Multiple factor analysis to identify correlated variable among microclimate, thermal comfort and infrared thermography in agroforestry systems.

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Resumo: Goal was to use the Multiple Factor Analysis to reduce dimensionality of variables, to identify groups of correlated variables and to obtain a common assessment tool to evaluate microclimate, thermal comfort and infrared thermography in agroforestry systems. The experiment was conducted at the Embrapa Beef Cattle, Campo Grande, MS, from July 2015 to February 2016, corresponding to winter and summer seasons, in two agroforestry systems with different tree densities and spatial arrangements of native and planted trees. Readings were made from 8:00 a.m. to 4:00 p.m., for microclimate parameters (air temperature, dew point temperature, black globe temperature, relative humidity, wind speed, global solar radiation, photosynthetically active radiation and luminosity), thermal comfort (Temperature and Humidity Index, Black Globe and Humidity Index, Radiation Thermal Load), and infrared thermography (temperature and humidity of tree crown and soil surface), under full sun and shadow projection. Multiple Factor Analysis found three Synthetic Analytical Dimensions that explained 55.5% of the total observed variance. Strong and positive associations between infrared thermography, microclimate, thermal comfort and radiation were found. Thus, it is suggested that infrared thermography is a potential tool to be used for microclimate prediction and thermal comfort under agroforestry systems.

Ano de publicação: 2019

Tipo de publicação: Artigo em anais e proceedings

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