Time Program 09:30-10:00 Registration (36th floor, LOTTE Hotel Seoul)
10:00-10:20
Welcome
Hong-sang KIM, President of Korea Rural Economic Institute Federico Failla ,Ambassador of Italy
Photo Time
10:20-12:00
Session ➊ Ⅰ Status of ICT for smart agriculture
Presentation 1: Development Strategies of ICT for Smart Agriculture Ji-yun PARK, KREI
Presentation 2: Broadband and narrowband applications for agriculture and rural areas: the Italian experience
Guido Bonati, CREA
Presentation 3: KOREA`s Smart Agriculture &Policy Sang-ho, PARK, MAFRA
Presentation 4: IoT for digital Agriculture Carlo Bisaglia, CREA
Lunch(12:00-13:30)
13:30-15:10
Session ➋ Ⅰ Development of ICT for sustainable Agriculture
Presentation 1: 4th Industrial Revolution and Sustainable Agriculture in Korea Yong-lyoul KIM, KREI
Presentation 2: Biophysical modelling: engineering components and services Marcello Donatelli, CREA
Presentation 3: Application of Agrifood Big Data in Various Fields Tae-wan KIM, EPIS
Presentation 4: Satellite-based advisory services for smart agriculture Giovanni Battista Chirico, University of Naples
Coffee Break(15:10-15:30)
15:30-16:20
Session ➌ Ⅰ Innovation for Sustainable Agriculture
Presentation 1: Sustainable Agriculture in Response to Climate Change Eun-suk JANG, RDA
Presentation 2: Logistic and innovation drivers for the adoption of precision farming Remigio Berruto, University of Turin
16:20–16:50 Q&A Session – Prof. Chang-gil KIM
16:50 -16:55 Closing - Prof. Francesco Canganella (Embassy of Italy) Coffee Break(16:55 - 17:00)
17:00-17:49 Round Table (CREA-KREI)
Program
시간 일정 09:30-10:00 등록
10:00-10:20 개회사 Ⅰ 김홍상 한국농촌경제연구원 원장
축 사 Ⅰ Federico Failla 주한 이탈리아 대사
10:20-12:00
세션➊ Ⅰ 스마트 농업을 위한 ICT 활용 현황
스마트 농업을 위한 ICT 발전 방향 Ⅰ 박지연 (한국농촌경제연구원, 한국)
Broadband and narrowband applications for agriculture and rural areas : the Italian experience Ⅰ Guido Bonati (CREA, 이탈리아)
한국 스마트농업 현황 및 정책방향 Ⅰ 박상호 (농림축산식품부, 한국) IoT for digital Agriculture Ⅰ Carlo Bisaglia (CREA, 이탈리아)
점심식사(12:00-13:30)
13:30-15:10
세션➋ Ⅰ 지속가능한 농업을 위한 ICT 발전
4차산업혁명과 지속가능한 농업 Ⅰ 김용렬 (한국농촌경제연구원, 한국) Biophysical modelling: engineering components and services
Marcello Donatelli (CREA, 이탈리아)
농업 분야 빅데이터 활용 Ⅰ 김태완 (농림수산식품교육문화정보원, 한국) Satellite-based advisory services for smart agriculture
Giovanni Battista Chirico (University of Naples, 이탈리아)
휴식(15:10-15:30)
15:30-16:20
세션➌ Ⅰ 지속가능한 농업을 위한 혁신 방안
기후변화에 대응한 지속가능 농업 발전 방안 Ⅰ 장은숙 (농촌진흥청, 한국) Logistic and innovation drivers for the adoption of precision farming Remigio Berruto (University of Turin, 이탈리아)
16:40-16:55 Q&A 세션
휴식(16:55-17:00)
17:00-17:49 Round Table (KREI-CREA)
프로그램
Session ➊
Status of ICT for smart agriculture
스마트 농업을 위한 ICT 활용 현황∙ Presentation 1 I Development Strategies of ICT for Smart Agriculture
스마트 농업을 위한 ICT 발전 방향 ··· 1
Ji-yun PARK, KREI / 박지연 (한국농촌경제연구원, 한국)∙ Presentation 2 I Broadband and narrowband applications for agriculture and rural areas:
the Italian experience ··· 21
Guido Bonati (CREA, 이탈리아)∙ Presentation 3 I KOREA`s Smart Agriculture & Policy
한국 스마트농업 현황 및 정책방향 ··· 31
Sang-ho, PARK, MAFRA / 박상호 (농림축산식품부, 한국)∙ Presentation 4 I IoT for digital Agriculture ··· 55
Carlo Bisaglia (CREA, 이탈리아)Session ➋
Development of ICT for sustainable Agriculture
지속가능한 농업을 위한 ICT 발전∙ Presentation 1 I 4th Industrial Revolution and Sustainable Agriculture in Korea
4차산업혁명과 지속가능한 농업 ··· 79
Yong-lyoul KIM, KREI / 김용렬 (한국농촌경제연구원, 한국)∙ Presentation 2 I Biophysical modelling: engineering components and services ··· 103
Marcello Donatelli (CREA, 이탈리아)∙ Presentation 3 I Application of Agrifood Big Data in Various Fields
농업 분야 빅데이터 활용 ··· 131
Tae-wan KIM, EPIS / 김태완 (농림수산식품교육문화정보원, 한국)∙ Presentation 4 I Satellite-based advisory services for smart agriculture ··· 145
Giovanni Battista Chirico (University of Naples, 이탈리아)Contents
Session ➌
Innovation for Sustainable Agriculture
지속가능한 농업을 위한 혁신 방안∙ Presentation 1 I Sustainable Agriculture in Response to Climate Change
기후변화에 대응한 지속가능 농업 발전 방안 ··· 165
Eun-suk JANG, RDA / 장은숙 (농촌진흥청, 한국)∙ Presentation 2 I Logistic and innovation drivers for the adoption of precision farming ··· 187
Remigio Berruto (University of Turin, 이탈리아)Ji-yun PARK, KREI 박지연 (한국농촌경제연구원, 한국)
Session ➊
Presentation 1
Development Strategies of ICT for Smart Agriculture
스마트 농업을 위한 ICT 발전 방향
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Profile
Jiyun PARK
Biography
After graduating with a Ph.D. in agricultural economics from Texas A & M University, she has worked for the Korea Rural Economic Institute since 2013. The main research field of Dr. Park is science and technology-based agriculture and she participated in research projects on smart agriculture, the fourth industrial revolution in agriculture, agri-food R & D, renewable energy, and bio-economics.
