Protection of postharvest grains from fungal spoilage by biogenic volatiles.

Fungal spoilage of postharvest grains poses serious problems with respect to food safety, human health, and the economic value of grains. The protection of cereal grains from deleterious fungi is a critical aim in postharvest grain management. Considering the bulk volume of grain piles in warehouses or bins and food safety, fumigation with natural gaseous fungicides is a promising strategy to control fungal contamination on postharvest grains. Increasing research has focused on the antifungal properties of biogenic volatiles. This review summarizes the literature related to the effects of biogenic volatiles from microbes and plants on spoilage fungi on postharvest grains and highlights the underlying antifungal mechanisms. Key areas for additional research on fumigation with biogenic volatiles in postharvest grains are noted. The research described in this review supports the protective effects of biogenic volatiles against grain spoilage by fungi, providing a basis for their expanded application in the management of postharvest grains.

The antifungal mechanisms of plant volatile compound 1-octanol against Aspergillus flavus growth.

The exploitation of active ingredients from plant volatile organic compounds as natural gaseous fungicides shows remarkable potential for controlling fungal decay in postharvest agroproducts. Although 1-octanol is a common component of cereal volatiles, its antifungal potency against spoilage fungi in postharvest grains remains unclear. In this study, we studied the effectiveness of 1-octanol against Aspergillus flavus growth in postharvest grains and its mechanisms of action. 1-Octanol vapor and liquid contact dose-dependently inhibited A. flavus spore germination and mycelial growth at a low concentration. The simulated storage experiment demonstrated that 300 µL/L of 1-octanol vapor completely controlled A. flavus growth in wheat, corn, and paddy grains with 20% moisture content. 1-Octanol treatment irreversibly damaged the conidial and mycelial morphology of A. flavus and caused electrolyte leakage due to reduced plasma membrane integrity. It induced apoptosis along with morphological abnormalities, phosphatidylserine externalization, mitochondrial membrane potential depolarization, intracellular reactive oxygen species accumulation, and DNA fragmentation in A. flavus cells. Metabolomic analysis revealed that 1-octanol treatment disrupted the biosynthesis of unsaturated fatty acids, ATP-binding cassette transporters, amino acid metabolism, and glycerophospholipid metabolism. This study demonstrated the promising application potential of 1-octanol as a biofumigant for preventing fungal spoilage of postharvest cereal grains. KEY POINTS: • (1) 1-Octanol inhibits Aspergillus flavus growth in the vapor phase and liquid contact; • (2) 1-Octanol damages membrane integrity and induces apoptosis of A. flavus; • (3) Metabolomic changes in A. flavus mycelia were analyzed after 1-octanol treatment.

Transcriptomics analyses and biochemical characterization of Aspergillus flavus spores exposed to 1-nonanol.

The exploitation of plant volatile organic compounds as biofumigants to control postharvest decaying of agro-products has received considerable research attention. Our previous study reported that 1-nonanol, the main constituent of cereal volatiles, can inhibit Aspergillus flavus growth and has the potential as a biofumigant to control the fungal spoilage of cereal grains. However, the antifungal mechanism of 1-nonanol against A. flavus is still unclear at the molecular level. In this study, the minimum inhibitory concentration and minimum fungicidal concentration of 1-nonanol against A. flavus spores were 2 and 4 µL/mL, respectively. Scanning electron microscopy revealed that the 1-nonanol can distort the morphology of A. flavus spore. Annexin V-FITC/PI double staining showed that 1-nonanol induced phosphatidylserine eversion and increased membrane permeability of A. flavus spores. Transcriptional profile analysis showed that 1-nonanol treatment mainly affected the expression of genes related to membrane damage, oxidative phosphorylation, blockage of DNA replication, and autophagy in A. flavus spores. Flow cytometry analysis showed that 1-nonanol treatment caused hyperpolarization of mitochondrial membrane potential and accumulation of reactive oxygen species in A. flavus spores. 4',6-diamidino-2-phenylindole staining showed that treatment with 1-nonanol destroyed the DNA. Biochemical analysis results confirmed that 1-nonanol exerted destructive effects on A. flavus spores by decreasing intracellular adenosine triphosphate content, reducing mitochondrial ATPase activity, accumulating hydrogen peroxide and superoxide anions, and increasing catalase and superoxide dismutase enzyme activities. This study provides new insights into the antifungal mechanisms of 1-nonanol against A. flavus. KEY POINTS: • 1-Nonanol treatment resulted in abnormal morphology of A. flavus spores. • 1-Nonanol affects the expression of key growth-related genes of A. flavus. • The apoptosis of A. favus spores were induced after exposed to 1-nonanol.

