Agriculture 4.0 and Viticulture: the Current Status of Digital Technologies And Future Perspectives
Özet
Agriculture 4.0 refers to the integration of advanced technologies such as digitization, automation, and data analytics in the agricultural sector. This study examines the current status and future potential of Agriculture 4.0 applications in viticulture. Innovations such as sensor technologies, drones, and AI-supported decision-making systems are utilized to enhance productivity, optimize resource use, and promote sustainability. For major agricultural economies like Türkiye, the adoption of these technologies is crucial for improving food security and minimizing environmental impacts. The study evaluates the strengths and weaknesses of Agriculture 4.0, highlighting weaknesses such as the lack of digital literacy and strengths like access to smart farming technologies. In conclusion, while Agriculture 4.0 holds significant potential for increasing efficiency in viticulture, overcoming challenges requires investments in training and infrastructure.
Referanslar
Abbasi, R., Martinez, P., & Ahmad, R. (2022). The digitization of the agricultural industry–A systematic literature review on Agriculture 4.0. Smart Agricultural Technology, 2, 100042.
Acun, D. Z. A. (2024). Development of herbicide-tolerant carrot genotypes using the CRISPR/Cas9 cytidine base-editing technique.
Agin, O., & Malasli, M. Z. (2016). The role and importance of image processing techniques in sustainable agriculture: A literature review. Journal of Agricultural Machinery Science, 12(3), 199-206.
Agizan, K., Bayramoglu, Z., & Agizan, S. (2022). The advantages of smart farming technologies for agricultural business management. Turkish Journal of Agriculture-Food Science and Technology, 10(9), 1697-1706.
Akin, T., Yildirim, C., & Cakan, H. (2015). Information-based decision support systems in agriculture and livestock.
Akman, A. Z. (2023). The place of the interaction between digital transformation and organizational culture in Society 5.0 structuring: A field study (Doctoral dissertation, Necmettin Erbakan University).
Aksoy, C. (2024). Digital transformation of businesses and the digital leadership approach. Journal of Quality and Strategy Management, 4(1), 1-29.
Aldag, M. C., & Eker, B. (2018). Artificial intelligence applications in the manufacturing of agricultural machinery. International Refereed Journal of Engineering and Sciences, 1.
Alkan, B., & Ozgunaltay Ertugrul, G. (2022). Pesticide applications with agricultural unmanned aerial vehicles. Kirsehir Ahi Evran University Journal of Agriculture Faculty, 2(2), 232-238.
Al-Saffar, B. S. F. (2019). Implementation and performance evaluation of classifiers SVM, CNN, and ANN in vineyard estimation (Master's thesis, Institute of Natural Sciences).
Altas, Z., Ozguven, M. M., & Yanar, Y. (2018). Determination of sugar beet leaf spot disease level (Cercospora beticola Sacc.) with image processing techniques using drones. Current Investigations in Agriculture and Current Research, 5(3), 621-631. https://doi.org/10.32474/CIACR.2018.05.000214
Altin, O. (2021). Analysis of the use of information and communication technologies in agricultural extension and marketing services by members of agricultural producer unions: The case of Tokat province.
Ammoniaci, M., Kartsiotis, S. P., Perria, R., & Storchi, P. (2021). State of the art of monitoring technologies and data processing for precision viticulture. Agriculture, 11(3), 201.
Anonymous. (2014). https://mis.sadievrenseker.com/2014/02/karar-destek-sistemleri-kds-decision-support-systems-dss/
Anonymous. (2021). https://www.platinonline.com/tarim-4-0/tarimda-fark-yaratan-4-ulke-1079290
Anonymous. (2022). https://www.elaisian.com/en/2022/07/18/viticulture-4-0-what-is-there-to-know/
Apolo-Apolo, O. E., Martínez-Guanter, J., Egea, G., Raja, P., & Pérez-Ruiz, M. (2020). Deep learning techniques for estimation of yield and size of citrus fruits using a UAV. European Journal of Agronomy, 115, 126030.
Araujo, J., Pimenta, V., Campos, J., Pinheiro, P., Porto, J. V., Manso, J., ... & Graca, A. (2023). Innovation co-development for viticulture and enology: Novel tele-detection web-service fuses vineyard data. BIO Web of Conferences, 56, 01006.
Arklan, U. (2008). Information society and communication: The role of mass communication tools and the internet in the dissemination of information. Selcuk Communication, 5(3), 67-80.
Arslan, U., Erbek, E., & Ozyoruk, A. (2018). Determination of pesticide use attitudes and behaviors of fruit producers in Gursu and Kestel districts of Bursa province. Bursa Uludag University Journal of Agriculture Faculty, 32(2), 69-74.
Atak, A. (2024). Recent table grape breeding studies worldwide. Bahce, 53(Special Issue 1), 14-22.
Aydin, N. (2022). Information technologies in the agricultural sector. Balkan & Near Eastern Journal of Social Sciences (BNEJSS), 8.
Aydinbas, G. (2024). Identification of factors related to agricultural productivity: The case of BRICS-T countries. Turkish Journal of Agriculture and Natural Sciences, 11(2), 524-535.
Bal, C. E., & Bal, H. C. (2023). Effects of Industry 4.0 applications on the agriculture sector and economic growth. Third Sector Social Economic Review, 58(3), 2553-2572.
Baran, E., & Ersoy Karacuha, M. (2021). Adapting to global climate change: Smart agriculture practices and occupational health and safety. Proceedings of the National Occupational Health and Safety Student Congress, Istanbul, 13-20.
Baran, M. F., Belliturk, K., & Celik, A. (2023). Preface, Environmental Pressures, and Agriculture. ISBN: 978-625-367-436-6. Ankara, Turkey.
Barrile, V., Simonetti, S., Citroni, R., Fotia, A., & Bilotta, G. (2022). Experimenting Agriculture 4.0 with sensors: A data fusion approach between remote sensing, UAVs, and self-driving tractors. Sensors, 22(20), 7910.
