Abstract
Thrips (Pseudodentrothrips mori) infestation is an emerging constraint in mulberry cultivation, causing subtle yet significant deterioration in leaf quality that adversely affects silkworm growth and cocoon productivity. Early detection of thrips damage using conventional field scouting is difficult due to the inconspicuous nature of initial symptoms. The present study evaluated the potential of hyperspectral radiometry for non-destructive detection and quantification of thrips-induced stress in mulberry (Morus spp.). The present study evaluated the potential of hyperspectral radiometry for detection, discrimination, and quantification of thrips-induced stress in mulberry through band sensitivity analysis, vegetation index sensitivity analysis, regression analysis and linear correlation intensity analysis. Field experiments were conducted in a V1 mulberry garden using naturally infested and protected control plots in Tamil Nadu Agricultural University, Coimbatore during 2018. Spectral reflectance data were collected using a field-portable hyperspectral spectroradiometer (350–1050 nm) at different crop stages, and vegetation indices including NDVI, Simple Ratio (SR), and GRVI were derived. Thrips infestation resulted in increased reflectance in the visible region and reduced reflectance in the near-infrared region, indicating chlorophyll degradation and internal tissue disruption. Vegetation indices were consistently lower in damaged plants compared to healthy plants, with SR and NDVI showing higher sensitivity to thrips-induced stress. Linear regression analysis revealed strong negative relationships between percent leaf damage and NDVI (R² = 0.886) and SR (R² = 0.791), whereas GRVI exhibited poor predictive capability. Linear correlation intensity analysis identified diagnostically important wavelengths, with the highest positive correlation observed at 689.45 nm (r = 0.94) in the red region and the strongest negative correlation at 763.26 nm (r = −0.10) in the NIR region. Overall, the study demonstrates that hyperspectral radiometry combined with correlation intensity analysis and vegetation indices provides a robust, non-invasive approach for early detection and assessment of thrips damage in mulberry, supporting precision pest management in sericulture systems.
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Claims 10
Claim · model-written summary
Thrips infestation increased reflectance in the visible region of mulberry leaves.
- Taxon
- Morus indica
Morus indicat0 - Treatment
- Thrips infestatione3
- Interactor
- Pseudodentrothrips morie2pest
- Outcome
- reflectance in the visible regione3
- Direction
- increasede3
- Comparator
- protected control plotse1
Organisms pictured · Representative pictures of the matched species, not figures from the paper.
Verbatim
t0“Thrips Infested Mulberry (Morus indica L.) Leaves”
e1“Field experiments were conducted in a V1 mulberry garden using naturally infested and protected control plots”
e2“Thrips (Pseudodentrothrips mori) infestation is an emerging constraint in mulberry cultivation”
e3“Thrips infestation resulted in increased reflectance in the visible region and reduced reflectance in the near-infrared region, indicating chlorophyll degradation and internal tissue disruption”
Claim · model-written summary
Thrips infestation reduced reflectance in the near-infrared region of mulberry leaves.
- Taxon
- Morus indicaMorus indicat0
- Treatment
- Thrips infestatione3
- Interactor
- Pseudodentrothrips morie2pest
- Outcome
- reflectance in the near-infrared regione3
- Direction
- reducede3
- Comparator
- protected control plotse1
Organisms pictured · Representative pictures of the matched species, not figures from the paper.
Verbatim
t0“Thrips Infested Mulberry (Morus indica L.) Leaves”
e1“Field experiments were conducted in a V1 mulberry garden using naturally infested and protected control plots”
e2“Thrips (Pseudodentrothrips mori) infestation is an emerging constraint in mulberry cultivation”
e3“Thrips infestation resulted in increased reflectance in the visible region and reduced reflectance in the near-infrared region, indicating chlorophyll degradation and internal tissue disruption”
Claim · model-written summary
Thrips infestation indicates chlorophyll degradation and internal tissue disruption in mulberry leaves.
- Taxon
- Morus indicaMorus indicat0
- Treatment
- Thrips infestatione3
- Outcome
- chlorophyll degradation and internal tissue disruptione3
Organisms pictured · Representative pictures of the matched species, not figures from the paper.
