MétaCan
Menu
Back to cohort
Record W3093470871 · doi:10.3390/agriculture10100471

Investigating the Influence of Biochar Amendment on the Physicochemical Properties of Podzolic Soil

2020· article· en· W3093470871 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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueAgriculture · 2020
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicSoil Carbon and Nitrogen Dynamics
Canadian institutionsMemorial University of Newfoundland
Fundersnot available
KeywordsBiocharTopsoilAmendmentCation-exchange capacitySoil waterBulk densityChemistrySoil scienceSoil pHSoil horizonEnvironmental scienceAgronomyEnvironmental chemistryBiology

Abstract

fetched live from OpenAlex

Research into biochar, as an amendment to soil, has increased over the last decade. However, there is still much to understand regarding the effects of biochar type and rates on the physicochemical properties of different soil types. This study aimed to investigate the effects of biochar application on the physicochemical properties of podzolic soils. Soil samples were collected from the research site in Pasadena, Newfoundland, Canada. Experimental treatments consisted of three types of soils (topsoil, E-horizon soil and mixed soil (topsoil 2: E-horizon soil 1)), two biochar types (granular and powder) and four biochar application rates (0%, 0.5%, 1% and 2% on a weight basis). Ten physicochemical parameters (bulk density (BD), porosity, field capacity (FC), plant available water (PAW), water repellency (WR), electrical conductivity (EC), pH, cation exchange capacity (CEC), total carbon (TC), and nitrogen (N)) were investigated through a total of 72 experimental units. Biochar morphological structure and pore size distribution were examined using a scanning electron microscope, whereas specific surface area was assessed by the Brunauer−Emmett−Teller method. The result indicated that the E-horizon soil was highly acidic compared to control (topsoil) and mixed soils. A significant difference was observed between the control and 2% biochar amendment in all three soil mixtures tested in this experiment. Biochar amendments significantly reduced the soil BD (E-horizon: 1.40–1.25 > mixed soil: 1.34–1.21 > topsoil: 1.31–1.18 g cm−3), increased the CEC (mixed soil: 2.83–3.61 > topsoil: 2.61–2.70 > E-horizon: 1.40–1.25 cmol kg−1) and total C (topsoil: 2.40–2.41 > mixed soil: 1.74–1.75 > E-horizon: 0.43–0.44%). Water drop penetration tests showed increased WR with increasing biochar doses from 0 to 2% (topsoil: 2.33–4.00 > mixed soil: 2.33–3.33 > E-horizon: 4.00–4.67 s), and all the biochar–soil combinations were classified as slightly-repellent. We found significant effects of biochar application on soil water retention. Porosity increased by 2.8%, FC by 10%, and PAW by 12.9% when the soil was treated with powdered biochar. Additionally, we examined the temporal effect of biochar (0 to 2% doses) on pH and EC and observed an increase in pH (4.3–5.5) and EC (0.0–0.20 dS/m) every day from day 1–day 7. Collectively the study findings suggest 2% powder biochar application rate is the best combination to improve the physicochemical properties of the tested mixed podzolic soil. Granular and powdered biochar was found to be hydrophobic and hydrophilic, respectively. These findings could be helpful to better understand the use of biochar for improving the physicochemical properties of podzolic soils when used for agricultural practices in boreal ecosystems.

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 score0.026
Threshold uncertainty score0.086

Codex and Gemma teacher scores by category

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

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 head0.024
GPT teacher head0.190
Teacher spread0.166 · 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