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Prediction of starch content in meatballs using near infrared spectroscopy (NIRS)

Meatballs are a popular food in Asian countries. A good quality consists of low starch. In this study, the quality of meatballs was evaluated by starch content using short and long-wavelength near infrared spectroscopy (NIRS). The result found that long-wavelength NIRS can predict starch contents in...

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Main Authors: Vichasilp, C., Kawano, S.
Format: Journal Contribution
Language:English
Published: 2017
Subjects:
Processed foods
Beef
Pork
Chicken meat
Starch
Infrared spectrophotometry
Food quality
Temperature profile
Polysaccharides
Food science
Online Access:http://agris.upm.edu.my:8080/dspace/handle/0/12624
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spelling oai:http:--agris.upm.edu.my:0-12624Prediction of starch content in meatballs using near infrared spectroscopy (NIRS)Vichasilp, C.Kawano, S.Processed foodsBeefPorkChicken meatStarchInfrared spectrophotometryFood qualityTemperature profilePolysaccharidesFood scienceMeatballs are a popular food in Asian countries. A good quality consists of low starch. In this study, the quality of meatballs was evaluated by starch content using short and long-wavelength near infrared spectroscopy (NIRS). The result found that long-wavelength NIRS can predict starch contents in all kinds of meatballs. The model of beef meatballs showed a high coefficient of multiple determination of validation set (R2-val) of 0.97 and a low standard error of cross-validation (SECV) of 2.64%; the chicken meatballs model had an R2-val of 0.97 and a SECV of 2.63%; and the pork meatballs model had an R2-val of 0.98 and a SECV of 2.37%. In addition, a universal model was created by combining the spectra of all meatballs. The universal model had an coefficient of multiple determination of calibration set (R2-cal) of 0.98, standard error of calibration (SEC) of 2.22%, R2-val of 0.97, standard error of prediction (SEP) of 2.67% and Bias of 0.05%. The results indicated that NIRS can predict starch contents with high accuracy and could apply for quality classification via rapid analysis.2017-03-01T06:29:37Z2017-03-01T06:29:37Z2015Journal ContributionArticleNon-RefereedInternational Food Research Journal (Malaysia), 22(4), p. 1501-150622317546http://agris.upm.edu.my:8080/dspace/handle/0/12624MY2017050120enhttp://ifrj.upm.edu.my/22%20(04)%202015/(26).pdfhttp://www.oceandocs.org/license
institution AGRIS
collection AGRIS
language English
topic Processed foods
Beef
Pork
Chicken meat
Starch
Infrared spectrophotometry
Food quality
Temperature profile
Polysaccharides
Food science
spellingShingle Processed foods
Beef
Pork
Chicken meat
Starch
Infrared spectrophotometry
Food quality
Temperature profile
Polysaccharides
Food science
Vichasilp, C.
Kawano, S.
Prediction of starch content in meatballs using near infrared spectroscopy (NIRS)
description Meatballs are a popular food in Asian countries. A good quality consists of low starch. In this study, the quality of meatballs was evaluated by starch content using short and long-wavelength near infrared spectroscopy (NIRS). The result found that long-wavelength NIRS can predict starch contents in all kinds of meatballs. The model of beef meatballs showed a high coefficient of multiple determination of validation set (R2-val) of 0.97 and a low standard error of cross-validation (SECV) of 2.64%; the chicken meatballs model had an R2-val of 0.97 and a SECV of 2.63%; and the pork meatballs model had an R2-val of 0.98 and a SECV of 2.37%. In addition, a universal model was created by combining the spectra of all meatballs. The universal model had an coefficient of multiple determination of calibration set (R2-cal) of 0.98, standard error of calibration (SEC) of 2.22%, R2-val of 0.97, standard error of prediction (SEP) of 2.67% and Bias of 0.05%. The results indicated that NIRS can predict starch contents with high accuracy and could apply for quality classification via rapid analysis.
format Journal Contribution
author Vichasilp, C.
Kawano, S.
author_facet Vichasilp, C.
Kawano, S.
author_sort Vichasilp, C.
title Prediction of starch content in meatballs using near infrared spectroscopy (NIRS)
title_short Prediction of starch content in meatballs using near infrared spectroscopy (NIRS)
title_full Prediction of starch content in meatballs using near infrared spectroscopy (NIRS)
title_fullStr Prediction of starch content in meatballs using near infrared spectroscopy (NIRS)
title_full_unstemmed Prediction of starch content in meatballs using near infrared spectroscopy (NIRS)
title_sort prediction of starch content in meatballs using near infrared spectroscopy (nirs)
publishDate 2017
url http://agris.upm.edu.my:8080/dspace/handle/0/12624
_version_ 1819284791801937920
score 13.4562235

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