Remotely Sensing Arthropod and Nutrient Stressed Plants: A Case Study With Nitrogen and Cotton Aphid (Hemiptera: Aphididae)

Abstract

Remote sensing can be used in combination with ground sampling to detect aphid- (Aphis gossypii Glover) infested cotton (Gossypium hirsutum L.). Changes in wavelengths in the near-infrared (NIR) have proven useful for such detection, but these changes can be confused with other factors stressing plants, such as water deficiency and nutrient status. This study was designed to test the utility of this technology to distinguish between two factors stressing plants: nitrogen deficiency and aphids. Field plots were created by applying varying rates of nitrogen to cotton at different dates in the growing season in 2003 and 2004. Subplots were created by applying disruptive insecticides, which increased aphid populations in a portion of the subplots. Airplane and satellite remote sensing data in 2003 and 2004 were supplemented with ground sampling of aphid populations in both years. Insecticide application, nitrogen application rate and date influenced aphid abundance. Cotton with higher aphid populations could be distinguished from cotton with natural aphid infestations independent of plant nitrogen status using a NIR wavelength in 2003 and a proprietary 2004 index. Complex distinctions among varying nitrogen treatments and aphid abundance were not possible using this data. In the future, possible confounding factors should be investigated from the perspective of their change on crop physiology before remote sensing can be used in an integrated pest management (IPM) program.

Detection of brown planthopper infestation based on SPAD and spectral data from rice under different rates of nitrogen fertilizer

“…The numbers of BPH (BPH population level), nitrogen fertilizer rate and leaf position on the stem were three fixed factors, and SPAD and spectral indices from the same rice at different days after BPH infestation (duration of BPH infestation) were considered as a repeated measurement variable (Reisig and Godfrey 2010). The ratio indices of SPAD readings (RSPAD 3/1 , RSPAD 4/1 and RSPAD 4/2 ) from the three hills of rice infested with BPH for 40 days were analysed by GLM model because the balanced data were acquired from all treatments.…”

Drones: Innovative Technology for Use in Precision Pest Management

“…Aphids were counted throughout the experimental period. Different amounts of nitrogen were applied, which was verified with soil samples and analysis of plant nitrogen uptake (Reisig and Godfrey 2010).…”

Remote Sensing and Reflectance Profiling in Entomology

“…It may be challenging to accurately classify remote sensing data under real-world conditions due to simultaneous interactions among various abiotic and biotic stressors. For example, upon analyzing spectral reflectance data, Yang et al (150) experienced difficulties differentiating stress to wheat induced by greenbugs from that induced by moisture deficit, and Reisig & Godfrey (115) could not accurately detect nitrogen deficiency in cotton due to stress by cotton aphids (Aphis gossypii ). Despite important challenges, remote sensing technologies will undoubtedly be of major importance in optimized management of agricultural systems in the twenty-first century; for example, remote sensing-based crop management is being adopted to detect insect infestations, such as fall armyworms (Spodoptera frugiperda) in wheat (157).…”