Energy Requirement Optimization of Greenhouse Vegetable Production Using Data Envelopment Analysis (DEA) Method in Algeria
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 greenho...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
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Sciendo
2020-06-01
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| Series: | Acta Technologica Agriculturae |
| Subjects: | |
| Online Access: | https://doi.org/10.2478/ata-2020-0010 |
| _version_ | 1798016776422817792 |
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| author | Nourani Ahmed Bencheikh Abdelaali |
| author_facet | Nourani Ahmed Bencheikh Abdelaali |
| author_sort | Nourani Ahmed |
| collection | DOAJ |
| description | 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). |
| first_indexed | 2024-04-11T15:56:08Z |
| format | Article |
| id | doaj.art-bed5c15ab1a74655ab065fe959563fd8 |
| institution | Directory Open Access Journal |
| issn | 1338-5267 |
| language | English |
| last_indexed | 2024-04-11T15:56:08Z |
| publishDate | 2020-06-01 |
| publisher | Sciendo |
| record_format | Article |
| series | Acta Technologica Agriculturae |
| spelling | doaj.art-bed5c15ab1a74655ab065fe959563fd82022-12-22T04:15:10ZengSciendoActa Technologica Agriculturae1338-52672020-06-01232606610.2478/ata-2020-0010ata-2020-0010Energy Requirement Optimization of Greenhouse Vegetable Production Using Data Envelopment Analysis (DEA) Method in AlgeriaNourani Ahmed0Bencheikh Abdelaali1Scientific and Technical Research Center on Arid Regions (CRSTRA),Biskra, AlgeriaUniversity of Ahmed Draia Adrar,AlgeriaAlgeria 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).https://doi.org/10.2478/ata-2020-0010greenhouse cultivationinput–output analysisbiskradeaalgeria |
| spellingShingle | Nourani Ahmed Bencheikh Abdelaali Energy Requirement Optimization of Greenhouse Vegetable Production Using Data Envelopment Analysis (DEA) Method in Algeria Acta Technologica Agriculturae greenhouse cultivation input–output analysis biskra dea algeria |
| title | Energy Requirement Optimization of Greenhouse Vegetable Production Using Data Envelopment Analysis (DEA) Method in Algeria |
| title_full | Energy Requirement Optimization of Greenhouse Vegetable Production Using Data Envelopment Analysis (DEA) Method in Algeria |
| title_fullStr | Energy Requirement Optimization of Greenhouse Vegetable Production Using Data Envelopment Analysis (DEA) Method in Algeria |
| title_full_unstemmed | Energy Requirement Optimization of Greenhouse Vegetable Production Using Data Envelopment Analysis (DEA) Method in Algeria |
| title_short | Energy Requirement Optimization of Greenhouse Vegetable Production Using Data Envelopment Analysis (DEA) Method in Algeria |
| title_sort | energy requirement optimization of greenhouse vegetable production using data envelopment analysis dea method in algeria |
| topic | greenhouse cultivation input–output analysis biskra dea algeria |
| url | https://doi.org/10.2478/ata-2020-0010 |
| work_keys_str_mv | AT nouraniahmed energyrequirementoptimizationofgreenhousevegetableproductionusingdataenvelopmentanalysisdeamethodinalgeria AT bencheikhabdelaali energyrequirementoptimizationofgreenhousevegetableproductionusingdataenvelopmentanalysisdeamethodinalgeria |