Liveweight loss associated with handling and weighing of grazing sheep

Wishart, HM; Morgan-Davies, C; Stott, Alistair W.; Wilson, Ron; Waterhouse, A.

doi:10.1016/j.smallrumres.2017.06.013

Cited by 18 publications

(21 citation statements)

References 18 publications

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“…In order to reduce this measurement error, it would be imperative that liveweight losses due to delayed weighing be accounted for with respect to time of delay (the period from when the animal last fed to weight recording) in using prediction equations. Time-dependent, liveweight adjusting equations for ewes have been developed but are not regularly used [ 41 ].…”

Section: Discussionmentioning

confidence: 99%

Predicting Ewe Body Condition Score Using Lifetime Liveweight and Liveweight Change, and Previous Body Condition Score Record

Semakula

Corner-Thomas

Morris

et al. 2020

Animals

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The body condition score (BCS) in sheep (Ovis aries) is a widely used subjective measure of body condition. Body condition score and liveweight have been reported to be statistically and often linearly related in ewes. Therefore, it was hypothesized that current BCS could be accurately and indirectly predicted using a ewe’s lifetime liveweight, liveweight change, and previous BCS record. Ewes born between 2011 and 2012 (n = 11,798) were followed from 8 months to approximately 67 months of age in New Zealand. Individual ewe data was collected on liveweight and body condition scores at each stage of the annual cycle (pre-breeding, pregnancy diagnosis, pre-lambing, and weaning). Linear regression models were fitted to predict BCS at a given ewe age and stage of the annual cycle using a ewe’s lifetime liveweight records (liveweight alone models). Further, linear models were then fitted using previous BCS and changes in liveweight, in addition to the lifetime liveweight records (combined models). Using the combined models improved (p < 0.01) the R2 value by 39.8% (from 0.32 to 0.45) and lowered the average prediction error by 10% to 12% (from 0.29 to 0.26 body condition scores). However, a significant portion of the variability in BCS remained unaccounted for (39% to 89%) even in the combined models. The procedures found in this study, therefore, may overestimate or underestimate measures by 0.23 to 0.32 BCS, which could substantially change the status of the ewe, leading to incorrect management decisions. However, the findings do still suggest that there is potential for predicting ewe BCS from liveweight using linear regression if the key variables affecting the relationship between BCS and liveweight are accounted for.

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Section: Discussionmentioning

confidence: 99%

Predicting Ewe Body Condition Score Using Lifetime Liveweight and Liveweight Change, and Previous Body Condition Score Record

Semakula

Corner-Thomas

Morris

et al. 2020

Animals

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“…Liveweight (LW) is a widely approved indicator of the energy standing of sheep at a given time, while changes in liveweight indicates whether the animal possesses a positive energy balance (liveweight gain) or a negative energy balance (liveweight loss) [1][2][3]. Liveweight quantifies total body mass and includes organ, muscle, bone, fat, body fluids and gut-fill [2]. Liveweight is rather stable over shorter time periods (i.e., a few days), but changes over a long period of time in response to physiological and environmental conditions [2,4].…”

Section: Introductionmentioning

confidence: 99%

The Effect of Herbage Availability, Pregnancy Stage and Rank on the Rate of Liveweight Loss during Fasting in Ewes

et al. 2021

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Sheep liveweight and liveweight change are vital tools both for commercial and research farm management. However, they can be unreliable when collection procedures are not standardized or when there are varying time delays between sheep removal from grazing and weighing. This study had two stages with different objectives: (1) A liveweight loss study to determine the effect of herbage availability (Low and High) on the rate of liveweight loss of ewes at different pregnancy stages (approximately 100 days of pregnancy: P100 and 130 days: P130) and ranks (single and twin); (2) A follow-up liveweight loss study to develop and validate correction equations for delayed liveweights by applying them to data sets collected under commercial conditions. Results from each stage showed that the rate of liveweight loss varied by herbage availability and stage of pregnancy (p < 0.05) but not pregnancy-rank (p > 0.05). Further, the rate of liveweight loss differed by farm (p < 0.05). Applying liveweight correction equations increased the accuracy of without delay liveweight estimates in P100 ewes by 56% and 45% for single-bearing and twin-bearing ewes, respectively, when offered the Low-level diet. In ewes offered the High-level diet, accuracies of without delay liveweight estimates were increased by 53% and 67% for single-bearing and twin-bearing ewes, respectively. Among P130 ewes, accuracy was increased by 43% and 37% for single-bearing and twin-bearing ewes, respectively, when offered the Low herbage level and by 60% and 50% for single-bearing and twin-bearing ewes, respectively, when offered the High herbage level. In conclusion, a short-term delay of up to 8 hours prior to weighing, which is commonly associated with practical handling operations, significantly reduced the liveweight recorded for individual sheep. Using delayed liveweights on commercial farms and in research can have consequences for management practices and research results; thus, liveweight data should be collected without delay. However, when this is not feasible, delayed ewe liveweights should be corrected and, in the absence of locally devised correction equations, the ones generated in the current study could be applied on farms with similar management conditions and herbage type.

