Surveying the Awareness of Smart Agriculture Practices among Paddy Producers in Bafra Plain in Mid-Black Sea
Yıl 2024,
Cilt: 7 Sayı: 2, 132 - 141
İsa Akın
,
Gürkan A. K. Gürdil
,
Bahadır Demirel
Öz
Paddy fields in the northern part of Turkey are concentrated in the Bafra Plain in Mid-Black Sea region, where the highest wheat and leguminous production is performed. Turkey's longest river, Kızılırmak, flows into the Bafra plain. For this reason, it can be said that the most fertile lands in our country are in Bafra Plain and its surroundings. The aim of the present study is to determine the awareness of paddy producers located in the Bafra Plain about smart agriculture applications. A field survey has been conducted at the plain and the results were analyzed. Interviews were conducted in September 2024 with a total of 150 participants coming from different villages. 44% of farmers had more than 100 da paddy field each. At the end of the research some striking results were obtained. The level of awareness along with their reasons were determined. Awareness of smart agricultural tools was low at all. But, hopefully (3.3%) of farmers declared that the smart agriculture practices is and will keep on being important for the future in rice farming.
Kaynakça
- Adamides, G., Kalatzis, N., Stylianou, A., Marianos, N., Chatzipapadopoulos, F., Giannakopoulou, M., ... & Neocleous, D., 2020. Smart farming techniques for climate change adaptation in Cyprus. Atmosphere, 11(6), 557.
- Adesipo, A., Fadeyi, O., Kuca, K., Krejcar, O., Maresova, P., Selamat, A., & Adenola, M., 2020. Smart and climate-smart agricultural trends as core aspects of smart village functions. Sensors, 20(21), 5977.
- Albats, E., Bogers, M., & Podmetina, D., 2020. Companies’ human capital for university partnerships: A micro-foundational perspective. Technological Forecasting and Social Change, 157, 120085.
- Alfred, R., Obit, J. H., Chin, C. P. Y., Haviluddin, H., & Lim, Y., 2021. Towards paddy rice smart farming: a review on big data, machine learning, and rice production tasks. Ieee Access.
- Autio, A., Johansson, T., Motaroki, L., Minoia, P., & Pellikka, P., 2021. Constraints for adopting climate-smart agricultural practices among smallholder farmers in Southeast Kenya. Agricultural Systems, 194, 103284.
- Azadi, H., Moghaddam, S. M., Burkart, S., Mahmoudi, H., Van Passel, S., Kurban, A., & Lopez-Carr, D., 2021. Rethinking resilient agriculture: From climate-smart agriculture to vulnerable-smart agriculture. Journal of Cleaner Production, 319, 128602.
- Chuang, J. H., Wang, J. H., & Liou, Y. C., 2020. Farmers’ knowledge, attitude, and adoption of smart agriculture technology in Taiwan. International Journal of Environmental Research and Public Health, 17(19), 7236.
- Dewi, L. J. E., Wijaya, I. N. S. W., & Seputra, K. A., 2021. Web-based Buleleng regency agriculture product information system development. In Journal of Physics: Conference Series (Vol. 1810, No. 1, p. 012029). IOP Publishing.
- Dhanaraju, M., Chenniappan, P., Ramalingam, K., Pazhanivelan, S., & Kaliaperumal, R., 2022. Smart farming: Internet of Things (IoT)-based sustainable agriculture. Agriculture, 12(10), 1745.
- Gupta, A., & Nahar, P., 2023. Classification and yield prediction in smart agriculture system using IoT. Journal of Ambient Intelligence and Humanized Computing, 14(8), 10235-10244.
- Gürdil, G.A.K., Hidayat, B., Demirel, Cevher, E.Y, 2024. Smart Agriculture Application in Rice Cultivation. Jurnal Pertanian Tropik. 11(2), 009-021
- Hayes, D., Camacho, E. M., Ronaldson, A., Stepanian, K., McPhilbin, M., Elliott, R. A., ... & Slade, M., 2024. Evidence-based Recovery Colleges: developing a typology based on organisational characteristics, fidelity and funding. Social Psychiatry and Psychiatric Epidemiology, 59(5), 759-768.
- Hopkins, P. M., Girard, T., Dalay, S., Jenkins, B., Thacker, A., Patteril, M., & McGrady, E., 2021. Malignant hyperthermia 2020: Guideline from the Association of Anaesthetists. Anaesthesia, 76(5), 655-664.
- Javaid, M., Haleem, A., Singh, R. P., & Suman, R., 2022. Enhancing smart farming through the applications of Agriculture 4.0 technologies. International Journal of Intelligent Networks, 3, 150-164.
- Kwaghtyo, D. K. & Eke, C. I., 2023. Smart farming prediction models for precision agriculture: a comprehensive survey. Artificial Intelligence Review.
