Research Article: Smart tools and artificial intelligence for enhanced quality and safety in agriculture, fisheries, and aquaculture: A review

سال انتشار: 1404
نوع سند: مقاله ژورنالی
زبان: انگلیسی
مشاهده: 29

فایل این مقاله در 39 صفحه با فرمت PDF قابل دریافت می باشد

استخراج به نرم افزارهای پژوهشی:

لینک ثابت به این مقاله:

شناسه ملی سند علمی:

JR_JIFRO-24-4_013

تاریخ نمایه سازی: 19 مرداد 1404

چکیده مقاله:

This study investigates the transformative potential of smart tools and artificial intelligence (AI) in enhancing quality assurance and safety within the agriculture, fisheries, and aquaculture sectors. A structured analytical framework is used to evaluate key AI algorithms—Naive Bayes, Support Vector Machines (SVM), Deep Learning, Machine Learning (ML), Artificial Neural Networks (ANNs), Fuzzy Logic, and Random Forests—emphasizing their mathematical foundations and practical integration into intelligent systems. The convergence of AI with advanced technologies such as computer vision (CV), the Internet of Things (IoT), and sensor-based monitoring is identified as a catalyst for real-time decision-making, robust quality control, and improved operational efficiency across the food supply chain. In agriculture, AI-powered tools enable precision farming, early pest and disease detection, and data-driven crop health monitoring. In fisheries and aquaculture, intelligent systems support automated feeding, disease prediction, and sustainable resource utilization. This study applies a structured literature-based analysis combined with performance benchmarking from empirical studies, showcasing validated use cases and quantitative accuracy metrics across various AI applications. The integration of AI technologies significantly improves traceability, reduces post-harvest losses, and enhances food safety in complex supply networks. Reported outcomes indicate high performance, with accuracy rates exceeding ۸۰% in areas such as pathogen prediction, food recognition, microplastic detection, aquaculture optimization, and species classification. Specific applications show notable precision in microalgae classification (۹۷.۶۷–۹۷.۸۶%), seaweed identification (۹۳.۵%), and fish freshness assessment (up to ۱۰۰%). Despite these advancements, the study acknowledges ongoing challenges related to data standardization, infrastructure, and regulatory frameworks. The findings highlight the need for interdisciplinary collaboration and continuous innovation. Ultimately, the strategic adoption of AI and smart tools is essential for building resilient, secure, and sustainable food systems and also offers significant indicators for future research.

نویسندگان

I. Kilinc

Katip Celebi University, Fisheries Faculty, Fish Processing Technology Department, ۳۵۶۱۰ CiGli-Izmir, Turkiye

B. Kilinc

Ege University, Fisheries Faculty, Fish Processing Technology Department, ۳۵۱۰۰ Bornova-Izmir, Turkiye

C. Takma

Ege University, Agriculture Faculty, Animal Science Department, Biometry and Genetics Unit, ۳۵۱۰۰ Bornova-Izmir, Turkiye

Y. Gevrekci

Ege University, Agriculture Faculty, Animal Science Department, Biometry and Genetics Unit, ۳۵۱۰۰ Bornova-Izmir, Turkiye

مراجع و منابع این مقاله:

لیست زیر مراجع و منابع استفاده شده در این مقاله را نمایش می دهد. این مراجع به صورت کاملا ماشینی و بر اساس هوش مصنوعی استخراج شده اند و لذا ممکن است دارای اشکالاتی باشند که به مرور زمان دقت استخراج این محتوا افزایش می یابد. مراجعی که مقالات مربوط به آنها در سیویلیکا نمایه شده و پیدا شده اند، به خود مقاله لینک شده اند :
  • Alhasan, M., & Hasaneen, M. (۲۰۲۱). Digital imaging, technologies and ...
  • Ali, A. M. A., & Alrobaian, M. M. (۲۰۲۴). Strengths ...
  • Almoselhy, R. I. M., & Usmani, A. (۲۰۲۴). AI in ...
  • Amore, A., & Philip, S. (۲۰۲۳). Artificial intelligence in food ...
  • Assaf, S. (۲۰۲۴). Food Database Meets Artificial Intelligence: A New ...
  • Bagnulo, E., Strocchi, G., Bicchi, C., & Liberto, E. (۲۰۲۴). ...
  • Barthwal, R., Kathuria, D., Joshi, S., Kaler, R. S. S., ...
  • Beck, K. L., Haiminen, N., Agarwal, A., Carrieri, A. P., ...
  • Bhagat, S. K., Tung, T. M., & Yaseen, Z. M. ...
  • Caratti, A., Squara, S., Bicchi, C., Liberto, E., Vincenti, M., ...
  • Chang, J., Wang, H., Su, W., He, X., & Tan, ...
  • Chiang, A. L., & Hong, H. (۲۰۲۵). The Role of ...
  • Chong, J. W. R., Khoo, K. S., Chew, K. W., ...
  • Choudhary, B., Das, A., & Choudhary, V. (۲۰۲۵). Chapter Fourteen-Application ...
  • Chotwanvirat, P., Prachansuwan, A., Sridonpai, P., & Kriengsinyos, W. (۲۰۲۴). ...
  • Cortes, C., & Vapnik, V. (۱۹۹۵). Machine learning. Support vector ...
  • Das, P., Altemimi, A. B., Nath, P. C., Katyal, M., ...
  • Demirci, M. (۲۰۱۹). Destek Vektör Makineleri ve M۵ Karar Ağacı ...
  • Esmaeily, R., Razavi, M. A., & Razavi, S. H. (۲۰۲۴). ...
  • Feng, Y., Li, X., Zhang, Y., & Xie, T. (۲۰۲۳). ...
  • Feng, Y., Soni, A., Brightwell, G., Reis, M. M., Wang, ...
  • Fernandes, S., & DMello, A. (۲۰۲۵). Artificial intelligence in the ...
  • Frank, B. (۲۰۲۴). Consumer preferences for artificial intelligence-enhanced products: Differences ...
  • Gao, Z., Huang, J., Chen, J., Shao, T., Ni, H., ...
  • Genç, İ. Y., Gürfidan, R., & Yiğit, T. (۲۰۲۵). Quality ...
  • Gladju, J., Kamalam, B. S., & Kanagaraj, A. (۲۰۲۲). Applications ...
  • Goodfellow, I., Bengio, Y., & Courville, A. (۲۰۱۶). Deep learning ...
  • Grira, S., Mozumder, M. S., Mourad, A. H. I., Ramadan, ...
  • Goyache, F., Bahamonde, A., Alonso, J., Lopez, S., Coz, J. ...
  • Goulart, F., Anna, V. S., Almli, V. L., & Maschio, ...
  • Guo, Y., Liu, Y., Oerlemans, A., Lao, S., Wu, S., ...
  • Hashemi, S., Vosough, P., Taghizadeh, S., & Savardashtaki, A. (۲۰۲۴). ...
  • Hassoun, A., Dankar, I., Bhat, Z., & Bouzembrak, Y. (۲۰۲۴). ...
  • Hinton, G. E., Osindero, S., & Teh, Y. W. (۲۰۰۶). ...
  • Huang, J., Zhang, M., Mujumdar, A. S., & Li, C. ...
  • Hwa, L. S., & Chuan, L. T. (۲۰۲۴). A Brief ...
  • Jadhav, H. B., Alaskar, K., Desai, V., Sane, A., Choudhary, ...
  • Kandilci, M., Yakıcı, G., & Kayar, M. B. (۲۰۲۴). Artificial ...
  • Karanth, S., Benefo, E. O., Patra, D., & Pradhan, A. ...
  • Kaushal, S., Tammineni, D. K., Rana, P., Sharma, M., Sridhar, ...
  • Khokher, M. R., Little, L. R., Tuck, G. N., Smith, ...
  • Kılınç, B., Kılınç, İ., & Takma, Ç. (۲۰۲۲). Chapter ۴ ...
  • Kılınç, B., Takma, C., & Kılınç, I. (۲۰۲۳a). Chapter ۱۰ ...
