MétaCan
Menu
Back to cohort
Record W2030972426 · doi:10.5539/jas.v5n10p34

Plant Production in Solar Collector Greenhouses - Influence on Yield, Energy Use Efficiency and Reduction in CO2 Emissions

2013· article· en· W2030972426 on OpenAlexvenueno aff
Dennis Dannehl, Ingo Schuch, Uwe Schmidt

Bibliographic record

VenueJournal of Agricultural Science · 2013
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicGreenhouse Technology and Climate Control
Canadian institutionsnot available
Fundersnot available
KeywordsGreenhouseEnvironmental scienceHeat exchangerSolar energyEnvironmental engineeringCarbon dioxideWaste managementChemistryHorticultureEngineeringMechanical engineering

Abstract

fetched live from OpenAlex

A semi-closed solar collector greenhouse was tested to evaluate the yield and the energy saving potential compared with a commercial greenhouse. As such, new algorithm for ventilation, carbon dioxide (CO2) enrichment, as well as for cooling and heating purposes initiated by a heat pump, cooling fins under the roof and a low temperature storage tank were developed. This cooling system showed that the collector greenhouse can be kept longer in the closed operation mode than a commercial one resulting in high levels of CO2 concentrations, relative humidity and temperatures. Based on these conditions, the photosynthesis and associated CO2 fixations within the plant population were promoted during the experiment, resulting in a yield increase by 32%. These results were realized, although the mean light interception by energy screens and finned tube heat exchangers was increased by 11% compared to the reference greenhouse. The energy use efficiency was improved by 103% when the collector greenhouse was considered as energy production facility. In this context, the energy saving per kilogram produced tomatoes in the collector greenhouse is equivalent to the combustion of high amounts of different fossil fuels, where the reduced CO2 emissions ranged between 2.32 kg and 4.18 kg CO2 per kg produced tomatoes. The generated total heat was composed of approximately one-third of the latent heat and over two-thirds of the sensible heat, where a maximum collector efficiency factor of 0.7 was achieved.

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 imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.014
GPT teacher head0.199
Teacher spread0.184 · 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 source (direct Gemma or distilled Codex), 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

Citations13
Published2013
Admission routes1
Has abstractyes

Explore more

Same venueJournal of Agricultural ScienceSame topicGreenhouse Technology and Climate ControlFrench-language works237,207