Isolation and Identification of Antifungal Bacterial Strain KL-1 against Plant Wilt Disease

[Objective] The antifungal bacteria of plant wilt disease was screened and identified to provide foundation for the study on bio-control preparation of plant wilt disease.[Method] Confrontation culture method was adopted to screen the bio-control bacteria with good antifungal effect against plant wilt disease,Biolog bacteria automatic identification system and 16S rDNA sequence analysis method were selected to identify its taxonomic status,the biological safety of the strain towards cotton and mice was also determined.[Result] 12 bacterial strains were isolated from rhizosphere of cotton.Among those strains,5 isolates showed antifungal activity against F.decemcellulare Brick,F.oxysporum f.sp.Diathi,F.oxysporum f.sp.vasinfectum.The antifungal effect of KL-1 strain against three target strains of pathogen reached 69.09%,80.78% and 78.89% respectively.Identification results of Biolog bacteria automatic identification system and 16S rDNA sequence analysis method showed that KL-1strain was Bacillus amyloliquefaciens;primary determination results of biological safety also showed that the strain KL-1 was safe and non-toxic towards cotton and mice.[Conclusion] KL-1strain of B.amyloliquefaciens had antifungal effect against several pathogens of plant wilt diseases,which was safe and non-toxic towards cotton and mice,being the bio-control strain with research and development potential.

Impact factors identification of spatial heterogeneity of herbaceous plant diversity on five southern islands of Miaodao Archipelago in North China

Herbaceous plants are widely distributed on islands and where they exhibit spatial heterogeneity.Accurately identifying the impact factors that drive spatial heterogeneity can reveal typical island biodiversity patterns.Five southern islands in the Miaodao Archipelago,North China were studied herein.The spatial distribution of herbaceous plant diversity on these islands was analyzed,and the impact factors and their degree of impact on spatial heterogeneity were identified using CCA ordination and ANOVA.The results reveal 114 herbaceous plant species,belonging to 94 genera from 34 families in the50 plots sampled.The total species numbers on different islands were significantly positively correlated with island area,and the average a diversity was correlated with human activities,while the(3 diversity among islands was more affected by island area than mutual distances.Spatial heterogeneity within islands indicated that the diversities were generally high in areas with higher altitude,slope,total nitrogen,total carbon,and canopy density,and lower moisture content,pH,total phosphorus,total potassium,and aspect.Among the environmental factors,pH,canopy density,total K,total P,moisture content,altitude,and slope had significant gross effects,but only canopy density exhibited a significant net effect.Terrain affected diversity by restricting plantation,plantation in turn influenced soil properties and the two together affected diversity.Therefore,plantation was ultimately the fundamental driving factor for spatial heterogeneity in herbaceous plant diversity on the five islands.

Genome-wide Identification and Analysis of MVD Gene Family in Euphorbiaceae Plants

The mevalonate diphosphate deearboxylase （MVD） is an essential enzyme in mevalonate （MVA） pathway that catalyzes the irreversible Mg2＋ -ATP de- pendent decarboxylation of 6-carben compound mevalonate-5-diphosphate （MVAPP） into 5-carbon isopentenyl diphosphate （ IPP）, the building block of sterol and isoprenoid biosynthesis. In this study, based on the published geanme sequences and ESTs, a genome-wide search was carried out for the first time to identify MVD gene family in four genome-sequenced Euphorbiaceae plants, i.e. castor bean （ Ricinus communis）, physic nut （ Jatropha curcas）, cassava （Manihot esculenta） and rubber tree （Hevea brasiliensis）, and to analyze the gene structure and phylogenetic characteristics. According to the experimental results, 1, 1,2 and 2 MVD genes, which all contain 9 introns, were identh＇ied from castor bean, physic nut, cassava and rubber tree, respectively. Homology analysis indicates that MVD genes are widely distributed in eukaryotes, some archaea and eubacteria, which suggests an early origin of this gerte family. Although MVD genes were identified in most green plants, no homologous genes were found in unicellular green algae. In most genome-sequenced plants including castor bean and physic nut, a single copy of MVD gene was found; however, in cassava and rubber tree, two copies were identified just like that in moss, maize, Arabidopsis and poplar. ＂In castor bean, digital expression profiling suggests that in five examined tissues, i.e. leaf, flower, II/III stage endosperm, V/VI stage endosperm and seed, RcPMK was expressed strongly in flower and II/III stage endosperm, moderately in V/VI stage endosperm and leaf, and weakly in seed.

