Rural Agricultural Efficiency, Climate Sustainability, and Economic Performance: An Examination of Organic and Conventional Farming
Hayder M. Ali
Department of Information Technology, College of Science, University of Warith Al-Anbiyaa, Karbala 56001, Iraq
Department of Information Technology, School of Computer Science, Engineering and Information Systems, Vellore Institute of Technology, Vellore 632014, India
Anusha Papasani
Department of Computer Science and Engineering, Koneru Lakshmaiah Education Foundation, Guntur 522502, India
Suvathipriya Subramani
Department of Agricultural Engineering, V.S.B. College of Engineering Technical Campus, Coimbatore 642109, India
Tariq Qarem
Faculty of Architecture and Design, Al-Ahliyya Amman University, Amman 19328, Jordan
Aseel Smerat
Hourani Center for Applied Scientific Research, Al-Ahliyya Amman University, Amman 19328, Jordan
Zokir Mamadiyarov
Department of Finance and Tourism, Termez University of Economics and Service, Termez, Uzbekistan
Department of Economics, Mamun University, Khiva, Uzbekistan
Department of Bank Accounting and Auditing, Tashkent State University of Economics, Tashkent, Uzbekistan
Department of Computer and Science and Engineering, Erode Sengunthar Engineering College, Erode 638057, Tamil Nadu, India
DOI: https://doi.org/10.36956/rwae.v7i3.2740
Received: 14 September 2025 | Revised: 9 November 2025 | Accepted: 7 December 2025 | Published Online: 12 August 2026
Copyright © 2026 Hayder M. Ali, Gayathri Ananthakrishnan, Anusha Papasani , Suvathipriya Subramani, Tariq Qarem, Aseel Smerat , Zokir Mamadiyarov, Sudhakar Sengan. Published by Nan Yang Academy of Sciences Pte. Ltd.
This is an open access article under the Creative Commons Attribution-NonCommercial 4.0 International (CC BY-NC 4.0) License.
Abstract
Organic farming has emerged as a sustainable alternative to conventional farming, providing potential benefits in environmental conservation, crop quality, and market access. This study measures the impact of organic farming on agricultural productivity, resource utilisation, environmental sustainability, and trade competitiveness in Punjab, India. A comparative analysis of organic and conventional farming was conducted, focusing on key metrics such as crop yield per hectare, soil health, biological diversity, carbon footprint, and market access. As indicated by the research results, while conventional farming generated higher crop yield (e.g., the wheat crop: 4.47 vs. 3.82 t/ha, p = 0.034), organic farming improved in terms of resource utilisation, using less water (130.4 vs. 160.2 m3/t, p = 0.03) and energy consumption (225.6 vs. 270.8 kWh/t, p = 0.02). Organic farming was associated with better soil health (organic farming: 3.8% vs. 2.9%, p = 0.005) and superior biological diversity (species richness: 25 vs. 15, p = 0.008). Both findings were considered statistically significant. In terms of the marketplace, 68.2% of organic farming were able to access top marketplaces, whereas only 40.5% of conventional farming were (p = 0.01). By doing this, these individuals were able to negotiate higher costs (₹75.6 vs. ₹63.4/kg, p = 0.02). There is a clear result that organic farming products can be successful globally, as shown by the revealed comparative advantage (1.53).
Keywords: Organic Farming Practices; Agricultural Productivity; Market Access; Revealed Comparative Advantage; Soil Health; Machine Learning
References
[1] Gamage, A., Gangahagedara, R., Gamage, J., et al., 2023. Role of organic farming for achieving sustainability in agriculture. Farming System. 1(1), 100005.
[2] Soni, R., Gupta, R., Agarwal, P., et al., 2022. Organic farming: A sustainable agricultural practice. Vantage: Journal of Thematic Analysis. 3(1), 21–44.
[3] Thakur, N., Nigam, M., Tewary, R., et al., 2022. Drivers for the behavioural receptiveness and non-receptiveness of farmers towards organic cultivation system. Journal of King Saud University-Science. 34(5), 102107.
