Predicting pork freshness using multi-index statistical information fusion method based on near infrared spectroscopy. (December 2018)

• Record Type: Journal Article
• Authors: Qu, Fangfang; Ren, Dong; He, Yong; Nie, Pengcheng; Lin, Lei; Cai, Chengyong; Dong, Tao
• Is Part Of: Meat science. Volume 146(2018)
• Page Start: 59
• Page End: 67
• Publication Date: 2018-12
• Subjects: Near infrared spectroscopy -- Pork freshness -- Variable selection -- Multi-index -- Information fusion -- Total volatile basic-nitrogen; Meat -- Periodicals; Meat industry and trade -- Periodicals; Viande -- Périodiques; Viande -- Industrie -- Périodiques; Meat; Meat industry and trade; Periodicals; 641.36
• DOI: 10.1016/j.meatsci.2018.07.023
• Languages: English
• ISSNs: 0309-1740

Abstract

Abstract: In this work, the near infrared spectroscopy (NIR) technology was applied to nondestructively evaluate the freshness of pork. The total volatile basic-nitrogen (TVB-N) and pH value of pork were detected as freshness evaluation indicators. A multi-index statistical information fusion (MSIF) modeling method based on variable selection was proposed to evaluate pork freshness. In the experiment, the proposed MSIF was compared with other state-of-the-art variable selection methods. Results showed that the proposed method achieved the best generalization performance and stability. The prediction correlation coefficient (Rval) and root mean square error (RMSEP) of MSIF were: Rval = 0.8618 and RMSEP = 3.910 for TVB-N content, Rval = 0.9379 and RMSEP = 0.1046 for pH value. The research demonstrated that NIR combined with MSIF has the potential for rapid and nondestructive determination of pork freshness, and so hopefully to provide a promising tool for monitoring meat quality and enriching the extracted information from food industry. Highlights: A multi-index statistical information fusion (MSIF) method was proposed to detect pork freshness. MSIF used an ensemble framework to select variables interactively. A comprehensive evaluation index (CEI) was proposed to control the selected variables in MSIF. TVB-N and pH of pork were detected as the freshness evaluation indicators. MSIF has good stability and precision in the quantitative detection of pork freshness.