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      Effects of supplementation on production of beef cattle grazing tropical pastures in Brazil during the wet and dry seasons: a meta-analysis

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          Abstract

          ABSTRACT A meta-analysis was undertaken to examine the effects of different supplementation strategies on production of beef cattle grazing tropical pastures during the wet and dry seasons in Brazil. The database was built with 132 studies published from 1999 to 2010, which accounted for 6,275 individual animals. The supplements assessed were classified into three groups: energy supplement containing <20% crude protein (CP), protein supplement containing ≥20% CP, and urea mineral supplement. The supplementation levels ranged from 0 to 1.6% body weight (BW), and the effects of type and level of supplementation were examined during both dry and wet seasons. The meta-analysis was performed using mixed models. Cattle grazing tropical pastures during the wet season had higher average daily gain (ADG) than that in the dry season (0.81 vs. 0.56 kg/day). In response to supplementation, cattle receiving >1.0% BW of energetic supplement in the wet season had the greatest gain per hectare (GPH; 8.16 kg/ha per day) and daily stocking rate (DSR; 2045 kg BW/ha/day). In the dry season, protein supplementation at rates >0.5% BW provided higher GPH (on average 2.33 kg/ha per day). Neither level nor type of supplement altered the DSR in the dry season (on average 883 kg/ha per day). Estimated regression showed that the ADG of beef cattle increased by 0.308 kg for each 1% of supplement intake. Increased supplementation intake by beef cattle grazing tropical pastures resulted in greater ADG in the warm season, whereas offering energy supplementation at rates >1.0% BW during the wet season as well as protein supplementation at rates >0.5% BW during the dry season increased gain per area.

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          Nutritional Ecology of the Ruminant

          This monumental text-reference places in clear persepctive the importance of nutritional assessments to the ecology and biology of ruminants and other nonruminant herbivorous mammals. Now extensively revised and significantly expanded, it reflects the changes and growth in ruminant nutrition and related ecology since 1982. Among the subjects Peter J. Van Soest covers are nutritional constraints, mineral nutrition, rumen fermentation, microbial ecology, utilization of fibrous carbohydrates, application of ruminant precepts to fermentive digestion in nonruminants, as well as taxonomy, evolution, nonruminant competitors, gastrointestinal anatomies, feeding behavior, and problems fo animal size. He also discusses methods of evaluation, nutritive value, physical struture and chemical composition of feeds, forages, and broses, the effects of lignification, and ecology of plant self-protection, in addition to metabolism of energy, protein, lipids, control of feed intake, mathematical models of animal function, digestive flow, and net energy. Van Soest has introduced a number of changes in this edition, including new illustrations and tables. He places nutritional studies in historical context to show not only the effectiveness of nutritional approaches but also why nutrition is of fundamental importance to issues of world conservation. He has extended precepts of ruminant nutritional ecology to such distant adaptations as the giant panda and streamlined conceptual issues in a clearer logical progression, with emphasis on mechanistic causal interrelationships. Peter J. Van Soest is Professor of Animal Nutrition in the Department of Animal Science and the Division of Nutritional Sciences at the New York State College of Agriculture and Life Sciences, Cornell University.
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            Invited review: Integrating quantitative findings from multiple studies using mixed model methodology.

            In animal agriculture, the need to understand complex biological, environmental, and management relationships is increasing. In addition, as knowledge increases and profit margins shrink, our ability and desire to predict responses to various management decisions also increases. Therefore, the purpose of this review is to help show how improved mathematical and statistical tools and computer technology can help us gain more accurate information from published studies and improve future research. Researchers, in several recent reviews, have gathered data from multiple published studies and attempted to formulate a quantitative model that best explains the observations. In statistics, this process has been labeled meta-analysis. Generally, there are large differences between studies: e. g., different physiological status of the experimental units, different experimental design, different measurement methods, and laboratory technicians. From a statistical standpoint, studies are blocks and their effects must be considered random because the inference being sought is to future, unknown studies. Meta-analyses in the animal sciences have generally ignored the Study effect. Because data gathered across studies are unbalanced with respect to predictor variables, ignoring the Study effect has as a consequence that the estimation of parameters (slopes and intercept) of regression models can be severely biased. Additionally, variance estimates are biased upward, resulting in large type II errors when testing the effect of independent variables. Historically, the Study effect has been considered a fixed effect not because of a strong argument that such effect is indeed fixed but because of our prior inability to efficiently solve even modest-sized mixed models (those containing both fixed and random effects). Modern statistical software has, however, overcome this limitation. Consequently, meta-analyses should now incorporate the Study effect and its interaction effects as random components of a mixed model. This would result in better prediction equations of biological systems and a more accurate description of their prediction errors.
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              Effects of supplementation on voluntary forage intake, diet digestibility, and animal performance

