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. 2026 Feb 2;13:1744053. doi: 10.3389/fvets.2026.1744053

Figure 4.

Flowchart illustrating the process of predicting offspring performance based on maternal blood attributes. It starts with collecting routine blood samples before gestation and analyzing maternal attributes like hormones and metabolites. This data, combined with animal records, influences colostrum profile and newborn growth. A machine learning model correlates this data during late gestation. The model's predictions are evaluated in both physical and digital twin environments, focusing on nutrition, breeding, vaccination, and reproduction effects. The outcomes emphasize immunity, growth, and productivity. Information feedback aids in refining the process.

Describes the virtual lab model in extending the research findings.