Non-destructive measurement of tomato maturity by near-infrared diffuse transmission spectroscopy

LIU Yande; XU Hai; SUN Xudong; RAO Yu

doi:10.7510/jgjs.issn.1001-3806.2019.01.006

LASER TECHNOLOGY > 2019 > 43(1): 25-29. > DOI: 10.7510/jgjs.issn.1001-3806.2019.01.006

LIU Yande, XU Hai, SUN Xudong, RAO Yu. Non-destructive measurement of tomato maturity by near-infrared diffuse transmission spectroscopy[J]. LASER TECHNOLOGY, 2019, 43(1): 25-29. DOI: 10.7510/jgjs.issn.1001-3806.2019.01.006

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Non-destructive measurement of tomato maturity by near-infrared diffuse transmission spectroscopy

Institute of Optics Mechanics Electronics Technology and Application, East China Jiaotong University, Nanchang 330013, China

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Received Date: April 08, 2018
Revised Date: April 29, 2018
Published Date: January 24, 2019

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Abstract

In order to prove that near-infrared diffuse transmission spectroscopy combining with chemometrics can effectively detect the maturity of tomatoes, diffuse transmission spectroscopy data of tomatoes were obtained by using QE65000 spectrometer of Ocean Optics Company of America, and the color datum of brightness, red and green, yellow blue color and total chromatic aberration were obtained by using CR-10 reflectance colorimeter of Konica Minolta of Japan. The color model was established by the standard mathematical modeling method, and the near infrared spectroscopy model was established by the partial least squares regression correction algorithm. The results show that, the red-green phase index was the best for both models. Among the 99 unknown samples, the misjudgments of the color model were immature 0%, semi-mature 33.33% and mature 0%, while the misjudgments of the near-infrared spectroscopy prediction model were immature 32.14%, semi-mature 50% and mature 0% respectively. This study verifies the feasibility of non-destructive detection of tomato maturity by near infrared spectroscopy, which has a certain practical significance for rapid and batch sorting of tomatoes.
- spectroscopy,
- Lab color index,
- near-infrared diffuse transmission spectroscopy,
- partial least squares regression algorithm,
- qualitative,
- tomato

