A preliminary study on the development of an easy method for beef freshness using a cyclic voltammetric system

Noh, Dae-Hyun; Chung, ShuYing; Choi, Seung-Yun; Hur, Sun

doi:10.1016/j.foodcont.2010.06.007

Cited by 5 publications

(1 citation statement)

References 9 publications

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“…So it is an important index to evaluate the degree of beef freshness [1]. At present, the detection of beef freshness mainly includes sensory detection, physical and chemical detection, microbial detection, and so on [2][3][4][5][6]. However, these traditional detection methods are not conducive to the rapid detection of beef freshness in the product circulation.…”

Section: Introductionmentioning

confidence: 99%

Determination of Total Volatile Basic Nitrogen (TVB-N) Content in Beef by Hyperspectral Imaging Technique

Liu

2016

MATEC Web of Conferences

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Abstract. Non-destructive determination of TVB-N content in beef using hyperspectral imaging (HSI) technique was evaluated. In order to create a robust model to predict the TVB-N content in beef, partition of sample set, spectral pretreatment, and the optimum wavelength selection were discussed. After the beef sample set was parted by concentration gradient (CG) algortithm, and the spectra of beef samples were preprocessed by standard normalized variate (SNV) combined with auto scale(AS), the partial least square regression (PLSR) model was established using the full spectral range, which had the best prediction abilities with R cv 2 of 0.9124, R p 2 of 0.8816, RMSECV of 1.5889, and RMSEP of 1.7719, respectively. After the optimum wavelengths which is closely related to the TVB-N content of beef samples was obtained using the competitive adaptive reweighted (CARS) algorithm, a new PLSR model was established using the optimum wavelengths, which had outstanding prediction abilities with R cv 2 of 0.9235, R p 2 of 0.9241, RMSECV of 1.4881, and RMSEP of 1.4882, respectively.The study showed that HSI is a powerful technique to predict the TVB-N content in beef by a nondestructive way.

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