Comparative Life Cycle Assessment (LCA) in the Agri-Food Industry, Focusing on Organic and Conventional Coffee
Bibliographic record
Abstract
This study evaluates the environmental burden of organic and conventional coffee systems with a functional unit (FU) of 1 kg for market-ready, dried coffee. The ISO 14040 and ISO 14044 framework and guidelines are applied to organic and conventional coffee systems, using a cradle-to-grave approach and the methodology of ReCiPe Endpoint 2008, cumulative energy demand (CED), and the Intergovernmental Panel for Climate Change (IPCC). Superior sustainability was achieved for organic coffee compared to the performance of conventional coffee, with values of 218.50 mPt (conventional) and 146.10 mPt (organic), and a global warming potential (GWP) of 2.12 kg CO2 eq FU−1 (organic) and 1.44 kg CO2 eq FU−1 (conventional). CED fossil-based consumption totalled 25 MJ and 35 MJ for organic and conventional coffee systems, respectively. Conventional and organic coffee system hotspots stemmed from the planting (chemical fertilizer), drying, and packaging processes. This study emphasizes the environmental benefits of organic practices and their relatively lower impact than conventional methods. Within a growing sector, best management practices in the form of actionable insights from a life cycle assessment must be sought to ensure environmental sustainability in parallel with the UN’s goals.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".