EFEITOS DE ESTRATÉGIAS DE APLICAÇÃO DE FUNGICIDAS NO DESEMPENHO AGRONÔMICO DA SOJA

Abstract

Proper fungicide management is essential to ensure soybean agronomic performance, especially under foliar disease pressure. This study aimed to evaluate the impact of different fungicide application strategies on soybean morphological, reproductive, and yield-related variables using Linear Mixed Models (REML), Principal Component Analysis (PCA), and Path Analysis with Ridge regularization. The experiment was conducted in a randomized complete block design, with four treatments (three BASF commercial programs and one farm-based program) and four replications. The BASF 2 program achieved the highest mean yield (66.31 bags ha⁻¹), outperforming BASF 1 by +19.8%, BASF 3 by +14.0%, and the farm program by +7.6%. Analyses indicated that the number of grains per plant (NGP) and the total number of pods (NTV) were the most decisive variables for yield, with additional positive direct effects for NV3G and AP, and negative effects for DC and NV1G. The first two PCA axes explained 67.8% of the total variability, positioning BASF 2 as the most reproductively efficient program. Although disease severity was not directly measured, the results show that combining multiple modes of action enhances productivity and improves the crop’s morphophysiological balance. Further studies should be conducted across different environments and cultivars to confirm the consistency of these effects and refine management recommendations.