Cereal production is a key component of food security and economic stability in Bangladesh; however, it is increasingly influenced by the interplay between climatic stress and non-climatic pressures, including land-use change and ecological degradation. Nevertheless, no study at the national level has jointly quantified the long-term effects of these drivers. Using a multidisciplinary systematic framework involving detrending of the time series through linear regression, followed by iterative refinement and diagnostic validation of model robustness, this study addresses that gap by evaluating annual data spanning 1961–2022. All 11 explanatory variables were subjected to model selection, which revealed that the final model retained four significant predictors: land under cereal production (LUCP), arable land, observed annual precipitation, and forest area. The results indicate that land-use structure and ecological trade-offs are stronger predictors of cereal yield than annual climatic variability alone. The strongest predictor was forest area (β = −0.607, p < 0.001), followed by LUCP (β = 0.300, p < 0.001) and arable land (β = −0.147, p = 0.012), whereas annual precipitation had an independent effect that remained statistically non-significant (β = 0.037, p = 0.303). These findings imply that climate is not the sole determinant of agricultural productivity; rather, the allocation, management, and transformation of land also play critical roles. This evidence underscores the need for policy priorities to focus on sustainable intensification of existing cereal land, restoration of degraded arable land, and integrated governance of land use. Such an approach will directly contribute to achieving Sustainable Development Goal (SDG) 2 (Zero Hunger), SDG 13 (Climate Action), and SDG 15 (Life on Land).
Citation: A. K. M. Kanak Pervez, R. Ifty Isfaqur, Akira Ishida, Md Mahedi, Md Nazirul Islam Sarker. Exploring the climatic and non-climatic determinants of cereal production in Bangladesh[J]. AIMS Agriculture and Food, 2026, 11(3): 422-446. doi: 10.3934/agrfood.2026022
Cereal production is a key component of food security and economic stability in Bangladesh; however, it is increasingly influenced by the interplay between climatic stress and non-climatic pressures, including land-use change and ecological degradation. Nevertheless, no study at the national level has jointly quantified the long-term effects of these drivers. Using a multidisciplinary systematic framework involving detrending of the time series through linear regression, followed by iterative refinement and diagnostic validation of model robustness, this study addresses that gap by evaluating annual data spanning 1961–2022. All 11 explanatory variables were subjected to model selection, which revealed that the final model retained four significant predictors: land under cereal production (LUCP), arable land, observed annual precipitation, and forest area. The results indicate that land-use structure and ecological trade-offs are stronger predictors of cereal yield than annual climatic variability alone. The strongest predictor was forest area (β = −0.607, p < 0.001), followed by LUCP (β = 0.300, p < 0.001) and arable land (β = −0.147, p = 0.012), whereas annual precipitation had an independent effect that remained statistically non-significant (β = 0.037, p = 0.303). These findings imply that climate is not the sole determinant of agricultural productivity; rather, the allocation, management, and transformation of land also play critical roles. This evidence underscores the need for policy priorities to focus on sustainable intensification of existing cereal land, restoration of degraded arable land, and integrated governance of land use. Such an approach will directly contribute to achieving Sustainable Development Goal (SDG) 2 (Zero Hunger), SDG 13 (Climate Action), and SDG 15 (Life on Land).