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[1]	CAMPS C, DELTHEIL L, GILLI C. Qualitative and quantitative models based on handheld NIR spectroscopy to monitor the tomato fruit development during darly and full season[DB/OL].(2014-11-27)[2018-04-08].https://www.researchgate.net/publication/269016068.
[2]	CAMPS C, SIMONE C, GILLI C. Assessment of tomato quality using portable NIR spectroscopy and PLSR with wavelengths selection[DB/OL].(2014-12-01)[ 2018-04-08].https://www.researchgate.net/publication/290241088.
[3]	ZHANG B F, YUAN L B, ZHANG B X. Study on predicting total acid content and soluble sugar of tomato juice by near infrared optical fiber spectrometer technique[J]. Spectroscopy and Spectral Analysis, 2014, 34(2): 350-353(in Chinese). http://www.wanfangdata.com.cn/details/detail.do?_type=perio&id=gpxygpfx201402015
[4]	SUN T, XU H R, YING Y B. Progress in application of near infrared spectroscopy to nondestructive on-line detection of products/ food quality[J]. Spectroscopy and Spectral Analysis, 2009, 29(1): 122-126(in Chinese). http://www.wanfangdata.com.cn/details/detail.do?_type=perio&id=gpxygpfx200901028
[5]	LIU Y D, WU M M, SUN X D, et al. Simultaneous detection of surface deficiency and soluble solids content for amygdalus persica by online visible-near infrared transmittance spectroscopy[J]. Transactions of the Chinese Society of Agricultural Engineering, 2016, 32(6): 289-295(in Chinese). http://www.wanfangdata.com.cn/details/detail.do?_type=perio&id=nygcxb201606040
[6]	PAN Y Y, LIU Y D, SUN X D. Research progress o f on-line detection of fruit quality using near infrared spectroscopy[J]. Laser & Infrared, 2010, 40(8): 805-810(in Chinese). http://d.wanfangdata.com.cn/Periodical/jgyhw201008002
[7]	CHU X L, LIU H Y, YAN Z Ch. Near-infrared spectroscopy techno-logy practical manual[M].Beijing: Machinery Industry Press, 2016: 114-133(in Chinese).
[8]	RAO X Q, YING Y B. Grading a fruit by it's surface color[J]. Journal of Zhejiang University (Engineering Science Edition), 2009, 43(5): 869-871(in Chinese).
[9]	LIU Y D, CHEN X M, OUYANG A G. Non-destructive measurement of surface color of pear by visible/near-infrared diffuse reflectance spectra[J].Journal of Infrared and Millimeter Waves, 2008, 27(4): 266-268(in Chinese). http://www.wanfangdata.com.cn/details/detail.do?_type=perio&id=hwyhmb200804006
[10]	ZHANG Y P, LI Ch, ZHAO M, et al. Analysis of color difference of cigarette packaging material based spectroscopy on near-infrared[J]. Tobacco Science & Technology, 2016, 49(2): 75-81(in Chinese). http://www.wanfangdata.com.cn/details/detail.do?_type=perio&id=yckj201602013
[11]	QIN J, ZHANG M M, ZHAO G J, et al. Characterization of wood surface treated with electroless copper plating by near infrared spectroscopy technology[J]. Spectroscopy and Spectral Analysis, 2015, 35(5): 1253-1257(in Chinese). http://www.ncbi.nlm.nih.gov/pubmed/26415438
[12]	PANG X M, YAN Z J, KAN J M. Color image segmentation based on HSI and LAB color space[J]. Journal of Guangxi University(Natural Science Edition), 2011, 36(6): 976-980(in Chinese). http://www.cnki.com.cn/Article/CJFDTotal-GXKZ201106019.htm
[13]	JI Sh J, LUO Y, LI D H, et al. Effect of honey color on determination model establishment of near infrared spectrum[J]. Science and Technology of Food Industry, 2010, 31(8): 345-347(in Chinese). http://d.old.wanfangdata.com.cn/Periodical/spgykj201008104
[14]	YAN Y L. Fundamentals and applications of near infrared spectroscopy[M]. Beijing: China Light Industry Press, 2005: 8-39(in Ch-inese).
[15]	CHU X L. Chemometrics and molecular spectroscopy[M]. Beijing: Chemical Industry Press, 2011:41-53(in Chinese).
[16]	MA C H, CUI J L. Quantitative analysis of composition in molten steel by LIBS based on improved partial least squares[J]. Laser Technology, 2016, 40(6): 876-881(in Chinese). http://www.wanfangdata.com.cn/details/detail.do?_type=perio&id=jgjs201606021
[17]	LIU Y D, XIE Q H, WANG H Y, et al. Quantitative study on phosmet residues in navel oranges based on surface enhanced Raman spectra[J]. Laser Technology, 2017, 41(4): 545-548(in Chin-ese). http://www.wanfangdata.com.cn/details/detail.do?_type=perio&id=jgjs201704017
[18]	FU Y, ZHANG Y J, CHEN H C, et al. Establishment of NIR mo-dels for components determination in fresh chestnut[J]. Food Science and Technology, 2012, 37(5): 42-45(in Chinese).
[19]	OUYANG A G, XIE X Q, ZHOU Y R, et al. Partial least squares regression variable screening studies on apple soluble solids NIR spectral detection[J]. Spectroscopy and Spectral Analysis, 2012, 32(10): 2680-2684(in Chinese). http://www.wanfangdata.com.cn/details/detail.do?_type=perio&id=gpxygpfx201210020
[20]	XU L, SHAO X G. Methods of chemometrics[M]. 2nd ed. Beijing: Science Press, 2004: 163-169(in Chinese).

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