Prediction for Chemical Component of Pork Meat by Personal Computer Color Image Analysis (Research Note)

Kuchida, Keigo; Suzuki, K.; Yamaki, Kouya; Shinohara, Hiroyuki; Yamaguchi, Takahiro

doi:10.2508/chikusan.62.477

Cited by 2 publications

(2 citation statements)

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“…In recent years, computer-aided software has been developed and this software has been used for livestock production. Investigations have shown that the digital image analysis has been applied to determine meat quality, egg quality, marbling score, BM, liveweight and growth of pigs, rabbits, chickens, horses, goats, sheep and cattle (McDonald and Chen 1990;Kuchida et al 1991;Shackelford et al 1998;Shiranita et al 1998;Karnuah et al 2001;Cannell et al 2002;Teira et al 2003;De Wet et al 2003;Aktan 2004;Bozkurt et al 2007;Negretti et al , 2008Negretti et al , 2011Ozkaya and Bozkurt 2008;Wang et al 2008;Mollah et al 2010;Tasdemir et al 2011). Stajnko et al (2008) reported that the BM and liveweight of the bulls were estimated by thermal camera.…”

Section: Introductionmentioning

confidence: 99%

Accuracy of body measurements using digital image analysis in female Holstein calves

Özkaya¹

2012

Anim. Prod. Sci.

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The objective of this study was to determine the accuracy of body measurements (BM) in Holstein female calves using digital image analysis. BM including body length, wither height, chest depth, hip height, and hip width of calves were recorded by stick and tape measurements at birth, weaning and 24 weeks of age. Then photos of calves were taken while calves were standing in a squeeze chute by a digital camera and were analysed by image analysis software to obtain BM of each calf from the image in centimetres. After comparing the actual and predicted BM, the accuracy was determined as 71, 97 and 99% for body length, 69, 87 and 99% for wither height, 43, 98 and 99% for chest depth, 74, 99 and 99% for hip height and 53, 99 and 98% for hip width at birth, weaning and 24 weeks of age, respectively. The difference between actual and predicted BM was significant at birth (P < 0.01). Although there were numerical differences between actual and predicted BM, the differences were not significant at weaning and 24 weeks of age (P > 0.01). According to these results, the BM estimation of Holstein female calves using digital image analysis produced high prediction accuracy at weaning and 24 weeks of age, but not at birth. The data presented in this study indicate that the digital image analysis provides very close agreement and reality for prediction of BM of Holstein female calves.

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Section: Introductionmentioning

confidence: 99%

Accuracy of body measurements using digital image analysis in female Holstein calves

Özkaya¹

2012

Anim. Prod. Sci.

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“…LI et al, (1997) showed that brittleness of meat could be determined by vision texture analysis. Similarly, investigations have shown this method can be used to analyze meat, determine marbling score and evaluate MLD area (NEWMAN, 1984;KUCHIDA et al, 1991;SHACKELFORD et al, 1998;SHIRANITA et al, 2000;KARNUAH et al, 2001;CANNELL et al, 2002;TEIRA et al, 2003). BOZKURT et al, (2006) used digital image analysis technology regarding prediction of body weight from body measurements in beef cattle.…”

Section: Introductionmentioning

confidence: 99%

The relationship of parameters of body measures and body weight by using digital image analysis in pre-slaughter cattle

Özkaya

Bozkurt

2008

Arch. Anim. Breed.

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The relationship of parameters of body measures and body weight by using digital image analysis in pre-slaughter cattle AbstractThe objective of this study was to predict body weight (BW) of pre-slaughtering beef cattle using digital image analysis. Data used in this study were collected from slaughterhouses in Isparta and nearby provinces from 140 animals. Selected body measurements such as body weight (BW), wither height (WH), body length (BL), chest depth (CD), hip width (HW), hip height (HH) and body area (BA) of different breeds of beef cattle were combined and compared by digital image analysis. The body area was included as a different parameter for prediction of BW instead of chest girth. However, regression equation that included only body area gave the lowest R 2 value for Holstein (18.0%), but the R 2 value was 43.2 and 51.7% for Brown Swiss and crossbred animals, respectively. The regression equation which included all body traits resulted in R 2 values 35.3, 85.1, and 79.6% for Holstein, Brown Swiss and crossbred, respectively. The regression equation which included body area and body length showed that prediction ability of digital image analysis was high for prediction of BW in Brown Swiss and crossbred animals compared to Holsteins (R 2 82.6, 76.5, and 29.5%, respectively). Results indicated that the prediction ability of digital image analysis was low for prediction of BW. Although possibility of using body area as a parameter in predicting BW is low it can be developed by further and better designed experiments.

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Prediction for Chemical Component of Pork Meat by Personal Computer Color Image Analysis (Research Note)

Cited by 2 publications

References 3 publications

Accuracy of body measurements using digital image analysis in female Holstein calves

Accuracy of body measurements using digital image analysis in female Holstein calves

The relationship of parameters of body measures and body weight by using digital image analysis in pre-slaughter cattle

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