Bento, C., da Cunha, P. R., & Barata, J. (2019). Cultivating sociomaterial transformations in agriculture 4.0: The case of precision viticulture.
Bicakci, S. N. (2019). Internet of Things. Takvim-i vekayi, 7(1), 24-36.
Bilgin, I., & Medeni, T. D. (2023). SWOT analysis for the digitalization of agricultural service delivery: Connectivity between the Ministry of Agriculture and Forestry and KAYSIS. Journal of Public Administration and Technology, 4(2), 189-217. https://doi.org/10.58307/kaytek.1175247
Bohler, J. E., Schaepman, M. E., & Kneubühler, M. (2020). Crop separability from individual and combined airborne imaging spectroscopy and UAV multispectral data. Remote Sensing, 12(8), 1256. https://doi.org/10.3390/rs12081256
Borghi, M., Pacifico, D., Crucitti, D., Squartini, A., Berger, M. M., Gamboni, M., ... & Zottini, M. (2024). Smart selection of soil microbes for resilient and sustainable viticulture. The Plant Journal.
Brunori, E., Moresi, F. V., Maesano, M., De Horatis, M., Salvati, R., Mugnozza, G. S., & Biasi, R. (2022). Field survey and UAV remote sensing as tools for evaluating the canopy management effects in smallholder grapevine farms. In BIO Web of Conferences (Vol. 44, p. 05001). EDP Sciences.
Caglar, N., & Sensoy, S. (2021). Vegetable Breeding, Volume II: Cucurbitaceae (Kabakgiller) (A. Abak, A. Balkaya, S. S. Ellialtioglu, & E. Duzyaman, Eds.). Volume 2, pp. 95-197. Gece Kitapligi Publishing, Ankara.
Cakır, Ö. Ü. A., & İşlek, Ö. G. F. (2021). Chapter 7: Turkey’s Smart Agriculture (Agriculture 4.0) Potential. In Organic Agriculture and Agro-Ecological Developments in Turkey (pp. 155).
Cakmakci, M. F., & Cakmakci, R. (2023). Remote sensing, artificial intelligence, and future smart agriculture technology trends. European Journal of Science and Technology, 52, 234-246.
Cam, M. (2023). Innovative agricultural practices in a human-centered society: The case of Kasaplar Village (Order No. 30822686). Available from ProQuest Dissertations & Theses Global. (2925078183). Retrieved from https://www.proquest.com/dissertations-theses/innovative-agricultural-practices-human-centered/docview/2925078183/se-2
CEBIT. (2020). https://japan.kantei.go.jp/97_abe/statement/201703/1221682_11573.html
Cengiz, B., & Daş, R. (2022). Data fusion: Data sources, architectures, challenges, and solution approaches. Fırat University Journal of Engineering Sciences, 34(2), 899-922.
Cengiz, S. A., & Demirel, M. (2019). Reflections of the Industry 4.0 process on the education system: The example of Turkey (Master's thesis, Nevşehir Hacı Bektaş Veli University).
Cesco, S., Pii, Y., Borruso, L., Orzes, G., Lugli, P., Mazzetto, F., ... & Mimmo, T. (2021). A smart and sustainable future for viticulture is rooted in soil: How to face Cu toxicity. Applied Sciences, 11(3), 907.
Chen, C. J., Huang, Y. Y., Lu, Y. S., Chen, Y. C., Chang, C. Y., & Huang, Y. M. (2021). Identification of fruit tree pests with deep learning on embedded drones to achieve accurate pesticide spraying. IEEE Access, 9, 21986-21997. https://doi.org/10.1109/ACCESS.2021.3056082
Çokuysal, B. (2021). Ethical issues in the triangle of agriculture, digitalization, and sustainability. Proceedings Book of the Congress, 294.
Compant, S., & Mathieu, F. (Eds.). (2016). Biocontrol of major grapevine diseases: Leading research. CABI.
Demir, Ü., Kula, N., & Uğurlu, B. (2021). A decision support model proposal for the use of artificial intelligence in agriculture: An example of tomato pest detection. Lapseki Vocational School Journal of Applied Research, 2(4), 91-108.
Dogan, A., & Guzel, D. U. (2020). Development of a spatial decision support system using GIS techniques in Amur grape (Vitis amurensis Rupr.) cultivation: The case of Erciş-Van (Turkey). Euroasia Journal of Mathematics, Engineering, Natural & Medical Sciences, 7(13), 227-243.
Dogancukuru, H. (2009). Mobile applications as an alternative communication tool in agricultural extension in Konya province: Development opportunities.
Dogru, B., & Meçik, O. (2018). Effects of Industry 4.0 on the labor market in Turkey: Firm expectations. Suleyman Demirel University Journal of Economic and Administrative Sciences, 23(Special Issue on Industry 4.0 and Organizational Change), 1581-1606.
Dolo, A. (2018). Flood modeling based on drone data for the Arhavi district (Master's thesis, Institute of Social Sciences).
Dorofeeva, A. A., Ponomarenko, E. A., Lukyanova, Y. Y., Fomina, E. A., & Buchatskiy, P. Y. (2021). High precision unmanned agro copters in eco-friendly viticulture systems. In CEUR Workshop Proceedings (Vol. 2914, pp. 299-306).
Dressler, M., & Paunovic, I. (2021). Sensing technologies, roles, and technology adoption strategies for digital transformation of grape harvesting in SME wineries. Journal of Open Innovation: Technology, Market, and Complexity, 7(2), 123.
Duman, Ö. G. D. B., & Şen, E. B. (2019). Chapter 3: The Internet of Things in the context of blockchain technology. In New Approaches in the Field of Engineering in Turkey: The Internet of Things in Engineering (pp. 29-64). Ankara, Turkey.
Durna Daştan, S. (2023). The future of plant biotechnology and the conservation of plant genetic resources. In Current Applications and Assessments in Plant Biotechnology (Chapter 1). Lyon.
