Fingerprinting Patterns of SSR Markers Constructed for 33 Loquat[Eriobotrya japonica (Thunb. ) Lindl. ]Germplasms

[ Objective ] This study aimed to explore the ways of using SSR technology to construct the fingerprinting maps of the loquat. [ Method ] Fingerprinting patterns of the SSR markers for 33 loquat varieties in national loquat germplasm resource garden were constructed by specifically amplifying palymorphism from 7 pairs of primers screened from 51 pairs of primers of the relatives Mains and Pyrus. [ Result ] The results showed that the uses of 7 primers, namely, Hi01d05F, Hil2iO4F, CH02B10F, Hi03a03, Hi03e04, Hi04a05 and Hi02c07 could distinguish 33 loquat germplasms from one another completely. [ Conclusion] This study provides an essential criterion for classification and identification of the loquat resources.

Construction of DNA Fingerprint Using SSR Marker for Hybrid Rice Cultivars Approved by Hunan Province

[Objective] This study aimed to construct DNA fingerprint for hybrid rice cultivars those have been approved by Hunan Province. [Method] The primers which produced polymorphic and bright DNA bands were selected to construct the DNA molecular fingerprint map for 77 major hybrid rice cultivars approved by Hunan Province. [ Result] A total of 48 SSR primers were selected. Every cultivar had its unique fingerprint map so that the obtained data could identify differ- ent hybrid rice cultivars. [ Conclusion] This study made great contributions to the perfection of hybrid rice germplasm identification.

Communicating Is Crowdsourcing: Wi-Fi Indoor Localization with CSI-Based Speed Estimation

Numerous indoor localization techniques have been proposed recently to meet the intensive demand for location- based service （LBS）. Among them, the most popular solutions are the Wi-Fi fingerprint-based approaches. The core challenge is to lower the cost of fingerprint site-survey. One of the trends is to collect the piecewise data from clients and establish the radio map in crowdsourcing manner. However the low participation rate blocks the practical use. In this work, we propose a passive crowdsourcing channel state information （CSI） based indoor localization scheme, C2IL. Despite a crowdsourcing based approach, our scheme is totally transparent to the client and the only requirement is to connect to our 802.11n access points （APs）. C2IL is built upon an innovative method to accurately estimate the moving speed solely based on 802.11n CSI. Knowing the walking speed of a client and its surrounding APs, a graph matching algorithm is employed to extract the received signal strength （RSS） fingerprints and establish the fingerprint map. For localization phase, we design a trajectory clustering based localization algorithm to provide precise real-time indoor localization and tracking. We develop and deploy a practical working system of C2IL in a large office environment. Extensive evaluations indicate that the error of speed estimation is within 3%, and the localization error is within 2 m at 80% time in a very complex indoor environment.

Quantitative resistance against Bemisia tabaci in Solanum pennellii:Genetics and metabolomics

The whitefly Bemisia tabaci is a serious threat in tomato cultivation worldwide as all varieties grown today are highly susceptible to this devastating herbivorous insect.Many accessions of the tomato wild relative Solanum pennellii show a high resistance towards B. tabaci. A mapping approach was used to elucidate the genetic background of whiteflyresistance related traits and associated biochemical traits in this species. Minor quantitative trait loci（QTLs） for whitefly adult survival（AS） and oviposition rate（OR） were identified and some were confirmed in an F2BC1 population, where they showed increased percentages of explained variance（more than 30%）. Bulked segregant analyses on pools of whiteflyresistant and-susceptible F2 plants enabled the identification of metabolites that correlate either with resistance or susceptibility. Genetic mapping of these metabolites showed that a large number of them co-localize with whiteflyresistance QTLs. Some of these whitefly-resistance QTLs are hotspots for metabolite QTLs. Although a large number of metabolite QTLs correlated to whitefly resistance or susceptibility, most of them are yet unknown compounds and further studies are needed to identify the metabolic pathways and genes involved. The results indicate a direct genetic correlation between biochemical-based resistance characteristics and reduced whitefly incidence in S. pennellii.