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Record W1984888632 · doi:10.4000/vertigo.11497

Effet du zaï amélioré sur la productivité du sorgho en zone sahélienne

2012· article· fr· W1984888632 on OpenAlexvenueno aff
Philippe Bayen, Salifou Traoré, Fidèle Bognounou, Dorkas Kaiser, Adjima Thiombiano

Bibliographic record

VenueVertigO · 2012
Typearticle
Languagefr
FieldAgricultural and Biological Sciences
TopicAgriculture and Rural Development Research
Canadian institutionsnot available
Fundersnot available
KeywordsForestryCompostSorghum bicolorHumanitiesSorghumPhysicsChemistryHorticultureBiologyAgronomyPhilosophyGeography

Abstract

fetched live from OpenAlex

La présente étude a pour objectif de montrer qu’en combinant la gestion de l’eau et de la matière organique avec la technique de zaï de restauration des sols, on peut assurer une meilleure production des cultures sur les sols dégradés. Dans ce cadre, un dispositif expérimental en blocs de Fischer randomisés a été utilisé pour tester la capacité de germination, la croissance et le rendement du sorgho sur les sols dégradés en fonction de la taille des poquets et des amendements organiques. En se basant sur les différents niveaux de ces deux facteurs, ce dispositif est constitué de 32 parcelles élémentaires représentant 8 traitements factoriels (2 x 4) et 4 réplications. Les résultats montrent un effet significatif de la taille des poquets et du type d’amendement sur la germination, la croissance et le rendement du sorgho. Le rendement en grains varie entre 383,10 ± 32,13 kg/ha dans les grands poquets de zaï + compost et 5,77 ± 1,90 kg/ha dans les petits poquets de zaï sans amendement. Les grands poquets augmentent les rendements en grains surtout au niveau des traitements zaï + compost dont ils améliorent significativement les rendements de 25 % par rapport aux petits poquets. La technique du zaï avec les grands poquets associée à l’amendement du compost peut donc permettre une production soutenue de la culture sur les terres dégradées en zone sahélienne.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.182
Threshold uncertainty score0.998

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 communication0.0000.001
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.003

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 head0.010
GPT teacher head0.208
Teacher spread0.198 · 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; both teacher heads agree on what is shown here.

Study designNot applicable
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

Citations8
Published2012
Admission routes1
Has abstractyes

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Same venueVertigOSame topicAgriculture and Rural Development ResearchFrench-language works237,207