The use of technology and planning in agricultural production is essential in Northeastern Brazil, which is the region of the country that most suffers from water shortage. For the best irrigation management, it is necessary to know the potential evapotranspiration rate for water control in order to increase productivity. There are several direct and indirect methods for estimating evapotranspiration, but the standard method recommended by the United Nations Agriculture Organization (FAO) is the Penman-Monteith (PETpm) method because it has higher accuracy than other methods. However, it is a difficult method to be used due to the need for a large number of meteorological elements. In this context, the objective of this study was to estimate potential evapotranspiration by the Penman-Monteith method in the micro-region of Baixo Parnaíba in Maranhão state using artificial neural networks. Agro-meteorological data were collected daily over 34 years, from 1984 to 2017, and these data were obtained from the NASA/POWER website. Subsequently, liquid radiation and potential evapotranspiration were calculated by the Penman-Monteith standard method (1998). To predict potential daily evapotranspiration, the Multi-Layer Perceptron (MLP) was chosen, which is a traditional Artificial Neural Network. The period that presented a higher evapotranspiration index was the same one that showed precipitation with a lower volume and higher temperatures. The artificial neural network model that best adapted to estimate PETpm was MLP 2-5-1. It is concluded that artificial neural networks estimate with accuracy and precision the Penman-Monteith daily potential evapotranspiration of the Lower Parnaiba in Maranhão, and potential evapotranspiration can be estimated by the Penman-Monteith method using neural networks with inputs of air temperatures.

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Ao longo do processo de produção de hortaliças, há diversos riscos de contaminação suscetíveis às culturas. O objetivo dessa pesquisa foi analisar as técnicas de produção de hortaliças e os riscos ocupacionais aos quais podem estar expostos os agricultores da Comunidade Kolping, de Chapadinha (MA) (COKC). Esta pesquisa baseia-se em um estudo de caso, em que os dados foram coletados através de aplicação de questionários e interpretados por estatística descritiva. De acordo com as informações levantadas, a comunidade é constituída, predominantemente, por mulheres, que correspondem a 89% dos entrevistados. No que tange ao sistema de produção, é caracterizado como de baixa produtividade, sem uso de tecnologias. A análise e caracterização do sistema de produção adotado pelos agricultores da COKC permitiram compreender que a eficiência da atividade agrícola dos membros é comprometida em função de fatores limitantes, como gestão da produção ineficiente, ausência de articulação e falta de assistência técnica. Nesse sentido, as recomendações sugeridas aos membros da COKC se pautaram na valorização do trabalho em equipe e na adoção de boas práticas agrícolas.

The objective of this work was to analyze the effects of different organic substrates, fertigated with effluents from biodigesters in the production of coriander. The experiment was carried out in a greenhouse, greenhouse type. It was used a completely randomized design, with three replications, in a 2x2x2 factorial arrangement, being: cultivars (king and tabocas); substrates (natural, fermented) and source of irrigation (water, biofertilizer). The size of the plants were evaluated; number of stems and yield of green mass. No significant effect was observed between the organic substrates and the coriander cultivars for any of the analyzed variables, however, regarding the irrigation source, statistical significance was observed for the variables plant size and green mass yield, and the best means were obtained when the plan ts were irrigated with water. It is concluded that organic substrates and coriander cultivars studied are recommended for cultivation. However, the use of concentrated biofertilizers did not increase coriander production, and more research is needed to recommend the best doses of this biofertilizer.