Abstract
Fall in livestock productivity and reproduction due to high summer temperatures has been a serious problem in livestock industry. Applying heat shielding coating to a livestock barn roof is effective to suppress the rise of air temperature inside the barn. However, the effect of applying heat shielding coating to the roof on improvement in livestock productivity have not been made clear yet. In this study, seasonal change of milk yield in dairy cow was predicted by a simulation using neural network to examine the effect of heat shielding coating to a livestock barn roof on improvement in livestock productivity. Seasonal changes of air temperatures, amount of precipitation and milk yield from April through October for five years from 2014 to 2018 in Tokachi, Hokkaido were trained by a neural network. Assuming that air temperature inside the barn due to heat shielding coating barn roof is expected to reduce by up to four degrees Celsius, we performed numerical simulations for estimation of milk yield. As a result, the increase in milk yield per a cow per a month was up to 20.0 kilograms, and the rate of increase in milk yield per a cow was up to 2.1 percent. Therefore, the simulation using the neural network in which seasonal change of milk yield in dairy cow was trained showed that heat shielding coating barn roof was effective to improve the fall in milk yield of dairy cow.
