Correlações de variáveis meteorológicas e ocorrência da Cigarrinha-do-milho na região noroeste do Rio Grande do Sul

Abstract

Corn (Zea mays L.) is the second most important agricultural crop in Brazil, playing a significant role in food production and product diversity. The Rio Grande do Sul state has been crucial in national corn production due to its favorable climatic conditions and extensive cultivable areas. However, the crop can be affected by various pests and diseases that impact grain quality and quantity, leading to losses and reduced yield. The corn leafhopper (Dalbulus maidis), an insect vector responsible for transmitting the stunting complex (pale stunting, red stunting, and maize rayado fino virus), has raised significant concerns, with its increasing population becoming a challenge for pest management in corn cultivation. This study aimed to evaluate the correlation between corn leafhopper populations and meteorological variables in two municipalities in the northwest region of Rio Grande do Sul, and to determine how variations in elements such as temperature, wind, rain, radiation, and relative humidity influence the population dynamics of this insect. Data from weekly monitoring using double-sided yellow adhesive traps (10 x 27 cm) were collected in two experimental areas of the CCGL TEC cooperative technical network, covering the period from June 6, 2021, to February 11, 2023. Daily data on rainfall, average, maximum, and minimum air temperature, daytime average air temperature (between 6 a.m. and 6 p.m.), nighttime average air temperature (between 6 p.m. and 6 a.m.), average relative humidity, incident solar radiation, and average wind speed were obtained every 30 minutes from meteorological stations at these two experimental units. Additionally, air temperature data were subjected to two nonlinear arthropod development models. The set of meteorological variables was correlated with corn leafhopper populations and their natural logarithm to reduce the effect of extreme peak values, using Pearson and Spearman correlations. Furthermore, Sigma Plot and Microsoft Excel software were used for data tabulation, significance testing of correlations, and graph creation. The results indicated that nighttime average temperatures above 26°C are positively correlated with the increase in corn leafhopper populations. This finding suggests that both daily and nighttime average temperatures are critical variables influencing the population dynamics of the corn leafhopper. Therefore, these variables may be essential for developing predictive tools and effective management strategies to control this insect's population, helping to mitigate negative impacts on corn yield.