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“…Body weight (BW) is one of the most accurate measurements to determine livestock growth (1) . The further understanding of body growth allows for novel diet optimization approaches with consequences on the improvement of prediction of sales prices (2) , as well as management strategies that can improve therapeutic treatments for livestock diseases (2,3) .…”

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confidence: 99%

“…Despite of BW being an important economic trait that can assist feeding and management decision supports; small producers can rarely afford expensive scales necessary to perform such measurement (3,4,5) . Although, several techniques to measure or estimate the BW of livestock have been reported, the use if weighing scales, are still the most accurate method, but less preferred by small producers because it's cumbersomeness, time-consuming efforts, associated cost for implementation, and stress to animals (1,2) .…”

mentioning

confidence: 99%

“…Recently, it has been reported that the sheep lose a significant amount of BW over a short-term delay prior to weighing as a result of handling operations leading to losses around to 1.8 to 2.9 kg or 3.5 to 5.6 % BW (1) . Therefore, it is important to develop alternative practical methods that are of low cost and ease allowing smallholders to monitor the body growth of production animals (4,6) .…”

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confidence: 99%

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Development and evaluation of equations to predict body weight of Pelibuey ewes using heart girth

Chay-Canul

García‐Herrera

Salazar-Cuytún

et al. 2019

Rev. Mex. Cienc. Pecu.

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The main objective was to develop equations to predict body weight (BW) using heart girth (HG) in Pelibuey ewes. A second objective was to evaluate this model for precision using an independent dataset. For model develop a data set composed by 366, 2-3-yr-old, non-pregnant and non-lactating ewes; with a mean BW of 45.7 ± 9.16 kg and HG of 87.55 ± 7.93 cm was used. A linear equation was fitted: BW=-47.97 (±2.01) + 1.07 (±0.02)×HG (r 2 = 0.86, Root mean square error (RMSE)= 3.46, y n= 366). A second data set composed by 67 animals, with similar characteristics (BW of 38.25 ± 8.62 kg and HG of 80.37 ± 7.03 cm) was used to evaluate the developed equations. For the evaluation, the relationship between observed and predicted values of BW by linear regression, the mean squared error of prediction (MSEP) and root MSEP (RMSEP), and concordance correlation coefficient analysis were used. The proposed equation was highly precise (R 2 =0.913) and accurate (Cb=0.996) with a reproducibility index of 0.95. The MEF has indicated a higher efficiency of prediction with higher proportion of the total variance of the observed values been explained by the predicted data (0.91). The partition of the MSEP has indicated a very small mean bias (0.082). The systematic bias has shown that only 1.93 % of the error of prediction was associated with the slope and most of the error was explained by the random component indicating small biases with the predictions. The proposed equation accurately and precisely estimated the BW of non-pregnant and non-lactating Pelibuey ewe using HG and therefore is recommended to be used.

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Liveweight loss associated with handling and weighing of grazing sheep

Cited by 18 publications

References 18 publications

Predicting Ewe Body Condition Score Using Lifetime Liveweight and Liveweight Change, and Previous Body Condition Score Record

Predicting Ewe Body Condition Score Using Lifetime Liveweight and Liveweight Change, and Previous Body Condition Score Record

The Effect of Herbage Availability, Pregnancy Stage and Rank on the Rate of Liveweight Loss during Fasting in Ewes

Development and evaluation of equations to predict body weight of Pelibuey ewes using heart girth

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