Effect of Coloured Agro-Net Covers on Insect Pest Control and Yield of Tomato (Solanum lycopersicon Mill)
Bibliographic record
Abstract
Tomato (Solanum lycopersicon Mill) is one of the most important vegetable crops consumed throughout the world; and is rich in important vitamins, minerals and antioxidants. Production of the crop in open fields is however constrained by several biotic and abiotic stresses that lead to low tomato yields and quality. This study aimed at determining the effects of coloured agro-net covers on microclimate, pest infestation and yield of tomato cultivar ‘‘Rio Grande’’. The study consisted of two trials conducted using a randomized complete block design (RCBD) with five replications and six treatments. Tomato plants were grown under blue, yellow, grey, white or multi-coloured net covers with a no net cover as the control. Data were collected on microclimate (temperature, soil moisture, relative humidity and photosynthetically active radiation), pest counts and crop yield variables. Net covering modified the tomato crop microclimate with highest temperatures and soil moisture and, relative humidity levels recorded under white (21.03 oC), blue (30.03%) and multi-coloured net covers (76.26%), respectively compared to the no net control treatment (16.32 oC, 14.82% and 64.90%). Photosynthetically active radiation (PAR) was lowest under the blue agro-net cover (416.09 µmol m-2 s-1) and highest under control treatment (985.00 µmol m-2 s-1). Tomato plants grown under coloured-colour nets (yellow and blue) had lower population of silverleaf whitefly, thrips and aphids while mite population was lower under neutral-colour net covers (white, grey and multi-coloured). The neutral-colour net covers (24938.87, 19525.16 and 21541.93 kg/ha) resulted in higher yields compared to coloured-colour net covers (16804.62 and 14551.05 kg/ha). Results of the study indicate that use of agro-net covers especially the neutral-colour net cover can improve microclimate, protect tomato against insect pests and can be considered a viable strategy for tomato production by smallholder growers.
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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".