- Nguyen, L. L. H., Khuu, D. T., Halibas, A., & Nguyen, T. Q., 2024. Factors that influence the intention of smallholder rice farmers to adopt cleaner production practices: An empirical study of precision agriculture adoption. Evaluation Review, 48(4), 692-735.
- Onyeneke, R. U., Amadi, M. U., Njoku, C. L., & Osuji, E. E., 2021. Climate change perception and uptake of climate-smart agriculture in rice production in Ebonyi State, Nigeria. Atmosphere.
- Oo, S. P. & Usami, K., 2020. Farmers' perception of good agricultural practices in rice production in Myanmar: A case study of Myaungmya District, Ayeyarwady Region. Agriculture.
- Rani, S., Mishra, A. K., Kataria, A., Mallik, S., & Qin, H., 2023. Machine learning-based optimal crop selection system in smart agriculture. Scientific Reports.
- Roos Lindgreen, E., Opferkuch, K., Walker, A. M., Salomone, R., Reyes, T., Raggi, A., ... & Caeiro, S., 2022. Exploring assessment practices of companies actively engaged with circular economy. Business Strategy and the Environment, 31(4), 1414-1438.
- Santiteerakul, S., Sopadang, A., Yaibuathet Tippayawong, K., & Tamvimol, K., 2020. The role of smart technology in sustainable agriculture: A case study of wangree plant factory. Sustainability, 12(11), 4640.
- Sarkar, D., Kar, S. K., Chattopadhyay, A., Rakshit, A., Tripathi, V. K., Dubey, P. K., & Abhilash, P. C., 2020. Low input sustainable agriculture: A viable climate-smart option for boosting food production in a warming world. Ecological Indicators, 115, 106412.
- Smit, J. P. & Hessels, L. K., 2021. The production of scientific and societal value in research evaluation: a review of societal impact assessment methods. Research Evaluation.
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Orta Karadeniz Bafra Ovası'ndaki Çeltik Üreticilerinin Akıllı Tarım Uygulamalarına İlişkin Farkındalığının Araştırılması
Yıl 2024,
Cilt: 7 Sayı: 2, 132 - 141
İsa Akın
,
Gürkan A. K. Gürdil
,
Bahadır Demirel
Öz
Türkiye'nin kuzeyindeki çeltik tarlaları, en fazla buğday ve baklagil üretiminin yapıldığı Orta Karadeniz Bölgesi'ndeki Bafra Ovası'nda yoğunlaşmaktadır. Türkiye'nin en uzun nehri Kızılırmak Bafra Ovası'na akmaktadır. Bu nedenle ülkemizde en verimli toprakların Bafra Ovası ve çevresinde olduğu söylenebilir. Bu çalışmanın amacı Bafra Ovası'nda yer alan çeltik üreticilerinin akıllı tarım uygulamalarına ilişkin farkındalıklarının belirlenmesidir. Ovada arazi araştırması yapılmış ve sonuçları analiz edilmiştir. Eylül 2024'te farklı köylerden gelen toplam 150 katılımcıyla görüşmeler gerçekleştirildi. Çiftçilerin %44'ünün her birinin 100 dekardan fazla çeltik tarlası vardı. Araştırma sonunda çarpıcı sonuçlara ulaşıldı. Farkındalık düzeyleri ve nedenleri belirlendi. Akıllı tarım araçlarına yönelik farkındalık ise oldukça düşüktü. Ancak, umut verici bir şekilde çiftçilerin (%3.3) çeltik tarımında akıllı tarım uygulamalarının gelecek için önemli olduğunu ve önemli olmaya devam edeceğini ifade etmiştir.
Kaynakça
- Adamides, G., Kalatzis, N., Stylianou, A., Marianos, N., Chatzipapadopoulos, F., Giannakopoulou, M., ... & Neocleous, D., 2020. Smart farming techniques for climate change adaptation in Cyprus. Atmosphere, 11(6), 557.
- Adesipo, A., Fadeyi, O., Kuca, K., Krejcar, O., Maresova, P., Selamat, A., & Adenola, M., 2020. Smart and climate-smart agricultural trends as core aspects of smart village functions. Sensors, 20(21), 5977.
- Albats, E., Bogers, M., & Podmetina, D., 2020. Companies’ human capital for university partnerships: A micro-foundational perspective. Technological Forecasting and Social Change, 157, 120085.
- Alfred, R., Obit, J. H., Chin, C. P. Y., Haviluddin, H., & Lim, Y., 2021. Towards paddy rice smart farming: a review on big data, machine learning, and rice production tasks. Ieee Access.
