Non-destructive analysis of Japanese table grape qualities using near-infrared spectroscopy

© 2020, Korean Society for Horticultural Science. Near-infrared (NIR) spectroscopy is a useful technique for the non-destructive analysis of fruit quality. The key quality parameters of table grapes (Vitis vinifera) that affect consumer preference are the soluble solids content (SSC), pH, firmness,...

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Main Authors: Chaorai Kanchanomai, Shintaroh Ohashi, Daruni Naphrom, Wakana Nemoto, Phonkrit Maniwara, Kazuhiro Nakano
Format: Journal
Published: 2020
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http://cmuir.cmu.ac.th/jspui/handle/6653943832/69994
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Institution: Chiang Mai University
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spelling th-cmuir.6653943832-699942020-10-14T08:25:26Z Non-destructive analysis of Japanese table grape qualities using near-infrared spectroscopy Chaorai Kanchanomai Shintaroh Ohashi Daruni Naphrom Wakana Nemoto Phonkrit Maniwara Kazuhiro Nakano Agricultural and Biological Sciences Biochemistry, Genetics and Molecular Biology © 2020, Korean Society for Horticultural Science. Near-infrared (NIR) spectroscopy is a useful technique for the non-destructive analysis of fruit quality. The key quality parameters of table grapes (Vitis vinifera) that affect consumer preference are the soluble solids content (SSC), pH, firmness, and seedlessness. This research focused on using NIR spectroscopy for assessing the quality of ‘Kyoho’ table grapes, as a non-destructive analysis under laboratory and field conditions. NIR spectra for each sample were acquired in the wavelength range of 400–1000 nm, using a visible/NIR spectrometer with fibre optics in the interactance mode. Partial least-square regression was used to calibrate the NIR spectral data with all the measured properties of table grapes. The best prediction model for firmness was the Savitzky–Golay first derivative (SGD1) with a coefficient of determination (Rprediction2) of 0.7427 in the laboratory, and 0.7804 in the field. The Rprediction2 values for pH in the laboratory and the field was 0.6276 using multiplicative scatter correction (MSC), and 0.7676 using SGD1, respectively. These values were similar to the Rprediction2 values of SSC, which were 0.6926 using MSC, and 0.8052 using the Savitzky–Golay second derivative, respectively. In both analyses the R2 of the calibration model was between 0.6944 and 0.8877. The partial least-square discriminant analysis was used to classify the percentage of seedlessness, which was 93.10% in the laboratory using SGD1 or MSC, and 79.31% in the field using MSC. Therefore, NIR spectroscopy is an efficient non-destructive technique for rapidly analysing Japanese table grape qualities in laboratory and field settings. 2020-10-14T08:22:48Z 2020-10-14T08:22:48Z 2020-08-01 Journal 22113460 22113452 2-s2.0-85087302704 10.1007/s13580-020-00256-4 https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85087302704&origin=inward http://cmuir.cmu.ac.th/jspui/handle/6653943832/69994
institution Chiang Mai University
building Chiang Mai University Library
continent Asia
country Thailand
Thailand
content_provider Chiang Mai University Library
collection CMU Intellectual Repository
topic Agricultural and Biological Sciences
Biochemistry, Genetics and Molecular Biology
spellingShingle Agricultural and Biological Sciences
Biochemistry, Genetics and Molecular Biology
Chaorai Kanchanomai
Shintaroh Ohashi
Daruni Naphrom
Wakana Nemoto
Phonkrit Maniwara
Kazuhiro Nakano
Non-destructive analysis of Japanese table grape qualities using near-infrared spectroscopy
description © 2020, Korean Society for Horticultural Science. Near-infrared (NIR) spectroscopy is a useful technique for the non-destructive analysis of fruit quality. The key quality parameters of table grapes (Vitis vinifera) that affect consumer preference are the soluble solids content (SSC), pH, firmness, and seedlessness. This research focused on using NIR spectroscopy for assessing the quality of ‘Kyoho’ table grapes, as a non-destructive analysis under laboratory and field conditions. NIR spectra for each sample were acquired in the wavelength range of 400–1000 nm, using a visible/NIR spectrometer with fibre optics in the interactance mode. Partial least-square regression was used to calibrate the NIR spectral data with all the measured properties of table grapes. The best prediction model for firmness was the Savitzky–Golay first derivative (SGD1) with a coefficient of determination (Rprediction2) of 0.7427 in the laboratory, and 0.7804 in the field. The Rprediction2 values for pH in the laboratory and the field was 0.6276 using multiplicative scatter correction (MSC), and 0.7676 using SGD1, respectively. These values were similar to the Rprediction2 values of SSC, which were 0.6926 using MSC, and 0.8052 using the Savitzky–Golay second derivative, respectively. In both analyses the R2 of the calibration model was between 0.6944 and 0.8877. The partial least-square discriminant analysis was used to classify the percentage of seedlessness, which was 93.10% in the laboratory using SGD1 or MSC, and 79.31% in the field using MSC. Therefore, NIR spectroscopy is an efficient non-destructive technique for rapidly analysing Japanese table grape qualities in laboratory and field settings.
format Journal
author Chaorai Kanchanomai
Shintaroh Ohashi
Daruni Naphrom
Wakana Nemoto
Phonkrit Maniwara
Kazuhiro Nakano
author_facet Chaorai Kanchanomai
Shintaroh Ohashi
Daruni Naphrom
Wakana Nemoto
Phonkrit Maniwara
Kazuhiro Nakano
author_sort Chaorai Kanchanomai
title Non-destructive analysis of Japanese table grape qualities using near-infrared spectroscopy
title_short Non-destructive analysis of Japanese table grape qualities using near-infrared spectroscopy
title_full Non-destructive analysis of Japanese table grape qualities using near-infrared spectroscopy
title_fullStr Non-destructive analysis of Japanese table grape qualities using near-infrared spectroscopy
title_full_unstemmed Non-destructive analysis of Japanese table grape qualities using near-infrared spectroscopy
title_sort non-destructive analysis of japanese table grape qualities using near-infrared spectroscopy
publishDate 2020
url https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85087302704&origin=inward
http://cmuir.cmu.ac.th/jspui/handle/6653943832/69994
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