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Record W4205846668 · doi:10.3390/earth3010004

Does Climate Change Affect the Yield of the Top Three Cereals and Food Security in the World?

2022· article· en· W4205846668 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueEarth · 2022
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicClimate change impacts on agriculture
Canadian institutionsMemorial University of Newfoundland
Fundersnot available
KeywordsFood securityClimate changeArable landGreenhouse gasAgricultureStaple foodEnvironmental scienceAgronomyGlobal warmingAgricultural productivityPopulationEffects of global warmingProductivityCrop yieldCropNatural resource economicsBiologyEcologyEconomics

Abstract

fetched live from OpenAlex

Climate prediction models suggest that agricultural productivity will be significantly affected in the future. The expected rise in average global temperature due to the higher release of greenhouse gases (GHGs) into the atmosphere and increased depletion of water resources with enhanced climate variability will be a serious threat to world food security. Moreover, there is an increase in the frequency and severity of long-lasting drought events over 1/3rd of the global landmass and five times increase in water demand deficits during the 21st century. The top three cereals, wheat (Triticum aestivum), maize (Zea mays), and rice (Oryza sativa), are the major and staple food crops of most people across the world. To meet the food demand of the ever-increasing population, which is expected to increase by over 9 billion by 2050, there is a dire need to increase cereal production by approximately 70%. However, we have observed a dramatic decrease in area of fertile and arable land to grow these crops. This trend is likely to increase in the future. Therefore, this review article provides an extensive review on recent and future projected area and production, the growth requirements and greenhouse gas emissions and global warming potential of the top three cereal crops, the effects of climate change on their yields, and the morphological, physiological, biochemical, and hormonal responses of plants to drought. We also discuss the potential strategies to tackle the effects of climate change and increase yields. These strategies include integrated conventional and modern molecular techniques and genomic approach, the implementation of agronomic best management (ABM) practices, and growing climate resilient cereal crops, such as millets. Millets are less resource-intensive crops and release a lower amount of greenhouse gases compared to other cereals. Therefore, millets can be the potential next-generation crops for research to explore the climate-resilient traits and use the information for the improvement of major cereals.

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.

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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.084
Threshold uncertainty score0.933

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)0.0010.000

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 head0.048
GPT teacher head0.242
Teacher spread0.194 · 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