Ammonia levels on in vitro degradation of fibrous carbohydrates from buffel grass

This study was carried out to examine the degradation dynamics of neutral detergent fibre (NDF) and the profile of volatile fatty acids that originate from the fermentation of buffel grass (Cenchrus ciliaris, L.) with various levels of ammonia in the growth medium. The treatments consisted of six levels of ammonia in the growth medium (0, 5, 10, 15, 20 and 30 mg/dL), which were obtained by adding urea. These in vitro incubation times were evaluated in three replicates per time for 0, 3, 6, 9, 12, 24, 36, 48, 72 and 96 hours. Rumen concentrations of acetate and propionate responded quadratically to the ammonia levels. The treatment with 15 mg/dL of ammonia nitrogen in the rumen fluid provided mean acetate and propionate contents of 57.6 mM and 23.1 mM, respectively. Urea addition elevated the degradation rate of potentially degradable fraction of NDF (pdNDF) from 2.5% to 20.1% in comparison with the treatment without urea and to a reduction in estimated discrete lag time from 0.34 to 2.31 hours. Urea supplementation increased the specific microorganism growth rate from 2.6% to 20.1%. At the end of the incubation trial, NDF degradation showed a quadratic response, with maximum value obtained at 17.76 mg/dL of ammonia in the rumen fluid. Urea improves the degradation dynamics of NDF from deferred buffel grass and increases the concentrations of acetate and propionate.Keywords: Cenchrus ciliaris, degradation kinetics, non-protein nitrogen, ure

Simulating maize yield in sub-tropical conditions of southern Brazil using Glam model

The objective of this work was to evaluate the feasibility of simulating maize yield in a sub‑tropical region of southern Brazil using the general large area model (Glam). A 16‑year time series of daily weather data were used. The model was adjusted and tested as an alternative for simulating maize yield at small and large spatial scales. Simulated and observed grain yields were highly correlated (r above 0.8; p<0.01) at large scales (greater than 100,000 km2), with variable and mostly lower correlations (r from 0.65 to 0.87; p<0.1) at small spatial scales (lower than 10,000 km2). Large area models can contribute to monitoring or forecasting regional patterns of variability in maize production in the region, providing a basis for agricultural decision making, and Glam‑Maize is one of the alternatives

Particle swarm optimization for the Steiner tree in graph and delay-constrained multicast routing problems

This paper presents the first investigation on applying a particle swarm optimization (PSO) algorithm to both the Steiner tree problem and the delay constrained multicast routing problem. Steiner tree problems, being the underlining models of many applications, have received significant research attention within the meta-heuristics community. The literature on the application of meta-heuristics to multicast routing problems is less extensive but includes several promising approaches. Many interesting research issues still remain to be investigated, for example, the inclusion of different constraints, such as delay bounds, when finding multicast trees with minimum cost. In this paper, we develop a novel PSO algorithm based on the jumping PSO (JPSO) algorithm recently developed by Moreno-Perez et al. (Proc. of the 7th Metaheuristics International Conference, 2007), and also propose two novel local search heuristics within our JPSO framework. A path replacement operator has been used in particle moves to improve the positions of the particle with regard to the structure of the tree. We test the performance of our JPSO algorithm, and the effect of the integrated local search heuristics by an extensive set of experiments on multicast routing benchmark problems and Steiner tree problems from the OR library. The experimental results show the superior performance of the proposed JPSO algorithm over a number of other state-of-the-art approaches