Machine effects on accuracy of ultrasonic prediction of backfat and ribeye area in beef bulls, steers and heifers

Charagu, Patrick; Crews, D. H.; Kemp, R. A.; Mwansa, P. B.

doi:10.4141/a99-044

Cited by 15 publications

(10 citation statements)

References 13 publications

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“…It was previously found that both FAT and marbling scores were greater in docile feedlot cattle when compared with excitable feedlot cattle (Schmidt et al, 2013). These conflicting results may be due to differences in gender, nutrition, and genetics between our study and theirs, all of which have been noted to influence FAT (Smith et al, 1984;Crouse et al, 1989;Charagu et al, 2000) and IMF (Field et al, 1966;Crouse et al, 1989;Pethick et al, 2004). Furthermore, Schmidt et al (2013) examined a large population (n = 2,877) where both calm and truly excitable cattle were present, which is in contrast to the smaller population size used in our study.…”

Section: Figurecontrasting

confidence: 56%

Relationships among temperament, behavior, and growth during performance testing of bulls1

Lockwood

Kattesh

Krawczel

et al. 2015

Journal of Animal Science

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Excitable cattle are dangerous to personnel and have reduced individual performance. The aim of this study was to 1) identify objective criteria for evaluating bull temperament and 2) examine relationships among temperament, behavior, and performance of bulls during an 84-d performance test. Angus bulls ( = 60) were reared in 6 pens based on BW and age. Pen scores (PS; 1 = docile and 5 = very aggressive) were assigned on d -1, 27, 55, and 83. Exit velocity (EV), BW, time to exit the chute, and order through the chute were recorded on d 0, 28, 56, and 84. The ADG was calculated for the 84-d test period, and ultrasound data and frame score calculations were recorded on d 84. Dataloggers measured steps taken, lying time, number of lying bouts, and lying bout duration of bulls ( = 27; 3 pens) from d 3 to 28 and d 59 to 84. Bulls with a d -1 PS of 1 or 2 were categorized as calm (PScalm; = 40), whereas bulls with a PS of 3 or 4 were categorized as excitable (PSexcitable; = 20). Bulls were separated into 2 groups based on the bottom 20 EV (EVcalm) and top 20 EV (EVexcitable) on d 0. Mixed model ANOVA (SAS 9.3) was used to compare groups for the two temperament assessment methods, behavior, and growth performance. Mean EV decreased ( < 0.05) by d 84. Total lying time from d 3 to 28 was greater ( < 0.05) for PScalm bulls when compared with PSexcitable bulls. However, total lying time from d 59 to 84 was greater ( < 0.05) for EVexcitable bulls when compared with EVcalm bulls. Regardless of initial contemporary group assignment, all bulls exited the chute slower ( < 0.001) on d 84 than on d 0. The PSexcitable bulls had greater ( < 0.01) frame scores and greater ADG than PScalm bulls. The PSexcitable bulls had more ( < 0.01) backfat than PScalm bulls. However, ribeye area was smaller ( < 0.01) in EVexcitable bulls than EVcalm bulls. Based on these results, bulls appeared to have habituated over the testing period. Additionally, the potential lack of innate temperament variation may have attributed to the little difference seen among the behavioral and performance data. Therefore, temperament should be reassessed within a novel environment with new handlers to differentiate between the bull's true temperament and its ability to habituate.

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Section: Figurecontrasting

confidence: 56%

Relationships among temperament, behavior, and growth during performance testing of bulls1

Lockwood

Kattesh

Krawczel

et al. 2015

Journal of Animal Science

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“…These results suggest that the relationship between ultrasound fat depth and whole side lean meat yield is somewhat different from the relationship between carcass fat depth and whole side lean meat yield. This is not surprising, given the common finding that the relationship between live ultrasound and carcass fat depth is not perfect (Perkins et al 1992;Herring et al 1994b;Charagu et al 2000).…”

Section: Objective 1: Comparison Of Equations Predicting Whole Side Cmentioning

confidence: 95%

“…Until 1984 the Canadian beef grading system based carcass yield grades on 11th/12th rib measurements; this was changed to the 12th/13th rib site to correspond to international standards (Jones et al 1986). The site of ultrasonic fat depth measurements in beef bull testing programs was also changed from the 11th/12th to 12th/13th ribs in the late 1980s (deRose and Wilton 1988;deRose 1990). In the present study, replacing ultrasound fat depth and longissimus muscle area measurements collected at the 12th/13th rib site with 11th/12th rib measurements produced numeric improvements in lean meat yield prediction accuracy and precision (RSD = 23.2 and 22.1 g kg -1 and R 2 = 0.41 and 0.46 for Long12 and Long11, respectively; Table 4).…”

Section: Objective 2: Value Of Alternative Measurements and Ultrasounmentioning

confidence: 99%

“…This is a concern because ultrasound measurements tend to over-predict carcass fat depth on lean animals, and under-predict carcass longissimus muscle area on heavily muscled cattle (Perkins et al 1992;Herring et al 1994b;Charagu et al 2000). Since intact males raised on moderate energy diets tend to be larger, leaner and more heavily muscled than feedlot steers (Jones et al 1984), an equation predicting carcass composition based on steer data may give an inaccurate or biased evaluation of carcass composition of young bulls.…”

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confidence: 99%

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Use of live ultrasound, weight and linear measurements to predict carcass composition of young beef bulls

Bergen¹,

Miller²,

Mandell³

et al. 2005

Can. J. Anim. Sci.