| [1] | Miah MD, Hasan R, Uddin H (2020) Agricultural development and the rural economy: The case of Bangladesh. In: Barai MK (Ed.), Bangladesh's Economic and Social Progress: From a Basket Case to a Development Model, Singapore, Springer, 237–266. https://doi.org/10.1007/978-981-15-1683-2_8 |
| [2] |
D'Odorico P, Davis KF, Rosa L, et al. (2018) The global food-energy-water nexus. Rev Geophys 56: 456–531. https://doi.org/10.1029/2017RG000591 doi: 10.1029/2017RG000591
|
| [3] |
Akanmu AO, Akol AM, Ndolo DO, et al. (2023) Agroecological techniques: Adoption of safe and sustainable agricultural practices among the smallholder farmers in Africa. Front Sustain Food Syst 7: 1143061. https://doi.org/10.3389/fsufs.2023.1143061 doi: 10.3389/fsufs.2023.1143061
|
| [4] |
Epule TE, Ford JD, Lwasa S, et al. (2018) The determinants of crop yields in Uganda: what is the role of climatic and non-climatic factors? Agric & Food Secur 7: 10. https://doi.org/10.1186/s40066-018-0159-3 doi: 10.1186/s40066-018-0159-3
|
| [5] |
Srivastav AL, Dhyani Rajni, Ranjan M, et al. (2021) Climate-resilient strategies for sustainable management of water resources and agriculture. Environ Sci Pollut Res 28: 41576–41595. https://doi.org/10.1007/s11356-021-14332-4 doi: 10.1007/s11356-021-14332-4
|
| [6] |
Sims B, Kienzle J (2017) Sustainable agricultural mechanization for smallholders: What is it and how can we implement it? Agriculture 7: 50. https://doi.org/10.3390/agriculture7060050 doi: 10.3390/agriculture7060050
|
| [7] |
Ghose B, Islam ARMdT, Islam HMT, et al. (2021) Rain-fed rice yield fluctuation to climatic anomalies in Bangladesh. Int J Plant Prod 15: 183–201. https://doi.org/10.1007/s42106-021-00131-x doi: 10.1007/s42106-021-00131-x
|
| [8] |
Chandio AA, Jiang Y, Fatima T, et al. (2022) Assessing the impacts of climate change on cereal production in Bangladesh: evidence from ARDL modeling approach. Int J Climate Change Strategies Manage 14: 125–147. https://doi.org/10.1108/IJCCSM-10-2020-0111 doi: 10.1108/IJCCSM-10-2020-0111
|
| [9] |
Dey NC, Saha R, Parvez M, et al. (2017) Sustainability of groundwater use for irrigation of dry-season crops in northwest Bangladesh. Groundwater Sustainable Dev 4: 66–77. https://doi.org/10.1016/j.gsd.2017.02.001 doi: 10.1016/j.gsd.2017.02.001
|
| [10] |
Sarker MR, Galdos MV, Challinor AJ, et al. (2021) A farming system typology for the adoption of new technology in Bangladesh. Food Energy Secur 10: e287. https://doi.org/10.1002/fes3.287 doi: 10.1002/fes3.287
|
| [11] |
Li C, Chandio AA, Abid N, et al. (2025) Exploring the impact of digital technologies adoption and climate change on food security: Policy framework for achieving sustainable development goals. Int J Climate Change Strategies Manage 17: 1140–1160. https://doi.org/10.1108/IJCCSM-07-2025-0214 doi: 10.1108/IJCCSM-07-2025-0214
|
| [12] |
Merlin ML, Chen Y (2021) Analysis of the factors affecting electricity consumption in DR Congo using fully modified ordinary least square (FMOLS), dynamic ordinary least square (DOLS) and canonical cointegrating regression (CCR) estimation approach. Energy 232: 121025. https://doi.org/10.1016/j.energy.2021.121025 doi: 10.1016/j.energy.2021.121025
|
| [13] | Khan SR (2022) Resource potentials of the marine areas of Bangladesh. Bangladesh Geosciences and Resources Potential, CRC Press. https://doi.org/10.1201/9781003080817-9 |
