Monells, Spain
Monells, Spain

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Font-i-Furnols M.,IRTA Product Quality | Candek-Potokar M.,Agricultural Institute of Slovenia | Candek-Potokar M.,University of Maribor | Daumas G.,IFIP Institute du Porc | And 3 more authors.
Meat Science | Year: 2016

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. © 2015 Elsevier Ltd.


PubMed | IFIP Institute du Porc, IRTA Product Quality, Ghent University, Agricultural Institute of Slovenia and MRI Institute of Safety and Quality of Meat
Type: | Journal: Meat science | Year: 2016

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.


PubMed | IRTA Product Quality, Danish Technological Institute DTI, Gorbatovs All Russian Meat Research Institute VNIIMP, Nanjing Agricultural University and Connecting Agri and Food
Type: | Journal: Meat science | Year: 2016

The aim of this work was to study the sensitivity of Chinese and Russian female consumers to androstenone and skatole and to identify their preference for pork patties from entire male pigs compared with those from castrated pigs. One-hundred-twenty women in each country were enrolled. The sensitivity of the consumers to both compounds was tested using smell strips and triangular tests. Pairwise tests were performed comparing patties from castrated male pigs with patties from boars with different levels of androstenone and skatole. Approximately 70% of the Russian and 60% of the Chinese consumers were sensitive to skatole and 37% and 32% were sensitive to androstenone, respectively. Nevertheless, a higher percentage of sensitive Russian consumers compared to Chinese consumers disliked the smell of both compounds. In Russia, the consumers preferences were higher for patties with low levels of both compounds, while no differences were found in China. In both countries, consumers who were sensitive to skatole also preferred patties with low levels of both compounds. Thus, the levels of androstenone and skatole affect boar patty preferences.


Font-i-Furnols M.,IRTA Product Quality | Brun A.,IRTA Product Quality | Tous N.,IRTA Monogastric Nutrition | Tous N.,Rovira i Virgili University | Gispert M.,IRTA Product Quality
Chemometrics and Intelligent Laboratory Systems | Year: 2013

The intramuscular fat (IMF) content is related to the sensory acceptability of pork, and it can be non-destructively estimated using computed tomography (CT). The aim of this paper is to evaluate the potential use of ordinary linear regression (OLR) of the relative volumes associated with ranges of Hounsfield (HU) values and partial least square (PLS) regression applied to the relative volumes associated with each individual HU value to predict the IMF content using data from one or two different tomograms. The tomograms were obtained from pork loins, and the relative volume associated with each HU value was calculated. The IMF was measured in the loins using a near infrared transmittance device. The best prediction of IMF was obtained by OLR when data from 2 tomograms were used (R2=0.83 and RMSEPCV=0.46%). The results suggest that CT has good potential for measuring the IMF in loins and that the accuracy improves when the data from 2 tomograms were combined. The use of partial volumes as predictors with OLR allows for improved accuracy compared to the use of all of the individual volumes with PLS. © 2013 Elsevier B.V.


Carabus A.,IRTA Product Quality | Gispert M.,IRTA Product Quality | Brun A.,IRTA Product Quality | Rodriguez P.,IRTA Nutrition | Font-i-Furnols M.,IRTA Product Quality
Livestock Science | Year: 2014

The purposes of the present study were: (1) to evaluate variations in the body composition of three genetic types at the live weights of 30, 70, 100 and 120. kg by analysing live pigs with CT and (2) to determine the allometric growth of the main body parts in relation to body weight and lean, fat and bone contents in relation to the cut weight and body weight. Forty-five gilts of various genetic types: Duroc×(Landrace×Large White), Pietrain×(Landrace×Large White) and Landrace×Large White were scanned in vivo at 30, 70, 100 and 120. kg. CT images were analysed and used to predict the lean, fat and bone contents. The results reflected clear differences in the body compositions between crossbreeds, particularly when pigs were ≥ 100. kg. However, certain significant differences also appeared at the earliest weight of 30. kg, which demonstrates the importance of genetic traits. © 2014 Elsevier B.V.