Antifungal mechanism of 1-nonanol against Aspergillus flavus growth revealed by metabolomic analyses.

Chemical control of fungal spoilage of postharvest cereal grains is an important strategy for the management of grain storage. Here, the potential antifungal activity of 1-nonanol, a main component of cereal volatiles, against Aspergillus flavus was studied. The growth of A. flavus was completely inhibited by 0.11 and 0.20 µL/mL 1-nonanol at vapor and liquid contact phases, respectively. Metabolomic analysis identified 135 metabolites whose expression was significantly different between 1-nonanol-treated and untreated A. flavus. These metabolites were involved in the tricarboxylic acid cycle, amino acid biosynthesis, protein degradation and absorption, aminoacyl-tRNA biosynthesis, mineral absorption, and in interactions with ABC transporters. Biochemical validation confirmed the disruptive effect of 1-nonanol on A. flavus growth, as indicated by the leakage of intracellular electrolytes, decreased succinate dehydrogenase, mitochondrial dehydrogenase, and ATPase activity, and the accumulation of reactive oxygen species. We speculated that 1-nonanol could disrupt cell membrane integrity and mitochondrial function and might induce apoptosis of A. flavus mycelia. Simulated grain storage experiments showed that 1-nonanol vapor, at a concentration of 264 µL/L, completely inhibited A. flavus growth in wheat, corn, and paddy grain with an 18% moisture content. This study provides new insights into the antifungal mechanism of 1-nonanol against A. flavus, indicating that it has a promising potential as a bio-preservative to prevent fungal spoilage of postharvest grains. KEY POINTS: • 1-Nonanol showed higher antifungal activity against A. flavus. • The antifungal mechanisms of 1-nonanol against A. flavus were revealed. • 1-Nonanol could damage cell membrane integrity and mitochondrial function.

High-resolution terahertz coded-aperture imaging for near-field three-dimensional target.

In this paper, we propose a high-resolution terahertz coded-aperture imaging method with fast beam scanning for near-field three-dimensional targets. This method utilizes a coded aperture to modulate incident terahertz waves randomly and drive the terahertz beam to scan the entire imaging space step by step. Theoretical analyses based on physical optics are performed, and simulation experiments are implemented to demonstrate the feasibility of the proposed method.

Experimental Research on Interferometric Inverse Synthetic Aperture Radar Imaging with Multi-Channel Terahertz Radar System.

The all solid-state terahertz (THz) radar has obvious miniaturized integration and high resolution imaging advantages compared with conventional microwave radar. In this paper, a 0.22 THz active frequency-modulated pulse radar system with one transmission channel and four receiving channels is presented, and interferometric inverse synthetic aperture radar (InISAR) imaging experiments, which can acquire altitude information of objects, are carried out. In order to acquire high-quality InISAR images, a calibration method is presented to solve the nonlinearity of wideband signal frequency and phase inconsistency of different receiving channels together. Furthermore, to deal with the phase wrapping in InISAR imaging of objects with large scale, a novel method based on the dominant scatterers to estimate the objects rotation rate is presented. Finally, to show more information of objects in the InISAR images, the imaging results with a large rotation angle by the convolutional back-projection algorithm are obtained. The imaging results verify the superior performance of the multi-channel THz radar system and the imaging processing method, which can provide support for further research on InISAR imaging in the THz band.

Phaseless Terahertz Coded-Aperture Imaging Based on Incoherent Detection.

