ABSTRACT Careful implementation of a filtration system is essential for maintaining the operation of an irrigation system. Failure to maintain a filtration system can have a negative eff ect on irrigation pressure and uniformity. To avoid this problem, it is important to clean the filters, which can be done either manually or automatically. Predicting the correct time to clean the filters helps maintain the pressure and efficiency of the system. The aim of this study was to model backwash pressure as a function of water quality and the filter inlet pressure load using artificial neural networks. The characteristics of the water were determined using sensors to measure the pH (hydrogen potential), turbidity, total dissolved solids (TDS), and temperature. A pressure transducer was used to quantify the drop in pressure and the need to clean the filters. To predict the need for cleaning the irrigation filters, a hydraulic structure was constructed that included a screen filtration system with a mesh size of 120, cleaned by backwashing. The need for cleaning estimated by the multilayer perceptron feedforward artificial neural networks with 2-4-1 architecture performed well in modelling the temporal evolution of the pressure load in the screen filtration system (120 mesh), whereas adjusting the pressure load based on the water quality characteristics (pH, turbidity, total dissolved solids and temperature) performed poorly. uniformity problem automatically hydrogen potential, potential , potential) turbidity TDS, TDS (TDS) temperature 120 backwashing 241 2 4 1 2-4- (12 mesh, mesh) pH, (pH poorly (TDS 12 24 2-4 (1 2- (

ABSTRACT Knowledge of soil water dynamics is essential for establishing appropriate methods of irrigation management. Water dynamics in unsaturated soils is a complex process that can be explained by the Richards equation. As this is a non-linear differential equation, there is no analytical solution, but requires the use of the finite element method, for example, to obtain solutions, where simulations using numerical modelling make it possible to predict the the flow of water from the soil. As such, the aim of this study was to evaluate a 2D numerical model in simulating water distribution and wet bulb formation resulting from a subsurface irrigation system, in addition to validating the generated model. The Pearson correlation coefficient (r), the coefficient of determination (R2) and the root-mean-square error (RMSE) were calculated. For each treatment, both during and after irrigation, the model showed a small relative error, high values for R2 and a positive correlation with the field data. It was concluded that the model is applicable to the design and management of subsurface irrigation systems, varying the installation depth of the drip tube, the spacing between emitters and the soil moisture, giving good results for the various simulated scenarios. equation nonlinear non linear solution method example solutions such D system r, r , (r) R (R2 rootmeansquare root mean square RMSE (RMSE calculated treatment data systems tube moisture scenarios (r (R

Resumo As mudanças climáticas são uma ameaça para o setor agrícola. O objetivo do estudo foi avaliar a influência da temperatura e radiação ultravioleta (UV) no desenvolvimento in vitro de isolados de Trichoderma spp. Os experimentos foram conduzidos no Laboratório de Patologia Pós-Colheita, da Embrapa Agroindústria Tropical (Fortaleza - CE). Avaliou-se a influência da temperatura de incubação (30, 35 e 40 °C) no crescimento micelial, bem como na esporulação (conídios.mL-1) e na germinação (%) dos conídios dos isolados de Trichoderma spp. (T. asperellum - SF 04, Quality WG®; T. harzianum - IBLF 006, Ecotrich WP®; e T. harzianum ESALQ - 1306, Trichodermil 1306). Para a avaliação da influência da UV, as placas de Petri contendo os isolados fúngicos foram expostas à luz em diferentes intervalos de tempo (0, 2, 4, 6 e 8 minutos) e obteve-se a germinação relativa. O isolado mais sensível à temperatura foi T. asperellum (SF 04), no qual, a temperatura de 35 °C apresentou menor área de crescimento micelial e menor germinação relativa (38,4%). O isolado T. harzianum (ESALQ 1306) apresentou a menor porcentagem de conídios germinados a 30 °C (63%), porém, teve o maior número a 35 °C (100%). A radiação UV diminuiu a germinação dos conídios e os isolados que apresentaram maior germinação relativa ao final do período de exposição foi T. asperellum (SF 04) e T. harzianum (ESALQ 1306). Estes resultados podem demonstrar uma maior capacidade de adaptação do isolado T. harzianum (ESALQ 1306) às condições extremas de temperatura.

Abstract Climate change is a threat to the agricultural sector. The objective of this study was to evaluate the influence of temperature and ultraviolet radiation (UV) on the in vitro development of Trichoderma spp. The experiments were conducted at the Postharvest Pathology Laboratory, at Embrapa Agroindústria Tropical (Fortaleza - CE). It was evaluated the influence of the incubation temperature (30, 35 and 40 °C) on mycelial growth, as well as sporulation (conidia.mL-1) and germination (%) of the conidia of the Trichoderma spp. (T. asperellum - SF 04, Quality WG®; T. harzianum - IBLF 006, Ecotrich WP®; and T. harzianum ESALQ - 1306, Trichodermil 1306). To evaluate the influence of UV, the Petri dishes of the fungal strains were exposed to light at different time intervals (0, 2, 4, 6 and 8 minutes) and obtained relative germination. The most temperature sensitive strain was T. asperellum (SF 04), in which the temperature of 35 °C showed a lower area of mycelial growth and lower relative germination (38.4%). The T. harzianum strain (ESALQ 1306) presented the lowest percentage of conidia germinated at 30 °C (63%), but had the highest number at 35 °C (100%). The UV radiation decreased the germination of the conidia and the strains that had the highest germination relative to the end of the exposure period were T. asperellum (SF 04) and T. harzianum (ESALQ 1306). These results may demonstrate a higher adaptability of the T. harzianum strain (ESALQ 1306) to extreme temperature conditions.