The Role of Pericarp Cell Wall Components in Maize Weevil Resistance
Bibliographic record
Abstract
The maize weevil (MW), Sitophilus zeamais (Motsch.), is a storage pest that causes serious losses in maize ( Zea mays L.) in developing countries. This study was conducted to investigate the role of pericarp cell wall components as factors that contribute to MW resistance in nine genotypes of tropical maize. Six susceptibility parameters to MW were measured and related to cell wall components such as simple phenolic acids, diferulic acids (DiFAs), hydroxyproline‐rich glycoproteins (HRGPs), and nutritional and physical traits. Weevil susceptibility was negatively correlated ( P < 0.001) with total DiFAs ( r = −0.77), HRGPs ( r = −0.82), grain hardness ( r = −0.87), pericarp/whole kernel (P/K) ratio ( r = −0.68), and pericarp thickness ( r = −0.86). A detailed analysis of phenolics indicated the presence of trans ‐ferulic acid (FA), p ‐coumaric acid (CA), and four isomers of DiFA. The most prominent were 5,5′‐DiFA, 8‐O‐4‐DiFA, and 8,5′‐DiFA benzofuran form (DiFAb). On the basis of regression models, 5,5′‐DiFA, 8‐O‐4‐DiFA, trans ‐FA, and p ‐CA were the most important phenolic components of resistance. Grain hardness was correlated ( P < 0.001) with cell wall bound HRGPs ( r = 0.61) and DiFAs ( r = 0.75). Cell wall cross‐linking components could contribute to MW resistance by fortification of the pericarp cell wall as well as increase grain hardness. This structurally based mechanism should be considered in the development of hybrids and varieties where storage pests are prevalent.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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 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".