Tous N.,IRTA Monogastric Nutrition | Lizardo R.,IRTA Monogastric Nutrition | Vila B.,IRTA Monogastric Nutrition | Gispert M.,IRTA Product Quality | And 2 more authors.
Meat Science | Year: 2013

Sixteen gilts were fed a control (4% of sunflower oil) or an experimental diet (4% conjugated linoleic acid (CLA) oil). CLA had no effect on intramuscular fat (IMF) content neither in longissimus thoracis (LT) nor in semimembranosus (SM) muscles but increased liver weight, reduced perirenal fat and tended to reduce backfat between the last 3th-4th lumbar vertebrae. Despite the fact that 9c,11t and 10t,12c CLA isomers were included in the same proportion in the diet, the 9c,11t and 9c,11c were the isomers more deposited in all tissues. Addition of CLA in the diet affected fatty acid composition in a tissue specific manner, increasing percentages of SFA in all tissues, reducing percentages of MUFA in LT and LT subcutaneous fat, and of PUFA in LT subcutaneous fat, liver and SM. The FA modification by dietary CLA in LT IMF was reflected in the different lipid fractions, SFA and MUFA mainly in the neutral lipid fraction, and PUFA in the polar fraction. © 2012 Elsevier Ltd.


Font-I-Furnols M.,IRTA Product Quality | Carabus A.,IRTA Product Quality | Pomar C.,Agriculture and Agri Food Canada | Gispert M.,IRTA Product Quality
Animal | Year: 2014

The aim of the present work was (1) to study the relationship between cross-sectional computed tomography (CT) images obtained in live growing pigs of different genotypes and dissection measurements and (2) to estimate carcass composition and cut composition from CT measurements. Sixty gilts from three genotypes (Duroc×(Landrace×Large White), Pietrain×(Landrace×Large White), and Landrace×Large White) were CT scanned and slaughtered at 30 kg (n=15), 70 kg (n=15), 100 kg (n=12) or 120 kg (n=18). Carcasses were cut and the four main cuts were dissected. The distribution of density volumes on the Hounsfield scale (HU) were obtained from CT images and classified into fat (HU between -149 and -1), muscle (HU between 0 and 140) or bone (HU between 141 and 1400). Moreover, physical measurements were obtained on an image of the loin and an image of the ham. Four different regression approaches were studied to predict carcass and cut composition: linear regression, quadratic regression and allometric equations using volumes as predictors, and linear regression using volumes and physical measurements as predictors. Results show that measurements from whole animal taken in vivo with CT allow accurate estimation of carcass and cut composition. The prediction accuracy varied across genotypes, BW and variable to be predicted. In general, linear models, allometric models and linear models, which included also physical measurements at the loin and the ham, produced the lowest prediction errors. © The Animal Consortium 2014.


Carabus A.,IRTA Product Quality | Gispert M.,IRTA Product Quality | Font-i-Furnols M.,IRTA Product Quality
Spanish Journal of Agricultural Research | Year: 2016

Image techniques are increasingly being applied to livestock animals. This paper overviews recent advances in image processing analysis for live pigs, including ultrasound, visual image analysis by monitoring, dual-energy X-ray absorptiometry, magnetic resonance imaging and computed tomography. The methodology for live pigs evaluation, advantages and disadvantages of different devices, the variables and measurements analysed, the predictions obtained using these measurements and their accuracy are discussed in the present paper. Utilities of these technologies for livestock purposes are also reviewed. Computed tomography and magnetic resonance imaging yield useful results for the estimation of the amount of fat and lean mass either in live pigs or in carcasses. Ultrasound is not sufficiently accurate when high precision in estimating pig body composition is necessary but can provide useful information in agriculture to classify pigs for breeding purposes or before slaughter. Improvements in factors, such as the speed of scanning, cost and image accuracy and processing, would advance the application of image processing technologies in livestock animals. © 2016 INIA.


Zomeno C.,IRTA Product Quality | Gispert M.,IRTA Product Quality | Carabus A.,IRTA Product Quality | Brun A.,IRTA Product Quality | Font-i-Furnols M.,IRTA Product Quality
Animal | Year: 2015

