Energy is currently one of the main production costs in irrigated agriculture and its cost must always be considered in irrigation projects. In regions such as the Brazilian Cerrado, where there is a continuous growth of irrigated agriculture, it is important to evaluate technologies that can increase the efficiency and viability of irrigation. Precision irrigation has great potential to increase the economic return on rural properties with a reduction in electricity consumption. The present work aimed to evaluate the increased profitability and energy savings potential of the soybean crop using precision irrigation with a center pivot. To evaluate the potential benefits of precision irrigation (PI), irrigation demand was simulated through modeling. The irrigation computer model was developed in Python language. The study was carried out in the area of two center pivots with soils with different hydro-physical characteristics. Soil available water capacity (AWC) was calculated based on field capacity, permanent wilting point and bulk density data. The irrigation management under homogeneous soil conditions was carried out considering the lowest, the average, and the highest AWC value. The management under variable conditions was carried out individually for each pixel, considering the real AWC value of the pixel. Also, four sowing dates of the soybean crop were considered in a rainy year and a dry year. The results indicated an average energy savings potential (ESP) of 5.0% in the rainy year and 4.5% in the dry year. The average potential for increasing profitability (IPP) was 20.4% in the rainy year and 12.5% in the dry year. The use of PI can reach ESPs of up to 25.3% and IPPs of up to 106.2%. The benefits documented here are an important step towards the development of precision irrigation as an efficient irrigation management strategy.

能源目前是灌溉农业的主要生产成本之一，在灌溉项目中必须始终考虑其成本。在巴西塞拉多等灌溉农业持续增长的地区，评估能够提高灌溉效率和可行性的技术非常重要。精准灌溉在减少用电量的同时增加农村财产的经济回报的潜力巨大。目前的工作旨在评估增加的盈利能力使用带中心枢轴的精密灌溉技术，提高大豆作物的节能潜力。为了评估精准灌溉 (PI) 的潜在效益，通过建模模拟了灌溉需求。灌溉计算机模型是用 Python 语言开发的。该研究是在两个具有不同水物理特性的土壤的中心支点区域进行的。根据田间持水量、永久萎蔫点和容重数据计算土壤有效水分容量（AWC）。均质土壤条件下的灌溉管理考虑了最低、平均和最高的AWC值。考虑到像素的实际AWC值，对每个像素单独进行可变条件下的管理。还有四大豆作物的播种期分为雨年和旱年。结果表明，雨年的平均节能潜力 (ESP) 为 5.0%，旱年为 4.5%。增加盈利能力 (IPP) 的平均潜力在雨年为 20.4%，在旱年为 12.5%。PI 的使用可以达到高达 25.3% 的 ESP 和高达 106.2% 的 IPP。此处记录的好处是朝着将精准灌溉发展为一种有效的灌溉管理策略迈出的重要一步。