Reveals metabolic and hormonal biomarkers predict reproductive health in dairy cattle, indicating improved management strategies.
Reproductive efficiency is one of the most important determinants of profitability and sustainability in dairy farming. Among the various reproductive disorders affecting cattle and buffaloes, anestrus is the most frequently encountered condition, particularly during the postpartum period. It is characterized by the absence of visible estrus signs and failure of the ovaries to resume normal cyclic activity, leading to prolonged calving intervals, reduced conception rates, increased insemination costs, and substantial economic losses to dairy farmers. Traditionally, diagnosis of anestrus relied on clinical examination and hormonal assays; however, advances in veterinary clinical biochemistry have revealed that several metabolic, hormonal, mineral, inflammatory, and oxidative stress biomarkers can provide valuable insights into the physiological status of affected animals. Biomarkers such as glucose, cholesterol, non-esterified fatty acids (NEFA), beta-hydroxybutyrate (BHBA), calcium, phosphorus, zinc, progesterone, estradiol, insulin-like growth factor-1 (IGF-1), malondialdehyde (MDA), superoxide dismutase (SOD), glutathione peroxidase (GPx), and acute phase proteins have emerged as reliable indicators of reproductive health. Early identification of alterations in these biomarkers allows timely nutritional correction, hormonal intervention, and managemental improvements before irreversible reproductive dysfunction occurs. Furthermore, rapidly evolving technologies including metabolomics, biosensors, nanotechnology, wearable sensors, and artificial intelligence are transforming reproductive monitoring by enabling real-time health assessment and precision livestock management. This article highlights the scientific significance of these biomarkers and discusses their growing role in improving fertility management and reproductive efficiency in dairy cattle.
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Divyanshi Sharma1, Naman Munjal, Sheetal Chaudhary, Geetanjali Singh, Rishika Vij (2026) studied this question.
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