Different methods of image segmentation in the process of meat marbling evaluation

Ludwiczak, Agnieszka; Śłósarz, P.; Lisiak, D.; Przybylak, Andrzej; Boniecki, P.; Stanisz, Marek; Koszela, Krzysztof; Zaborowicz, Maciej; Przybył, Krzysztof; Wojcieszak, Dawid; Janczak, Damian; Bykowska, Marta

doi:10.1117/12.2197071

Cited by 3 publications

(2 citation statements)

References 16 publications

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“…It is recognized that intramuscular fat (IMF), usually perceived by consumers as marbling, plays an important role in the eating quality of beef, affecting both sensory and physical-chemical properties. IMF can be predicted by image analysis and is considered an indicator for the assessment of marbling level (LUDWICZAK et al, 2015). An intramuscular fat of 6.68% corresponds to 'light' marbling meat, in agreement with the measures of 'light' marbling (3.3 points) obtained by the visual observation of the photos using the Brazilian scoring system.…”

Section: Meat Characteristicssupporting

confidence: 68%

Performance and body composition of young Nellore bulls slaughtered at different body weights

Passetti

Macêdo

Teixeira

et al. 2019

SCA

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The objective of this work was to evaluate the effect of slaughter body weight on the quantitative characteristics of carcasses and the yield of commercial cuts of young Nellore bulls. Twenty-four non-castrated, 11-month-old, feedlot-fed Nellore bulls were distributed in a completely randomized design, in three treatments: 350 kg, 400 kg or 450 kg of body weight at slaughter (SBW). Slaughter was performed in a commercial slaughterhouse. The data were analyzed by an ANOVA followed by a Tukey test (p ? 0.05). SBW had no relationship with dry matter intake (6.05 kg/day or 75.74 g/kg BW0.75), feed efficiency (22.16) or feed conversion (4.67). Average daily gain was different depending on the SBW. Animal slaughtered at 350 kg had gained 1.17 kg/day, whereas animals slaughtered at 400 and 450 kg had gained 1.49 and 1.47 kg/day, respectively. Cold carcass weight increased with SBW (189.50, 209.33, and 242.39, respectively). Other carcass characteristics, like pH at 48 h (5.75), cold dressing carcass (52.61%), chilling losses (1.79%), fat thickness (5.54 mm), marbling (3.34 points), intramuscular fat (6.68%), longissimus muscle area (63.10 cm2) and sarcomere length (1.60 ?m), were not affected by SBW, but SBW increased cold carcass weight. The treatments had effects on the primary and commercial cut weights. However, the cut yields for the forequarter (39.84%), hindquarter (47.82%) and side-cut (12.34%), and the secondary cuts: chuck (14.38%), hump steak (1.94%), shoulder clod (16.97%), brisket point end (5.56%), neck steak (1.00%), striploin (7.77%), outside flat (5.30%), topside (9.36%), tenderloin (2.16%), flank steak (3.41%), eyeround (2.67%), rump tail (1.20%), rump eye (3.89%), shank (4.44%), knuckle (5.25%) and rump cap (1.40%), were not affected by SBW. SBW did not influence (p > 0.05) the commercial cut compositions for all cuts in the forequarter and hindquarter. Finishing young bulls in a feedlot is a strategy to produce beef with reduced feed costs. After all, the slaughter body weight (350, 400 or 450 kg) influenced the quantitative characteristics of the carcass; however, it did not affect the yield of commercial cuts from young Nellore bulls.

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Section: Meat Characteristicssupporting

confidence: 68%

Performance and body composition of young Nellore bulls slaughtered at different body weights

Passetti

Macêdo

Teixeira

et al. 2019

SCA

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“…One of the most common issues encountered in the literature concerning agricultural production using artificial neural networks (ANNs) are classification and prediction problems. Examples of the use of this type of modern method are research on the application of modern methods as an alternative or support for processes encountered in agriculture [15], both in classification and prediction issues.…”

Section: Introductionmentioning

confidence: 99%

Quality Evaluation of Potato Tubers Using Neural Image Analysis Method

et al. 2020

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This paper describes the research aimed at developing an effective quality assessment method for potato tubers using neural image analysis techniques. Nowadays, the methods used to identify damage and diseases are time-consuming, require specialized knowledge, and often rely on subjective judgment. This study showed the use of the developed neural model as a tool supporting the evaluation of potato tubers during the sorting process in the storage room.

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Image Segmentation Method Based on Statistical Parameters of Homogeneous Data Set

Shkurat

Sulema

Suschuk-Sliusarenko

et al. 2019

Advances in Artificial Systems for Medicine and Education II

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Different methods of image segmentation in the process of meat marbling evaluation

Cited by 3 publications

References 16 publications

Performance and body composition of young Nellore bulls slaughtered at different body weights

Performance and body composition of young Nellore bulls slaughtered at different body weights

Quality Evaluation of Potato Tubers Using Neural Image Analysis Method

Image Segmentation Method Based on Statistical Parameters of Homogeneous Data Set

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