Groundwater is an important source of drinking water.Groundwater pollution severely endangers drinking water safety and sustainable social development.In the case of groundwater pollution,the top priority is to identi...Groundwater is an important source of drinking water.Groundwater pollution severely endangers drinking water safety and sustainable social development.In the case of groundwater pollution,the top priority is to identify pollution sources,and accurate information on pollution sources is the premise of efficient remediation.Then,an appropriate pollution remediation scheme should be developed according to information on pollution sources,site conditions,and economic costs.The methods for identifying pollution sources mainly include geophysical exploration,geochemistry,isotopic tracing,and numerical modeling.Among these identification methods,only the numerical modeling can recognize various information on pollution sources,while other methods can only identify a certain aspect of pollution sources.The remediation technologies of groundwater can be divided into in-situ and ex-situ remediation technologies according to the remediation location.The in-situ remediation technologies enjoy low costs and a wide remediation range,but their remediation performance is prone to be affected by environmental conditions and cause secondary pollution.The ex-situ remediation technologies boast high remediation efficiency,high processing capacity,and high treatment concentration but suffer high costs.Different methods for pollution source identification and remediation technologies are applicable to different conditions.To achieve the expected identification and remediation results,it is feasible to combine several methods and technologies according to the actual hydrogeological conditions of contaminated sites and the nature of pollutants.Additionally,detailed knowledge about the hydrogeological conditions and stratigraphic structure of the contaminated site is the basis of all work regardless of the adopted identification methods or remediation technologies.展开更多
Background:Euphorbia prostrata Ait.is an annual herb widely distributed in the southern region of China with great medical values on Anti-inflammation,insect repellent,treatment of diarrhea.Despite its extensive uses ...Background:Euphorbia prostrata Ait.is an annual herb widely distributed in the southern region of China with great medical values on Anti-inflammation,insect repellent,treatment of diarrhea.Despite its extensive uses as a traditional Chinese medicine,no systematic research on the identification of E.prostrata has been reported.Methods:The study aimed to establish an accurate identification system for E.prostrata through traditional pharmacognostical methods,including botanical origin,morphological characters,medicinal material characters,microscopic characters,physicochemical parameters determination,phytochemical screening,and DNA barcoding analysis.Results:Physicochemical results show that this plant likely contains flavonoids,anthraquinones,and other substances.The ITS loci of the nuclear genome and psbA-trnH loci of the chloroplast genome were selected and evaluated,which were the most variable loci.Conclusion:The findings of this study are expected to contribute to the development of species identification,as well as provide references for authenticity identification,genetic relationship analysis,and further utilization of E.prostrata.展开更多
[Objectives] To investigate the systematic evaluation of pharmacognostic identification of Polygonum capitatum . [Methods] 10 batches of P. capitatum cultivated in Guizhou were chosen for plant samples. Macroscopical ...[Objectives] To investigate the systematic evaluation of pharmacognostic identification of Polygonum capitatum . [Methods] 10 batches of P. capitatum cultivated in Guizhou were chosen for plant samples. Macroscopical identification was conducted on plant roots, stems, leaves, flowers and fruits. The P. capitatum powder was processed for physical and chemical distinction by FeCl 3 chromogenic reaction, hydrochloric acid magnesium powder reaction, AlCl 3 color development reaction and thin-layer chromatography.Microscope identification was carried out on the powder. Plant genome DNeasy Plant Kit was adopted for DNA molecular marker identification. [Results] The results showed that the stem of P. capitatum was tufted, the leaves were oval, 2 to 5 cm long, and 1 to 2 cm wide;the leaf apex was acute and cuneate at the base, the inflorescence was capitate, paired or solitary;the raceme was erect and nearly spherical, and the perianth was light red. Furthermore, for the chromogenic reaction of FeCl 3 ethanol extract of P. capitatum , appeared blue and turned to dark blue after long time storing at room temperature. For the reaction of hydrochloric acid magnesium powder, the alcohol extract of P. capitatum , exhibited deep red. In the color reaction of AlCl 3, the alcohol extract revealed yellow fluorescence under 360 nm UV lamp. Microscope identification of the powder displayed pollen grains, crystal sheath fibers, cellulose, vessels, starch grains, cork cells, and other characteristic fragments. In addition, DNA barcoding electrophoresis results showed that P. capitatum showed a clear and bright single band near 500 bp, and further sequencing results showed that the sequence differences were mainly concentrated in ITS1 and ITS2 region. [Conclusions] Systematic evaluation for the identification of P. capitatum is established, which combines with macroscopic identification, physicochemical identification, powder microscope identification, and DNA molecular identification. Finally, the original medicinal material is identified as P. capitatum Buch.-Ham. ex D. Don.展开更多