Identification of Damage on Different Plants Caused by Botrytis cinerea and its Extracellular Macromolecular Toxin

With Bowytis cinerea and its extracellular macromolecular toxins as the test materials, 30 speiees of plants belonging to 29 genera and 21 families were selected as the test plants to observe the infectivity of B. dnerea and damage status of macromolecular toxins secreted by B. cinerea on plants. The resulsts showed that 17 species of plants were beth infected by B. cinerea and damaged by toxins, accounting for 56.7% of the total plants. Two species of plants could be neither infected by B. cinerea nor damaged by toxins. The study provided the reference for further understanding of pathogenic mechanism of plant pathogenic fungi toxins.

DNA Barcoding and Identification of Medicinal Plants in the Kingdom of Bahrain

Authentication of medicinally important plants is essential for increasingly demands of herbal remedies worldwide. DNA barcoding technology is currently gaining importance as a reliable tool for plant species identification, although one barcode gene is not enough in the exceptions. Short sequence diversity of standardized specific coding gene regions of rbcLa and matK of plastid genome together with noncoding ribosomal internal transcribed spacer 2 (ITS2) marker is used as barcode to compare and differentiate plant species. The success of obtaining sequences of the 29 analyzed plants distributed in 21 families using three different barcode genes rbcLa, matK and ITS2 were 97%, 79% and 75% respectively. Multiple sequence alignment confirmed the medicinal plants at species level by 89.28%, 86.32% and 60.86% obtained through rbcLa, ITS2 and matK barcodes sequences respectively. The genetic distance between sequence pairs (GD) and percentage identity (PI) is compared to analyze the plant identity at species level. The phylogenic trees constructed to show the relatedness and distance of the analyzed plants in the history of evolution by the analysis of richness of clades. The construction of DNA barcode library of desert medicinal plants is an introductory research arena in Kingdom of Bahrain in helping the routine identification of plants, and developing guidelines for detection of adulterants in herbal medicines as well as protection of biodiversity.

Identification of Tibetan and Qiang Edible and Medicinal Herbs Cardamine tangutorum and Cardamine macrophylla

[Objectives]To study the original plants,characters,tissue structure,powder characteristics and thin-layer chromatography(TLC)characteristics of Cardamine tangutorum and Cardamine macrophylla as Tibetan and Qiang edible and medicinal herbs,and to provide the basis for the identification of C.tangutorum and C.macrophylla.[Methods]The identification of C.macrophyll and C.tangutorum was carried out by original plant identification,character identification,microscopic identification and TLC identification.[Results]C.tangutorum and C.macrophylla can be distinguished according to the shape of rhizome and stem,the difference of stem leaves and leaflets,and the difference of flower color;there is no obvious difference between the characteristics of the shape and the powder;the thin layer chromatography shows that in the thin layer chromatography of C.tangutorum and C.macrophylla,spots with the same color are shown on the corresponding positions of the ground part and the reference substance quercetin;the underground part and the position corresponding to the reference substanceβ-sitosterol all show the same color spots.[Conclusions]This study provides a reference for the identification of C.tangutorum and C.macrophylla.

AN INTERNATIONAL VIEW OF DIFFERENT APPROACHES FOR FAULTS DETECTION AND IDENTIFICATION IN NUCLEAR POWER PLANTS

An extensive survey of computer based systems that apply different approaches for faults diagnostics and identifications in nuclear power plants (NPPs) was presented. In the light of reviewed material, the classification criteria were developed. The classification of computational techniques (class of computing devices, class of programming languages, and simulation programs) was discussed. The classification of theoretical aspects applied (brief aspects, and detailed aspects) in computer based diagnostic systems were established. The classification of metholology applied (symbolic reasoning methodology, event based methodology, and function based methodology) in the diagnostic systems was also depicted. In the end, the personal comments on the reviewed material, and scope of the study were described.

Identification of Original Plants, Traits, Microstructure and Powder of Leontopodium franchetii Beauv.

