Ecosystem for Successful Agriculture. Collaborative Approach as a Driver for Agricultural Development

[1] Alho, E. (2015). Farmers’ self-reported value of cooperative membership: evidence from heterogeneous business and organization structures. Agricultural and Food Economics 3(23). DOI: 10.1186/s40100-015-0041-6.10.1186/s40100-015-0041-6Search in Google Scholar

[2] Baker, T., Caracciolo, C., Doroszenko, A. & Suominen, O. (2016). GACS core: Creation of a global agricultural concept scheme. In Garoufallou, E., Subirats Coll, I., Stellato, A. & Greenberg, J., eds., Metadata and Semantics Research (pp. 311–316). Cham: Springer. DOI: 10.1007/978-3-319-49157-8_27.10.1007/978-3-319-49157-8_27Search in Google Scholar

[3] Balafoutis, A., Beck, B., Fountas, S., Vangeyte, J., van der Wal, T., Soto, I., Gómez-Barbero, M., Barnes, A. & Eory, V. (2017). Precision Agriculture Technologies Positively Contributing to GHG Emissions Mitigation, Farm Productivity and Economics. Sustainability 9(1339), 1–28. DOI: 10.3390/su9081339.10.3390/su9081339Search in Google Scholar

[4] Banhazi, T., Babinszky, L., Halas, V. & Tscharke, T. (2012). Precision livestock farming: Precision feeding technologies and sustainable livestock production. International Journal of Agricultural and Biological Engineering 5(4), 54–61. DOI: 10.3965/j.ijabe.20120504.006.Search in Google Scholar

[5] Barakabitze, A., Kitindi, E., Sanga, C., Shabani, A., Philipo, J. & Kibirige, G. (2015). New technologies for disseminating and communicating agriculture knowledge and information: Challenges for agricultural research institutes in Tanzania. Electronic Journal of Information Systems in Developing Countries 70 (1), 1–22. DOI. 10.1002/j.1681-4835.2015.tb00502.x.10.1002/j.1681-4835.2015.tb00502.xSearch in Google Scholar

[6] Barati, A. A., Kalantari, K., Nazari, M. R. & Asadi, A. (2017). A hybrid method (ANP-SWOT) to formulate and choose strategic alternatives for development of rural cooperatives in Iran. Journal of Agricultural Science and Technology 19(4), 757–769.Search in Google Scholar

[7] Barnes, A., De Soto, I., Eory, V., Beck, B., Balafoutis, A., Sánchez, B., Vanguyte, J., Fountas, S., van der Wal, T. & Gómez-Barbero, M. (2019). Influencing factors and incentives on the intention to adopt precision agricultural technologies within arable farming systems. Environmental Science and Policy 93, 66–74. DOI: 10.1016/j.envsci.2018.12.014.10.1016/j.envsci.2018.12.014Search in Google Scholar

[8] Bazzani, C. & Canavari, M. (2013). Alternative agri-food networks and short food supply chains: A review of the literature. Economia Agro-Alimentare 15(2), 11–34. DOI: 10.3280/ECAG2013-002002.10.3280/ECAG2013-002002Search in Google Scholar

[9] Berckmans, D. (2014). Precision livestock farming technologies for welfare management in intensive livestock systems. Revue scientifique et technique 33(1), 189–196. DOI: 10.20506/rst.33.1.2273.10.20506/rst.33.1.227325000791Search in Google Scholar

[10] Blom-Zandstra, M., Korevaar, H., Stuiver, M. & Groot, A. (2016). Critical success factors for governing farmer-managed public goods in rural areas in the Netherlands. International Journal of Agricultural Sustainability 14(1), 45–64. DOI: 10.1080/14735903.2015.1024972.10.1080/14735903.2015.1024972Search in Google Scholar

[11] Bojar, W. L. & Drelichowski, L. (2008). Analysis of tendencies in agribusiness networking coopetition in Poland and in the partner countries. Journal of Central European Agriculture 9(3), 445–456.Search in Google Scholar

[12] Cantarelli, F. (2016). Le sfide per uno sviluppo sostenibile del sistema agroalimentare italiano e non solo. Economia Agro-Alimentare 2, 229–238. DOI: 10.3280/ECAG2016-002007.10.3280/ECAG2016-002007Search in Google Scholar

[13] Carbone, A. (2017). Food supply chains: coordination governance and other shaping forces. Agricultural and Food Economics 5(7). DOI: 10.1186/s40100-017-0077-x.10.1186/s40100-017-0077-xSearch in Google Scholar