Elciyar, K. (2018). Internet of Things and concerns. In 1st International CICMS Conference, May 4-5, 2018, Kusadasi, Turkey (p. 336).
Ercan, Ş., Öztep, R., Güler, D., & Saner, G. (2019). Assessment of Agriculture 4.0 and its applicability in Turkey. Journal of Agricultural Economics, 25(2), 259-265. https://doi.org/10.24181/tarekoder.650762
Ertas, B. (2020). A sustainable future with Agriculture 4.0. Icontech International Journal, 4(1), 1-12.
Faoro, A., Romero, M. E., & Frausin, M. (2022). Inclusion of ICT skills, digital literacy, and open-source platforms in the teaching of industrial design applied to smart agriculture. In EDULEARN22 Proceedings (pp. 9027-9031). IATED.
Ferro, M. V., & Catania, P. (2023). Technologies and innovative methods for precision viticulture: A comprehensive review. Horticulturae, 9(3), 399.
Ford-Lloyd, B. V., & Jackson, M. T. (1991). Biotechnology and methods of conservation of plant genetic resources.
Gago, J., Douthe, C., Coopman, R. E., Gallego, P. P., Ribas-Carbo, M., Flexas, J., Escalona, J., & Medrano, H. (2015). UAVs challenge to assess water stress for sustainable agriculture. Agricultural Water Management, 153, 9–19. https://doi.org/10.1016/j.agwat.2015.01.020
Gazioglu Sensoy, R. I., & Balta, F. (2011). Identification of some local grapevine forms from the Van region and their characterization using RAPD markers. Journal of the Institute of Science and Technology, 1(3), 41-56.
Giordano, S., & Verrastro, V. (2020). IoT technologies in viticulture: Innovation and sustainability. The IoF Project case study. GeoProgress Journal, 7(1), 57-72.
Govez, E. (2023). An innovative perspective on the agricultural sector: Agriculture 4.0. In Social Issues (Theories, Policies, Applications) (p. 87). Efe Akademi Publications, Istanbul, Turkey.
Gucenmez, T. (2023). The impact of digital transformation on labor markets in Turkey and the relationship with income distribution. Kahramanmaraş Sütçü İmam University Journal of Social Sciences, 20(3), 995-1005. https://doi.org/10.33437/ksusbd.1361092
Gulcubuk, B., & Aluftekin, N. (2006). The use of internet-based information systems in rural development. In XI. Internet Conference in Turkey, 21-23.
Gungor, E., & Demiryürek, K. (2021). Genetically modified organisms in Turkey. Journal of Agricultural Economics Research, 7(2), 140-154.
Guzel, D. U., & Dogan, A. (2020). Identification of potential areas for grape (Vitis spp.) cultivation in the Erciş (Van) region using geographic information systems (GIS) techniques based on climate, soil, and topography factors. Yuzuncu Yil University Journal of Agricultural Sciences, 30(4), 672-687. https://doi.org/10.29133/yyutbd.752603
Kadagan, O., & Gurbuz, I. B. (2022). Consumers' perceptions and attitudes towards precision agriculture applications: A case study of Bursa Province. Balkan & Near Eastern Journal of Social Sciences (BNEJSS), 8.
Karaman, N., Aksoy, S., Cesur, F., & Saygin, F. (2022). Determining the impact of urbanization on agricultural lands using remote sensing and geographic information system techniques. Journal of Agricultural Research in Turkey, 9(3), 385-394.
Kazancoglu, Y., Lafci, C., Kumar, A., Luthra, S., Garza‐Reyes, J. A., & Berberoglu, Y. (2024). The role of agri‐food 4.0 in climate‐smart farming for controlling climate change‐related risks: A business perspective analysis. Business Strategy and the Environment, 33(4), 2788-2802.
Kerkech, M., Hafiane, A., & Canals, R. (2020). Vine disease detection in UAV multispectral images using optimized image registration and deep learning segmentation approach. Computers and Electronics in Agriculture, 174, 105446. https://doi.org/10.1016/j.compag.2020.105446
Kilavuz, E., & Erdem, I. (2019). Agriculture 4.0 applications worldwide and the transformation of Turkish agriculture. Social Sciences, 14(4), 133-157.
Kilic, S., & Alkan, R. M. (2018). The fourth industrial revolution Industry 4.0: Evaluations of the world and Turkey. Journal of Entrepreneurship Innovation and Marketing Research, 2(3), 29-49.
Koken, A. (2019). Drying of Sultani seedless grape variety (Vitis vinifera L.) in a solar-powered tunnel dryer and dryer automation (Master's thesis, Graduate School of Education).
Korkmaz, M. K. (2023). Sustainability, agriculture, future. In The Role and Importance of Agricultural Activities in Sustainable Development (p. 151).
Mattivi, P., Pappalardo, S. E., Nikolic, N., Mandolesi, L., Persichetti, A., Marchi, M. D., & Masin, R. (2021). Can commercial low-cost drones and open-source GIS technologies be suitable for semiautomatic weed mapping for smart farming? A case study in northeastern Italy. Remote Sensing, 13(10), 1869. https://doi.org/10.3390/rs13101869
Mazzon, F. (2019). Smart and digital agrifood: Evidence from six case studies. Università Ca' Foscari Venezia.
Mehedi, I. M., Hanif, M. S., Bilal, M., Vellingiri, M. T., & Palaniswamy, T. (2024). Remote sensing and decision support system applications in precision agriculture: Challenges and possibilities. IEEE Access.
Onder, N. (2023). Industry 4.0 and the labor market. Financial Analysis Journal, 33(175).
Oreški, D., Pihir, I., & Cajzek, K. (2021, September). Smart agriculture and digital transformation: A case of an intelligent system for wine quality prediction. In 2021 44th International Convention on Information, Communication and Electronic Technology (MIPRO) (pp. 1370-1375). IEEE.
