Oxidative stress significantly compromises the production efficiency of laying hens. It has been reported in literature that selenium (Se) in poultry diets has a positive effect on mitigating these effects. This study has been carried out to evaluate the effects of Se supplementation in feeds, from either an inorganic or a hydroxy-selenomethionine (OH-SeMet) source, on the performance and physiological traits of 50- to 70-wk-old Dekalb Brown laying hens under heat stress, and on their egg quality after different storage durations. The treatments consisted in supplementing 0.3 ppm of Se as sodium selenite (SS; 45%–0.7g/ton) or OH-SeMet (2%–15g/ton) in twelve 16-bird replicates. Supplementation with OH-SeMet resulted in a better performance of the laying hens than with SS: −5% feed conversion ratio and +3.6% of egg mass. A reduction in egg quality was observed with prolonged egg storage, which was mitigated with the use of OH-SeMet in laying hen diets. The use of OH-SeMet increased the antioxidant capacity of the birds, which showed higher glutathione peroxidase levels in the blood, kidneys, liver, and intestinal mucosa, in addition to a higher Se content in the eggs and a greater bone resistance. Thus, supplementing feeds with 0.3 ppm of OH-SeMet to 50- to 70-wk-old semi-heavy laying hens enhances their antioxidant capacity and leads to a higher egg quality and productivity than SS supplementation.

This study aimed to evaluate the impact of DL-Methionine (DL-Met) or OH-Methionine (OH-Met) when supplemented beyond the usually accepted requirements in sulfur amino acids (SAA) on the performance and carcass traits of growing-finishing pigs. Two hundred mixed sex pigs were distributed in a randomized block (body weight and sex), under a 2 × 2 factorial design with two methionine sources, DL-methionine, or OH-Methionine and two methionine doses (100% SAA or 120% of the SAA level present in the control). Diets were formulated to meet amino acids recommendations of the Brazilian Tables for Poultry and Swine (2017), except for SAA, which varied with the methionine doses. Daily feed intake, daily weight gain, and feed conversion were evaluated. Moreover, the carcasses were measured electronically for fat thickness (FT), longissimus dorsi muscle depth (LD), and lean meat (%). During the growing phase II (92 till 122 days of age), daily feed intake (p < 0.001) and daily weight gain (p < 0.05) increased with the high SAA levels. High SAA levels also provided greater daily weight gain during the entire period of the trial (0.90 versus 0.86 kg; p < 0.05) No significant interaction was observed between the methionine source and the SAA level for any carcass traits. However, animals that received OH-Met had greater (p < 0.05) loin depth (58.37 versus 55.21 mm) and those that received higher doses of methionine presented heavier (p < 0.05) carcass weight (78.16 versus 74.70 kg), and more (p < 0.05) lean meat weight (43.69 versus 41.90 kg). Taken together, these results demonstrated that supplementation of high sulfur amino acids levels under hot conditions provided heavier carcasses and more lean meat.

Broilers raised in tropical environments face significant oxidative stress due to heat, which can impair performance. Vitamin E and selenium (Se) are key nutrients supporting antioxidant defenses and are commonly supplemented in feed. This study evaluated the effects of two selenium sources-sodium selenite (SS) and hydroxy‑selenomethionine (OH-SeMet)-combined with standard or reduced vitamin E levels on broiler performance. A total of 800 male broilers were assigned to a 2 × 2 factorial design. Results demonstrated that OH-SeMet improved growth and feed efficiency compared to SS, regardless of vitamin E level, while reduced vitamin E impaired early growth but not overall performance. The combination of OH-SeMet with standard vitamin E provided the best feed conversion ratio at 44 days. These findings highlight the benefits of using OH-SeMet with adequate vitamin E supplementation to enhance broiler resilience to heat stress, offering a practical strategy for improving production efficiency in tropical commercial operations.

