The aim of this paper is to propose a multi-attribute hierarchical evaluation model for the evaluation of the aggregate sustainability of livestock farms integrating the economic, environmental, and social aspects. This approach uses an aggregation criterion based on the geometric mean to assess a farm’s current level of sustainability. Sustainability was measured through the use of indicators including carbon footprint, farm income, and animal welfare. Secondly, based on the relationships between the sustainability aspects, the effects of improvement measures on all the indicators were estimated. This paper presents eight livestock case studies from Italy, analyzed in 2014. The results show intermediate values for the aggregate index of sustainability for most of the farms. The index mainly depends on the estimated values of the sustainability indicators related to the economic and environmental aspects. Lower values of animal welfare sustainability are quantified. The introduction of improvement measures in relation to the preparation of the soil had positive effects, both in terms of emissions and animal welfare. The increase of available space per Livestock Unit (LU) resulted in the greatest positive effect on animal welfare, among all the other actions analyzed.

This article aims to investigate the environmental and economic sustainability of five dairy farms in the Umbria Region (Italy). The study also provides an assessment of aggregate sustainability, which is less investigated with reference to cattle milk both globally and in Italy, through the analysis of the relationship between economic and environmental performance. Primary data were collected through a direct survey carried out in 2014. The environmental assessment was conducted with a Life Cycle Assessment (LCA) “cradle to farm gate” approach, while the economic dimension was evaluated by determining the direct and indirect costs related to the factors involved in the production process. A correlation analysis and a linear regression were performed in order to study the relationship between the carbon footprint (CF) and operating income. The average operating income amounted to 0.03 Euro/L of milk. The CF values of the five companies are contained within a variation range comprised between 0.90 and 1.76 kg CO₂ eq/L of milk. The existence of an inverse relationship between the CF of milk and operating income confirms the hypothesis regarding the possibility of implementing strategies aimed at improving performance in both investigated dimensions at the same time, thus increasing the aggregate sustainability.

In recent years, eco-efficiency assessment has proven to be an effective tool to reduce the environmental damages of agricultural activities while preserving their economic sustainability. Hence, this paper aims to assess the eco-efficiency of a sample of 148 beef cattle farms operating in the extensive livestock system of Central Italy. The analysis is based on Farm Accountancy Data Network (FADN) economic data in the year 2020 and includes, as environmental pressures, farm expenditure for the use of fuels, electricity and heating, and fertilizers. A two-stage approach was implemented: in the first stage, an input-oriented DEA model including slack variables was used to quantify farm eco-efficiency scores and determine the polluting inputs’ abatement potentials. In the second stage, the influence of possible influencing factors on eco-efficiency scores was tested using a regression model for truncated data. The analyzed farms were found to be highly eco-inefficient, as they could abate their environmental pressures, on average, in a range from 56% to 60% while keeping the value of their global production constant. Fertilizers and fuel consumption were identified as the least efficiently operating inputs, with potential reductions in terms of the related expenditures fluctuating between 9% and 42%. Farms showing a high-intensity livestock system, a low labor intensity, and a larger farm area were recognized as the most eco-efficient. Environmental and animal welfare subsidies were found to not affect eco-efficiency, while a negative influence was estimated for a single farm payment, which does not seem to be an incentive mechanism for farms to operate efficiently.

The productive sectors related to agriculture have the potential to contribute significantly to the energy transition. The paper describes an in-depth investigation on the extra virgin olive oil production towards the decarbonization of the sector. A multidimensional approach is applied, integrating surveys on environmental impacts through Life Cycle Assessment and Carbon Footprint, carbon sequestration, carbon balance associated to emissions and removals, and socio-economic impacts via Life Cycle Costing and consumer surveys. The assessment was performed in the different Mediterranean regions, and the paper includes the results from a representative case study in Italy. Focusing on the production of 1 l of olive oil as functional unit, the most impacting technical processes were identified, and cleaner alternatives proposed and implemented. The amount of CO₂ sequestered annually by olive trees was found 1.59 kg/l_oil, comparable to the CO_2eq emitted for oil production - i.e., 1.58 kg/l_oil for a 0.75 l glass bottle, and 1.16 kg/l_oil for a 5 l tin can - and then resulting in a neutral/negative carbon footprint product in the sustainable management scenario. In economic terms the introduction of the low-impact technical process allows to reduce production costs of 270 euros/ha; while the willingness to pay a premium price for the olive oil with Carbon Footprint certification is estimated around 3 € for a 0.75 l glass bottle. The proposed methodology could be extended to other agronomic sectors to reduce carbon emissions, enhance traditional techniques and promote sustainable practices, while also seeking to engage the consumer through transparent certification and communication.

Saffron (Crocus sativus L.) is one of the most expensive spices in the world due to its strong market demand combined with its labor-intensive production process, which needs a lot of labor and has significant costs. New cultivation methods and traceability systems are required to improve and valorize local Italian saffron production. In this study, we conducted a three-year trial in Umbria (Central Italy), looking for a soilless cultivation method based on wooden bins posted at a suitable height from the ground to ease the sowing of corms and harvesting of flowers. Moreover, the spice traceability could be based on investigating the genetic variability of Italian saffron populations using SNP markers. The proposed novel cultivation method showed significantly higher stigma and corm production than the traditional one. At the same time, the genetic analysis revealed a total of 55 thousand SNPs, 53 of which were specific to the Italian saffron populations suitable to start a food traceability and spice certification.