Ozguven, M. M., Altas, Z., Guven, D., & Cam, A. (2022). The use and future of drones in agriculture. Ordu University Journal of Science and Technology, 12(1), 64-83. https://doi.org/10.54370/ordubtd.1097519
Pagliai, A., Ammoniaci, M., Sarri, D., Lisci, R., Perria, R., Vieri, M., ... & Kartsiotis, S. P. (2022). Comparison of aerial and ground 3D point clouds for canopy size assessment in precision viticulture. Remote Sensing, 14(5), 1145.
Pakdemirli, B., Birişik, N., Aslan, I., Sönmez, B., & Gezici, M. (2021). The use of digital technologies in Turkish agriculture and Agriculture 4.0 in the agriculture-food chain. Soil and Water Journal, 10(1), 78-87.
Pampuri, A., Giovenzana, V., Tugnolo, A., Casson, A., Vignati, S., Guidetti, R., & Beghi, R. (2022). Grape-HAND: A smart optical prototype for measuring grapes' qualitative parameters.
Pampuri, A., Tugnolo, A., Giovenzana, V., Casson, A., Guidetti, R., & Beghi, R. (2021). Design of cost-effective LED-based prototypes for the evaluation of grape (Vitis vinifera L.) ripeness. Computers and Electronics in Agriculture, 189, 106381.
Pampuri, A., Tugnolo, A., Giovenzana, V., Casson, A., Pozzoli, C., Brancadoro, L., ... & Beghi, R. (2022). Application of a cost-effective visible/near infrared optical prototype for the measurement of qualitative parameters of Chardonnay grapes. Applied Sciences, 12(10), 4853.
Pampuri, A., Tugnolo, A., Giovenzana, V., Vignati, S., Casson, A., Zambelli, M., ... & Guidetti, R. (2022). Grape polyphenol content prediction through vis/NIR spectroscopy for real-time application at winery consignment.
Quarato, C. (2018). FerMentor connected system: A sustainable approach for innovating traditional farms (Doctoral dissertation, Politecnico di Torino).
Reis, M. J. C. S., Morais, R., Peres, E., Pereira, C., Contente, O., Soares, S., Valente, A., Baptista, J., Ferreira, P. J. S. G., & Cruz, J. B. (2012). Automatic detection of bunches of grapes in a natural environment from color images. Journal of Applied Logic, 10, 285–290.
Romualdi, M. (2019). Viticulture 4.0: Preliminary tests in a wine company in Abruzzo.
Sahin, H. (2022). Digital Agriculture, Agriculture 4.0, Smart Agriculture, Robotic Applications, and Autonomous Systems. Journal of Agricultural Machinery Science, 18(2), 68-83.
Sanchez, L. O. S., Miranda, R. C., Escalante, J. J. G., Pacheco, I. T., Gonzalez, R. G. G., Miranda, C. L. C., & Lumbreras, P. D. A. (2011). Scale invariant feature approach for insect monitoring. Computers and Electronics in Agriculture, 75, 92–99.
Sarac, H. (2022). The rise of automation: mass unemployment or new employment? An evaluation of its impact on the labor market. Journal of Labor Relations, 13(2), 55-76.
Sarri, D., Lombardo, S., Pagliai, A., Perna, C., Lisci, R., De Pascale, V., ... & Vieri, M. (2020). Smart farming introduction in wine farms: A systematic review and a new proposal. Sustainability, 12(17), 7191.
Sassu, A., Gambella, F., Ghiani, L., Mercenaro, L., Caria, M., & Pazzona, A. L. (2021). Advances in unmanned aerial system remote sensing for precision viticulture. Sensors, 21(3), 956.
Saygili, F., Kaya, A. A., Çalışkan, E. T., & Kozal, Ö. E. (2018). Global integration of Turkish agriculture and Agriculture 4.0. Izmir Commodity Exchange, Publication No: 98, Izmir.
Senol, C. (2021). Innovation, Support, Sustainability: The Turkish Economy and Agriculture. International Journal of Geography and Geography Education, (44), 475-488.
Sevli, O. (2023). A digital agriculture application on the scale of Agriculture 4.0: Farm Monitoring and Management System. International Journal of Sustainable Engineering and Technology, 7(2), 105-116.
Sheikh, M. (2022). The impact of artificial intelligence usage on the labor market. Journal of Economics and Political Sciences, 2(1), 102-111.
Tanyolac, B., Kaya, H. B., Soya, S., & Akkale, C. (2010). Biotechnology and bioinformatics. In A. Yıldırım, F. Bardakçı, & M. Karataş (Eds.), Nobel Publication Distribution (pp. 601-638). Ankara.
Terribile, F., Bonfante, A., D'Antonio, A., De Mascellis, R., De Michele, C., Langella, G., ... and Basile, A. (2017). A geospatial decision support system for supporting quality viticulture at the landscape scale. Computers and Electronics in Agriculture, 140, 88-102.
Tugnolo, A., Giovenzana, V., Vignati, S., Pampuri, A., Casson, A., Zambelli, M., ... & Beghi, R. (2022). Development of a cost-effective IoT hyperspectral device for distributed and autonomous monitoring of vine crops.
Turgut, K. B. K. (2020). Current status and future of biotechnology and biosecurity in agriculture. Proceedings of the IX Technical Congress of Agricultural Engineering in Turkey, 281.
Turker, M. M. O. U., Akdemir, B., Acar, A. C. A. I., Ozturk, R., & Eminoglu, M. B. (2020). The digital age in agriculture. Proceedings of the IX Technical Congress of Agricultural Engineering in Turkey, 55.
Tziolas, E., Karapatzak, E., Kalathas, I., Karampatea, A., Grigoropoulos, A., Bajoub, A., ... & Kaburlasos, V. G. (2023). Assessing the economic performance of multipurpose collaborative robots toward skillful and sustainable viticultural practices. Sustainability, 15(4), 3866.
Unal, I., & Topakci, M. (2013). Cloud computing technology in agricultural production applications. Academic Informatics Conference-AB, 23-25.