Development Strategies of ICT for Smart Agriculture
Jiyun PARK
Korea Rural Economic Institute Naju-si Bitgaram-ro 601
jiyunpark@krei.re.kr
Through convergence between agriculture and ICT, we try to overcome the difficulties faced by Korean agriculture and achieve innovative growth in agriculture. In the presentation, the vision of Korean agriculture is presented as the creation of new value added through the convergence between industries and the strengthening of private innovation capacity and the continuous growth of agriculture.
To realize the vision, the following four goals are suggested. First, ICT convergence innovation ecosystem creation; Second, expansion of climate smart agriculture and precision agriculture; third, strengthening the on-off linking platform of the agri-food industry; fourth, creating new value through the convergence of bio and ICT for the expansion of agriculture.
The main strategies are to promote agricultural industry ventures and start-ups with core technological competitiveness, to establish a platform for sharing data with high availability and reliability in the agricultural sector, to modify laws, systems and regulations in response to agricultural environment and technological changes, to invest in smart agricultural R&D that can secure global competitiveness, and to cultivate technology utilization and distribution manpower.
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Guido Bonati (CREA, 이탈리아)
Session ➊
Presentation 2
Broadband and narrowband applications for agriculture and
rural areas: the Italian experience
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Profile
Guido BONATI
Biography
Guido Bonati is a director of research at the Italian Council for research in agriculture and economics – Centre for Policies and Bioeconomy, in Rome.
After graduating in Agricultural Sciences, University of Piacenza, he was awarded in a Master in Business Administrations from Boston University.
His main areas of research have been on IT applications on agriculture, being one one the initial participants tp EUNITA (European Network for Information Technlogies in Agriculture) and one of the founding members the European Federation for IT in Agriculture.
Since 1998 he is also working in agro-environmental policies, including water management, desertification, impact of climate change in agriculture, renewable energies. He has been co-chair of the Joint Working Party on Agriculture and Environment at OECD and is currently member of the Steering Committee of the Tropical Agriculture Platform at FAO.
Selected publications
Pulighe, G.; Bonati, G. et al. - Assessment of the Agronomic Feasibility of Bioenergy Crop Cultivation on Marginal and Polluted Land: A GIS-Based Suitability Study from the Sulcis Area, Italy, Energies 2016, 9(11), 895; https://doi.org/10.3390/en9110895
Pulighe, G.; Bonati, G. et al. - Ongoing and emerging issues for sustainable bioenergy production on marginal lands in the Mediterranean regions - December 2018Renewable and Sustainable Energy Reviews 103:58-70
Coderoni, S.; Bonati, G. et al. - Carbon Footprint of Italian Farms Using Farm Accounting Data Network – Proceedings of the Pacioli meeting, 2012.
Bonati, G. et al – White paper on climate change and agriculture – Rural Development Network – Italian Ministry of Agriculture, 2012
Gelb, E. M.; Bonati, G. - Evaluating Internet for extension in agriculture - The Journal of Agricultural Education and Extension, 1750-8622, Volume 5, Issue 3, 1998, Pages 211 – 216
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Broadband and narrowband applications for agriculture and rural areas:
the Italian experience
Guido BONATI
Consiglio per la ricerca in agricoltura e l’analisi dell’economia agraria Centro di ricerca Politiche e Bioeconomia
Via Po, 14 - Roma, Italy guido.bonati@crea.gov.it
The Italian Strategy for Ultrabroadband aims at providing 100 Mbps Internet connectivity to at least 85% of the population within 2020. For the remaining 15% of the population the minimum connectivity should be at least at 30Mbps. Furthermore, all public buildings (i.e. schools, hospitals, research centers) will benefit of a 100 Mbps connectivity.
Currently Italy features a 58% connectivity rate at 30 Mbps (vs. 80% in Europe) and 12.11% at 100 Mbps (58% at European level).
In order to ensure that the strategy is applied in a uniform way at national level, the government, through a public consultation, identified areas in which telecommunication companies are not wishing to invest in providing advanced connectivity, due to either low population density, or income below average, or a combination of these. In those locations, identified as “market failure” or “white” areas, public support is provided, in order to ensure an adequate level of advanced connectivity.
The overall public investment is in the range of 4 billion Euros, of which 10% will be provided by the Agricultural European Eund for Rural Development and will be specifically targeted at rural areas.
