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Record W4416981309 · doi:10.34101/actaagrar/2/15988

Maize nutrient dynamics: growth, yield and sustainable practices: A narrative review

2025· article· W4416981309 on OpenAlexaff
M. Osman, Ronald Kuunya, Raina Alrasheed, Mohammed Mahgoub Hassan, Erastus Wasikoyo, Costa Gumisiriya, Hanan Ibrahim Mudawi, Randa H. Elsalahi, Tamás Rátonyi

Bibliographic record

VenueActa Agraria Debreceniensis · 2025
Typearticle
Language
FieldAgricultural and Biological Sciences
TopicCrop Yield and Soil Fertility
Canadian institutionsMcGill University
FundersNemzeti Kutatási, Fejlesztési és Innovaciós AlapDebreceni EgyetemMagyar Tudományos Akadémia
KeywordsNutrientFood securityMicronutrientYield (engineering)CropCrop yieldSustainable agricultureNutrient management

Abstract

fetched live from OpenAlex

Nutrient acquisition is the fundamental regulator of maize (Zea mays) growth, development, and yield. The present narrative review intends to integrate existing information on dynamics of nutrient uptake in maize under scrutiny for understanding how the processes affect growth and yield. We focus on the effective absorption and utilization of macronutrients (N, P and K) and micronutrients that promote plant health, grain development, and stress tolerance. Key determinants of nutrient availability (soil type, pH, organic matter, environment) and physiological or yield impacts of deficiency are studied. Strategies to optimize uptake efficiency precision application of fertilizer, organic fertilizers, and sustainable soil management are discussed. Optimizing these dynamics is central to maize productivity, enhancement and sustainable crop production. This review provides valuable insights into optimizing maize nutrition for improved food security and sustainable crop production.

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)0.002
metaresearch head score (Gemma)0.007
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.184
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.007
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.002
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
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 head0.018
GPT teacher head0.261
Teacher spread0.243 · 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.

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

Citations0
Published2025
Admission routes1
Has abstractyes

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