Increasing the efficiency of solar dryers with ensuring that the system remains accessible to all users can be achieved with their automation through low-cost and easy-to-use technique sensors. The objective was to develop, implement and evaluate an automatic system for monitoring drying parameters in a hybrid solar-electric dryer (HSED). Initially, an automated data acquisition system for collecting the parameters of sample mass, air temperature, and relative air humidity was developed and installed. The automatic mass data acquisition system was calibrated in the hybrid solar-electric dryer. The automated system was validated by comparing it with conventional devices for measuring the parameters under study. The data obtained were subjected to analysis of variance, Tukey test and linear regression at p ≤ 0.05. The system to turn on/off the exhaust worked efficiently, helping to reduce the errors related to the mass measurement. The GERAR Mobile App showed easy to be used since it has intuitive icons and compatibility with the most used operating systems for mobile devices. The responses in communication via Bluetooth were fast. The use of Arduino, a low-cost microcontroller, to automate the monitoring activity allowed estimating the mass of the product and collecting the drying air temperature and relative air humidity data through the DHT22. This sensor showed a good correlation of mass and air temperature readings between the automatic and conventional system, but low correlation for relative air humidity. In general, the automatic data acquisition system monitored in real time the parameters for drying agricultural products in the HSED.

The clogging dynamics of pressure-compensating drippers is still poorly addressed, and its understanding is quite important to control clogging. The aim of this study was to evaluate the flow performance of pressure-compensating drippers under clogging effect. Eight pressure-compensating emitters, model J-SC Jain PC-PLUS with nominal flow rate of 2.2 L h^-1 were evaluated. The tests were run for 8 h d^-1 for 4 weeks, a total of 160 h. Every 40 h, the concentration and granulometry of suspended particles were increased, by adding 125 mg L^-1 of solids, composed of sand. The flow rate of the emitters was determined using a weight measurement system. Flow rate variations of the emitters did not follow a defined pattern. Clogging seems to occur randomly and abruptly. Sometimes the flow rate exceeded the nominal value (maximum relative flow rate of 182%) and other times it was lower than the nominal value (minimum relative flow rate of 0%).

The increase in the demand for seedlings of native tree species makes it important to determine their water and light requirements, which are important factors in their production, in terms of costs and time. Water use and productivity in the growth of seedlings of Dalbergia nigra (Vell.) Allemão ex Benth., Apuleia leiocarpa (Vogel) J.F. Macbr and Hymenaea courbaril L. were determined under four light levels (three shading levels and control), using a randomized block design with four replicates. Height, stem diameter, leaf area and biomass, as well as Dickson quality index (DQI) were evaluated. The seedlings were transplanted into 280-cm3 plugs, filled with substrate composed of pure biosolids, and irrigated by a drip system with automatic management. The highest total volumes applied were 3.1 L per D. nigra seedling (in 37 and 58% shading), 2.5 L per A. leiocarpa seedling (in 37% shading) and 3.8 L per H. courbaril seedling (in full sun). Growth indices, confirmed by the DQI, indicate that shading levels of 37 and 58% for D. nigra, 37% for A. leiocarpa, and full sun for H. courbaril are the most recommended. The highest volumes of irrigation promoted the greatest development of the species, in general for intermediate shading, which provided the highest values of DQI and irrigation water productivity.

Soil erosion studies using rainfall simulators are generally expensive and time consuming. Thus, the aim of this study was to develop a prototype of an automatic runoff collector, capable of real-time quantifying runoff volume and soil loss in field trials using a rainfall simulator. The used sensors were chosen based on the type A uncertainty computed from different volumes of water and concentrations of sediment. Through specific programming, the runoff volume, sediment concentrations and the time of occurrence of the collections corresponding to each 200 cm³ of runoff were recorded on a micro-SD card. The robustness of the calibration and the programming developed were also evaluated in the Arduino Mega® 2560 microcontroller. The pressure (PSI.420) and turbidity (ST100) sensors were selected for developing the prototype, which was evaluated in the field with the InfiAsper rainfall simulator. Then, the data collected automatically by the sensors were compared to those obtained by manual measurement. The automatic runoff collector equipped with the PSI.420 and ST100 sensors has potential to obtain and store runoff data, and it was effective in evaluating the erosion process, generating mean errors of 12.25 and 13.16% for runoff volume and soil loss, respectively. The proposed prototype has a low cost of manufacture, in addition to optimizing the collection of erosion data in studies with rainfall simulators.

Sensibilidade dos microtubos à obstrução por agentes físicos - DOI: 10.7127/rbai.v9n400310