[14] Carrillo, F. J., Yigitcanlar, T., Garcia, B. & Lonnqvist, A. (2014). Knowledge and the city: Concepts, applications and trends of knowledge-based urban development. New York: Routledge.10.4324/9781315856650Search in Google Scholar

[15] Casieri, A., Nazzaro, C. & Roselli, L. (2010). Trust building and social capital as development policy tools in rural areas. An empirical analysis: The case of the LAG CDNISAT. New Medit 9(1), 24–30.Search in Google Scholar

[16] Chmieliński, P., Faccilongo, N., Fiore, M., La Sala, P. (2018). Design and implementation of the Local Development Strategy: a case study of Polish and Italian Local Action Groups in 2007–2013. Studies in Agricultural Economics 120, 25–31. DOI: 10.7896/j.1726.10.7896/j.1726Search in Google Scholar

[17] Contò, F., Fiore, M., La Sala, P. (2012). The Metadistrict as the Territorial Strategy: From Set Theory and a Matrix Organization Model Hypothesis. International Journal on Food System Dynamics 3(1), 82–94. DOI: 10.18461/ijfsd.v3i1.318.Search in Google Scholar

[18] Contò, F., Santini, C., La Sala, P., Fiore, M. (2016). Reducing information gap and Increasing market orientation in the agribusiness sector: some evidences from Apulia Region. Recent Patents on Food, Nutrition & Agriculture 8(1), 48–54. DOI: 10.2174/221279840801160304144309.10.2174/22127984080116030414430926957468Search in Google Scholar

[19] de Olde, E., Carsjens, G. & Eilers, C. (2017). The role of collaborations in the development and implementation of sustainable livestock concepts in The Netherlands. International Journal of Agricultural Sustainability 15(2), 153–168. DOI: 10.1080/14735903.2016.1193423.10.1080/14735903.2016.1193423Search in Google Scholar

[20] Dong, S. (2007). How to promote the commercialization of emerging technology: The challenge and the role of chinese government. In Advances in Management of Technology – Proceedings of the International Conference on Management of Technology (pp. 498–503). Taiyuan.University of Technology.Search in Google Scholar

[21] El Bilali, H. & Allahyari, M. (2018). Transition towards sustainability in agriculture and food systems: Role of information and communication technologies. Information Processing in Agriculture 5(4), 456–464. DOI: 10.1016/j.inpa.2018.06.006.10.1016/j.inpa.2018.06.006Search in Google Scholar

[22] Elijah, O., Rahman, T., Orikumhi, I., Leow, C. & Hindia, M. (2018). An Overview of Internet of Things (IoT) and Data Analytics in Agriculture: Benefits and Challenges. IEEE Internet of Things Journal 5(5), 3758–3773. DOI: 10.1109/jiot.2018.2844296.10.1109/JIOT.2018.2844296Search in Google Scholar

[23] Faccilongo, N., Contò, F., Dicceca, R., Zaza, C. & La Sala, P. (2016). RFID sensor for agri-food supply chain management and control. International Journal of Sustainable Agricultural Management and Informatics 2(2–4), 206–221. DOI: 10.1504/ijsami.2016.10002896.10.1504/IJSAMI.2016.10002896Search in Google Scholar

[24] Fernandez, P. (2016). Through the looking glass: envisioning new library technologies – people tracking technologies. Library Hi Tech News 36(2). 1–5. DOI: 10.1108/lhtn-07-2016-0033.10.1108/LHTN-07-2016-0033Search in Google Scholar

[25] Fischer, C. (2013). Trust and communication in European agri-food chains. Supply Chain Management: 18(2), 208–218, DOI: 10.1108/13598541311318836.10.1108/13598541311318836Search in Google Scholar

[26] Frascarelli A. (2012), Migliorare il funzionamento della filiera alimentare: una valutazione degli strumenti per la pac dopo il 2013. Economia Agro-Alimentare 1, 319–340. DOI: 10.3280/ECAG2012-001015.10.3280/ECAG2012-001015Search in Google Scholar

[27] Fu, W., Gao, N., An, X. & Zhang, J. (2018). Study on Precision Application Rate Technology for maize no-tillage planter in North China Plain. IFAC-Papers OnLine 51(17), 412–417. DOI: 10.1016/j.ifacol.2018.08.186.10.1016/j.ifacol.2018.08.186Search in Google Scholar