This paper investigates the adaptive trajectory tracking control problem and the unknown parameter identification problem of a class of rotor-missiles with parametric system uncertainties.First,considering the uncerta...This paper investigates the adaptive trajectory tracking control problem and the unknown parameter identification problem of a class of rotor-missiles with parametric system uncertainties.First,considering the uncertainty of structural and aerodynamic parameters,the six-degree-of-freedom(6Do F) nonlinear equations describing the position and attitude dynamics of the rotor-missile are established,respectively,in the inertial and body-fixed reference frames.Next,a hierarchical adaptive trajectory tracking controller that can guarantee closed-loop stability is proposed according to the cascade characteristics of the 6Do F dynamics.Then,a memory-augmented update rule of unknown parameters is proposed by integrating all historical data of the regression matrix.As long as the finitely excited condition is satisfied,the precise identification of unknown parameters can be achieved.Finally,the validity of the proposed trajectory tracking controller and the parameter identification method is proved through Lyapunov stability theory and numerical simulations.展开更多
In petroleum engineering,real-time lithology identification is very important for reservoir evaluation,drilling decisions and petroleum geological exploration.A lithology identification method while drilling based on ...In petroleum engineering,real-time lithology identification is very important for reservoir evaluation,drilling decisions and petroleum geological exploration.A lithology identification method while drilling based on machine learning and mud logging data is studied in this paper.This method can effectively utilize downhole parameters collected in real-time during drilling,to identify lithology in real-time and provide a reference for optimization of drilling parameters.Given the imbalance of lithology samples,the synthetic minority over-sampling technique(SMOTE)and Tomek link were used to balance the sample number of five lithologies.Meanwhile,this paper introduces Tent map,random opposition-based learning and dynamic perceived probability to the original crow search algorithm(CSA),and establishes an improved crow search algorithm(ICSA).In this paper,ICSA is used to optimize the hyperparameter combination of random forest(RF),extremely random trees(ET),extreme gradient boosting(XGB),and light gradient boosting machine(LGBM)models.In addition,this study combines the recognition advantages of the four models.The accuracy of lithology identification by the weighted average probability model reaches 0.877.The study of this paper realizes high-precision real-time lithology identification method,which can provide lithology reference for the drilling process.展开更多
Marine oil spill emulsions are difficult to recover,and the damage to the environment is not easy to eliminate.The use of remote sensing to accurately identify oil spill emulsions is highly important for the protectio...Marine oil spill emulsions are difficult to recover,and the damage to the environment is not easy to eliminate.The use of remote sensing to accurately identify oil spill emulsions is highly important for the protection of marine environments.However,the spectrum of oil emulsions changes due to different water content.Hyperspectral remote sensing and deep learning can use spectral and spatial information to identify different types of oil emulsions.Nonetheless,hyperspectral data can also cause information redundancy,reducing classification accuracy and efficiency,and even overfitting in machine learning models.To address these problems,an oil emulsion deep-learning identification model with spatial-spectral feature fusion is established,and feature bands that can distinguish between crude oil,seawater,water-in-oil emulsion(WO),and oil-in-water emulsion(OW)are filtered based on a standard deviation threshold–mutual information method.Using oil spill airborne hyperspectral data,we conducted identification experiments on oil emulsions in different background waters and under different spatial and temporal conditions,analyzed the transferability of the model,and explored the effects of feature band selection and spectral resolution on the identification of oil emulsions.The results show the following.(1)The standard deviation–mutual information feature selection method is able to effectively extract feature bands that can distinguish between WO,OW,oil slick,and seawater.The number of bands was reduced from 224 to 134 after feature selection on the Airborne Visible Infrared Imaging Spectrometer(AVIRIS)data and from 126 to 100 on the S185 data.(2)With feature selection,the overall accuracy and Kappa of the identification results for the training area are 91.80%and 0.86,respectively,improved by 2.62%and 0.04,and the overall accuracy and Kappa of the identification results for the migration area are 86.53%and 0.80,respectively,improved by 3.45%and 0.05.(3)The oil emulsion identification model has a certain degree of transferability and can effectively identify oil spill emulsions for AVIRIS data at different times and locations,with an overall accuracy of more than 80%,Kappa coefficient of more than 0.7,and F1 score of 0.75 or more for each category.(4)As the spectral resolution decreasing,the model yields different degrees of misclassification for areas with a mixed distribution of oil slick and seawater or mixed distribution of WO and OW.Based on the above experimental results,we demonstrate that the oil emulsion identification model with spatial–spectral feature fusion achieves a high accuracy rate in identifying oil emulsion using airborne hyperspectral data,and can be applied to images under different spatial and temporal conditions.Furthermore,we also elucidate the impact of factors such as spectral resolution and background water bodies on the identification process.These findings provide new reference for future endeavors in automated marine oil spill detection.展开更多
