Food Crops Low in Seed-Phytate Improve Human and Other Non-Ruminant Animals’ Health
Bibliographic record
Abstract
Background: Low phytic acid crops may offer improved nutrition for human population that largely depend upon on cereals- and legume-based staple foods, reduce the risk of eutrophication, but may compromise crops productivity and nutritional quality.\nMethods: Google search was conducted for the period between 2000 to 2021 to search for published literature in high impact factor journals focusing key words/phrases such as ‘genes and diagnostic markers’, ‘genetically modified low-seed phytate crops’, ‘high-seed phytase activity’, ‘low-seed phytate mutants’, ‘phytate and minerals bioavailability and absorption’, ‘phytate and stress tolerance’, ‘phytate-human-nonruminant livestock’s health’, ‘seed phytate, plant growth, development and yield’, ‘seed phytate and germination & seedling establishment’, ‘seed phytate and nutritional quality’, and ‘seed phytate and baking and nutritional quality’.\nResults: Low phytate mutants (except with few exceptions in barley and common bean) often carry negative pleiotropic effects in grain crops. Oil and protein contents in soybean lpa mutants were not affected, but some mutants relative to the wild type (WT) had greater sucrose and isoflavone and lower raffinose. Predominance of crossing parents on the metabolite profile and imprinting of a specific mutation induced metabolites—consistently expressed in the homozygous lpa mutant offspring—were noted across generations and environments. A few functionally characterized genes and many putative candidate genes associated with low seed phytate or seed phytase have been discovered in grain crops. Both crossbreeding and biotechnology-led genetic improvement with lpa led to offspring combining high yield and low seed phytate in maize, rice, soybean, and wheat. Crossbreeding has shown that it is possible to combine lower seed phytate with greater iron and zinc in the offspring. A few lpa cultivars are commercially grown in USA and Canada, while such developments are yet to occur in the developing world. A fine balance between yield-nutrition-stress tolerance may be achieved by deploying modern biotechnology. Accumulated evidence suggests more bioavailable iron in biofortified and lpa grains than normal phytate grains. The lack of phytic acid however perturb Ca distribution, which as a consequence may alter cooking time and stability of storage proteins, thereby causing serious gastrointestinal discomfort, and should be factored while developing biofortified or lpa beans. The low phytate-based products by and large were not associated with detrimental effects on nutritional and baking quality or retention of nutrients in the food. A long-term assessment may be necessary to assess bioavailability and absorption of minerals from diets differing in phytate concentrations and its effect on human health. Low-phytate-based feed has demonstrated substantial health and productivity benefits to nonruminant animals. Enabling policy for taxing high phytate animal waste may encourage more investments on private agricultural research programs to deal with excess phytate in food and feedstocks.\nConclusions: This review highlights advances regarding seed phytate or phytase activity in cultigen gene pools and suggests how to organize cost-effective breeding programs for developing low seed phytate cultivars. The use of modern biotechnology effectively untangled negative pleiotropic effects associated with low phytate grains. A moderate reduction of seed phytate should be achievable to combining crops productivity and adaptation across environments. Effects of low phytate diet on human and nonruminant livestock’s health are also highlighted.
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How this classification was reachedexpand
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 | 0.000 | 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 | 0.000 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".