In this paper, we propose a phaseless terahertz coded-aperture imaging (PTCAI) method by using a single incoherent detector or an incoherent detection array. We at first analyze and model the system architecture, derive the matrix imaging equation, and then study the phase retrieval techniques to reconstruct the original target with high resolution. Numerical experiments are performed and the results show that the proposed method can significantly reduce the system complexity in the receiving process while maintaining high resolution imaging capability. Furthermore, the approach of using incoherent detection array instead of single detector is capable of decreasing the encoding and sampling times, and therefore helps to improve the imaging frame rate. In our future research, the method proposed in this paper will be experimentally tested and validated, and high-speed PTCAI at nearly real-time frame rates will be the main work.

Novel Efficient 3D Short-range Imaging Algorithms for a Scanning 1D-MIMO Array.

Recently, millimeter-wave (MMW) 3D holography techniques employing a scanning 1D multiple input multiple output (MIMO) array have shown several superiorities for short-range applications than traditional single input single output (SISO) ones. However, current imaging algorithms for this emerging regime are not satisfied, either too slow as a back projection (BP) manner is used or of poor quality since several steps of approximations are introduced. In this paper, two fast fully-focused imaging algorithms are developed towards fixing these drawbacks. Both algorithms are based on the assumption that the receivers are evenly distributed. The first algorithm further hypothesizes that the transmitters are also evenly located, while the second algorithm needs looser restrictions that the transmitters can be arbitrarily positioned. The frequency domain expressions of the modified Kirchhoff method are also derived and used to promote the precision of the proposed algorithms. In addition, several implementation issues including resolution, sampling criteria and computational complexity are discussed. Finally, both simulation and experimental results validate the effectiveness of the proposed methods on reconstruction quality and computational efficiency.

Envelope Correction of Micro-Motion Targets in the Terahertz ISAR Imaging.

Motion compensation is a crucial step to inverse synthetic aperture radar imaging, and envelope correction is the foundation of motion compensation. Research on envelope correction based on the small-angle imaging model has matured after years of development. However, the small-angle imaging model is not applicable to parameter estimation and imaging of micro-motion targets. According to the characteristics of the micro-motion targets and the superiorities of terahertz imaging radar, an envelope correction method for micro-motion targets in the terahertz region was proposed in this paper, including the jump error correction based on periodic correction and drift error compensation based on nonlinear fitting. Then a 330 GHz imaging radar and two experiments on corner reflectors and a warhead model were introduced. The validity of the method was verified by the experimental results, and the performance of the method was proved by the inverse Radon transform of the range profile sequences.

Robust Covariance Estimators Based on Information Divergences and Riemannian Manifold.

This paper proposes a class of covariance estimators based on information divergences in heterogeneous environments. In particular, the problem of covariance estimation is reformulated on the Riemannian manifold of Hermitian positive-definite (HPD) matrices. The means associated with information divergences are derived and used as the estimators. Without resorting to the complete knowledge of the probability distribution of the sample data, the geometry of the Riemannian manifold of HPD matrices is considered in mean estimators. Moreover, the robustness of mean estimators is analyzed using the influence function. Simulation results indicate the robustness and superiority of an adaptive normalized matched filter with our proposed estimators compared with the existing alternatives.

Information Geometry for Radar Target Detection with Total Jensen-Bregman Divergence.

This paper proposes a radar target detection algorithm based on information geometry. In particular, the correlation of sample data is modeled as a Hermitian positive-definite (HPD) matrix. Moreover, a class of total Jensen-Bregman divergences, including the total Jensen square loss, the total Jensen log-determinant divergence, and the total Jensen von Neumann divergence, are proposed to be used as the distance-like function on the space of HPD matrices. On basis of these divergences, definitions of their corresponding median matrices are given. Finally, a decision rule of target detection is made by comparing the total Jensen-Bregman divergence between the median of reference cells and the matrix of cell under test with a given threshold. The performance analysis on both simulated and real radar data confirm the superiority of the proposed detection method over its conventional counterparts and existing ones.

Information Geometry for Covariance Estimation in Heterogeneous Clutter with Total Bregman Divergence.

