Endophytic bacterial communities in wild rice (Oryza officinalis) and their plant growth-promoting effects on perennial rice.

Endophytic bacterial microbiomes of plants contribute to the physiological health of the host and its adaptive evolution and stress tolerance. Wild rice possesses enriched endophytic bacteria diversity, which is a potential resource for sustainable agriculture. Oryza officinalis is a unique perennial wild rice species in China with rich genetic resources. However, endophytic bacterial communities of this species and their plant growth-promoting (PGP) traits remain largely unknown. In this study, endophytic bacteria in the root, stem, and leaf tissues of O. officinalis were characterized using 16S rRNA gene Illumina sequencing. Culturable bacterial endophytes were also isolated from O. officinalis tissues and characterized for their PGP traits. The microbiome analysis showed a more complex structure and powerful function of the endophytic bacterial community in roots compared with those in other tissue compartments. Each compartment had its specific endophytic bacterial biomarkers, including Desulfomonile and Ruminiclostridium for roots; Lactobacillus, Acinetobacter, Cutibacterium and Dechloromonas for stems; and Stenotrophomonas, Chryseobacterium, Achromobacter and Methylobacterium for leaves. A total of 96 endophytic bacterial strains with PGP traits of phosphate solubilization, potassium release, nitrogen fixation, 1-aminocyclopropane-1-carboxylate (ACC) deaminase secretion, and siderophore or indole-3-acetic acid (IAA) production were isolated from O. officinalis. Among them, 11 strains identified as Enterobacter mori, E. ludwigii, E. cloacae, Bacillus amyloliquefaciens, B. siamensis, Pseudomonas rhodesiae and Kosakonia oryzae were selected for inoculation of perennial rice based on their IAA production traits. These strains showed promising PGP effects on perennial rice seedlings. They promoted plants to form a strong root system, stimulate biomass accumulation, and increase chlorophyll content and nitrogen uptake, which could fulfil the ecologically sustainable cultivation model of perennial rice. These results provide insights into the bacterial endosphere of O. officinalis and its application potential in perennial rice. There is the prospect of mining beneficial endophytic bacteria from wild rice species, which could rewild the microbiome of cultivated rice varieties and promote their growth.

An INS and UWB Fusion-Based Gyroscope Drift Correction Approach for Indoor Pedestrian Tracking.

Information fusion combining inertial navigation and radio frequency (RF) technologies, is commonly applied in indoor positioning systems (IPSs) to obtain more accurate tracking results. The performance of the inertial navigation system (INS) subsystem is affected by sensor drift over time and the RF-based subsystem aims to correct the position estimate using a fusion filter. However, the inherent sensor drift is usually not corrected during fusion, which leads to increasingly erroneous estimates over a short period of time. Among the inertial sensor drifts, gyroscope drift has the most significant impact in determining the correct orientation and accurate tracking. A gyroscope drift correction approach is proposed in this study and is incorporated in an INS and ultra-wideband (UWB) fusion IPS where only distance measurements from UWB subsystem are used. The drift correction approach is based on turn detection to account for the fact that gyroscope drift is accumulated during a turn. Practical pedestrian tracking experiments are conducted to demonstrate the accuracy of the drift correction approach. With the gyroscope drift corrected, the fusion IPS is able to provide more accurate tracking performance and achieve up to 64.52% mean position error reduction when compared to the INS only tracking result.

A Hybrid Indoor Localization and Navigation System with Map Matching for Pedestrians Using Smartphones.

Pedestrian dead reckoning is a common technique applied in indoor inertial navigation systems that is able to provide accurate tracking performance within short distances. Sensor drift is the main bottleneck in extending the system to long-distance and long-term tracking. In this paper, a hybrid system integrating traditional pedestrian dead reckoning based on the use of inertial measurement units, short-range radio frequency systems and particle filter map matching is proposed. The system is a drift-free pedestrian navigation system where position error and sensor drift is regularly corrected and is able to provide long-term accurate and reliable tracking. Moreover, the whole system is implemented on a commercial off-the-shelf smartphone and achieves real-time positioning and tracking performance with satisfactory accuracy.