Seven sharp eyespot resistance QTL were detected consistently across five environments and delimited to seven DNA marker intervals, respectively, six of which were independent of plant height and heading time. Sharp eyespot, caused mainly by the soil-borne fungus Rhizoctonia cerealis, is one of the important diseases of bread wheat (Triticum aestivum L.). This disease has escalated into a major threat to wheat production in some regions of the world. Wheat resistance to sharp eyespot can be a potential means to reduce the needs for application of fungicides and agricultural inputs. In the present study, the winter wheat lines, Luke and AQ24788-83, both of which possess quantitative resistance to sharp eyespot, were crossed and a population consisting 241 recombinant-inbred lines (RILs) was constructed. These RILs were assessed for sharp eyespot resistance by conducting five field and greenhouse trials during the period from 2008 to 2012, and they were genotyped with 549 simple-sequence repeat DNA markers. Seven quantitative trait loci (QTL) were detected consistently across the five trial environments to be associated with the sharp eyespot resistance. They were mapped on chromosomes 1A, 2B, 3B, 4A, 5D, 6B, and 7B. Four of these QTL are unequivocally novel, while it is possible that the other three might also be novel. Plant height and heading date of the 241 RILs were recorded in the four field trials. All of the seven disease resistance QTL were independent of plant height and heading time except one that was significantly associated with plant heading time. This association might be attributed genetically to a single QTL, or to different but closely linked QTL. In the case of single QTL, pleiotropism might be involved or the sharp eyespot resistance might be conferred in a physical instead of physiological nature.
In this paper, we focus on edge computing in smart grid and have improved the automated meter reading (AMR) system. In addition, to achieve security processing of a large number of intelligent terminals and massive data in real time and efficient responses, this paper presents an open platform which is developed on the edge of the network close to the power terminal devices or data sources, and proposes a security protection framework of smart grid based on edge computing. As a result, this new AMR system can provide real-time services, possess abilities of efficient data processing and applied intelligence, and effectively resist attacks on smart grid.
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