Energy, Environmental and Economic Analysis of Broiler Production Systems with and Without Photovoltaic Systems
Bibliographic record
Abstract
The study analyzed energy, environmental impact, and costs in intensive broiler production systems in the southeast of the state of Minas Gerais, Brazil, comparing scenarios with and without photovoltaic systems. Four configurations were evaluated, considering different ventilation types (positive and negative pressure) and photovoltaic generation. The Life Cycle Assessment (LCA), with a functional unit of 1 kg of live weight of chicken and a cradle-to-gate approach, indicated that photovoltaic systems reduce between 2.58 t and 4.96 t of CO2-eq annually, in addition to offering better energy efficiency. Economically, sheds with positive pressure ventilation have the lowest cost–benefit ratios, while the feeding subsystem was the one that contributed the most to global warming, among the environmental impact categories evaluated in the LCA. Photovoltaic systems demonstrated the potential to reduce electricity costs between 19.4% and 26.5% per year. However, coffee husks used as chicken litter accounted for 36.5% of production costs, highlighting the need for more economical alternatives. It was concluded that photovoltaic systems are a viable solution to reduce environmental impacts and increase profitability, reinforcing the importance of resource-use optimization strategies in poultry farming.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".