Yarım, M. A., & Çelik, S. (2020). The necessity and role of teachers through the eyes of students in the age of Industry 4.0. Journal of Social Sciences, Mehmet Akif Ersoy University Institute of Social Sciences, (31), 76-92.
Zhai, Z., Martínez, J. F., Beltran, V., & Martínez, N. L. (2020). Decision support systems for Agriculture 4.0: Survey and challenges. Computers and Electronics in Agriculture, 170, 105256.
Referanslar
Abbasi, R., Martinez, P., & Ahmad, R. (2022). The digitization of the agricultural industry–A systematic literature review on Agriculture 4.0. Smart Agricultural Technology, 2, 100042.
Acun, D. Z. A. (2024). Development of herbicide-tolerant carrot genotypes using the CRISPR/Cas9 cytidine base-editing technique.
Agin, O., & Malasli, M. Z. (2016). The role and importance of image processing techniques in sustainable agriculture: A literature review. Journal of Agricultural Machinery Science, 12(3), 199-206.
Agizan, K., Bayramoglu, Z., & Agizan, S. (2022). The advantages of smart farming technologies for agricultural business management. Turkish Journal of Agriculture-Food Science and Technology, 10(9), 1697-1706.
Akin, T., Yildirim, C., & Cakan, H. (2015). Information-based decision support systems in agriculture and livestock.
Akman, A. Z. (2023). The place of the interaction between digital transformation and organizational culture in Society 5.0 structuring: A field study (Doctoral dissertation, Necmettin Erbakan University).
Aksoy, C. (2024). Digital transformation of businesses and the digital leadership approach. Journal of Quality and Strategy Management, 4(1), 1-29.
Aldag, M. C., & Eker, B. (2018). Artificial intelligence applications in the manufacturing of agricultural machinery. International Refereed Journal of Engineering and Sciences, 1.
Alkan, B., & Ozgunaltay Ertugrul, G. (2022). Pesticide applications with agricultural unmanned aerial vehicles. Kirsehir Ahi Evran University Journal of Agriculture Faculty, 2(2), 232-238.
Al-Saffar, B. S. F. (2019). Implementation and performance evaluation of classifiers SVM, CNN, and ANN in vineyard estimation (Master's thesis, Institute of Natural Sciences).
Altas, Z., Ozguven, M. M., & Yanar, Y. (2018). Determination of sugar beet leaf spot disease level (Cercospora beticola Sacc.) with image processing techniques using drones. Current Investigations in Agriculture and Current Research, 5(3), 621-631. https://doi.org/10.32474/CIACR.2018.05.000214
Altin, O. (2021). Analysis of the use of information and communication technologies in agricultural extension and marketing services by members of agricultural producer unions: The case of Tokat province.
Ammoniaci, M., Kartsiotis, S. P., Perria, R., & Storchi, P. (2021). State of the art of monitoring technologies and data processing for precision viticulture. Agriculture, 11(3), 201.
Anonymous. (2014). https://mis.sadievrenseker.com/2014/02/karar-destek-sistemleri-kds-decision-support-systems-dss/
Anonymous. (2021). https://www.platinonline.com/tarim-4-0/tarimda-fark-yaratan-4-ulke-1079290
Anonymous. (2022). https://www.elaisian.com/en/2022/07/18/viticulture-4-0-what-is-there-to-know/
Apolo-Apolo, O. E., Martínez-Guanter, J., Egea, G., Raja, P., & Pérez-Ruiz, M. (2020). Deep learning techniques for estimation of yield and size of citrus fruits using a UAV. European Journal of Agronomy, 115, 126030.
Araujo, J., Pimenta, V., Campos, J., Pinheiro, P., Porto, J. V., Manso, J., ... & Graca, A. (2023). Innovation co-development for viticulture and enology: Novel tele-detection web-service fuses vineyard data. BIO Web of Conferences, 56, 01006.
Arklan, U. (2008). Information society and communication: The role of mass communication tools and the internet in the dissemination of information. Selcuk Communication, 5(3), 67-80.
Arslan, U., Erbek, E., & Ozyoruk, A. (2018). Determination of pesticide use attitudes and behaviors of fruit producers in Gursu and Kestel districts of Bursa province. Bursa Uludag University Journal of Agriculture Faculty, 32(2), 69-74.
Atak, A. (2024). Recent table grape breeding studies worldwide. Bahce, 53(Special Issue 1), 14-22.
Aydin, N. (2022). Information technologies in the agricultural sector. Balkan & Near Eastern Journal of Social Sciences (BNEJSS), 8.
Aydinbas, G. (2024). Identification of factors related to agricultural productivity: The case of BRICS-T countries. Turkish Journal of Agriculture and Natural Sciences, 11(2), 524-535.
Bal, C. E., & Bal, H. C. (2023). Effects of Industry 4.0 applications on the agriculture sector and economic growth. Third Sector Social Economic Review, 58(3), 2553-2572.
Baran, E., & Ersoy Karacuha, M. (2021). Adapting to global climate change: Smart agriculture practices and occupational health and safety. Proceedings of the National Occupational Health and Safety Student Congress, Istanbul, 13-20.
Baran, M. F., Belliturk, K., & Celik, A. (2023). Preface, Environmental Pressures, and Agriculture. ISBN: 978-625-367-436-6. Ankara, Turkey.
Barrile, V., Simonetti, S., Citroni, R., Fotia, A., & Bilotta, G. (2022). Experimenting Agriculture 4.0 with sensors: A data fusion approach between remote sensing, UAVs, and self-driving tractors. Sensors, 22(20), 7910.
Bento, C., da Cunha, P. R., & Barata, J. (2019). Cultivating sociomaterial transformations in agriculture 4.0: The case of precision viticulture.
Bicakci, S. N. (2019). Internet of Things. Takvim-i vekayi, 7(1), 24-36.
