The globalization of contemporary Food Supply Chains (FSCs) has introduced complexities involving multiple actors, food product transportation, and diverse information. Traditional information systems in FSCs face challenges in ensuring transparency and traceability due to the inherent complexities of multi-actor involvement, global transportation, and diverse information, making it difficult to ascertain product origin and processes, exacerbating issues such as food loss, safety concerns, and financial hazards. Blockchain technology, in conjunction with ancillary technologies, offers potential solutions to these challenges. This systematic literature review endeavors to comprehensively explore the multifaceted dimensions of blockchain’s role in FSC management, with an emphasis on food safety and traceability, across six thematic areas, each guided by distinct criteria. These areas include general information, FSC application, factors of blockchain adoption, blockchain platform, ancillary technologies, and the related impact of blockchain adoption. From the 2097 documents found, 122 full-text articles were assessed, and 61 were included and classified in this study based on criteria. These criteria underscore blockchain's capacity for transparency, resilience, and sustainability in FSCs. The results further indicate that blockchain's integration within the FSCs has unveiled a tapestry of possibilities and considerations that underpin its transformative potential in business systems. Blockchain’s inherent traits of transparency and immutability can enhance traceability, mitigate food fraud, and facilitate consumer trust, reshaping the information system’s implementation in the FSC landscape. However, challenges such as integration complexities, data quality, scalability, and regulatory concerns should be addressed. Through these challenges, Artificial Intelligence (AI) arises as a potential solution complementing Blockchain. This amalgamation can effectively tackle certain existing obstacles, such as ensuring data accuracy and system compatibility, while providing stronger solutions for food safety and fraud prevention. The implementation of a comprehensive blockchain solution requires strategic collaboration, technological refinement, and regulatory alignment to fully realize its benefits and address the intricate management challenges of traditional FSC information systems.

Glasshouse farming is one of the most intensive types of production of agricultural products. Via this process, consumers have the ability to consume mainly off-season vegetables and farmers are able to reduce operational risks, due to their ability to control micro-climate conditions. This type of farming is quite competitive worldwide, this being the main reason for formulating and implementing assessment models measuring operational performance. The methodology used in this study is Data Envelopment Analysis (DEA), which has wide acceptance in agriculture, among other sectors of the economy. The production protocols of four different vegetables—cucumber, eggplant, pepper, and tomato—were evaluated. Acreage (m²), crop protection costs (€), fertilizers (€), labor (Hr/year), energy (€), and other costs (€) were used as inputs. The turnover of every production unit (€) was used as the output. Ninety-eight agricultural holdings participated in this survey. The dataset was obtained by face-to-face interviews. The main findings verify the existence of significant relative deficiencies (including a mean efficiency score of 0.87) as regards inputs usage, as well as considerably different efficiency scores among the different cultivations. The most efficient of these was the eggplant production protocol and the least efficient was that used for the tomato. The implementation of DEA verified its utility, providing incentives for continuing to use this methodology for improving land management decision making.

The Agricultural Knowledge and Innovation System (AKIS) and the Farm Advisory Service (FAS) are important elements of the current Programming Period of the Common Agricultural Policy (2023–2027), as it is now deemed necessary to transition the European agricultural model to more sustainable forms, through the dissemination of agricultural knowledge, while simultaneously promoting innovative methods. An Agricultural Knowledge and Innovation System must be able to propose and develop ideas for the transmission of agricultural knowledge, promoting innovation and the exchange of ideas. The present study includes a significant number of investigations on the effectiveness of the implementation of the AKIS and the FAS so that the conclusions are representative of the scope of the work. The object in question is now the cornerstone of the modernization of agricultural production and an important way out towards more competitive models of agriculture. The purpose of this paper is to give an extensive overview of the degree of implementation of Agricultural Knowledge and Innovation Systems in the countries of the European Union (including the United Kingdom until 2019) from 2014 until today, essentially during the implementation of the second period of Common Agricultural Policy. In the context of this article, the main results of the research carried out in the EU countries during the period under study and the proposed improvements by the researchers, where they are mentioned, are recorded epigrammatically. Finally, the countries are categorized according to the degree of implementation of the AKIS and the contribution of the Agricultural Advisory System to more sustainable forms of agricultural practices.

This study aims to evaluate critical success factors (CSFs), considering the perspectives of various stakeholders who are involved in enterprise resource planning (ERP) implementation in agricultural processing companies in Central Macedonia (Greece). This evaluation—combined with aspects from the literature—may show how a digital production system can be managed and redesigned to become sustainable for a company. Research was conducted through the use of a specially designed questionnaire that was addressed to various stakeholders in the ERP implementation in agricultural processing companies. Descriptive statistics, Grey Relational Analysis (GRA), and Friedman test methods were used in order for relevant information to be identified and valid conclusions to be drawn. Given the results of the grey relational analysis (GRA), respondents consider 33 out of 37 critical success factors to be “very important”. Friedman test results seem to differ from GRA results in 19 out of 37 factors with regard to their ranking. Based on this, and using two different methods, the most important ERP critical success factors are highlighted. For the objective aim of this paper to be fulfilled, there is a contribution giving insights into stakeholders’ perspectives regarding the management of a digital production system in the field of agricultural processing companies. It also contributes to the literature, as it highlights methods that refer to the evaluation of critical success factors for ERP implementation.

The aim of this study is to compare three mathematical programing models used for sustainable land and farm management. The sample for the comparison was 219 agricultural holdings participating as beneficiaries of the measure ‘Modernization of agricultural holdings’ in the Rural Development Plan at the Region of Central Macedonia in Greece. Using the crop plan of the agricultural land of these farms the mathematical programming models calculate the optimum solution under different and conflicting goals. The results of the methodologies of Linear Programming (LP), of Positive Mathematical Programming (PMP) and Weighted Goal Programming (WGP), are compared in terms of the proposed agricultural land changes. The sustainability of farms is measured with the use of eleven economic, social, and environmental indicators. Each model has some unique advantages and disadvantages that can enable it to be implemented in particular situations. In the conclusions to this research the characteristics of each model are highlighted.