Identification of turkey meat and processed products using near infrared spectroscopy. (January 2020)

• Record Type: Journal Article
• Authors: Barbin, Douglas Fernandes; Badaró, Amanda Teixeira; Honorato, Danielle C.B.; Ida, Elza Youko; Shimokomaki, Massami
• Is Part Of: Food control. Volume 107(2020)
• Publication Date: 2020-01
• Subjects: Authentication -- Ham -- Partial least squares -- Discriminant analysis -- Principal component analysis; Food -- Quality -- Periodicals; Food -- Analysis -- Periodicals; Food handling -- Periodicals; Food industry and trade -- Quality control -- Periodicals; Aliments -- Industrie et commerce -- Qualité -- Contrôle -- Périodiques; Aliments -- Qualité -- Périodiques; Aliments -- Analyse -- Périodiques; Hygiène alimentaire -- Périodiques; Food -- Analysis; Food handling; Food -- Quality; Periodicals; Electronic journals; 664.07
• DOI: 10.1016/j.foodcont.2019.106816
• Languages: English
• ISSNs: 0956-7135

Abstract

Abstract: Meat processors and consumers are greatly concerned about nutritional value, safety and quality of food products. Besides the reproducibility, which is a significant quality parameter of processed food product, the adulteration of meat products is a crucial concern for manufactures and consumers. Therefore, fast and objective techniques are demanded to ensure the quality of raw or processed meat. In the current study, near-infrared (NIR) spectroscopy was verified as a prospective technique to discriminate turkey cuts and processed turkey meat products. Spectral information in the wavelengths between 400 and 2500 nm of raw material and ready-to-eat turkey products were acquired and studied for their potential application for quality control and authentication. Principal component analysis (PCA) was explore the spectra information and samples were classified using linear discriminant analysis (LDA). PCA carried out on NIR dataset revealed the effect of chemical composition and quality features on the spectra. This investigation suggested that NIR spectroscopy is a convenient tool for quality evaluation of turkey meat. Highlights: NIR spectroscopy was used for turkey meat products classification. Multivariate statistical analysis was applied to spectral data. Turkey meat products were analysed by traditional analytical methods. LDA models could successfully classify samples according to spectral characteristics.