We are going through a period in which the concept of the smart village (SV) is a novelty for the management of a community, and the new smart economy of the village is based on the power of community support. Appropriately, the development of a SV is related to a family’s participation in the motivation and access to education, the increase in knowledge of information technology, information and communications technology (ICT) literacy, and also in the creation of facilities for research and development (R&D). The partnership between the public administration, the private sector, and the community heads will lead to a smart economy within the village. At the same time, the intervention of the food system to support climate change can be supported by intelligent agriculture. The SV has a strong social significance; research in the field can be multidisciplinary, including human nutrition, climate change, and community education. This paper aims to X-ray the research areas of the SV from a multidisciplinary sense, in support of the partnership with the community, and to identify the main directions of strategic development. In total, 368 pieces of research on SVs from the last ten years were analyzed through bibliometric analysis using VOSviewer software, doubled by the co-occurrence of keywords and the bibliometric combination of documents, followed by a systematic review of the literature. The research undertaken was intended to contribute to the development of research for SVs, with the analysis of identified clusters. The results obtained will have a special contribution at the SV level through strategic and research proposals and suggest that the most important strategic and research directions for SVs focus on community education, its satiety, as well as several environmental and social changes generated by SVs.

Moldova possesses the largest area of farmland as a share of its total land surface, an advantage which should encourage economic development strategies oriented towards the agriculture sector. Government subsidies and agriculture loans have been used as tools for developing the Moldavian agriculture. However, considering the challenges generated by both climate change (the drought from year 2012 that affected 80% of farmland) and a difficult political situation (restrictions imposed by the Russian Federation on the Republic of Moldova’s agri-food imports and exports between 2013 and 2014), the country’s agricultural system ranks very low when it comes to agricultural production efficiency. The present paper analyses the performances of the agricultural sector and its impact on the Moldavian economy over a nine-year period (between 2008 and 2016), by using a custom-developed analytical framework based on a dataset containing 21 relevant indicators. The analytical framework generates various perspectives that can be used to elaborate an economic sustainable development strategy of the Moldavian agriculture sector. The development of the analytical framework is based on the dynamics of agriculture subsidies, agricultural loans, the agricultural sector’s gross domestic product (GDP) and gross value added (GVA), as well as the dynamics of agricultural production and production value, also considering the main crops belonging to the Moldavian agriculture sector. The results are presented as sets of mathematical regression models that quantify the relationships found between the relevant agricultural parameters and their impact on the economics of the agricultural sector. It has been identified that the agriculture sector has a considerable impact on the Moldavian economy, a fact revealed by the significant model between the agriculture GVA and total GVA and GDP. A significant, negative correlation model was identified between agriculture subsidies and agriculture loans, although a small percentage of Moldavian agriculture farms were subsidized. Strong correlation models were also identified between wheat and maize production and total agriculture production, emphasizing the importance of these two crops for the Moldavian agricultural economy. Grape and maize production values also generated a correlation model, emphasizing the market interconnection between these crops It can be concluded that the increase in value of governmental agriculture subsidies, as well as expanding their addressability in order to maximize the access possibility for a higher number of agriculture farms, are essential for the Moldavian agriculture sector’s future development, since considering the limiting value of and accessibility to subsidies, a direct correlation model was identified between governmental agriculture subsidies and agriculture GVA.

The current paper presents a fuzzy sensory quality certification of organic mint honey as a component of the strategy to promote intensive beekeeping. This sensory analysis is based on fuzzy logic that allows the processing of data represented by linguistic terms. For the development of the fuzzy sensory analysis model of bee honey, we develop a MATLAB application, with the help of which we modeled the sensory perceptions in relation to the main quality characteristics of mint honey in relation to the other varieties of honey. The sensory quality index of each honey assortment is obtained by converting qualitative assessments through linguistic terms into a set of three numerical values on a sensory scale of assessment of results with five linguistic values: unsatisfactory, satisfactory, average, good, excellent. Indices of fuzzy sensory quality associated with honey varieties are certified using a blockchain model that is an information technology that offers the opportunity to develop local markets for organic bee products.

This paper presents a fuzzy quality certification of wheat. This analysis is based on the fuzzy analysis model of wheat. We developed a Matlab application with the help of which we modeled the perceptions in relation to the main quality physical and chemical characteristics of wheat obtaining a quality index of wheat lots. The algorithm presented in this article allows for obtaining and using the global quality index, generating applicability not only to the commercial sphere as a quality reference and price setting, but also a measure of appreciation of processing opportunities. Indices of fuzzy quality associated with wheat lots using a fuzzy model offer the opportunity to develop local markets through quality certification.

This study explores the effects of applying agri-environmental measures and digitalization on cereal farms in Dunărea de Jos Basin, Romania. Through structured interviews with 40 wheat producers, complemented by field observations and data analysis, effects are identified in highlighting planning, data evaluation and approximation to European environmental requirements. Wheat productivity and input efficiency are investigated in partially technologically advanced farms compared to poorly technologically advanced farms. Regression is used in the relationship between average wheat production and the main agricultural inputs. The results show statistically significant correlations, supported by coefficients (R² > 0.45). In partially mechanized farms, wheat production is influenced by the use of plant protection products (R² = 0.943), demonstrating high technological consistency and improved efficiency of phytosanitary applications. In farms not using Geofolia, the application of NPK fertilizers appears as the dominant factor of productivity (R² = 0.968), indicating that chemical fertilization compensates for limited mechanization and restricted access to technological operations. Digitalization of farms contributes to the optimization of resources, reducing diesel consumption by 45% and developing overall efficiency by 34%, reducing the pressure on the environment by 30%. Technology can be responsible for increasing farm productivity and yield performance, while reducing resource intensity and environmental impact.