The presentation will cover two different aspects of connectivity for agriculture and in rural areas. In the first part, the current situation of ultrabroadband connectivity in Europe and in Italy, with a specific on the amount of public subsidies to bring fiber to the building (FTTB) or to the home (FTTH), will be presented.
The second part is devoted to the most advanced and innovative services for agriculture that will benefit by the availability of ultrabroadband connectivity, i.e. rural tourism, marketing and promotion of agricultural products, e-government, precision farming, health services, advisory agricultural services.
A special mention is also given to narrowband networks, that might be particularly relevant for agricultural applications.
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Sang-ho, PARK, MAFRA 박상호 (농림축산식품부, 한국)
Session ➊
Presentation 3
KOREA`s Smart Agriculture & Policy
한국 스마트농업 현황 및 정책방향
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Profile
Sangho PARK
Biography
Sangho Park started his career as a public servant in 1998, and continued to work for the MAF (Ministry of Agriculture, Food and Rural Affairs). His current position is the ‘director of Agricultural Industry Policy Team’ in charge of disseminating smart farms and supporting farm ventures, one of national policy and 8 innovative growth tasks of the Moon Administration.
In particular, the smart agriculture industry integrated with ICT technology of Korea is growing fast, and a positive program is established for providing financial support and improving government legislations to make it a representative industry leading the growth of Korean agriculture.
As a manager of International Cooperation Team just before the current position, he was in charge of international cooperation of the MAF, ODA, and overseas agriculture development tasks. One of his achievements is the food aid project with rice produced in Korea since 2018. He made efforts to strengthen the cooperative relationship with international organizations including the IFAD and FAO.
He worked for diverse teams including the Agricultural Policy Team, Rural Policy Team, Cooperative Society Team, Spokesperson Team, Legal Affair Team, Food Industry Policy Team, and Quarantine Research Planning Team of the MAF, and for the Regional Development Committee directly under the Presidential Committee. In addition, he worked as an agricultural policy officer in the EU Embassy based in Belgium for 3 years.
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Smart Agriculture and Policy of Korea
Sangho PARK
Ministry of Agriculture, Food and Rural Affairs 94, Dasom 2-ro, Sejong City
psh23@korea.kr
Korean agriculture is facing difficult challenges. The proportion of agriculture in national GDP is decreasing, and the income gap between urban and rural households becomes wider. A positive trend, however, appears, for example, an increase in rural population or young farmers.
Korea has developed the manufacturing industry, information and communication, that is, IT technology, semiconductor and machinery, which are introduced into and integrated with agriculture, implying future growth of agriculture.
In this context, smart farms (agriculture) are disseminated fast across Korea. As smart farms have positive impact on agriculture, by improving productivity and creating jobs, the government specified smart farms as a leading sector for innovative growth (2017) and actively supports them.
The Moon Administration has enforced the smart agriculture policy to support young farmers, and promotes the related strongholds as an “Innovative Smart Farm Valley.” The government will create 4 Innovative Smart Farm Valleys across Korea by 2022 to provide specialized smart farm training services to young people, and conduct R&D and demonstration of equipment for the smart farm industry.
The concept of smart farming is also applied fast to all sectors of agriculture including farming in unprotected farmland, livestock farming, agricultural robots, self-driving agricultural machinery as well as protected horticulture farming mainly in greenhouses.
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Carlo Bisaglia (CREA, 이탈리아)
Session ➊
Presentation 4
IoT for digital Agriculture
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Profile
Carlo BISAGLIA
Biography
Dr. Carlo Bisaglia is a senior researcher at Consiglio per la ricerca in agricoltura e l’analisi dell’economia agraria, Centro di ricerca ingegneria e trasformazioni agroalimentari, Treviglio, Bergam, Italy. After graduating in Agricultural Science, University of Padua, he achieved the Ph.D. in Technological Innovation for Agri-Food and Environmental Sciences at the University of Milan (Italy).
His research activity concerns the mechanization and automation in the dairy farms; precision agriculture and livestock farming; safety and ergonomics in agricultural machinery; renewable energy production and use in agriculture. He participated to the definition of the Italian guidelines for precision farming. He is contract professor in some Italian Universities and expert for the evaluation of national and UE research projects. He is OECD Tractor test Engineer following Code 2 and 5 since 2000. ORCID ID: http://orcid.org/0000-0002-2699-0757.
Selected publications
1. Pallottino F., Antonucci F., Costa C., Bisaglia C., Figorilli S., Menesatti P. 2018. Optoelectronic proximal sensing vehicle-mounted technologies in precision agriculture: a review. Computers and Electronics in Agriculture 162, 859-873. ISSN 0168-1699. DOI: https://doi.org/10.1016/j.compag.
2019.05.034.
2. Bisaglia C., Brambilla M., Cutini M., Fiorati S., Howell M. 2018. Bi-fuel methane/gasoline engine as powersource for standard agriculture tractors: development and testing activities. Applied Engineering in Agriculture 34(2): 365-375. DOI: http://doi.org/10.13031/aea.12262.
3. Bisaglia C., Brambilla M., Cutini M., Bortolotti A., Rota G., Minuti G., Sargiani R. 2018. Reusing pruning residues for thermal energy production: a mobile app to match biomass availability with the heating energy balance of agro-industrial buildings. Sustainability 10(11), 4218. DOI:
https://doi.org/10.3390/su10114218.