[28] FuJun, W., Zhou, Y., YingGang, O., XiangJun, Z. & JieLi, D. (2018). “Government-industry-university-research-promotion” collaborative innovation mechanism construction to promote the development of agricultural machinery technology. IFAC-PapersOnLine 51(17), 552–559. DOI: 10.1016/j.ifacol.2018.08.147.10.1016/j.ifacol.2018.08.147Search in Google Scholar

[29] Ghosh, D. (2016). Big Data in Logistics and Supply Chain management – A rethinking step. In 2015 International Symposium on Advanced Computing and Communication, ISACC (pp. 168–173). Piscataway: IEEE. DOI: 10.1109/isacc.2015.7377336.10.1109/ISACC.2015.7377336Search in Google Scholar

[30] Huttunen, S. (2012). Wood energy production, sustainable farming livelihood and multifunctionality in Finland. Journal of Rural Studies 28(4), 549–558. DOI: 10.1016/j.jrurstud.2012.06.003.10.1016/j.jrurstud.2012.06.003Search in Google Scholar

[31] Jordan, R., Eudoxie, G., Maharaj, K., Belfon, R. & Bernard, M. (2016). AgriMaps: Improving site-specific land management through mobile maps. Computers and Electronics in Agriculture 123, 292–296. DOI: 10.1016/j.compag.2016.02.009.10.1016/j.compag.2016.02.009Search in Google Scholar

[32] Kamilaris, A., Kartakoullis, A. & Prenafeta-Boldú, F. (2017). A review on the practice of big data analysis in agriculture. Computers and Electronics in Agriculture 143, 23–37. DOI: 10.1016/j.compag.2017.09.037.10.1016/j.compag.2017.09.037Search in Google Scholar

[33] Keeney, D. (1990). Sustainable Agriculture: Definition and Concepts. Journal of Production Agriculture 3(3), 281. DOI: 10.2134/jpa1990.0281.10.2134/jpa1990.0281Search in Google Scholar

[34] Kotu, B. H., Alene, A., Manyong, V., Hoeschle-Zeledon, I. & Larbi, A. (2017). Adoption and impacts of sustainable intensification practices in Ghana. International Journal of Agricultural Sustainability 15(5), 539–554. DOI: 10.1080/14735903.2017.1369619.10.1080/14735903.2017.1369619Search in Google Scholar

[35] Koutsos, T. & Menexes, G. (2019). Economic, agronomic, and environmental benefits from the adoption of precision agriculture technologies: A systematic review. International Journal of Agricultural and Environmental Information Systems 10(1), 40–56. DOI: 10.4018/ijaeis.2019010103.10.4018/IJAEIS.2019010103Search in Google Scholar

[36] Krantz, L. (2001). The Sustainable Livelihood Approach to Poverty Reduction. Stockholm: SIDA.Search in Google Scholar

[37] Kühne, B., Gellynck, X. & Weaver, R. D. (2015). Enhancing Innovation Capacity Through Vertical, Horizontal, and Third-Party Networks for Traditional Foods. Agribusiness 31 (3), 294–313. DOI: 10.1002/agr.21408.10.1002/agr.21408Search in Google Scholar

[38] La Sala, P., Silvestri, R., Lamonaca, E. & Faccilongo, N. (2017a). Le capacità relazionali quali risorse critiche per la creazione di valore nella filiera vitivinicola lucana. Economia Agro-Alimentare 3, 383–398. DOI: 10.3280/ECAG2017-003005.10.3280/ECAG2017-003005Search in Google Scholar

[39] La Sala, P., Silvestri, R. & Contò, F. (2017b). Differentiation strategies for the wine and nursery sector: empirical evidence from an Italy region. Agricultural and Food Economics (AFE) 5(23). DOI: 10.1186/s40100-017-0091-z.10.1186/s40100-017-0091-zSearch in Google Scholar

[40] Luck, J., Pitla, S., Shearer, S., Mueller, T., Dillon, C., Fulton, J. & Higgins, S. (2010). Potential for pesticide and nutrient savings via map-based automatic boom section control of spray nozzles. Computers and Electronics in Agriculture 70(1), 19–26. DOI: 10.1016/j.compag.2009.08.003.10.1016/j.compag.2009.08.003Search in Google Scholar

[41] Luostarinen, M. (1998). Integrated environmental research and networking of economy and information in rural areas of Finland. Agricultural and Food Science in Finland 7(2), 315–328. DOI: 10.23986/afsci.72856.10.23986/afsci.72856Search in Google Scholar

[42] Mah, J. S. & Yeo, M. (2014). The role of the government in R&D promotion and the development of technology-intensive industries in China. China Report 50(2), 91–107. DOI: 10.1177/0009445514523644.10.1177/0009445514523644Search in Google Scholar