| [14] | Sahoo G, Wani AM, Swamy SL, et al. (2022) Livelihood strategy and sustainability aspects in industrialization as a source of employment in rural areas. In: Hassan MI, Sen Roy S, Chatterjee U, et al. (Eds.), Social Morphology, Human Welfare, and Sustainability, Cham, Springer International Publishing, 643–670. https://doi.org/10.1007/978-3-030-96760-4_26 |
| [15] |
Islam MdR, Rahman MdA, Anik AR, et al. (2023) The role of minor cereals in food and nutrition security in Bangladesh: Constraints to sustainable production. Food Secur 15: 1151–1160. https://doi.org/10.1007/s12571-023-01364-6 doi: 10.1007/s12571-023-01364-6
|
| [16] |
Haq A, Md S (2022) Extreme weather events and spiraling debt: A double whammy for Bangladeshis affected by climate change. Front Psychol 13: 879219. https://doi.org/10.3389/fpsyg.2022.879219 doi: 10.3389/fpsyg.2022.879219
|
| [17] |
Mahedi M, Pervez AKMK, Ishida A, et al. (2026) Living with drought: climate change perceptions, adaptation, and mitigation among farmers in rural Bangladesh. Front Clim 8: 1744133. https://doi.org/10.3389/fclim.2026.1744133 doi: 10.3389/fclim.2026.1744133
|
| [18] |
Sidhu BS, Mehrabi Z, Kandlikar M, et al. (2022) On the relative importance of climatic and non-climatic factors in crop yield models. Climatic Change 173: 8. https://doi.org/10.1007/s10584-022-03404-0 doi: 10.1007/s10584-022-03404-0
|
| [19] |
Bhatti UA, Bhatti MA, Tang H, et al. (2024) Global production patterns: Understanding the relationship between greenhouse gas emissions, agriculture greening and climate variability. Environ Res 245: 118049. https://doi.org/10.1016/j.envres.2023.118049 doi: 10.1016/j.envres.2023.118049
|
| [20] |
Xing Y, Wang X (2024) Impact of agricultural activities on climate change: A review of greenhouse gas emission patterns in field crop systems. Plants 13: 2285. https://doi.org/10.3390/plants13162285 doi: 10.3390/plants13162285
|
| [21] |
Friedlingstein P, O'Sullivan M, Jones MW, et al. (2022) Global Carbon Budget 2022. Earth Syst Sci Data 14: 4811–4900. https://doi.org/10.5194/essd-14-4811-2022 doi: 10.5194/essd-14-4811-2022
|
| [22] |
Lobell DB, Burke MB (2008) Why are agricultural impacts of climate change so uncertain? The importance of temperature relative to precipitation. Environ Res Lett 3: 034007. https://doi.org/10.1088/1748-9326/3/3/034007 doi: 10.1088/1748-9326/3/3/034007
|
| [23] |
Sarker MdAR, Alam K, Gow J (2012) Exploring the relationship between climate change and rice yield in Bangladesh: An analysis of time series data. Agric Syst 112: 11–16. https://doi.org/10.1016/j.agsy.2012.06.004 doi: 10.1016/j.agsy.2012.06.004
|
| [24] |
Gerssen‐Gondelach S, Wicke B, Faaij A (2015) Assessment of driving factors for yield and productivity developments in crop and cattle production as key to increasing sustainable biomass potentials. Food Energy Secur 4: 36–75. https://doi.org/10.1002/fes3.53 doi: 10.1002/fes3.53
|
| [25] |
Melvani K, Myers TLB, Stacey N, et al. (2022) Farmers' values for land, trees and biodiversity underlie agricultural sustainability. Land Use Policy 117: 105688. https://doi.org/10.1016/j.landusepol.2021.105688 doi: 10.1016/j.landusepol.2021.105688
|
| [26] | Akenji L, Bengtsson M, Toivio V, et al. (2021) 1.5-degree lifestyles: Towards a fair consumption space for all, Hot or Cool. |
| [27] |
