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Assessment of yield loss due to fall armyworm in maize using high-resolution multispectral spaceborne remote sensing.

Authors :
Mathyam, Prabhakar
Kodigal A, Gopinath
Nakka, Ravi Kumar
Merugu, Thirupathi
Uppu, Sai Sravan
Golla, Srasvan Kumar
Gutti, Samba Siva
Pebbeti, Chandana
Adhikari, Suryakala
Singh, Vinod Kumar
Source :
International Journal of Remote Sensing. Sep2024, Vol. 45 Issue 18, p6744-6758. 15p.
Publication Year :
2024

Abstract

The fall armyworm (FAW), Spodoptera frugiperda (J.E. Smith), invasion endangered the maize production worldwide, including India. The objective of this study was to quantify the FAW damage severity and its impact on leaf area index (LAI), biomass and grain yield of maize and to detect the field damage using high-resolution multispectral spaceborne remote sensing data. Maize growing fields in the Kurnool District of Andhra Pradesh and the Gadwal District of Telangana, India, were randomly surveyed to collect detailed ground-truth information. Foliar damage due to FAW was recorded, and the fields were categorized into various severity grades (healthy, low, medium and severe). FAW infestation caused significant change in LAI between the severity grades, which formed the basis for its damage detection using multispectral spaceborne remote sensing. Severe FAW infestation caused significant reduction in LAI, biomass and grain yield ranging between 36.9 and 39.9% compared to healthy grade. The infestation at the leaf collar (LC) stage caused significant yield loss of up to 26.5% compared to the tassel initiation (TI) and tasselling and silking (TS) stages. Canopy spectral reflectance from healthy and FAW-infested plants showed significant differences in the visible and near infrared (NIR) regions. A reflectance peak was observed in the NIR region of healthy plants compared to infested plants. Among various spaceborne vegetation indices, the Soil Adjusted Vegetation Index (SAVI) performed better in identifying the FAW infestation (R2 = 0.61**), biomass (R2 = 0.70**) and yield loss (R2 = 0.82**). These findings indicate the feasibility of utilizing multispectral remote sensing data for monitoring FAW infestation on a spatial scale, thus enabling the site-specific management. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
01431161
Volume :
45
Issue :
18
Database :
Academic Search Index
Journal :
International Journal of Remote Sensing
Publication Type :
Academic Journal
Accession number :
179638004
Full Text :
https://doi.org/10.1080/01431161.2024.2394233