Bilgin, I., & Medeni, T. D. (2023). SWOT analysis for the digitalization of agricultural service delivery: Connectivity between the Ministry of Agriculture and Forestry and KAYSIS. Journal of Public Administration and Technology, 4(2), 189-217. https://doi.org/10.58307/kaytek.1175247
Bohler, J. E., Schaepman, M. E., & Kneubühler, M. (2020). Crop separability from individual and combined airborne imaging spectroscopy and UAV multispectral data. Remote Sensing, 12(8), 1256. https://doi.org/10.3390/rs12081256
Borghi, M., Pacifico, D., Crucitti, D., Squartini, A., Berger, M. M., Gamboni, M., ... & Zottini, M. (2024). Smart selection of soil microbes for resilient and sustainable viticulture. The Plant Journal.
Brunori, E., Moresi, F. V., Maesano, M., De Horatis, M., Salvati, R., Mugnozza, G. S., & Biasi, R. (2022). Field survey and UAV remote sensing as tools for evaluating the canopy management effects in smallholder grapevine farms. In BIO Web of Conferences (Vol. 44, p. 05001). EDP Sciences.
Caglar, N., & Sensoy, S. (2021). Vegetable Breeding, Volume II: Cucurbitaceae (Kabakgiller) (A. Abak, A. Balkaya, S. S. Ellialtioglu, & E. Duzyaman, Eds.). Volume 2, pp. 95-197. Gece Kitapligi Publishing, Ankara.
Cakır, Ö. Ü. A., & İşlek, Ö. G. F. (2021). Chapter 7: Turkey’s Smart Agriculture (Agriculture 4.0) Potential. In Organic Agriculture and Agro-Ecological Developments in Turkey (pp. 155).
Cakmakci, M. F., & Cakmakci, R. (2023). Remote sensing, artificial intelligence, and future smart agriculture technology trends. European Journal of Science and Technology, 52, 234-246.
Cam, M. (2023). Innovative agricultural practices in a human-centered society: The case of Kasaplar Village (Order No. 30822686). Available from ProQuest Dissertations & Theses Global. (2925078183). Retrieved from https://www.proquest.com/dissertations-theses/innovative-agricultural-practices-human-centered/docview/2925078183/se-2
CEBIT. (2020). https://japan.kantei.go.jp/97_abe/statement/201703/1221682_11573.html
Cengiz, B., & Daş, R. (2022). Data fusion: Data sources, architectures, challenges, and solution approaches. Fırat University Journal of Engineering Sciences, 34(2), 899-922.
Cengiz, S. A., & Demirel, M. (2019). Reflections of the Industry 4.0 process on the education system: The example of Turkey (Master's thesis, Nevşehir Hacı Bektaş Veli University).
Cesco, S., Pii, Y., Borruso, L., Orzes, G., Lugli, P., Mazzetto, F., ... & Mimmo, T. (2021). A smart and sustainable future for viticulture is rooted in soil: How to face Cu toxicity. Applied Sciences, 11(3), 907.
Chen, C. J., Huang, Y. Y., Lu, Y. S., Chen, Y. C., Chang, C. Y., & Huang, Y. M. (2021). Identification of fruit tree pests with deep learning on embedded drones to achieve accurate pesticide spraying. IEEE Access, 9, 21986-21997. https://doi.org/10.1109/ACCESS.2021.3056082
Çokuysal, B. (2021). Ethical issues in the triangle of agriculture, digitalization, and sustainability. Proceedings Book of the Congress, 294.
Compant, S., & Mathieu, F. (Eds.). (2016). Biocontrol of major grapevine diseases: Leading research. CABI.
Demir, Ü., Kula, N., & Uğurlu, B. (2021). A decision support model proposal for the use of artificial intelligence in agriculture: An example of tomato pest detection. Lapseki Vocational School Journal of Applied Research, 2(4), 91-108.
Dogan, A., & Guzel, D. U. (2020). Development of a spatial decision support system using GIS techniques in Amur grape (Vitis amurensis Rupr.) cultivation: The case of Erciş-Van (Turkey). Euroasia Journal of Mathematics, Engineering, Natural & Medical Sciences, 7(13), 227-243.
Dogancukuru, H. (2009). Mobile applications as an alternative communication tool in agricultural extension in Konya province: Development opportunities.
Dogru, B., & Meçik, O. (2018). Effects of Industry 4.0 on the labor market in Turkey: Firm expectations. Suleyman Demirel University Journal of Economic and Administrative Sciences, 23(Special Issue on Industry 4.0 and Organizational Change), 1581-1606.
Dolo, A. (2018). Flood modeling based on drone data for the Arhavi district (Master's thesis, Institute of Social Sciences).
Dorofeeva, A. A., Ponomarenko, E. A., Lukyanova, Y. Y., Fomina, E. A., & Buchatskiy, P. Y. (2021). High precision unmanned agro copters in eco-friendly viticulture systems. In CEUR Workshop Proceedings (Vol. 2914, pp. 299-306).
Dressler, M., & Paunovic, I. (2021). Sensing technologies, roles, and technology adoption strategies for digital transformation of grape harvesting in SME wineries. Journal of Open Innovation: Technology, Market, and Complexity, 7(2), 123.
Duman, Ö. G. D. B., & Şen, E. B. (2019). Chapter 3: The Internet of Things in the context of blockchain technology. In New Approaches in the Field of Engineering in Turkey: The Internet of Things in Engineering (pp. 29-64). Ankara, Turkey.
Durna Daştan, S. (2023). The future of plant biotechnology and the conservation of plant genetic resources. In Current Applications and Assessments in Plant Biotechnology (Chapter 1). Lyon.
Elciyar, K. (2018). Internet of Things and concerns. In 1st International CICMS Conference, May 4-5, 2018, Kusadasi, Turkey (p. 336).
Ercan, Ş., Öztep, R., Güler, D., & Saner, G. (2019). Assessment of Agriculture 4.0 and its applicability in Turkey. Journal of Agricultural Economics, 25(2), 259-265. https://doi.org/10.24181/tarekoder.650762
Ertas, B. (2020). A sustainable future with Agriculture 4.0. Icontech International Journal, 4(1), 1-12.
