便携式葡萄专用可见-近红外光谱检测仪器开发与实验
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摘要
基于可见-近红外光谱技术,研发低成本、便携式葡萄专用多参数检测仪器,用于满足葡萄采后品质快速、无损的检测需求。本仪器选用凹面全息光栅搭配电荷耦合器件的光谱仪作为核心器件,用于获取样品400～1 100 nm的漫反射光谱数据;选用卤素灯作为稳定可靠的光源、低OH的Y型石英光纤作为光传输的可靠媒介,并设计可调型样品池满足不同大小和品种样品的需求,基于Windows系统采用C#撰写的软件性能稳定,便于模型的更新操作。以"美人指"、"白玉霓"两个葡萄品种进行实验,指标参数包含CIE L*a*b*、可溶性固形物含量及总酚含量。结果显示,本仪器基于最小二乘-支持向量机模型对2个品种的a*值、可溶性固形物、总酚有较好的建模效果,"美人指"各指标的模型决定系数(R_c~2)分别为0.91、0.94和0.90;"白玉霓"各指标的模型决定系数分别为0.96、0.99和0.95。最后,利用70个非建模葡萄样本模型进行外部测试,结果表明"美人指"的a*值、可溶性固形物、总酚3个指标的预测根均方误差分别为3.15、1.39°Brix和0.24 g/kg;"白玉霓"3个指标的预测根均方误差分别为0.78、1.56°Brix和0.22 g/kg。结果表明,本仪器能完成对葡萄多个理化指标的建模预测,同时样品池的设计能够满足不同品种葡萄的需求。本研究为果蔬专用型近红外仪器的开发提供技术参考。
In this study, a specialized portable low-cost visible and near-infrared(Vis-NIR) instrument for the evaluation of grape quality was designed to meet the need for fast and non-destructive detection in the grape industry. A holographic concave diffractive grating combined with a charge-coupled device was used as the core component of this system to obtain diffuse re?ectance spectral data of grape samples in the wavelength range between 400 and 1 100 nm, and the combined application of a halogen light source with low-OH Y-shaped quartz optical ?ber as a reliable optical transmission medium was proposed to provide a stable Vis-NIR light source. In order to meet the requirements of different varieties with fruits of different sizes, an adjustable sample cuvette with both internal and external threads was designed. The software, written in C# based on windows operating system, was stable and could facilitate model updating. Two Vitis vinifera cultivars,Manicure Finger and Ugni Blanc, were detected using this instrument. CIE L*, a* and b* values, total solid soluble content(SSC) and total phenolic(TP) content were taken into consideration in the development of predictive models using least squares support vector machine(LS-SVM). The results showed that for both cultivars a* value, SSC and TP could be well predicted by the proposed models with a coef?cient of determination for calibration(R_c~2) of 0.91, 0.94 and 0.90, respectively.In the external validation using 70 unknown samples, the root mean square error of prediction(RMSEP) of a* value,SSC and TP were 3.15, 1.39 °Brix and 0.24 g/kg for Manicure Finger; and 0.78, 1.56 °Brix and 0.22 g/kg for Ugni Blanc,respectively. This study has con?rmed the feasibility of this Vis-NIR instrument for grape quality detection and can provide a technical basis for developing specialized Vis-NIR instruments to detect fruit and vegetable quality.
In this study, a specialized portable low-cost visible and near-infrared(Vis-NIR) instrument for the evaluation of grape quality was designed to meet the need for fast and non-destructive detection in the grape industry. A holographic concave diffractive grating combined with a charge-coupled device was used as the core component of this system to obtain diffuse re?ectance spectral data of grape samples in the wavelength range between 400 and 1 100 nm, and the combined application of a halogen light source with low-OH Y-shaped quartz optical ?ber as a reliable optical transmission medium was proposed to provide a stable Vis-NIR light source. In order to meet the requirements of different varieties with fruits of different sizes, an adjustable sample cuvette with both internal and external threads was designed. The software, written in C# based on windows operating system, was stable and could facilitate model updating. Two Vitis vinifera cultivars,Manicure Finger and Ugni Blanc, were detected using this instrument. CIE L*, a* and b* values, total solid soluble content(SSC) and total phenolic(TP) content were taken into consideration in the development of predictive models using least squares support vector machine(LS-SVM). The results showed that for both cultivars a* value, SSC and TP could be well predicted by the proposed models with a coef?cient of determination for calibration(R_c~2) of 0.91, 0.94 and 0.90, respectively.In the external validation using 70 unknown samples, the root mean square error of prediction(RMSEP) of a* value,SSC and TP were 3.15, 1.39 °Brix and 0.24 g/kg for Manicure Finger; and 0.78, 1.56 °Brix and 0.22 g/kg for Ugni Blanc,respectively. This study has con?rmed the feasibility of this Vis-NIR instrument for grape quality detection and can provide a technical basis for developing specialized Vis-NIR instruments to detect fruit and vegetable quality.
