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Record W7112532774

Evaluating Cut Flower Sustainability: An Environmental and Social Life Cycle Framework for Rose Production in North America

2024· article· en· W7112532774 on OpenAlexaboutno aff

Bibliographic record

VenueDigital Access to Scholarship at Harvard (DASH) (Harvard University) · 2024
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicGreenhouse Technology and Climate Control
Canadian institutionsnot available
Fundersnot available
KeywordsFloricultureCarbon footprintSustainabilityEcological footprintGreenhouse gasProduction (economics)Life-cycle assessmentCut flowersRose (mathematics)
DOInot available

Abstract

fetched live from OpenAlex

The global floriculture industry has expanded significantly, driven by increasing consumer demand and facilitated by international trade agreements. This growth, particularly in the cut flower sector, has shifted production from North America to equatorial regions like Colombia and Ecuador, where favorable climatic conditions and lower production costs prevail. This transition has raised concerns about environmental sustainability and social justice within the industry. This research project explored some of these issues by calculating the carbon footprint of roses grown in North America and comparing the results with case study data from Ecuador. The primary research questions were: 1) What are the environmental and social impacts of rose production in North America? 2) Will the carbon footprint of greenhouse grown roses in California be less than those grown in more northerly climates in North America? 3) Will the carbon footprint of greenhouse grown roses in North America be higher than those grown in Ecuador, based on case study data from South America? 4) Will the environmental and social life cycle data collected for North American farms, when compared with information gathered on South American rose operations, support the commonly held notion that local is more sustainable? 5) Is it possible to create a set of principles that can incorporate environmental and social metrics in a way that offers industry representatives and consumers a means of choosing a sustainable rose? To calculate the carbon footprint of roses grown in North America, I distributed questionnaires to four rose farms that agreed to participate in this study: two from California, one from Minnesota, and one from Ontario, Canada. Data were analyzed according to the recent product footprint category rules for cut flowers established by researchers in the EU. Similar calculations were made based on a data set of a rose farm in Ecuador. The North American results were compared with the calculations from the Ecuadorian data set. Social metrics obtained for the North American farms were also compared with data on minimum and living wages for Ecuador, providing a simple means of examining potential social sustainability for rose workers. The results from this study represent the first known carbon footprint calculations for cut flowers grown in North America. The primary data obtained from North American farms substantiates previous research in other countries that heat and electricity in temperate climates is a significant contributor to CO2e emissions. Heat and electricity accounted for between 68%-99% of kgCO2e emissions per stem across all four North American farms for the cultivation phase of production. By comparison, only 22% of the overall kgCO2e emissions per stem were associate with cultivation for roses grown in Ecuador. Based on environmental and social analyses, this study concludes by advocating for a simple approach to estimating carbon footprint and basic social sustainability by gathering data on environmental and social ‘hotspots’ that can provide meaningful insights into sustainability that should be achievable by flower farmers.

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.488
Threshold uncertainty score0.708

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0010.003
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.032
GPT teacher head0.275
Teacher spread0.243 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2024
Admission routes1
Has abstractyes

Explore more

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