Abstract
This study aimed to evaluate the effect of parity order on milk yield (MY) and composition over time of grazing beef cows and to evaluate non-linear models to describe the lactation curve. Thirty-six pregnant Nellore cows (12 nulliparous, 2 years; 12 primiparous, 3 years; and 12 multiparous, 4–6 years) were included in the study. With calving day assigned as day 0, milking was performed using a milking machine to estimate MY on days 7, 14, 21, 42, 63, 91, 119, 154, and 203. Dummy variable analyses were applied to estimate its effects on MY, composition (kg and percentage), afternoon/morning, and afternoon/total proportions. Since multiparous cows had higher MY than nulliparous and primiparous cows, two different groups were used for lactation curve analysis: Mult (multiparous) and Null/Prim (nulliparous and primiparous). The MY estimated by the last edition of BR-Corte (Nutrient Requirements of Zebu and Crossbred Cattle) equation was compared with the observed values from this study. Five nonlinear models proposed by Wood (WD), Jenkins & Ferrell (JF), Wilmink (WK), Henriques (HR) and Cobby & Le Du (CL) were evaluated. Models were validated using an independent dataset of multiparous and primiparous cows. The estimates for parameters a, b, and c of the CL equation were compared between groups, and the BR-Corte equation used the model identity methodology. Nulliparous and primiparous cows displayed similar MY (P > 0.05); however, multiparous cows had an average MY that is 0.70 kg/day greater than that of nulliparous and primiparous cows (P < 0.05). Milk protein and total solids were higher for multiparous cows (P < 0.05). Effect of days in milking was found for milk fat, protein, and total solids (P < 0.05). The yield of all milk components was higher for multiparous cows than for nulliparous and primiparous cows. The afternoon/morning and afternoon/total proportions of milk production were not affected by parities and days in milking (P > 0.05), with an average of 0.76 and 0.42, respectively. The BR-Corte equation did not correctly estimate the MY (P < 0.05). The equations of WD, WK, and CL had the best estimate of MY for both Mult and Null/Prim datasets. The equations had a very similar Akaike's information criterion with correction and mean square error of prediction.
Highlights
The milking ability of beef cows is one of the main factors influencing the weaning weights of calves [1]; many methods have been used to attempt to estimate beef cows’ milk production and its influence on calf preweaning growth [2,3,4]
In general, data collection and handling procedures of grazing animals, pregnant Nellore cows, are laborious since animals have a poor temperament and require extreme care. This challenge would explain the low number of studies and the low number of data points to fit an equation of milk production for grazing beef cows
Milk yield was different between parities (P < 0.05)
Summary
The milking ability of beef cows is one of the main factors influencing the weaning weights of calves [1]; many methods have been used to attempt to estimate beef cows’ milk production and its influence on calf preweaning growth [2,3,4]. Milk yield can be estimated by different methods including determining differences in calf weights before and after suckling [2, 7, 8] and hand milking [3, 4] or machine milking procedures [9,10,11] Those methods are possible with small numbers of animals but are not adaptable to larger herds. In general, data collection and handling procedures of grazing animals, pregnant Nellore cows, are laborious since animals have a poor temperament and require extreme care This challenge would explain the low number of studies and the low number of data points to fit an equation of milk production for grazing beef cows
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