Comparison of rapid techniques for classification of ground meat

Autor: Nolasco Pérez, Irene Marivel, 1973, Cruz-Tirado, Luis Jam Pier, Pollonio, Marise Aparecida Rodrigues, 1961, Barbin, Douglas Fernandes, 1980
Přispěvatelé: UNIVERSIDADE ESTADUAL DE CAMPINAS
Rok vydání: 2019
Předmět:
Zdroj: Repositório da Produção Científica e Intelectual da Unicamp
Universidade Estadual de Campinas (UNICAMP)
instacron:UNICAMP
Popis: Agradecimentos: This study was financed in part by the Coordenação de Aperfeiçoamento de Pessoal de Nível Superior - Brasil (CAPES) - Finance Code 001. Irene Marivel Nolasco Pérez acknowledges Coordination for the Improvement of Higher Education Personnel (CAPES) for the scholarship. The authors acknowledge the Brazilian National Council for Scientific and Technological Development (CNPq) (Grant no. 404852/2016-5), São Paulo Research Foundation (FAPESP), Young Researchers Award (Grant no. 2015/24351-2); FAPESP Grant no. 2008/57808-1 and 2014/50951-4; CNPq Grant no. 465768/2014-8. The authors kindly acknowledge the support provided by Mrs. Cristiane Vidal during NIR-HSI system operation and data processing Abstract: Computer vision and near infrared spectroscopy are fast and non-invasive techniques currently available for processing control in the meat industry. These techniques can be used, either separately or combined, for on-line assessment of meat quality parameters. This study aimed to compare a portable near-infrared (NIR) spectrometer, near infrared hyperspectral imaging (NIR-HSI) and red, green and blue imaging (RGB-I) to differentiate ground samples from beef, pork and chicken meat; and to quantify amounts of each in mixtures. Chicken breast meat was adulterated with either pork leg meat or beef round meat from 0 to 50% (w/w). Partial Least Squares regression (PLSR) models were performed using full spectra and after selecting most important wavelengths. The best results were obtained with NIR-HSI, with coefficient of prediction (RP2) of 0.83 and 0.94, ratio performance to deviation (RPD) of 1.96 and 3.56, and ratio of error range (RER) of 10.0 and 18.1, for samples of chicken adulterated with pork and beef, respectively. In addition, the results obtained using NIR spectroscopy and RGB-I confirm that these techniques provide an alternative for rapid, on-line inspection of ground meat in the food industry CONSELHO NACIONAL DE DESENVOLVIMENTO CIENTÍFICO E TECNOLÓGICO - CNPQ COORDENAÇÃO DE APERFEIÇOAMENTO DE PESSOAL DE NÍVEL SUPERIOR - CAPES FUNDAÇÃO DE AMPARO À PESQUISA DO ESTADO DE SÃO PAULO - FAPESP Fechado
Databáze: OpenAIRE
Externí odkaz: