Root Morphology of Contrasting Maize Genotypes
Bibliographic record
Abstract
Image analysis has greatly simplified the measurement of root systems, allowing more detailed and accurate assessment of standard root variables. However, maize (Zea mays L.) root morphology has primarily been studied in conventional hybrids. We tested the hypothesis that genotypes carrying the leafy trait (taller plants with more leaves and greater leaf area development) would have root morphologies differing from those of conventional maize hybrids. A 3 × 3 factorial experiment was arranged in a randomized complete block design with three blocks, three fertilization levels (0, 127.5, and 255 kg N ha−1 as NH4NO3), and three maize genotypes [leafy reduced stature (LRS), leafy normal stature (LNS), and a conventional commercial hybrid Pioneer 3905 (P3905)]. The genotypes were selected for their contrasting canopy and root architectures. Plants were grown in 63‐L plastic containers, and the roots were measured at the silking stage (80 d from emergence) by scanner‐based image analysis. In general, greater root length and root surface areas were obtained at an N fertilization rate of 127.5 kg N ha−1 compared with either the absence of fertilizer N or the higher rate of 255 kg N ha−1. For all genotypes, 95% of root length was comprised of roots ranging from 0.20 to 0.40 mm in diameter. Total root length (4 km) and total root surface area (3.2 m2) were similar for LNS and LRS genotypes and were greater than those of P3905 (1.4 km total root length and 1.1 m2 surface area). Root diameter did not differ among genotypes.
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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 | 0.000 |
| 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".