Abstract
This paper explores the integration of ChatGPT, a state-of-the-art language model, into sugar industry research. ChatGPT, developed by OpenAI, offers advanced natural language processing capabilities that have the potential to revolutionize research practices. By leveraging its vast knowledge base and conversational abilities, ChatGPT can automate literature reviews, provide up-to-date insights, and facilitate collaboration among researchers and industry professionals. It analyzes diverse data sources, identifies emerging trends, and contributes to strategic planning and product development. However, researchers must critically evaluate ChatGPT’s outputs due to the possibility of generating inaccurate or biased information. Its lack of deep contextual understanding and domain expertise requires careful interpretation. Ethical considerations, including biases in training data and data privacy, must be addressed to ensure responsible utilization. By understanding and mitigating these limitations, researchers can harness ChatGPT’s power to drive innovation, optimize processes, and improve operational efficiency in the sugar industry. Ongoing discussions, ethical guidelines, and transparent auditing mechanisms are essential for the responsible integration of ChatGPT in sugar industry research.
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References
Afiomah, C.S., and K.O. Iwuozor. 2020. Nutritional and phytochemical properties of beta vulgaris linnaeus (chenopodiaceae)–a review. Nigerian Journal of Pharmaceutical and Applied Science Research 9 (4): 38–44.
Biswas, S.S. 2023. Potential use of chat gpt in global warming. Annals of Biomedical Engineering 51 (6): 1126–1127. https://doi.org/10.1007/s10439-023-03171-8.
Dergaa, I., K. Chamari, P. Zmijewski, and H.B. Saad. 2023. From human writing to artificial intelligence generated text: examining the prospects and potential threats of ChatGPT in academic writing. Biology of Sport 40 (2): 615–622. https://doi.org/10.5114/biolsport.2023.125623.
Dwivedi, Y.K., N. Kshetri, L. Hughes, E.L. Slade, A. Jeyaraj, A.K. Kar, A.M. Baabdullah, A. Koohang, V. Raghavan, and M. Ahuja. 2023. “So what if ChatGPT wrote it?” Multidisciplinary perspectives on opportunities, challenges and implications of generative conversational AI for research, practice and policy. International Journal of Information Management 71: 102642. https://doi.org/10.1016/j.ijinfomgt.2023.102642.
Hassani, H., and E.S. Silva. 2023. The role of ChatGPT in data science: how ai-assisted conversational interfaces are revolutionizing the field. Big Data and Cognitive Computing 7 (2): 62. https://doi.org/10.3390/bdcc7020062.
Higgins, A., P. Thorburn, A. Archer, and E. Jakku. 2007. Opportunities for value chain research in sugar industries. Agricultural Systems 94 (3): 611–621. https://doi.org/10.1016/j.agsy.2007.02.011.
Iwuozor, K.O., L.A. Ogunfowora, and I.P. Oyekunle. 2021a. Review on sugarcane-mediated nanoparticle synthesis: a green approach. SugarTech 24: 1186–1197. https://doi.org/10.1007/s12355-021-01038-7.
Iwuozor, K.O., I.P. Oyekunle, I.O. Oladunjoye, E.M. Ibitogbe, and T.S. Olorunfemi. 2021b. A review on the mitigation of heavy metals from aqueous solution using sugarcane bagasse. SugarTech 24: 1167–1185. https://doi.org/10.1007/s12355-021-01051-w.
Iwuozor, K.O., A.G. Adeniyi, E.C. Emenike, M.I. Adepoju, and M.O. Ahmed. 2022a. Sugarcane juice powder produced from spray drying technology: A review of properties and operating parameters. SugarTech 25: 497–507. https://doi.org/10.1007/s12355-022-01211-6.
Iwuozor, K.O., V.U. Anyanwu, B.O. Olaniyi, P.S. Mbamalu, and A.G. Adeniyi. 2022b. Adulteration of sugar: a growing global menace. SugarTech 24: 914–919. https://doi.org/10.1007/s12355-022-01122-6.
Iwuozor, K.O., E.C. Emenike, M. Abdulkadir, S. Ogunniyi, and A.G. Adeniyi. 2022c. Effect of salt modification on biochar obtained from the thermochemical conversion of sugarcane bagasse. SugarTech 25: 223–233. https://doi.org/10.1007/s12355-022-01166-8.
Iwuozor, K.O., P.S. Mbamalu, B.O. Olaniyi, V.U. Anyanwu, E.C. Emenike, and A.G. Adeniyi. 2022d. Fortification of sugar: a call for action. SugarTech 24: 1284–1294. https://doi.org/10.1007/s12355-022-01183-7.
Iwuozor, K.O., E.C. Emenike, J.O. Ighalo, S. Eshiemogie, P.E. Omuku, and A.G. Adeniyi. 2022e. Valorization of sugar industry’s by-products: a perspective. SugarTech 24: 1052–1078. https://doi.org/10.1007/s12355-022-01143-1.
Iwuozor, K.O., E.C. Emenike, J.O. Ighalo, F.O. Omoarukhe, P.E. Omuku, and A.G. Adeniyi. 2022f. A review on the thermochemical conversion of sugarcane bagasse into biochar. Cleaner Materials 6: 100162. https://doi.org/10.1016/j.clema.2022.100162.