引文
[1]彭彦昆.农畜产品品质安全光学无损快速检测技术[M].北京:科学出版社,2015:53-57.
[2]BLAKEY R J.Evaluation of avocado fruit maturity with a portable near-infrared spectrometer[J].Postharvest Biology and Technology,2016,121:101-105.DOI:10.1016/j.postharvbio.2016.06.016.
[3]GUO W C,FANG L J,LIU D Y,et al.Determination of soluble solids content and firmness of pears during ripening by using dielectric spectroscopy[J].Computers and Electronics in Agriculture,2015,117:226-233.DOI:10.1016/j.compag.2015.08.012.
[4]傅霞萍,应义斌.基于NIR和Raman光谱的果蔬质量检测研究进展与展望[J].农业机械学报,2013,44(8):148-164.DOI:10.6041/j.issn.1000-1298.2013.08.026.
[5]QU J H,LIU D,CHENG J H,et al.Applications of near-infrared spectroscopy in food safety evaluation and control:a review of recent research advances[J].Critical Reviews in Food Science&Nutrition,2015,55(13):1939-1954.DOI:10.1080/10408398.2013.871693.
[6]陆婉珍,袁洪福.现代近红外光谱分析技术[M].北京:中国石化出版社,2000:77-79.
[7]ZHANG Z H,MUO X X,GUO Y J,et al.Micro Hadamard transform near-infrared spectrometer[J].Spectroscopy and Spectral Analysis,2011,31(7):1975-1979.
[8]郭志明,陈全胜,张彬,等.果蔬品质手持式近红外光谱检测系统设计与试验[J].农业工程学报,2017,33(8):245-250.DOI:10.11975/j.issn.1002-6819.2017.08.033.
[9]冯帮,陈斌,颜辉.便携式近红外光谱检测系统的开发[J].现代仪器与医疗,2014(2):12-16.DOI:10.11876/mimt201402004.
[10]闻明,吉海彦.基于LED的便携式近红外整粒小麦成分测量仪的研制[J].光谱学与光谱分析,2014,24(10):1276-1279.DOI:10.3321/j.issn:1000-0593.2004.10.035.
[11]王凡,李永玉,彭彦昆,等.便携式番茄多品质参数可见/近红外检测装置研发[J].农业工程学报,2017,33(19):295-299.DOI:10.11975/j.issn.1002-6819.2017.19.038.
[12]李倩倩,刘大洋,杨彪,等.斜率/截距算法在猕猴桃可溶性固形物含量便携式检测中的应用[J].食品科学,2018,39(14):257-262.DOI:10.7506/spkx1002-6630-201814038.
[13]尹慧敏,陈思羽.便携式谷物成分近红外检测仪设计[J].粮油加工(电子版),2015(8):44-45.
[14]FERNANDEZ-NOVALES J,LOPEZ M I,SANCHEZ M T,et al.Shortwave-near infrared spectroscopy for determination of reducing sugar content during grape ripening,winemaking,and aging of white and red wines[J].Food Research International,2009,42(2):285-291.DOI:10.1016/j.foodres.2008.11.008.
[15]NOGALES-BUENO J,HERNANDEZ-HIERRO J M,RODRIGUEZPULIDOF J,et al.Determination of technological maturity of grapes and total phenolic compounds of grape skins in red and white cultivars during ripening by near infrared hyperspectral image:a preliminary approach[J].Food Chemistry,2014,152(2):586-591.DOI:10.1016/j.foodchem.2013.12.030.
[16]HERNANDEZ-HIERRO J M,NOGALES-BUENO J,RODRIGUEZPULIDOF J,et al.Feasibility study on the use of near-infrared hyperspectral imaging for the screening of anthocyanins in intact grapes during ripening[J].Journal of Agricultural&Food Chemistry,2013,61(41):9804-9809.DOI:10.1021/jf4021637.
[17]URRACA R,SANZ-GARCIA A,TARDAGUILA J,et al.Estimation of total soluble solids in grape berries using a hand-held NIRspectrometer under field a hand-held NIR spectrometer under field conditions[J].Journal of the Science of Food and Agriculture,2016,96(9):3007-3016.DOI:10.1002/jsfa.7470.
[18]严衍禄.近红外光谱分析基础与应用[M].北京:中国轻工业出版社,2005:132-135.
[19]BEGHI R,GIOVENZANA V,BRANCADORO L,et al.Rapid evaluation of grape phytosanitary status directly at the check point station entering the winery by using visible/near infrared spectroscopy[J].Journal of Food Engineering,2017,204:46-54.DOI:10.1016/j.jfoodeng.2017.02.012.