Boretti A (2025) Evaluating water use efficiency and CO₂ absorption in plants under rising atmospheric carbon dioxide levels. J Atmos Sol-Terr Phys 266: 106409. https://doi.org/10.1016/j.jastp.2024.106409 doi: 10.1016/j.jastp.2024.106409
|
| [28] | Ekka P, Patra S, Upreti M, et al. (2023) Land degradation and its impacts on biodiversity and ecosystem services. In: Raj A, Jhariya MK, Banerjee A, et al. (Eds.), Land and Environmental Management through Forestry, Wiley, 77–101. https://doi.org/10.1002/9781119910527.ch4 |
| [29] |
Müller R, Pistorius T, Rohde S, et al. (2013) Policy options to reduce deforestation based on a systematic analysis of drivers and agents in lowland Bolivia. Land Use Policy 30: 895–907. https://doi.org/10.1016/j.landusepol.2012.06.019 doi: 10.1016/j.landusepol.2012.06.019
|
| [30] |
Okamura H, Osada Y, Nishijima S, et al. (2021) Novel robust time series analysis for long-term and short-term prediction. Sci Rep 11: 11938. https://doi.org/10.1038/s41598-021-91327-8 doi: 10.1038/s41598-021-91327-8
|
| [31] |
Onyekwere SC, Otuyelu O (2021) Inward foreign direct investments (FDI) and location choice determinants: Empirical evidence from India. Daengku: J Humanit Soc Sci Innovation 1: 111–129. https://doi.org/10.35877/454RI.daengku580 doi: 10.35877/454RI.daengku580
|
| [32] |
Rho Y, Shao X (2015) Inference for time series regression models with weakly dependent and heteroscedastic errors. J Bus & Econ Stat 33: 444–457. https://doi.org/10.1080/07350015.2014.962698 doi: 10.1080/07350015.2014.962698
|
| [33] |
Hossain M, Biswas P, Islam MR (2023) Cold-tolerant and short-duration rice (Oryza sativa L.) for sustainable food security of the flash flood-prone Haor wetlands of Bangladesh. Sustainability 15: 16873. https://doi.org/10.3390/su152416873 doi: 10.3390/su152416873
|
| [34] |
Chakraborty S, Pan S, Pal SC, et al. (2025) Evaluating the impact of rainfall patterns on sustainable agricultural crop production. Discov Sustain 6: 516. https://doi.org/10.1007/s43621-025-01392-6 doi: 10.1007/s43621-025-01392-6
|
| [35] |
Mondol MF, Hasan MF, Tania MJ, et al. (2025) An ensemble machine learning framework for predicting agricultural droughts in the Ganges Delta of Bangladesh. Earth Syst Environ 10: 6429–6450. https://doi.org/10.1007/s41748-025-00943-1 doi: 10.1007/s41748-025-00943-1
|
| [36] |
Chang D, Li S, Lai Z (2023) Effects of extreme precipitation intensity and duration on the runoff and nutrient yields. J Hydrol 626: 130281. https://doi.org/10.1016/j.jhydrol.2023.130281 doi: 10.1016/j.jhydrol.2023.130281
|
| [37] |
Jion MostMMF, Kamruzzaman M, Mallick J, et al. (2025) Agricultural drought risk in aman rice season: A case from western region of Bangladesh. Theor Appl Climatol 156: 561. https://doi.org/10.1007/s00704-025-05827-y doi: 10.1007/s00704-025-05827-y
|
| [38] |
Korie N, Njeru L, Mburu J, et al. (2023) Assessment of factors influencing adoption of tomato post-harvest loss-reduction technologies in Kaduna state, Nigeria. EAJSTI 4: No. 2. https://doi.org/10.37425/eajsti.v4i2.599 doi: 10.37425/eajsti.v4i2.599
|
| [39] | Sajid Hasan A (2017) Study on the impact of climate change on the production of BR11 aman rice in Bangladesh. |
| [40] |
Nyamayevu D, Nyagumbo I, Chiduwa M, et al. (2024) Understanding crop diversification among smallholder farmers: Socioeconomic insights from Central Malawi. Sustainability 16: 9078. https://doi.org/10.3390/su16209078 doi: 10.3390/su16209078
|
| [41] |
