Understanding consumers' perceptions towards Iberian pig production and animal welfare.

The Spanish market offers a greater variety of Iberian pork products. The aim of this paper is to determine the perception of consumers of several aspects of Iberian pig production and animal welfare depending on the consumers' characteristics. Consumers from two Spanish regions (n = 403) answered a questionnaire about their beliefs and the importance of pig production, their purchase intentions and their willingness to pay. Consumers were segmented according to their level of knowledge about Iberian pig production. The results of this work indicate that consumers have poor knowledge about Iberian pig production. Even so, consumers show a remarkable preference for Iberian products, especially when the animals are reared freely and in natural conditions, giving great importance to animal welfare. Consumer preferences indicate the importance of emphasizing Iberian traditional pig product characteristics on the label to promote their purchase choices.

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.

Comparison of national ZP equations for lean meat percentage assessment in SEUROP pig classification.

The objectives of the present work were (1) to compare pig carcass classification using different ZP ("Zwei-Punkt-Messverfahren") equations approved in the EU, applied on the same dataset, and to discuss the origin of differences between member states; (2) to evaluate the effect of a possible common ZP equation from the combined dataset and analyse how do the different subsets perform; and (3) to discuss the consequences of different national equations within the EU in view of the harmonization of pig carcass classification. A dataset of 951 carcasses from Belgium, France, Germany, Slovenia and Spain was used, 12 approved ZP equations in Europe were applied and the results were compared. Observed differences can be due not only to differences in genetics and sexes, but also to differences in the ZP measurement and dissection trials performed to obtain national equations. Important differences between some equations (up to almost 5 lean meat percentage) indicate a low harmonization among them and a need for improvements.