Verbatim
t0“Thrips Infested Mulberry (Morus indica L.) Leaves”
e3“Thrips infestation resulted in increased reflectance in the visible region and reduced reflectance in the near-infrared region, indicating chlorophyll degradation and internal tissue disruption”
Claim · model-written summary
Vegetation indices were consistently lower in damaged mulberry plants than in healthy plants.
- Taxon
- Morus indicaMorus indicat0
- Treatment
- damaged plantse4
- Outcome
- Vegetation indicese4
- Direction
- lowere4
- Qualifier
- consistentlye4
- Comparator
- healthy plantse4
Organisms pictured · Representative pictures of the matched species, not figures from the paper.
Verbatim
t0“Thrips Infested Mulberry (Morus indica L.) Leaves”
e4“Vegetation indices were consistently lower in damaged plants compared to healthy plants”
Claim · model-written summary
SR and NDVI showed higher sensitivity to thrips-induced stress than GRVI.
Verbatim
e5“with SR and NDVI showing higher sensitivity to thrips-induced stress”
e6“whereas GRVI exhibited poor predictive capability”
Claim · model-written summary
NDVI was strongly negatively related to percent leaf damage (R² = 0.886).
- Taxon
- Morus indicaMorus indicat0
- Treatment
- percent leaf damagee7
- Outcome
- NDVIe7
- Value
- R² = 0.886e7
- Qualifier
- strong negativee7
Not reportedDirection
Organisms pictured · Representative pictures of the matched species, not figures from the paper.
Verbatim
t0“Thrips Infested Mulberry (Morus indica L.) Leaves”
e7“Linear regression analysis revealed strong negative relationships between percent leaf damage and NDVI (R² = 0.886) and SR (R² = 0.791), whereas GRVI exhibited poor predictive capability”
Claim · model-written summary
SR was strongly negatively related to percent leaf damage (R² = 0.791).
- Taxon
- Morus indicaMorus indicat0
- Treatment
- percent leaf damagee7
- Outcome
- SRe7
- Value
- R² = 0.791e7
- Qualifier
- strong negativee7
Not reportedDirection
Organisms pictured · Representative pictures of the matched species, not figures from the paper.
Verbatim
t0“Thrips Infested Mulberry (Morus indica L.) Leaves”
e7“Linear regression analysis revealed strong negative relationships between percent leaf damage and NDVI (R² = 0.886) and SR (R² = 0.791), whereas GRVI exhibited poor predictive capability”
Claim · model-written summary
GRVI had poor predictive capability compared with NDVI.
Not reportedDirection
Verbatim
e6“whereas GRVI exhibited poor predictive capability”
e7“Linear regression analysis revealed strong negative relationships between percent leaf damage and NDVI (R² = 0.886) and SR (R² = 0.791), whereas GRVI exhibited poor predictive capability”
Claim · model-written summary
The highest positive correlation with thrips damage was at 689.45 nm in the red region (r = 0.94).
- Taxon
- Morus indicaMorus indicat0
- Outcome
- correlatione1
- Direction
- positivee1
- Value
- r = 0.94e1
- Qualifier
- at 689.45 nme1
- Setting
- red regione1
Organisms pictured · Representative pictures of the matched species, not figures from the paper.
Verbatim
t0“Thrips Infested Mulberry (Morus indica L.) Leaves”
e1“the highest positive correlation observed at 689.45 nm (r = 0.94) in the red region”
Claim · model-written summary
The strongest negative correlation with thrips damage was at 763.26 nm in the NIR region (r = −0.10).
- Taxon
- Morus indicaMorus indicat0
- Outcome
- correlatione1
- Direction
- negativee1
- Value
- r = −0.10e1
- Qualifier
- at 763.26 nme1
- Setting
- NIR regione1
Organisms pictured · Representative pictures of the matched species, not figures from the paper.
Verbatim
t0“Thrips Infested Mulberry (Morus indica L.) Leaves”
e1“the strongest negative correlation at 763.26 nm (r = −0.10) in the NIR region”