Agriculture is facing severe challenges from crop stresses, threatening its sustainable development and food security. This work exploits aerial visual perception for yellow rust disease monitoring, which seamlessly integrates state-of-the-art techniques and algorithms including UAV sensing, multispectral imaging, vegetation segmentation and deep learning U-Net. A field experiment is designed by infecting winter wheat with yellow rust inoculum, on top of which multispectral aerial images are captured by DJI Matrice 100 equipped with RedEdge camera. After image calibration and stitching, multispectral orthomosaic is labelled for system evaluation by inspecting high-resolution RGB images taken by Parrot Anafi Drone. The merits of the developed framework drawing spectral-spatial information concurrently are demonstrated by showing improved performance over purely spectral based classifier by the classical random forest algorithm. Moreover, various network input band combinations are tested including three RGB bands and five selected spectral vegetation indices by Sequential Forward Selection strategy of Wrapper algorithm.

Using biological control agents (BCAs) is an essential component of integrated pest and diseases management. Despite much research on biocontrol of plant diseases, success in field crops has been limited with most successes being achieved in greenhouse cultivation. This lack of success is often attributed to the complex ecological processes involved in biocontrol. We used next generation sequencing (NGS) technology to study environmental fate of Bacillus subtilis, a widely used BCA, focusing on its dispersal aspect in open field and under protection. The dispersal of B. subtilis was very limited, particularly under protection. The reduction in the BCA population size was relatively small within 8 days; indeed, no overall reduction in the relative abundance was observed under the protected condition. These results suggested that limited dispersal is probably the main reason for its variable (and often low) control efficacy under field conditions. Thus to increase biocontrol efficacy, it is necessary to frequently apply this BCA with the application interval depending on the growth rate of target host tissues. Phyllosphere microbiota differed significantly between plants grown in open field and under protection but were not greatly affected by the introduced BCA.

WRKY transcription factors (TFs) play crucial roles in plant resistance responses to pathogens. Wheat stripe rust, caused by the fungal pathogen Puccinia striiformis f. sp. tritici (Pst), is a destructive disease of wheat (Triticum aestivum) worldwide. In this study, the two WRKY genes TaWRKY49 and TaWRKY62 were originally identified in association with high-temperature seedling-plant resistance to Pst (HTSP) resistance in wheat cultivar Xiaoyan 6 by RNA-seq. Interestingly, the expression levels of TaWRKY49 and TaWRKY62 were down- and up-regulated, respectively, during HTSP resistance in response to Pst. Silencing of TaWRKY49 enhanced whereas silencing TaWRKY62 reduced HTSP resistance. The enhanced resistance observed on leaves following the silencing of TaWRKY49 was coupled with increased expression of salicylic acid (SA)- and jasmonic acid (JA)-responsive genes TaPR1.1 and TaAOS, as well as reactive oxygen species (ROS)-associated genes TaCAT and TaPOD; whereas the ethylene (ET)-responsive gene TaPIE1 was suppressed. The decreased resistance observed on leaves following TaWRKY62 silencing was associated with increased expression of TaPR1.1 and TaPOD, and suppression of TaAOS and TaPIE1. Furthermore, SA, ET, MeJA (methyl jasmonate), hydrogen peroxide (H₂O₂) and abscisic acid (ABA) treatments increased TaWRKY62 expression. On the other hand, MeJA did not affect the expression of TaWRKY49, and H₂O₂ reduced TaWRKY49 expression. In conclusion, TaWRKY49 negatively regulates while TaWRKY62 positively regulates wheat HTSP resistance to Pst by differential regulation of SA-, JA-, ET and ROS-mediated signaling.