4. Calcante A., Brambilla M., Bisaglia C., Oberti R. 2017. Proposal to estimate the engine oil consumption in agricultural tractors. Applied Engineering in Agriculture 33(2): 191-194. DOI 10.13031/aea.11992.
5. Bisaglia C., Romano E. 2017. A novel magnetic device for intercepting metal foreign objects in Total Mixed Rations. Applied Engineering in Agriculture 33(1): 55-61. DOI: 10.13031/aea.11722.
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IoT for digital agriculture
Carlo BISAGLIA
Consiglio per la ricerca in agricoltura e l’analisi dell’economia agraria Centro di ricerca ingegneria e trasformazioni agroalimentari, sede di Treviglio
Via Milano 43, 24047 Treviglio BG, Italy carlo.bisaglia@crea.gov.it
IoT combines two concepts “Internet” and “Thing” and can therefore semantically be defined as “a world-wide network of interconnected objects uniquely addressable, based on standard communication protocols” [Infso & EpoSS, 2008]. Generally speaking, IoT refers to the networked interconnection of everyday objects, which are often equipped with ubiquitous intelligence. IoT increases the ubiquity of the Internet by integrating every object for interaction via embedded systems, which leads to a highly distributed network of devices communicating with human beings as well as other devices [Xia et al., 2012]. Economic impact of IoT will be considerable ranging from 2.7 to 6.2 trillion $, where agriculture sector account for 0.1 [McKinsey Global Institute, 2015]. 50 billion IP devices will be connected by 2022 [Cisco Systems Inc., 2018]. In this context, agriculture plays a key role in gaining efficiency, but has a challenge to face with considering that, in this sector, “Things” are often living and natural objects (i.e., plants, animals, square meters of soil and amounts of perishable food products) [Verdouw et al., 2019]. For these reasons IoT devices (e.g., microprocessors, sensors, antennas) cannot be easily embedded in products themselves. Furthermore, agricultural production is depending on natural conditions, such as climate (day length and temperature), soil, pests and diseases and weather, harsh environments (open air, cold storage, hot cleaning treatments, etc.). In addition, IoT devices must operate in remote areas (fields, stables, etc.) often coping with internet connectivity problems in rural areas (solar powering of sensors), so autonomy and exchanging data modes are of primary importance. Another peculiarity of agricultural sector deals with matching the seasonality with market requirements. As a matter of fact, food products take time to grow and get ripe with great uncertainties; consumers demand safety food, health and fresh food all year around. Finally, agricultural enterprises are mainly small and medium sized with different management and technical expertise skills, consequently IoT diffusion is often slowed down by management fragmentation.
Following these constraints and considering the technical specificity of the different agricultural areas, some examples with be provided from: i) arable farming sector (i.e. integrating the operations combining IoT technologies); ii) dairy farming (i.e. using of real-time sensor data); iii) orchards and vineyard sector (i.e. integrating the IoT technology throughout the whole supply chain from farm, logistics, processing to retail); iv) vegetables production (i.e. combination of environmental control levels in greenhouse cultivation) and v) meat sector (i.e. automated monitoring and control of animal growth).
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Yong-lyoul KIM, KREI
김용렬 (한국농촌경제연구원, 한국)
Session ➋
Presentation 1
4th Industrial Revolution and Sustainable Agriculture in Korea
4차산업혁명과 지속가능한 농업
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Profile
Yonglyoul, Kim
CONTACT INFORMATION E-mail: kimyl@krei.re.kr
CURRENT POSITION
Research Director, Korea Rural Economic Institute
RESEARCH AREAS
Regional economy, Rural industry, Rural tourism, Rural development, and Impact analysis
EDUCATION
2006 Ph.D., Agricultural Economics, University of Missouri Columbia (July 2006), USA,
JOB EXPERIENCE
Korea Rural Economic Institute (KREI), Mar. 1996 – present
Policy Advisor of Ministry. Ministry of Food, Agriculture, Forestry and Fisheries. June. 2009-Aug.
2010
SOCIAL ACTIVITY
Chairman, Rural Industry Activation Forum, 2016 - present
Policy advisory, Korea Agro-Industrial Complex Council, 2019 - present
Member of Promotion Committee, Asian Afforestation Organization of Climate Change Center, 2014 - present
Executive Director, Korea Regional Economics Association, 2014 - present Executive Director, Korean Green Tourism Association, 2009 - present
POLICY ACTIVITY
Central Advisory, Committee for Rural Convergence Industry, Ministry of Agriculture, Food and Rural Affairs. May, 2017-present
Advisory Committee Member, Presidential Committee for Balanced National Development, 2019-present Committee, Special Committee of Agro-Food Industry, Korea Federation of Small and Medium Business, July, 2011-2014
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PUBLICATIONS
AUG 2, 2019. KIM, Yong-lyoul·LEE, Jung-min·WOO, Sung-hwui. 5G, Changes in Agriculture and Rural Areas, KREI
JAN 25, 2019. LEE, Jung-min·KIM, Chang-ho·KIM, Yong-lyoul. Current Status and Implications of Blockchain technology in the Agriculture. KREI
JUN 2019. KIM, Yong-lyoul‧Ahn, Byeong-il(Corresponding author), “An analysis of the cooperation conditions for pursuing 6th industrialization: application of Shapley value”, The Korean Journal of Agricultural Economics, Vol.60, No.2, The Korean Agricultural Economics Association.
