近红外光谱定量和定性分析技术在鲜食葡萄果实无损检测中的应用
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摘要
选取10种不同鲜食葡萄品种、3个不同成熟期和1种病害的果实共计188个葡萄果实样品,并采集果实样品的近红外光谱。建立了以葡萄果实的总酚、总糖、果糖、蔗糖和可溶性固形物为指标的偏最小二乘(PLS)定量分析模型,模型的可信度较高,除少数指标的相关系数在0.77~0.89,其余指标均在0.90以上,均方根误差在0.022~1.410。结合主成分分析法,对谱区为4 119.20~9 881.46 cm~(-1)的光谱建立了区分葡萄果实品种、成熟度和是否受病害的判别分析(DA)模型,模型的正识率依次为92.11%、88.89%和96.15%。研究表明,近红外检测技术可用于鲜食葡萄果实的5个主要内含物的定量分析以及果实品种、果实成熟度和有病虫害的二次果进行的定性识别。
Ten different varieties of fresh grapes,3 different mature period and 1 kind of diseased fruit with a total of188 samples were selected as the research object,and the near infrared spectra of these samples collected by near-infrared spectrometers. Using partial least squares( PLS),the quantitative analysis model with higher credibility by determining the content of total phenol,total sugar,fructose,sucrose and soluble solids. The correlation coefficients of indicators were above 0. 90 except minority were between 0. 77 and 0. 89,and root mean square error were all between 0. 022 and 1. 410. By combining with principal component analysis in 4 199. 20 ~ 9 881. 46 cm~(-1) spectral region,the discriminant analysis( DA) model with correctness of 92. 11%,88. 89% and 96. 15% for variety identification,maturity identification and diseased fruit identification respectively has been established. This study showed that near infrared detection technology can not only be used for quantitative analysis of 5 main inclusions in fresh grape,but also be used for identification of varieties,maturity and diseased fruit of fresh grape.
Ten different varieties of fresh grapes,3 different mature period and 1 kind of diseased fruit with a total of188 samples were selected as the research object,and the near infrared spectra of these samples collected by near-infrared spectrometers. Using partial least squares( PLS),the quantitative analysis model with higher credibility by determining the content of total phenol,total sugar,fructose,sucrose and soluble solids. The correlation coefficients of indicators were above 0. 90 except minority were between 0. 77 and 0. 89,and root mean square error were all between 0. 022 and 1. 410. By combining with principal component analysis in 4 199. 20 ~ 9 881. 46 cm~(-1) spectral region,the discriminant analysis( DA) model with correctness of 92. 11%,88. 89% and 96. 15% for variety identification,maturity identification and diseased fruit identification respectively has been established. This study showed that near infrared detection technology can not only be used for quantitative analysis of 5 main inclusions in fresh grape,but also be used for identification of varieties,maturity and diseased fruit of fresh grape.
引文
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[13]牛晓颖,邵利敏,赵志磊,等.基于BP-ANN的草莓品种近红外光谱无损鉴别方法研究[J].光谱学与光谱分析,2012,32(8):2095-2099.NIU X Y,SHAO L M,ZHAO Z L,et al.Nondestructive discrimination of strawberry varieties by NIR and BP-ANN[J].Spectroscopy and Spectral Analysis,2012,32(8):2095-2099.(in Chinese with English abstract)
[14]闫润,王新忠,张莹莹.基于神经网络及近红外光谱的草莓成熟度快速识别方法[J].安徽农业科学,2012,40(10):6292-6294.YAN R,WANG X Z,ZHANG Y Y.Fast recognition method of strawberries'maturity level based on neural network and near infrared spectra[J].Journal of Anhui Agricultural Sciences,2012,40(10):6292-6294.(in Chinese with English abstract)
[15]BOVO B,MARCHI M D,CARLOT M,et al.Indirect evaluation of microbial spoiling activity in grape marcs by near-infrared spectroscopy[J].American Journal of Enology&Viticulture,2013,64(3):411-415.
[16]COZZOLINO D,CYNKAR W,SHAH N,et al.Quantitative analysis of minerals and electric conductivity of red grape homogenates by near infrared reflectance spectroscopy[J].Computers&Electronics in Agriculture,2011,77(1):81-85.
