ABSTRACT A common scenario in the developing countries is the low income and less education of producers. Thus, the tools used for irrigation management must be cheap and easy to handle. In this work, an autonomous and low-cost network of micro-weather stations has been developed for irrigation management. Simulations were performed to evaluate the ability of intelligent systems to compute evapotranspiration with noisy and insufficient data. The network of micro-weather stations was then applied to autonomous irrigation management of a crop of bell peppers. Statistical analysis was performed on data from the developed system and a standard weather station. The results show no statistical difference between the values of evapotranspiration calculated with data from these two sources. The developed system performed with a coefficient of determination of 0.968, mean absolute error of 0.055 mm day−1, and root mean square error of 0.063 mm day−1. The study shows that low-cost intelligent systems can be used as viable tools for efficient irrigation management.

RESUMO Conhecer a umidade de solo disponível para as plantas é preponderante para o manejo adequado do uso da água nas propriedades agrícolas, sendo os métodos automatizados os mais precisos. Entretanto, os custos de aquisição são elevados e a maioria dos controladores de irrigação ainda trabalha com tempos pré-definidos. Assim, o estudo teve por objetivo desenvolver e calibrar um tensiômetro automatizado de baixo custo e alta eficiência no controle da irrigação, baseado em monitoramento em tempo real. A pesquisa foi conduzida nos Laboratórios de Hidráulica e Relação Água-Solo-Planta-Atmosfera pertencentes à Universidade Federal da Grande Dourados (UFGD), em Dourados, MS, com solo classificado como Oxisol. Foram utilizados transdutores de pressão e um microcrontrolador capazes de assimilar a pressão no interior dos tensiômetros e transformá-la em leituras de potencial matricial de água no solo - Ψm. Desta forma, realizou-se a calibração comparando as diferentes leituras do transdutor e do tensímetro digital de agulha. Foram aplicadas diferentes tensões para obtenção da curva de umidade do solo, partindo do ponto mais úmido (saturado) para o mais seco (solo seco em estufa), coletando 20 pontos válidos. Posteriormente, os dados foram submetidos ao teste de normalidade, com posterior análise estatística e modelos de curva de regressão. Foram verificados ajustes lineares com altos valores de coeficiente de determinação (R2 = 0,99), sendo o sistema automatizado construído, capaz de monitorar a tensão de água do solo em tempo real.

ABSTRACT Knowing the soil moisture available to plants is important for adequate management of water use in agricultural farms, with automated methods being the most accurate. However, acquisition costs are high and most of the commercially available irrigation controllers still work using pre-set times. This study aimed to develop and calibrate a low-cost automated tensiometer with high efficiency in irrigation control, based on real-time monitoring. The research was conducted at the Laboratories of Hydraulics and of Water Soil Plant and Atmosphere Relationship, which belong to the Federal University of Grande Dourados (UFGD), in Dourados, MS, Brazil, with soil classified as an Oxisol. Pressure transducers and a microcontroller were used to assimilate the pressure inside tensiometers and transform it into readings of soil water matric potential (Ψm). Thus, the calibration was carried out by comparing the different readings of the transducer and digital tension meter. Different tensions were applied to obtain a soil moisture curve, starting from the most humid point (saturated) to the driest one (oven-dried soil), collecting 20 valid points. Subsequently, the data were subjected to the normality test, with subsequent statistical analysis and regression curve models. Linear adjustments with a high coefficient of determination (R2 = 0.99) were observed, with the automated system built in this study being capable of monitoring soil water tension in real-time.