Sumo TV, Ritho C, Irungu P (2022) Effect of farmer socio-economic characteristics on extension services demand and its intensity of use in post-conflict Liberia. Heliyon 8: e12268. https://doi.org/10.1016/j.heliyon.2022.e12268 doi: 10.1016/j.heliyon.2022.e12268
|
| [42] | Dubey A, Singh PK, Singh S, et al. (2025) Impact of climate change and land degradation on agriculture. In: Chatterjee U, Ghosh A, Roy SK (Eds.), Eco-Resilience: Climate Change, Land Degradation and Sustainable Solutions, Cham, Springer Nature Switzerland, 49–95. https://doi.org/10.1007/978-3-032-00708-7_3 |
| [43] | Singh J, Asim M, Tshering P (2025) Comprehensive review of land resource policies of South Asia. In: Rani S (Ed.), Land and Water Nexus in South Asia: Exploring the Interplay of Resources, Cham, Springer Nature Switzerland, 407–447. https://doi.org/10.1007/978-3-031-87429-1_15 |
| [44] |
Sharma UC, Datta M, Sharma V (2022) Land use and management. In: Soils in the Hindu Kush Himalayas, Cham, Springer International Publishing, 295–462. https://doi.org/10.1007/978-3-031-11458-8_7 doi: 10.1007/978-3-031-11458-8_7
|
| [45] |
Maja MM, Ayano SF (2021) The impact of population growth on natural resources and farmers' capacity to adapt to climate change in low-income countries. Earth Syst Environ 5: 271–283. https://doi.org/10.1007/s41748-021-00209-6 doi: 10.1007/s41748-021-00209-6
|
| [46] |
Azadi H, Ho P, Hasfiati L (2011) Agricultural land conversion drivers: A comparison between less developed, developing and developed countries. Land Degrad Dev 22: 596–604. https://doi.org/10.1002/ldr.1037 doi: 10.1002/ldr.1037
|
| [47] |
Ahmed Z, Gui D, Murtaza G, et al. (2023) An overview of smart irrigation management for improving water productivity under climate change in drylands. Agronomy 13: 2113. https://doi.org/10.3390/agronomy13082113 doi: 10.3390/agronomy13082113
|
| [48] |
Chan JY-L, Leow SMH, Bea KT, et al. (2022) Mitigating the multicollinearity problem and its machine learning approach: A review. Mathematics 10: 1283. https://doi.org/10.3390/math10081283 doi: 10.3390/math10081283
|
| [49] |
Osman EGA (2025) Entropy based solutions for detecting and treating multicollinearity in econometrics. Discov Anal 3: 18. https://doi.org/10.1007/s44257-025-00047-0 doi: 10.1007/s44257-025-00047-0
|
| [50] |
Okorie IE, Afuecheta E, Nadarajah S (2023) Time series and power law analysis of crop yield in some east African countries. PLoS ONE 18: e0287011. https://doi.org/10.1371/journal.pone.0287011 doi: 10.1371/journal.pone.0287011
|
| [51] |
Silva JV, Heerwaarden J van, Reidsma P, et al. (2023) Big data, small explanatory and predictive power: Lessons from random forest modeling of on-farm yield variability and implications for data-driven agronomy. Field Crops Res 302: 109063. https://doi.org/10.1016/j.fcr.2023.109063 doi: 10.1016/j.fcr.2023.109063
|
| [52] |
Therond O, Duru M, Roger-Estrade J, et al. (2017) A new analytical framework of farming system and agriculture model diversities. A review. Agron Sustain Dev 37: 21. https://doi.org/10.1007/s13593-017-0429-7 doi: 10.1007/s13593-017-0429-7
|
| [53] |
Cornia GA (1985) Farm size, land yields and the agricultural production function: An analysis for fifteen developing countries. World Dev 13: 513–534. https://doi.org/10.1016/0305-750X(85)90054-3 doi: 10.1016/0305-750X(85)90054-3
|
| [54] |