- Autio, A., Johansson, T., Motaroki, L., Minoia, P., & Pellikka, P., 2021. Constraints for adopting climate-smart agricultural practices among smallholder farmers in Southeast Kenya. Agricultural Systems, 194, 103284.
- Azadi, H., Moghaddam, S. M., Burkart, S., Mahmoudi, H., Van Passel, S., Kurban, A., & Lopez-Carr, D., 2021. Rethinking resilient agriculture: From climate-smart agriculture to vulnerable-smart agriculture. Journal of Cleaner Production, 319, 128602.
- Chuang, J. H., Wang, J. H., & Liou, Y. C., 2020. Farmers’ knowledge, attitude, and adoption of smart agriculture technology in Taiwan. International Journal of Environmental Research and Public Health, 17(19), 7236.
- Dewi, L. J. E., Wijaya, I. N. S. W., & Seputra, K. A., 2021. Web-based Buleleng regency agriculture product information system development. In Journal of Physics: Conference Series (Vol. 1810, No. 1, p. 012029). IOP Publishing.
- Dhanaraju, M., Chenniappan, P., Ramalingam, K., Pazhanivelan, S., & Kaliaperumal, R., 2022. Smart farming: Internet of Things (IoT)-based sustainable agriculture. Agriculture, 12(10), 1745.
- Gupta, A., & Nahar, P., 2023. Classification and yield prediction in smart agriculture system using IoT. Journal of Ambient Intelligence and Humanized Computing, 14(8), 10235-10244.
- Gürdil, G.A.K., Hidayat, B., Demirel, Cevher, E.Y, 2024. Smart Agriculture Application in Rice Cultivation. Jurnal Pertanian Tropik. 11(2), 009-021
- Hayes, D., Camacho, E. M., Ronaldson, A., Stepanian, K., McPhilbin, M., Elliott, R. A., ... & Slade, M., 2024. Evidence-based Recovery Colleges: developing a typology based on organisational characteristics, fidelity and funding. Social Psychiatry and Psychiatric Epidemiology, 59(5), 759-768.
- Hopkins, P. M., Girard, T., Dalay, S., Jenkins, B., Thacker, A., Patteril, M., & McGrady, E., 2021. Malignant hyperthermia 2020: Guideline from the Association of Anaesthetists. Anaesthesia, 76(5), 655-664.
- Javaid, M., Haleem, A., Singh, R. P., & Suman, R., 2022. Enhancing smart farming through the applications of Agriculture 4.0 technologies. International Journal of Intelligent Networks, 3, 150-164.
- Kwaghtyo, D. K. & Eke, C. I., 2023. Smart farming prediction models for precision agriculture: a comprehensive survey. Artificial Intelligence Review.
- Nguyen, L. L. H., Khuu, D. T., Halibas, A., & Nguyen, T. Q., 2024. Factors that influence the intention of smallholder rice farmers to adopt cleaner production practices: An empirical study of precision agriculture adoption. Evaluation Review, 48(4), 692-735.
- Onyeneke, R. U., Amadi, M. U., Njoku, C. L., & Osuji, E. E., 2021. Climate change perception and uptake of climate-smart agriculture in rice production in Ebonyi State, Nigeria. Atmosphere.
- Oo, S. P. & Usami, K., 2020. Farmers' perception of good agricultural practices in rice production in Myanmar: A case study of Myaungmya District, Ayeyarwady Region. Agriculture.
- Rani, S., Mishra, A. K., Kataria, A., Mallik, S., & Qin, H., 2023. Machine learning-based optimal crop selection system in smart agriculture. Scientific Reports.
- Roos Lindgreen, E., Opferkuch, K., Walker, A. M., Salomone, R., Reyes, T., Raggi, A., ... & Caeiro, S., 2022. Exploring assessment practices of companies actively engaged with circular economy. Business Strategy and the Environment, 31(4), 1414-1438.
- Santiteerakul, S., Sopadang, A., Yaibuathet Tippayawong, K., & Tamvimol, K., 2020. The role of smart technology in sustainable agriculture: A case study of wangree plant factory. Sustainability, 12(11), 4640.
- Sarkar, D., Kar, S. K., Chattopadhyay, A., Rakshit, A., Tripathi, V. K., Dubey, P. K., & Abhilash, P. C., 2020. Low input sustainable agriculture: A viable climate-smart option for boosting food production in a warming world. Ecological Indicators, 115, 106412.
- Smit, J. P. & Hessels, L. K., 2021. The production of scientific and societal value in research evaluation: a review of societal impact assessment methods. Research Evaluation.
- Yin, H., Cao, Y., Marelli, B., Zeng, X., Mason, A. J., & Cao, C., 2021. Soil sensors and plant wearables for smart and precision agriculture. Advanced Materials, 33(20), 2007764.