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Use of live ultrasound, weight and linear measurements to predict carcass composition of young beef bulls. Can. J. Anim. Sci. 85: 23-35. Pre-slaughter ultrasound and whole side dissection data from 47 crossbred bulls were used to assess (1) the relative value of six previously published equations based on live animal measurements, (2) the value of alternative pre-slaughter measurements, and (3) the value of alternative ultrasound probes as predictors of whole side lean meat yield. Analysis of absolute bias-corrected residuals indicated that all six previously published equations predicted whole side lean meat yield with similar accuracy (P = 0.62), but analysis of absolute rank residuals indicated that an equation originally based on carcass measurements tended (P = 0.17) to rank bulls less precisely than five ultrasound-based equations. Breed composition, age, liveweight, hip width, heart girth, and round muscle depths did not contribute to new lean meat yield prediction equations (P > 0.10), but height, 12th/13th rib body wall, rump fat, and gluteus medius muscle depths and marbling score did (P < 0.10). However, examination of absolute residuals and absolute rank residuals indicated that accuracy (P = 0.55) and precision (P = 0.64) did not improve significantly compared to equations based only on height, rib fat and longissimus muscle size. Similarly, analysis of absolute residuals and absolute rank residuals indicated that fat and longissimus muscle depth measurements collected with a short probe predicted whole side lean meat yield as accurately and precisely as measurements collected with a long probe. Results indicated that (1) equations based on live measurements may provide more precise predictions of lean meat yield than equations derived from carcass measurements, (2) supplementing ultrasonic rib fat and longissimus muscle measurements with additional ultrasound measurements did not improve the accuracy or precision of lean meat yield prediction, and (3) lean meat yield of yearling bulls can be accurately predicted using fat and longissimus muscle depth measurements collected with a short probe. L'analyse des restes absolus après correction du biais indique que les six équations publiées antérieurement prédisent le rendement en viande maigre avec la même exactitude (P = 0,62), mais l'analyse des restes absolus pour le rang révèle qu'une équation reposant au départ sur les mesures de la carcasse a tendance (P = 0,17) à classer les animaux moins précisément que cinq équations s'articulant sur les relevés aux ultrasons. La race, l'âge, le poids vif, la largeur aux hanches, le périmètre thoracique et l'épaisseur de la ronde n'apportent rien aux nouvelles équations de prévision du rendement en viande maigre (P > 0,10), contrairement à la hauteur, à la paroi corporelle entre la 12 e et la 13 e côte, à la couche de gras de la croupe, à l'épaisseur du gluteus medius et au persillé (P < 0,10). L'examen des restes absolus et des restes absolus pour le rang montrent néanmoins que l'exactitude (P = 0,55) et la pr...

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“…Other factors such as ultrasound manufacturer and model, measurement magnitude (FT thickness and REA size) and technician's skill, may influence measurements' precision, as reported by several authors (Perkins et al, 1992b;Charagu et al, 2000;Greiner, 2001). Positioning of the probe both in live animal and in carcass is also a source of variation.…”

Section: Introductionmentioning

confidence: 99%

Ultrasonography as a predicting tool for carcass traits of young bulls

Suguisawa

Mattos

Oliveira

et al. 2003

Sci. agric. (Piracicaba, Braz.)

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Considerable resources have been allocated to support research in the development of noninvasive and non-destructive techniques for carcass composition and quality evaluation. Ultrasonography is a reliable and relatively low-cost technique that can be used. In the present study, real-time ultrasonography was used to predict ribeye area (REA) and subcutaneous fat thickness (FT) in live animals as compared to carcass measurements. Animals used were 115 yearling bull calves (initial body weight, 329 kg), kept under feedlot conditions, of four genetic groups (30, ½ Angus x Nellore; 30, ½ Canchim x Nellore; 30, ½ Simmental x Nellore, and 25 Nellore), and two finishing frame sizes (small and large). Four ultrasonographic measurements were taken every 28 days until slaughter. Predictive precision of ultrasonographic measurements increased as animals approached slaughter, reaching maximum values at the last measurement (R 2 =0.68 and 0.82 for REA and FT, respectively). FT carcass measurements was influenced by genetic group and live measurements (P < 0.05). Frame size did not influence REA and FT, probably due to small, but distinctive differences among genetic groups.

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Machine effects on accuracy of ultrasonic prediction of backfat and ribeye area in beef bulls, steers and heifers

Cited by 15 publications

References 13 publications

Relationships among temperament, behavior, and growth during performance testing of bulls1

Relationships among temperament, behavior, and growth during performance testing of bulls1

Use of live ultrasound, weight and linear measurements to predict carcass composition of young beef bulls

Ultrasonography as a predicting tool for carcass traits of young bulls

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