Predictive models of incident solar radiation and its reflectance on surfaces with anti-weed screens

Abstract

In agriculture, the wavelengths of interest are UV A + B radiation and photosynthetically active radiation. Different techniques can be used by farmers to enhance radiation distribution on crops, with one alternative being the installation of polypropylene anti-weed nets. The analysis of the radiation balance can be performed using different predictive methods, which are a function of solar geometry, climate, and weather variables. The objective of this research was to develop multiple regression models for comparison with the Holt-Winters model in time series to analyze and estimate incident radiation and its reflectance on surfaces covered with white and black polypropylene anti-weed nets and soil without cover. The results indicate an increase in radiation and temperature between Julian days 116 and 273, decreasing significantly with cloud cover. The white polypropylene anti-weed nets reflected a higher amount of solar radiation. On the other hand, the multiple regression models presented better accuracy for the prediction of incident solar radiation and its reflectance compared to the Holt Winters time series model. However, each model provides a different analysis of radiation, so that they can be complementary in decision making for agricultural purposes.