Silymarin, a natural acknowledged hepatoprotector used in humans to treat liver diseases, has been tested in dairy cows during peripartum, a period during which animals are subject to subclinical fatty liver. Ten grams of silymarin (76% pure extract consisting in flavonolignans, taxifolin, and other trace compounds) per day, was administered as a water suspension by an oral drench to 15 cows from d 10 before expected calving to 15 d after calving. Milk production was measured, and colostrum, milk, and blood samples were analyzed during the experimental period. Treated animals showed the peak of milk production at 55 +/- 1.85 d after calving, 1 wk before the control group (62 +/- 3.27 d); the average peak production was 41.6 +/- 1.05 kg for the treated group vs. 39.1 +/- 1.44 kg for the control; the treated animals maintained a greater milk production than control cows throughout lactation (9922.1 +/- 215.7 vs. 9597.8 +/- 225.4 kg). Milk composition was unaffected by treatment. No silymarin residues were detected in colostrum and all milk samples. After calving, body condition score (BCS) decrease was greater for control compared with treated cows. Glucose, urea, triglycerides (TG), total cholesterol, beta-hydroxibutyrate (BHBA), and gamma-glutamyl transferase (GGT) in plasma were unaffected by treatment. Plasma nonesterified fatty acids (NEFA) on d-7 were higher in treated cows compared with the control group (741 vs. 181 micromol/L). From this evidence, it is possible to conclude that silymarin beneficially affected lactation performances and body condition of treated animals. Blood and milk parameters do not indicate any adverse effects of feeding this natural compound.

The expansion of dairy cattle farms and the increase in herd size have made the control and management of animals more complex, with potentially negative effects on animal welfare, health, productive/reproductive performance and consequently farm income. Precision Livestock Farming (PLF) is based on the use of sensors to monitor individual animals in real time, enabling farmers to manage their herds more efficiently and optimise their performance. The integration of sensors and devices used in PLF with the Internet of Things (IoT) technologies (edge computing, cloud computing, and machine learning) creates a network of connected objects that improve the management of individual animals through data-driven decision-making processes. This paper illustrates the main PLF technologies used in the dairy cattle sector, highlighting how the integration of sensors and devices with IoT addresses the challenges of modern dairy cattle farming, leading to improved farm management.