AGROMETEOROLOGICAL DYNAMICS IN GREEN DWARF COCONUT AGROECOSYSTEM IN IRRIGATED AND NON-IRRIGATED SYSTEM IN THE EASTERN AMAZON
: Cocos nucifera L. Seasonality. Tropical fruit growing.
The cultivation of coconut palms is becoming increasingly important in Amazonian fruit growing, making the north of Brazil one of the largest producing regions in the country. The dwarf coconut tree is highly sensitive to weather conditions, which requires a good understanding of the effects of the atmosphere on this species. Given this need and the scarcity of information of this type, the objective of this study was to characterize and understand the agrometeorological dynamics associated with the cultivation of the dwarf green coconut palm in consortium with the tropical cover crop kudzu, under irrigated and non-irrigated conditions, in the microclimatic conditions of Santa Izabel do Pará, in the eastern part of the Brazilian Amazon. The experiment was carried out in a commercial area of green dwarf coconut palms in the municipality of Santa Izabel do Pará, Pará, Brazil, with one area irrigated and the other rainfed, following the farm pattern. A micrometeorological tower was installed in each experimental area to obtain information on the variables air and soil temperature, relative humidity, soil moisture, global radiation, radiation balance, photosynthetically active radiation, wind speed and direction, soil heat flux and precipitation. At the same time, plant growth and development variables were measured, such as number of leaves, flowers, bunches and fruits, fresh and dry fruit biomass, production, leaf area index, among others. In general, it was observed that climatic seasonality affects important crop variables such as fruit and water mass and the length of the commercial cycle. Irrigated cultivation stands out as a stabilizing factor for seasonal losses due to reduced water availability and the homogeneous spatial distribution of the radiation balance. In this sense, the information obtained so far already covers key points for crop management, providing essential data for maximizing production and agricultural planning.