Getting to the roots of N, P, and K uptake
Bibliographic record
Abstract
The soil contributes to the main pool of essential mineral nutrients for plants. These mineral nutrients are critical elements for the building blocks of plant biomolecules, play fundamental roles in cell processes, and act in various enzymatic reactions. The roots are the main entry point for mineral nutrients used within the plant to grow, develop, and produce seeds. In this regard, a suite of plant nutrient transport systems, sensors, and signaling proteins function in acquiring mineral nutrients through the roots. Mineral nutrients from chemical fertilizers, composed mainly of nitrogen, phosphorus, and potassium (NPK), are added to agricultural land to maximize crop yields, worldwide. However, improving nutrient uptake and use within crops is critical for economically and environmentally sustainable agriculture. Therefore, we review the molecular basis for N, P, and K nutrient uptake into the roots. Remarkably, plants are responsive to heterogeneous nutrient distribution and align root growth and nutrient uptake with nutrient-rich patches. We highlight the relationship between nutrient distribution in the growth environment and root system architecture. We discuss the exchange of information between the root and shoot systems through the xylem and phloem, which coordinates nutrient uptake with photosynthesis. The size and structure of the root system, along with the abundance and activity of nutrient transporters, largely determine the nutrient acquisition rate. Lastly, we discuss connections between N, P, and K uptake and signaling.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.004 |
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".