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Record W7163043637 · doi:10.7451/cbe.2024.66.1.1

Evaluation of cattail fibre as a sustainable alternative to rock wool as a substrate in aeroponic systems

2024· article· W7163043637 on OpenAlexaffvenueabout
Farhatun Nabi, Ramanathan Sri Ranjan, Mashiur Rahman

Bibliographic record

VenueCanadian Biosystems Engineering · 2024
Typearticle
Language
FieldAgricultural and Biological Sciences
TopicComposting and Vermicomposting Techniques
Canadian institutionsUniversity of Manitoba
Fundersnot available
KeywordsGerminationSubstrate (aquarium)Rainwater harvestingWoolSurface runoffNutrient

Abstract

fetched live from OpenAlex

Aeroponic systems offer an efficient method for growing vegetables in cold regions, like Canada’s northern and urban areas during winter. Rock wool, a commonly used growth medium, is synthetic, non-environmentally friendly, and not locally available. This study explored cattail blocks (Typha latifolia) as a sustainable alternative by comparing germination rates, plant survival, plant weights, and reusability for arugula (Eruca sativa), lettuce (Lactuca sativa), and tomato (Solanum lycopersicum). Results showed that germination was initially faster in cattail blocks than in rock wool, with significant differences (p < 0.05) across all three vegetables. Plant survival in aeroponic systems was significantly higher in cattail blocks (p < 0.05). After 35 days, fresh plant mass was higher in rock wool, but the difference was not significant for arugula, though it was significant for lettuce and tomato (p < 0.05). Rock wool degraded and developed mould, making it unsuitable for reuse, while cattail fibres retained their structural integrity. Fourier Transform Infrared (FTIR) analysis indicated nutrient loss in used cattail fibres, as peaks at 2360 cm⁻¹ and 1597 cm⁻¹ were absent. Overall, cattail fibres showed potential as an eco-friendly, locally available alternative to rock wool for aeroponic systems, supporting sustainable agriculture in cold climates.

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)0.003
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.578
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.002
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.023
GPT teacher head0.254
Teacher spread0.231 · 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.

Study designSimulation or modeling
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 routes3
Has abstractyes

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