Journal
LWT-FOOD SCIENCE AND TECHNOLOGY
Volume 62, Issue 2, Pages 1060-1068Publisher
ELSEVIER SCIENCE BV
DOI: 10.1016/j.lwt.2015.01.021
Keywords
Hyperspectral imaging; Total viable counts (TVC); Successive projections algorithm (SPA); Grass carp fillet; Prediction map
Categories
Funding
- Guangdong Province Government (China)
- National Key Technologies RD Program [2014BAD08B09]
- International S&T Cooperation Projects of Guangdong Province [2013B051000010]
Ask authors/readers for more resources
The feasibility of visible and near infrared hyperspectral imaging in the range of 400-1000 nm for determinating total viable counts (TVC) to evaluate microbial spoilage of fish fillets was investigated. Partial least square regression (PLSR) and least square support vector machines (LS-SVM) models established based on full wavelengths showed excellent performances and the LS-SVM model was better with higher residual predictive deviation (RPD) of 3.89, determination coefficients in prediction (R(2)p) of 0.93 and lower root mean square errors in prediction (RMSEP) of 0.49 log(10) CFU/g. Seven optimal wavelengths were selected by successive projections algorithm (SPA) and the simplified SPA-PLSR was better than SPA-LS-SVM models with RPD of 3.13, R(2)p of 0.90 and RMSEP of 0.57 log(10) CFU/g, and was transferred to each pixel of the hyperspectral images for generating the TVC distribution map. This study showed that hyperspectral imaging is suitable to determine TVC value for evaluating microbial spoilage of grass carp fillets in a rapid and non-invasive manner. (C) 2015 Elsevier Ltd. All rights reserved.
Authors
I am an author on this paper
Click your name to claim this paper and add it to your profile.
Reviews
Recommended
No Data Available