Rahman S, Anik AR, Sarker JR (2022) Climate, environment and socio-economic drivers of global agricultural productivity Growth. Land 11: 512. https://doi.org/10.3390/land11040512 doi: 10.3390/land11040512
|
| [55] |
Ali Chandio A, Sethi N, Prasad Dash D, et al. (2022) Towards sustainable food production: What role ICT and technological development can play for cereal production in Asian–7 countries? Comput Electron Agric 202: 107368. https://doi.org/10.1016/j.compag.2022.107368 doi: 10.1016/j.compag.2022.107368
|
| [56] |
Naorem A, Jayaraman S, Dang YP, et al. (2023) Soil constraints in an arid environment—Challenges, prospects, and implications. Agronomy 13: 220. https://doi.org/10.3390/agronomy13010220 doi: 10.3390/agronomy13010220
|
| [57] |
Islam I, Cui S, Hoque MZ, et al. (2022) Dynamics of tree outside forest land cover development and ecosystem carbon storage change in Eastern Coastal Zone, Bangladesh. Land 11: 76. https://doi.org/10.3390/land11010076 doi: 10.3390/land11010076
|
| [58] |
Moghadam NT, Malekmohammadi B, Schirmer M (2024) Vulnerability assessment of hydrological ecosystem services under future climate and land use change dynamics. Ecol Indic 160: 111905. https://doi.org/10.1016/j.ecolind.2024.111905 doi: 10.1016/j.ecolind.2024.111905
|
| [59] |
Masolele RN, Marcos D, De Sy V, et al. (2024) Mapping the diversity of land uses following deforestation across Africa. Sci Rep 14: 1681. https://doi.org/10.1038/s41598-024-52138-9 doi: 10.1038/s41598-024-52138-9
|
| [60] |
Jui MJF, Haque MdM, Billah M (2025) A spatiotemporal analysis of four decades of temperature-precipitation interactions and their agricultural consequences in Bangladesh. Discov Atmos 3: 36. https://doi.org/10.1007/s44292-025-00063-5 doi: 10.1007/s44292-025-00063-5
|
| [61] |
Mainuddin M, Peña-Arancibia JL, Karim F, et al. (2022) Long-term spatio-temporal variability and trends in rainfall and temperature extremes and their potential risk to rice production in Bangladesh. PLOS Climate 1: e0000009. https://doi.org/10.1371/journal.pclm.0000009 doi: 10.1371/journal.pclm.0000009
|
| [62] |
Wang X, Folberth C, Skalsky R, et al. (2022) Crop calendar optimization for climate change adaptation in rice-based multiple cropping systems of India and Bangladesh. Agric For Meteorol 315: 108830. https://doi.org/10.1016/j.agrformet.2022.108830 doi: 10.1016/j.agrformet.2022.108830
|
| [63] |
Kidane R, Wanner T, Nursey-Bray M, et al. (2022) The role of climatic and non-climatic factors in smallholder farmers' adaptation responses: Insights from Rural Ethiopia. Sustainability 14: 5715. https://doi.org/10.3390/su14095715 doi: 10.3390/su14095715
|
| [64] |
Sharma R, Rallapalli S, Magner J (2025) Optimizing water-efficient agriculture: evaluating the sustainability of soil management and irrigation synergies using fuzzy extent analysis. Sci Rep 15: 29382. https://doi.org/10.1038/s41598-025-15426-6 doi: 10.1038/s41598-025-15426-6
|
| [65] |
Pandey PC, Pandey M (2023) Highlighting the role of agriculture and geospatial technology in food security and sustainable development goals. Sustainable Dev 31: 3175–3195. https://doi.org/10.1002/sd.2600 doi: 10.1002/sd.2600
|
Figures(4) / Tables(3)
A. K. M. Kanak Pervez, R. Ifty Isfaqur, Akira Ishida, Md Mahedi, Md Nazirul Islam Sarker. Exploring the climatic and non-climatic determinants of cereal production in Bangladesh[J]. AIMS Agriculture and Food, 2026, 11(3): 422-446. doi: 10.3934/agrfood.2026022
DownLoad: