Black globe temperature from meteorological data and a bioclimatic analysis of the Brazilian Northeast for Saanen goats

摘要

The black globe temperature (BGT) is not a common measurement for weather station networks, despite having great relevance to bioclimatic studies. The aim of this study was to propose equations for estimating the BGT, using meteorological data for different time scales and a bioclimatic evaluation of the Brazilian Northeast for breeding Saanen dairy goats. The data used in elaborating the equations were collected between 1 November 2014 and 31 October 2017. Data for BGT, incident global solar radiation (SR), air temperature (AT), relative humidity (RH) and wind speed were handled on a daytime, night-time, daily and monthly scale. One half of the database was used to adjust the equations and the other half in the evaluation. The bioclimatic diagnosis of the Brazilian Northeast was carried out based on mean monthly values of the black globe temperature and humidity index (BGHI) estimated for the four seasons of the year. For the daytime scale, an equation based on AT (BGT = 1.3897.AT-5.4421, r(2) = 0.80) and a multiplicative model combining the effects of AT and SR (BGT = [1.3897.AT-5.4421] (0.0384.In(SR) + 0.7935J, r(2) = 0.91) were obtained. AT adjusted well for BGT on the night-time scale (BGT = 0.995.AT-0.6964, r(2) = 0.99), daily scale (BGT = 1.1641.AT-1.5941, r(2) = 0.97) and monthly scale (BGT = 1.1550.AT-1.3498, r(2) = 0.98). The BGT can therefore be calculated from AT and/or SR for the daytime scale, and from AT only for the night-time, daily and monthly scales. In general, the west and centre-south of the state of Bahia offer the animals the most thermal comfort during each season of the year. In the state of Maranhao, heat stress occurs throughout the year, with the BGTI predominately in the range of 85-95. As such, strategies to combat heat stress should be encouraged to minimise the negative effects of climate on milk production in Saanen goats, and favour the milk-production chain in the northeast of Brazil.