The Aspects of Artificial Intelligence in Different Phases of the Food Value and Supply Chain

被引:11
作者
Baciuliene, Vaida [1 ]
Bilan, Yuriy [2 ]
Navickas, Valentinas [1 ,3 ]
Civin, Lubomir [2 ]
机构
[1] Kaunas Univ Technol, Sch Econ & Business, LT-44249 Kaunas, Lithuania
[2] Czech Univ Life Sci, Fac Econ & Management, Prague 16500, Czech Republic
[3] Lithuania Business Univ Appl Sci, LT-91249 Klaipeda, Lithuania
关键词
artificial intelligence; food supply chain; artificial intelligence challenges; MANAGEMENT;
D O I
10.3390/foods12081654
中图分类号
TS2 [食品工业];
学科分类号
0832 ;
摘要
The types of artificial intelligence, artificial intelligence integration to the food value and supply chain, other technologies embedded with artificial intelligence, artificial intelligence adoption barriers in the food value and supply chain, and solutions to overcome these barriers were analyzed by the authors. It was demonstrated by the analysis that artificial intelligence can be integrated vertically into the entire food supply and value chain, owing to its wide range of functions. Different phases of the chain are affected by developed technologies such as robotics, drones, and smart machines. Different capabilities are provided for different phases by the interaction of artificial intelligence with other technologies such as big data mining, machine learning, the Internet of services, agribots, industrial robots, sensors and drones, digital platforms, driverless vehicles and machinery, and nanotechnology, as revealed by a systematic literature analysis. However, the application of artificial intelligence is hindered by social, technological, and economic barriers. These barriers can be overcome by developing the financial and digital literacy of farmers and by disseminating good practices among the participants of the food supply and value chain.
引用
收藏
页数:12
相关论文
共 55 条
  • [1] Precision Irrigation Management Using Machine Learning and Digital Farming Solutions
    Abioye, Emmanuel Abiodun
    Hensel, Oliver
    Esau, Travis J.
    Elijah, Olakunle
    Abidin, Mohamad Shukri Zainal
    Ayobami, Ajibade Sylvester
    Yerima, Omosun
    Nasirahmadi, Abozar
    [J]. AGRIENGINEERING, 2022, 4 (01): : 70 - 103
  • [2] Digital transformation, development and productivity in developing countries: is artificial intelligence a curse or a blessing?
    Aly, Heidi
    [J]. REVIEW OF ECONOMICS AND POLITICAL SCIENCE, 2022, 7 (04) : 238 - 256
  • [3] Digitalization in the agri-food industry: the relationship between technology and sustainable development
    Annosi, Maria Carmela
    Brunetta, Federica
    Capo, Francesca
    Heideveld, Laurens
    [J]. MANAGEMENT DECISION, 2020, 58 (08) : 1737 - 1757
  • [4] Performance measurement in agri-food supply chains: a case study
    Aramyan, Lusine H.
    Lansink, Alfons G. J. M. Oude
    van der Vorst, Jack G. A. J.
    van Kooten, Olaf
    [J]. SUPPLY CHAIN MANAGEMENT-AN INTERNATIONAL JOURNAL, 2007, 12 (04) : 304 - 315
  • [5] Baiulien V., 2020, EUR SCI, V2, P34
  • [6] Baruchelli P., 2020, EIT DIGIT
  • [7] Bikausk D., 2020, SOCIALNO EKON REV, V2, P12
  • [8] Machine Vision and Machine Learning for Intelligent Agrobots: A review
    Bini, D.
    Pamela, D.
    Prince, Shajin
    [J]. 2020 5TH INTERNATIONAL CONFERENCE ON DEVICES, CIRCUITS AND SYSTEMS (ICDCS' 20), 2020, : 12 - 16
  • [9] Carrico G., 2018, EUR VIEW, V17, P29, DOI DOI 10.1177/1781685818764821
  • [10] CHRISTOPHER M., 2005, LOGISTICS SUPPLY CHA, V3rd