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The effects of four protein sources (soybean meal, sunflower meal, pea, and fish meal as the main protein source) and three apparent ileally digestible Lys:DE ratios (0.50, 0.43, 0.36 and 0.42, 0.36, 0.30 g Lys/MJ DE for 30 to 60 kg BW and 60 to 105 kg BW, respectively) in pig diets on growing-finishing performance, and carcass and meat quality traits were investigated. Eight individually housed animals per treatment received the diets from 30 to 105 kg BW at a level of 3.0 times maintenance requirements of energy. The ileal digestibility of protein sources was determined in a previous digestibility experiment. Protein sources showed no differences in growth performance from 30 to 105 kg BW. From 30 to 60 kg BW soybean treatment had lowest performance. The protein sources had no effect on lean meat percentage, liver weight, or meat quality (intramuscular fat content, pH at 45 min and 24 h after slaughter, drip loss, and meat color measured 24 h and 4 d after slaughter). The experimental diets formulated on the basis of similar apparent ileal digestible lysine content resulted in similar body composition regardless of the protein source used (P > 0.05). Reducing the Lys:DE ratio from 0.50/0.43 to 0.36/0.30 (by about 28%) reduced BW gain by 119 g/d from 30 to 60 kg and by 151 g/d from 60 to 105 kg BW. The gain:feed ratio increased by 82 g/kg in the first phase and by 47 g/kg in the second phase for the highest Lys:DE treatment compared with the lowest. Reducing Lys:DE ratio did not modify meat quality traits. A high Lys:DE ratio was associated with a high lean meat percentage. Differences between the medium- and low-Lys:DE groups were not significant. Lowering the Lys:DE ratio increased (P < 0.05) crude fat and fatty tissue content and decreased (P < 0.05) protein and muscle content in the body. Ash content and bone volume were not affected by Lys:DE ratio (P > 0.05). The chemical composition of the carcass can be predicted with moderate accuracy (R2 = 0.39 to 0.58) using volumetric composition data of previously frozen carcasses. In conclusion, similar growth performance, carcass and meat quality, and body composition can be expected if diet formulation is based on the apparent ileally digestible amino acid contents of feedstuffs, independent of dietary protein sources. Diminishing Lys:DE ratios reduce growth performance but do not modify meat quality traits. The chemical composition of the carcass can be predicted with moderate accuracy using the volumetric composition of thawed carcasses.

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The aim of this review was to discuss the effects of heat stress on antioxidant status and performance in poultry. Based on the recent literature data, the following conclusions can be drawn: (1) Heat stress can cause harmful effects in birds (e.g. increased ROS (Reactive Oxygen Spices) production and lipid peroxidation, decreased vitamin concentrations, changed enzyme activity) and consequently in production parameters (e.g. feed intake, body weight and feed conversion ratio). (2) Diets containing high Vitamin A (9000-15 000 IU/kg diet), E (150-500 mg/ kg diet), C (150-500 mg/kg diet) and Zn (30/60 mg/kg diet) and Se (0.1-1 mg/kg diet) can decrease the amounts of free radicals, support enzyme activity and prevent lipid peroxidation in poultry.(3) Application of antioxidant vitamins and micro minerals in poultry nutrition is more effective in combination than separately. ARTICLE HISTORY

