MétaCan
Menu
Back to cohort
Record W4409621729 · doi:10.3390/agronomy15040992

The Impact of Fulvic Acids on Cotton Growth, Yield and Phosphorus Fertilizer Use Efficiency Under Different Phosphorus Fertilization Rates in Xinjiang, China

2025· article· en· W4409621729 on OpenAlexaff
Kai Zhang, Xiaopeng Gao, Chao Ma, Bing Chen, Yuan Fang, Jiandong Sheng

Bibliographic record

VenueAgronomy · 2025
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicPlant Growth Enhancement Techniques
Canadian institutionsUniversity of Manitoba
FundersScience and Technology Department of Xinjiang Uyghur Autonomous RegionNational Natural Science Foundation of China
KeywordsHuman fertilizationPhosphorusFertilizerYield (engineering)AgronomyChemistryPhosphate fertilizerEnvironmental scienceBiologyMaterials scienceMetallurgy

Abstract

fetched live from OpenAlex

Chemical phosphorus (P) fertilizer is often overused in arid regions with alkaline soils due to soil fixation. Fulvic acid (FA) can increase soil P availability, enhancing crop yield and P use efficiency, but its interaction with P fertilization rates and potential to reduce P fertilizer application remains unclear. A 2-year (2019–2020) field experiment was conducted in Xinjiang, China, to study the impact of FA addition (45 kg ha−1) on cotton yield and P use efficiency under different P fertilization rates (0, 50, 100 and 150 kg P2O5 ha−1). Our results showed that P fertilization significantly enhanced cotton biomass, P uptake and seed cotton yields by 17–37%, but the partial nutrient balance (PNB), agronomic efficiency (AE) and partial factor productivity (PFP) decreased with increasing P fertilization rates. FA addition did not change cotton biomass and P uptake, but significantly enhanced seed cotton yield, AE and PFP by increasing bolls per plant. No significant interactions between FA addition and P fertilization rates were observed for cotton biomass, P uptake, seed cotton yield and P use efficiencies. These findings suggest that FA can improve cotton productivity, AE and PPF of P fertilizers, helping to keep the P balance in the cotton field.

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)0.000
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.045
Threshold uncertainty score0.283

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 head0.016
GPT teacher head0.248
Teacher spread0.232 · 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.

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

Citations1
Published2025
Admission routes1
Has abstractyes

Explore more

Same venueAgronomySame topicPlant Growth Enhancement TechniquesFrench-language works237,207