<abstract xmlns="http://www.w3.org/1999/xhtml">Algeria has recently experienced an important agricultural development in terms of gardening in plastic greenhouses thanks to the favourable factors (climatic conditions, etc.). In order to optimize the energy requirements, data from 29 farmers were collected, who qualitatively represent the greenhouse vegetable producers from the most productive sub-provinces of Biskra region (south of Algeria). Considering the various parametric and non-parametric methods for energy consumption optimization, data envelopment analysis is the most common non-parametric method applied. Results showed that the mean radial technical efficiency assumptions of the samples under constant returns to scale and variable returns to scale models were 0.88 and 0.98, respectively. The 51.72% of decision-making units were efficient on the basis of the constant returns to scale model; 79.31% decision-making units were observed efficient on the basis of variable returns to scale model. Calculation of optimal energy requirements for vegetable greenhouse indicated that 108.50 GJ·ha−1 can be saved on machinery (1.38 GJ·ha-1); diesel fuel (4.68 GJ·ha−1); infrastructure (9.35 GJ·ha−1); fertilizers (17.08 GJ·ha−1); farmyard manure (12.05 GJ·ha−1); pesticides (3.93 GJ·ha−1); and electricity (60.03 GJ·ha−1).</abstract>

Algeria has recently experienced an important agricultural development in terms of gardening in plastic greenhouses thanks to the favourable factors (climatic conditions, etc.). In order to optimize the energy requirements, data from 29 farmers were collected, who qualitatively represent the greenhouse vegetable producers from the most productive sub-provinces of Biskra region (south of Algeria). Considering the various parametric and non-parametric methods for energy consumption optimization, data envelopment analysis is the most common non-parametric method applied. Results showed that the mean radial technical efficiency assumptions of the samples under constant returns to scale and variable returns to scale models were 0.88 and 0.98, respectively. The 51.72% of decision-making units were efficient on the basis of the constant returns to scale model; 79.31% decision-making units were observed efficient on the basis of variable returns to scale model. Calculation of optimal energy requirements for vegetable greenhouse indicated that 108.50 GJ·ha−1 can be saved on machinery (1.38 GJ·ha-1); diesel fuel (4.68 GJ·ha−1); infrastructure (9.35 GJ·ha−1); fertilizers (17.08 GJ·ha−1); farmyard manure (12.05 GJ·ha−1); pesticides (3.93 GJ·ha−1); and electricity (60.03 GJ·ha−1).

Energy Requirement Optimization of Greenhouse Vegetable Production Using Data Envelopment Analysis (DEA) Method in Algeria

Acta Technologica Agriculturae

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.

Algeria has recently experienced an important agricultural development in terms of gardening in plastic greenhouses thanks to the favourable factors (climatic...

Energy Requirement Optimization of Greenhouse Vegetable Production Using Data Envelopment Analysis (DEA) Method in Algeria

Published Online: Jun 05, 2020

Page range: 60 - 66

DOI: https://doi.org/10.2478/ata-2020-0010

Keywords
greenhouse cultivation, input–output analysis, Biskra, DEA, Algeria

© 2020 Ahmed Nourani et al., published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.

Energy Requirement Optimization of Greenhouse Vegetable Production Using Data Envelopment Analysis (DEA) Method in Algeria

Published Online: Jun 05, 2020

Page range: 60 - 66

DOI: https://doi.org/10.2478/ata-2020-0010

Keywordsgreenhouse cultivation, input–output analysis, Biskra, DEA, Algeria

© 2020 Ahmed Nourani et al., published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.

Keywords
greenhouse cultivation, input–output analysis, Biskra, DEA, Algeria