  • Kılınç, B., Kılınç, I., Takma, Ç., & Gevrekçi, Y. (۲۰۲۳b). ...
  • Kılınç, B., Kılınç, İ., Takma, Ç., & Gevrekçi, Y. (۲۰۲۴a). ...
  • Kılınç, İ., Kılınç, B., & Takma, Ç. (۲۰۲۲). Chapter ۴, ...
  • Kılınç, İ., Kılınç, B., Gevrekçi, Y., & Takma, Ç. (۲۰۲۴b). ...
  • Kilinc, I. (۲۰۲۴). The Place of Industry ۴.۰ Artificial Intelligence ...
  • Kutyauripo, I., Rushambwa, M., & Chiwazi, L. (۲۰۲۳). Artificial intelligence ...
  • Medina, V. Y. (۲۰۲۳). Predictive Microbiology and Machine Learning by ...
  • Nawaz, A., Afzal, A., Khatibi, A., Shankar, A., Madan, H., ...
  • Niu, H., Zhang, M., Yu, Q., & Liu, Y. (۲۰۲۴). ...
  • Nunes, C. A., Ribeiro, M. N., Carvalho, T. C., Ferreira, ...
  • O’Shea, N., Greene, D., & Fenelon, M. A. (۲۰۲۴). Artificial ...
  • Othman, S., Mavani, N. R., Hussain, M. A., Rahman, N. ...
  • Pajila, P. B., Sheena, B. G., Gayathri, A., Aswini, J., ...
  • Pane, R. A., Mubarok, S. M., & Huda, N. S. ...
  • Pantanowitz, L., Hanna, M., Pantanowitz, J., Lennerz, J., Henricks, W. ...
  • Ramandani, A. A., Chong, J. W. R., Srinuanpan, S., Lim, ...
  • Rather, M. A., Ahmad, I., Shah, A., Hajam, Y. A., ...
  • Rochva, S., Teimourpour, B., & Soltani, A. H. (۲۰۲۴). Computer ...
  • Schmidhuber, J. (۲۰۱۵). Deep learning in neural networks: An overview. ...
  • Shamtej, S. R. B. S., Jacob, S. G. B. A., ...
  • Sharifmousavi, M., Kayvanfar, V., & Baldacci, R. (۲۰۲۴). Distributed Artificial ...
  • Sharma, P., Vimal, A., Vishvakarma, R., Kumar, P., Vandenberghe, L. ...
  • Sherbini, A. E., Rosenson, R. S., Rifai, M. A., Virk, ...
  • Singh, Y., Kaur, A., & Malhora, R. (۲۰۰۹). Application of ...
  • Singh, S. K., Jha, R., Pandey, S., Mohan, C., Ghosh, ...
  • Srinivasan, A., Gupta, A., & Narayanamurthy, V. (۲۰۲۵). A comprehensive ...
  • Sriprateep, K., Pitakaso, R., Khonjun, S., Luesak, P., Jutagate, A., ...
  • Subramanian, R. S., & Prabha, D. (۲۰۲۲). Ensemble variable selection ...
  • Thapa, A., Nishad, S., Biswas, D., & Roy, S. (۲۰۲۳). ...
  • Thibault, B., Zeynoddin, M., Bonakdari, H., Ratti, C., & Khalloufi, ...
  • Ubina, N. A., Lan, H. Y., Cheng, S. C., Chang, ...
  • Vapnik, V. (۱۹۹۵). The Nature of Statistical Learning Theory. Springer ...
  • Vapnik, V., Golowich, S., & Smola, A. (۱۹۹۷). Support vector ...
  • Welch, H., Ames, R. T., Kolla, N., Kroodsma, D. A., ...
  • Widyawati, D., Faradibah, A., & Belluano, P. L. L. (۲۰۲۳). ...
  • Wu, X., Kumar, V., Quinlan, J. R., Ghosh, J., Yang, ...
  • Xing, W., & Du, D. (۲۰۱۸). Dropout Prediction in MOOCs: ...
  • Yan, L., Zhang, B., Zhou, W., Hao, J., Shi, H., ...
  • Yang, Y., Du, Y., Gupta, V. K., Ahmad, F., Amiri, ...
  • Yang, T., Zhang, X., Yan, Y., Liu, Y., Lin, X., ...
  • Yasin, E. T., Özkan, İ. A., & Koklu, M. (۲۰۲۳). ...
  • Yi, L., Wang, W., Diao, Y., Yi, S., Shang, Y., ...
  • Yu, W., Ouyang, Z., Zhang, Y., Lu, Y., Wei, C., ...
  • Yuan, J., Ma, D., Yang, Y., Zhao, Y., Ren, H., ...
  • Xu, Q., Zhou, Y., & Wu, L. (۲۰۲۴). Advancing tea ...
  • Zatsu, V., Shine, A. E., Tharakan, J. M., Peter, D., ...
  • Zhang, H., Ding, Y., Niu, J., & Jung, S. (۲۰۲۴). ...
  • نمایش کامل مراجع