Special Issue "Intelligent Decision Support for Agri-Food Green Supply Chain"

A special issue of Agronomy (ISSN 2073-4395). This special issue belongs to the section "Farming Sustainability".

Deadline for manuscript submissions: 22 October 2021.

Special Issue Editors

Dr. Giacomo Falcone
E-Mail Website
Guest Editor
Department of Agricultural Sciences, Mediterranean University of Reggio Calabria, Feo di Vito, 89122 Reggio Calabria, Italy
Interests: life cycle assessment; life cycle costing; social life cycle assessment; life cycle sustainability assessment; agricultural economics; food production cost; agribusiness economics; organization and management of agribusinesses
Special Issues and Collections in MDPI journals
Dr. Antonio Violi
E-Mail Website
Guest Editor
Department of Law, Economics, Management and Quantitative Methods, Università degli Studi del Sannio, Via delle Puglie 82, 82100 Benevento, Italy
Interests: decision support systems; stochastic programming; decision models for energy and financial markets; optimization models for agri-food logistics; risk management

Special Issue Information

Dear colleagues,

The agri-food sector is moving towards a new evolutionary era that will characterize the economy and ecology of the future: a productive version of agriculture that, in line with the principles of ecology, puts order back into the agronomic disciplines, a perfectly agro-ecological version of agriculture: the so-called Agriculture 5.0.

Consistent with this wave of renewal of production models, the European Union, through the Green Deal, has set the goal of rewriting the future of food and agriculture within a global program that aims to achieve climate neutrality by 2050 and a 55% reduction in emissions by 2030.

The reduction of environmental impacts, the reduction of waste, and the valorisation of by-products are only some of the possible strategies that the entrepreneur can adopt for a greener and more circular supply chain.

Technologies can play a decisive role in achieving these objectives without, however, threatening the economic sustainability of the company and affecting the technical feasibility of the processes. A new impetus towards this change has been given by the COVID-19 pandemic, which is redesigning economic sectors and posing new challenges to the world population.

It is therefore necessary that agri-food entrepreneurs are supported in their choices in order to pursue the ambitious objective of re-designing the supply chains with a view to sustainability. In such a context Intelligent Decision Support Systems (IDSS), based on the new huge availability of data and on advanced methodological results, can lead to significant improvements on both efficiency and effectiveness of decision processes in the agri-food supply chain.

Methodological applications, theoretical discussions, and literature reviews are welcome to this Special Issue. Papers received will be subject to a rigorous peer review procedure with the aim of rapid and wide dissemination of research results, developments, and applications.

Dr. Giacomo Falcone
Dr. Antonio Violi
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All papers will be peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Agronomy is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1800 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • agri-food green supply chains
  • environmental sustainability
  • smart agriculture
  • operations research methods for agri-food
  • decision making under uncertainty & risk management
  • decision Support Systems
  • green logistics

Published Papers (2 papers)

Order results
Result details
Select all
Export citation of selected articles as:

Research

Article
Life Cycle Assessment to Highlight the Environmental Burdens of Early Potato Production
Agronomy 2021, 11(5), 879; https://doi.org/10.3390/agronomy11050879 - 29 Apr 2021
Viewed by 421
Abstract
Climate change, food security, and the protection of the planet’s resources require the adoption of sustainable production models. Achieving sustainable development in the agri-food sector enables the creation of new opportunities for operators, guiding farmers towards more environmentally friendly practices and offering cost-effective [...] Read more.
Climate change, food security, and the protection of the planet’s resources require the adoption of sustainable production models. Achieving sustainable development in the agri-food sector enables the creation of new opportunities for operators, guiding farmers towards more environmentally friendly practices and offering cost-effective results. Organic farming paradigms are promoted by the transformation of some harmful practices of conventional agriculture, such as the wide use of chemical products of synthesis, the deep workings that favor the erosive processes, the excessive use of nitrogenous fertilizers. There are still gaps in the knowledge of the real performance of some products that strongly support the local economic system of Sicily (Italy). The research aims to highlight the differences in environmental impact caused by the cultivation of organic early potatoes compared to the conventional regime and the same per kg of product obtained. To this end, the widely used methodology for comparing the environmental impacts of agricultural production systems is the Life Cycle Assessment, which allows us to highlight the phases in which environmental criticalities are most concentrated. An interesting agroecological picture of knowledge emerges, since organic farming is by definition an ecological model that supports the principles of the Green Deal, it often requires interventions to improve the yields obtained in order to achieve a positive result both in terms of cultivated surface and kg of product obtained. Full article
(This article belongs to the Special Issue Intelligent Decision Support for Agri-Food Green Supply Chain)
Show Figures

Figure 1

Article
Optimized Supply Chain Management of Rice in South Korea: Location–Allocation Model of Rice Production
Agronomy 2021, 11(2), 270; https://doi.org/10.3390/agronomy11020270 - 31 Jan 2021
Cited by 1 | Viewed by 712
Abstract
Planning for optimized farming with the aim of providing ideal site and cultivar selection is critical for a stable and sustainable supply of rice with sufficient quantity and quality to customers. In this study, a range of morphological characteristics and yield of eight [...] Read more.
Planning for optimized farming with the aim of providing ideal site and cultivar selection is critical for a stable and sustainable supply of rice with sufficient quantity and quality to customers. In this study, a range of morphological characteristics and yield of eight rice cultivars that are commonly cultivated in Korea were investigated from 2005 to 2020. All morphological characteristics were significantly different among the eight rice cultivars. The dataset of morphological characteristics and yield was used to isolate groups of similar rice cultivars. The k-means clustering method was used to group the rice cultivars. Three groups (Group 1, Group 2, and Group 3) were created. Most cultivars were in Group 1. High-yielding rice cultivars were in Group 2, while the rice cultivars in Group 3 had the lowest rice grain yield. After grouping these rice cultivars, ideal farming locations for all three rice cultivar groups were identified to reduce transportation cost using an optimized location–allocation model. Simulation results suggested the following: (1) Group 1 should be produced in Jellanam-do (south west region), (2) Group 2 should be produced in Chungcheongnam-do (central west region), and (3) Group 3 should be mainly produced in the central west region of South Korea. Simulation results showed the potential to reduce transportation cost by around 0.014%. This can also reduce 21.04 tons of CO2 emission from a freight truck. Because these eight cultivars only make up 19.76% of the total rice production in South Korea, the cost reduction proportion was only 0.014% of total revenue. In future studies, more rice cultivars should be investigated to increase the efficiency of the model performance. Full article
(This article belongs to the Special Issue Intelligent Decision Support for Agri-Food Green Supply Chain)
Show Figures

Figure 1

Back to TopTop