Bibliographic record
Abstract
Brazil stands out as one of the world's main producers of animal protein, ranking sixth in global egg production. However, production growth, along with environmental impacts, pose a potential threat to the sustainability of the food system. Methods for evaluating and quantifying the environmental impacts generated by Brazilian egg production remain scarce, lacking current reports on comparative effects or guiding standards. Therefore, new production systems are being implemented slowly, as the adoption of new systems can impact the price of the product and make it less accessible to the consumer. With the aim of supporting and promoting improvements related to sustainability in the Brazilian egg industry, this study aims to carry out an assessment of the life cycle, from the cradle to the farm gate, in accordance with ISO 14040 and 14044 standards, for the intensive production of eggs in cages. Egg production-related emissions results were 65.06 kg SO2 eq., 27.74 kg N eq., 3,086.71 kg CO2 eq., 75,152.66 CTUe, 2.75E-05 CFC-11 eq.; 1,0044.68 kg MJ eq. per ton of eggs produced. When considering the results of CO2 emissions eq. in international life cycle assessments in egg production, the values represent 1.4 to 5.58 kg of CO2 eq. per kg of egg produced. Countries such as Czech Republic, Canada, USA, UK, Australia and Sweden have smaller carbon footprints when compared to Brazilian production. While Mexico, Spain and the Netherlands represent larger footprints than Brazilian egg production. When comparing the results of this study with the values of the environmental impacts of Brazilian agro-industrial productions, egg production represents impacts relatively close to the average impacts of broiler and swine production. To compose this work, four articles were developed. The first two articles dealt with the state of the art in approaching the topics: I) life cycle thinking as a qualitative model and life cycle assessment as a quantitative scientific method; II) assessment of the life cycle of egg production, focusing on international studies, but aimed at assessing the life cycle of the Brazilian egg industry. The last two scientific articles address: III) the modeling of the composting area included as part of the life cycle inventory; IV) the final assessment of all environmental impacts related to the production of eggs and related products in the intensive cage system. As this is the first assessment of the life cycle of the Brazilian egg industry, the results presented may serve as a comparative reference for future studies and data analyzes in different egg production systems in Brazil. These findings provide a basis for continued efforts to improve sustainability practices in the industry and offer valuable information for stakeholders seeking to implement effective interventions for a more sustainable egg production system in the country. Keywords: Agricultural sector. Category of impacts. Emissions. Environmental impacts. Inventory analysis. Productive chain. Sustainability.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".