[17]吴桂芳,黄凌霞,何勇.葡萄浆果糖度可见/近红外光谱检测的研究[J].光谱学与光谱分析,2008,28(9):2090-2093.WU G F,HUANG L X,HE Y.Research on the sugar content measurement of grape and berries by using Vis/NIR spectroscopy technique[J].Spectroscopy and Spectral Analysis,2008,28(9):2090-2093.(in Chinese with English abstract)
[18]FADOCK M,BROWN R B,REYNOLDS A G.Visible-near infrared reflectance spectroscopy for nondestructive analysis of red winegrapes[J].American Journal of Enology&Viticulture,2016,67:38-46.
[19]蔡正云,吴龙国,王菁,等.宁夏赤霞珠葡萄水分含量的高光谱无损检测研究[J].食品工业科技,2017,38(2):79-83.CAI Z Y,WU L G,WANG J,et al.Non-destructive determination of moisture composition in Ningxia wine grapes based on visible near-infrared hyperspectral imaging technique[J].Science and Technology of Food Industry,2017,38(2):79-83.(in Chinese with English abstract)
[20]李瑞,傅隆生.基于高光谱图像的蓝莓糖度和硬度无损测量[J].农业工程学报,2017,33(增刊1):362-366.LI R,FU L S.Nondestructive measurement of firmness and sugar content of blueberries based on hyperspectral imaging[J].Transactions of the Chinese Society of Agricultural Engineering,2017,33(S1):362-366.(in Chinese with English abstract)
[2]GUIDETTI R,BEGHI R,BO L.Evaluation of grape quality parameters by a simple VIS/NIR system[J].Transactions of the Asabe,2010,53:477-484.
[3]CAYUELA J A.Prediction of intact nectarine quality using a Vis/NIR portable spectrometer[J].Inderscience Publishers,2011,2:131-144.
[4]杨帆,李雅婷,顾轩,等.便携式近红外光谱仪测定苹果酸度和抗坏血酸的研究[J].光谱学与光谱分析,2011,31(9):2386-2389.YANG F,LI Y T,GU X,et al.Determination of acidity and vitamin c in apples using portable NIR analyzer[J].Spectroscopy and Spectral Analysis,2011,31(9):2386-2389.(in Chinese with English abstract)
[5]王铭海,郭文川,谷静思,等.成熟期梨可溶性固形物含量的近红外漫反射光谱无损检测[J].西北农林科技大学学报(自然科学版),2013,41(12):113-119.WANG M H,GUO W C,GU J S,et al.Nondestructive detection of pears'soluble solid content in ripening period based on near infrared diffused spectroscopy[J].Journal of Northwest A&F University(Natural Science Edition),2013,41(12):113-119.(in Chinese with English abstract)
[6]付苗苗,刘梅英,牛智有,等.基于近红外光谱法的水稻秸秆可溶性糖快速检测[J].华中农业大学学报,2016(2):115-121.FU M M,LIU M Y,NIU Z Y,et al.Rapidly detecting the content of soluble sugar in rice straw with near infrared reflectance spectroscopy[J].Journal of Huazhong Agricultural University,2016(2):115-121.(in Chinese with English abstract)
[7]罗曦,吴方喜,谢鸿光,等.近红外光谱的水稻抗性淀粉含量测定研究[J].光谱学与光谱分析,2016,36(3):697-701.LUO X,WU F X,XIE H G,et al.Research on resistant starch content of rice grain based on NIR spectroscopy model[J].Spectroscopy and Spectral Analysis,2016,36(3):697-701.(in Chinese with English abstract)
[8]艾施荣,刘木华.遗传算法结合区间偏最小二乘法在草莓酸度近红外光谱检测的研究[J].江西农业大学学报,2010,32(3):633-636.AI S R,LIU M H.Nondestructive measurement of acidity in strawberry using genetic algorithm and NIR spectroscopy[J].Acta Agriculturae Universitis Jiangxiensis,2010,32(3):633-636.(in Chinese with English abstract)
[9]刘燕德,施宇,蔡丽君,等.基于CARS算法的脐橙可溶性固形物近红外在线检测[J].农业机械学报,2013,44(9):138-144.LIU Y D,SHI Y,CAI L J,et al.On-line NIR detection model optimization of soluble solids content in navel orange based on CARS[J].Transactions of the Chinese Society of Agricultural Machinery,2013,44(9):138-144.(in Chinese with English abstract)
