Spectral Analysis of Pink Mealy Bug Damaged Mulberry Plants Using Hyperspectral Radiometry
Kalpana R, Murugesh K.A, Kumara Perumal R, M. Mithilasri, Balaji Kannan
Journal of Advances in Biology & Biotechnology · pp. 81–91 · Published 27 Mar 2024
10.9734/jabb/2024/v27i5765Abstract
Mulberry (Morus spp.) foliage forms a sole food to silkworms, Bombyx mori L. Its quality plays a pivotal role in superior silk fiber production. Like any other plants, mulberry is susceptible to detrimental diseases and infested by insect pests. Many sucking pests cause damage to mulberry among which, pink mealybug causes severe damage leading to significant loss in mulberry leaf yield (12-25 %). Conventional approaches to assess and manage damage caused by pink mealybugs demand substantial manpower and expertise, resulting in time-consuming and inefficient processes. However, leveraging modern tools and technologies like remote sensing has emerged as a remarkably effective strategy for crop protection and management.Specifically, hyperspectral remote sensing proves invaluable by furnishing insights into the biophysical and biochemical traits of crops. This is achieved through the recording of narrow wave bands that reflect specific plant characteristics. The main objectives were to understand the spectral reflectance characteristics of healthy and pink mealy bug damaged mulberry crops, to identify the optimal spectral bands and vegetative indices for detecting pink mealy bug damage in mulberry and to explore the feasibility of estimating pest damage levels based on the spectral properties of mulberry crops. Top of FormAt the mulberry garden of the Department of Sericulture, Tamil Nadu Agricultural University (TNAU), Coimbatore, studies were conducted on spectral analysis of pink mealy bug damaged mulberry plants using hyperspectral radiometry during 2018. In this trial, at 15-day intervals during the active damage stage, the percentage damage was observed in plots infested with pink mealy bugs and those that were healthy. Measurements of spectral reflectance across various wavelengths and vegetation indices (VIs) were taken using a hyperspectral radiometer. The analysis included evaluating the sensitivity of different spectral bands and VIs to pink mealybug damage, along with employing correlation and regression analyses between the extent of pest damage and the VIs. The findings revealed distinct differences in the spectral reflectance profiles of mulberry plants compared to their healthy counterparts. Typically, affected plants exhibited increased reflectance in the red (620–680 nm) and green (520–590 nm) bands and reduced near-infrared (NIR) reflectance (770–860 nm). The average values of the Normalized Difference Vegetation Index (NDVI), Green Red Vegetation Index (GRVI), and Ratio Vegetation Index (RVI) were significantly lower in the pink mealybug-damaged plants across all measurements. Notably, red reflectance demonstrated the greatest sensitivity to pink mealybug-induced damage. The study highlighted the Simple Ratio (SR) index as particularly effective for identifying pest damage. Damage estimation by pink mealybugs was refined using linear regression models based on spectral indices, specifically NDVI, RVI, and GRVI. The correlation intensity analysis pinpointed the green region at 516.73 nm as showing the most significant negative correlation (r = -0.02), whereas the highest positive correlation with pink mealybug damage was observed in the NIR region (r = 0.77), underscoring the precise wavelengths and indices most indicative of pest impact. Thus, using hyperspectral radiometry identification of damage caused by pink mealy bug possible, through analysis of spectral bands and indices.
References (25)
- 1 Relationships between leaf pigment content and spectral reflectance across a wide range of species, leaf structures and developmental stages [DOI]
- 2 Canopy reflectance, photosynthesis and transpiration [DOI]
- 3 Hyperspectral Vegetation Indices and Their Relationships with Agricultural Crop Characteristics [DOI]
- 4 Quantifying Chlorophylls and Caroteniods at Leaf and Canopy Scales [DOI]
- 5 Applicability of Green-Red Vegetation Index for Remote Sensing of Vegetation Phenology [DOI]
- 6 RESPONSES OF LEAF SPECTRAL REFLECTANCE TO PLANT STRESS [DOI]
- 7 Detecting sugarcane ‘orange rust’ disease using EO-1 Hyperion hyperspectral imagery [DOI]
- 8 Direct Immunological Detection of Wood Cell Wall Polysaccharides after Microwave-Assisted Ionic Liquid Disruption [DOI]
- 9 Leaf Reflectance Spectra of Cereal Aphid‐Damaged Wheat [DOI]
- 10 A Textbook of Agricultural Statistics
- 11 Detection of Sclerotinia rot disease on celery using hyperspectral data and partial least squares regression [DOI]
- 12 Potential of spectroscopic data sets for sugarcane thrips (Fulmekiola serrataKobus) damage detection [DOI]
- 13 Differentiating stress induced by greenbugs and Russian wheat aphids in wheat using remote sensing [DOI]
- 14 Canopy water deficit detection in paddy rice using a high resolution field spectroradiometer [DOI]
- 15 Spider Mite Detection and Canopy Component Mapping in Cotton Using Hyperspectral Imagery and Spectral Mixture Analysis [DOI]
- 16 Remote sensing of spider mite damage in California peach orchards [DOI]
- 17 Non-destructive detection of protein content in mulberry leaves by using hyperspectral imaging [DOI]
- 18 Insect Pest Infestation, an Obstacle in Quality Mulberry Leaves Production [DOI]
- 19 Development of an Index of Balsam Fir Vigor by Foliar Spectral Reflectance [DOI]
- 20 Detection and Estimation of Damage Caused By Thrips Thrips tabaci (Lind) of Cotton Using Hyperspectral Radiometer [DOI]
- 21 Ecofriendly Technologies for Disease and Pest Management in Mulberry-A Review [DOI]
- 22 Monitoring and Managing Rice Pest Infestation through Hyperspectral Remote Sensing Technology under Field Conditions [DOI]
- 23 Spectral signatures of rice crop damaged by brown planthopper under field and glass house conditions
- 24 Hyperspectral radiometry for the detection and discrimination of damage caused by sucking pests of cotton
- 25 Analysis of the trend of infestation by sap suckers in mulberry (Morus spp.) crop system
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