Intensification of tropical grassland can be a strategy to increase beef production, but methods for achieving this should maintain or reduce its environmental impact and should not compromise future food-producing capacity. The objective of this review was to discuss the aspects of grassland management, animal supplementation, the environment, and the socioeconomics of grassland intensification. Reducing environmental impact in the form of, for example, greenhouse gas (GHG) emissions is particularly important in Brazil, which is the second-largest beef producer in the world. Most Brazilian pastures, however, are degraded, representing a considerable opportunity for the mitigation and increase of beef-cattle production, and consequently increasing global protein supply. Moreover, in Brazil, forage production is necessary for seasonal feeding strategies that maintain animal performance during periods of forage scarcity. There are many options to achieve this objective that can be adopted alone or in association. These options include improving grassland management, pasture fertilization, and animal supplementation. Improving grazing management has the potential to mitigate GHG emissions through the reduction of the intensity of CO₂ emissions, as well as the preservation of natural areas by reducing the need for expanding pastureland. Limitations to farmers adopting intensification strategies include cultural aspects and the lack of financial resources and technical assistance.

Meat production by goats has become an important livestock enterprise in several parts of the world. Nonetheless, energy and protein requirements of meat goats have not been defined thoroughly. The objective of this study was to determine the energy and protein requirements for maintenance and growth of 34 ¾ Boer × ¼ Saanen crossbred, intact male kids (20.5 ± 0.24 kg of initial BW). The baseline group was 7 randomly selected kids, averaging 21.2 ± 0.36 kg of BW. An intermediate group consisted of 6 randomly selected kids, fed for ad libitum intake, that were slaughtered when they reached an average BW of 28.2 ± 0.39 kg. The remaining kids (n = 21) were allocated randomly on d 0 to 3 levels of DMI (treatments were ad libitum or restricted to 70 or 40% of the ad libitum intake) within 7 slaughter groups. A slaughter group contained 1 kid from each treatment, and kids were slaughtered when the ad libitum treatment kid reached 35 kg of BW. Individual body components (head plus feet, hide, internal organs plus blood, and carcass) were weighed, ground, mixed, and subsampled for chemical analyses. Initial body composition was determined using equations developed from the composition of the baseline kids. The calculated daily maintenance requirement for NE was 77.3 ± 1.05 kcal/kg^0.75 of empty BW (EBW) or 67.4 ± 1.04 kcal/kg^0.75 of shrunk BW. The daily ME requirement for maintenance (118.1 kcal/kg^0.75 of EBW or 103.0 kcal/kg^0.75 of shrunk BW) was calculated by iteration, assuming that the heat produced was equal to the ME intake at maintenance. The partial efficiency of use of ME for NE below maintenance was 0.65. A value of 2.44 ± 0.4 g of net protein/kg^0.75 of EBW for daily maintenance was determined. Net energy requirements for growth ranged from 2.55 to 3.0 Mcal/kg of EBW gain at 20 and 35 kg of BW, and net protein requirements for growth ranged from 178.8 to 185.2 g/kg of EBW gain. These results suggest that NE and net protein requirements for growing meat goats exceed the requirements previously published for dairy goats. Moreover, results from this study suggest that the N requirement for maintenance for growing goats is greater than the established recommendations. Copyright © 2007. . Copyright 2007 Journal of Animal Science

Grasslands cover approximately 24% of the Earth’s surface and are the main feed source for cattle and other ruminants. Sustainable and efficient grazing systems require regular monitoring of the quantity and nutritive value of pastures. This study demonstrates the potential of estimating pasture leaf forage mass (FM), crude protein (CP) and fiber content of tropical pastures using Sentinel-2 satellite images and machine learning algorithms. Field datasets and satellite images were assessed from an experimental area of Marandu palisade grass (Urochloa brizantha sny. Brachiaria brizantha) pastures, with or without nitrogen fertilization, and managed under continuous stocking during the pasture growing season from 2016 to 2020. Models based on support vector regression (SVR) and random forest (RF) machine-learning algorithms were developed using meteorological data, spectral reflectance, and vegetation indices (VI) as input features. In general, SVR slightly outperformed the RF models. The best predictive models to estimate FM were those with VI combined with meteorological data. For CP and fiber content, the best predictions were achieved using a combination of spectral bands and meteorological data, resulting in R² of 0.66 and 0.57, and RMSPE of 0.03 and 0.04 g/g dry matter. Our results have promising potential to improve precision feeding technologies and decision support tools for efficient grazing management.

