Explore the vast range of titles available.

The ongoing climate crisis and growing water scarcity are exerting increasing pressure on agriculture in Southern and Western Europe, leading to reduced crop yields, greater risk of land abandonment, and deterioration of soil quality. Despite the extensive literature on irrigation and water use in agriculture, the specific relationship between irrigation availability and changes in the type of farming (ToF) remains insufficiently investigated. This study aims to address this gap by analyzing data from the 2010 and 2020 Italian General Agricultural Censuses conducted by ISTAT, in combination with microdata from the Italian Farm Accountancy Data Network (FADN), focusing on irrigated farms in Southern Italy. Descriptive analysis reveals that over 60% of irrigated farms specialize in permanent crops and predominantly adopt efficient irrigation systems such as drip irrigation. Between 2010 and 2020, approximately 23.8% of farms changed their ToF; however, these transitions were not generally associated with improvements in productivity or profitability. Results from logistic regression models suggest that structural variables—including Utilized Agricultural Area (UAA), economic size, and demographic characteristics such as the farmer’s gender—play a more significant role in determining changes in the ToF than the presence of irrigation itself. Moreover, the adoption of organic practices and larger farm sizes are positively associated with ToF changes. These findings suggest that while there has been some shift toward less water-demanding and potentially more sustainable crops, the impact of irrigation on such transitions remains limited. The results underscore the need for more targeted agricultural policies and improved data collection to support effective climate adaptation strategies in the sector.

Small farms are gaining space and importance within the agricultural policies implemented by the European Union, mainly for the role that they play for the preservation of the territory and for the economic development of local rural areas. Small farms represent a new opportunity to guarantee the permanence of populations and agricultural workers in rural areas, contributing to the formation of the income of farming families. Therefore, in this study, after identifying small farms as those farms that have a Standard Output (SO) of less than EUR 25,000, their structural characteristics were defined, as well as their economic and financial situation. The analysis was performed using the Italian FADN data for the years 2018–2020 and using a set of structural and economic–financial indicators. Furthermore, the study analyzes the relationship between farm performance and agricultural resources and also with farmer demographics and farm size. The principal Component analysis was used to reduce the number of variables used in the Ordinary Least Square (OLS) regression model which was applied to identify the factors contributing to the small farms’ profitability. The territorial distribution of small farms shows a polarization: 37% of them are in Southern Italy, and more than 34% of them are in Northern Italy. The analysis also reveals that about 67% of the Italian small farms are specialized, in particular, in arable land (37.6%) and herbivores (16.8%). They are mainly conducted by men with a high school education level and with an age that is between 40 and 65 years. The economic results also show a good performance, however, there is a wide district differentiation: while the Northern regions have the best results in terms of farm net income, those of Southern Italy are more dependent on the public support they receive. The results of the multiple linear regression analysis revealed which variables (e.g., land size, labor, public aid, etc.) had a direct relationship with the profitability of small farms. The research provides interesting insights to stakeholders on the public support (specific measures) that needs to be designed and implemented to favor the survival of small farms in rural areas.

The increasing number of supermarkets and hypermarkets poses a risk to the survival of small local shops in rural areas. As a result, people living in remote areas might need to travel several kilometers to obtain food, and this can create objective difficulties for those who do not drive or cannot afford the cost of owning a car. This study uses a natural experiment to analyze outshopping practices in Italian remote areas using the database of the multipurpose survey on Italian families carried out by Italian National Institute of Statistics. For this study, we used the COVID-19 lockdown as a state of nature when long-range shopping trips were less frequent, and we compared it with the pre-COVID-19 habits, in order to identify changes in consumption and shopping behavior. Our study is the first to explore outshopping behaviors in remote areas of Italy, offering original insights into food access and healthy eating where research is currently lacking. We performed a difference-in-difference analysis, comparing remote areas with other areas in Italy, to highlight the effect of outshopping in remote areas. Our results show how a considerable share of consumer food expenditure is paid to firms outside the local area, supporting the hypothesis of financial resources shift from the local business to large retailers. Moreover, we found limited food access and diet issues in Italian internal areas when outshopping practices are constrained.

The new Common Agricultural Policy (CAP) for the period 2023–2027 commits farmers towards achieving ambitious environmental objectives through farm organization and management. This European agricultural policy has adapted to the contemporary challenges faced by the new model of agricultural development. It aims to enhance the contribution of agriculture to the EU’s environmental and climate objectives while providing better targeted support to small-scale farmers to promote farms’ competitiveness. The main objective of this paper is to describe Italian farms and classify them into groups based on their main characteristics, as well as to analyze their performance and behavior in terms of sustainability and competitiveness. The novelty and innovativeness of this study are found in the data used; a 2020 dataset from the Italian Farm Accounting Data Network (FADN) was used. The quality of FADN data in farm sustainability assessment is widely acknowledge in the literature. To achieve the purpose of this study, a multivariate analysis, in particular, the Principal Components Analysis (PCA), and a Cluster Analysis (CA) were applied. These analyses helped us to obtain the factorial axes which then enabled us to identify economic information on farms, and a better interpretation of farmers’ aptitude to undertake environmentally friendly actions. As a result, eight groups of farms were identified, and their characteristics and performance were described at Italian district level. The results of the study reflect the influence of European interventions towards encouraging farmers to use more environmentally friendly agricultural practices. Under this perspective, the findings contribute to the current debate on green architecture pursued by the future European agricultural policy.