MAY 2018. KIM, Yong-lyoul(Corresponding author)‧Lee, Hyungyong‧Chung, Dochai, “Business Ecosystem Characteristics on the Regional 6th Industrialization”, Journal Of The Korean Society Of Rural Planning, Vol. 24, No. 2,Korean Society of Rural Planning.
NOV 2017. Lee, Jinghong‧KIM, Yong-lyoul(Corresponding author)‧Jung, Goo-hyun, LEE Hae-gil, “A Study on the Revitalization of the Sixth Industry Value Chain through Living Labs”, Journal of Korean Society of Rural Planning, Vol.23, No.4, Korean Society of Rural Planning
FEB 2016. HEO, Joo-nyung∙KIM, Yong-lyoul(Corresponding author). Analysis of Priorities of the 6th Industrialization Policies for Agriculture through AHP. Journal of Korean Society of Rural Planning. vol. 22, no. 1, 2016 (121-128). Korean Society of Rural Planning.
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4
thIndustrial Revolution and Sustainable Agriculture in Korea
Yonglyoul Kim
Korea Rural Economic Institute
601, Bitgaram-ro, Naju-si, Jeollanam-do, 58321, Korea kimyl@krei.re.kr
This presentation is composed of four parts. That is, the first part is ‘The 4th Industrial Revolution and Smart Agriculture; the second is ‘The Effectiveness of Smart Agriculture in Korea’;
the third is ‘How to Use Technology for Sustainable Agriculture’; and the fourth is ‘Directions for Sustainable Agricultural Innovation’.
The first, ‘The 4th Industrial Revolution and Smart Agriculture’, describes the impact of 4th Industrial Revolution Technology on Agriculture. Integration and combination of agriculture with advanced technology can contribute to efficient use of resources, convenience of work, and improved productivity. For such integration and combination, it is necessary to maximize imagination and creativity to find a new road which is not based on conventional ideas.
The second, ‘The Effectiveness of Smart Agriculture in Korea’, examines the effect of smart technology on agriculture. Recent studies show the effect of improved convenience of work, reduced time of work, and more fruits harvested in horticulture, fruit farming, and livestock farming. A survey shows the advanced agricultural technology farmers want the most is agricultural drones, followed by the system for forecasting harmful insects and weeds and the system for early warning about weather disasters customized to farms.
The third, ‘How to Use Technology for Sustainable Agriculture’, is about the report presented in the World Economic Forum. This report describes the positive effect shown when 12 new technologies in 3 sectors are applied to the food industry. The 3 sectors are an exemplary innovation for changing consumer’s demands, an exemplary innovation for strengthening value chains, and an exemplary innovation for efficient production systems.
The 4th part suggests the direction for sustainable agricultural innovation. From the perspective of current trend of the big picture, the focus should be laid on efficiency, sustainability, tolerance, health and food safety. To this end, integration and combination with advanced technology is required from production to distribution and consumption. Three directions are required to advocate this with legislation. First, Activate agricultural ventures and start-ups with competitive technology; Second, Build a platform for sharing data with high availability and reliability; and Third, Improve laws, regulations, and systems to cope with the industrial environment and technological changes.
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Marcello Donatelli (CREA, 이탈리아)
Session ➋
Presentation 2
Biophysical modelling: engineering components and services
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Profile
Marcello DONATELLI
Biography
Dr. Donatelli holds title of Doctor in Agricultural Sciences with a major in Agricultural Engineering at University of Perugia. Tenured researcher since 1985. Sabbaticals at KSU-USA, WSU-USA, and at FAO-Italy. National Expert at the Joint Research Centre of the European Commission for six years.
Director of Research since 2001 and full professor of Agronomy since 2012. Currently Director of the Research Centre for Agriculture and Environment (CREA-AA) of the Italian Council for Agricultural Research and Economics (CREA). The research activity has been on the development and application of simulation models for biophysical systems, also collaborating on the development of the cropping systems model CropSyst. In the last ten years activity has focused on the development of software frameworks for agricultural systems simulation, with applications mainly in the area of climate change impact and adaptation on agriculture. Leader of the development of the BioMA – Biophysical Model Applications framework for the modular development of model components and modelling solutions.
Selected publications
1. Donatelli M., Magarey R.D., Bregaglio S., Willocquet L., Whish J.P.M., Savary S., 2017.
Modelling the impacts of pests and diseases on agricultural systems. Agricultural Systems.
http://www.sciencedirect.com/science/article/pii/S0308521X1730104X
2. Donatelli M., Srivastava, A.K., Duveiller G., Niemeyer S., Fumagalli D,. 2015. Climate change impact and potential adaptation strategies under alternate realizations of climate scenarios for three major crops in Europe. Environmental Research Letters,
http://iopscience.iop.org/1748-9326/10/7/075005/article
3. Bregaglio, S., Donatelli, M., 2015. A set of components for the simulation of plant airborne diseases. Environmental Modelling and Software, 72: 426-444.
http://www.sciencedirect.com/science/article/pii/S13648152150015894 .
4. Donatelli M., Bregaglio S., Confalonieri R., De Mascellis R., Acutis M. 2014. A generic framework for evaluating hybrid models by reuse and composition ? A case study on soil temperature simulation. Environmental Modelling & Software, volume 62, 478-486.
http://dx.doi.org/10.1016/j.envsoft.2014.04.011
5. Donatellli M., G. Russell, A.E Rizzoli, et al. 2010. A component-based framework for simulating agricultural production and externalities. In: Environmental and agricultural modelling: Integrated approaches for policy impact assessment, F.Brouwer and M. van Ittersum editors, Springer, 63-108.
