Modeling the relationship between heat stress, feed intake, and day relative to calving in nonlactating dairy cows.

Heat stress (HS) during the dry period can affect animal welfare, health, dry matter intake (DMI), and milk production in the subsequent lactation, which will negatively affect the profitability of dairy farms. In this study, the objective was to model the changes in DMI in pregnant nonlactating heat-stressed dairy cows with or without access to evaporative cooling systems. A database was built, composed of individual DMI records from 244 pregnant nonlactating dairy cows from an average -29.3 d (range: -42 to -21 d; SD: ±7.54 d) to -1 d relative to calving (DRC) and housed in environmental conditions in which temperature-humidity index (THI) ranged from 58.4 to 83.3, with or without access to evaporative cooling systems. Generalized additive mixed-effects models were used to describe the relationships of DMI with HS and DRC. Changes in DMI with the increase in THI and the progression of pregnancy in cows with or without evaporative cooling systems were estimated using differential equations. On average, cows housed in barns without evaporative cooling systems had a reduction in DMI of 1.30 kg/d and increased rectal temperature in 0.22°C in relation to those housed in barns with evaporative cooling systems. Dry matter intake decreased as THI increased, but the reduction was greater for noncooled cows as THI values increased. In addition, regardless of the THI, DMI started to decrease at -14 DRC for cooled cows, whereas for noncooled cows it already started at -30 DRC, relative to the previous days evaluated. The intensity of the reduction was lesser for cows that had access to evaporative cooling systems or were in the dry period in May to June as compared with those that were in the dry period in July to August or September to October. The models generated in this study, which include environmental variables, should lead to more accurate predictions of DMI during HS that can be used to formulate diets to meet the needs of the late pregnant cow because it is possible to predict changes in DMI as the heat load and DRC change. Such models are also expected to help dairy nutritionists to decide when and how to apply the dietary strategies available to attenuate the reductions in DMI with the intensity of HS and progression of pregnancy.