Faoro, A., Romero, M. E., & Frausin, M. (2022). Inclusion of ICT skills, digital literacy, and open-source platforms in the teaching of industrial design applied to smart agriculture. In EDULEARN22 Proceedings (pp. 9027-9031). IATED.
Ferro, M. V., & Catania, P. (2023). Technologies and innovative methods for precision viticulture: A comprehensive review. Horticulturae, 9(3), 399.
Ford-Lloyd, B. V., & Jackson, M. T. (1991). Biotechnology and methods of conservation of plant genetic resources.
Gago, J., Douthe, C., Coopman, R. E., Gallego, P. P., Ribas-Carbo, M., Flexas, J., Escalona, J., & Medrano, H. (2015). UAVs challenge to assess water stress for sustainable agriculture. Agricultural Water Management, 153, 9–19. https://doi.org/10.1016/j.agwat.2015.01.020
Gazioglu Sensoy, R. I., & Balta, F. (2011). Identification of some local grapevine forms from the Van region and their characterization using RAPD markers. Journal of the Institute of Science and Technology, 1(3), 41-56.
Giordano, S., & Verrastro, V. (2020). IoT technologies in viticulture: Innovation and sustainability. The IoF Project case study. GeoProgress Journal, 7(1), 57-72.
Govez, E. (2023). An innovative perspective on the agricultural sector: Agriculture 4.0. In Social Issues (Theories, Policies, Applications) (p. 87). Efe Akademi Publications, Istanbul, Turkey.
Gucenmez, T. (2023). The impact of digital transformation on labor markets in Turkey and the relationship with income distribution. Kahramanmaraş Sütçü İmam University Journal of Social Sciences, 20(3), 995-1005. https://doi.org/10.33437/ksusbd.1361092
Gulcubuk, B., & Aluftekin, N. (2006). The use of internet-based information systems in rural development. In XI. Internet Conference in Turkey, 21-23.
Gungor, E., & Demiryürek, K. (2021). Genetically modified organisms in Turkey. Journal of Agricultural Economics Research, 7(2), 140-154.
Guzel, D. U., & Dogan, A. (2020). Identification of potential areas for grape (Vitis spp.) cultivation in the Erciş (Van) region using geographic information systems (GIS) techniques based on climate, soil, and topography factors. Yuzuncu Yil University Journal of Agricultural Sciences, 30(4), 672-687. https://doi.org/10.29133/yyutbd.752603
Kadagan, O., & Gurbuz, I. B. (2022). Consumers' perceptions and attitudes towards precision agriculture applications: A case study of Bursa Province. Balkan & Near Eastern Journal of Social Sciences (BNEJSS), 8.
Karaman, N., Aksoy, S., Cesur, F., & Saygin, F. (2022). Determining the impact of urbanization on agricultural lands using remote sensing and geographic information system techniques. Journal of Agricultural Research in Turkey, 9(3), 385-394.
Kazancoglu, Y., Lafci, C., Kumar, A., Luthra, S., Garza‐Reyes, J. A., & Berberoglu, Y. (2024). The role of agri‐food 4.0 in climate‐smart farming for controlling climate change‐related risks: A business perspective analysis. Business Strategy and the Environment, 33(4), 2788-2802.
Kerkech, M., Hafiane, A., & Canals, R. (2020). Vine disease detection in UAV multispectral images using optimized image registration and deep learning segmentation approach. Computers and Electronics in Agriculture, 174, 105446. https://doi.org/10.1016/j.compag.2020.105446
Kilavuz, E., & Erdem, I. (2019). Agriculture 4.0 applications worldwide and the transformation of Turkish agriculture. Social Sciences, 14(4), 133-157.
Kilic, S., & Alkan, R. M. (2018). The fourth industrial revolution Industry 4.0: Evaluations of the world and Turkey. Journal of Entrepreneurship Innovation and Marketing Research, 2(3), 29-49.
Koken, A. (2019). Drying of Sultani seedless grape variety (Vitis vinifera L.) in a solar-powered tunnel dryer and dryer automation (Master's thesis, Graduate School of Education).
Korkmaz, M. K. (2023). Sustainability, agriculture, future. In The Role and Importance of Agricultural Activities in Sustainable Development (p. 151).
Mattivi, P., Pappalardo, S. E., Nikolic, N., Mandolesi, L., Persichetti, A., Marchi, M. D., & Masin, R. (2021). Can commercial low-cost drones and open-source GIS technologies be suitable for semiautomatic weed mapping for smart farming? A case study in northeastern Italy. Remote Sensing, 13(10), 1869. https://doi.org/10.3390/rs13101869
Mazzon, F. (2019). Smart and digital agrifood: Evidence from six case studies. Università Ca' Foscari Venezia.
Mehedi, I. M., Hanif, M. S., Bilal, M., Vellingiri, M. T., & Palaniswamy, T. (2024). Remote sensing and decision support system applications in precision agriculture: Challenges and possibilities. IEEE Access.
Onder, N. (2023). Industry 4.0 and the labor market. Financial Analysis Journal, 33(175).
Oreški, D., Pihir, I., & Cajzek, K. (2021, September). Smart agriculture and digital transformation: A case of an intelligent system for wine quality prediction. In 2021 44th International Convention on Information, Communication and Electronic Technology (MIPRO) (pp. 1370-1375). IEEE.
Ozguven, M. M., Altas, Z., Guven, D., & Cam, A. (2022). The use and future of drones in agriculture. Ordu University Journal of Science and Technology, 12(1), 64-83. https://doi.org/10.54370/ordubtd.1097519
Pagliai, A., Ammoniaci, M., Sarri, D., Lisci, R., Perria, R., Vieri, M., ... & Kartsiotis, S. P. (2022). Comparison of aerial and ground 3D point clouds for canopy size assessment in precision viticulture. Remote Sensing, 14(5), 1145.