This work presents a harmonized multi-year dataset on crop areas (hectares) and production (tonnes) for 20 major crops at the European regional classification of Nomenclature of Territorial Units for Statistics (NUTS 2 level), sourced from Eurostat and national statistics for the period 2017–2021. The dataset was created through a systematic process of data collection, integration and validation, ensuring consistency and reliability across countries and years. Data processing and harmonisation were performed using an R script, with detailed metadata provided to support transparency and reproducibility of the workflow. Validation was carried out using independent and official data sources to ensure the accuracy and consistency of the dataset over time. The resulting dataset supports comparative assessments of crop area and production across regions and time and provides a robust and reliable resource for various domains (strategic planning, environmental impact assessments, modeling, research, and statistical reporting), aids in shaping regional agricultural policies, and contributes to promoting a more sustainable agricultural landscape across Europe.

Italy is divided into 773 Agricultural Regions (ARs) based on shared physical and agronomic characteristics. These regions offer a valuable tool for analyzing various geographical, socio-economic, and environmental aspects of agriculture, including the climate. However, the ARs have lacked geospatial data, limiting their analytical potential. This study introduces the “Italian ARs Dataset”, a georeferenced shapefile defining the boundaries of each AR. This dataset facilitates geographical assessments of Italy’s complex agricultural sector. It also unlocks the potential for integrating AR data with other datasets like the Farm Accounting Data Network (FADN) dataset, in Italy represented by the Rete di Informazione Contabile Agricola (RICA), which samples hundreds of thousands of farms annually. To demonstrate the dataset’s utility, a large sample of RICA data encompassing 179 irrigated crops from 2011 to 2021, covering all of Italy, was retrieved. Validation confirmed successful assignment of all ARs present in the RICA sample to the corresponding shapefile. Additionally, to encourage the use of the ARs Dataset with gridded data, different spatial-scale resolutions are tested to identify a suitable threshold. The minimal spatial scale identified is 0.11 degrees, a commonly adopted scale by several climate datasets within the EURO-CORDEX and COPERNICUS programs.

Recent studies have pointed out how digital innovations may boost more sustainable farming systems and have positive impacts on supporting the trajectories of smart rural development. The present work aims to analyze possible connections among digitalization, innovation and sustainable rural development through a three-pronged nexus thinking approach. This link is examined from a 'discrete context' perspective, by assuming heterogeneity (which means that differences among farms may emerge in the process of adopting innovation) as a characteristic in adopting innovation and by investigating the potential impacts on local rural development. The empirical analysis draws on secondary sources, taking farms from the last Italian census of agriculture into account. Through a multivariate analysis, farms are grouped into homogenous clusters according to different types of nexuses. The results reveal a very interesting reality characterized by high levels of territorial heterogeneity in the adoption of digital and innovative solutions, bringing about scattered geographies of nexuses in the Italian farming system.

This study dealt with multifunctional farming, which is meant as a dynamic strategy that is carried out by Italian farms. The path alongside the multifunctional paradigm is carried out through both supply chain and territorial strategies, which deserve more attention. These strategies reinforce sustainable business models characterized by the presence of both deepening and broadening strategies. The first ones are centered around product differentiation and valorization through geographical indications, organic farming, etc. Broadening strategies are implemented through new on-farm activities, such as agritourism, and other gainful activities carried out at the farm level. Set against this background, the article discusses the evolution of farms according to the Farm Accountancy Data Network (FADN) database by putting forward an empirical analysis, which considered the evolution of farm typologies oriented toward multifunctionality in the last decade. The analysis underlined the positive dynamics and the evolution of farms adhering to the multifunctional paradigm. Moreover, as evidenced in the econometric analysis, the adoption of multifunctional farming activities provided a sound contribution to income formation. This addressed some policy issues that were identified at the beginning of the new programming period for rural development of the EU and their resolution aims to reinforce the virtuous trajectory toward multifunctional farming.

One of the main challenges faced by many rural areas is the presence of natural constraints, such as climatic conditions, steep slopes, and poor soil quality, which make agricultural production and activities more difficult and costly. In these areas, there is a significant risk of agricultural land abandonment, leading to potential losses in biodiversity, degradation of rural landscapes, desertification, and increased forest fire risk. The Common Agricultural Policy (CAP) aims to mitigate these risks through specific payment schemes provided to areas facing natural and other specific constraints. In this context, mapping and measuring territorial differentiation is essential for informing policy responses. At the end of the previous CAP programming period, the EU updated its classification of Less Favored Areas (LFAs), experimenting with a flexible approach based on common biophysical criteria (definitions and thresholds) and methodological guidelines to delineate territorial differentiations that are both locally relevant and comparable across member states. This contribution presents a review of the current state of data and spatial inference systems used in Italy to delineate biophysical limitations and assess the presence of factors that may help offset the impact of natural constraints. This process has supported the analysis of territorial differentiation and highlighted the related implications for agricultural entrepreneurs operating in diverse contexts.

The multifunctionality model is receiving more and more attention from policymakers as a result of recent initiatives to build more resilient and sustainable food systems as well as the potential for increased farm revenue. This paper explores the role of multifunctional farming in the Italian agriculture viewed through the lens of an entrepreneurial strategy grounded on-farm diversification. Farm diversification strategies, which broaden the farm’s traditional boundaries to include additional activities at the farm level, help the evolution towards multifunctionality. A policy-driven transition towards multifunctional farming has been noticed in Italy during the past few decades, which has prompted a strategic reconfiguration of the farm’s business models. Drawing on the identified activity of portfolio diversification, this study provides an overview of the analyzed 49,429 Italian farms, by articulating diversification strategies into four entrepreneurial activities, which are related to on/off-farm/farm-related or farm-diverse diversification strategies. This article has attempted to verify the presence of farm types that responded to portfolio diversification management strategies through the use of a cluster analysis on data from the general census of Italian agriculture. Supporting new patterns in the adoption of business models focused on multifunctionality should be considered in European rural development policies.