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Simulation study reveals optimal high- and low-protein base feeds for precision-fed pigs, indicating that single robust feed pairs minimize costs and nitrogen excretion without added complexity.
The strategic formulation of base feeds in precision feeding (PF) systems for growing-finishing pigs remains a critical upstream challenge for balancing production costs and nitrogen (N) excretion. This study evaluated a conditional scenario-analysis tool designed to identify optimal standardized ileal digestible lysine (SID Lys) concentrations for high-protein (H) and low-protein (L) base feeds. Daily feed intake and body weight records from 179 Duroc × (Large White × Landrace) barrows (days 17 to 84 of fattening) were used as a fixed performance baseline. A simulation pipeline explored a grid of 1,368H/L feed combinations (H: 10.1–11.8 g/kg SID Lys; L: 2.5–10.0 g/kg SID Lys) across three historical feed price scenarios (September 2021, July 2022, and March 2023). Feasible candidate feeds were filtered using a dual feasibility criterion based on the i100 limitation index (paired Wilcoxon signed-rank test P ≥ 0.05 and median i100 difference ≤ 1.5 percentage points relative to the trial). Formulations with H feed below 11.5 g/kg SID Lys systematically increased nutrient inadequacy (P < 0.05). Retained candidate pairs demonstrated that H = 11.5 g/kg SID Lys achieved minimal feed cost per animal across all price scenarios, while optimal L feed concentrations shifted between 6.6, 7.9, and 7.6 g/kg SID Lys depending on ingredient market volatility. From an environmental perspective, H = 11.5 g/kg and L = 7.4 g/kg SID Lys minimized estimated N excretion to 43.34% of N intake (1.245 kg N/animal). Temporal clustering of the fattening period into three phases yielded only marginal feed cost reductions compared to a single full-period base feed specification. Consequently, swine operations can prioritize a single, robust pair of base feeds (11.5 g/kg H and intermediate L) managed via daily dynamic blending without increasing operational or logistical complexity.
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Sacanell et al. (2026) studied this question.
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