Zinc bioavailability response curvature in wheat grains under incremental zinc applications
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Bibliographic record
Abstract
Abstract Zinc application is generally recommended to enrich wheat grains with Zn; however, its influence on Zn bioavailability to humans has not received appreciable attention from scientists. In this pot experiment, seven Zn rates (from 0 to 18 mg kg−1 soil) were applied to two wheat cultivars (Shafaq-2006 and Auqab-2000). Application of Zn significantly increased grain yield, grain Zn concentration and estimated Zn bioavailability, and significantly decreased grain phytate concentration and [phytate]:[Zn] ratio in wheat grains. The response of grain yield to Zn application was quadratic, whereas maximum grain yield was estimated to be achieved at 10.8 mg Zn kg−1 soil for Shafaq-2006 and 7.4 mg Zn kg−1 soil for Auqab-2000. These estimated Zn rates were suitable for increasing grain Zn concentration and Zn bioavailability (>2.9 mg Zn in 300 g grains) to optimum levels required for better human nutrition. Conclusively, Zn fertilization for Zn biofortification may be practiced on the bases of response curve studies aimed at maximizing grain yield and optimum Zn bioavailability. Moreover, additive Zn application progressively reduced the grain Fe concentration and increased the grain [phytate]:[Fe] ratio. However, a medium Zn application rate increased grain Ca concentration and decreased the grain [phytate]:[Ca] ratio. Hence, rate of Zn application for mineral biofortification needs to be carefully selected. Keywords: bioavailabilitybiofortificationmineralspolynomial comparisons Triticum aestivum L.zinc Acknowledgements We acknowledge Leland V. Miller, Senior Professional Research Assistant in the Department of Pediatrics, University of Colorado Denver (Aurora, Colorado, USA), for his guidance with the trivariate model of Zn absorption. The financial support for the study was provided by Higher Education Commission of Pakistan through Indigenous Ph.D. Fellowship Program.
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Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it