[43] Miller, N., Griffin, T., Ciampitti, I. & Sharda, A. (2018). Farm adoption of embodied knowledge and information intensive precision agriculture technology bundles. Precision Agriculture 20(2), 348–361. DOI: 10.1007/s11119-018-9611-4.10.1007/s11119-018-9611-4Search in Google Scholar

[44] Morimoto, E. & Wadamori, T. (2018). Data evaluation for tractor operation based on GNSS and multiple sensors. In 2018 ASABE Annual International Meeting (No. 1800999). St. Joseph, MI: American Society of Agricultural and Biological Engineers. DOI: 10.13031/aim.201800999.10.13031/aim.201800999Search in Google Scholar

[45] Nazzaro, C. & Marotta, G. (2016). The Common Agricultural Policy 2014–2020: scenarios for the European agricultural and rural systems. Agricultural and Food Economics 4(16), 1–5. DOI: 10.1186/s40100-016-0060-y.10.1186/s40100-016-0060-ySearch in Google Scholar

[46] Odara, S., Khan, Z. & Ustun, T. S. (2015). Integration of precision agriculture and SmartGrid technologies for sustainable development. Proceedings – 2015 IEEE International Conference on Technological Innovations in ICT for Agriculture and Rural Development TIAR 2015, 84–89. DOI: 10.1109/TIAR.2015.7358536.10.1109/TIAR.2015.7358536Search in Google Scholar

[47] Paraforos, D., Vassiliadis, V., Kortenbruck, D., Stamkopoulos, K., Ziogas, V., Sapounas, A. & Griepentrog, H. (2016). A Farm Management Information System Using Future Internet Technologies. IFAC-PapersOnLine 49(16), 324–329. DOI: 10.1016/j.ifacol.2016.10.060.10.1016/j.ifacol.2016.10.060Search in Google Scholar

[48] Parra, H., Gomes, J. & Shebl, H. (2017). Integrated workflow for building 3D digital outcrop models using unmanned aerial vehicles – Drones: Field case Thamama Group, Wadih Rahbah, UAE. In Abu Dhabi International Petroleum Exhibition & Conference, 13–16 November, Abu Dhabi, UAE. Abu Dhabi: Society of Petroleum Engineers. DOI: 10.2118/188477-ms.10.2118/188477-MSSearch in Google Scholar

[49] Rajeswari, S., Suthendran, K. & Rajakumar, K. (2018). A smart agricultural model by integrating IoT, mobile and cloud-based big data analytics. Proceedings of 2017 International Conference on Intelligent Computing and Control (pp. 1–5), Piscataway: IEEE. DOI: 10.1109/i2c2.2017.8321902.10.1109/I2C2.2017.8321902Search in Google Scholar

[50] Rickard, S. (2015). Food security and climate change: The role of sustainable intensification, the importance of scale and the CAP. EuroChoices 14(1), 48–53. DOI: 10.1111/1746-692x.12082.10.1111/1746-692X.12082Search in Google Scholar

[51] Rossi, V., Caffi, T. & Salinari, F. (2012). Helping farmers face the increasing complexity of decision-making for crop protection. Phytopathologia Mediterranea 51(3), 457–479. DOI: 10.14601/Phytopathol_Mediterr-11038.Search in Google Scholar

[52] Sacchi, G., Cei, L., Stefani, G., Lombardi, G. V., Rocchi, B., Belletti, G., Padel, S., Sellars, A., Gagliardi, E., Nocella, G., Cardey, S., Mikkola, M., Ala-Karvia, U., Macken-Walsh, A., McIntyre, B., Hyland, J., Henchion, M., Bocci, R., Bussi, B., De Santis, G., Rodriguez, Y., Hurtado, I., de Kochko, P., Riviere, P., Carrascosa-García, M., Martínez, I., Pearce, B., Lampkin, N., Vindras, C., Rey, F., Chable, V., Cormery, A. & Vasvari, G. (2018). A multi-actor literature review on alternative and sustainable food systems for the promotion of cereal biodiversity. Agriculture (Switzerland) 8(11), 173. DOI: 10.3390/agriculture8110173.10.3390/agriculture8110173Search in Google Scholar

[53] Schwab, K. (2017). The Fourth Industrial Revolution. New York: Currency.Search in Google Scholar

