Intake, water consumption, ruminal fermentation, and stress response of beef heifers fed after different lengths of delays in the daily feed delivery time

Four rumen-fistulated Holstein heifers (134 +/- 1 kg initial BW) were used in a 4 x 4 Latin square design to determine the effects of delaying daily feed delivery time on intake, ruminal fermentation, behavior, and stress response. Each 3-wk experimental period was preceded by 1 wk in which all animals were fed at 0800 h. Feed bunks were cleaned at 0745 h and feed offered at 0800 h (T0, no delay), 0900 (T1), 1000 (T2), and 1100 (T3) from d1 to 21 with measurements taken during wk 1 and 3. Heifers were able to see each other at all times. Concentrate and barley straw were offered in separate compartments of the feed bunks, once daily and for ad libitum intake. Ruminal pH and saliva cortisol concentrations were measured at 0, 4, 8, and 12 h postfeeding on d 3 and 17 of each experimental period. Fecal glucocorticoid metabolites were measured on d 17. Increasing length of delay in daily feed delivery time resulted in a quadratic response in concentrate DMI (low in T1 and T2; P = 0.002), whereas straw DMI was greatest in T1 and T3 (cubic P = 0.03). Treatments affected the distribution of DMI within the day with a linear decrease observed between 0800 and 1200 h but a linear increase during nighttimes (2000 to 0800 h), whereas T1 and T2 had reduced DMI between 1200 and 1600 h (quadratic P = 0.04). Water consumption (L/d) was not affected but decreased linearly when expressed as liters per kilogram of DMI (P = 0.01). Meal length was greatest and eating rate slowest in T1 and T2 (quadratic P <= 0.001). Size of the first meal after feed delivery was reduced in T1 on d 1 (cubic P = 0.05) and decreased linearly on d 2 (P = 0.01) after change. Concentrate eating and drinking time (shortest in T1) and straw eating time (longest in T1) followed a cubic trend (P = 0.02). Time spent lying down was shortest and ruminating in standing position longest in T1 and T2. Delay of feeding time resulted in greater daily maximum salivary cortisol concentration (quadratic P = 0.04), which was greatest at 0 h in T1 and at 12 h after feeding in T2 (P < 0.05). Daily mean fecal glucocorticoid metabolites were greatest in T1 and T3 (cubic P = 0.04). Ruminal pH showed a treatment effect at wk 1 because of increased values in T1 and T3 (cubic P = 0.01). Delaying feed delivery time was not detrimental for rumen function because a stress response was triggered, which led to reduced concentrate intake, eating rate, and size of first meal, and increased straw intake. Increased salivary cortisol suggests that animal welfare is compromised.

Aflatoxins and cyclopiazonic acid in feed and milk from dairy farms in Sao Paulo, Brazil

The occurrence of aflatoxins (AF) B(1), B(2), G(1), G(2) and cyclopiazonic acid (CPA) in feeds, and AFM(1) and CPA in milk was determined in dairy farms located in the northeastern region of Sao Paulo state, Brazil, between October 2005 and February 2006. AF and CPA determinations were performed by HPLC. AFB(1) was found in 42% of feed at levels or 1.0-26.4 mu g kg(-1) (mean: 7.1 +/- 7.2 mu g kg(-1)). The concentrations of AFM(1) in raw milk varied between 0.010 and 0.645 mu g l(-1) (mean: 0.104 +/- 0.138 mu g l(-1)). Only one sample was above the tolerance limit adopted in Brazil (0.50 mu g l(-1)) for AFM(1) in milk. Regarding CPA in feed, six (12%) samples showed concentrations of 12.5-1533 mu g kg(-1) (mean: 57.6 +/- 48.7 mu g kg(-1)). CPA was detected in only three milk samples (6%) at levels of 6.4, 8.8 and 9.1 mu g l(-1). Concentrations of aflatoxins and CPA in feed and milk were relatively low, although the high frequency of both mycotoxins indicates the necessity to continuously monitor dairy farms to prevent contamination of feed ingredients.

