A novel approach to grading pork carcasses: computer vision and ultrasound

Fortin, A.; Tong, A. K. W.; Robertson, W. M.; Zawadski, S.; Landry, Samuel J.; Robinson, Desmond; Liu, Tingting; Mockford, R.J.

doi:10.1016/s0309-1740(02)00104-3

Cited by 49 publications

(19 citation statements)

References 18 publications

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“…F1 Large White × Landrace) and primarily Duroc terminal boars, wheat/barley based diets and slaughter weights around 110-115 kg (Fortin et al 2005;Fortin et al 2003;Juárez et al 2009). Product differentiation at the retail level is minimal and mainly based on credence quality attributes, such as animal welfare or lack of use of antibiotics.…”

Section: Introductionmentioning

confidence: 99%

Relative contribution of breed, slaughter weight, sex and diet to the fatty acid composition of differentiated pork

et al. 2016

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Section: Introductionmentioning

confidence: 99%

Relative contribution of breed, slaughter weight, sex and diet to the fatty acid composition of differentiated pork

et al. 2016

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“…The US has been tested since the early 1950s and it has been performed in live animals or carcasses to measure fat thickness and assess the quality of meat (Fortin et al, 2003). The US has also been used to study intramuscular fat in live pigs (Newcom et al, 2002) and in other species, such in cattle to study the repeatability and accuracy of US in measuring backfat (Brethour, 1992) and sheep to study estimation of sheep carcass composition using real-time ultrasound (Silva et al, 2006).…”

Section: A) Visual Image Analysis By Monitoringmentioning

confidence: 99%

Imaging technologies to study the composition of live pigs: A review

Carabús¹,

Gispert²,

Font-i-Furnols³

2016

Span. j. agric. res.

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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.

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“…The belly was squared, skinned and trimmed. Fortin et al (2003) provided a detailed description of the cutting procedure used. Grade yield is defined as follows:…”

Section: Duction (Anonymous 2002)mentioning

confidence: 99%

The relationships of fat thickness and muscle depth with grade yield in pork carcasses

Fortin¹

2004

Can. J. Anim. Sci.

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Fortin, A. 2004. The relationships of fat thickness and muscle depth with grade yield in pork carcasses. Can. J. Anim. Sci. 84: 297-300. Under the Canadian pork grading system, grade yield, a function of fat thickness and muscle depth, is estimated from a prediction equation derived from a national sample. Data from the 1992 National project (Québec, n = 306; Ontario, n = 306; Alberta, n = 262) are used to examine the relevancy of a national sampling on these relationships. Regional origin did not have an effect (P > 0.05) on the relationship of grade yield with fat thickness whereas it did (P < 0.05) for the relationship with muscle depth.Key words: Canada pork grading, grade yield , fat thickness, muscle depth, sampling Fortin, A. 2004. Lien de l'épaisseur de la couche de gras et de l'épaisseur du muscle avec le rendement des carcasses de porc au classement. Can. J. Anim. Sci. 84: 297-300. Dans le système canadien de classement du porc, la catégorie dépend de l'épais-seur de la couche de gras et de l'épaisseur du muscle. On l'établit au moyen d'une équation prévisionnelle élaborée à partir d'un échantillon national. L'auteur se sert des données de 1992 du projet national (Québec, n = 306; Ontario, n = 306; Alberta, n = 262) pour vérifier la pertinence d'un tel échantillonnage sur la relation entre ces paramètres. La provenance régionale n'a aucune incidence (P > 0,05) sur le lien entre la catégorie et l'épaisseur de la couche de gras, mais elle en a bien une (P < 0,05) sur le lien entre la catégorie et l'épaisseur du muscle.Mots clés: Système canadien de classement du porc, rendement au classement, épaisseur de la couche de gras, épaisseur du muscle, échantillonnage 297In Canada, the overall objective of the pork carcass grading is to identify the true commercial value of a carcass by segregating carcasses on the basis of lean content and carcass weight (Fortin 1989). The Canadian grading system has elements of a classification scheme in that it uses the objective determination of grade yield in the carcass for establishing a carcass grade. It makes use of the negative relationship between fat thickness and carcass lean and the positive relationship between depth of the loin and carcass lean. Under the Canadian grading system, the grade yield of the carcass is estimated from a prediction equation based on fat thickness and muscle depth measured with a light reflectance probe between the 3rd and 4th last ribs, 7 cm off the exposed surface of the split carcass. Until 1996, the Canadian grading system was truly a national system: a unique prediction equation was used, delivery of grading was uniform across Canada and under the responsibility of Agriculture and Agri-Food Canada. With the exception of the 1986 equation (Fortin et al. 1984), the unique prediction equation was derived from national cutouts (Fredeen 1967;Martin et al. 1981; CPC 1994). Carcasses were obtained from all pork-producing regions of Canada to ensure that the prediction equation could be used across the country as there were concerns in the ...

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A novel approach to grading pork carcasses: computer vision and ultrasound

Cited by 49 publications

References 18 publications

Relative contribution of breed, slaughter weight, sex and diet to the fatty acid composition of differentiated pork

Relative contribution of breed, slaughter weight, sex and diet to the fatty acid composition of differentiated pork

Imaging technologies to study the composition of live pigs: A review

The relationships of fat thickness and muscle depth with grade yield in pork carcasses

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