An observational study of growth rate and body weight variance partition for United Kingdom dairy calves from birth to 20 weeks of age

Archer, Simon C.

doi:10.3168/jdsc.2020-0068

Cited by 3 publications

(1 citation statement)

References 20 publications

(33 reference statements)

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“…One limitation of the current study is the relatively high variability in ADG, which was higher than anticipated when performing the sample size calculations. Increased variability in weights at calf rather than farm level during early life has been reported previously (Archer, 2021). However, due to the commercial practices of the farm in the current study, it was not possible to retain calves for longer periods of time to reduce the variability in ADG and thereby increase the likelihood of finding a significant result.…”

Section: Discussionmentioning

confidence: 68%

The effect of environmental temperature on average daily gain in preweaned calves: A randomized controlled trial and Bayesian analysis

Hyde

Green

Hudson

et al. 2022

Journal of Dairy Science

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Neonatal calves are relatively susceptible to heat loss, and previous research suggests that reduced environmental temperatures are associated with reduced average daily gain (ADG) during the preweaning phase. Current methods of mitigating negative effects of colder environmental conditions include the use of calf jackets and the provision of supplementary heat sources; however, previous research is limited. The aim of this study was to evaluate the effect of calf jackets and 1-kW heat lamps on the growth rates of preweaning calves and evaluate associations between environmental temperature and ADG using a Bayesian approach to incorporate both current and previous data. Seventy-nine calves from a single British dairy farm were randomly allocated at birth to 1 of the following 4 groups: no jacket and no heat lamp, heat lamp but no jacket, jacket but no heat lamp, or both heat lamp and jacket between January and April of 2021. Calves were weighed at both birth and at approximately 21 d of age. Temperature was recorded both inside and outside of the calf building, and in pens both with and without heat lamps using data loggers. To explore the effect of treatment group and environmental temperature on ADG, a fixed effects model was fitted over 1,000 bootstrap samples. The effect of environmental temperature on ADG was further explored within a Bayesian framework that used temperature and ADG data for 484 calves from 16 farms available from a previous trial as prior information. Calves housed under a 1-kW heat lamp had an increased ADG of 0.09 kg/d (95% bootstrap confidence interval: −0.02 to 0.20 kg/d), and no effect of jacket or interactions between jacket and heat lamp were found. A significant positive association was identified between the mean environmental temperature of the calf building and ADG, with a 1°C increase in temperature being associated with a 0.03 kg/d increase in ADG (95% bootstrap confidence interval: 0.01 to 0.04 kg/d). Associations between environmental temperature and ADG were further evaluated within a Bayesian framework, and posterior estimates were 0.014 kg/d of ADG per 1°C increase (95% credible interval: 0.009 to 0.021 kg/d). This study demonstrated that a 1-kW heat lamp was effective in increasing ADG in calves, and no significant effect of calf jacket on ADG was found. A significant, positive effect of increased pen temperature on calf ADG was identified in this study and was reinforced when including prior information from previous research within a Bayesian framework.

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Section: Discussionmentioning

confidence: 68%

The effect of environmental temperature on average daily gain in preweaned calves: A randomized controlled trial and Bayesian analysis

Hyde

Green

Hudson

et al. 2022

Journal of Dairy Science

View full text Add to dashboard Cite

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First Lactation Milk Yield Predicted by the Heifer’s Growth Curve Derivatives

Guevara-Escobar,

Cervantes-Jiménez,

Lemus-Ramírez

et al. 2024

Dairy

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Replacement heifers are regularly weighed to assess their health. These data also predict the milk yield in their first lactation (L). The first derivative of the growth curve represents the weight change rate at a given time. It is interesting to use the higher-order derivatives of one biological process, such as growth, to predict the outcome of another process, like lactation. With 78 records of grazing heifers, machine learning was used to predict the L based on variables calculated during the rearing period, from 3 to 21 months of age, every 3 months: body weight (P), first (1D), and second derivative (2D) of an individually modeled Fourier function. Other variables were the age at effective insemination (AI) and the season of the year when the heifer was born (E). The average deviance of the fitted models represented the goodness of fit. The models were trained using 85% of the records, and the fit was evaluated using the remaining data. The deviance was lower for the models including both derivatives in comparison to the models where the derivatives were not included (p = 0.022). The best models predicted the L using data of heifers at six months of age (r2 = 0.62) and the importance of the variables in the model was 35, 28, 21, and 16% for 1D, AI, 2D, and P, respectively. By utilizing this type of model, it would be possible to select and eliminate excess heifers early on, thereby reducing the financial and environmental costs.

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Farklı Lokasyonlarda İki Farklı Yönteme Göre Yetiştirilen Doğu Anadolu Kırmızı Buzağılarda Büyüme Özelliklerinin Fenotipik Değerlendirilmesi

YÜKSEL

2023

Osmaniye Korkut Ata Üniversitesi Fen Bilimleri Enstitüsü Dergisi

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Bu çalışmada farklı lokasyonlarda ex-situ ve in-situ koşullarda yetiştirilen, Doğu Anadolu Kırmızısı ırkı buzağıların büyüme özelliklerinin fenotipik değerlendirilmesi amaçlamıştır. Araştırma materyalini iki farklı lokasyonun her birinde ex-situ ve in-sitü yöntemlerle yetiştirilen buzağılar oluşturmuştur. Ex-situ şartlarda 128 dişi, 133 erkek toplam 261 baş, in-situ şartlarda 34 dişi, 36 erkek toplam 70 baş buzağı değerlendirilmiştir. Her iki lokasyondaki buzağıların doğum ve sütten kesim dönemi canlı ağırlıkları ve vücut ölçüleri farklılıklarının analizi yapılmıştır. Bu işlem için Deskriptif analiz yöntemi kullanılmıştır. Buzağıların morfolojik karakterleri arasındaki korelasyon katsayıları Pearson Bivariete tekniği ile belirlenmiştir. Doğum ve sütten kesim ağırlıklarının tahmini için vücut ölçülerinden istifade edilmiştir. Bu işlem Çoklu Regresyon Analizi kapsamında Stepwise tekniği ile yapılmıştır. Ex-situ koşullardaki buzağılar doğum ile sütten kesim dönemi vücut ölçüleri değişim farklılıkları bakımından in-situ koşullara göre daha büyük varyasyon göstermiştir. Doğum ağırlığı ile aynı dönem vücut ölçüleri arasında önemli (p < 0,01) korelasyonlar tespit edilmiştir. Canlı ağırlık tespiti için geliştirilen Çoklu Regresyon Denklemi R2 değerleri doğum ağırlığı ve sütten kesim ağırlığı için sırasıyla 0,66; 0,77 dir.

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An observational study of growth rate and body weight variance partition for United Kingdom dairy calves from birth to 20 weeks of age

Cited by 3 publications

References 20 publications

The effect of environmental temperature on average daily gain in preweaned calves: A randomized controlled trial and Bayesian analysis

The effect of environmental temperature on average daily gain in preweaned calves: A randomized controlled trial and Bayesian analysis

First Lactation Milk Yield Predicted by the Heifer’s Growth Curve Derivatives

Farklı Lokasyonlarda İki Farklı Yönteme Göre Yetiştirilen Doğu Anadolu Kırmızı Buzağılarda Büyüme Özelliklerinin Fenotipik Değerlendirilmesi

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