Agronomic Approach to Iron Biofortification in Chickpea
Bibliographic record
Abstract
Chickpea (Cicer arietinum L.) is a staple crop in many developing countries where iron (Fe) deficiency is severe. The biofortification of chickpea is a possible solution to address the Fe deficiency problem. A chickpea biofortification experiment was conducted under field conditions to evaluate the effects of different doses of Fe fertilizer (0 kg ha−1,10 kg ha−1 and 30 kg ha−1 of Fe-EDDHA) on the Fe content in seeds from 18 chickpea cultivars. The experiment was designed as a factorial combination of 18 chickpea cultivars and three Fe fertilizer doses in a randomized complete block design with four replications at two locations in Saskatchewan in 2015 and 2016. The Fe concentration in seeds across 18 different chickpea cultivars increased with Fe fertilization. Fe concentration in X05TH20-2 and CDC Frontier cultivars increased from 57 µg g−1 to 59 µg g−1 and from 56 µg g−1 to 58 µg g−1, respectively, after adding Fe fertilizer in both locations in 2015 and 2016. The biofortified seeds of these two cultivars can provide approximately 6 mg Fe 100−1 g seeds. Thus, 67 and 150 g of Fe biofortified chickpea seeds can provide 50% of the recommended dietary allowance of Fe for men and women.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".