LAUSR

BACKGROUND With steadily growing interest in use of remote sensing technologies to detect and diagnose pest infestations in crops, it is important to investigate and characterize possible associations between crop leaf reflectance and unique pest-induced changes in plant compositional traits. Accordingly, we compiled plant compositional traits from chrysanthemum and gerbera plants in four treatments: non-infested or infested with mites, thrips, or whiteflies, and we acquired hyperspectral leaf reflectance data from the same plants over time (0-14 days). RESULTS Plant compositional traits changed significantly in response to arthropod infestations, and individual chrysanthemum and gerbera plants were classified with 78% and 80% accuracy, respectively. Based on leaf reflectance, individual plants from the four treatments were classified with moderate accuracy of 76% (gerbera) and 73% (chrysanthemum) but with clear distinction between non-infested and infested plants. Accurate and consistent diagnosis of biotic stressors was not achieved. CONCLUSION To our knowledge, this is the first study, in which infestations by multiple economically important arthropod pests are directly compared and associated with leaf reflectance responses and changes in plant compositional traits. It is important to highlight that imposed stress levels were low, period of infestation was short, hyperspectral remote sensing data were acquired at four time points with analyses based on large data sets (chrysanthemum = 3,826 leaf reflectance profiles and gerbera = 4,041 leaf reflectance profiles). This study provides novel insight into crop responses to different biotic stressors and into possible associations between plant compositional traits and hyperspectral leaf reflectance data acquired from crop leaves. This article is protected by copyright. All rights reserved.