This study was conducted to investigate the effect of carotenoid, oligosaccharide and anthocyanin supplementation in broiler diets under Escherichia coli lipopolysaccharide (LPS) challenge. Ross 308 chickens were fed 5 diets: basal diet (control diet), diet supplemented with β-glucan in 0.05% (positive control) and diets with 0.5% carotenoid-, oligosaccharide- or anthocyanin contents. On the 26th days of age, chickens were challenged intraperitoneally 2 mg LPS per kg of body weight. 12 h after injection, birds were euthanized, then spleen and ileum samples were collected. LPS induced increased relative mRNA expression of splenic (p = 0.0445) and ileal (p = 0.0435) interleukin-1β (IL-1β), which was lower in the spleen in carotenoid (p = 0.0114), oligosaccharide (p = 0.0497) and anthocyanin (p = 0.0303)-treated chickens compared to LPS-injected control birds. Dietary supplementation of carotenoids also decreased relative gene expression of splenic interleukin-6 (IL-6) (p = 0.0325). In the ileum, β-glucan supplementation showed lower relative mRNA expression of toll-like receptor 5 (TLR-5) (p = 0.0387) compared to anthocyanin treatment. Gene expression of both splenic and ileal interferon-α (IFN-α), interferon-γ (IFN-γ), toll-like receptor 4 (TLR-4) and toll-like receptor 5 (TLR-5) were not influenced by dietary supplements. In conclusion, carotenoids, oligosaccharides and anthocyanins could partially mitigate the immune stress caused by LPS challenge. All of the compounds impacted longer villus height (p < 0.0001), villus height:crypt depth ratios were higher after β-glucan (p < 0.0001) and anthocyanin (p = 0.0063) supplementations and thickened mucosa was observed in β-glucan (p < 0.0001), oligosaccharide (p < 0.0001) and anthocyanin (p = 0.048) treatments. All of these findings could represent a more effective absorption of nutrients.

A dynamic mechanistic model was developed for growing and fattening pigs. The aim of the model was to predict growth rate and the chemical and anatomical body compositions from the digestible nutrient intake of gilts (20 -105 kg live weight). The model represents the partitioning of digestible nutrients from intake through intermediary metabolism to body protein and body fat. State variables of the model were lysine, acetyl-CoA equivalents, glucose, volatile fatty acids and fatty acids as metabolite pools, and protein in muscle, hide-backfat, bone and viscera and body fat as body constituent pools. It was assumed that fluxes of metabolites follow saturation kinetics depending on metabolite concentrations. In the model, protein deposition rate depended on the availability of lysine and of acetyl-CoA. The anatomical body composition in terms of muscle, organs, hide-backfat and bone was predicted from the chemical body composition and accretion using allometric relationships. Partitioning of protein, fat, water and ash in muscle, organs, hide-backfat and bone fractions were driven by the rates of muscle protein and body fat deposition. Model parameters were adjusted to obtain a good fit of the experimental data from literature. Differential equations were solved numerically for a given set of initial conditions and parameter values. In the present paper, the model is presented, including its parameterisation. The evaluation of the model is described in a companion paper. Modelling: Anatomical body composition: Chemical body composition: PigSince the introduction of pig growth models, applicable in a scientific and a practical environment in the 1970s and 1980s (for example, see Whittemore & Fawcett, 1976;Moughan et al. 1987;Black et al. 1988), interest in prediction of pig growth has increased over the years. New models have been introduced, each serving their own objective: some models have focused on nutrient digestion processes (Bastianelli et al. 1996), on protein digestion in the small intestine (Rivest et al. 2000) or on estimating amino acid requirements (Moughan, 1989). Others have aimed to model growth rate and its composition in terms of protein and lipid (Burlacu et al. 1989;Pomar et al. 1991;Danfaer, 2000;Birkett & de Lange, 2001b), or especially fatty acid composition of the body fat (Lizardo et al. 2002), or improving understanding of different processes, such as protein turnover and ion pumping (Gill et al. 1989b), or the process of growth (Lovatto & Sauvant, 2003). In addition, pig growth modelling efforts have been reviewed and various approaches have been discussed extensively (Black, 1995;Gerrits & Dijkstra, 2000;Halas & Babinszky, 2000;Birkett & de Lange, 2001a). Most pig growth simulation models until the 1990s considered protein and energy as separate entities (de Lange, 1995).As acknowledged in more recently developed models, this approach ignored the effects of differences in the composition of the dietary energy (Danfaer, 2000;Birkett & de Lange, 2001a). In addition to models predicting che...

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