MétaCan
Menu
Back to cohort
Record W3155695487 · doi:10.3390/agriculture11040348

Short-Term Carbon Sequestration and Changes of Soil Organic Carbon Pools in Rice under Integrated Nutrient Management in India

2021· article· en· W3155695487 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.

Bibliographic record

VenueAgriculture · 2021
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicSoil Carbon and Nitrogen Dynamics
Canadian institutionsMcGill UniversityUniversity of Guelph
Fundersnot available
KeywordsSoil carbonTotal organic carbonAgronomyNutrient managementFertilizerCarbon sequestrationVermicompostStrawChemistryPhosphorusCarbon fibersNutrientAnimal scienceNitrogenSoil waterBiologyEnvironmental chemistryMathematicsEcology

Abstract

fetched live from OpenAlex

While the capability of integrated nutrient management (INM) in rice systems has been adequately studied, little is known about the related short-term carbon sequestration and changes in soil carbon fractions. Our study examined the responses of organic carbon pools, carbon sequestration and rice yields after application of different organic manures combined with chemical fertilizers in a rice–rice (Oryza sativa L.) cropping system in the red and laterite agro-climatic zones of West Bengal, India. The treatments included non-fertilized control; rice straw (RS) + nitrogen, phosphorus and potassium fertilizer (NPK); Gliricidia (GL) + NPK; farmyard manure (FYM) + NPK; vermicompost (VC) + NPK; and NPK only. Rice straw + NPK treatment resulted in the highest total organic carbon and passive pool of carbon. Vermicompost + NPK treatment resulted in the highest oxidizable organic carbon (0.69%), dissolved organic carbon (0.007%) and microbial biomass carbon (0.01%), followed by FYM + NPK, GL + NPK and RS + NPK as compared to control. Rice straw + NPK sequestered the highest amount of carbon dioxide (CO2) as the total organic carbon (91.10 t ha−1) and passive pool of carbon (85.64 t ha−1), whereas VC + NPK resulted in the highest amount of CO2 (10.24 t ha−1) being sequestered as the active pool of carbon, followed by FYM + NPK (8.33 t ha−1) and GL + NPK (7.22 t ha−1). The application of both NPK only and VC + NPK treatments resulted in the highest grain yields over the three cropping seasons. In spite of high carbon sequestration being observed in more recalcitrant carbon pools, RS + NPK resulted in little increase (3.52 t ha−1) in rice yield over the short term. The results of this study suggest that the short-term changes of soil carbon fractions and carbon sequestration primarily depend on the type of organic manure used. Vermicompost, FYM and GL provide more labile carbon, which can improve rice yield over the short term. However, it is suggested to explore the dynamics of different carbon fractions, carbon sequestration in different pools and rice yields over longer periods of time.

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.858
Threshold uncertainty score0.996

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 studies0.0000.000
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 head0.011
GPT teacher head0.208
Teacher spread0.197 · 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