Determination of the Factors Affecting Live Weight Gain Using Factor Analysis and Stepwise Regression Model

Hatice, Işık; Topçu, Yavuz; Güler, Olcay

doi:10.1080/09712119.2009.9707008

Cited by 5 publications

(2 citation statements)

References 1 publication

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Body weight is closely related to BM, with HG representing the most satisfactory single predictor of BW in cattle [13,[20][21][22]. This method is cheap and accurate; thus, the literature has developed several predictive regression equations based on this parameter, alone or in combination with others [10,23,24].…”

Section: Discussionmentioning

confidence: 99%

Designing Statistical Models for Holstein Rearing Heifers’ Weight Estimation from Birth to 15 Months Old Using Body Measurements

Turini

Conte

Bonelli

et al. 2021

Animals

View full text Add to dashboard Cite

Body measurements could be used to estimate body weight (BW) with no need for a scale. The aim was to estimate heifers weight based on their body dimension characteristics. Twenty-five Holstein heifers represent the study group (SG); another 13 animals were evaluated as a validation group (VG). All the heifers were weighed (BW) and their wither height (WH), shin circumference (SC), heart girth circumference (HG), body length (BL), hip width (HW) and body condition score (BCS) were measured immediately after birth, and then weekly until 2 months and monthly until 15 months old. Equations were built with a stepwise regression in order to estimate the BW at each time using body measures for the SG. A linear regression was applied to evaluate the relationship between the estimated BW and the real BW. Equations found were to be statistically significant (r2 = 0.688 to 0.894; p < 0.0001). Three variables or fewer were needed for BW estimation a total of 11/23 times. Regression analysis indicated that the use of HG was promising in all the equations built for BW estimation. These models were feasible in the field; further studies will evaluate possible modifications to our equations based on different growing rate targets.

show abstract

Section: Discussionmentioning

confidence: 99%

Designing Statistical Models for Holstein Rearing Heifers’ Weight Estimation from Birth to 15 Months Old Using Body Measurements

Turini

Conte

Bonelli

et al. 2021

Animals

View full text Add to dashboard Cite

show abstract

“…Body weight is closely related to body measurements, with HG generally accepted as the most satisfactory single predictor of LW in cattle (Fall et al 1982;Dodo et al 2001;Yan et al 2009;Isik et al 2009;Lesosky et al 2012;Lukuyu et al 2016). The method is cheap, accurate and consistent; thus, many predictive regression equations are based on this parameter alone or in combination with others.…”

Section: Introductionmentioning

confidence: 99%

Using body measurements to estimate live weight of dairy cattle in low-input systems in Senegal

Tebug

Missohou

Sabi

et al. 2016

Journal of Applied Animal Research

View full text Add to dashboard Cite

We investigated the prediction of live weight (LW) of dairy cattle in low-to medium-input systems in Senegal, based on measurements of heart girth (HG) and height at the withers (HW). A total of 459 female dairy cattle, mainly comprising indigenous Zebu and their crosses with Guzerat or Bos Taurus, were weighed (kg), and their HG (cm) and HW (cm) determined. Farmers were asked to provide their own weight estimates for each animal. The single explanatory variable that explained the most variation in LW was HG. The best model to predict LW from HG for the overall data was LW = 4.81 HG − 437.52 with an adjusted R 2 of 0.85 and a root mean square error of 34.25 kg corresponding to 11.10% of the mean LW. This model predicted the LW of 91-100% of cows and 64-100% of heifers within 20% of their true-live weight, in the weight range of about 100-500 kg. In comparison, farmers could only estimate the LW of about a quarter of their animals within 20% of their true LW. This weight prediction equation, when translated into a weigh band, could provide a simple and reliable method for cattle keepers to estimate the weight of studied cattle breed types. ARTICLE HISTORY

show abstract

Prediction of body weight of Curraleiro Pé-Duro cattle based on morphometric measurements

Rocha-Silva,

Britto,

da Silva

et al. 2024

Trop Anim Health Prod

View full text Add to dashboard Cite

Determination of the Factors Affecting Live Weight Gain Using Factor Analysis and Stepwise Regression Model

Cited by 5 publications

References 1 publication

Designing Statistical Models for Holstein Rearing Heifers’ Weight Estimation from Birth to 15 Months Old Using Body Measurements

Designing Statistical Models for Holstein Rearing Heifers’ Weight Estimation from Birth to 15 Months Old Using Body Measurements

Using body measurements to estimate live weight of dairy cattle in low-input systems in Senegal

Prediction of body weight of Curraleiro Pé-Duro cattle based on morphometric measurements

Contact Info

Product

Resources

About