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Record W4380202671 · doi:10.21608/sinjas.2013.301192

Sudan's Role to achieve Arab Food Security and Bio-fuel Production

2013· article· en· W4380202671 on OpenAlexaboutno aff

Bibliographic record

VenueSinai Journal of Applied Sciences/Sinai Journal of Applied Sciences · 2013
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicAgriculture, Land Use, Rural Development
Canadian institutionsnot available
Fundersnot available
KeywordsProduction (economics)Food securityBusinessNatural resource economicsEconomicsBiologyAgricultureEcology

Abstract

fetched live from OpenAlex

Problem in the continuous increase of the gap Arab food that exceeded $ 40 billion in the year with the availability of all the factors of production that enable the Arab world to bridge the food gap and export the surplus to other countries, the world around us was accelerated to increase the production of biofuels (fuel future) and the Arab world is still interested in oil production and employs much of its revenue in the production of biofuels. For research purposes and to achieve its objectives the following hypotheses were tested: 1 - The natural resources available in Sudan managed to bridge the food gap and achieving Arab countries food security. 2 - Sudan has factors that qualify it to achieve self-sufficiency of bio fuels to the Arab world while maintaining the acreage devoted to food production. - That the continued increase in the world's population with climate change and declining acreage are all factors which indicate that the world is on the verge of a food crisis. Therefore the Arab world needs to secure their food direct capital to invest in Arab countries eligible to fill the food gap. - Sudan has agricultural areas, livestock and water sources that can contribute to the estimated void achieving Arab countries food security. This only requires Arab capital and technology transfers to activate the role of scientific research to increase productivity expansion and vertical increase plantings, especially after completion of development projects as large as the Merowe Dam and Roseires dam which increase the irrigated area to about 4 million hectares. - Sudan needs investments estimated at $ 20 billion in the agricultural sector, both (plant and animal) and agro-processing to bridge the food gap and also secure a return of $ 40 billion annually to pay for food. - The results confirmed that Sudan has conducted all preliminary experiments successfully to produce bio fuels from a tree called (jatropha) and is currently preparing to plant 400 Thousand hectares to secure the production of fuel-friendly environments to meet domestic demand and issued note that Sudan produces ethanol currently from Bmusenai Kenana Sugar and White Nile and issued to EU countries. The research was presented several recommendations including: - Arab funds invested in Western countries are estimated at more than a trillion dollars and are subject to the risk of the global financial crisis, if only 10٪ of this amount was invested within the Arab world it can make the Arab world a powerful economic force, especially in the field of food production. The need to return the funds and migratory Arab cadres for the construction of the Arab world and strengthen the economies of all Arab countries, the integration of the factors of production. - Arab invest surplus funds and sovereign funds balances for investment in the agricultural sector, both the development of industry and the export of manufactured products to benefit from the added value. - Sudan Uncategorized globally within three countries contributing to the provision of food next to Canada and Australia for it to be political will on the part of Arab leaders to guide the Arab investments to Sudan to secure food for the Arab world.

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)0.004
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: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.603
Threshold uncertainty score0.986

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.003
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0020.000
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 head0.012
GPT teacher head0.205
Teacher spread0.193 · 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 designTheoretical or conceptual
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
Published2013
Admission routes1
Has abstractyes

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