Paradigm Shift in Laying Hen Nutritional Strategies: Precision Feeding for Sustained Egg Production

  The commercial egg industry is increasingly interested in extending laying cycles toward 100 weeks to improve resource efficiency and distribute pullet-replacement costs over a greater number of eggs. However, feeding programs based mainly on fixed crude protein (CP) concentrations tend not to adequately account for age-related changes in feed intake, egg mass output, amino acid utilization, energy balance, and eggshell formation. Extended laying cycles also present increasing challenges related to liver health, skeletal integrity, and eggshell quality. This review examines precision-feeding strategies based on standardized ileal digestible (SID) amino acids and the ideal protein concept. Phase-specific adjustment of nutrient supply may align amino acid and energy intake more closely with changes in production, maintenance requirements, and feed intake during early, mid, and late lay. Crystalline amino acid supplementation can facilitate reductions in dietary CP while maintaining a balanced digestible amino acid profile; however, excessive CP reduction may impair egg mass output, body condition, or productivity unless all limiting amino acids are adequately supplied. The review also considers the integration of precision livestock farming technologies. Sensor-based monitoring, nutritional response models, and artificial intelligence-assisted decision support can enable more frequent evaluation of flock performance and more responsive feeding and environmental management. Nevertheless, fully autonomous systems linking real-time data directly to diet reformulation and feed delivery remain largely experimental in commercial laying-hen production. Overall, phase-specific precision feeding can improve nitrogen-use efficiency, support metabolic health and eggshell quality, and enhance the economic and environmental sustainability of extended laying cycles. Its practical benefits depend on diet formulation, flock performance, ingredient prices, housing conditions, manure management, and the reliability of data-driven technologies.