Fuzzy modeling of vegetable straw cover crop productivity at different nitrogen doses

Abstract

The Direct Planting System (DPS), also referred to as direct seeding or no-tillage farming, is distinguished by the permanent occupation of the agricultural land with plant crops besides the maintenance of the straw under the soil surface. However, for its effectiveness, it is necessary to adopt suitable cover crops for each region. Sorghum has a high tolerance to the dry season and a high volume of dry matter production, which are important characteristics for adoption as a cover crop. Millet, besides having a high resistance to periods of water stress, has also a high concentration of biomass production. In this context, the present work aimed to analyze, through the use of mathematical models, the effects of nitrogen in sorghum and millet crops, adopted as vegetation cover crops, under different levels of nitrogen in relation to the dry matter production variables. The comparison of the fuzzy (Gaussian and triangular) and polynomial regression models was performed using statistical tests and verification of the determination coefficient. Analytically, the best statistical parameters for triangular fuzzy modeling were verified in comparison to the Gaussian fuzzy model and polynomial regression of degree two. However, in relation to the behavior of the mathematical modeling curve, the Gaussian model proved to be best in keeping with the reality of the agronomic phenomena, mainly due to the smoothing of the curve over the data set.