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Record W4413044603 · doi:10.34198/ejcs.12325.311330

Study of the agronomic performance of methanization digestate: the case of cucumbers

2025· article· en· W4413044603 on OpenAlexfundno aff
Marc Cyril Kouadio, Ossey Clovis Seka, Kamélé Zakari Kobenan, Benjamin Yao

Bibliographic record

VenueEarthline Journal of Chemical Sciences · 2025
Typearticle
Languageen
FieldEnvironmental Science
TopicPhosphorus and nutrient management
Canadian institutionsnot available
FundersInternational Development Research Centre
KeywordsDigestateFertilizerAgronomyManureEnvironmental scienceAgricultureNutrientMineralization (soil science)Organic fertilizerAmmoniacal nitrogenAnaerobic digestionBiologySoil waterEnvironmental engineering

Abstract

fetched live from OpenAlex

Soil Agricultural intensification in tropical regions faces significant challenges, including soil depletion and increasing reliance on chemical fertilizers, the environmental impacts of which are concerning. This study aims to assess the agronomic potential of methacompost, a solid residue derived from the anaerobic digestion of laying hen manure, as an alternative organic fertilizer for cucumber (Cucumis sativus L.) cultivation. A field experiment was conducted in the Gontougo region (Côte d’Ivoire), comparing seven methacompost formulations, an unfertilized control, and a reference treatment with NPK fertilizer (15-15-15). Physicochemical analyses revealed a high ammoniacal nitrogen content in all methacompost formulations. Agronomic results showed that the treatments MP75%, MP50%, MP25%, as well as the combination NPK50% + MP50%, resulted in vegetative growth and yields comparable to or exceeding those obtained with mineral fertilizer. These performances are attributed to the rapid mineralization of nutrients, ensuring their availability to plants. Economically, some methacompost formulations also demonstrated a lower cost per unit of fertilizer compared to NPK. This study confirms the potential of methacompost as a viable organic fertilizer for vegetable crops in tropical zones. It paves the way for the agronomic valorization of livestock waste in a circular and sustainable agricultural framework.

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)0.001
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 score0.700
Threshold uncertainty score0.178

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.008
GPT teacher head0.242
Teacher spread0.234 · 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

Citations0
Published2025
Admission routes1
Has abstractyes

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