Share Email Print
cover

Proceedings Paper

Detection of the total viable counts in chicken based on visible/near-infrared spectroscopy
Author(s): Fachao Jiang; Yuan Long; Xiuying Tang; Linlin Zhao; Yankun Peng; Caiping Wang
Format Member Price Non-Member Price
PDF $14.40 $18.00
cover GOOD NEWS! Your organization subscribes to the SPIE Digital Library. You may be able to download this paper for free. Check Access

Paper Abstract

The viable counts in chicken have significant effects on food safety. Exceeding standard index can have negative influence to the public. Visible-near infrared spectra have had rapid development in food safety recently. The objective of this study was to detect the total viable counts in chicken breast fillets.36 chicken breast fillets used in the study were stored in a refrigerator at 4°C for 9 days. Each day four samples were taken and Vis/NIR spectra were collected from each sample before detecting their total viable counts by standard method. The original data was processed in four main steps: Savitzky-Golay smoothing method, standard normalized variate (SNV), model calibrating and model validating. Prediction model was established using partial least squares regression (PLSR) method. Several statistical indicators such as root mean squared errors and coefficients were calculated for determination of calibration and validation accuracy respectively. As a result, the Rc, SEC, Rv and SEV, of the best model were obtained to be 0.8854, 0.7455, 0.9070 and 0.6045 respectively, which demonstrate that visible-near infrared spectra is a potential technique to detect the total viable counts(TVC) in chicken and the best wavelengths for the establishment of the calibration model are near 449nm.

Paper Details

Date Published: 28 May 2014
PDF: 7 pages
Proc. SPIE 9108, Sensing for Agriculture and Food Quality and Safety VI, 91080S (28 May 2014); doi: 10.1117/12.2053201
Show Author Affiliations
Fachao Jiang, China Agricultural Univ. (China)
Yuan Long, China Agricultural Univ. (China)
Xiuying Tang, China Agricultural Univ. (China)
Linlin Zhao, China Agricultural Univ. (China)
Yankun Peng, China Agricultural Univ. (China)
Caiping Wang, Xinjiang Yurun Food Group Ltd. (China)


Published in SPIE Proceedings Vol. 9108:
Sensing for Agriculture and Food Quality and Safety VI
Moon S. Kim; Kuanglin Chao, Editor(s)

© SPIE. Terms of Use
Back to Top