[Objectives] This study aimed to provide experimental data for the identification and application of Leontopodium franchetii Beauv. [Methods] The original plants, traits, microstructure and powder of L. franchetii Beauv. were identified. [Results] The identification characteristics of L. franchetii Beauv. in the original plants, traits and microstructure were obvious. [Conclusions] This study can provide reference for the identification of original plants and herbs and the development of quality standards of L. franchetii Beauv. and provide a basis for further research and development.

Potential of plant identification apps in urban forestry studies in China:comparison of recognition accuracy and user experience of five apps

Information on species composition of an urban forest is essential for its management.However,to obtain this information becomes increasingly difficult due to limited taxonomic expertise.In this study,we tested the possibility of using plant identification applications running on mobile platforms to fill this vacuum.Five plant identification apps were compared for their potential in identifying urban tree species in China.An online survey was conducted to determine the features of apps that contributed to users’satisfaction.The results show that identification accuracy varied significantly among the apps.The best performer achieved an accuracy of 74.6%at the species level,which is comparable to the accuracy by professionals in field surveys.Among the features of apps,accuracy of identification was the most important factor that contributed to users’satisfaction.However,plant identification apps did not perform well when used on rare species or outside of the regions where they have been developed.Results indicate that plant identification apps have great potential in urban forest studies and management,but users need to be cautious when deciding which one to use.

Research on Plant Species Identification Based on Improved Convolutional Neural Network

Plant species recognition is an important research area in image recognition in recent years.However,the existing plant species recognition methods have low recognition accuracy and do not meet professional requirements in terms of recognition accuracy.Therefore,ShuffleNetV2 was improved by combining the current hot concern mechanism,convolution kernel size adjustment,convolution tailoring,and CSP technology to improve the accuracy and reduce the amount of computation in this study.Six convolutional neural network models with sufficient trainable parameters were designed for differentiation learning.The SGD algorithm is used to optimize the training process to avoid overfitting or falling into the local optimum.In this paper,a conventional plant image dataset TJAU10 collected by cell phones in a natural context was constructed,containing 3000 images of 10 plant species on the campus of Tianjin Agricultural University.Finally,the improved model is compared with the baseline version of the model,which achieves better results in terms of improving accuracy and reducing the computational effort.The recognition accuracy tested on the TJAU10 dataset reaches up to 98.3%,and the recognition precision reaches up to 93.6%,which is 5.1%better than the original model and reduces the computational effort by about 31%compared with the original model.In addition,the experimental results were evaluated using metrics such as the confusion matrix,which can meet the requirements of professionals for the accurate identification of plant species.

Lightweight Method for Plant Disease Identification Using Deep Learning

In the deep learning approach for identifying plant diseases,the high complexity of the network model,the large number of parameters,and great computational effort make it challenging to deploy the model on terminal devices with limited computational resources.In this study,a lightweight method for plant diseases identification that is an improved version of the ShuffleNetV2 model is proposed.In the proposed model,the depthwise convolution in the basic module of ShuffleNetV2 is replaced with mixed depthwise convolution to capture crop pest images with different resolutions;the efficient channel attention module is added into the ShuffleNetV2 model network structure to enhance the channel features;and the ReLU activation function is replaced with the ReLU6 activation function to prevent the gen-eration of large gradients.Experiments are conducted on the public dataset PlantVillage.The results show that the proposed model achieves an accuracy of 99.43%,which is an improvement of 0.6 percentage points compared to the ShuffleNetV2 model.Compared to lightweight network models,such as MobileNetV2,MobileNetV3,EfficientNet,and EfficientNetV2,and classical convolutional neural network models,such as ResNet34,ResNet50,and ResNet101,the proposed model has fewer parameters and higher recognition accuracy,which provides guidance for deploying crop pest identification methods on resource-constrained devices,including mobile terminals.

Computer-aided system for hazard zone identification in ship power plants

The most dangerous places in ships are their power plants. Particularly, they are very unsafe for operators carrying out various necessary operation and maintenance activities. For this reason, ship machinery should be designed to ensure the maximum safety for its operators. It is a very difficult task. Therefore, it could not be solved by means of conventional design methods, which are used for design of uncomplicated technical equipment. One of the possible ways of solving this problem is to provide appropriate tools, which allow us to take the operator's safety into account during a design process, especially at its early stages. A computer-aided system supporting design of safe ship power plants could be such a tool. This paper deals with developing process of a prototype of the computer-aided system for hazard zone identification in ship power plants.

