Impact of the Implementation of Environmental Management Systems in Agribusiness Worldwide. A Systematic Review
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The main objective of this research was to determine the most relevant impact on the implementation of Environmental Management Systems (EMS) in agribusiness worldwide according to the most recent research work published. For this, the methodology of systematic review of the literature was used, considering IOP SCIENCE, PROQUEST and SCOPUS DATABASES, and information search strategies under inclusion and exclusion criteria. The results obtained were 38 articles, in which the impacts derived from the application of environmental management systems in agroindustrial activity were evidenced, identifying economic, environmental, and social impacts and research published by country, among which Indonesia, Brazil, Colombia and Greece stand out. It is concluded that the most relevant impact in the environmental field was the reduction and control of emissions, effluents, waste, as well as the reduction of the use of agrochemicals including pesticides and fertilizers. In the economic field, the increase in revenues was reported due to the opening of global markets and increase in product sales prices, reducing energy consumption and reducing losses due to waste, improving productivity, as well as reducing expenses for the application of sanctions due to environmental accidents and waste treatment.In the social sphere, it is reported that recycling practices are adopted, awareness is raised and the knowledge and capacities of stakeholders for environmental care and protection are improved.
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.
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.000 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| 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 it