Intramuscular fat prediction using color and image analysis of bísaro pork breed
Autor: | Severiano Silva, José M H Almeida, Marianne Hasse, Luís G. Dias, Alfredo Teixeira |
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Jazyk: | angličtina |
Rok vydání: | 2018 |
Předmět: |
Multivariate statistics
Health (social science) Longissimus Thoracis Plant Science lcsh:Chemical technology Health Professions (miscellaneous) Microbiology Article Image analysis 0404 agricultural biotechnology Polynomial kernel Statistics Bísaro pork lcsh:TP1-1185 Mathematics Image (category theory) 0402 animal and dairy science food and beverages Regression analysis Intramuscular fat 04 agricultural and veterinary sciences 040401 food science 040201 dairy & animal science Breed Discriminant Prediction Food Science |
Zdroj: | Foods, Vol 10, Iss 143, p 143 (2021) Foods Repositório Científico de Acesso Aberto de Portugal Repositório Científico de Acesso Aberto de Portugal (RCAAP) instacron:RCAAP Volume 10 Issue 1 |
Popis: | This work presents an analytical methodology to predict meat juiciness (discriminant semi-quantitative analysis using groups of intervals of intramuscular fat) and intramuscular fat (regression analysis) in Longissimus thoracis et lumborum (LTL) muscle of Bí saro pigs using as independent variables the animal carcass weight and parameters from color and image analysis. These are non-invasive and non-destructive techniques which allow development of rapid, easy and inexpensive methodologies to evaluate pork meat quality in a slaughterhouse. The proposed predictive supervised multivariate models were non-linear. Discriminant mixture analysis to evaluate meat juiciness by classified samples into three groups&mdash 0.6 to 1.1% 1.25 to 1.5% and, greater than 1.5%. The obtained model allowed 100% of correct classifications (92% in cross-validation with seven-folds with five repetitions). Polynomial support vector machine regression to determine the intramuscular fat presented R2 and RMSE values of 0.88 and 0.12, respectively in cross-validation with seven-folds with five repetitions. This quantitative model (model&rsquo s polynomial kernel optimized to degree of three with a scale factor of 0.1 and a cost value of one) presented R2 and RSE values of 0.999 and 0.04, respectively. The overall predictive results demonstrated the relevance of photographic image and color measurements of the muscle to evaluate the intramuscular fat, rarther than the usual time-consuming and expensive chemical analysis. |
Databáze: | OpenAIRE |
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