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<p>The study focuses on current banana production and its prospects in Bangladesh, among the eight divisions, namely Barisal, Chattogram, Dhaka, Khulna, Mymensingh, Rajshahi, Rangpur, and Sylhet. Data for 2000–2021 from the Bangladesh Bureau of Statistics (BBS) were analyzed using autoregressive integrated moving average (ARIMA) models. The study also provides a&#xa0;detailed overview of the cultivated area of banana in Bangladesh from 2000 to 2021, highlighting the country’s diverse agricultural landscape and the potential for further growth. Among the eight divisions, Dhaka (4,237,050.54 metric tons (MT)) recorded the largest overall volume of banana production. Additionally, the predictive precision was evaluated using mean absolute error (MAE), mean absolute percentage error (MAPE), and symmetric mean absolute percentage error (SMAPE) to assess the resulting ARIMA models for quarterly banana production. Therefore, the various models and projected productions identified in this research are crucial to maintaining market stability and reliable banana supplies.</p>

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Numerical Breakdown of Contemporary Banana Production and Its Prospects in Bangladesh

  • 期刊论文

  • 发表日期：

    2025年9月22日

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  • Sayed Mohibul Hossen,
  • Rakibul Islam

摘要

The study focuses on current banana production and its prospects in Bangladesh, among the eight divisions, namely Barisal, Chattogram, Dhaka, Khulna, Mymensingh, Rajshahi, Rangpur, and Sylhet. Data for 2000–2021 from the Bangladesh Bureau of Statistics (BBS) were analyzed using autoregressive integrated moving average (ARIMA) models. The study also provides a detailed overview of the cultivated area of banana in Bangladesh from 2000 to 2021, highlighting the country’s diverse agricultural landscape and the potential for further growth. Among the eight divisions, Dhaka (4,237,050.54 metric tons (MT)) recorded the largest overall volume of banana production. Additionally, the predictive precision was evaluated using mean absolute error (MAE), mean absolute percentage error (MAPE), and symmetric mean absolute percentage error (SMAPE) to assess the resulting ARIMA models for quarterly banana production. Therefore, the various models and projected productions identified in this research are crucial to maintaining market stability and reliable banana supplies.