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Biophysical models: engineering components and services
Marcello DONATELLI
CREA Council for Agricultural Research and Economics – Research Centre Agriculture and Environment
Via di Corticella 133, 40128 Bologna, Italy marcello.donatelli@crea.gov.it
The demand of model tools to perform integrated evaluation of agro-ecological systems has further increased in the last decade. New requirements for simulation capabilities have emerged, and the capability to timely transfer research results to modelling tools is key to meet the demand of various stakeholders. The major obstacle to develop such simulation systems has been the fragmented availability of modelling resources, partly due to technical bottlenecks. Extension of modelling resources by adding modules and replacing or changing existing ones to accommodate new modules, has not been at reach except by duplication via full recoding. Furthermore, the intrinsic complexities of the simulation domain and the ever-increasing demand for high resolution of large scale simulations poses a serious problem of resource scaling. In recent years several providers have begun to offer a wide array of cloud services at a competitive price, fostering the mass adoption of cloud technologies. All major cloud platforms nowadays offer scalable, reliable, and resilient computational and data storage assets. To address the challenges posed by big science a twofold effort is required:
engineering model software to allow rapid prototyping and moving both data and computation to a cloud infrastructure to achieve scalability and better replicability.
CREA is currently undergoing a profound IT renovation to refactor its existing simulation tools environment as cloud-based services and microservices. This transformation not only improves dramatically the effectiveness of current research actions, allowing to give rapid response to research problems and to run large scale simulations, but it also offers several research and cooperation opportunities, providing researchers with new tools and business and research partners with production-ready services. Modelling solutions, which are the model resources made available via cloud services, are developed by composition of model components implemented using the framework BioMA. BioMA is a public domain software framework designed and implemented for developing, parameterizing and running modelling solutions based on biophysical models in the domains of agriculture and environment. It is based on discrete conceptual units codified in freely extensible software components. The goal of this framework is to rapidly bridge from prototypes to operational applications, enabling running and comparing different modelling solutions. The goal is not only to provide a framework for model development and operational use but also, and of no lesser importance, to provide a loose collection of objects re-usable either standalone or in different frameworks. Examples of services use are shown.
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Tae-wan KIM, EPIS
김태완 (농림수산식품교육문화정보원, 한국)
Session ➋
Presentation 3
Application of Agrifood Big Data in Various Fields
농업 분야 빅데이터 활용
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Profile
Taewan Kim
Biography
General manager Taewan Kim, studied agricultural economics in Seoul National University, and has worked for the Knowledge Integration Division of Korea Agency of Education, Promotion &
Information Service in Food, Agriculture, Forestry & Fisheries since October, 2019. He was CEO of EZFARM from 2004 to 2013, and the chairperson of Korea Horticulture & ICT Cooperative, and is interested in and studies how to integrate agriculture with information & communication technology.
Use of Big Data for Agri-food
Taewan Kim
Korea Agency of Education, Promotion and Information Service in Food, Agriculture, Forestry and Fisheries
email: wan118@epis.or.kr
The Korea Agency of Education, Promotion & Information Service has collected, analyzed and provided agri-food data since 2015 to find new business models through integration and combination of public data with private data.
It collects information from various fields, for example, production data including the agricultural management, and livestock farm environment, and growth information, distribution data including prices in wholesale markets, rural area information including rural development and farmland information, agricultural policy and subsidy information including the direct payment program.
It collects and analyzes production environment and growth information, and management information of each farmer to provide production and management consulting services to farmers, and data to research institutes and enterprises so that they can use the data for developing best growing models or products.
It provides time-series analysis information about prices in 35 public wholesale markets to facilitate farmers’ and distributors’ decision making, and analyzes social media data to provide services for tracking people’s consumption trends.
It has developed public data since 2015 so that people can use them, builds public data maps to encourage more people to use them, and finds exemplary cases using data to give citations.
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Giovanni Battista Chirico (University of Naples, 이탈리아)
Session ➋
Presentation 4
Satellite-based advisory services for smart agriculture
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Profile
Giovanni Battista CHIRICO
Biography
Current position:
Associate professor of agricultural hydraulics and hydraulic-forest systems for watershed restoration at the Department of Agricultural Sciences Division for Agricultural, Forest and Biosystems Engineering University of Napoli Federico II
Academic career:
2015 – Associate Professor at the University of Naples Federico II 2003 – 2015 Assistant Professor at the University of Naples Federico II
2002 – 2002 Post-doc at the Hydraulic Institute of Vienna University of Technology - Austria
2000 – 2002 Research Fellow at The Department of Civil and Environmental Engineering of The University of Melbourne Australia
Education:
Ph.D. 2002 University of Naples Federico II, Hydraulic Engineering
M.Sc. 1996 University of Salerno, Civil Engineering, with a major in Hydraulics
Awards and academic recognitions for research activities
2019 – Scientific habilitation as full professor for Agricultural Hydraulics
2016 – Certificate of Outstanding Contribution in Reviewing - Journal of Hydrology 2016 – Best Poster Award by the Italian Hydrological Society
2015 – Award “Innovation for sustainable agro-food systems" Milano Expo 2015 2014 – Scientific habilitation as full professor for Agricultural Hydraulics
2014 – Scientific habilitation as associate professor for Agricultural Hydraulics 2013 – Scientific habilitation as associate professor for Hydraulic Engineering
2000 – Outstanding Paper Award - Hydrology Section 2000 Fall Meeting, EOS Trans. AGU, Volume 82, No. 15, pag.176-177, April 10 2001
Main research achievements
Forecasting system of crop water requirement based on the integration of satellite images and numerical weather forecast
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Data assimilation techniques for soil hydrological predictions A hydrological distributed model for catchment hydrology
Selected publications
1. Chirico, G.B., Medina, H., Romano, N. Kalman filters for assimilating near-surface observations into the Richards equation - Part 1: Retrieving state profiles with linear and nonlinear numerical schemes (2014) Hydrology and Earth System Sciences, 18 (7), pp. 2503-2520.
