Coffee pest severity by agrometeorological models in subtropical climate.

This study aimed to estimate the number of generations and cycle duration of the southern red mite, coffee berry borer, and coffee leaf miner using the thermal index to assist in controlling these main coffee pests in the state of Paraná, Brazil. The data of maximum and minimum air temperature (°C) and precipitation (mm) of all municipalities in the state from 1984 to 2018 were collected from the National Aeronautics and Space Administration/Prediction of Worldwide Energy Resources (NASA/POWER). The reference evapotranspiration was estimated using the (Camargo Campinas IAC Boletim 116:9, 1971) method and the water balance was calculated using the method of ( Thornthwaite C, Mather J (1955) The water balance publications in climatology, 8 (1). DIT, Laboratory of climatology, Centerton, NJ, USA). The basal temperature of each pest minus the average temperature of the years was used to calculate the degrees-day, the duration of the pest cycle, and the number of generations per year. The influence of altitude on the development of coffee pests was measured using the Pearson correlation. The thermal index is able to estimate the damage caused by coffee pests in the state of Pará, Brazil. Coffee pests show greater severity in the north of Paraná, in the regions with the highest temperatures. It is the same region that concentrates most of the coffee production of the state. The results of the life cycle and number of generations were interpolated for the entire state using the kriging method. Coffee pests showed the highest severity in the north region of the state of Paraná, more specifically in the Northwest, North Central, and West Central mesoregions. These regions have concentrated most of the state's coffee production. Mesoregions with the highest coffee production in the state showed higher susceptibility to coffee pests. Altitude showed a high correlation (r > 0.6) with the cycle variability and number of generations of coffee pests. The average cycles of the coffee berry borer, coffee leaf miner, and southern red mite are 24.13 (± 8.34), 45.64 (± 18.61), and 21.51 (± 3.51) days, respectively. The average annual generation was 16.67 (± 4.77), 9.02 (± 2.75), and 17.32 (± 2.63) generations, for the coffee berry borer, the coffee red mite, and the southern red mite, respectively.

Bioclimatic zoning for dairy cows in Brazil by statistical modeling.

BACKGROUND: Climate conditions affect animal welfare directly, influencing milk production. The Midwest region is the largest cattle-producing region in Brazil. The objective of this study was to elaborate on bioclimatic zoning for dairy cattle in the Midwest region of Brazil. Air temperature (Ta, °C) and relative humidity (%, RH) data from a 30-year historical series (1989-2019) collected by the National Aeronautics and Space Administration/Prediction of Worldwide Energy Resources (NASA/POWER) platform were used. The Temperature and Humidity Index (THI) was determined for the hottest and coldest months. Milk production losses due to climate factors in the Midwest of Brazil for two daily production levels, 10 kg Milk (PL10) and 25 kg Milk (PL25), were estimated. RESULTS: The Midwest presented three THI classifications throughout the year: 'normal', 'alert', and 'critical alert'. The entire Midwest region was classified as 'normal' (THI < 70) between autumn and winter. The decrease in milk production (DMP) during the autumn and winter presented no loss for both production levels (PL10 and PL25). CONCLUSION: On the other hand, a 1 to 2 kg reduction in milk production was observed for cows with a PL25 production level between spring and summer in the southern Midwest region, while cows with a PL10 production level showed no reduction in milk production. Only the cities of Sinop and Cuiabá did not present a 'critical alert' during spring/summer for the risk of heat stress. © 2021 Society of Chemical Industry.

Climate risk to peanut cultivation in Brazil across different planting seasons.

BACKGROUND: Peanuts are widely grown in Brazil because of their great importance in the domestic vegetable oil industry and the succession of sugarcane, soybean and maize crops, contributing to soil conservation and improvement in agricultural areas. Thus, the present study aimed to determine the zoning of peanuts' climatic risk by estimating the water requirement satisfaction index (WRSI) for the crop in Brazil. We used a historical series of data on average air temperature and rainfall between 1980 and 2016. Reference evapotranspiration was estimated using the method of Thornthwaite, and we subsequently calculated crop evapotranspiration and maximum evapotranspiration. Water balances for all stations were calculated using the method of Thornthwaite and Mather, with an available water capacity in the soil of 15, 30 and 45 mm. The definitions of suitable, unfit and restricted areas and the planting season were performed using the WRSI. RESULTS: Brazil has low climatic risk areas for growing peanuts throughout the year, except for winter. The country reveals that 88.19%, 97.93%, 99.16% and 39.25% of its area is suitable for planting peanuts on planting dates in spring, summer, autumn and winter, respectively. CONCLUSION: Brazil has a large part of the areas favorable to the planting of peanuts. The maximum availability of soil water at a depth of 15, 30 and 45 mm does not influence regions with respect to peanut growing in Brazil. The states of Piauí, Ceará and Bahia are the most unsuitable on the winter planting date, with an average WRSI of 0.22. © 2021 Society of Chemical Industry.

Neural networks in spatialization of meteorological elements and their application in the climatic agricultural zoning of bamboo.

Bamboo has an important role in international commerce due to its diverse uses, but few studies have been conducted to evaluate its climatic adaptability. Thus, the objective of this study was to construct an agricultural zoning for climate risk (ZARC) for bamboo using meteorological elements spatialized by neural networks. Climate data included air temperature (TAIR, °C) and rainfall (P) from 4947 meteorological stations in Brazil from the years 1950 to 2016. Regions were considered climatically apt for bamboo cultivation when TAIR varied between 18 and 35 °C, and P was between 500 and 2800 mm year-1, or PWINTER was between 90 and 180 mm year-1. The remainder of the areas was considered marginal or inapt for bamboo cultivation. A multilayer perceptron (MLP) neural network with a multilayered "backpropagation" training algorithm was used to spatialize the territorial variability of each climatic element for the whole area of Brazil. Using the overlapping of the TAIR, P, and PWINTER maps prepared by MLP, and the established climatic criteria of bamboo, we established the agricultural zoning for bamboo. Brazil demonstrates high seasonal climatic variability with TAIR varying between 14 and 30 °C, and P varying between < 400 and 4000 mm year-1. The ZARC showed that 87% of Brazil is climatically apt for bamboo cultivation. The states that were classified as apt in 100% of their territories were Mato Grosso do Sul, Goiás, Tocantins, Rio de Janeiro, Espírito Santo, Sergipe, Alagoas, Ceará, Piauí, Maranhão, Rondônia, and Acre. The regions that have restrictions due to low TAIR represent just 11% of Brazilian territory. This agroclimatic zoning allowed for the classification of regions based on aptitude of climate for bamboo cultivation and showed that 71% of the total national territory is considered to be apt for bamboo cultivation. The regions that have restrictions are part of southern Brazil due to low values of TAIR and portions of the northern region that have high levels of P which is favorable for the development of diseases.