Automatic ham classification method based on support vector machine model increases accuracy and benefits compared to manual classification.

The thickness of the subcutaneous fat (SFT) is a very important parameter in the ham, since determines the process the ham will be submitted. This study compares two methods to predict the SFT in slaughter line: an automatic system using an SVM model (Support Vector Machine) and a manual measurement of the fat carried out by an experienced operator, in terms of accuracy and economic benefit. These two methods were compared to the golden standard obtained by measuring SFT with a ruler in a sample of 400 hams equally distributed within each SFT class. The results show that the SFT prediction made by the SVM model achieves an accuracy of 75.3%, which represents an improvement of 5.5% compared to the manual measurement. Regarding economic benefits, SVM model can increase them between 12 and 17%. It can be concluded that the classification using SVM is more accurate than the one performed manually with an increase of the economic benefit for sorting.

[1]  Nasser M. Nasrabadi,et al.  Pattern Recognition and Machine Learning , 2006, Technometrics.

[2]  Marina Gispert,et al.  Comparison of different devices for predicting the lean meat percentage of pig carcasses. , 2009, Meat science.

[3]  H. Busk,et al.  The estimated accuracy of the EU reference dissection method for pig carcass classification. , 2006, Meat science.

[4]  Carmen García,et al.  Texture and appearance of dry cured ham as affected by fat content and fatty acid composition , 2000 .

[5]  Antonio Velarde,et al.  Carcass and meat quality characteristics of immunocastrated male, surgically castrated male, entire male and female pigs. , 2010, Meat science.

[6]  Norman G. Marriott,et al.  ACCELERATED DRY CURING OF PORK LEGS (HAMS): A REVIEW , 1992 .

[7]  G. T. Schelling,et al.  Fatty acid profiles and sensory and carcass traits of tissues from steers and swine fed an elevated monounsaturated fat diet. , 1987, Journal of animal science.

[8]  R. Fernando,et al.  Influence of slaughter weight on growth and carcass characteristics, commercial cutting and curing yields, and meat quality of barrows and gilts from two genotypes. , 1996, Journal of animal science.

[9]  Fidel Toldrá,et al.  Dry-cured ham flavour: enzymatic generation and process influence , 1997 .

[10]  M. Čandek-Potokar,et al.  Factors in pig production that impact the quality of dry-cured ham: a review. , 2012, Animal : an international journal of animal bioscience.

[11]  Marjeta Čandek-Potokar,et al.  Comparison of national ZP equations for lean meat percentage assessment in SEUROP pig classification. , 2016, Meat science.

[12]  N Warnants,et al.  Incorporation of dietary polyunsaturated fatty acids in pork tissues and its implications for the quality of the end products. , 1996, Meat science.

[13]  Anil K. Jain,et al.  Statistical Pattern Recognition: A Review , 2000, IEEE Trans. Pattern Anal. Mach. Intell..

[14]  Pere Marti-Puig,et al.  On-line Ham Grading using pattern recognition models based on available data in commercial pig slaughterhouses. , 2018, Meat science.

[15]  J. Pulkrábek,et al.  Pig carcass quality in relation to carcass lean meat proportion , 2018 .

[16]  J. R. Landis,et al.  The measurement of observer agreement for categorical data. , 1977, Biometrics.

[17]  A. Velarde,et al.  Relationships between carcass quality parameters and genetic types. , 2007, Meat science.

[18]  F. Toldrá,et al.  The role of muscle proteases and lipases in flavor development during the processing of dry-cured ham. , 1998, Critical reviews in food science and nutrition.

[19]  H. Busk,et al.  On-line measurements in pig carcass classification: Repeatability and variation caused by the operator and the copy of instrument. , 2007, Meat science.

[20]  H. Busk,et al.  On-line pork carcass grading with the Autofom ultrasound system. , 1998, Journal of animal science.

[21]  Martin Škrlep,et al.  Comparison of entire male and immunocastrated pigs for dry-cured ham production under two salting regimes. , 2016, Meat science.

[22]  P. Bosi,et al.  The production of the heavy pig for high quality processed products , 2004 .

[23]  G Monin,et al.  Time-related changes in intramuscular lipids of French dry-cured ham. , 1994, Meat science.