ABSTRACT
Due to the worldwide water supply crisis, sustainable strategies are required for a better use of this resource. The use of magnetic water has been shown to have potential for improving irrigation efficacy. However, a lack of modelling methods that correspond to the experimental results and minimize error is observed. This study aimed to estimate the replacement rates of magnetic water provided by irrigation for lettuce production using a mathematical model based on fuzzy logic and to compare multiple polynomial regression analysis and the fuzzy model. A greenhouse study was conducted with lettuce using two types of water, magnetic water (MW) and conventional water (CW), and five irrigation levels (25, 50, 75, 100 and 125%) of crop evapotranspiration. Plant samples for biometric lettuce were taken at 14, 21, 28 and 35 days after transplanting. The data were analyzed via multiple polynomial regression and fuzzy mathematical modeling, followed by an inference of the models and a comparison between the methods. The highest biometric values for lettuce were observed when irrigated with MW during the different phenological stage evaluated. The fuzzy model provided a more exact adjustment when compared to the multiple polynomial regressions.
ABSTRACT
The tomato crop is very sensitive to stress conditions. A water deficit is defined as when precipitation is less than the evapotranspiration (ETc) of the crop in a given period, and in this scenario of climate change, it is identified as responsible for global productivity losses. The use of potential technologies for better irrigation management, such as electromagnetically treated water, remains controversial. Thus, the objective of the present work was to investigate the effects of very low-frequency electromagnetic resonance field treatment on water for tomato crops submitted to different irrigation rates. For this, an experiment was carried out under controlled conditions with different types of water: electromagnetically treated water (WTVLF) and untreated water (UNW), as well as four water replacement rates: 40, 60, 80, and 100% ETc. The electromagnetic treatment of the water was carried out using the commercial equipment AQUA4D®. The experiment was carried out in pots with five replications per treatment. Lower activity of SOD, POD, CAT, and APX enzymes was observed in plants irrigated with water treated with very low-frequency electromagnetic resonance fields (WTVLF), indicating less oxidative stress caused by water deficit. Water deficit reduced chlorophyll content, but the effects were less harmful with WTVLF water. The water deficit resulted in less accumulation of dry matter and less productivity in a linear relationship. However, plants irrigated with WTVLF showed increments of about 20% in dry matter accumulation and 20% in fruit production concerning plants irrigated with untreated water, independent of the irrigation rates. We can conclude that irrigation with WTVLF can be a solution to reduce the damage caused by water deficits and increase the productivity of tomato crops.
ABSTRACT
This study aimed to develop a fuzzy mathematical model to estimate the impacts of global warming on the vitality of Laelia purpurata growing in different Brazilian environmental conditions. In order to develop the mathematical model was considered as intrinsic factors the parameters: temperature, humidity and shade conditions to determine the vitality of plants. Fuzzy model results could accurately predict the optimal conditions for cultivation of Laelia purpurata in several sites of Brazil. Based on fuzzy model results, we found that higher temperatures and lacking of properly shading can reduce the vitality of orchids. Fuzzy mathematical model could precisely detect the effect of higher temperatures causing damages on vitality of plants as a consequence of global warming.