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Effects of soil properties, water quality and management practices on pistachio yield in Rafsanjan region, southeast of Iran

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  • Pourmohammadali, Behrooz
  • Hosseinifard, Seyed Javad
  • Hassan Salehi, Mohammad
  • Shirani, Hossein
  • Esfandiarpour Boroujeni, Isa

Abstract

In recent decades, the quantity and quality of irrigation water have been reduced due to a significant increase in pistachio cultivation and uncontrolled exploitation of groundwater resources as well as reduction in rainfall precipitation. Therefore, agricultural producers, researchers and policy makers need to pay more attention to appropriate land management as an important strategy to achieve greater yield per unit area and to use soil and water resources in an optimal way. So, the present study was conducted to model the relationships between pistachio yield and soil, water and management variables in Rafsanjan region, the southeast of Iran. One hundred and ninety nine mature orchards were selected and sampled in such a way that an acceptable range of soil and water quality and management were included. The data set consisted of a dependent variable (pistachio yield) and 67 independent variables including soil, water and management characteristics. The results of hybrid genetic algorithm-artificial neural network (GA-ANN) showed that the lowest error was related to the case in which the 23 features were used in modeling. Then, stepwise multiple linear regression (MLR) and artificial neural network (ANN) techniques were applied to estimate pistachio yield. The results indicated that MLR could explain only 28% of the pistachio yield variation, whereas its accuracy increased when the data became more homogeneous via geographically dividing the study area into four parts with the highest densities of pistachio orchards. ANN-based model had a 90% accuracy to predict pistachio yield in the study area. Thus, an accurate estimation of pistachio yield could be achieved by reducing the data dimensionality using feature selection techniques and modeling with ANN. As the models were highly sensitive to irrigation water features, special attention should be paid to new irrigation methods and management practices as an effective strategy to minimize water losses and increase water use efficiency.

Suggested Citation

  • Pourmohammadali, Behrooz & Hosseinifard, Seyed Javad & Hassan Salehi, Mohammad & Shirani, Hossein & Esfandiarpour Boroujeni, Isa, 2019. "Effects of soil properties, water quality and management practices on pistachio yield in Rafsanjan region, southeast of Iran," Agricultural Water Management, Elsevier, vol. 213(C), pages 894-902.
    • Handle: RePEc:eee:agiwat:v:213:y:2019:i:c:p:894-902
    DOI: 10.1016/j.agwat.2018.12.005
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    References listed on IDEAS

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    1. Iniesta, F. & Testi, L. & Goldhamer, D.A. & Fereres, E., 2008. "Quantifying reductions in consumptive water use under regulated deficit irrigation in pistachio (Pistacia vera L.)," Agricultural Water Management, Elsevier, vol. 95(7), pages 877-886, July.
    2. Kaul, Monisha & Hill, Robert L. & Walthall, Charles, 2005. "Artificial neural networks for corn and soybean yield prediction," Agricultural Systems, Elsevier, vol. 85(1), pages 1-18, July.
    3. Yazdanpanah, Najme & Pazira, Ebrahim & Neshat, Ali & Mahmoodabadi, Majid & Rodríguez Sinobas, Leonor, 2013. "Reclamation of calcareous saline sodic soil with different amendments (II): Impact on nitrogen, phosphorous and potassium redistribution and on microbial respiration," Agricultural Water Management, Elsevier, vol. 120(C), pages 39-45.
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    Cited by:

    1. Tadros, Maher J. & Al-Mefleh, Naji K. & Othman, Yahia A. & Al-Assaf, Amani, 2021. "Water harvesting techniques for improving soil water content, and morpho-physiology of pistachio trees under rainfed conditions," Agricultural Water Management, Elsevier, vol. 243(C).
    2. Mohammad Reza Mehrnejad, 2020. "Arthropod pests of pistachios, their natural enemies and management," Plant Protection Science, Czech Academy of Agricultural Sciences, vol. 56(4), pages 231-260.

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