Non-linear modelling to describe lactation curve in Gir crossbred cows

Bangar, Yogesh C.; Verma, Med Ram

doi:10.1186/s40781-017-0128-6

Cited by 17 publications

(16 citation statements)

References 15 publications

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“…However, WD nlin indicated the best fit for 1/2H, 3/4H, 7/8H and H groups. Torshizi et al (2011) and Bangar and Verma (2017), using similar criteria, reported the superiority of the non-linear Wood's model compared to Wood's linear model when fitting test day milk yield records of Holstein and Gyr breeds, respectively. In fact, Wood's model in the non-linear form has been considered one of the best and most popular functions to describe the lactation curve in dairy cattle (Macciotta et al 2011).…”

Section: Discussionmentioning

confidence: 96%

“…The individual performance of animals with different genetic compositions will depend on the prediction of the shape of the lactation curve (Pereira et al 2016). The pattern of the lactation curve is very important in the study of dairy cattle (Bangar and Verma 2017). In general, the common pattern of lactation curves is that milk yield increases in the early stage of lactation reaches a peak yield and then decreases slowly until the end of lactation (Chang et al 2001).…”

Section: Introductionmentioning

confidence: 99%

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Heterosis in the components of lactation curves of Girolando cows

Daltro

Padilha

Gama

et al. 2018

Italian Journal of Animal Science

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The objective of this study was to evaluate the effect of heterosis on the lactation curve components of Girolando cattle obtained by fitting different mathematical models. Data consisted of 258,891 test day milk yield records of the first lactation from 37,965 cows of Minas Gerais State (Brazil) between 1998 and 2014. Those cows were from the Holstein breed (H), Gyr breed (G) and six genetic cross-breedings of Holstein Â Gyr, (1/4H, 3/4G (1/4H); 3/8H, 5/8G (3/8H); 1/2H, 1/ 2G (1/2H), 5/8H, 3/8G (5/8H); 3/4H, 1/4G (3/4H); 7/8H, 1/8G (7/8H)), which is officially named as Girolando breed in Brazil. The Wood's linear model (WD lin ), Wood's non-linear model (WD nlin ), Wilmink's model (WL) and Ali and Schaeffer's model (ASH) were used for estimating the peak milk yield (PY), time to peak yield (PT), 305-day milk yield (TMY) and four different persistency measures (P, P 2:1 , P 3:1 and P 3:2 ). Regardless of the fitted model, the highest estimates of PY and TMY were for the H group. The heterosis effect was significant (p < .001) for TMY and all components of the lactation curve, except for P 2:1 . Girolando cattle presented a heterosis effect of 12.30% and 13.03% for PY and TMY, respectively. The magnitude of heterosis effect was larger for PT (24.18%), whereas the different persistency measures presented the smallest magnitude of heterosis values. The producers may use the different genetic groups to benefit from the heterosis mainly for the time to peak, peak yield and 305-day milk yield. HIGHLIGHTSGirolando cows in production systems in Brazil has shown positive results. The greater productive efficiency may be because of heterosis on the production. Thus effect of heterosis on lactation curve can contribute to the improvement of the production system. ARTICLE HISTORY

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Section: Discussionmentioning

confidence: 96%

Section: Introductionmentioning

confidence: 99%

Heterosis in the components of lactation curves of Girolando cows

Daltro

Padilha

Gama

et al. 2018

Italian Journal of Animal Science

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“…Genomic prediction of lactation curves represents the genetic behavior of the milk production of the animals in the herd throughout lactation. According to Bangar and Verma (2017), the lactation curve cannot be fitted through a linear model, since its trend is not linear with time. Therefore, several mathematical models have been applied to explain the flow of milk production throughout lactation in dairy cows (Macciotta et al, 2011;Bangar and Verma, 2017;Piccardi et al, 2017).…”

Section: Discussionmentioning

confidence: 99%

“…Studies addressing the construction of lactation curves for dairy cattle usually aim to identify the lactation behavior of the herds (Bangar and Verma, 2017) and/or to evaluate the genetic parameters for the lactation traits under study (Macciotta et al, 2015). These approaches are important for characterizing the milk productivity of the herd and for assisting the choice of the equation that best describes its behavior.…”

Section: Introductionmentioning

confidence: 99%

Research Article Genomic prediction of lactation curves of Girolando cattle based on nonlinear mixed models

Teixeira¹,

Nascimento²,

Cecon³

et al. 2021

Genet. Mol. Res.