[20]MARTINEZ-SANDOVAL J R,NOGALESBUEN O J,RODRIGUEZPULIDO F J,et al.Screening of anthocyanins in single red grapes using a non-destructive method based on the near infrared hyperspectral technology and chemometrics[J].Journal of the Science of Food&Agriculture,2016,96(5):1643-1647.DOI:10.1002/jsfa.7266.
[21]KEMPS B,LEON L,BEST S,et al.Assessment of the quality parameters in grapes using VIS/NIR spectroscopy[J].Biosystems Engineering,2010,105(4):507-513.DOI:10.1016/j.biosystemseng.2010.02.002.
[22]叶华俊,刘立鹏,张学峰,等.便携式近红外光谱分析仪的研制及应用[J].光学技术,2008,34(增刊1):531-535.DOI:10.3321/j.issn:1002-1582.2008.z1.024.
[23]MARCUSE D.Theory of dielectric optical waveguides[M].2nd ed.New York:Academic Press,1974:367-372.
[24]GELADI P,KOWALSKI B R.Partial least-squares regression:a tutorial[J].Analytica Chimica Acta,1986,185(86):1-17.DOI:10.1016/0003-2670(86)80028-9.
[25]HU X Z.Tha quenching sirengthen principle of optical fiber[J].Optical Communication Technology,1994.
[26]FRAGOSO S,ACENA L,GUASCH J,et al.Application of FTMIRspectroscopy for fast control of red grape phenolic ripening[J].Journal of Agricultural&Food Chemistry,2011,59(6):2175-2183.DOI:10.1021/jf104039g.
[27]CHU X L,YUAN H F,LU W Z.Progress and application of spectral data pretreatment and wavelength selection methods in NIR analytical technique[J].Progress in Chemistry,2014,16(4):528-542.
[28]SUYKENS J A K,VANDEWALLE J.Least squares support vector machine classifiers[J].Neural Processing Letters,1999,9(3):293-300.DOI:10.1023/A:1018628609742.
[29]COZZOLINO D,CYNKAR W U,SHAH N,et al.Multivariate data analysis applied to spectroscopy:potential application to juice and fruit quality[J].Food Research International,2011,44(7):1888-1896.DOI:10.1016/j.foodres.2011.01.041.
[30]FERRER-GALLEGO R,HERNANDEZ-HIERRO J M,RIVASGONZALOJ C,et al.Evaluation of sensory parameters of grapes using near infrared spectroscopy[J].Journal of Food Engineering,2013,118(3):333-339.DOI:10.1016/j.jfoodeng.2013.04.019.
[2]BLAKEY R J.Evaluation of avocado fruit maturity with a portable near-infrared spectrometer[J].Postharvest Biology and Technology,2016,121:101-105.DOI:10.1016/j.postharvbio.2016.06.016.
[3]GUO W C,FANG L J,LIU D Y,et al.Determination of soluble solids content and firmness of pears during ripening by using dielectric spectroscopy[J].Computers and Electronics in Agriculture,2015,117:226-233.DOI:10.1016/j.compag.2015.08.012.
[4]傅霞萍,应义斌.基于NIR和Raman光谱的果蔬质量检测研究进展与展望[J].农业机械学报,2013,44(8):148-164.DOI:10.6041/j.issn.1000-1298.2013.08.026.
[5]QU J H,LIU D,CHENG J H,et al.Applications of near-infrared spectroscopy in food safety evaluation and control:a review of recent research advances[J].Critical Reviews in Food Science&Nutrition,2015,55(13):1939-1954.DOI:10.1080/10408398.2013.871693.
[6]陆婉珍,袁洪福.现代近红外光谱分析技术[M].北京:中国石化出版社,2000:77-79.
[7]ZHANG Z H,MUO X X,GUO Y J,et al.Micro Hadamard transform near-infrared spectrometer[J].Spectroscopy and Spectral Analysis,2011,31(7):1975-1979.
[8]郭志明,陈全胜,张彬,等.果蔬品质手持式近红外光谱检测系统设计与试验[J].农业工程学报,2017,33(8):245-250.DOI:10.11975/j.issn.1002-6819.2017.08.033.
[9]冯帮,陈斌,颜辉.便携式近红外光谱检测系统的开发[J].现代仪器与医疗,2014(2):12-16.DOI:10.11876/mimt201402004.
[10]闻明,吉海彦.基于LED的便携式近红外整粒小麦成分测量仪的研制[J].光谱学与光谱分析,2014,24(10):1276-1279.DOI:10.3321/j.issn:1000-0593.2004.10.035.
[11]王凡,李永玉,彭彦昆,等.便携式番茄多品质参数可见/近红外检测装置研发[J].农业工程学报,2017,33(19):295-299.DOI:10.11975/j.issn.1002-6819.2017.19.038.
