Abstract
Remote sensing data that are efficiently used in ecological research and management are seldom used to study insect pest infestations in agricultural ecosystems. Here, we used multispectral satellite and aircraft data to evaluate the relationship between normalized difference vegetation index (NDVI) and Hessian fly (Mayetiola destructor) infestation in commercial winter wheat (Triticum aestivum) fields in Kansas, USA. We used visible and near-infrared data from each aerial platform to develop a series of NDVI maps for multiple fields for most of the winter wheat growing season. Hessian fly infestation in each field was surveyed in a uniform grid of multiple sampling points. For both satellite and aircraft data, NDVI decreased with increasing pest infestation. Despite the coarse resolution, NDVI from satellite data performed substantially better in explaining pest infestation in the fields than NDVI from high-resolution aircraft data. These results indicate that remote sensing data can be used to assess the areas of poor growth and health of wheat plants due to Hessian fly infestation. Our study suggests that remotely sensed data, including those from satellites orbiting >700 km from the surface of Earth, can offer valuable information on the occurrence and severity of pest infestations in agricultural areas.
Highlights
Multi- and hyper-spectral data from a wide range of aerial and handheld sensors are generally used to develop a series of vegetation indices that are related to plant status, chemistry, and physiological activity[10,11]
We performed a field study to evaluate the spectral reflectance of winter wheat (Triticum aestivum, Poaceae) fields infested by an introduced insect pest, the Hessian fly (Mayetiola destructor (Say); Diptera: Cecidomyiidae)
A weak, but statistically significant, negative effect of pest infestation on normalized difference vegetation index (NDVI) was evident in November 2016 (P = 0.021) that strengthened in intensity in the subsequent imagery dates in 2017 (January 30: P < 0.0001; March 1: P < 0.0001; April 10: P = 0.004; Fig. 1)
Summary
Multi- and hyper-spectral data from a wide range of aerial and handheld sensors are generally used to develop a series of vegetation indices that are related to plant status, chemistry, and physiological activity[10,11]. Despite the technological and analytical advances, and associated ecological applications, remotely sensed data are underutilized in the study and management of arthropod pests in agricultural ecosystems. Efforts on this subject are primarily limited to laboratory and field experiments evaluating reflectance spectra of pest infested plants collected by a sensor located within a few meters of the plant canopy. We expected high-resolution NDVI from aircraft data (see Methods: Remote sensing data) to exhibit a stronger relationship with pest infestation than low-resolution NDVI acquired from satellite data. (3) High-resolution NDVI from aircraft data will exhibit a stronger relationship with pest infestation in the field than low-resolution NDVI from either platform Using NDVI from different platforms and Hessian fly infestation in the field, we tested the following hypotheses. (1) NDVI will decrease with increased infestation by Hessian fly. (2) The relationship between the pest infestation and NDVI will increase in strength overtime. (3) High-resolution NDVI from aircraft data will exhibit a stronger relationship with pest infestation in the field than low-resolution NDVI from either platform
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