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Determination of cotton and wheat yield using the standard precipitation evaporation index in Pakistan

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Abstract

This study presents an efficient approach to predict the Rabi and Kharif crop yield using a relatively new and robust machine learning (ML) model named random forest (RF). The standard precipitation evaporation index (SPEI) with different time lags (e.g., 1 to 12 months) are utilized as predictive variables. The SPEI was estimated using the climate prediction center (CPC) precipitation, and temperature dataset for the period 1981–2015 are employed. The feasibility of the RF model is validated against some other well-known ML models such as support vector regression (SVR), k-nearest neighbors (K-NN), and bagged CART models. The results showed a significant relationship between crop yields and the SPEI. The RF model showed the highest performance with the minimum values of absolute error measures (e.g., root mean square error (RMSE) and mean absolute error (MAE)) in the testing phase (0.1826–0.1383) and (0.1234–0.1092) for cotton and wheat production, respectively. Cotton yield prediction accuracy using the RF model improved compared to the SVR, K-NN, bagged CART, and ANN in terms of RMSE, and MAE indices are 12–10.79%, 12.33–10.79%, and 5.7–0.17%, respectively. Overall, the RF model provided a reliable alternative ML-based strategy for the cotton and wheat yield prediction over the Pakistan region.

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Authors and Affiliations

  1. School of Civil Engineering, Universiti Teknologi Malaysia (UTM), 81310, Johor Bahru, Malaysia

    Najeebullah Khan, Shamsuddin Shahid & Tarmizi Ismail

  2. Faculty of Engineering Sciences and Technology, Lasbela University of Agriculture Water and Marine Sciences, Uthal, Balochistan, 90150, Pakistan

    Najeebullah Khan, Kamal Ahmed & Nadeem Nawaz

  3. Department of Civil Engineering, Science and Research Branch, Islamic Azad University, Tehran, Iran

    Ahmad Sharafati

  4. New Era and Development in Civil Engineering Research Group, Scientific Research Center, Al-Ayen University, Thi-Qar, 64001, Iraq

    Zaher Mundher Yaseen

  5. College of Creative Design, Asia University, Taichung City, Taiwan

    Zaher Mundher Yaseen

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  1. Najeebullah Khan
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  2. Shamsuddin Shahid
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Correspondence to Ahmad Sharafati.

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Khan, N., Shahid, S., Sharafati, A. et al. Determination of cotton and wheat yield using the standard precipitation evaporation index in Pakistan. Arab J Geosci 14, 2035 (2021). https://doi.org/10.1007/s12517-021-08432-1

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