{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,22]],"date-time":"2026-07-22T16:34:25Z","timestamp":1784738065033,"version":"3.55.0"},"reference-count":40,"publisher":"MDPI AG","issue":"8","license":[{"start":{"date-parts":[[2025,7,24]],"date-time":"2025-07-24T00:00:00Z","timestamp":1753315200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"National Research Program for Universities (NRPU) of the Higher Education Commission (HEC) of Pakistan","award":["20-17332\/NRPU\/R&D\/HEC\/2021-2020"],"award-info":[{"award-number":["20-17332\/NRPU\/R&D\/HEC\/2021-2020"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Information"],"abstract":"<jats:p>The use of intelligent crop recommendation systems has become crucial in the era of smart agriculture to increase yield and enhance resource utilization. In this study, we compared different machine learning (ML), and deep learning (DL) models utilizing structured tabular data for crop recommendation. During our experimentation, both ML and DL models achieved decent performance. However, their architectures are not suited for setting up conversational systems. To overcome this limitation, we converted the structured tabular data to descriptive textual data and utilized it to fine-tune Large Language Models (LLMs), including BERT and GPT-2. In comprehensive experiments, we demonstrated that GPT-2 achieved a higher accuracy of 99.55% than the best-performing ML and DL models, while maintaining precision of 99.58% and recall of 99.55%. We also demonstrated that GPT-2 not only keeps up competitive accuracy but also offers natural language interaction capabilities. Due to this capability, it is a viable option to be used for real-time agricultural decision support systems.<\/jats:p>","DOI":"10.3390\/info16080632","type":"journal-article","created":{"date-parts":[[2025,7,24]],"date-time":"2025-07-24T14:11:44Z","timestamp":1753366304000},"page":"632","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":13,"title":["Evaluation of Learning-Based Models for Crop Recommendation in Smart Agriculture"],"prefix":"10.3390","volume":"16","author":[{"given":"Muhammad Abu","family":"Bakr","sequence":"first","affiliation":[{"name":"Department of Electrical Engineering, National University of Technology, Islamabad 44000, Pakistan"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ahmad Jaffar","family":"Khan","sequence":"additional","affiliation":[{"name":"Department of Electrical Engineering, National University of Technology, Islamabad 44000, Pakistan"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7406-8441","authenticated-orcid":false,"given":"Sultan Daud","family":"Khan","sequence":"additional","affiliation":[{"name":"Department of Computer Science, National University of Technology, Islamabad 44000, Pakistan"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5637-4798","authenticated-orcid":false,"given":"Mohammad Haseeb","family":"Zafar","sequence":"additional","affiliation":[{"name":"Cardiff School of Technologies, Cardiff Metropolitan University, Cardiff CF5 2YB, UK"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0222-6340","authenticated-orcid":false,"given":"Mohib","family":"Ullah","sequence":"additional","affiliation":[{"name":"Intelligent Systems and Analytics (ISA) Research Group, Department of Computer Science (IDI), Norwegian University of Science and Technology (NTNU), 2815 Gj\u00f8vik, Norway"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Habib","family":"Ullah","sequence":"additional","affiliation":[{"name":"Faculty of Science and Technology, Norwegian University of Life Sciences, 1433 \u00c5s, Norway"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2025,7,24]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","unstructured":"Pawlak, K., and Ko\u0142odziejczak, M. 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