[10]朱亨银,傅霞萍,游贵荣,等.近红外光谱定性与定量分析技术在莲子无损检测中的应用[J].光谱学与光谱分析,2015,35(10):2752-2756.ZHU H Y,FU X P,YOU G R,et al.Application of NIR spectroscopy for nondestructive qualitative and quantitative analysis of lotus seeds[J].Spectroscopy and Spectral Analysis,2015,35(10):2752-2756.(in Chinese with English abstract)
[11]康志亮,陈韵羽,王思,等.便携式受损水果检测装置的设计[J].农机化研究,2010,32(12):52-56.KANG Z L,CHEN Y Y,WANG S,et al.Design of portable detector for damaged fruit[J].Journal of Agricultural Mechanization Research,2010,32(12):52-56.(in Chinese with English abstract)
[12]郭文川,王铭海,岳绒.基于近红外漫反射光谱的损伤猕猴桃早期识别[J].农业机械学报,2013,44(2):142-146.GUO W C,WANG M H,YUE R.Early recognition of bruised kiwifruit based on near infrared diffuse reflectance spectroscopy[J].Transactions of The Chinese Society of Agricultural Machinery,2013,44(2):142-146.(in Chinese with English abstract)
[13]牛晓颖,邵利敏,赵志磊,等.基于BP-ANN的草莓品种近红外光谱无损鉴别方法研究[J].光谱学与光谱分析,2012,32(8):2095-2099.NIU X Y,SHAO L M,ZHAO Z L,et al.Nondestructive discrimination of strawberry varieties by NIR and BP-ANN[J].Spectroscopy and Spectral Analysis,2012,32(8):2095-2099.(in Chinese with English abstract)
[14]闫润,王新忠,张莹莹.基于神经网络及近红外光谱的草莓成熟度快速识别方法[J].安徽农业科学,2012,40(10):6292-6294.YAN R,WANG X Z,ZHANG Y Y.Fast recognition method of strawberries'maturity level based on neural network and near infrared spectra[J].Journal of Anhui Agricultural Sciences,2012,40(10):6292-6294.(in Chinese with English abstract)
[15]BOVO B,MARCHI M D,CARLOT M,et al.Indirect evaluation of microbial spoiling activity in grape marcs by near-infrared spectroscopy[J].American Journal of Enology&Viticulture,2013,64(3):411-415.
[16]COZZOLINO D,CYNKAR W,SHAH N,et al.Quantitative analysis of minerals and electric conductivity of red grape homogenates by near infrared reflectance spectroscopy[J].Computers&Electronics in Agriculture,2011,77(1):81-85.
[17]吴桂芳,黄凌霞,何勇.葡萄浆果糖度可见/近红外光谱检测的研究[J].光谱学与光谱分析,2008,28(9):2090-2093.WU G F,HUANG L X,HE Y.Research on the sugar content measurement of grape and berries by using Vis/NIR spectroscopy technique[J].Spectroscopy and Spectral Analysis,2008,28(9):2090-2093.(in Chinese with English abstract)
[18]FADOCK M,BROWN R B,REYNOLDS A G.Visible-near infrared reflectance spectroscopy for nondestructive analysis of red winegrapes[J].American Journal of Enology&Viticulture,2016,67:38-46.
[19]蔡正云,吴龙国,王菁,等.宁夏赤霞珠葡萄水分含量的高光谱无损检测研究[J].食品工业科技,2017,38(2):79-83.CAI Z Y,WU L G,WANG J,et al.Non-destructive determination of moisture composition in Ningxia wine grapes based on visible near-infrared hyperspectral imaging technique[J].Science and Technology of Food Industry,2017,38(2):79-83.(in Chinese with English abstract)
[20]李瑞,傅隆生.基于高光谱图像的蓝莓糖度和硬度无损测量[J].农业工程学报,2017,33(增刊1):362-366.LI R,FU L S.Nondestructive measurement of firmness and sugar content of blueberries based on hyperspectral imaging[J].Transactions of the Chinese Society of Agricultural Engineering,2017,33(S1):362-366.(in Chinese with English abstract)