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Record W2936407828 · doi:10.5539/sar.v8n2p68

Climate Change and Cereal Production Evolution Trend in the Sahel: Case Study in Mali from 1951 to 2010

2019· article· en· W2936407828 on OpenAlexvenueno aff
Mamoutou Kouressy, Benjamin Sultan, Michel Vaksmann, Jean‐François Bélières, Lieven Claessens, Michaël Dingkuhn, Niaba Témé

Bibliographic record

VenueSustainable Agriculture Research · 2019
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicAgriculture and Rural Development Research
Canadian institutionsnot available
Fundersnot available
KeywordsSorghumClimate changeEnvironmental scienceCropGeographyAgricultureAgronomyBiologyEcology

Abstract

fetched live from OpenAlex

Mali is a Sahelian country with a large climatic contrast from North to South. The current climatic and production evolutionary study is focused on the six major agro-climatic cereal production zones ranging from Kayes (400 mm) to Sikasso (>1000 mm) of rainfalls. Climatic data are rainfall records, daily maximum and minimum temperatures from 60 years of the six major synoptic weather observation stations. Data were analyzed on comparing average decades of the two normal periods of 30 years (1951-1980) and (1981-2010). Annual agronomic production data for millet, sorghum, maize and rice are derived from Mali's agricultural statistics base from 1984 to 2013. Main climatic results analyses indicate that climate change resulted in a decrease of 100 mm isohyets between the 2 periods of 30 years. The structure of the rainy season was little changed between these two periods since the average start of the season was delayed by 6 days and the average end date of the season became earlier by 4 days. Maximum temperatures increased significantly from + 0.44°C to + 1.53°C and minimum temperatures significantly increased from + 1.05°C to + 1.93°C in varying way depending on the sites. Statistics of major agronomic food crop production in Mali from 1984 to 2013 indicate an average increase of 985 to 4492 thousand tones, or 22% increase per year. There is a positive upward in saw tooth trend in Malian production from 1984 to 2013. This positive trend is the result of a combination of agricultural extension, agronomic research application and the management of small farmer holder in the Sahel. This evolution needs better study for drawing necessary right conclusions.

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)0.003
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 score0.200
Threshold uncertainty score0.952

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.003
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.055
GPT teacher head0.312
Teacher spread0.258 · 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

Citations6
Published2019
Admission routes1
Has abstractyes

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