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©FUNPEC-RP www.funpecrp.com.br Genetics and Molecular Research 20 (1): gmr18691 F.R.F. Teixeira et al. 2using the Bayesian LASSO method. Then, based on the genomic estimated breeding values (GEBVs) obtained, genomic predictions of lactation curves were constructed, and the genetic parameters were calculated. Wood's equation showed the best fit among the evaluated models. Heritabilities ranged from 0.09 to 0.29 for the seven lactation variables (initial production, rates of increase and decline, lactation peak, time to peak yield, persistence and total production). The correlations among GEBVs ranged from -0.85 to 0.98. The concordances between the best animals selected according to the selected traits were greater when the correlations between GEBVs for these traits were also high. Consequently, the methodology allowed us to identify the best nonlinear model and to construct the genetic lactation curves of a Girolando cattle population, as well as to assess the differences between animals and the association between lactation variables.

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“…Because of the factors mentioned previously, we believe that those variations occurred when cows presented the peak milk yield on the day of parturition or nearly after parturition. These types of lactation profiles occurred for groups BPO 41 and BPO 43 , which might be associated with the poor dairy temperament of Zebu breeds and its crossbreeds with dairy breeds (Bangar and Verma, 2017). Sometimes, even cows that exhibited a typical convex-shaped lactation profile in a previous lactation fail to present a peak milk yield in a further lactation, because of environmental factors such as metabolic disorders, mastitis, other diseases, and nutritional or other management errors (Wood, 1968(Wood, , 1970(Wood, , 1972(Wood, , 1976(Wood, , 1980Macciotta et al, 2005;Hossein-Zadeh, 2016;Ahmed et al, 2019).…”

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confidence: 99%

The geometry of the lactation curve based on Wood's equation: a two-step prediction

Oliveira

Sant’Anna

Lourenço

et al. 2020

Revista Brasileira De Zootecnia

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-Lactation records from cows of the southwestern Paraná state, Brazil, form the dataset of this study. We applied the information-theoretic approach to evaluate the ability of the nonlinear Wood, Brody, Dijkstra, and Gamma functions to fit to these data by employing a two-step technique based on nonlinear mixed-effects models and generalized linear mixed-effects models. Wood's equation was fitted with the combination of a first-order autoregressive correlation structure and a variance function to account for heteroscedasticity. This version was the best choice to mimic lactation records. Some geometric attributes of Wood's model were deduced, mainly the ascending specific rate from parturition to peak milk yield and the descending specific rate as a measure of the lactation persistence of the milk yield at peak production. Breed and parity order of the cows were assumed as fixed effects to obtain a reliable model fitting process. Regardless of breed, first-order parity cows had greater persistency than their older counterparts, and the greater the ascending rate of milk yield from the parturition to the peak, the sharper the decrease in milk yield post-peak; therefore, the rates (absolute values) of ascending and descending phases correlated positively. Nonetheless, the actual estimated values of the descending phase rates are negative. Wood's equation was flexible enough to mimic either concave-and convex-shaped lactation profiles. The correlations between both peak milk yield and random estimates for β with total milk yield per lactation were positive. However, peak milk yield might not be the only variable used for ranking cows; the total milk yield integrates all information of the lactation profile through the estimated parameters of Wood's equation.

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Non-linear modelling to describe lactation curve in Gir crossbred cows

Cited by 17 publications

References 15 publications

Heterosis in the components of lactation curves of Girolando cows

Heterosis in the components of lactation curves of Girolando cows

Research Article Genomic prediction of lactation curves of Girolando cattle based on nonlinear mixed models

The geometry of the lactation curve based on Wood's equation: a two-step prediction

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