Identification of Plant-Pathogenic Fungi Using Fourier Transform Infrared Spectroscopy Combined with Chemometric Analyses

Identification of plant-pathogenic fungi is time-consuming due to cultivation and microscopic examination and can be influenced by the interpretation of the micro-morphological characters observed.The present investigation aimed to create a simple but sophisticated method for the identification of plant-pathogenic fungi by Fourier transform infrared(FTIR)spectroscopy.In this study,FTIR-attenuated total reflectance(ATR)spectroscopy was used in combination with chemometric analysis for identification of important pathogenic fungi of horticultural plants.Mixtures of mycelia and spores from 27fungal strains belonging to nine different families were collected from liquid PD or solid PDA media cultures and subjected to FTIR-ATR spectroscopy measurements.The FTIR-ATR spectra ranging from 4 000to 400cm-1 were obtained.To classify the FTIRATR spectra,cluster analysis was compared with canonical vitiate analysis(CVA)in the spectral regions of3 050~2 800and 1 800~900cm-1.Results showed that the identification accuracies achieved 97.53%and99.18%for the cluster analysis and CVA analysis,respectively,demonstrating the high potential of this technique for fungal strain identification.

Molecular identification of plants regenerated from somatic hybridization between rice and apomictic Panicum

We attempted to introduce apomictic gene(s)into rice via somatic hybridization by usingapomictic Panicum maximum Jacq.as thedonor of apomictic gene(s).Protoplasts of rice derived from suspen-sion cells were inactivated with indoacetamide(IOA)and protoplasts of Panicum maximum

Identification of Parameters in 2D-FEM of Valve Piping System within NPP Utilizing Seismic Response

Nuclear power plants(NPP)contain plenty of valve piping systems(VPS’s)which are categorized into high anti-seismic grades.Tasks such as seismic qualification,health monitoring and damage diagnosis of VPS’s in its design and operation processes all depend on finite element method.However,in engineering practice,there is always deviations between the theoretical and the measured responses due to the inaccurate value of the structural parameters in the model.The structure parameters identification of VPS within NPP is still an unexplored domain to a large extent.In this paper,the initial 2D-finite element model(FEM)for VPS with a DN80 gate valve was updated by utilizing seismic response.The objective function used in the model updating procedure is the vibration control equation error of the VPS.The experimental results show that the updated 2D-FEM can accurately predict the original dynamic characteristic of the VPS.It was also found the Rayleigh damping coefficients corresponding to the VPS vary slightly with the change in seismic excitation amplitude.The research displayed the complete procedure of updating the complex structured initial FEM by utilizing seismic response,and the results show that the parameters can be accurately identified even if the seismic response used for updating merely contained the fundamental frequency information of the structure.

Identification and Control of Typical Industrial Process

Many industrial processes such as heating furnaces have over damping dynamic characteristics. Based on an innovative impulse response model, a method of identification and control for the over damping plant is introduced in the paper. The number of parameters of the model is much less than conventional impulse response model. The model based on tuning procedure of numerical optimum PID controller parameters is presented. For an actual instance, a large scale airflow circulatory resistance furnace control system with cascades of time delays is developed. In the system, the optimum PID control is used in the inner loop. A nonlinear PI compensation control is applied in the outer loop. The coordinating control among each output is realized by a fuzzy control strategy. A process surveillance organization monitors running situation of system and tunes controller parameters.

Genome-wide identification and expression analysis of GDSL esterase/lipase genes in tomato

The GDSL esterase/lipase family contains many functional genes that perform important biological functions in growth and development, morphogenesis, seed oil synthesis, and defense responses in plants. The expression of GDSL esterase/lipase genes can respond to biotic and abiotic stresses. Although GDSL esterase/lipase family genes have been identified and studied in other plants, they have not been identified and their functions remain unclear in tomato. This study is the first to identify 80 GDSL esterase/lipase family genes in tomato, which were named SlGELP1–80. These genes were mapped to their positions on the chromosomes and their physical and chemical properties, gene structure, phylogenetic relationships, collinear relationships, and cis-acting elements were analyzed. The spatiotemporal expression characteristics of the Sl GELP genes in tomato were diverse. In addition, RNA-seq analysis indicated that the expression patterns of the SlGELP genes in tomato differed before and after inoculation with Stemphylium lycopersici. qRT-PCR was used to analyze the expression of five Sl GELP genes after treatments with S. lycopersici, salicylic acid and jasmonic acid. Finally, this study was the first to identify and analyze GDSL esterase/lipase family genes in tomato via bioinformatics approaches, and these findings provide new insights for improving the study of plant disease resistance.

