Antifungal efficacy of Bacillus amyloliquefaciens ZK-9 against Fusarium graminearum and analysis of the potential mechanism of its lipopeptides.

Fusarium graminearum is a destructive fungal pathogen that seriously threatens wheat production and quality. In the management of fungal infections, biological control is an environmentally friendly and sustainable approach. Here, the antagonistic strain ZK-9 with a broad antifungal activity was identified as Bacillus amyloliquefaciens. ZK-9 could produce extracellular enzymes such as pectinase, protease, cellulase, and amylase, as well as plant growth-promoting substances including IAA and siderophore. Lipopeptides extracted from strain ZK-9 had the high inhibitory effects on the mycelia of F. graminearum with the minimum inhibitory concentration (MIC) of 0.8 mg/mL. Investigation on the action mechanism of lipopeptides showed they could change the morphology of mycelia, damage the cell membrane, lower the content of ergosterol and increase the relative conductivity of membrane, cause nucleic acid and proteins leaking out from the cells, and disrupt the cell membrane permeability. Furthermore, metabolomic analysis of F. graminearum revealed the significant differences in the expression of 100 metabolites between the lipopeptides treatment group and the control group, which were associated with various metabolic pathways, mainly including amino acid biosynthesis, pentose, glucuronate and glycerophospholipid metabolism. In addition, strain ZK-9 inhibited Fusarium crown rot (FCR) with a biocontrol efficacy of 82.14 % and increased the plant height and root length by 24.23 % and 93.25 %, respectively. Moreover, the field control efficacy of strain ZK-9 on Fusarium head blight (FHB) was 71.76 %, and the DON content in wheat grains was significantly reduced by 69.9 %. This study puts valuable insights into the antifungal mechanism of lipopeptides against F. graminearum, and provides a promising biocontrol agent for controlling F. graminearum.

Multiplexed vortex state array toward high-dimensional data multicasting.

Optical vortex array has drawn widespread attention since the boom of special applications such as molecular selecting and optical communication. Here, we propose an integrated phase-only scheme to generate multiple multiplexed vortex beams simultaneously, constituting a multiplexed vortex state array, where the spatial position, as well as the corresponding orbital angular momentum (OAM) spectrum, can be manipulated flexibly as desired. Proof-of-concept experiments are carried out and show a few different multiplexed vortex state arrays that fit well with the simulation. Moreover, regarding the array as a data-carrier, a one-to-many multicasting link through multi-state OAM shift keying, a high-dimensional data coding, is also available in free space. In the experiment, four various OAM states are employed and achieve four bits binary symbols, and finally distribute three different images to three separate receivers independently from the same transmitter, showing great potential in the future high-dimensional optical networks.

Sorting orbital angular momentum of photons through a multi-ring azimuthal-quadratic phase.

Beams carrying orbital angular momentum (OAM) already play significant roles in many domains. Here we propose a practical design of an OAM beam splitter based on a single phase-only multi-ring azimuthal-quadratic diffraction optical element that can sort different OAM components into various spatial positions, and OAM state probing is also achieved. The performance is demonstrated through proof-of-principle experiments and shows favorable results. Furthermore, the intensity proportion of each OAM component, namely the OAM spectrum, is also diagnosed. This work offers high applicability and practicability for the recognition and separation of photon OAM, and thus paves the way for many advanced scenarios such as quantum communication, holographic encryption, and remote sensing.

Adjusted EfficientNet for the diagnostic of orbital angular momentum spectrum.

Orbital angular momentum (OAM) is one of multiple dimensions of beams. A beam can carry multiple OAM components, and their intensity weights form the OAM spectrum. The OAM spectrum determines complex amplitude distributions of a beam and features unique characteristics. Thus, measuring the OAM spectrum is of great significance, especially for OAM-based applications. Here we employ a deep neural network combined with a phase-only diffraction optical element to measure the OAM spectrum. The diffraction optical element is designed to diffract incident beams into distinct patterns corresponding to OAM distributions. Then, the EfficientNet, a kind of deep neural network, is adjusted to adapt and analyze the diffraction pattern to calculate the OAM spectrum. The favorable experimental results show that our proposal can reconstruct the OAM spectra with high precision and speed, works well for different numbers of OAM channels, and is also robust to Gaussian noise and random zooming. This work opens a new, to the best of our knowledge, ability for OAM spectrum recognition and will find applications in a number of advanced domains including large capacity optical communications, quantum key distribution, optical trapping, rotation detection, and so on.