Role of winter-active aphids spreading Barley yellow dwarf virus in decreasing wheat yields in a Mediterranean-type environment
Bibliographic record
Abstract
In the grainbelt of south-western Australia, which experiences Mediterranean-type climatic conditions, 3 field experiments with wheat were sown in autumn, 2 at Site A over 2 years and 1 at Site B in the first year only. These experiments related both activity of aphid vectors (migration into and colonisation of wheat) and the spread of infection with Barley yellow dwarf virus (BYDV) serotype PAV to wheat grain yield and quality. Incidences of BYDV serotype RMV and Cereal yellow dwarf (CYDV) were mostly low and BYDV serotype MAV was not distinguished. Rhopalosiphum padi was the predominant vector species but small numbers of R. maidis and Sitobion miscanthi were also present. Repeated insecticide spray applications began at different times in the different experimental treatments. These sprays killed or repelled aphid vectors, thereby preventing further virus spread from the time they were first applied. At both sites, migrant aphids were caught flying into the wheat throughout the winter period. Peak numbers of colonising aphids ranged from 0 to 99/0.5-m transect of crop. BYDV-PAV incidence ranged from 0.1 to 58% of plants and yields ranged from 1.9 to 8.6 t/ha. First aphid arrival was earlier, and virus spread and resulting yield losses greater at Site A. At this site, in treatments where repeated insecticide sprays did not start until 8 weeks after crop emergence (WAE), virus incidence and subsequent yield losses were significantly greater than when the regular applications started at emergence. However, delaying the start of sprays beyond 8 weeks had no further effect on virus spread. Since aphid numbers were very low up to 8–10 WAE, yield losses were due entirely to virus infection of plants during this early growth period. Variation in BYDV-PAV incidence explained 81 or 91% of the variation in yield gaps in the 2 years at Site A where, for each 1% increase in virus incidence, there was a yield decrease of 55 or 72 kg/ha. It also explained the variation in seed weight (88%) and protein content (69%), but not in seed screenings. At Site B, virus spread started too late to cause significant yield or quality losses. These results show that wheat yields are decreased substantially in a Mediterranean-type environment, when aphids immigrate early into wheat crops and remain active throughout the winter-growing period, spreading virus infection at young plant growth stages.
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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) | 0.000 | 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".