Pakdemirli, B., Birişik, N., Aslan, I., Sönmez, B., & Gezici, M. (2021). The use of digital technologies in Turkish agriculture and Agriculture 4.0 in the agriculture-food chain. Soil and Water Journal, 10(1), 78-87.
Pampuri, A., Giovenzana, V., Tugnolo, A., Casson, A., Vignati, S., Guidetti, R., & Beghi, R. (2022). Grape-HAND: A smart optical prototype for measuring grapes' qualitative parameters.
Pampuri, A., Tugnolo, A., Giovenzana, V., Casson, A., Guidetti, R., & Beghi, R. (2021). Design of cost-effective LED-based prototypes for the evaluation of grape (Vitis vinifera L.) ripeness. Computers and Electronics in Agriculture, 189, 106381.
Pampuri, A., Tugnolo, A., Giovenzana, V., Casson, A., Pozzoli, C., Brancadoro, L., ... & Beghi, R. (2022). Application of a cost-effective visible/near infrared optical prototype for the measurement of qualitative parameters of Chardonnay grapes. Applied Sciences, 12(10), 4853.
Pampuri, A., Tugnolo, A., Giovenzana, V., Vignati, S., Casson, A., Zambelli, M., ... & Guidetti, R. (2022). Grape polyphenol content prediction through vis/NIR spectroscopy for real-time application at winery consignment.
Quarato, C. (2018). FerMentor connected system: A sustainable approach for innovating traditional farms (Doctoral dissertation, Politecnico di Torino).
Reis, M. J. C. S., Morais, R., Peres, E., Pereira, C., Contente, O., Soares, S., Valente, A., Baptista, J., Ferreira, P. J. S. G., & Cruz, J. B. (2012). Automatic detection of bunches of grapes in a natural environment from color images. Journal of Applied Logic, 10, 285–290.
Romualdi, M. (2019). Viticulture 4.0: Preliminary tests in a wine company in Abruzzo.
Sahin, H. (2022). Digital Agriculture, Agriculture 4.0, Smart Agriculture, Robotic Applications, and Autonomous Systems. Journal of Agricultural Machinery Science, 18(2), 68-83.
Sanchez, L. O. S., Miranda, R. C., Escalante, J. J. G., Pacheco, I. T., Gonzalez, R. G. G., Miranda, C. L. C., & Lumbreras, P. D. A. (2011). Scale invariant feature approach for insect monitoring. Computers and Electronics in Agriculture, 75, 92–99.
Sarac, H. (2022). The rise of automation: mass unemployment or new employment? An evaluation of its impact on the labor market. Journal of Labor Relations, 13(2), 55-76.
Sarri, D., Lombardo, S., Pagliai, A., Perna, C., Lisci, R., De Pascale, V., ... & Vieri, M. (2020). Smart farming introduction in wine farms: A systematic review and a new proposal. Sustainability, 12(17), 7191.
Sassu, A., Gambella, F., Ghiani, L., Mercenaro, L., Caria, M., & Pazzona, A. L. (2021). Advances in unmanned aerial system remote sensing for precision viticulture. Sensors, 21(3), 956.
Saygili, F., Kaya, A. A., Çalışkan, E. T., & Kozal, Ö. E. (2018). Global integration of Turkish agriculture and Agriculture 4.0. Izmir Commodity Exchange, Publication No: 98, Izmir.
Senol, C. (2021). Innovation, Support, Sustainability: The Turkish Economy and Agriculture. International Journal of Geography and Geography Education, (44), 475-488.
Sevli, O. (2023). A digital agriculture application on the scale of Agriculture 4.0: Farm Monitoring and Management System. International Journal of Sustainable Engineering and Technology, 7(2), 105-116.
Sheikh, M. (2022). The impact of artificial intelligence usage on the labor market. Journal of Economics and Political Sciences, 2(1), 102-111.
Tanyolac, B., Kaya, H. B., Soya, S., & Akkale, C. (2010). Biotechnology and bioinformatics. In A. Yıldırım, F. Bardakçı, & M. Karataş (Eds.), Nobel Publication Distribution (pp. 601-638). Ankara.
Terribile, F., Bonfante, A., D'Antonio, A., De Mascellis, R., De Michele, C., Langella, G., ... and Basile, A. (2017). A geospatial decision support system for supporting quality viticulture at the landscape scale. Computers and Electronics in Agriculture, 140, 88-102.
Tugnolo, A., Giovenzana, V., Vignati, S., Pampuri, A., Casson, A., Zambelli, M., ... & Beghi, R. (2022). Development of a cost-effective IoT hyperspectral device for distributed and autonomous monitoring of vine crops.
Turgut, K. B. K. (2020). Current status and future of biotechnology and biosecurity in agriculture. Proceedings of the IX Technical Congress of Agricultural Engineering in Turkey, 281.
Turker, M. M. O. U., Akdemir, B., Acar, A. C. A. I., Ozturk, R., & Eminoglu, M. B. (2020). The digital age in agriculture. Proceedings of the IX Technical Congress of Agricultural Engineering in Turkey, 55.
Tziolas, E., Karapatzak, E., Kalathas, I., Karampatea, A., Grigoropoulos, A., Bajoub, A., ... & Kaburlasos, V. G. (2023). Assessing the economic performance of multipurpose collaborative robots toward skillful and sustainable viticultural practices. Sustainability, 15(4), 3866.
Unal, I., & Topakci, M. (2013). Cloud computing technology in agricultural production applications. Academic Informatics Conference-AB, 23-25.
Yarım, M. A., & Çelik, S. (2020). The necessity and role of teachers through the eyes of students in the age of Industry 4.0. Journal of Social Sciences, Mehmet Akif Ersoy University Institute of Social Sciences, (31), 76-92.
Zhai, Z., Martínez, J. F., Beltran, V., & Martínez, N. L. (2020). Decision support systems for Agriculture 4.0: Survey and challenges. Computers and Electronics in Agriculture, 170, 105256.