The aims of this study were (1) to evaluate the ability of computed tomography (CT) to predict the chemical composition of live pigs and carcasses, (2) to compare the chemical composition of four different sex types at a commercial slaughter weight and (3) to model and evaluate the chemical component growth of these sex types. A total of 92 pigs (24 entire males (EM), 24 surgically castrated males (CM), 20 immunocastrated males (IM) and 24 females (FE)) was used. A total of 48 pigs (12 per sex type) were scanned repeatedly in vivo using CT at 30, 70, 100 and 120 kg and slaughtered at the end of the experiment. The remaining 44 were CT scanned in vivo and slaughtered immediately: 12 pigs (4 EM, 4 CM and 4 FE) at 30 kg and 16 pigs each at 70 kg and 100 kg (4 per sex type). The left carcasses were CT scanned, and the right carcasses were minced and analysed for protein, fat, moisture, ash, Ca and P content. Prediction equations for the chemical composition were developed using Partial Least Square regression. Allometric growth equations for the chemical components were modelled. By using live animal and carcass CT images, accurate prediction equations were obtained for the fat (with a root mean square error of prediction (RMSEPCV) of 1.31 and 1.34, respectively, and R 2=0.91 for both cases) and moisture relative content (g/100 g) (RMSEPCV=1.19 and 1.38 and R 2=0.94 and 0.93, respectively) and were less accurate for the protein (RMSEPCV=0.65 and 0.67 and R 2=0.54 and 0.63, respectively) and mineral content (RMSEPCV from 0.28 to 1.83 and R 2 from 0.09 to 0.62). Better equations were developed for the absolute amounts of protein, fat, moisture and ash (kg) (RMSEPCV from 0.26 to 1.14 and R 2 from 0.91 to 0.99) as well as Ca and P (g) (RMSEPCV=144 and 71, and R 2=0.76 to 0.66, respectively). At 120 kg, CM had a higher fat and lower moisture content than EM. For protein, CM and IM had lower values than FE and EM. The ash content was higher in EM and IM than in FE and CM, while IM had a higher Ca and P content than the others. The castrated animals showed a higher allometric coefficient for fat and a lower one for moisture, with IM having intermediate values. However, for the Ca and P models, IM presented higher coefficients than EM and FE, and CM were intermediate. © The Animal Consortium 2015


PubMed | IRTA Product Quality
Type: Journal Article | Journal: Animal : an international journal of animal bioscience | Year: 2015

The aims of this study were (1) to evaluate the ability of computed tomography (CT) to predict the chemical composition of live pigs and carcasses, (2) to compare the chemical composition of four different sex types at a commercial slaughter weight and (3) to model and evaluate the chemical component growth of these sex types. A total of 92 pigs (24 entire males (EM), 24 surgically castrated males (CM), 20 immunocastrated males (IM) and 24 females (FE)) was used. A total of 48 pigs (12 per sex type) were scanned repeatedly in vivo using CT at 30, 70, 100 and 120 kg and slaughtered at the end of the experiment. The remaining 44 were CT scanned in vivo and slaughtered immediately: 12 pigs (4 EM, 4 CM and 4 FE) at 30 kg and 16 pigs each at 70 kg and 100 kg (4 per sex type). The left carcasses were CT scanned, and the right carcasses were minced and analysed for protein, fat, moisture, ash, Ca and P content. Prediction equations for the chemical composition were developed using Partial Least Square regression. Allometric growth equations for the chemical components were modelled. By using live animal and carcass CT images, accurate prediction equations were obtained for the fat (with a root mean square error of prediction (RMSEPCV) of 1.31 and 1.34, respectively, and R 2=0.91 for both cases) and moisture relative content (g/100 g) (RMSEPCV=1.19 and 1.38 and R 2=0.94 and 0.93, respectively) and were less accurate for the protein (RMSEPCV=0.65 and 0.67 and R 2=0.54 and 0.63, respectively) and mineral content (RMSEPCV from 0.28 to 1.83 and R 2 from 0.09 to 0.62). Better equations were developed for the absolute amounts of protein, fat, moisture and ash (kg) (RMSEPCV from 0.26 to 1.14 and R 2 from 0.91 to 0.99) as well as Ca and P (g) (RMSEPCV=144 and 71, and R 2=0.76 to 0.66, respectively). At 120 kg, CM had a higher fat and lower moisture content than EM. For protein, CM and IM had lower values than FE and EM. The ash content was higher in EM and IM than in FE and CM, while IM had a higher Ca and P content than the others. The castrated animals showed a higher allometric coefficient for fat and a lower one for moisture, with IM having intermediate values. However, for the Ca and P models, IM presented higher coefficients than EM and FE, and CM were intermediate.

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