2. Chirico, G.B., Pelosi, A., De Michele, C., Falanga Bolognesi, S., D'Urso, G. Forecasting potential evapotranspiration by combining numerical weather predictions and visible and near-infrared satellite images: An application in southern Italy (2018) Journal of Agricultural Science, 156 (5), pp. 702-710.
3. Pelosi, A., Medina, H., Villani, P., D'Urso, G., Chirico, G.B. Probabilistic forecasting of reference evapotranspiration with a limited area ensemble prediction system
(2016) Agricultural Water Management, 178, pp. 106-118.
4. Medina, H., Tian, D., Srivastava, P., Pelosi, A., Chirico, G.B. Medium-range reference evapotranspiration forecasts for the contiguous United States based on multi-model numerical weather predictions (2018) Journal of Hydrology, 562, pp. 502-517.
IRRISAT: the Italian experience in satellite-based advisory services for smart agriculture
Giovanni Battista CHIRICO
Department of Agricultural Sciences Division for Agricultural, Forest and Biosystems Engineering University of Napoli Federico II
Via Università, 100 – 80055 Portici (NA) gchirico@unina.it
Earth Observation and meteorological forecast are combined in an innovative web-based advisory service (IRRISAT) for monitoring irrigation and crop growth. A simple, intuitive web app makes real time irrigation, evapotranspiration maps and customized weather forecasts (based on high resolution climatic models) accessible from desktop computers, tablets and smartphones. The tool is operationally employed in Italy and has been also successfully applied Southern Australia. The key-points of this tool are: a) personalized irrigation requirement; b) timely delivery of information; c) visual representation of in-field variability in crop development and water demand.
Satellite-based vegetation indexes, such as NDVI, have been intensively used to monitor vegetation biomass and crop growth. In few cases these data have been transferred to final users (i.e. farmers and water managers) to improve cropping and irrigation practices. As today, two main developments
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in the field of Earth Observation have occurred: a) availability of new generations of sensors, with enhanced spectral and spatial resolution; b) detailed knowledge of the processes that determine the response of vegetated surface as detected from remote sensors in different regions of the electromagnetic spectrum. These advancements have made possible a “quantitative” approach in the interpretation of Earth Observation data, ready for operational applications i.e. irrigation scheduling and water management.
The IRRISAT service has been developed by the Department of Agricultural Sciences of the University of Naples Federico II, in collaboration with the spin-off company Ariespace (www.ariespace.com). IRRISAT is based on the state-of-art research to provide users (farmers, water managers, river basin authorities) with satellite-based maps of actual canopy development and variability at sub-plot scale, and irrigation requirements. IRRISAT goes beyond the classic NDVI approach since it aims at the estimation of canopy parameters such as Leaf Area Index to derive crop water requirements and growth. It is based on the processing of high-resolution (10-20 m) multispectral satellite images, which are processed to deliver final products to farmers in near real time (24-36 hours), The information, both in map and numerical form, is presented in a dedicated webGIS-site with access restricted to growers and basin authorities in order to better control the irrigation process and consequently improve its overall efficiency. Furthermore, IRRISAT is integrated with meteorological forecast up to five days (Chirico et al., 2018).
Depending on the crop phenology, IRRISAT processes from weekly images throughout the irrigation season, acquiring data from the SENTINEL-2 platforms of the European Space Agency to take full advantage of its enhanced spectral capabilities at 10 m spatial resolution. The algorithm for determining the evapotranspiration and successively the irrigation requirements is based on the well-known FAO-Penman-Monteith, with canopy parameters (LAI, albedo) estimated from multispectral images. This information together with the actual irrigation depth applied, allows for benchmarking the irrigation efficiency from the plot to the district scale.
The platform of IRRISAT is designed to be visualized either on PCs either on tablets and smartphones by means of a simple and intuitive interface. Daily irrigation maps with a forecast horizon of 5 days from the last irrigation can be visualized together with crop and weather data (LAI, evapotranspiration, irrigation, rain, temperature). The color range of the map goes from red (low evapotranspiration – bare soil) to intense blue (high evapotranspiration – fully developed vegetation). It takes only one click within one of the plots to acquire information from the tabs appearing below the map. The system displays the data for every required pixel (pixel based). It is possible to view information in every plot and compare the data of one plot to the others. Different field locations can be selected to compare in-plot variability of all the relevant data in form of multitemporal plots.
