):1 230-1 233.
[16]张令标,何建国,刘贵珊,等.基于可见/近红外高光谱成像技术的番茄表面农药残留无损检测[J].食品与机械,2014,30(1):82-85.ZHANG Lingbiao,HE Jianguo,LIU Guishan,et al. Detection of pesticide residue on cherry tomatoes by hyperspectral image technology[J]. Food&Machinery,2014,30(1):82-85.
[17]李建东,杨薇,贾晶霞,等.基于近红外光谱扫描的马铃薯内部品质检测装置设计[J].农业工程,2015,5(1):74-75.LI Jiandong,YANG Wei,JIA Jingxia,et al. Design on checking device of potato inside quality based on near-infrared light spectrum scanning[J]. Agricultural Engineering,2015,5(1):74-75.
[18]虞轶俊,吴声敢,于国光,等.新版食品中农药最大残留限量国家标准研究[J].农产品质量与安全,2014(4):37-40.
[19] LONG Qian,LI Haitao, ZHANG Youyu, et al. Upconversion nanoparticle-based fluorescence resonance energy transfer assay for organophosphorus pesticides[J]. Biosensors and Bioelectronics,2015(68):168-174.
[20]侯培国,李宁,常江,等. SG平滑和IBPLS联合优化水中油分析方法的研究[J].光谱学与光谱分析,2015,35(6):1 529-1 533.HOU Peiguo,LI Ning,CHANG Jiang,et al. Research on analysis of oil in water based on the joint optimization of Savitzky-Golay smoothing and IBPLS models[J]. Spectroscopy and Spectral Analysis,2015,35(6):1 529-1 533.
[21] GUO Ying,NI Yongnian,SERGE Kokot. Evaluation of chemical components and properties of the jujube fruit using near infrared spectroscopy and chemometrics[J]. Spectrochimica Acta Part A:Molecular and Biomolecular Spectroscopy,2016(153):79-86.
[22] TOM Fearn,CECILIA Riccioli,ANA Garrido-Varo,et al. On the geometry of SNV and MSC[J]. Chemometrics and Intelligent Laboratory Systems,2008,96(1):22-26.
[23]王动民,纪俊敏,高洪智.多元散射校正预处理波段对近红外光谱定标模型的影响[J].光谱学与光谱分析,2014,34(9):2 387-2 390.WANG Dongmin,JI Junming,GAO Hongzhi. The effect of MSC spectral pretreatment regions on near infrared spectroscopy calibration results[J]. Spectroscopy and Spectral Analysis,2014,34(9):2 387-2 390.
[24]高洪智,卢启鹏,丁海泉,等.基于连续投影算法的土壤总氮近红外特征波长的选取[J].光谱学与光谱分析,2009,29(11):2 951-2 954.GAO Hongzhi, LU Qipeng, DING Haiquan, et al. Choice of characteristic near-infrared wavelengths for soil Total nitrogen based on successive projection algorithm[J]. Spectroscopy and Spectral Analysis,2009,29(11):2 951-2 954.
[25] DENG Baichuan,YUN Yonghuan,CAO Dongsheng, et al. A bootstrapping soft shrinkage approach for variable selection in chemical modeling[J]. Analytica Chimica Acta,2016(908):63-74.
[26]于雷,洪永胜,周勇,等.高光谱估算土壤有机质含量的波长变量筛选方法[J].农业工程学报,2016,32(13):95-102.YU Lei,HONG Yongsheng,ZHOU Yong,et al. Wavelength variable selection methods for estimation of soil organic matter content using hyperspectral technique[J]. Transactions of the Chinese Society of Agricultural Engineering,2016,32(13):95-102.
[27]王璨,李志伟.利用融合高度与单目图像特征的支持向量机模型识别杂草[J].农业工程学报,2016,32(15):165-174.WANG Can,LI Zhiwei. Weed recognition using SVM model with fusion height and monocular image features[J]. Transactions of the Chinese Society of Agricultural Engineering,2016,32(15):165-174.
[28]唐美丽,张劲松,李璐,等.基于GPU的SVM参数优化并行算法[J].江苏大学学报(自然科学版),2017,38(5):576-581.TANG Meili,ZHANG Jinsong,LI Lu, et al. Optimization algorithm of SVM parallel parameters based on GPU[J]. Journal of Jiangsu University(Natural Science Edition), 2017, 38(5):576-581.
[29] SEYEDALI Mirjalili,SEYED Mohammad Mirjalili,ANDREW Lewis. Grey wolf optimizer[J]. Advances in Engineering Software,2014,69(3):46-61.