Assessing Sustainability Performance at the Farm Level: Examples from Greek Agricultural Systems

Abstract

In recent years, farmers and policymakers have faced ample challenges and have struggled to support the sustainability of the agricultural sector. Sustainable agriculture encompasses multiple concepts, and its performance produces extensive debate about data requirements, appropriate indicators, evaluation methods, and tools. Under the European Union (EU) financed project FLINT (Farm Level Indicators for New Topics in policy evaluation), detailed data have been collected at the farm level to provide broader coverage of sustainability indicators on a wide range of relevant topics to facilitate the assessment of sustainability performance. The approach has been applied in a pilot network of representative farms at the EU level, considering the heterogeneity of the EU farming sector to provide data infrastructure with up to date information for sustainability indicators. This study aims to assess sustainability performance at the farm level in Greece. Representative and dominant agricultural systems, such as permanent crops, olive trees, arable crops, and livestock (sheep) farms, comprise the Greek sample. It uses the analytical hierarchy process (AHP) methodology and attempts to gain insights into the sustainability performance of agricultural systems. The outcome of the sustainability assessment reveals knowledge and develops support for strategic farm choices in order to support both farmers and policymakers towards more sustainable development plans. The results indicate that three typical Mediterranean farming systems, like permanent crops, olive trees, and extensive livestock systems (sheep farms), are more sustainable in contrast to intensive and arable crop farms.

Long-term changes in rainfed olive production, rainfall and farmer’s income in Bailén (Jaén, Spain)

“…Recently, another pressure on olive groves-the urban sprawl-has begun to exert its influence. The main issue here is to achieve sustainability, and it is important to develop farm-scale approaches such as that we developed in Bailén or those developed by Tzouramani et al (2020) in Greece and Palese et al (2013) in Italy.…”

Assessing the important factors of sustainable agriculture development: An Indicateurs de Durabilité des Exploitations Agricoles‐Analytic Hierarchy Process study in the northern region of Vietnam

“…The AHP approach was developed by Saaty (1986) and involves three basic steps to (a) structure the criteria into a hierarchic system, (b) use the surveyed data to calculate the pairwise comparison matrices and the relevant statistics (e.g., the eigenvectors, the consistency index and the consistency ratio), and (c) assess the relative important of each criteria in different hierarchies. The details of those steps can be found in Saaty (1986), Rezaei‐Moghaddam and Karami (2008) and Tzouramani et al (2020), among others.…”

“…Similarly, Liang and Peng (2017) identified that manpower input is the most important factor whilst geographic location is the least important one in the autonomous landscape development of rural communities in Taiwan. In Greece, Bartzas and Komnitsas (2020) designed an environmental AHP model to identify the most sustainable agricultural management practices at regional level whilst Tzouramani, Mantziaris, and Karanikolas (2020) examined the sustainability performance at the farm level. In a similar vein, Hai, Hai, Y, and Hens (2009) used the AHP approach to analyse 16 health and environmental indicators of sustainable development in a central province in Vietnam and found that this development was weak during the 2000-2005 period.…”

Analysis of Sustainability In Livestock Production Systems In Cordoba, Colombia.

“…Step 1: For each of the farms, the environmental, economic, and social variables will be evaluated, taking into account the variables described in the methodology. (24) Step 2: For each of the categories, the variability of the variables is analyzed and those that have constant values or do not have information on at least 50% of said variable in the farms are not considered in the study (25)(26) of NA.…”