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Authors: Fernando F. Putti 1 ; Luís Roberto Almeida Gabriel Filho 1 ; Camila Pires Cremasco 1 and Antonio Evaldo Klar 2

Affiliations: 1 FCA, UNESP – Univ. Estadual Paulista, CET, UNESP – Univ. Estadual Paulista and Campus of Tupa, Brazil ; 2 CET, UNESP – Univ. Estadual Paulista and Campus of Tupa, Brazil

Keyword(s): Growth, Water Stress, Foggy, Uncertain, Precision, Curves.

Related Ontology Subjects/Areas/Topics: Artificial Intelligence ; Biomedical Engineering ; Biomedical Signal Processing ; Computational Intelligence ; Computer-Supported Education ; Domain Applications and Case Studies ; Fuzzy Systems ; Health Engineering and Technology Applications ; Human-Computer Interaction ; Industrial, Financial and Medical Applications ; Methodologies and Methods ; Neural Networks ; Neurocomputing ; Neurotechnology, Electronics and Informatics ; Pattern Recognition ; Physiological Computing Systems ; Sensor Networks ; Signal Processing ; Soft Computing ; Theory and Methods

Abstract: In the wake of the worldwide water supply crisis, several methods are being used to optimize the use of water, mainly in agriculture, which is the main consuming factor. Magnetically treated water for agriculture is beneficent due to an increase in quality and productivity. Current assay evaluates the effects of magnetically treated water in lettuce cultivations throughout its cycle and determines the intermediate rates by fuzzy models submitted at different reposition rates and assessed throughout the cycles. The assay was conducted in randomized blocks with a 4 x 5 factor scheme, with 5 reposition laminas and 4 dates after transplant. Development was evaluated by fuzzy mathematical modeling and by multiple polynomial regressions. Results were compared with data collected on the field. The highest development occurred for treatments irrigated with magnetically treated water, featuring a greater green aerial phytomass and number of leaves throughout the cycle. The fuzzy model provide d a more exact adjustment when compared with results from statistical models. (More)

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Paper citation in several formats:
Putti, F.; Gabriel Filho, L.; Cremasco, C. and Klar, A. (2015). Fuzzy Modeling of Development of Sheets Number in Different Irrigation Levels of Irrigated Lettuce with Magnetically Treated Water. In Proceedings of the 7th International Joint Conference on Computational Intelligence (ECTA 2015) - FCTA; ISBN 978-989-758-157-1, SciTePress, pages 162-169. DOI: 10.5220/0005599701620169

@conference{fcta15,
author={Fernando F. Putti. and Luís Roberto Almeida {Gabriel Filho}. and Camila Pires Cremasco. and Antonio Evaldo Klar.},
title={Fuzzy Modeling of Development of Sheets Number in Different Irrigation Levels of Irrigated Lettuce with Magnetically Treated Water},
booktitle={Proceedings of the 7th International Joint Conference on Computational Intelligence (ECTA 2015) - FCTA},
year={2015},
pages={162-169},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0005599701620169},
isbn={978-989-758-157-1},
}

TY - CONF

JO - Proceedings of the 7th International Joint Conference on Computational Intelligence (ECTA 2015) - FCTA
TI - Fuzzy Modeling of Development of Sheets Number in Different Irrigation Levels of Irrigated Lettuce with Magnetically Treated Water
SN - 978-989-758-157-1
AU - Putti, F.
AU - Gabriel Filho, L.
AU - Cremasco, C.
AU - Klar, A.
PY - 2015
SP - 162
EP - 169
DO - 10.5220/0005599701620169
PB - SciTePress