This paper presents a covariance matrix estimation method based on information geometry in a heterogeneous clutter. In particular, the problem of covariance estimation is reformulated as the computation of geometric median for covariance matrices estimated by the secondary data set. A new class of total Bregman divergence is presented on the Riemanian manifold of Hermitian positive-definite (HPD) matrix, which is the foundation of information geometry. On the basis of this divergence, total Bregman divergence medians are derived instead of the sample covariance matrix (SCM) of the secondary data. Unlike the SCM, resorting to the knowledge of statistical characteristics of the sample data, the geometric structure of matrix space is considered in our proposed estimators, and then the performance can be improved in a heterogeneous clutter. At the analysis stage, numerical results are given to validate the detection performance of an adaptive normalized matched filter with our estimator compared with existing alternatives.

Near-Field Three-Dimensional Planar Millimeter-Wave Holographic Imaging by Using Frequency Scaling Algorithm.

In this paper, a fast three-dimensional (3-D) frequency scaling algorithm (FSA) with large depth of focus is presented for near-field planar millimeter-wave (MMW) holographic imaging. Considering the cross-range range coupling term which is neglected in the conventional range migration algorithm (RMA), we propose an algorithm performing the range cell migration correction for de-chirped signals without interpolation by using a 3-D frequency scaling operation. First, to deal with the cross-range range coupling term, a 3-D frequency scaling operator is derived to eliminate the space variation of range cell migration. Then, a range migration correction factor is performed to compensate for the residual range cell migration. Finally, the imaging results are obtained by matched filtering in the cross-range direction. Compared with the conventional RMA, the proposed algorithm is comparable in accuracy but more efficient by using only chirp multiplications and fast Fourier transforms (FFTs). The algorithm has been tested with satisfying results by both simulation and experiment.

A Fast Terahertz Imaging Method Using Sparse Rotating Array.

For fast and standoff personal screening, a novel terahertz imaging scheme using a sparse rotating array is developed in this paper. A linearly sparse array is designed to move along a circular path with respect to an axis perpendicular to the imaging scenario. For this new scheme, a modified imaging algorithm is proposed based on the frequency-domain reconstruction method in circular synthetic aperture radar. To achieve better imaging performance, an optimization method of the sparse array is also proposed, according to the distribution of the spectral support. Theoretical and numerical analysis of the point spread function (PSF) is provided to demonstrate the high-resolution imaging ability of the proposed scheme. Comprehensive simulations are carried out to validate the feasibility and effectiveness of the array optimization method. Finally, the imaging results of a human-scattering model are also obtained to further demonstrate the good performance of this new imaging scheme and the effectiveness of the array optimization approach. This work can facilitate the design and practice of terahertz imaging systems for security inspection.

Micro-Doppler Ambiguity Resolution for Wideband Terahertz Radar Using Intra-Pulse Interference.

Micro-Doppler, induced by micro-motion of targets, is an important characteristic of target recognition once extracted via parameter estimation methods. However, micro-Doppler is usually too significant to result in ambiguity in the terahertz band because of its relatively high carrier frequency. Thus, a micro-Doppler ambiguity resolution method for wideband terahertz radar using intra-pulse interference is proposed in this paper. The micro-Doppler can be reduced several dozen times its true value to avoid ambiguity through intra-pulse interference processing. The effectiveness of this method is proved by experiments based on a 0.22 THz wideband radar system, and its high estimation precision and excellent noise immunity are verified by Monte Carlo simulation.

Electromagnetic Vortex-Based Radar Imaging Using a Single Receiving Antenna: Theory and Experimental Results.

Radar imaging based on electromagnetic vortex can achieve azimuth resolution without relative motion. The present paper investigates this imaging technique with the use of a single receiving antenna through theoretical analysis and experimental results. Compared with the use of multiple receiving antennas, the echoes from a single receiver cannot be used directly for image reconstruction using Fourier method. The reason is revealed by using the point spread function. An additional phase is compensated for each mode before imaging process based on the array parameters and the elevation of the targets. A proof-of-concept imaging system based on a circular phased array is created, and imaging experiments of corner-reflector targets are performed in an anechoic chamber. The azimuthal image is reconstructed by the use of Fourier transform and spectral estimation methods. The azimuth resolution of the two methods is analyzed and compared through experimental data. The experimental results verify the principle of azimuth resolution and the proposed phase compensation method.