Iwuozor, K.O., A.G. Adeniyi, E.C. Emenike, B.O. Olaniyi, V.U. Anyanwu, J.O. Bamigbola, and H.T. Ojo. 2023a. Adsorption Technology in the Sugar Industry: Current Status and Future Perspectives. SugarTech. https://doi.org/10.1007/s12355-023-01272-1.
Iwuozor, K.O., A.G. Adeniyi, E.C. Emenike, T. Ojeyemi, A.U. Egbemhenghe, C.J. Okorie, B.D. Ayoku, and O.D. Saliu. 2023b. Prospects and challenges of utilizing sugarcane bagasse as a bio-coagulant precursor for water treatment. Biotechnology Reports 39: e00805. https://doi.org/10.1016/j.btre.2023.e00805.
Li, S.W., M.W. Kemp, S.J. Logan, P.S. Dimri, N. Singh, C.N. Mattar, P. Dashraath, H. Ramlal, A.P. Mahyuddin, and S. Kanayan. 2023. ChatGPT outscored human candidates in a virtual objective structured clinical examination in obstetrics and gynecology. American Journal of Obstetrics and Gynecology. https://doi.org/10.1016/j.ajog.2023.04.020.
Liebrenz, M., R. Schleifer, A. Buadze, D. Bhugra, and A. Smith. 2023. Generating scholarly content with ChatGPT: ethical challenges for medical publishing. The Lancet Digital Health 5 (3): e105–e106. https://doi.org/10.1016/S2589-7500(23)00019-5.
Mbakwe, A.B., I. Lourentzou, L.A. Celi, O.J. Mechanic, and A. Dagan. 2023. ChatGPT passing USMLE shines a spotlight on the flaws of medical education. PLOS Digit Health 2 (2): e0000205. https://doi.org/10.1371/journal.pdig.0000205.
Miao, Q., W. Zheng, Y. Lv, M. Huang, W. Ding, and F.-Y. Wang. 2023. DAO to HANOI via DeSci: AI paradigm shifts from AlphaGo to ChatGPT. IEEE/CAA Journal of Automatica Sinica 10 (4): 877–897. https://doi.org/10.1109/JAS.2023.123561.
Mijwil, M.M., K.K. Hiran, R. Doshi, M. Dadhich, A.-H. Al-Mistarehi, and I. Bala. 2023. ChatGPT and the future of academic integrity in the artificial intelligence era: a new frontier. Al-Salam Journal for Engineering and Technology 2 (2): 116–127.
Panda, S., and N. Kaur. 2023. Exploring the viability of ChatGPT as an alternative to traditional chatbot systems in library and information centers. Library Hi Tech News 40 (3): 22–25. https://doi.org/10.1108/LHTN-02-2023-0032.
Qureshi, R., D. Shaughnessy, K.A. Gill, K.A. Robinson, T. Li, and E. Agai. 2023. Are ChatGPT and large language models “the answer” to bringing us closer to systematic review automation? Systematic Reviews 12: 72. https://doi.org/10.1186/s13643-023-02243-z.
Ray, P.P. 2023. ChatGPT: A comprehensive review on background, applications, key challenges, bias, ethics, limitations and future scope. Internet of Things and Cyber-Physical Systems 3: 121–154. https://doi.org/10.1016/j.iotcps.2023.04.003.
Shen, Y., L. Heacock, J. Elias, K.D. Hentel, B. Reig, G. Shih, and L. Moy. 2023. ChatGPT and other large language models are double-edged swords. Radiological Society of North America 307 (2): e230163. https://doi.org/10.1148/radiol.230163.
Sifat, R.I. 2023. ChatGPT and the future of health policy analysis: potential and pitfalls of using ChatGPT in policymaking. Annals of Biomedical Engineering 51: 1357–1359. https://doi.org/10.1007/s10439-023-03204-2.
Sifat, R.I., and U. Bhattacharya. 2023. Transformative potential of artificial intelligence in global health policy. Journal of Market Access & Health Policy 11 (1): 2230660. https://doi.org/10.1080/20016689.2023.2230660.
Solomon, S. 2016. Sugarcane production and development of sugar industry in India. SugarTech 18: 588–602. https://doi.org/10.1007/s12355-016-0494-2.
Stanner, S., and A. Spiro. 2020. Public health rationale for reducing sugar: strategies and challenges. Nutrition Bulletin 45 (3): 253–270. https://doi.org/10.1111/nbu.12460.
Tan, R., S. Chew, X. Cleanthous, K. Anastasiou, P.G. Brooker, T. Pham, and B.P. Smith. 2021. Assessment of artificial and natural sweeteners present in packaged non-alcoholic beverages (NABs) sold on the Singapore market. BMC Public Health 21: 1866. https://doi.org/10.1186/s12889-021-11924-0.
Zhu, J.-J., J. Jiang, M. Yang, and Z.J. Ren. 2023. ChatGPT and environmental research. Environmental Science & Technology in Press. https://doi.org/10.1021/acs.est.3c01818.
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Iwuozor, K.O., Olaniyi, B.O., Anyanwu, V.U. et al. The Effect of ChatGPT on Sugar Industry Research. Sugar Tech 25, 1278–1284 (2023). https://doi.org/10.1007/s12355-023-01300-0
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DOI: https://doi.org/10.1007/s12355-023-01300-0