              A data base was constructed to describe and estimate supplementation effects in nonlactating cattle consuming forage ad libitum. The data base included 66 publications on 126 forages (73 harvested and 53 grazed) and a total of 444 comparisons between a control, unsupplemented treatment and a supplemented treatment. Daily gains were reported for 301 comparisons and voluntary intake for 258. Direct measures of forage digestibility were reported for 202 comparisons, and total diet digestibility for 150. Supplements did not increase gain in all cases. Change in ADG due to supplement was not related closely to intake of supplemental TDN. Lowest increases in ADG were with native forages supplemented with molasses alone or with low intakes of molasses containing high levels of NPN. Greatest increases in gain were with improved forages, supplements with > 60% TDN, and supplemental CP intake > .05% of BW. Supplements decreased voluntary forage intake (VFI) when supplemental TDN intake was > .7% of BW, forage TDN:CP ratio was < 7 (adequate N), or VFI when fed alone was > 1.75% of BW. When supplements increased VFI, forage TDN: CP ratio was > 7 (N deficit), and VFI when fed alone was often low. There was little relationship between change in VFI and sources of supplemental CP and TDN. Supplements caused total diet TDN concentration to deviate from expected values by -10 to +5% of OM. When supplemental TDN intake was > .7% of BW, diet TDN concentration was always less than expected. There was little relationship between deviation from expected total diet TDN and type or composition of forages or supplements. Empirical multiple regression equations were developed to estimate effects of supplements on VFI and total diet TDN concentration. The most acceptable intake equation estimated VFI when fed with supplement (r2 = .84) That equation included VFI when fed alone, supplement intake, CP and TDN concentrations in forage and supplement, and classification codes describing forages and supplemental energy. The most acceptable equation for estimating total diet TDN concentration included only the expected total diet TDN concentration (r2 = .87). These equations may be used in nutritional models to account for associative effects.
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                Author and article information

                Journal
                rbz
                Revista Brasileira de Zootecnia
                R. Bras. Zootec.
                Sociedade Brasileira de Zootecnia (Viçosa, MG, Brazil )
                1516-3598
                1806-9290
                2021
                : 50
                : e20210020
                Affiliations
                [2] São Vicente do Sul RS orgnameInstituto Federal Farroupilha orgdiv1Campus São Vicente do Sul Brasil
                [3] Capão do Leão Rio Grande do Sul orgnameUniversidade Federal de Pelotas orgdiv1Departamento de Zootecnia Brazil
                [4] Capão do Leão Rio Grande do Sul orgnameUniversidade Federal de Pelotas orgdiv1Departamento de Fitotecnia Brazil
                [5] Santa Maria Rio Grande do Sul orgnameUniversidade Federal de Santa Maria orgdiv1Departamento de Zootecnia Brazil
                [1] Santa Maria Rio Grande do Sul orgnameUniversidade Federal de Santa Maria orgdiv1Programa de Pós-Graduação em Zootecnia Brazil
                Article
                S1516-35982021000100510 S1516-3598(21)05000000510
                10.37496/rbz5020210020
                fd495ccf-81d2-4edd-82b9-c2c050e9a299

                This work is licensed under a Creative Commons Attribution 4.0 International License.

                History
                : 04 August 2021
                : 29 January 2021
                Page count
                Figures: 0, Tables: 0, Equations: 0, References: 155, Pages: 0
                Product

                SciELO Brazil

                Categories
                Forage Crops

                dry season,grassland,supplement,wet season,animal performance

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