A Review of the Methods of Identifying and Testing Plant Cold Resistance

Low-tempemture stress is a major abiotic stress influencing plant growth, economic yield and quality worldwide. Precise and reliable identification and test of plant cold resistance is a foundation for exploring low-temperature damages, cold resistance mechanism of plants, cultivating and innovating quality cold-re- sistant germplasm resources, which is rather important for woody plants because their perennial and large-sized characteristics. Generally, most researches on plant cold-resistant physiology focused on identification and utilization of cold resistance worldwide, and a few on test methods of cold resistance, but cold resistance mechanism has been less reported. Therefore, researches on methods of identifying and testing plant resistance have achieved considerable progress, accumulated much experience and formed characteristics gradually in terms of methodology. Current methods of identifying plant cold resistance include open field/outdoor culti- vation evaluation, cold and frost damage investigation, simulated cold weather, and mathematical model forecast. And the methods of testing plant cold resistance include growth condition test, frozen index investigation, electrolyte leakage, bioelectrical impedance mapping and so on. Synthesizing the methods of identifying and testing plant cold resistance should be a key matter in the present and future researches and application of plant cold resistance physiology, improvement and in- novation of the identification and test will be an important direction of the future researches. Identification and test of plant cold resistance based on genomies, meta- bonomics and proteomics should be the new trend of the researches on physiology and ecology of plant cold resistance.

Electrochemical Identification of Yulania spp. by Fingerprinting of Leaves Using Glassy Carbon Electrode

In this communication,we used electrochemical sensor for recording the electrochemical profiles of eleven species of Yulania spp.from leaf extract.Two solvents and two buffer conditions were used for electrochemical fingerprints collection.Their electrochemical fingerprints can be converted to different patterns and consequently for species recognition.The results indicate the pattern recognition is much convenient than that of the recognition of species directly using voltammetric signal.The current information in electrochemical fingerprinting represents the type and amount of electrochemically active molecules,which linked to the genetic differences among the plants.Therefore,the electrochemical fingerprints were applied for further phylogenetic study.The phylogenetic tree deduced from voltametric curves is divided into three main groups.The first clade contains Y.denudate,Liriodendron chinense,Y.cylindrica,Y.biondii,Y.sprengeri.The second clade contains Y.zenii,Y.liliiflora,Y.kobus,and Y.amoena.The third clade contains Y.×soulangeana,Manglietia fordiana and Y.sinostellata.In addition,Y.salicifolia is not in these main clades.The results demonstrate that electrochemical fingerprinting can be used as a com-plementary tool in the study of phylogenetics.

Identification and Quantification of Microbial Contaminations Present in Herbal Medicines Commonly Consumed by Women in Riyadh, Saudi Arabia

The present study aimed to investigate the microbial populations such a bacteria and fungi contamination present in the herbal medicinal preparations (Lepidium sativum, Nigella sativa, Cuminum cyminum, Foeniculum vulgare, Pimpinella anisum, Trigoneela foenum-graecum, Cinnamomum verum, peel coffee, Alchemilla valgaris, Vitex agnus-castus) commonly available in different parts of Riyadh, Saudi Arabia. To determine the contamination of the herbal products, experiments such as total aerobic bacterial plate counts were evaluated by various plating techniques. The isolation and identification of fungi were done using czapek dox agar and potato dextrose agar. The results showed that a total of herbal remedies were contaminated with bacteria and fungi (100%). Among the contaminated products, peel of coffee and Vitex angnus-castus were noted more contamination than the other herbal medicinal plants. The results confirmed that the traditionally prepared herbal medications in Riyadh city are likely to be contaminated with a wide variety of potentially pathogenic bacteria and fungi. Therefore, before consumption, the quality assurance of these products should be thoroughly enforced and monitored in the production and distribution of herbal preparations. In conclusion, the present study gives proper evidence that the consumed herbal products contain different levels of pathogenic microbes.