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Article

Estimating Yield and Water Productivity of Tomato Using a Novel Hybrid Approach

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Agricultural Engineering Research Institute, Agricultural Research, Education and Extension Organization, Karaj P.O. Box 31585-845, Iran
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Department of Water Engineering, University of Tabriz, Tabriz 51666-16471, Iran
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Laboratory of Water & Environment, Faculty of Nature and Life Sciences, University Hassiba Benbouali of Chlef, Chlef, P. B 78C, Ouled Fares, Chlef 02180, Algeria
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Faculty of Water Resource Engineering, Thuyloi University, Hanoi 100000, Vietnam
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Institute of Applied Technology, Thu Dau Mot University, Thu Dau Mot City 75000, Vietnam
*
Authors to whom correspondence should be addressed.
Academic Editor: Arturo Alvino
Water 2021, 13(24), 3615; https://doi.org/10.3390/w13243615
Received: 21 October 2021 / Revised: 28 November 2021 / Accepted: 12 December 2021 / Published: 16 December 2021
(This article belongs to the Special Issue Inevitable Connection of River Flow Modeling, GIS, and Hydrogeology)
Water productivity (WP) of crops is affected by water–fertilizer management in interaction with climatic factors. This study aimed to evaluate the efficiency of a hybrid method of season optimization algorithm (SO) and support vector regression (SVR) in estimating the yield and WP of tomato crops based on climatic factors, irrigation–fertilizer under the drip irrigation, and plastic mulch. To approve the proposed method, 160 field data including water consumption during the growing season, fertilizers, climatic variables, and crop variety were applied. Two types of treatments, namely drip irrigation (DI) and drip irrigation with plastic mulch (PMDI), were considered. Seven different input combinations were used to estimate yield and WP. R2, RMSE, NSE, SI, and σ criteria were utilized to assess the proposed hybrid method. A good agreement was presented between the observed (field monitoring data) and estimated (calculated with SO–SVR method) values (R2 = 0.982). The irrigation–-fertilizer parameters (PMDI, F) and crop variety (V) are the most effective in estimating the yield and WP of tomato crops. Statistical analysis of the obtained results showed that the SO–SVR hybrid method has high efficiency in estimating WP and yield. In general, intelligent hybrid methods can enable the optimal and economical use of water and fertilizer resources. View Full-Text
Keywords: irrigation; season optimization algorithm; support vector regression; yield estimation irrigation; season optimization algorithm; support vector regression; yield estimation
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MDPI and ACS Style

Dehghanisanij, H.; Emami, S.; Achite, M.; Linh, N.T.T.; Pham, Q.B. Estimating Yield and Water Productivity of Tomato Using a Novel Hybrid Approach. Water 2021, 13, 3615. https://doi.org/10.3390/w13243615

AMA Style

Dehghanisanij H, Emami S, Achite M, Linh NTT, Pham QB. Estimating Yield and Water Productivity of Tomato Using a Novel Hybrid Approach. Water. 2021; 13(24):3615. https://doi.org/10.3390/w13243615

Chicago/Turabian Style

Dehghanisanij, Hossein, Somayeh Emami, Mohammed Achite, Nguyen T.T. Linh, and Quoc B. Pham. 2021. "Estimating Yield and Water Productivity of Tomato Using a Novel Hybrid Approach" Water 13, no. 24: 3615. https://doi.org/10.3390/w13243615

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