Taibaiella helva sp. nov., isolated from farmland soil in China.

A yellow-coloured bacterial strain, designated F-4T, was isolated from a farmland soil sample from Qianshan, Anhui province, China. Strain F-4T was Gram-stain-negative, strictly aerobic, oval-shaped, motile (by gliding) and non-spore-forming. Growth occurred at 20-35 °C (optimum, 30 °C), at pH 6.0-8.0 (pH 7.0) and with 0-1.0 % (w/v) NaCl (0 %). Phylogenetic analysis based on 16S rRNA gene sequences showed that strain F-4T belonged to the genus Taibaiella. 16S rRNA gene sequence similarity values between strain F-4T and the type strains of the three recognized species of the genus Taibaiella, Taibaiella koreensis KACC 17171T, Taibaiella soli KCTC 42277T and Taibaiella chishuiensis JCM 19637T, were 98.1, 96.4 and 95.9 %, respectively. The predominant respiratory quinone was MK-7, with MK-8 as a minor component. The major polar lipids of strain F-4T were three unidentified lipids, two unidentified aminolipids, three unidentified phospholipids, an unidentified aminophospholipid and phosphatidylethanolamine. The major cellular fatty acids were iso-C15 : 0, iso-C15 : 1 G and iso-C17 : 0. The G+C content of the genomic DNA based on total genome calculations was 51.3 mol%. The major polyamine of strain F-4T was homospermidine. The average nucleotide identity and the digital DNA-DNA hybridization values for draft genomes between strain F-4T and strain THG-DT86T were 79.8 and 22.6 %, respectively. On the basis of the genotypic and phenotypic data presented here, strain F-4T represents a novel species of the genus Taibaiella, for which the name Taibaiella helva sp. nov. is proposed. The type strain is F-4T (=KCTC 62442T=CGMCC 1.13562T).

Paenibacillus yanchengensis sp. nov., isolated from farmland soil.

A Gram-variable, short-rod-shaped, motile, spore-forming, strictly aerobic and alkaliresistant bacterium, designed strain J-3T, was isolated from farmland soil sampled in Yancheng city, Jiangsu province, China. Optimal growth occurred at 30 °C, pH 7.0-8.0 and 0.5 % (w/v) NaCl. Phylogenetic analysis based on the 16S rRNA gene sequences showed that strain J-3T was most closely related to Paenibacillusripae HZ1T (96.8 %), followed by Paenibacillussputi KIT00200-70066-1T (94.7 %). The major cellular fatty acids were anteiso-C15 : 0 and C16 : 0. The dominant respiratory quinone was menaquinone-7 and the DNA G+C content was 41.2 mol%. The major polar lipids of strain J-3T were aminolipid, phospholipid, diphosphatidylglycerol, phosphatidylglycerol, phosphoaminolipid and phosphatidylethanolamine. The diagnostic diamino acid of the cell-wall peptidoglycan was meso-diaminopimelic acid. On the basis of genotypic and phenotypic data, strain J-3T represents a novel species of the genus Paenibacillus, for which the name Paenibacillus yanchengensis sp. nov. is proposed. The type strain is J-3T (=KCTC 33926T=CGMCC 1.16455T).

Colonization on Cucumber Root and Enhancement of Chlorimuron-ethyl Degradation in the Rhizosphere by Hansschlegelia zhihuaiae S113 and Root Exudates.

The colonization of Hansschlegelia zhihuaiae S113 and its degradation of the herbicide chlorimuron-ethyl in the cucumber rhizosphere was investigated. The results reveal that S113 colonized the cucumber roots (2.14 × 105cells per gram of roots) and were able to survive in the rhizosphere (maintained for 20 d). The root exudates promoted colonization on roots and increased the degradation of chlorimuron-ethyl by S113. Five organic acids in cucumber-root exudates were detected and identified by HPLC. Citric acid and fumaric acid significantly stimulated S113 colonization on cucumber roots, with 18.4 and 15.5% increases, respectively, compared with the control. After irrigation with an S113 solution for 10 days, chlorimuron-ethyl could not be detected in the roots, seedlings, or rhizosphere soil, which allowed for improved cucumber growth. Therefore, the degradation mechanism of chlorimuron-ethyl residues by S113 in the rhizosphere could be applied in situ for the bioremediation of chlorimuron-ethyl contaminated soil to ensure crop safety.

Palmprint and face multi-modal biometric recognition based on SDA-GSVD and its kernelization.

When extracting discriminative features from multimodal data, current methods rarely concern themselves with the data distribution. In this paper, we present an assumption that is consistent with the viewpoint of discrimination, that is, a person's overall biometric data should be regarded as one class in the input space, and his different biometric data can form different Gaussians distributions, i.e., different subclasses. Hence, we propose a novel multimodal feature extraction and recognition approach based on subclass discriminant analysis (SDA). Specifically, one person's different bio-data are treated as different subclasses of one class, and a transformed space is calculated, where the difference among subclasses belonging to different persons is maximized, and the difference within each subclass is minimized. Then, the obtained multimodal features are used for classification. Two solutions are presented to overcome the singularity problem encountered in calculation, which are using PCA preprocessing, and employing the generalized singular value decomposition (GSVD) technique, respectively. Further, we provide nonlinear extensions of SDA based multimodal feature extraction, that is, the feature fusion based on KPCA-SDA and KSDA-GSVD. In KPCA-SDA, we first apply Kernel PCA on each single modal before performing SDA. While in KSDA-GSVD, we directly perform Kernel SDA to fuse multimodal data by applying GSVD to avoid the singular problem. For simplicity two typical types of biometric data are considered in this paper, i.e., palmprint data and face data. Compared with several representative multimodal biometrics recognition methods, experimental results show that our approaches outperform related multimodal recognition methods and KSDA-GSVD achieves the best recognition performance.