Computer Vision Based Detection and Quantification of Extraneous Water in Raw Milk

Asefa, Bezuayehu Gutema; Hagos, Legesse; Kore, Tamirat; Emire, Shimelis Admassu

doi:10.21203/rs.3.rs-625039/v1

Cited by 2 publications

(1 citation statement)

References 7 publications

(11 reference statements)

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“…The Boran cattle cuts (sirloin and chuck) had relatively high amounts of fat (12.68 ± 0.59 and 12.40 ± 0.63%, respectively). These results are in agreement with those of [ 20 ], who reported a fat content of 2.6 ± 4.7 in a retail-ready meat sample. A low percentage of fat content was observed in the cuts from the Sheko breed (11.40 ± 0.87 and 11.17 ± 1.03) sirloin and chunk, respectively.…”

Section: Resultssupporting

confidence: 93%

Modeling of Ethiopian Beef Meat Marbling Score Using Image Processing for Rapid Meat Grading

Erena,

Belay,

Hailu

et al. 2024

J. Imaging

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Meat characterized by a high marbling value is typically anticipated to display enhanced sensory attributes. This study aimed to predict the marbling scores of rib-eye, steaks sourced from the Longissimus dorsi muscle of different cattle types, namely Boran, Senga, and Sheko, by employing digital image processing and machine-learning algorithms. Marbling was analyzed using digital image processing coupled with an extreme gradient boosting (GBoost) machine learning algorithm. Meat texture was assessed using a universal texture analyzer. Sensory characteristics of beef were evaluated through quantitative descriptive analysis with a trained panel of twenty. Using selected image features from digital image processing, the marbling score was predicted with R2 (prediction) = 0.83. Boran cattle had the highest fat content in sirloin and chuck cuts (12.68% and 12.40%, respectively), followed by Senga (11.59% and 11.56%) and Sheko (11.40% and 11.17%). Tenderness scores for sirloin and chuck cuts differed among the three breeds: Boran (7.06 ± 2.75 and 3.81 ± 2.24, respectively), Senga (5.54 ± 1.90 and 5.25 ± 2.47), and Sheko (5.43 ± 2.76 and 6.33 ± 2.28 Nmm). Sheko and Senga had similar sensory attributes. Marbling scores were higher in Boran (4.28 ± 1.43 and 3.68 ± 1.21) and Senga (2.88 ± 0.69 and 2.83 ± 0.98) compared to Sheko (2.73 ± 1.28 and 2.90 ± 1.52). The study achieved a remarkable milestone in developing a digital tool for predicting marbling scores of Ethiopian beef breeds. Furthermore, the relationship between quality attributes and beef marbling score has been verified. After further validation, the output of this research can be utilized in the meat industry and quality control authorities.

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Section: Resultssupporting

confidence: 93%