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Record W2103814022 · doi:10.1017/s0960258500000039

Phytic acid and phosphorus in crop seeds and fruits: a global estimate

2000· article· en· W2103814022 on OpenAlexaff
John N. A. Lott, Irene Ockenden, Victor Raboy, Graeme Batten

Bibliographic record

VenueSeed Science Research · 2000
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicPhytase and its Applications
Canadian institutionsMcMaster University
Fundersnot available
KeywordsPhytic acidTonneCropPhosphorusAgronomyPhosphoric acidChemistryFood scienceBiology

Abstract

fetched live from OpenAlex

Abstract A very important mineral storage compound in seeds is phytate, a mixed cation salt of phytic acid (myo-inositol hexakis phosphoric acid). This compound is important for several reasons: (1) It is vital for seed/grain development and successful seedling growth. (2) It is often considered to be an antinutritional substance in human diets, but it may have a positivenutritional role as an anti-oxidant and an anti-cancer agent. (3) It represents a very significant amount of phosphorus being extracted from soilsand subsequently removed with the crop. (4) It plays a role in eutrophication of waterways. A key part of this review is an estimate of the annualtonnage of phosphorus and phytic acid sequestered in up to 4.1 billion metric tonnes of crop seeds and fruits globally each year. We estimate thatnearly 35 million metric tonnes of phytic acid, containing 9.9 million metric tonnes of P, is combined with about 12.5 and 3.9 million metric tonnes of K and Mg respectively, to form each year over 51 million metric tonnes of phytate. The amount of P inthis phytate is equal to nearly 65÷ of the elemental P sold world wide for use in mineral fertilizers. Dry cereal grains account for 69÷ of the total crop seed/fruit production but account for 77÷ of the total phytic acid stored each year. Low phytate mutants, that are now available for some key staple food crops such as maize and barley, offer potential benefits in such areas as the sustainability of lands used to grow crops, the mineral nutrition of humans and animals, and reduction in pollution of waterways.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.007
Threshold uncertainty score0.018

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0040.007
Science and technology studies0.0000.000
Scholarly communication0.0010.002
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0050.002

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 head0.046
GPT teacher head0.360
Teacher spread0.314 · 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 source (direct Gemma or distilled Codex), 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

Citations491
Published2000
Admission routes1
Has abstractyes

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