In order to study the smart management of dairy farms, this study combined Internet of Things (IoT) technology and dairy farm daily management to form an intelligent dairy farm sensor network and set up a smart dairy farm system (SDFS), which could provide timely guidance for dairy production. To illustrate the concept and benefits of the SDFS, two application scenarios were sampled: (1) Nutritional grouping (NG): grouping cows according to the nutritional requirements by considering parities, days in lactation, dry matter intake (DMI), metabolic protein (MP), net energy of lactation (NEL), etc. By supplying feed corresponding to nutritional needs, milk production, methane and carbon dioxide emissions were compared with those of the original farm grouping (OG), which was grouped according to lactation stage. (2) Mastitis risk prediction: using the dairy herd improvement (DHI) data of the previous 4 lactation months of the dairy cows, logistic regression analysis was applied to predict dairy cows at risk of mastitis in successive months in order to make suitable measurements in advance. The results showed that compared with OG, NG significantly increased milk production and reduced methane and carbon dioxide emissions of dairy cows (p < 0.05). The predictive value of the mastitis risk assessment model was 0.773, with an accuracy of 89.91%, a specificity of 70.2%, and a sensitivity of 76.3%. By applying the intelligent dairy farm sensor network and establishing an SDFS, through intelligent analysis, full use of dairy farm data would be made to achieve higher milk production of dairy cows, lower greenhouse gas emissions, and predict in advance the occurrence of mastitis of dairy cows.

Due to the increasing costs of livestock farming, it is important to find cost-effective alternatives of feed stuffs. This study investigated the effects of high-moisture ear corn (HMEC) feeding on the production performance, serum antioxidant capacity, immunity, and ruminal fermentation and microbiome of dairy cows. Thirty pluriparous Chinese Holstein cows were randomly allocated to two groups: steam-flaked corn (SFC) and HMEC (replacement of 2 kg equal dry matter SFC) and fed for a 60 day trial. The results showed replacing SFC with HMEC significantly increased dry matter intake, milk yield, and 4% fat-corrected milk yield (p < 0.05). Serum levels of superoxide dismutase, glutathione peroxidase, and immunoglobulins G, M, and A were significantly higher, and those of creatinine and cholesterol were significantly lower, in the HMEC group than in the SFC group (p < 0.05). HMEC also significantly increased total volatile fatty acid and acetate (p < 0.05) concentrations. In both groups, the dominant phyla of ruminal bacteria were Bacteroidetes, Firmicutes, and Actinobacteria, and the dominant genera were Prevotella, NK4A214-group, and Succiniclasticum. Mogibacterium, Eubacterium nodatum group, norank-f-Lachnospiraceae, and Eubacterium brachy group were significantly enriched in the ruminal fluid of HMEC-group cows (p < 0.05). In conclusion, replacing SFC with HMEC improved production performance, antioxidant capacity, and immunity, while regulating both ruminal fermentation and the composition of the ruminal microbiome in dairy cows.