Life cycle assessment of a commercial-scale valorized grocery food waste product and its potential use as a sustainable feed input for egg production
Bibliographic record
Abstract
Food waste is a major sustainability challenge in modern society. Livestock production also presents core sustainability challenges, notably due to its demand for feed inputs and associated impacts. Directly valorizing food wastes to livestock feed at a commercial scale has hence emerged as a potential strategy to solve both problems. However, case studies of such systems are limited, particularly in western countries, representing an important knowledge gap. This study reports a cradle-to-gate Life Cycle Assessment of a commercial-scale grocery waste-to-poultry feed input production system based in Pennsylvania, and the use of the resultant feed product for egg production in Canada. Findings for the valorized input product system showed a net environmental benefit for climate change and eutrophication impact categories due to avoided landfill emissions when no landfill gas collection is assumed. Using feed containing 5% valorized product in egg production reduced the life cycle environmental impacts of conventional Canadian eggs in 10 out of 11 impact categories, including a 17% impact reduction in climate change at the 20-year horizon. However, fossil fuel depletion saw a 57% increase in impacts, due to process and technical inefficiencies in the studied product system and Pennsylvania’s reliance on fossil fuel for electricity production. Contribution, scenarios, and sensitivity analyses highlighted the importance of utilizing green energy sources, along with efficient transportation and substrate drying technologies. The study also highlighted the need for further research to optimize the inclusion rate of the valorized product in poultry feeds, and better resolved regional, infrastructural, and logistical contexts.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".