Variáveis meteorológicas relacionadas ao início da epidemia causada por Phakopsora pachyrhizi em soja

Abstract

Asian soybean rust is caused by the pathogen Phakopsora pachyrhizi that develops and spreads rapidly under ambient conditions of humidity and temperature. The literature lacks information about the relationship between these factors and the appearance of the first symptom of the disease due mainly to the difficulty of performing this type of field experiment. The objective of this work was to identify which meteorological variables are determinant for the appearance of the first visible symptom of the disease using periods of days prior to Pearson (r) correlation, track analysis and principal component analysis field. The experiment was carried out in the agricultural years of 2015/16 and 2016/17, at the experimental station of the Phytus Institute, located in the municipality of Itaara, RS. The experiment was conducted in randomized blocks, with four replicates, in a factorial 5x2. Factor A consisting of five sowing seasons and factor C by two soybean cultivars. The meteorological observations concerning precipitation and temperature were obtained daily with the help of the automatic surface meteorological station. The cumulative precipitation in mm (PrecAcum), number of days without precipitation (NdSP), number of days with less than one mm (NdM1mm), number of days with precipitation between 1 and 25mm (Nd1-25mm), number of days with precipitation between 26 and 50mm (Nd26-50mm), number of days with precipitation between 51 and 75mm (Nd51-75mm) and referring to temperature were evaluated: mean temperature (NdTemp <15ºC), number of days with minimum temperatures above 15ºC (NdTemp>15ºC), number of days with minimum temperatures between 15-25ºC (NdT15-25ºC), number of days with minimum temperatures below 25ºC (NdTemp<25ºC), and, finally, the average relative humidity (URMédia). The main variable used was the date of the appearance of the first symptom, expressed in days after the emergency (AED). The periods used in the calculation of the meteorological variables were 5, 7, 8, 10, 11, 14 and 20 days prior to the appearance of the first symptom of the disease. Statistical analyzes were performed using Genes, Microsoft Office Excel and Minitab software. It was verified that the cultivars did not present expressive differences as the variables analyzed. The meteorological observations that included periods longer than 10 days were the ones that best characterized the beginning of the epidemic. The precipitation favored the anticipation of the symptoms directly and indirectly through Ndm1mm, Nd26-50mm and the average temperature was determinant in the 2016/17 crop, acting directly and indirectly on the main variable. The meteorological variables of greatest contribution to the appearance of the first symptom of P. pachyrhizi in the soybean crop, identified by the main components technique, were the number of days without precipitation, number of days with less than one mm, number of days with precipitation between 1 and 25mm and 26 and 50mm and number of days with a temperature between 15 and 25ºC.