[4] Arhin, I., Li, J., Mei, H., et al., 2022. Looking into the future of organic tea production and sustainable farming: A systematic review. International Journal of Agricultural Sustainability. 20(5), 942–954.
[5] Patel, S.K., Sharma, A., Singh, G.S., 2020. Traditional agricultural practices in India: An approach for environmental sustainability and food security. Energy, Ecology and Environment. 5(4), 253–271.
[6] Ferdous, Z., Zulfiqar, F., Datta, A., et al., 2021. Potential and challenges of organic agriculture in Bangladesh: A review. Journal of Crop Improvement. 35(3), 403–426.
[7] Maitra, S., Gitari, H., 2020. Scope for adoption of intercropping system in organic agriculture. Indian Journal of Natural Sciences. 11(63), 28624–28631.
[8] Aulakh, C.S., Sharma, S., Thakur, M., et al., 2022. A review of the influences of organic farming on soil quality, crop productivity, and produce quality. Journal of Plant Nutrition. 45(12), 1884–1905.
[9] Mogaka, H., 2023. Effects of Regenerative Agriculture Technologies on the Productivity of Cowpea in the Drylands of Embu County, Kenya. Journal of Experimental Biology and Agricultural Sciences. 11(1), 190–198. DOI: https://doi.org/10.18006/2023.11(1).190.198
[10] Singh, R., Babu, S., Avasthe, R.K., et al., 2021. Organic farming in North–East India: Status and strategies. Indian Journal of Agronomy. 66(5), 163–179.
[11] Schader, C., Heidenreich, A., Kadzere, I., et al., 2021. How is organic farming performing agronomically and economically in sub-Saharan Africa? Global Environmental Change. 70, 102325.
[12] Sánchez, A.C., Kamau, H.N., Grazioli, F., et al., 2022. Financial profitability of diversified farming systems: A global meta-analysis. Ecological Economics. 201, 107595.
[13] Nandwani, D., Jamarkattel, D., Dahal, K.R., et al., 2021. Attitudes of fruit and vegetable farmers towards organic farming in Kathmandu Valley, Nepal. Sustainability. 13(7), 3888.
[14] Tubagus, S., Mahyuni, L.P., 2024. Exploring the Implementation of Society 5.0: Utilizing Advanced Technology in Sustainable Smart Farming Governance. In Proceedings of the 10th International Conference on Smart Computing and Communication, Bali, Indonesia, 25–27 July 2024; pp. 539–543. DOI: https://doi.org/10.1109/ICSCC62041.2024.10690313
[15] Arif, S., Isdijoso, W., Fatah, A.R., et al., 2020. Strategic Review of Food Security and Nutrition in Indonesia—Latest Information 2019–2020. SMERU Research Institute: Jakarta, Indonesia. (in Indonesian)
[16] Rachmawati, R.R., 2020. Smart Farming 4.0 to Build Advanced, Independent, and Modern Indonesian Agriculture. Forum Penelitian Agro Ekonomi. 38(2), 137–154. (in Indonesian)
[17] Matsuda, K., Uesugi, S., Naruse, K., et al., 2019. Technologies of production with society 5.0. In Proceedings of the 6th International Conference on Behavioral Economic and Socio-Cultural Computing, 28–30 October 2019; pp. 1–4.
[18] Septantiningtyas, N., Laili, N., Nuraini, Y.P.I., et al., 2023. PKM Information Technology Training to Improve Digital Skills and Awareness of Rural Communities in Margoayu Hamlet, Pakuniran, Probolinggo. Jurnal Pengabdian Masyarakat Bangsa. 1(10), 2586–2591. (in Indonesian)
[19] Rasya, H.S., Triadi, I., 2024. Access to Justice and Social Inequality: Transformation through the Role of Constitutional Law. Indonesian Journal of Law and Justice. 1(4), 12.
