Morphometric and hormonal correlations in high- and low-yield baizi geese during off-season production

This study investigated the relationships among morphometric characteristics, reproductive hormones, and metabolic parameters in high-yielding versus low-yielding Baizi geese to identify physiological determinants of egg production performance during off-season breeding. Seventy female Baizi geese were classified into high-yielding (BHYG, n = 35) and low-yielding (BLYG, n = 35) groups based on individual production records. Morphometric measurements included body weight, body oblique length, neck length, neck circumference, pubic distance, and abdominal circumference. Serum samples were analyzed for reproductive hormones (estradiol [E2], follicle-stimulating hormone [FSH], luteinizing hormone [LH], prolactin [PRL], progesterone, testosterone) and metabolic indicators (uric acid [UA], creatinine [CREA], glucagon [GCG], glucose, total protein, triglycerides, calcium, phosphorus). BHYG exhibited significantly superior morphometric characteristics compared to BLYG, including greater body weight, body oblique length, pubic spacing, abdominal circumference, and neck length (P < 0.01 or P < 0.05). Hormonal profiles revealed significantly elevated E2 and FSH concentrations in BHYG (P < 0.01), with higher LH levels (P < 0.05). Metabolic analysis demonstrated significantly lower UA, CREA, and GCG concentrations in BHYG (P < 0.05). Correlation analysis identified strong positive associations between body weight and both pubic spacing (r = 0.711, P < 0.01) as well as abdominal circumference (r = 0.745, P < 0.01). Additionally, LH exhibited strong positive correlations with FSH (r = 0.396, P < 0.01) and E2 (r = 0.333, P < 0.01). These findings demonstrate that high egg production performance in Baizi geese is characterized by distinct morphometric, endocrine, and metabolic profiles. The results establish evidence-based phenotypic and physiological selection criteria for breeding programs and indicate that out-of-season production efficiency may be enhanced through targeted nutritional interventions and optimized environmental management strategies.