Differences among dietary protein levels suggested in the literature point out to the need for better evaluation of protein requirements of growing lambs, raised in drylot on a high-concentrate diet. This study evaluates the influence of crude protein (CP) levels in high concentrate diets on performance and carcass traits of ram lambs, confined for 56 days. Forty eight (48) Santa Ines lambs (initial body weight 18.4 ± 0.4 kg; 86 ± 2 days old) were fed 4 experimental diets containing 14, 16, 18 or 20% CP, in a completely randomized block design. Diets consisted of 80% concentrate and 20% sugarcane bagasse. There were no differences in average daily gain: values of 228, 220, 230 and 231 g d-1 were obtained for diets containing 14, 16, 18 and 20% CP, respectively. There were no differences in dry matter intake and feed conversion: values were 1.03; 1.02; 1.08 and 1.10 kg d-1; 4.19; 4.28; 4.35 and 4.44 kg DM kg-1 gain for diets with 14, 16, 18 and 20% CP, respectively. Plasma urea nitrogen concentrations increased linearly as diets contained more CP. There were no differences in carcass traits.

The objective of this study is to provide approaches to determine mature weight of female and intact and castrated male Saanen goats using body composition data. Our database combined 7 comparative slaughter studies and comprised 244 individual records of body composition of intact male (n = 94), female (n = 71), and castrated male (n = 79) Saanen goats weighing from 4.6 to 51.0 kg BW. Nonlinear regressions were fitted to predict empty body water, fat (EBF), protein (EBP), and ash, expressed as amounts and percentages of the empty BW (EBW) and water-free EBW. Candidate equations were selected on the basis of preliminary graphical examination of the observed body composition of the database, and the best one to describe the data was selected on the basis of convergence achievement with coherent biological interpretation. The selected nonlinear functions were the allometric function (Y = β₀ × EBW^β1) to describe the EBF content and the exponential function (Y = β₀ × e^−β1 × EBW) to describe EBP content in the water-free matter basis. None of the tested nonlinear functions were able to describe ash content, possibly because of its large variation. Mature weight was assumed to be the weight when net protein deposition (i.e., accretion minus degradation) tended to zero. The EBP (percentage of water-free EBW) plotted against the EBW using the exponential function enabled us to estimate the mature weight of intact and castrated males and females as 83.9, 33.6, and 26.4 kg EBW, respectively, indicating that the decrease of protein accretion of intact males approaches zero later than in females and castrated males during growth. Replacing these mature EBW estimates in the allometric function to describe the fat content in the EBW, we estimated that at maturity, castrated males and females had 21.6% and 22.4% EBF, whereas intact males had 36.8% EBF, which may not be biologically acceptable because it is too high. On the other hand, assuming that a goat matures at 22% EBF, one can backward estimate mature EBW of 42.6, 34.9, and 26.0 kg for intact and castrated males and females, respectively. This study indicated that fat percentage in the body may be used to describe maturity, as long as dietary challenges are not imposed on the animals. In addition, our results confirmed that female Saanen goats reach maturity at a lighter weight than males.

Requirements for growth in the different sexes remain poorly quantified in goats. The objective of this study was to develop equations for estimating net protein (NPG) and net energy (NEG) for growth in Saanen goats of different sexes from 5 to 45 kg of body weight (BW). A data set from 7 comparative slaughter studies (238 individual records) of Saanen goats was used. Allometric equations were developed to determine body protein and energy contents in the empty BW (EBW) as dependent variables and EBW as the allometric predictor. Parameter estimates were obtained using a linearized (log-transformation) expression of the allometric equations using the MIXED procedure in SAS software (SAS Institute Inc., Cary, NC). The model included the random effect of the study and the fixed effects of sex (intact male, castrated male, and female; n = 94, 73, and 71, respectively), EBW, and their interactions. Net requirements for growth were estimated as the first partial derivative of the allometric equations with respect to EBW. Additionally, net requirements for growth were evaluated based on the degree of maturity. Monte Carlo techniques were used to estimate the uncertainty of the calculated net requirement values. Sex affected allometric relationships for protein and energy in Saanen goats. The allometric equation for protein content in the EBW of intact and castrated males was log10 protein (g) = 2.221 (±0.0224) + 1.015 (±0.0165) × log10 EBW (kg). For females, the relationship was log10 protein (g) = 2.277 (±0.0288) + 0.958 (±0.0218) × log10 EBW (kg). Therefore, NPG for males was greater than for females. The allometric equation for the energy content in the EBW of intact males was log10 energy (kcal) = 2.988 (±0.0323) + 1.240 (±0.0238) × log10 EBW (kg); of castrated males, log10 energy (kcal) = 2.873 (±0.0377) + 1.359 (±0.0283) × log10 EBW (kg); and of females, log10 energy (kcal) = 2.820 (±0.0377) + 1.442 (±0.0281) × log10 EBW (kg). The NEG of castrated males was greater than that of intact males and lower than that of females. Using degree of maturity for estimating NPG and NEG, we could remove the differences between sexes. These results indicate that NPG and NEG differ among sexes in growing Saanen goats, and this difference should be accounted for by feeding systems. Including the degree of maturity as predictor cancels out those differences across sexes in protein and energy requirements.