Emergence of insect-transmitted plant viruses over the past 10-20 years has been disproportionately driven by two so-called supervectors: the whitefly, Bemisia tabaci, and the Western flower thrips, Frankliniella occidentalis. High rates of reproduction and dispersal, extreme polyphagy, and development of insecticide resistance, together with human activities, have made these insects global pests. These supervectors transmit a diversity of plant viruses by different mechanisms and mediate virus emergence through local evolution, host shifts, mixed infections, and global spread. Associated virus evolution involves reassortment, recombination, and component capture. Emergence of B. tabaci-transmitted geminiviruses (begomoviruses), ipomoviruses, and torradoviruses has led to global disease outbreaks as well as multiple paradigm shifts. Similarly, F. occidentalis has mediated tospovirus host shifts and global dissemination and the emergence of pollen-transmitted ilarviruses. The plant virus-supervector interaction offers exciting opportunities for basic research and global implementation of generalized disease management strategies to reduce economic and environmental impacts.

A remote sensing technique was developed to detect citrus canker in laboratory conditions and was verified in the grove by utilizing an unmanned aerial vehicle (UAV). In the laboratory, a hyperspectral (400–1000 nm) imaging system was utilized for the detection of citrus canker in several disease development stages (i.e., asymptomatic, early, and late symptoms) on Sugar Belle leaves and immature (green) fruit by using two classification methods: (i) radial basis function (RBF) and (ii) K nearest neighbor (KNN). The same imaging system mounted on an UAV was used to detect citrus canker on tree canopies in the orchard. The overall classification accuracy of the RBF was higher (94%, 96%, and 100%) than the KNN method (94%, 95%, and 96%) for detecting canker in leaves. Among the 31 studied vegetation indices, the water index (WI) and the Modified Chlorophyll Absorption in Reflectance Index (ARI and TCARI 1) more accurately detected canker in laboratory and in orchard conditions, respectively. Immature fruit was not a reliable tissue for early detection of canker. However, the proposed technique successfully distinguished the late stage canker-infected fruit with 92% classification accuracy. The UAV-based technique achieved 100% classification accuracy for identifying healthy and canker-infected trees.

Glyphosate-based herbicide products are the most widely used broad-spectrum herbicides in the world for postemergent weed control. There are ever-increasing concerns that glyphosate, if not used judiciously, may cause adverse nontarget impacts in agroecosystems. The purpose of this brief review is to present and discuss the state of knowledge with respect to its persistence in the environment, possible effects on crop health, and impacts on crop nutrition.