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Eun-suk JANG, RDA 장은숙 (농촌진흥청, 한국)
Session ➌
Presentation 1
Sustainable Agriculture in Response to Climate Change
기후변화에 대응한 지속가능 농업 발전 방안
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Profile
Eunsuk JANG
Biography
Jang Eun-sook acquired a doctorate in meteorology at Pusan National University. Currently, she works for the National Institute of Agricultural Sciences (NAS), where she supervises all duties related to climate-change ecology. She plans and manages NAS projects for the reduction of greenhouse gas, agricultural meteorology, agricultural environment information, and the preservation of the farming environment. Recently, she expands her work areas into the impact assessment of fine dust in farming and is in charge of a task to minimize its impact.
Sustainable Agriculture in Response to Climate Change
Eun-suk JANG
National Institute of Agriculture Sciences Rural Development Administration Jeonju-si Nongsaengmyeong-ro, 300
sun90g@korea.kr
Climate change, directly and indirectly, influences a wide range of areas, including meteorology, ecology, environment, and water resources. Extraordinary weather conditions caused by climate change such as hot waves, droughts, torrential rains, and extreme frosts transform the agricultural environment.
Also, these extreme weather conditions can damage agrarian infrastructure, such as irrigation facilities, resulting in impacts on food production. Sustainability in farming targets to preserve environmental resources and to keep agricultural productivity for agriculture of the present and future as well.
The reduction of greenhouse gas emissions will mitigate climate change, and climate-smart agriculture (CSA) is essential to strengthen adaptability to climate change and to maintain crop productivity.
Also, to realize CSA, it is necessary to assess the impact and vulnerability of climate change and to prepare climate-smart systems to adapt to or mitigate climate change and to recover from it. Against this backdrop, Korea’s smart farm is in progress using state-of-art technologies (drones, big data, IoT, AI, and robots) to tackle issues of local climate change and farming conditions.
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Remigio Berruto (University of Turin, 이탈리아)
Session ➌
Presentation 2
Logistic and innovation drivers for the adoption of
precision farming
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Profile
Remigio Berruto
Biography
Born in Moncalieri on 13/07/1963, he graduated in 1987 with a grade of 110 cum laude, and was qualified as an agronomist. In 2004, he received a Ph.D. in agricultural systems management from Purdue University, Indiana, USA, with a thesis on logistics strategies to improve the performance of grain storage centers.
Since 1990 he has been working at the Department of Agricultural Engineering at the University of Turin. He is currently an associate professor.
Since 1985 he has been a member of the Italian Association of Agricultural Engineering - AIIA.
Since 1996 he has been a member of ASABE - American Society of Agricultural and Biological Engineers. He is the founder of the CIGR working group on logistics and president of the CIGR (International Association of Agricultural Engineers) - section V - (2015-2018).
He is president of EFITA - the European Federation of Information Technologies for Agriculture and Agro-Food (2015-2017).
He was CIGR V President (2015-2018) and he is now CIGR Incoming President (2019-2020).
His research activity focuses on the analysis of systems and simulation of logistics distribution of agri-food products, management software for the agri-food industries and for traceability. He currently develops applications for smartphones and is an expert in flipped classroom, an innovative teaching methodology.
He teaches master classes on distribution logistics, renewable energy systems for agriculture, database management, simulation and biomass supply chains. He has presented over 200 articles in international journals and conferences.
Selected publications
1. A2. Busato, P., Sopegno, A., Pampuro, N., Sartori, L. and Berruto, R., 2019. Optimization tool for logistics operations in silage production. Biosystems Engineering, 180, pp. 146–160.
2. A3. Rodias, E.C., Sopegno, A., Berruto, R., Bochtis, D.D., Cavallo, E. and Busato, P., 2019. A combined simulation and linear programming method for scheduling organic fertiliser application.
Biosystems Engineering, 178, pp.233–243.
3. A11. Sopegno, A., Calvo, A., Berruto, R., Busato, P. and Bochtis, D., 2016. A web mobile
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application for agricultural machinery cost analysis. Computers and Electronics in Agriculture, 130, pp.158–168.
4. A12. Busato, P. and Berruto, R., 2016. Minimising manpower in rice harvesting and transportation operations. Biosystems Engineering, 151, pp.435–445.
5. A15. Pavlou, D., Orfanou, A., Busato, P., Berruto, R., Sørensen, C. and Bochtis, D., 2016.
Functional modeling for green biomass supply chains. Computers and Electronics in Agriculture, 122, pp.29–40.
6. A16. Busato, P., Berruto, R., Zazueta, F.S. and Silva-Lugo, J., 2016. Student Performance in Conventional and Flipped Classroom Learning Environments. Applied Engineering in Agriculture, 32(5), pp.509–518.
7. A19. Busato, P., 2015. A simulation model for a rice-harvesting chain. Biosystems Engineering, 129, pp.149–159.
Logistic and innovation drivers for the adoption of precision farming
Remigio Berruto
Dept. of Field, Forestry and Food Science Largo braccini, 2
Remigio.berruto@unito.it
There are 4 innovation drivers: they are the technology itself, the training, the entrepreneurship and availability of business models and communication. In addition to these factors we have the regulation that plays an important role too.
In addition, we will have a look at the logistics. Logistic is that part of the supply chain that plans, implements and controls the efficient and effective flow and storage of good, services and related information from the point of origin to point of consumption in order to meet customer’s requirements (Ricks et al., 2002). Farmers are no longer to be considered alone, but as a part of the food supply chain. Logistic has a very important impact on technical, economic and sustainability indicators of agricultural processes, and there are some logistic principles that drive the adoption of the precision farming and of the innovation in agriculture, especially related to machinery use in agriculture.
These aspects will be explained during the presentation.
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