Fruit growing, especially in family farming, has a significant income potential in small areas, but climate change is a major challenge. This study aimed to quantify the irrigation requirements for citrus, papaya, mango and passion fruit, in the Vão do Paranã region, Goiás state, Brazil. The climate data encompassed the observed periods from 1961 to 2020 and future scenarios from 2021 to 2100. The irrigation demand was obtained from the daily water balance, while the reference evapotranspiration (ETo) was estimated using the Penman-Monteith method and then compared with an artificial intelligence tool. The future scenarios indicated a higher increase for air temperature and a lower increase for rainfall. The ETo levels raised from 1,528 mm year¹, in 1991-2020, to 1,614-1,656 mm year¹, in 2021-2050. The artificial intelligence performance was limited in the ETo estimation, with a mean absolute error of 0.71 mm day⁻¹ and an “r” value of 0.59, when considering the air temperature as the input variable. For the 2021-2050 period, when compared with 1991-2020, there was an increase in irrigation demand, in which, under the extreme scenario, the citrus demand reached 690 mm year⁻¹ (+11 %); papaya (+10 %) and passion fruit (+5 %) surpassed 800 mm year⁻¹; and mango reached 491 mm year⁻¹ (+14 %). An increase in demand for irrigation was observed, with management alternatives in association with strategies for maximum cultivation area based on water supply being recommended.

The Brazilian savanna, South America’s second-largest biome, is vital to Brazil’s economy but has suffered from environmental degradation due to unregulated agricultural and urban expansion. This study assesses climate change in the biome from 1961 to 2021 using the Köppen climate classification, drought indices, historical trend analyses, and the climatological water balance. Fourteen municipalities across the biome were analyzed. According to the Köppen classification, most municipalities were identified as Aw (tropical with dry winters) and Am (tropical monsoon), with Dourados, MS, and Sapezal, MT, alternating between Am and Aw. The standardized precipitation index (SPI) revealed changes in rainfall distribution. The Mann–Kendall test detected rising air temperatures in 13 of the 14 municipalities, with Sen’s slope ranging from 0.0156 to 0.0605 °C per year. Rainfall decreased in seven municipalities, with decreases from −4.54 to −12.77 mm per year. The climatological water balance supported the observed decrease in precipitation. The results indicated a clear warming trend and declining rainfall in most of the Brazilian savanna, highlighting potential challenges for water availability in the face of ongoing climate change.

Although the beneficial effects of silicon on plant resistance to biotic and abiotic stresses are recognized, there is a lack of knowledge regarding its application in field conditions and its direct impact on physiological metabolism, root development, and, most importantly, the economic return of corn production in tropical regions. This study is justified by the need to quantify the effects of foliar silicon application on these variables, providing a scientific and economic basis for optimizing corn productivity and profitability in tropical environments. The objective of this study was to evaluate the effect of silicon on physiological metabolism, root system development, grain yield, and the potential economic return of maize production in a tropical region. The study was conducted under field conditions in two growing seasons (2020 and 2021), using a randomized block design in a 2 × 5 factorial arrangement with four replications. The first factor consisted of the maize growing seasons, and the second factor was foliar silicon fertilization (0 (control), 150, 300, 450, and 600 g ha⁻¹). Foliar fertilization with silicon at a dose of 150 g ha⁻¹ increases transpiration rate by up to 9%, net photosynthetic rate by 13%, and grain yield of maize by 10% after two growing seasons, regardless of the water deficit experienced during the crop cycle. At this dose, silicon application is economically viable, yielding the highest differential profit (USD 97.11 ha⁻¹). In conclusion, foliar fertilization with silicon is an agronomically and economically viable strategy for efficient maize grain production during the second growing season in tropical regions.

Crop management strategies are essential to achieve maximum crop yields. In this context, crop models can be used to understand yield variability. The aim of this study was to evaluate historical yields based on the sowing date and plant density. Field experiments were conducted during two growing seasons at two locations using a maturity group 7.6 cultivar, with distinct sowing dates and plant densities (10 to 50 plants m⁻²). After calibration, the model was applied to historical weather data (1990–2022) for nine locations across the Cerrado biome. The CSM-CROPGRO-Soybean model simulated soybean development with biases for physiological maturity of +8 and −7 days for calibration and evaluation, respectively. The relative root mean square error for yield was below 14%. Similar trends were observed for the leaf area index (LAI) across plant densities, while biomass partitioning proved to be a limiting component, mainly for stem biomass. The optimal plant population ranged from 20 to 30 plants m⁻², whereas a low density (10 plants m⁻²) resulted in higher yield losses under late sowing. Therefore, the use of crop simulation models is an effective tool to understand and optimize sowing dates and plant densities under historical climatic conditions in the Cerrado.