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Prediction of beef freshness attributes using reflectance spectroscopy
- Authors
- Choi, C.-H.[Choi, C.-H.]; Lee, D.-H.[Lee, D.-H.]; Kim, Y.-J.[Kim, Y.-J.]; Kim, B.-S.[Kim, B.-S.]; Kim, J.-H.[Kim, J.-H.]
- Issue Date
- 2017
- Publisher
- Elsevier B.V.
- Keywords
- Beef; Freshness; Near infrared; Partial least squares; Reflectance spectrum
- Citation
- Engineering in Agriculture, Environment and Food, v.10, no.4, pp.243 - 248
- Indexed
- SCOPUS
- Journal Title
- Engineering in Agriculture, Environment and Food
- Volume
- 10
- Number
- 4
- Start Page
- 243
- End Page
- 248
- ISSN
- 1881-8366
- Abstract
- This study was performed to determine the proper conditions for measurements of reflectance spectra, and to develop models to predict the freshness attributes of beef using visible and near infrared (NIR) spectroscopic technique. The measured attributes for beef freshness were volatile basic nitrogen (VBN), thiobarbituric acid reacted substance (TBARS), total viable counts (TVC), color (CIE L*, a*, b* values), and pH value. A total of 240 beef spectra were collected during the storage time. Partial least squares (PLS) models were developed, to predict freshness attributes for beef samples. The appropriate spectral regions of PLS models to predict freshness attributes of beef were found in the range of 550–1000 nm. VBN and TVC models showed a good relationship between the predicted and the measured values. The results showed that NIR spectroscopy would be one of the high potential tools to determine beef freshness in a real-life purchase environment. © 2017 Asian Agricultural and Biological Engineering Association
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