Navegando por Autor "Bendia, Laila Cecília Ramos"

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Simulation of diets for dairy goats and growing doelings using nonlinear optimization procedures
(Revista Brasileira de Zootecnia, 2016-08-03) Glória, Leonardo Siqueira; Abreu, Matheus Lima Corrêa; Rocha, Norberto Silva; Oliveira, Tadeu Silva de; Gomes, Raphael dos Santos; Rohem Júnior, Nardele Moreno; Bendia, Laila Cecília Ramos; Fernandes, Alberto Magno
The objective of this study was to simulate total dry matter intake and cost of diets optimized by nonlinear programming to meet the nutritional requirements of dairy does and growing doelings. The mathematical model was programmed in a Microsoft Excel(r) spreadsheet. Increasing values of body mass and average daily weight gain for growing doelings and increasing body mass values and milk yield for dairy does were used as inputs for optimizations. Three objective functions were considered: minimization of the dietary cost, dry matter intake maximization, and maximization of the efficiency of use of the ingested crude protein. To solve the proposed problems we used the Excel(r) Solver(r) algorithm. The Excel(r) Solver(r) was able to balance diets containing different objective functions and provided different spaces of feasible solutions. The best solutions are obtained by least-cost formulations; the other two objective functions, namely maximize dry matter intake and maximize crude protein use, do not produce favorable diets in terms of costs.
A two-location trial for selecting corn silage hybrids for the humid tropic: forage and grain yields and in vitro fermentation characteristics
(Brazilian Journal of Animal Science, 2021-04-01) Bendia, Laila Cecília Ramos; Oliveira, Jhone Gleison de; Azevedo, Flavio Henrique Vidal; Nogueira, Marcos Augusto dos Reis; Silva, Leonardo Viana da; Aniceto, Elon Souza; Sant’Anna, Daniel Furtado Dardengo; Crevelari, Jocarla Ambrosim; Pereira, Messias Gonzaga; Vieira, Ricardo Augusto Mendonça
The goal of our study was to evaluate the nutritional potential of dented corn hybrids for silage production. We performed a two-location trial in which 19 dented corn hybrids and five corn controls grew in four randomized blocks within two experimental areas located in the Northern (Campos dos Goytacazes) and Northwestern (Itaocara) Rio de Janeiro State, Brazil. We recorded yields of fresh and dry forage matter and yields of fresh and dry grain matter, as well as chemical composition variables. We interpreted variables by assuming a Normal distribution for yield variables and a Beta distribution for chemical composition and ratios. The SAS GLIMMIX procedure fitted the linear model under those assumptions. Dual-pool models fitted the gas production profiles generated by in vitro anaerobic fermentations. We used the nlme of R software to fit the dual-pool models and the information-theoretic approach to evaluate their quality of fit. We did a cluster analysis (NbClust of R) to group corn hybrids based on fresh and DM yields and kinetic parameters of in vitro gas production. Three clusters of corn hybrids stood out, their basic differences relied on fresh and DM yields. Nonetheless, the least-squares means for gas production characteristics among groups did not present disjoint confidence intervals. Therefore, we can infer that dented corn hybrids rank by forage yield, but not by forage quality, and recommend the most productive ones that consistently outstand in both locations (hybrids UENF-2203, UENF-2192, UENF-2193, and UENF-506-11)