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Application of land properties in estimation of wheat production by FAO and gene expression programming (GEP) models

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Abstract

This study aims to compare the Food and Agriculture Organization (FAO) framework as a common model and gene expression programming (GEP) model for predicting the irrigated wheat production by using land properties in Khajeh area, Iran. First, 80 representative soil profiles were described in wheat fields. Then, the soil samples were collected from each horizon, and soil properties were determined in the laboratory for obtaining the model input data. After that, wheat production models were developed by FAO and GEP models. Sensitivity analysis indicated that total N, available P, slope, coarse fragment, electrical conductivity, pH, and organic matter are important soil properties for wheat production. Based on the results, the value of predicted wheat production by GEP model (981–5382) is closer to the actual production (1000–5600) compared to the FAO models (1284–6123). The geometric mean error ratio (GMER), root mean square error (RMSE), and coefficient of determination (R2) between predicted and actual production for FAO and GEP models were calculated 1.24, 18.6, and 0.84 and 0.83, 15.4, and 0.91, respectively. The overall agreement was recognized between wheat predicted production by using FAO and GEP and actual production by composite operator. This agreement was 71.5 and 82.2% for FAO and GEP models, respectively. Therefore, gene expression programming model was introduced as an effective model for predicting the wheat production. This more accuracy was obtained due to good choosing and lack of interaction among land properties as input variables.

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Data availability

The data which support the findings of this study will be available from the corresponding author upon reasonable request.

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Authors and Affiliations

  1. Soil Science and Engineering Department, University of Zanjan, Zanjan, Iran

    Ali Bariklo, Parisa Alamdari & Kamran Moravej

  2. Shahid Bakeri High Education Center of Miandoab, Urmia University, Urmia, Iran

    Moslem Servati

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  1. Ali Bariklo
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  2. Parisa Alamdari
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  3. Kamran Moravej
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  4. Moslem Servati
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All the authors contributed to the study conception and design and read and approved the final manuscript.

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Correspondence to Moslem Servati.

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Responsible Editor: Haroun Chenchouni

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Bariklo, A., Alamdari, P., Moravej, K. et al. Application of land properties in estimation of wheat production by FAO and gene expression programming (GEP) models. Arab J Geosci 15, 590 (2022). https://doi.org/10.1007/s12517-022-09868-9

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