Video image analysis for on-line classification of lamb carcasses

Stanford, Kim; Richmond, R. J.; Jones, S. D. M.; Robertson, W. M.; Price, M. A.; Gordon, Aaron

doi:10.1017/s1357729800010079

Cited by 31 publications

(16 citation statements)

References 13 publications

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“…In this study and the studies by Stanford et al (1998), Brady et al (2003) and Rius-Vilarrasa et al (2009), the VIA technology predicted lean meat yield in the leg with the highest accuracy and lean in the loin, with the poorest accuracy of the three primal regions. Stanford et al (1998) did not find any significant VIAscan ® variables to use for predicting lean in the loin and concluded that this was because of the little variation found in this trait.…”

Section: Classification Trialmentioning

confidence: 50%

“…Stanford et al (1998) did not find any significant VIAscan ® variables to use for predicting lean in the loin and concluded that this was because of the little variation found in this trait. The poor performance in predicting lean in the loin in this study could be influenced by the decision to exclude the flanks from the loin, as this reduced the Loin% variability.…”

Section: Classification Trialmentioning

confidence: 97%

“…According to Stanford et al (1998) and Hopkins et al (2004), the VIAscan ® also performed better than the systems used as benchmarks for prediction of lean yield. Studies on other VIA systems for lamb carcasses have shown similar results (Horgan et al, 1995;Brady et al, 2003;Cunha et al, 2004).…”

Section: Classification Trialmentioning

confidence: 99%

“…The accuracy of the prediction equations based on VIAscan ® parameters was within the range of previous findings. Hopkins et al (2004) presented an R 2 value of 0.52 when predicting lean meat yield based on a model including VIAscan ® parameters, and Stanford et al (1998) reported an R 2 of 0.71 using seven VIA parameters and carcass weight. Brady et al (2003) studied the ability of the lamb vision system (LVS) where six parameters along with HCW explained 60% of the variation in saleable meat yield (%), and Cunha et al (2004) reported an R 2 value of 0.68 also based on the LVS technology.…”

Section: Classification Trialmentioning

confidence: 99%

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The ability of video image analysis to predict lean meat yield and EUROP score of lamb carcasses

Einarsson

Eythórsdóttir

Smith³

et al. 2014

animal

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A total of 862 lamb carcasses that were evaluated by both the VIAscan ® and the current EUROP classification system were deboned and the actual yield was measured. Models were derived for predicting lean meat yield of the legs (Leg%), loin (Loin%) and shoulder (Shldr%) using the best VIAscan ® variables selected by stepwise regression analysis of a calibration data set (n = 603). The equations were tested on validation data set (n = 259). The results showed that the VIAscan ® predicted lean meat yield in the leg, loin and shoulder with an R 2 of 0.60, 0.31 and 0.47, respectively, whereas the current EUROP system predicted lean yield with an R 2 of 0.57, 0.32 and 0.37, respectively, for the three carcass parts. The VIAscan ® also predicted the EUROP score of the trial carcasses, using a model derived from an earlier trial. The EUROP classification from VIAscan ® and the current system were compared for their ability to explain the variation in lean yield of the whole carcass (LMY%) and trimmed fat (FAT%). The predicted EUROP scores from the VIAscan ® explained 36% of the variation in LMY% and 60% of the variation in FAT%, compared with the current EUROP system that explained 49% and 72%, respectively. The EUROP classification obtained by the VIAscan ® was tested against a panel of three expert classifiers (n = 696). The VIAscan ® classification agreed with 82% of conformation and 73% of the fat classes assigned by a panel of expert classifiers. It was concluded that VIAscan ® provides a technology that can directly predict LMY% of lamb carcasses with more accuracy than the current EUROP classification system. The VIAscan ® is also capable of classifying lamb carcasses into EUROP classes with an accuracy that fulfils minimum demands for the Icelandic sheep industry. Although the VIAscan ® prediction of the Loin% is low, it is comparable to the current EUROP system, and should not hinder the adoption of the technology to estimate the yield of Icelandic lambs as it delivered a more accurate prediction for the Leg%, Shldr% and overall LMY% with negligible prediction bias.

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Section: Classification Trialmentioning

confidence: 50%

Section: Classification Trialmentioning

confidence: 97%

Section: Classification Trialmentioning

confidence: 99%

Section: Classification Trialmentioning

confidence: 99%

See 2 more Smart Citations

The ability of video image analysis to predict lean meat yield and EUROP score of lamb carcasses

Einarsson

Eythórsdóttir

Smith³

et al. 2014

animal

View full text Add to dashboard Cite

show abstract

“…The most promising and suitable technology developed in recent years is VIA (e.g. Stanford et al, 1998;Hopkins et al, 2004). This provides a non-invasive system operating at normal chain speeds and enables automatic acquisition of data on carcasses from the side and/or back view.…”

Section: Muscle Density and Intramuscular Fat (Imf)mentioning

confidence: 99%