MAPPING OF COTTON MEALYBUG (HEMIPTERA: PSEUDOCOCCIDAE) DAMAGE IN SIRSA DISTRICT, HARYANA USING GEOSPATIAL TECHNIQUE
| Main Authors: | S. K. Singh, Sujay Dutta, Nishith Dharaiya |
|---|---|
| Format: | Article Journal |
| Terbitan: |
, 2016
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| Subjects: | |
| Online Access: |
https://zenodo.org/record/47007 |
Daftar Isi:
- Detection of crop stress is one of the major applications of remote sensing in agriculture. Many researchers have confirmed the ability of remote sensing techniques for detection of pest/disease on cotton. Hence, this research was designed to investigate, (1) to study the spectral properties of noninfested and mealybug infested cotton crop (ii) damage assessment using remote sensing derived index. Mealybug-infested cotton crop showed significantly lower reflectance in the near infrared region and higher in the visible region of the spectrum when compared with the non-infested cotton crop. Mealybug Pest Stress Index-8 (MPSI-8), a remote sensing index derived in this study shows a significant negative relationship with mealybug severity (r2=0.6319) and shows the potential to assessment the pest and disease damage because of its characteristic that include pigment, leaf structure, and water sensitive band. MPSI-8 depicts the change in pigment concentration and water stress and shows a negative relationship with mealybug severity. The high negative value of the index shows the high severity of mealybug. Land Surface Temperature (LST) also shows a positive and significant relationship with mealybug severity (r2=0.5921).Multiple linear regression analysis showed a strong relationships (r2=0.752) between mealybug severity and remotely derive index. Model developed in this study for the mealybug damage assessment in cotton crop yielded significant relationship (r2=0.752) and was applied on satellite data of 21st September 2009 which reveals high severity of mealybug and it was low on 24th September 2010 which confirms the significance of the model and can be used in the identification of mealybug infested cotton zones. These results indicate that remote sensing data have the potential to distinguish damage by mealybug and quantify its abundance in cotton.