Comparison of the technical efficiency of greenhouse banana farms in terms of energy efficiency, costs and greenhouse gas emissions using Stochastic Frontier model in Turkey

• This study is the first to compare the input and output energy amounts, costs, GGH emission amounts of banana farms producing under greenhouse conditions according to the Good Agricultural Practice levels, and to the technical efficiency levels of the farms. • In farms operating within the scope of Good Agricultural Practices, the amount and cost of input energy and GGH emi have been reduced, while the amount of output energy has been increased, increasing the income of the farmers. • In farms where Good Agricultural Practices are applied, the rate of renewable energy use is higher, while the rate of non-renewable energy use is lower. • Technical efficiency was higher in farms operating within the scope of Good Agricultural Practices. The primary objective of this study was to evaluate the technical efficiency of greenhouse banana farms with respect to energy use, production costs, and greenhouse gas (GHG) emissions. A total of 255 farms were classified into three categories based on their adoption level of Good Agricultural Practices (GAP). The mean technical efficiencies for the Poor-, Mid-, and High-Level farms were 69.70 %, 70.60 %, and 88.50 %, corresponding to inefficiencies of 30.30 %, 29.40 %, and 11.50 %, respectively. Total input energies were 95,692.50, 97,854.83, and 98,466.65 MJ ha⁻¹, while the respective output energies were 195,621.88, 210,071.71, and 239,017.85 MJ ha⁻¹. Consequently, energy use efficiencies were 2.04, 2.15, and 2.43, and energy productivities reached 0.69102, 0.72772, and 0.82285 MJ kg⁻¹. Marginal physical productivity (MPP) analysis indicated that labor constituted the dominant contributor to input energy across all farm categories. Renewable energy use was 46,742.05, 47,985.93, and 52,342.32 MJ ha⁻¹, whereas non-renewable energy use was 49,220.71, 49,868.90, and 46,124.33 MJ ha⁻¹ in Poor-, Mid-, and High-Level farms, respectively. Total GHG emissions per hectare were 48,988.67, 45,227.22, and 37,306.99 kg CO₂-eq, corresponding to 0.739, 0.635, and 0.460 kg CO₂-eq per kilogram of banana. Scenario analysis further revealed that achieving 100 % technical efficiency under GAP conditions would enable substantial resource and emission savings. Specifically, average input energy use and GHG emissions could be reduced by 23,914.2 MJ ha⁻¹ and 10,894.3 kg CO₂-eq ha⁻¹, respectively. This improvement would translate into an estimated cost saving of USD 4563.8 per hectare in input energy and an additional USD 10,746.9 per hectare in output energy revenue.

Authors

Institutions

Publication Details

Journal
Energy Nexus
Published
2025-10-18
DOI
https://doi.org/10.1016/j.nexus.2025.100571
Citations
1
Primary Topic
Efficiency Analysis Using DEA
Type
article
Field-Weighted Citation Impact
2.11
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Comparison of the technical efficiency of greenhouse banana farms in terms of energy efficiency, costs and greenhouse gas emissions using Stochastic Frontier model in Turkey

Nuran TAPKI
1 citations
Energy Nexus
Efficiency Analysis Using DEA
2.11
article

Comparison of the technical efficiency of greenhouse banana farms in terms of energy efficiency, costs and greenhouse gas emissions using Stochastic Frontier model in Turkey

Nuran TAPKI
article en
1 citations

Abstract

• This study is the first to compare the input and output energy amounts, costs, GGH emission amounts of banana farms producing under greenhouse conditions according to the Good Agricultural Practice levels, and to the technical efficiency levels of the farms. • In farms operating within the scope of Good Agricultural Practices, the amount and cost of input energy and GGH emi have been reduced, while the amount of output energy has been increased, increasing the income of the farmers. • In farms where Good Agricultural Practices are applied, the rate of renewable energy use is higher, while the rate of non-renewable energy use is lower. • Technical efficiency was higher in farms operating within the scope of Good Agricultural Practices. The primary objective of this study was to evaluate the technical efficiency of greenhouse banana farms with respect to energy use, production costs, and greenhouse gas (GHG) emissions. A total of 255 farms were classified into three categories based on their adoption level of Good Agricultural Practices (GAP). The mean technical efficiencies for the Poor-, Mid-, and High-Level farms were 69.70 %, 70.60 %, and 88.50 %, corresponding to inefficiencies of 30.30 %, 29.40 %, and 11.50 %, respectively. Total input energies were 95,692.50, 97,854.83, and 98,466.65 MJ ha⁻¹, while the respective output energies were 195,621.88, 210,071.71, and 239,017.85 MJ ha⁻¹. Consequently, energy use efficiencies were 2.04, 2.15, and 2.43, and energy productivities reached 0.69102, 0.72772, and 0.82285 MJ kg⁻¹. Marginal physical productivity (MPP) analysis indicated that labor constituted the dominant contributor to input energy across all farm categories. Renewable energy use was 46,742.05, 47,985.93, and 52,342.32 MJ ha⁻¹, whereas non-renewable energy use was 49,220.71, 49,868.90, and 46,124.33 MJ ha⁻¹ in Poor-, Mid-, and High-Level farms, respectively. Total GHG emissions per hectare were 48,988.67, 45,227.22, and 37,306.99 kg CO₂-eq, corresponding to 0.739, 0.635, and 0.460 kg CO₂-eq per kilogram of banana. Scenario analysis further revealed that achieving 100 % technical efficiency under GAP conditions would enable substantial resource and emission savings. Specifically, average input energy use and GHG emissions could be reduced by 23,914.2 MJ ha⁻¹ and 10,894.3 kg CO₂-eq ha⁻¹, respectively. This improvement would translate into an estimated cost saving of USD 4563.8 per hectare in input energy and an additional USD 10,746.9 per hectare in output energy revenue.

Energy NexusVol. 20
Mustafa Kemal University (TR)
Openalex Percentile: Top 10%
Efficiency Analysis Using DEA
2.11
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.