Evaluation of nutrition models to estimate performance of young dairy calves: a meta-analytical study under tropical conditions.

Mathematical models are important tools to estimate nutritional requirements and animal growth. Very few calf models generated from other countries with different feeding programs, environment and production systems have been evaluated. The objective of this paper is to evaluate two calf models: (i) the National Research Council (NRC) in 2001 and (ii) the updates published by Van Amburgh and Drackley in 2005 and inputted into Agricultural Modeling and Training Systems (AMTS, version 3.5.8). Data from 16 previous studies involving 51 diets for dairy calves under tropical conditions (n=485 calves, initial BW 37.5±4.35 kg and weaning weight of 62.0±10.16 kg) were used. The calves were fed with whole milk, milk replacer or fermented colostrum, plus starter (20.9±1.78% of CP). The accuracy of the average daily gain (ADG) prediction was evaluated by mean bias, mean square prediction error (MSPE), concordance correlation coefficient, bias correction factor (Cb), and regression between the observed and predicted values. The ADG observed from birth to weaning was 0.452±0.121 kg/day. Calves fed with whole milk had greater ADG compared with calves fed milk replacer (0.477 v. 0.379 kg/day) during the milk-feeding period. When all data were pooled (n=51 diets), predictions had a mean bias of -0.019 and 0.068 kg/day for energy-allowable gain using NRC and AMTS models, respectively. The regression equation between observed and predicted values obtained from energy of diets showed an intercept different from zero (P0.05) indicate that the AMTS growth model resulted in accurate predictions for calves fed with milk replacer. However, within these latter two approaches, the goodness of fit (R 2) was low, representing low precision. The weight gain estimated by the energy available from the diet was overestimated by 19 g/day when calculated by the NRC and underestimated by 68 g/day when calculated by AMTS. The reasons for this discrepancy need to be understood, for only then new models could be developed and parameterized to estimate animal performance in tropical conditions more accurately and precisely.

Brazilian beef cattle feedlot manure management: a country survey.

No information regarding the management of manure from beef cattle feedlots is available for Brazil. To fill this knowledge gap, a survey of 73 feedlots was conducted in 7 Brazilian states. In this survey, questions were asked regarding animal characteristics, their diets, and manure handling management from generation to disposal. These feedlots finished 831,450 animals in 2010. The predominant breed fed was Nellore, with average feeding periods of 60 to 135 d. Corn was the primary source of grain used in the feedlot diets (76% of surveyed animals) with concentrate inclusion levels ranging from 81 to 90% (38% of surveyed animals). The most representative manure management practice was the removal of manure from pens only at the end of the feeding period. Subsequently, the manure was stored in mounds before being applied to crop and pasture lands. Runoff, mainly from rainwater, was collected in retention ponds and used for agriculture. However, the quantity of runoff was not known. Manure was composted for only 20% of the animals in the survey and was treated in anaerobic digesters for only 1% of the animals. Manure from 59% of the cattle surveyed was used as fertilizer, providing a cost savings over the use of synthetic fertilizers. Overall, chemical analysis of the manure before application to fields was conducted for the manure of 56% of the surveyed animals, but the exact quantity applied (per hectare) was unknown for 48%. Feedlots representing 48% of the surveyed animals noted similar or greater crop and pasture yields when using manure, rather than synthetic fertilizers. In addition, 32% mentioned an increase in soil organic matter. Feedlots representing 88% of the surveyed cattle indicated that information concerning management practices that improve manure use efficiency is lacking. Feedlots representing 93% of the animals in the survey reported having basic information regarding the generation of energy and fertilizer with anaerobic digesters. However, only 1 feedlot implemented this technology. In conclusion, the manure management evaluated in this study represents an important indirect economic benefit that was represented by decreased use of synthetic fertilizers in crops. However, little attention was given to the specific treatments and environmental impacts of handling manure. This survey provides information that should assist in the development of better research practices and broader application of future models.

A methodological approach to estimate the lactation curve and net energy and protein requirements of beef cows using nonlinear mixed-effects modeling.

The objective of this study was to evaluate methods to predict the secretion of milk and net energy and protein requirements of beef cows (Bos indicus and B. taurus) after approximately 1 mo postpartum using nonlinear mixed-effect modeling (NLME). Twenty Caracu × Nellore (CN) and 10 Nellore (NL) cows were inseminated to Red Angus bulls, and 10 Angus × Nellore (AN) were bred to Canchim bulls. Cows were evaluated from just after calving (25 ± 11 d) to weaning (220 d). Milk yield was estimated by weighing calves before and after suckling (WSW) and by machine milking (MM) methods at 25, 52, 80, 109, 136, 164, 193, and 220 ± 11 d of lactation. Brody and simple linear equations were consecutively fitted to the data and compared using information criteria. For the Brody equation, a NLME model was used to estimate all lactation profiles incorporating different sources of variation (calf sex and breed of cow, cow as a nested random effect, and within-cow auto-correlation). The CV for the MM method (29%) was less than WSW (45%). Consequently, the WSW method was responsible for reducing the variance about 1.5 times among individuals, which minimized the ability to detect differences among cows. As a result, only milk yield MM data were used in the NLME models. The Brody equation provided the best fit to this dataset, and inclusion of a continuous autoregressive process improved fit (P < 0.01). Milk, energy and protein yield at the beginning of lactation were affected by cow genotype and calf sex (P < 0.001). The exponential decay of the lactation curves was affected only by genotype (P < 0.001). Angus × Nellore cows produced 15 and 48% more milk than CN and NL during the trial, respectively (P < 0.05). Caracu × Nellore cows produced 29% more milk than NL (P < 0.05). The net energy and net protein requirements for milk yield followed a similar ranking. Male calves stimulated their dams to produce 11.7, 11.4, and 11.9% more milk, energy and protein, respectively (P < 0.05). The MM method is better than the WSW technique to detect genetic or environmental differences in milk yield among beef cows. The data obtained by the MM method and analyzed by NLME models allows the inclusion of fixed effects, random effects and an auto-regressive process in lactation equations to describe lactation curves and net energy and protein requirements. The NLME is a powerful tool to describe differences in the secretion of milk due to heterosis and cell mammary external stimulus in beef cows.