[12]李倩倩,刘大洋,杨彪,等.斜率/截距算法在猕猴桃可溶性固形物含量便携式检测中的应用[J].食品科学,2018,39(14):257-262.DOI:10.7506/spkx1002-6630-201814038.
[13]尹慧敏,陈思羽.便携式谷物成分近红外检测仪设计[J].粮油加工(电子版),2015(8):44-45.
[14]FERNANDEZ-NOVALES J,LOPEZ M I,SANCHEZ M T,et al.Shortwave-near infrared spectroscopy for determination of reducing sugar content during grape ripening,winemaking,and aging of white and red wines[J].Food Research International,2009,42(2):285-291.DOI:10.1016/j.foodres.2008.11.008.
[15]NOGALES-BUENO J,HERNANDEZ-HIERRO J M,RODRIGUEZPULIDOF J,et al.Determination of technological maturity of grapes and total phenolic compounds of grape skins in red and white cultivars during ripening by near infrared hyperspectral image:a preliminary approach[J].Food Chemistry,2014,152(2):586-591.DOI:10.1016/j.foodchem.2013.12.030.
[16]HERNANDEZ-HIERRO J M,NOGALES-BUENO J,RODRIGUEZPULIDOF J,et al.Feasibility study on the use of near-infrared hyperspectral imaging for the screening of anthocyanins in intact grapes during ripening[J].Journal of Agricultural&Food Chemistry,2013,61(41):9804-9809.DOI:10.1021/jf4021637.
[17]URRACA R,SANZ-GARCIA A,TARDAGUILA J,et al.Estimation of total soluble solids in grape berries using a hand-held NIRspectrometer under field a hand-held NIR spectrometer under field conditions[J].Journal of the Science of Food and Agriculture,2016,96(9):3007-3016.DOI:10.1002/jsfa.7470.
[18]严衍禄.近红外光谱分析基础与应用[M].北京:中国轻工业出版社,2005:132-135.
[19]BEGHI R,GIOVENZANA V,BRANCADORO L,et al.Rapid evaluation of grape phytosanitary status directly at the check point station entering the winery by using visible/near infrared spectroscopy[J].Journal of Food Engineering,2017,204:46-54.DOI:10.1016/j.jfoodeng.2017.02.012.
[20]MARTINEZ-SANDOVAL J R,NOGALESBUEN O J,RODRIGUEZPULIDO F J,et al.Screening of anthocyanins in single red grapes using a non-destructive method based on the near infrared hyperspectral technology and chemometrics[J].Journal of the Science of Food&Agriculture,2016,96(5):1643-1647.DOI:10.1002/jsfa.7266.
[21]KEMPS B,LEON L,BEST S,et al.Assessment of the quality parameters in grapes using VIS/NIR spectroscopy[J].Biosystems Engineering,2010,105(4):507-513.DOI:10.1016/j.biosystemseng.2010.02.002.
[22]叶华俊,刘立鹏,张学峰,等.便携式近红外光谱分析仪的研制及应用[J].光学技术,2008,34(增刊1):531-535.DOI:10.3321/j.issn:1002-1582.2008.z1.024.
[23]MARCUSE D.Theory of dielectric optical waveguides[M].2nd ed.New York:Academic Press,1974:367-372.
[24]GELADI P,KOWALSKI B R.Partial least-squares regression:a tutorial[J].Analytica Chimica Acta,1986,185(86):1-17.DOI:10.1016/0003-2670(86)80028-9.
[25]HU X Z.Tha quenching sirengthen principle of optical fiber[J].Optical Communication Technology,1994.
[26]FRAGOSO S,ACENA L,GUASCH J,et al.Application of FTMIRspectroscopy for fast control of red grape phenolic ripening[J].Journal of Agricultural&Food Chemistry,2011,59(6):2175-2183.DOI:10.1021/jf104039g.
[27]CHU X L,YUAN H F,LU W Z.Progress and application of spectral data pretreatment and wavelength selection methods in NIR analytical technique[J].Progress in Chemistry,2014,16(4):528-542.
[28]SUYKENS J A K,VANDEWALLE J.Least squares support vector machine classifiers[J].Neural Processing Letters,1999,9(3):293-300.DOI:10.1023/A:1018628609742.
[29]COZZOLINO D,CYNKAR W U,SHAH N,et al.Multivariate data analysis applied to spectroscopy:potential application to juice and fruit quality[J].Food Research International,2011,44(7):1888-1896.DOI:10.1016/j.foodres.2011.01.041.
[30]FERRER-GALLEGO R,HERNANDEZ-HIERRO J M,RIVASGONZALOJ C,et al.Evaluation of sensory parameters of grapes using near infrared spectroscopy[J].Journal of Food Engineering,2013,118(3):333-339.DOI:10.1016/j.jfoodeng.2013.04.019.