MétaCan
Menu
Back to cohort
Record W4405952809 · doi:10.1155/sci5/9550396

Unleashing the Potential of Biochar Composite as Organic Nutrient Source: Implications as Soil Ameliorant, Seed Yield, and Physiological Attributes of <i>Helianthus annuus</i> L.

2024· article· en· W4405952809 on OpenAlex

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.

fundA Canadian funder is recorded on the work.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueScientifica · 2024
Typearticle
Languageen
FieldNursing
TopicFood composition and properties
Canadian institutionsnot available
FundersAlberta Agricultural Research Institute
KeywordsBiocharHelianthus annuusYield (engineering)AgronomyEnvironmental scienceNutrientSoil conditionerSunflowerSoil nutrientsChemistrySoil waterBiologyPyrolysisMaterials scienceSoil science

Abstract

fetched live from OpenAlex

Agriculture needs a reduced dependency on synthetic chemical fertilizers and renewable biomaterials to add nutrients to soil, ameliorating degraded soil and gaining agronomic yield of crops. Biochar mixed with inorganic fertilizer has been effective in improving the crop yield. However, the influence of composite biochar (C‐BC) obtained from poultry feathers (PFs), cow bones (CBs), and rice straw (RS) waste streams as sources of N, P, and K, respectively, is still unclear. This study aimed to unveil a tripartite relationship of biochar composite applications with soil properties and agronomic attributes of sunflower var. orisun. Biochars associated with nutrient acquisition were characterized through Fourier transform infrared (FTIR) spectroscopy, scanning electron microscopy (SEM), and energy dispersive x‐ray (EDX) spectroscopy. To assess the bioavailability of nutrients and their impact on agronomic yield, a greenhouse trial was set up with sunflower, using each biochar individually as well as in composite application at three levels of amendments (0%, 2%, 4%, and 6% w/w) along with commercial fertilizer. The surface characterization through FTIR, SEM, and EDX of each biochar illustrated the presence of a wide range of functional groups, porosity, and multiple nutrients. C‐BC showed a significantly positive response to soil properties and exhibited the high availability of nutrients (N, P, and K) in soil as compared to commercial fertilizer. Application of C‐BC at 4% was found effective for dry biomass (47 g) and seed yield (35.16 g), resulted in oil and protein concentrations as high as 44.8% and 23.5%, respectively. Feather‐derived biochar (PF‐BC), bone char (CB‐BC), and RS‐derived biochar (RS‐BC) in the form of biochar composite can become an applicable substitute for chemical fertilizer in sustainable agriculture.

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 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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.012
Threshold uncertainty score0.388

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 studies0.0000.001
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 head0.026
GPT teacher head0.256
Teacher spread0.230 · 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