[54] Schneider, S., Salvate, N. & Cassol, A. (2016). Nested markets, food networks, and new pathways for rural development in Brazil. Agriculture (Switzerland) 6(4), 61. DOI: 10.3390/agriculture6040061.10.3390/agriculture6040061Search in Google Scholar

[55] Seeman, E. D., O’Hara, M. T., Holloway, J. & Forst, A. (2007). The impact of government intervention on technology adoption and diffusion: The example of wireless location technology. Electronic Government 4(1), 1–19. DOI: 10.1504/EG.2007.012176.10.1504/EG.2007.012176Search in Google Scholar

[56] Smith, W. & Chan, P. (2017). Impact of drones on precision agriculture. In 7th International Workshop on Computer Science and Engineering, WCSE 2017 (pp. 1235–1239). Beijing: China Agricultural University.Search in Google Scholar

[57] Stafford, J. V. (2000). Implementing Precision Agriculture in the 21st Century. Journal of Agricultural. Engineering Research 76(3), 267–275. DOI: 10.1006/jaer.2000.0577.10.1006/jaer.2000.0577Search in Google Scholar

[58] Steiner, B. E. (2017). A phenomenon-driven approach to the study of value creation and organizational design issues in agri-business value chains. Economia Agro-Alimentare 1, 89–118. DOI: 10.3280/ECAG2017-001005.10.3280/ECAG2017-001005Search in Google Scholar

[59] Stratigea, A. (2009). Participatory planning and sustainable local development-A methodological approach; paper presented at the 2nd National Conference of Urban and Regional Planning and Regional Development, Vol, 24 (Proceedings 43–51). University Publishing of Thessaly.Search in Google Scholar

[60] Teng, W., De Jeu, R., Doraiswamy, P., Kempler, S., Mladenova, I. & Shannon, H. (2010). Improving world agricultural supply and demand estimates by integrating NASA remote sensing soil moisture data into USDA World Agricultural outlook Board decision making environment. In American Society for Photogrammetry and Remote Sensing Annual Conference 2010: Opportunities for Emerging Geospatial Technologies 2 (pp. 906–916). Bethesda, MD: ASPRS.Search in Google Scholar

[61] Tenzin, S., Siyang, S., Pobkrut, T. & Kerdcharoen, T. (2017). Low cost weather station for climate-smart agriculture. In 2017 9th International Conference on Knowledge and Smart Technology: Crunching Information of Everything, KST 2017 (pp. 172–177). Piscataway, NJ: IEEE. DOI: 10.1109/kst.2017.7886085.10.1109/KST.2017.7886085Search in Google Scholar

[62] Tesdell, L. (2016). Innovating down on the farm: Communication networks that facilitate water quality practices. In 2016 IEEE International Professional Communication Conference (no. 7740531). Piscataway, NJ: IEEE. DOI: 10.1109/ipcc.2016.7740531.10.1109/IPCC.2016.7740531Search in Google Scholar

[63] Tripathy, A., Adinarayana, J., Vijayalakshmi, K., Merchant, S., Desai, U., Ninomiya, S., Hirafuji, M. & Kiura, T. (2014). Knowledge discovery and Leaf Spot dynamics of groundnut crop through wireless sensor network and data mining techniques. Computers and Electronics in Agriculture 107, 104–114. DOI: 10.1016/j.compag.2014.05.009.10.1016/j.compag.2014.05.009Search in Google Scholar

[64] van Evert, F., Gaitán-Cremaschi, D., Fountas, S. & Kempenaar, C. (2017). Can precision agriculture increase the profitability and sustainability of the production of potatoes and olives? Sustainability 9(10), No. 1863. DOI: 10.3390/su9101863.10.3390/su9101863Search in Google Scholar

[65] Van Rijmenam, M. & Ryan, P. (2018). Blockchain: Transforming your business and our World. London: Taylor and Francis LTD.10.4324/9780429457715Search in Google Scholar

[66] Viaggi, D., Manos, B., Chatzinikolaou, P., Bournaris, T. & Kiomourtzi, F. (2011). A prospective analysis for the role of the CAP in rural economies and related research needs: The case of Greece. In Lee, T.H., ed., Agricultural Economics: New Research (pp. 205–226). Hauppauge, NY: Nova Science Publishers.Search in Google Scholar

[67] Weaver, R. D. (2008). Collaborative pull innovation: Origins and adoption in the new economy. Agribusiness 24(3), 388–402. DOI: 10.1002/agr.20165.10.1002/agr.20165Search in Google Scholar

[68] Yan, J. (2017). Control of sprinkler irrigation intensity based on energy self-adaptation of a wireless sensor network. Agro Food Industry Hi-Tech 28 (1), 1997–2001.Search in Google Scholar