GRASP heuristic with path-relinking for the multi-plant capacitated lot sizing problem

This paper addresses the independent multi-plant, multi-period, and multi-item capacitated lot sizing problem where transfers between the plants are allowed. This is an NP-hard combinatorial optimization problem and few solution methods have been proposed to solve it. We develop a GRASP (Greedy Randomized Adaptive Search Procedure) heuristic as well as a path-relinking intensification procedure to find cost-effective solutions for this problem. In addition, the proposed heuristics is used to solve some instances of the capacitated lot sizing problem with parallel machines. The results of the computational tests show that the proposed heuristics outperform other heuristics previously described in the literature. The results are confirmed by statistical tests. (C) 2009 Elsevier B.V. All rights reserved.

An approach for solving the lot-sizing problem of a market-driven foundry

Foundries can be found all over Brazil and they are very important to its economy. In 2008, a mixed integer-programming model for small market-driven foundries was published, attempting to minimize delivery delays. We undertook a study of that model. Here, we present a new approach based on the decomposition of the problem into two sub-problems: production planning of alloys and production planning of items. Both sub-problems are solved using a Lagrangian heuristic based on transferences. An important aspect of the proposed heuristic is its ability to take into account a secondary practice objective solution: the furnace waste. Computational tests show that the approach proposed here is able to generate good quality solutions that outperform prior results. Journal of the Operational Research Society (2010) 61, 108-114. doi:10.1057/jors.2008.151

A Lagrangian relaxation approach to a coupled lot-sizing and cutting stock problem

Industrial production processes involving both lot-sizing and cutting stock problems are common in many industrial settings. However, they are usually treated in a separate way, which could lead to costly production plans. In this paper, a coupled mathematical model is formulated and a heuristic method based on Lagrangian relaxation is proposed. Computational results prove its effectiveness. (C) 2009 Elsevier B.V. All rights reserved.

Lot sizing and furnace scheduling in small foundries

A lot sizing and scheduling problem prevalent in small market-driven foundries is studied. There are two related decision levels: (I the furnace scheduling of metal alloy production, and (2) moulding machine planning which specifies the type and size of production lots. A mixed integer programming (MIP) formulation of the problem is proposed, but is impractical to solve in reasonable computing time for non-small instances. As a result, a faster relax-and-fix (RF) approach is developed that can also be used on a rolling horizon basis where only immediate-term schedules are implemented. As well as a MIP method to solve the basic RF approach, three variants of a local search method are also developed and tested using instances based on the literature. Finally, foundry-based tests with a real-order book resulted in a very substantial reduction of delivery delays and finished inventory, better use of capacity, and much faster schedule definition compared to the foundry`s own practice. (c) 2006 Elsevier Ltd. All rights reserved.

A coupling cutting stock-lot sizing problem in the paper industry

An important production programming problem arises in paper industries coupling multiple machine scheduling with cutting stocks. Concerning machine scheduling: how can the production of the quantity of large rolls of paper of different types be determined. These rolls are cut to meet demand of items. Scheduling that minimizes setups and production costs may produce rolls which may increase waste in the cutting process. On the other hand, the best number of rolls in the point of view of minimizing waste may lead to high setup costs. In this paper, coupled modeling and heuristic methods are proposed. Computational experiments are presented.

The influence of ARIMA-GARCH parameters in feed forward neural networks prediction

The objective of this article is to find out the influence of the parameters of the ARIMA-GARCH models in the prediction of artificial neural networks (ANN) of the feed forward type, trained with the Levenberg-Marquardt algorithm, through Monte Carlo simulations. The paper presents a study of the relationship between ANN performance and ARIMA-GARCH model parameters, i.e. the fact that depending on the stationarity and other parameters of the time series, the ANN structure should be selected differently. Neural networks have been widely used to predict time series and their capacity for dealing with non-linearities is a normally outstanding advantage. However, the values of the parameters of the models of generalized autoregressive conditional heteroscedasticity have an influence on ANN prediction performance. The combination of the values of the GARCH parameters with the ARIMA autoregressive terms also implies in ANN performance variation. Combining the parameters of the ARIMA-GARCH models and changing the ANN`s topologies, we used the Theil inequality coefficient to measure the prediction of the feed forward ANN.