Swine carcasses classified by degree of exudation and marbling content

Abstract

-The objective of this work was to develop and evaluate prediction equations, based on measurements obtained on the slaughter line, for carcass classification according to the degree of exudation and the content of marbling. A total of 747 pig carcasses originated from 27 producers were randomly selected on the slaughter line at two slaughterhouses, constituting representative samples from each one. Hot carcass weight, loin depth, back fat thickness, and pH and temperature 45 min after slaughter were used to generate the equations. The carcasses were classified as normal or exudative for drip loss of loin and ham, and as acceptable or undesirable for marbling content. For drip loss of loin and ham, respectively, the overall correct classification of the carcasses was 87.3 and 76.8%, using the discriminant functions, for both categories. For marbling, the overall correct classification was 67.2%, and only 69% of the carcasses were correctly classified as acceptable (marbling >1). The equations developed based on the measurements obtained on the slaughter line allow classifying swine carcasses with high accuracy, according to the degree of exudation, but not with the content of marbling.Index terms: drip loss, ham, loin, pigs, prediction equations. Carcaças suínas classificadas por grau de exsudação e conteúdo de marmoreioResumo -O objetivo deste trabalho foi desenvolver e avaliar equações de predição, baseadas em medidas obtidas na linha de abate, para classificação de carcaças suínas de acordo com o grau de exsudação e o conteúdo de marmoreio. Um total de 747 carcaças suínas, provenientes de 27 produtores, foi selecionado ao acaso na linha de abate, em dois abatedouros, tendo constituído amostras representativas de cada um. Para gerar as equações, foram utilizados peso da carcaça quente, profundidade do lombo, espessura de toucinho, e pH e temperatura medidos 45 min após o abate. As carcaças foram classificadas em normais ou exsudativas, quanto à perda por gotejamento do lombo e do pernil, e em aceitáveis ou indesejáveis, quanto ao marmoreio. Para a perda por gotejamento do lombo e do pernil, respectivamente, a classificação correta global das carcaças foi de 87,3 e 76,8%, a partir das funções discriminantes, para ambas as categorias. Para o marmoreio, a classificação correta global foi de 67,2%, e apenas 69% das carcaças foram classificadas corretamente como aceitáveis (marmoreio >1). As equações desenvolvidas com base nas medidas obtidas na linha de abate permitem classificar com elevada acurácia as carcaças suínas, de acordo com o grau de exsudação, mas não com o conteúdo de marmoreio.Termos para indexação: perda por gotejamento, pernil, lombo, porcos, equações de predição.

The relationship of pork carcass weight and leanness parameters in the Ontario commercial pork industry

“…Additionally, the weak negative correlation observed between hot carcass weight and predicted lean yield ( r = −0.235; P < 0.0001; Figure 3 ) were similar to previous scientific observations ( Fahey et al, 1977 ; Grisdale et al, 1984 ; Miar et al, 2014 ; Bertol et al, 2017 ). The weak correlation with hot carcass weight demonstrated the poor ability to predict lean yield at both lighter and heavier than average weights.…”

Classification accuracy of different pork quality evaluation methods in assessment of meat with lowered drip loss

“…However in survey of TRAORE et al (2012) no statistical differences in GP were noted between pork with DL 48 below 2.8% and above 4%. BERTOL et al (2017) suggested, that 87.33% of correctly classified carcasses with DL 48 below and above 6% is possible to evaluate on the basis of linear discriminant function using HCW, backfat thickness and loin depth in conjunction with pH and temperature measured at 45 min after slaughter. Also, as reported by cited authors using adjusted regression equations on the basis of the same parameters 85.44% of correctly classified carcasses to DL 48 threshold value of 6% and 80.32% to DL 48 threshold value of 5% could be obtain.…”