[20] Seufert, V., Ramankutty, N., Foley, J.A., 2012. Comparing the yields of organic and conventional agriculture. Nature. 485, 229–232. DOI: https://doi.org/10.1038/nature11069
[21] Ponisio, L.C., M’Gonigle, L.K., Mace, K.C., et al., 2015. Diversification practices reduce organic to conventional yield gap. Proceedings of the Royal Society B: Biological Sciences. 282(1799), 20141396. DOI: https://doi.org/10.1098/rspb.2014.1396
[22] Pretty, J., Benton, T.G., Bharucha, Z.P., et al., 2018. Global assessment of agricultural system redesign for sustainable intensification. Nature Sustainability. 1, 441–446. DOI: https://doi.org/10.1038/s41893-018-0114-0
[23] Tambo, J.A., Aliamo, C., Davis, T., et al., 2019. The impact of ICT-enabled extension campaign on farmers’ knowledge and management of fall armyworm in Uganda. PLoS ONE. 14(8), e0220844. DOI: https://doi.org/10.1371/journal.pone.0220844
[24] Lal, R., Sharan, B.R., Srinivasarao, C., et al., 2022. Greenhouse Gas Emission and Agronomic Productivity as Influenced by Varying Levels of N Fertilizer and Tank Silt in Degraded Semi-Arid Alfisol of Southern India. Land Degradation and Development. 34(4), 943–955.
[25] Campbell, B.M., Hansen, J., Stirling, C.M., et al., 2018. Urgent action to combat climate change and its impacts (SDG 13): Transforming agriculture and food systems. Current Opinion in Environmental Sustainability. 34, 13–20. DOI: https://doi.org/10.1016/j.cosust.2018.06.005
[26] Smith, P., Bustamante, M., Ahammad, H., et al., 2014. Agriculture, forestry and other land use (AFOLU). In: Edenhofer, O., Pichs-Madruga, R., Sokona, Y., et al. (Eds.). Climate Change 2014: Mitigation of Climate Change. Contribution of Working Group III to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change. Cambridge University Press: Cambridge, UK; New York, NY, USA. pp. 811–922.
[27] Gomiero, T., 2018. Agriculture and degrowth: State of the art and assessment of organic and biotech-based agriculture from a degrowth perspective. Journal of Cleaner Production. 197(Part 2), 1823–1839. DOI: https://doi.org/10.1016/j.jclepro.2017.03.237
[28] Crowder, D.W., Reganold, J.P., 2015. Financial competitiveness of organic agriculture on a global scale. Proceedings of the National Academy of Sciences. 112(24), 7611–7616. DOI: https://doi.org/10.1073/pnas.1423674112
[29] Jaffry, S., Pickering, H., Ghulam, Y., 2004. Consumer choices for quality and sustainability labeled seafood products in the UK. Food Policy. 29(3), 215–228.
[30] Barrett, C.B., Gómez, M.I., 2025. Fostering healthy, equitable, resilient, and sustainable agri-food value chains. Agricultural Economics. 56(3), 390–400. DOI: https://doi.org/10.1111/agec.70007
[31] Open Government Data (OGD) Platform India, n.d. Available from: https://www.data.gov.in (cited 10 September 2025).
[32] Government of India, Ministry of Statistics and Programme Implementation, n.d. Available from: https://www.mospi.gov.in/ (cited 10 September 2025).
[33] Wikipedia, n.d. Data.gov.in. Available from: https://en.wikipedia.org/wiki/Data.gov.in (cited 10 September 2025).
[34] Bergsten, A., Jiren, T.S., Leventon, J., et al., 2019. Identifying governance gaps among interlinked sustainability challenges. Environmental Science and Policy. 91, 27–38.
