Genotypic and Phenotypic Diversity of Pyricularia Oryzae in the Contemporary Rice Blast Pathogen Population in Arkansas

Rice blast, caused by Pyricularia oryzae (teleomorph: Magnaporthe grisea), is one of the most economically important diseases of rice worldwide, including Arkansas. Rice blast has been severe the past few years on conventional cultivars and, more recently, has been observed on hybrid rice cultivars. The first objective of the current research was to examine the genotypic and phenotypic variation in the P. oryzae population in Arkansas during the 2009, 2010, and 2011 growing seasons and compare isolates from conventional cultivars with those from and hybrids. A total of 904 isolates were recovered from symptomatic rice cultivars in Arkansas and were examined for their genotypic and phenotypic diversity. The isolates were evaluated for vegetative compatibility, MGR586 DNA fingerprint diversity, SSR marker diversity, and virulence on a set of 40 commercial cultivars or advanced breeding lines as well as hybrid cultivars. Examination of isolates indicated that three and of the four known VCGs were present (VCGs US-01, 02, and 04) and that one VCG (US-01) predominated (\u3e50%). Using SSR markers, MGR586 fingerprint, and virulence tests, the genotypic and phenotypic differences between lineages of P. oryzae from Arkansas were examined. Most of the isolates collected from hybrids showed a similar genotype and phenotype as the isolates recovered from conventional cultivars. Three atypical isolates, recovered from Plant Introduction accessions grown in Texas, had unique MGR586 fingerprints and could not be assigned to one of the known VCGs. One of the three isolates appeared to have a unique virulence phenotype and two of the isolates were not virulent on any of the rice germplasm tested. Population analysis could continue to provide a better understanding of pathogen virulence evolution, assist in screening for disease resistance, and help develop strategies to breed for durable resistance to blast disease. In addition, a second objective was to evaluate the stability of the AVR-Pita gene in-vitro. Previous research found structural variation of the AVR-Pita gene among field isolates. Examination of AVR-Pita over an eight week in-vitro experiment indicated that the AVR-Pita sequence were stable

Feature Selective Networks for Object Detection

Objects for detection usually have distinct characteristics in different sub-regions and different aspect ratios. However, in prevalent two-stage object detection methods, Region-of-Interest (RoI) features are extracted by RoI pooling with little emphasis on these translation-variant feature components. We present feature selective networks to reform the feature representations of RoIs by exploiting their disparities among sub-regions and aspect ratios. Our network produces the sub-region attention bank and aspect ratio attention bank for the whole image. The RoI-based sub-region attention map and aspect ratio attention map are selectively pooled from the banks, and then used to refine the original RoI features for RoI classification. Equipped with a light-weight detection subnetwork, our network gets a consistent boost in detection performance based on general ConvNet backbones (ResNet-101, GoogLeNet and VGG-16). Without bells and whistles, our detectors equipped with ResNet-101 achieve more than 3% mAP improvement compared to counterparts on PASCAL VOC 2007, PASCAL VOC 2012 and MS COCO datasets