Efficient Terahertz Wide-Angle NUFFT-Based Inverse Synthetic Aperture Imaging Considering Spherical Wavefront.

An efficient wide-angle inverse synthetic aperture imaging method considering the spherical wavefront effects and suitable for the terahertz band is presented. Firstly, the echo signal model under spherical wave assumption is established, and the detailed wavefront curvature compensation method accelerated by 1D fast Fourier transform (FFT) is discussed. Then, to speed up the reconstruction procedure, the fast Gaussian gridding (FGG)-based nonuniform FFT (NUFFT) is employed to focus the image. Finally, proof-of-principle experiments are carried out and the results are compared with the ones obtained by the convolution back-projection (CBP) algorithm. The results demonstrate the effectiveness and the efficiency of the presented method. This imaging method can be directly used in the field of nondestructive detection and can also be used to provide a solution for the calculation of the far-field RCSs (Radar Cross Section) of targets in the terahertz regime.

Performance Evaluation of Target Detection with a Near-Space Vehicle-Borne Radar in Blackout Condition.

Radar is a very important sensor in surveillance applications. Near-space vehicle-borne radar (NSVBR) is a novel installation of a radar system, which offers many benefits, like being highly suited to the remote sensing of extremely large areas, having a rapidly deployable capability and having low vulnerability to electronic countermeasures. Unfortunately, a target detection challenge arises because of complicated scenarios, such as nuclear blackout, rain attenuation, etc. In these cases, extra care is needed to evaluate the detection performance in blackout situations, since this a classical problem along with the application of an NSVBR. However, the existing evaluation measures are the probability of detection and the receiver operating curve (ROC), which cannot offer detailed information in such a complicated application. This work focuses on such requirements. We first investigate the effect of blackout on an electromagnetic wave. Performance evaluation indexes are then built: three evaluation indexes on the detection capability and two evaluation indexes on the robustness of the detection process. Simulation results show that the proposed measure will offer information on the detailed performance of detection. These measures are therefore very useful in detecting the target of interest in a remote sensing system and are helpful for both the NSVBR designers and users.

Sparse Auto-Calibration for Radar Coincidence Imaging with Gain-Phase Errors.

Radar coincidence imaging (RCI) is a high-resolution staring imaging technique without the limitation of relative motion between target and radar. The sparsity-driven approaches are commonly used in RCI, while the prior knowledge of imaging models needs to be known accurately. However, as one of the major model errors, the gain-phase error exists generally, and may cause inaccuracies of the model and defocus the image. In the present report, the sparse auto-calibration method is proposed to compensate the gain-phase error in RCI. The method can determine the gain-phase error as part of the imaging process. It uses an iterative algorithm, which cycles through steps of target reconstruction and gain-phase error estimation, where orthogonal matching pursuit (OMP) and Newton's method are used, respectively. Simulation results show that the proposed method can improve the imaging quality significantly and estimate the gain-phase error accurately.

A cognition-based method to ease the computational load for an extended Kalman filter.

The extended Kalman filter (EKF) is the nonlinear model of a Kalman filter (KF). It is a useful parameter estimation method when the observation model and/or the state transition model is not a linear function. However, the computational requirements in EKF are a difficulty for the system. With the help of cognition-based designation and the Taylor expansion method, a novel algorithm is proposed to ease the computational load for EKF in azimuth predicting and localizing under a nonlinear observation model. When there are nonlinear functions and inverse calculations for matrices, this method makes use of the major components (according to current performance and the performance requirements) in the Taylor expansion. As a result, the computational load is greatly lowered and the performance is ensured. Simulation results show that the proposed measure will deliver filtering output with a similar precision compared to the regular EKF. At the same time, the computational load is substantially lowered.