[35] Zulham, T., Hasan, M.I., Majid, H.N., et al., 2023. Economics of agricultural and coastal areas. Syiah Kuala University: Banda Aceh, Indonesia. (in Indonesian)
[36] Kawtrakul, A., Chanlekha, H., Waiyamai, K., et al., 2021. Towards Data-and-Innovation Driven Sustainable and Productive Agriculture: BIO-AGRI-WATCH as a Use Case Study. In Proceedings of the IEEE International Conference on Big Data, Orlando, FL, USA, 15–18 December 2021; pp. 3407–3415. DOI: https://doi.org/10.1109/BigData52589.2021.9671520
[37] Periola, A.A., Alonge, A.A., Ogudo, K.A. Networked computing systems for bio-diversity and environmental preservation. Scientific Reports. 12, 3249 (2022). DOI: https://doi.org/10.1038/s41598-022-07226-z
[38] Lopez-Cueva, M., Apaza-Cutipa, R., Araujo-Cotacallpa, R.L., et al., 2024. A Multi Moving Target Localization in Agricultural Farmlands by Employing Optimized Cooperative Unmanned Aerial Vehicle Swarm. Scalable Computing: Practice and Experience. 25(6), 4647–4660. DOI: https://doi.org/10.12694/scpe.v25i6.3130
[39] Ayasrah, F.T., Alsharafa, N.S., Sivaprakash, S., et al., 2024. Strategizing Low-Carbon Urban Planning through Environmental Impact Assessment by Artificial Intelligence-Driven Carbon Footprint Forecasting. Journal of Machine and Computing. 4(4), 1140–1151. DOI: https://doi.org/10.53759/7669/jmc202404105
[40] Roque-Claros, R.E., Flores-Llanos, D.P., Maquera-Humpiri, A.R., et al., 2024. UAV Path Planning Model Leveraging Machine Learning and Swarm Intelligence for Smart Agriculture. Scalable Computing: Practice and Experience. 25(5), 3752–3765. DOI: https://doi.org/10.12694/scpe.v25i5.3131
[41] Ghanimi, H.M.A., Suguna, R., Jeyaraj, J.P.G., et al., 2024. Smart Fertilizing Using IoT Multi-Sensor and Variable Rate Sprayer Integrated UAV. Scalable Computing: Practice and Experience. 25(5), 3766–3777. DOI: https://doi.org/10.12694/scpe.v25i5.3132
[42] Rahmani, M.K.I., Ghanimi, H.M., Jilani, S.F., et al., 2023. Early Pathogen Prediction in Crops Using Nano Biosensors and Neural Network-Based Feature Extraction and Classification. Big Data Research. 34, 100412. DOI: https://doi.org/10.1016/j.bdr.2023.100412
[43] Alsharafa, N.S., Sengan, S., Sri, S.T., et al., 2025. An Edge Assisted Internet of Things Model for Renewable Energy and Cost-Effective Greenhouse Crop Management. Journal of Machine and Computing. 5(1), 576–588. DOI: https://doi.org/10.53759/7669/jmc202505045
[44] Ali, H.M., Deivasigamani, A., Lal Karn, A., et al., 2024. The Influence of Direct Market Access on Profit Margins, Supply Chain Efficiency, and Economic Resilience for Small-Scale Dairy Farmers of Asian Country. Research on World Agricultural Economy. 6(1), 541–555. DOI: https://doi.org/10.36956/rwae.v6i1.1530
[45] Thiruvenkatasamy, K.V., Ghanimi, H.M.A., Sengan, S., et al., 2025. An online tool based on the Internet of Things and intelligent blockchain technology for data privacy and security in rural and agricultural development. Scientific Reports. 15, 27349. DOI: https://doi.org/10.1038/s41598-025-13231-9
[46] Hashim, N., Neo, T.G., Mohammed, M.N., et al., 2024. Toward sustainable smart cities: A new approach of solar and wind renewable energy in agriculture applications. In: Hamdan, A., Aldhaen, E.S. (Eds.). Artificial Intelligence and Transforming Digital Marketing: Studies in Systems, Decision and Control, Vol 487. Springer: Cham, Switzerland. pp. 555–563. DOI: https://doi.org/10.1007/978-3-031-35828-9_47