Extending the inputeoutput energy balance methodology in agriculture through cluster analysis

Abstract

The inputeoutput balance methodology has been applied to characterize the energy balance of agricultural systems. This study proposes to extend this methodology with the inclusion of multivariate analysis to reveal particular patterns in the energy use of a system. The objective was to demonstrate the usefulness of multivariate exploratory techniques to analyze the variability found in a farming system and, establish efficiency categories that can be used to improve the energy balance of the system. To this purpose an inputeoutput analysis was applied to the major greenhouse tomato production area in Colombia. Individual energy profiles were built and the k-means clustering method was applied to the production factors. On average, the production system in the study zone consumes 141.8 GJ ha 1 to produce 96.4 GJ ha 1 , resulting in an energy efficiency of 0.68. With the k-means clustering analysis, three clusters of farmers were identified with energy efficiencies of 0.54, 0.67 and 0.78. The most energy efficient cluster grouped 56.3% of the farmers. It is possible to optimize the production system by improving the management practices of those with the lowest energy use efficiencies. Multivariate analysis techniques demonstrated to be a complementary pathway to improve the energy efficiency of a system.