Understanding the green dwarf coconut palm development is essential to improve its management. This study aimed to characterize and understand the seasonality of the green dwarf coconut palm development and yield under rainfed and irrigated conditions in the northeastern region of the Pará state, Brazil. The longitudinal and transverse diameters, fruit mass and yield, in addition to the number of live leaves, live bunches, fruits of the bunches nº 11 and 14 and female fowers were monitored. The coconuts between the bunches nº 20 and 22 showed larger dimensions and biomass (fresh and dry). The partition of the production components varies according to the time of the year, with the liquid albumen mass, which is a component of greater commercial focus, being higher in the rainy season, with lower percentage losses in the irrigated cultivation. The meteorological seasonality plays a key role in fower dropping and fruit abortion, directly contributing to the amount of produced fruits.

Cowpeas are of high socioeconomic importance in the North and Northeast regions of Brazil, whereby the search for alternatives that offer increased productivity with financial returns has become an important challenge. Thus, the objective of this study was to estimate and evaluate the economic indicators of cowpea production in 2015 and 2016 when applying drip irrigation to different depths. Irrigation treatments were based on crop evapotranspiration (ETc). The experiment was laid in a randomized complete blocks design with four treatments (0, 25, 50, and 100% ETc) and six replications. For economic analysis, the results were extrapolated to an area of one hectare. Productivity in 2015 was lower than that in 2016; however, in all treatments, it was always higher when plants were grown under adequate water supply. In both years, the total operating costs were higher under irrigation than under rainfed conditions. The 100% ETc treatment resulted in a greater number of cowpea bags (60 kg) produced and a higher gross revenue than the rainfed treatment by 17 bags ha-1, equivalent to 1,020 kg ha-1 (gross revenue US$ 711.48) and 16 bags ha-1, equivalent to 960 kg ha-1 (gross revenue US$ 867.12), in 2015 and 2016, respectively. Water deficit limited cowpea yield in both years but made cultivation economically unfeasible only in 2015.

Inadequate management of the irrigation system has compromised yield and favoured the degradation and waste of water resources. To ensure efficient irrigation management, providing yield increases, sustainability in the use of water resources and reduction of production costs, studies about the water demand of coconut palms are needed. The objective of this study was to determine the energy partition, crop evapotranspiration (ET_c), and the simple crop coefficients (K_c) of the green dwarf coconut palms in Santa Izabel do Pará, Pará, Brazil. The experiment was carried out in a coconut plantation at Reunidas Sococo Farm, with an area of approximately 7 ha in a triangular spacing of 7.5 × 7.5 m, during 2020 and 2021. The ETc was determined by the Bowen ratio method, with measurements of temperature and relative humidity at two levels above the crop canopy and reference evapotranspiration (ET_o) by the FAO Penman-Monteith method, using data from the National Institute of Meteorology. The K_c was determined by the ratio between ETc and ETo. The total water demand of the coconut palm was 489 (2020) and 480 mm (2021), with a daily average of 4.21 (2020) and 4.14 mm (2021) for the dry season. The mean value of K_c was 1.06 (± 0.12). Evapotranspiration was driven mainly by energy availability, associated with a control of atmospheric demand on K_c values, suggesting a possible influence of coconut trees on Kc values even under good water availability and small variability in vegetation cover.

The growing demand for coconut water has led to the expansion of irrigated green dwarf coconut cultivation; however, the inefficient use of water has contributed to the degradation and waste of water resources, making fundamental studies aiming to optimize the use of water. The objective of this study was to determine the physical productivity and water productivity of green dwarf coconut palms under the climatic conditions of Santa Izabel do Pará, eastern Amazonia, Brazil. The experiment was carried out from 2020 to 2021, in a green dwarf coconut plantation spaced 7.5 m x 7.5 m in a triangle, at Fazenda Reunidas Sococo, with an area of approximately 7 ha. Water productivity (WP) was determined both in terms of fruit production (WP_f) and coconut water production (WP_ca), through the relationship of fruit productivity (fruit biomass and water volume) with accumulated evapotranspiration. The dwarf coconut tree presented a total production of 105 and 186 fruits plant^-1 and 37 and 62 L plant^-1 of coconut water in the years 2020 and 2021. The largest volumes of water and the highest weights occurred during the wettest season. WP_f was of 1.87 fruits m^-3 (2020) and 2.94 fruits m^-3 (2021) and WP_ca 0.66 L m^-3 (2020) and 0.98 L m^-3 (2021).

The culture of açaí (Euterpe oleraceae M.), originating from floodplain areas, was planted on dry land in many properties in Pará, Brazil, making necessary the use of irrigation. To irrigate adequately with less waste, it is necessary that studies aim at increasing efficiency in the use of water in this sector, and one of the ways to do so is to estimate evapotranspiration (ET). The objective of this study was to estimate the actual daily evapotranspiration using the Surface Energy Balance Algorithm for Land (SEBAL) in eastern Amazonia. Six images from the Landsat 8 satellite were used, and the estimates of evapotranspiration with the SEBAL algorithm showed good agreement with the results obtained by the Bowen ratio method in the area of açaí planting, including the mean absolute error (MAE), mean relative error (MRE), root of mean square error (RMSE), and the concordance index (d index) equal to 0.45 mm day⁻¹, 4.23%, 0.52 mm day⁻¹, and 0.80, respectively. SEBAL showed the ability to distinguish the soil cover, demonstrating the sensitivity of the model, which provided the mapping of the components analyzed. The use of the algorithm helps in decision making regarding irrigation management and reducing costs and water losses.