Update and evaluation of the egg production model in laying hens.

The egg production model (EPM) described here is a mechanistic and stochastic model that simulates the amino acid and energy requirements of laying hens. It takes into account their potential rate of laying, and egg weight over time, and the composition of the feed provided. The model predicts feed intake based on the assumption that hens will consume enough feed to reach their genetic potential. The environment is assumed to be non-limiting, although feed intake may be constrained by bulk capacity when bulky feeds are offered. The simulation model integrates a least-cost feed formulator, which enables the prediction of a feeding program that maximizes economic returns. A series of simulations were conducted to demonstrate the model behavior, external evaluation, and the economic optimization routine. The model behavior showed that as the energy content in the feed decreased, the simulated feed intake increased to compensate. Consequently, feeds with lower energy concentrations led to an overconsumption of nutrients, resulting in increased egg component weights (yolk and albumen). However, when the balanced protein was reduced while maintaining a constant energy-to-protein ratio, there was no change in egg components, consistent with published literature. The external evaluation indicated that feed intake, egg production, and egg weight were estimated with low error, and there was a similar trend observed between the estimated and observed data. This demonstrates the reliability of the model. Additionally, the paper provides a demonstration of how to use and interpret the results from the egg production model, including the economic optimization routine. The study found that a feed containing 7.8 g/kg of digestible lysine maximized economic returns. This optimization tool can be valuable in making nutritional decisions to optimize economic returns in an egg production system.

Review: When worlds collide - poultry modeling in the 'Big Data' era.

Within poultry production systems, models have provided vital decision support, opportunity analysis, and performance optimization capabilities to nutritionists and producers for decades. In recent years, due to the advancement of digital and sensor technologies, 'Big Data' streams have emerged, optimally positioned to be analyzed by machine-learning (ML) modeling approaches, with strengths in forecasting and prediction. This review explores the evolution of empirical and mechanistic models in poultry production systems, and how these models may interact with new digital tools and technologies. This review will also examine the emergence of ML and Big Data in the poultry production sector, and the emergence of precision feeding and automation of poultry production systems. There are several promising directions for the field, including: (1) application of Big Data analytics (e.g., sensor-based technologies, precision feeding systems) and ML methodologies (e.g., unsupervised and supervised learning algorithms) to feed more precisely to production targets given a 'known' individual animal, and (2) combination and hybridization of data-driven and mechanistic modeling approaches to bridge decision support with improved forecasting capabilities.

Maintenance valine, isoleucine, and tryptophan requirements for poultry.

Poultry maintenance requirements for valine, isoleucine, and tryptophan were measured by nitrogen balance using different unit systems. The nitrogen balance trial lasted 5 d with 48 h of fasting (with roosters receiving only water+sucrose) and the last 72 h for feeding and excreta collection. Forty grams of each diet first-limiting in valine, isoleucine, or tryptophan was fed by tube each day (3 d) to give a range of intakes from 0 to 101, 0 to 119, and 0 to 34 mg/kg BW d of valine, isoleucine, and tryptophan, respectively. A nitrogen-free diet containing energy, vitamins, and minerals, meeting the rooster requirements, was offered ad libitum during these three d. To confirm that the amino acids studied were limiting, a treatment was added with a control diet formulated by adding 0.24 g/kg of L-valine, 0.21 g/kg of L-isoleucine, and 0.10 g/kg of L-tryptophan to the diets with lower amino acid level. Excreta were collected during the last 3 d of the balance period and the nitrogen content of the excreta was analyzed. For each amino acid, a linear regression between nitrogen retention (NR) and amino acid intake was performed. The equations from linear regression were: NR=-98.6 (±10.1)+2.4 (±0.2)×Val, NR=-46.9 (±7.1)+2.3 (±0.1)×Ile, NR=-39.5 (±7.7)+7.3 (±0.4)×Trp; where Val, Ile, and Trp are the intakes of valine, isoleucine, and tryptophan in mg/kg body weight per d, respectively. The valine, isoleucine, and tryptophan required to maintain the body at zero NR were calculated to be 41, 20, and 5 mg/kg body weight per d, respectively. For the system unit mg per kg of metabolic weight, the intake of valine, isoleucine, and tryptophan was 59, 32, and 9, respectively. Considering the degree of maturity of the animal and body protein content (BPm (0.73)×u), the amounts of valine, isoleucine, and tryptophan required for maintenance were calculated to be 247, 134, and 37 mg per unit of maintenance protein (BPm (0.73)×u) per d. Maintenance requirement is more adequately expressed as body protein content.

Beta-thalassemia mutations in the Portuguese population.

In this study we have carried out haplotype analysis on the beta-globin gene cluster and characterized the beta-thalassemia mutation by oligonucleotide hybridization in 14 patients with thalassemia major and 5 with sickle cell/beta-thalassemia originating from southern Portugal. We found that three mutations, namely the beta(0)-39, beta(0) IVS-1 nt 1 and beta(+) IVS-1 nt 110 are prevalent accounting for 53%, 32% and 10% of the beta-thalassemia chromosomes respectively. In general each mutation was associated with a specific chromosomal haplotype; the beta(0)-39 mutation, however, was linked to three different haplotypes. These results indicate that three oligo-probes complementary to the most common mutations allow prenatal diagnosis by oligonucleotide analysis in 96% of the couples at risk of having offspring with thalassemia major in southern Portugal.