چکیده : 

Phenacoccus solenopsis Tinsley, a native of North America, is a widespread exotic mealybug infesting cotton,

Gossypium spp. in several countries. Monitoring of this pest is generally undertaken through regular

field surveys, which is labour intensive, time consuming and error prone. Alternately, radiometry is a reliable

technique for rapid and non-destructive assessment of plant health. Thus, a study was conducted to

characterize reflectance spectra of cotton plants with known mealybug infestation levels (grade-0 is

healthy and grade-4 is severe), and seek to identify specific narrow wavelengths sensitive to mealybug

damage. Reflectance measurements were made in the spectral range of 350–2500 nm using a hyperspectral

radiometer. Significant differences were found in green, near infrared and short wave infrared spectral

regions for plants with early stages of P. solenopsis infestation, and for plants showing higher grades

of infestation these differences extended to all the regions except blue. A significant reduction in total

chlorophyll (12.83–35.83%) and relative water content (1.93–23.49%) was observed in the infested plants.

Reflectance sensitivity analysis of the hyperspectral data revealed wavelengths centered at 492, 550, 674,

768 and 1454 nm as most sensitive to mealybug damage. Mealybug Stress Indices (MSIs) were developed

using two or three wavelengths, tested using multinomial logistic regression (MLR) analysis and compared

with other indices published earlier. Results showed that the MSIs were superior () to

all other spectral vegetation indices tested. Further, the proposed MLR models corresponding to each

MSIs were validated using two independent field data sets. The overall percent correct classification of

cotton plants into different mealybug damage severity grades was in the range of 38.3 and 54.9. High

classification accuracy for grade-1 (81.8%) showed that models are capable of early detection of mealybug

damage. Results of this study could suggest potential usage of remote sensing in monitoring spatial and

temporal distribution of the solenopsis mealybug, and thereby enable effective planning and implementation

of site-specific pest management practices.

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