Fuzzy Modeling Development for Lettuce Plants Irrigated with Magnetically Treated Water.

Autor: Ferrari Putti F; School of Science and Engineering, São Paulo State University (UNESP), Tupã 01049-010, SP, Brazil., Cremasco CP; School of Science and Engineering, São Paulo State University (UNESP), Tupã 01049-010, SP, Brazil., Neto AB; School of Science and Engineering, São Paulo State University (UNESP), Tupã 01049-010, SP, Brazil., Barbosa ACK; Department of Civil Engineering, Ponta Grossa State University (UEPG), Ponta Grossa 84010-330, PR, Brazil., Júnior JFDS; Department of Agronomy, Federal University of Triângulo Mineiro (UFMT), Iturama 38280-000, MG, Brazil., Reis ARD; School of Science and Engineering, São Paulo State University (UNESP), Tupã 01049-010, SP, Brazil., Góes BC; Department for Business, Adamantina College of Technology (FATEC), Adamantina 17800-000, SP, Brazil., Arruda B; School of Science and Engineering, São Paulo State University (UNESP), Tupã 01049-010, SP, Brazil., Filho LRAG; School of Science and Engineering, São Paulo State University (UNESP), Tupã 01049-010, SP, Brazil.
Jazyk: angličtina
Zdroj: Plants (Basel, Switzerland) [Plants (Basel)] 2023 Nov 09; Vol. 12 (22). Date of Electronic Publication: 2023 Nov 09.
DOI: 10.3390/plants12223811
Abstrakt: 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.
Databáze: MEDLINE