NEURO-FUZZY MODELING AS SUPPORT FOR DECISION-MAKING IN THE PRODUCTION OF IRRIGATED CORIANDER UNDER MULCH IN THE SEMI-ARID REGION Article Swipe
Luís Roberto Almeida Gabriel Filho
,
Golbery Rudolf Oliveira Rodrigueiro
,
Alexsandro Oliveira da Silva
,
Antônio Vanklane Rodrigues de Almeida
,
Camila Pires Cremasco
·
YOU?
·
· 2023
· Open Access
·
· DOI: https://doi.org/10.1590/1809-4430-eng.agric.v43n2e20220208/2023
YOU?
·
· 2023
· Open Access
·
· DOI: https://doi.org/10.1590/1809-4430-eng.agric.v43n2e20220208/2023
Reducing water consumption by crops in semi-arid regions is an important factor for the sustainability of agriculture in these locations. In this sense, this study aims to evaluate the neuro-fuzzy inference method as a support for decision-making in irrigated coriander cultivation. The experiment was performed in two cultivation cycles in Pentecoste-CE, Brazil. The experiment was conducted in randomized blocks arranged in a split-plot design with five primary treatments, consisting of irrigation depths (50, 75, 100, 125, and 150% of the localized evapotranspiration, ETcloc), and five secondary treatments, consisting of different levels of bagana mulch (0, 25, 50, 75, and 100%, equivalent to 16 t ha−1). Neuro-fuzzy models with two input variables and eight output biometric variables were developed to evaluate growth (plant height, number of roots, and root length) and yield variables (productivity and shoot and root fresh and dry mass). In the first cycle, the best results occurred close to 55% ETcloc and between 40 and 50% of mulch; in the second cycle, water consumption returned results between 50 and 80% ETcloc. The fuzzy and multiple regression models showed MAE, MSE, and RMSE errors of 9, 22, and 10% lower, respectively. The neuro-fuzzy model might be a viable option for decision-making in irrigated crops, being able to optimize the use of natural resources and available water in semi-arid regions. The use of 55% of irrigation depth and a range of 40 to 50% of mulch can be a strategy for a higher water use efficiency.
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Metadata
- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.1590/1809-4430-eng.agric.v43n2e20220208/2023
- https://www.scielo.br/j/eagri/a/zSvbjX97KLSpVvmWNmWsjrx/?lang=en&format=pdf
- OA Status
- gold
- Cited By
- 1
- References
- 21
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4376609614
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W4376609614Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.1590/1809-4430-eng.agric.v43n2e20220208/2023Digital Object Identifier
- Title
-
NEURO-FUZZY MODELING AS SUPPORT FOR DECISION-MAKING IN THE PRODUCTION OF IRRIGATED CORIANDER UNDER MULCH IN THE SEMI-ARID REGIONWork title
- Type
-
articleOpenAlex work type
- Language
-
enPrimary language
- Publication year
-
2023Year of publication
- Publication date
-
2023-01-01Full publication date if available
- Authors
-
Luís Roberto Almeida Gabriel Filho, Golbery Rudolf Oliveira Rodrigueiro, Alexsandro Oliveira da Silva, Antônio Vanklane Rodrigues de Almeida, Camila Pires CremascoList of authors in order
- Landing page
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https://doi.org/10.1590/1809-4430-eng.agric.v43n2e20220208/2023Publisher landing page
- PDF URL
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https://www.scielo.br/j/eagri/a/zSvbjX97KLSpVvmWNmWsjrx/?lang=en&format=pdfDirect link to full text PDF
- Open access
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YesWhether a free full text is available
- OA status
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goldOpen access status per OpenAlex
- OA URL
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https://www.scielo.br/j/eagri/a/zSvbjX97KLSpVvmWNmWsjrx/?lang=en&format=pdfDirect OA link when available
- Concepts
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Mathematics, Irrigation, Arid, Evapotranspiration, Mulch, Sorghum, Water-use efficiency, Water use, Agricultural engineering, Deficit irrigation, Agronomy, Environmental science, Irrigation management, Engineering, Biology, EcologyTop concepts (fields/topics) attached by OpenAlex
- Cited by
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1Total citation count in OpenAlex
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2024: 1Per-year citation counts (last 5 years)
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21Number of works referenced by this work
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10Other works algorithmically related by OpenAlex
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