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The objective of this study was to obtain different dry matter contents and proportions of melon plant biomass for silage making. A completely randomized design with factorial arrangement (3 × 2) and four replications was adopted. The first factor consisted of three melon biomass mixtures based on as-fed composition of plant (branches + leaves) and harvested melon (fruits)—100% plant (0% fruit), 90% plant + 10% fruit, and 100% fruit. The second factor corresponded to the ensiled material, which was either fresh or dehydrated in the field after harvest (40% dry matter). Silages produced from dehydrated biomass after fruit harvest, containing 0% and 10% fruit, showed the highest dry matter contents: 297 g/kg and 293 g/kg, respectively. Silages produced from fresh biomass containing 0% and 10% fruit showed high concentrations of acetic acid, reaching 14.9 g/kg and 14.1 g/kg, respectively. Silages produced from dehydrated biomass containing 10% and 100% fruit showed better results in terms of the indicators associated with high-quality silage. Dehydration improves the fermentative profile and overall quality of melon silage.

This study aimed to create an equation to predict dry matter intake (DMI) and milk production and N-ureic in the milk of dairy cows managed in tropical conditions in Brazil. We used 113 observations from three experiments using lactating Jersey, Girolando, and Holstein cows. The goodness of fit of the developed equations was evaluated using the coefficients of determination (r2) and root mean square error (RMSE). There was a positive correlation between body weight and milk yield (MY) of r = 0.73. The equation considered DMI to be the most important variable to estimate the MY (r2 = 0.65). Four equations were adjusted to estimate the DMI, where, by a stepwise procedure, the first variable included in the equation was the neutral detergent fibre intake, which explained 92% of the DMI of the cows. However, when the variables BW, MY, and milk fat were included in the equation, there was a reduction of 0.06 in RMSE and an increase in precision (r2 = 0.94). The nutrient intake, milk production, and characteristics prediction equations present satisfactory precision and accuracy for dairy cows managed in tropical conditions in Brazil.