The study evaluated the effects of replacing corn with whole and ground sorghum on the zootechnical performance of turkeys fed from one to 28 days of age. A total of 3,960 male Nicholas turkeys were used, divided into six treatments: A) Whole sorghum (100%Sw); B) Ground corn (100%Cg); C) 75% Ground Corn + 25% Ground Sorghum (75%Cg/25%Sg); D) 50% Ground Corn + 50% Ground Sorghum (50%Cg/50%Sg); E) 25% Ground Corn + 75% Ground Sorghum (25%Cg/75%SG) and F) Ground Sorghum (100%Sg). At seven days, live weight was the same between treatments (164 g per bird). At 28 days, the percentage of breast, thigh-drumstick, and wings remained constant in the corn-based diet or partial and total replacements by ground or whole sorghum grain. The length of the small intestine was shorter in treatments B and C. The digestibility of the lipid fraction of the diet (DEE) was significantly higher in the diet with ground sorghum. The treatment based on ground sorghum grain showed the same result for ground corn in the dry matter (DM) and mineral matter (MM DM%) composition of the turkey carcass at 28 days. Ground sorghum influenced the lipid portion of the carcasses (EE DM%). Thus, it is concluded that whole sorghum grain presented the same results as ground sorghum and ground corn for zootechnical performance, carcass muscle mass, and viscera morphometry in turkeys at 28 days of age.

Corn is the primary energy source for livestock and poultry. Corn nutrient composition and energy value vary due to genetics, country of origin, agronomic, harvest, and storage conditions. Analytical variability among and within-labs makes it more difficult to detect differences among sources and establish nutrient interrelationships to estimate amino acid (AA) content based on crude protein (CP), which is less variable. Near-infrared reflectance spectroscopy (NIRS) can standardize feedstuff evaluation and increase the sample size. The PNE system (Adisseo) has distinctive NIRS curves created using direct calibrations with in vivo data of standard chicken metabolizable energy (AME and AMEn) and AA digestibility studies. This study assessed the link between AA concentrations and CP and among proximate parameters (CP, crude fiber, ether extract, nitrogen-free extract, and ash), starch, AA concentrations and digestibilities with AME and AMEn. The PNE database used includes 84,331samples of maize scanned in diverse countries between 2018 and 2021 that came from Argentina (7,654), Brazil (49,672), Indonesia (18,072), Philippines (4,747), and the United States (4,186). Correlation and regression analyses between AA and CP were performed. The pairwise correlations (P < 0.001) observed between AA and CP ranged between 0.52 and 0.90. The positive linear associations with CP content can be used to predict the concentrations of all AAs in corn (P < 0.001). However, coefficients of determination (R²) ranged from 0.27 (Trp) to 0.80 (Val) or 0.81 (Phe). Prediction equations for Lys, sulfur AAs had lower R² values (0.37 to 0.47). Although the country of origin and CP interacted (P < 0.001), R² modestly increased when added to these models. The estimation of AME and AMEn based on proximate values, starch, amylose, amylose:amylopectin, AA concentrations, AA digestibility, and country of origin was done using multiple linear regression (MLR) and neural networks (NN) analysis. All factors were significant (P < 0.001), and MLR models including starch and amylopectin, had the best fit for AME (R² = 0.87, AICc = 149,635) and AMEn (R² = 0.87, AICc = 149,543). The NN models had a better fit for training and validation datasets for AME (R² = 0.95, RASE = 15.18) and AMEn (R² = 0.95, RASE = 15.23). The NN models helped to visualize the greater importance of starch, AA concentration (Trp, Ile, Thr), and Leu digestibility. In summary, some corn AA concentrations (Val, Phe, Ile) may be predicted from their CP content; other AA concentrations may be more difficult to predict. Corn AA content varies by country of origin and independent of CP content. Starch content, AA concentration, and AA digestibility are essential factors in determining energy value of corn. Relevant nutritional aspects were elucidated by data analytics of a NIRS database with direct calibration of in vivo parameters of energy utilization and AA digestibility.