[69] Yao, Y. C., Han, Q., Yang, H. Y. & Zhang, X. Y. (2018). The application of big data in production and environment. Journal of Physics: Conference Series 1087(3), No. 032019. DOI: 10.1088/1742-6596/1087/3/032019.10.1088/1742-6596/1087/3/032019Search in Google Scholar

[70] Yigezu, Y. A., Mugera, A., El-Shater, T., Aw-Hassan, A., Piggin, C., Haddad, A., Khalil, Y. & Loss, S. (2018). Enhancing adoption of agricultural technologies requiring high initial investment among smallholders. Technological Forecasting and Social Change 134, 199–206. DOI: 10.1016/j.techfore.2018.06.006.10.1016/j.techfore.2018.06.006Search in Google Scholar

[71] Zavala-Yoe, R., Ramírez-Mendoza, R. & García-Lara, S. (2017). A 3-SPS-1S parallel robot-based laser sensing for applications in precision agriculture. Soft Computing 21(3), 641–650. DOI: 10.1007/s00500-016-2457-7.10.1007/s00500-016-2457-7Search in Google Scholar

[72] Zaza, C., Bimonte, S., Faccilongo, N., La Sala, P., Contò, F. & Gallo, C. (2018). A new decision-support system for the historical analysis of integrated pest management activities on olive crops based on climatic data. Computers and Electronics in Agriculture 148, 237–249. DOI: 10.1016/j.compag.2018.03.015.10.1016/j.compag.2018.03.015Search in Google Scholar

[73] Zecca, F., Al Am, A. & Capocchi, E. (2014). Dai distretti alle reti d’impresa: soluzioni chiave per lo sviluppo territoriale. Rivista di Economia Agraria, 69 (2–3), 227–243. DOI: 10.13128/REA-16924.Search in Google Scholar

[74] Zhang, J., Wang, Y., Wang, C., Wang, R. & Li, F. (2017). Quantifying the emergy flow of an urban complex and the ecological services of a satellite town: a case study of Zengcheng, China. Journal of Cleaner Production Suppl. 163, S267–S276. DOI: 10.1016/j.jclepro.2016.02.059.10.1016/j.jclepro.2016.02.059Search in Google Scholar

[75] Zhao, L. & Yang, Z. (2018). Multi-sensor land data assimilation: Toward a robust global soil moisture and snow estimation. Remote Sensing of Environment 216, 13–27. DOI: 10.1016/j.rse.2018.06.033.10.1016/j.rse.2018.06.033Search in Google Scholar

[76] Zhao, S. L, Cacciolatti, L., Lee, S. H. & Song, W. (2014). Regional collaborations and indigenous innovation capabilities in China: A multivariate method for the analysis of regional innovation systems, Technological Forecasting and Social Change 94, 202–220. DOI: 10.1016/j.techfore.2014.09.014.10.1016/j.techfore.2014.09.014Search in Google Scholar

[77] EIP-AGRI (2015). Innovative Short Food Supply Chain management. Final report 2015. Available at: https://ec.europa.eu/eip/agriculture/en/publications/eip-agri-focus-group-innovative-short-food-supply.Search in Google Scholar

[78] European Union (2012). The Common Agricultural Policy. Luxembourg: Publications Office of the European Union.Search in Google Scholar

[79] FAO (2015, December 1). Google and FAO partner to make remote sensing data more efficient and accessible. Retrieved from http://www.fao.org/:http://www.fao.org/partnerships/container/news-article/en/c/356751/.Search in Google Scholar

[80] FAO (2017). The future of food and agriculture. Trends and challenges. Rome: Food and Agriculture Organization of the United Nations.Search in Google Scholar

[81] FAO (2018). Information and Communication Technology (ICT) in Agriculture: A Report to the G20 Agricultural Deputies. Food & Agriculture Org.Search in Google Scholar

[82] Rapsomanikis, G. (2017). G7 and Africa: Food Security, by FAO. Retrieved from ISPI – Italian Institute for International Political Studies: https://www.ispionline.it/en/pubblicazione/g7-and-africa-food-security-17852.Search in Google Scholar

[83] Regulation (EC) No 1305/2013 of the Commission.Search in Google Scholar

[84] UN DESA (2017, June 21). United Nations – Department of Economics and Social Affairs. Retrieved from www.un.org:https://www.un.org/development/desa/en/news/population/world-population-prospects-2017.html.Search in Google Scholar