Traditional particle identification methods face timeconsuming,experience-dependent,and poor repeatability challenges in heavy-ion collisions at low and intermediate energies.Researchers urgently need solutions to the...Traditional particle identification methods face timeconsuming,experience-dependent,and poor repeatability challenges in heavy-ion collisions at low and intermediate energies.Researchers urgently need solutions to the dilemma of traditional particle identification methods.This study explores the possibility of applying intelligent learning algorithms to the particle identification of heavy-ion collisions at low and intermediate energies.Multiple intelligent algorithms,including XgBoost and TabNet,were selected to test datasets from the neutron ion multi-detector for reaction-oriented dynamics(NIMROD-ISiS)and Geant4 simulation.Tree-based machine learning algorithms and deep learning algorithms e.g.TabNet show excellent performance and generalization ability.Adding additional data features besides energy deposition can improve the algorithm’s performance when the data distribution is nonuniform.Intelligent learning algorithms can be applied to solve the particle identification problem in heavy-ion collisions at low and intermediate energies.展开更多
The combination of structural health monitoring and vibration control is of great importance to provide components of smart structures.While synthetic algorithms have been proposed,adaptive control that is compatible ...The combination of structural health monitoring and vibration control is of great importance to provide components of smart structures.While synthetic algorithms have been proposed,adaptive control that is compatible with changing conditions still needs to be used,and time-varying systems are required to be simultaneously estimated with the application of adaptive control.In this research,the identification of structural time-varying dynamic characteristics and optimized simple adaptive control are integrated.First,reduced variations of physical parameters are estimated online using the multiple forgetting factor recursive least squares(MFRLS)method.Then,the energy from the structural vibration is simultaneously specified to optimize the control force with the identified parameters to be operational.Optimization is also performed based on the probability density function of the energy under the seismic excitation at any time.Finally,the optimal control force is obtained by the simple adaptive control(SAC)algorithm and energy coefficient.A numerical example and benchmark structure are employed to investigate the efficiency of the proposed approach.The simulation results revealed the effectiveness of the integrated online identification and optimal adaptive control in systems.展开更多
The social transformation brought aboutby digital technology is deeply impacting various industries.Digital education products, with core technologiessuch as 5G, AI, IoT (Internet of Things),etc., are continuously pen...The social transformation brought aboutby digital technology is deeply impacting various industries.Digital education products, with core technologiessuch as 5G, AI, IoT (Internet of Things),etc., are continuously penetrating areas such as teaching,management, and evaluation. Apps, miniprograms,and emerging large-scale models are providingexcellent knowledge performance and flexiblecross-media output. However, they also exposerisks such as content discrimination and algorithmcommercialization. This paper conducts anevidence-based analysis of digital education productrisks from four dimensions: “digital resourcesinformationdissemination-algorithm design-cognitiveassessment”. It breaks through corresponding identificationtechnologies and, relying on the diverse characteristicsof governance systems, explores governancestrategies for digital education products from the threedomains of “regulators-developers-users”.展开更多
Almost all sandstone reservoirs contain interlayers. The identification and characterization of these interlayers iscritical for minimizing the uncertainty associated with oilfield development and improving oil and ga...Almost all sandstone reservoirs contain interlayers. The identification and characterization of these interlayers iscritical for minimizing the uncertainty associated with oilfield development and improving oil and gas recovery.Identifying interlayers outside wells using identification methods based on logging data and machine learning isdifficult and seismic-based identification techniques are expensive. Herein, a numerical model based on seepageand well-testing theories is introduced to identify interlayers using transient pressure data. The proposed modelrelies on the open-source MATLAB Reservoir Simulation Toolbox. The effects of the interlayer thickness, position,and width on the pressure response are thoroughly investigated. A procedure for inverting interlayer parametersin the reservoir using the bottom-hole pressure is also proposed. This method uses only transient pressuredata during well testing and can effectively identify the interlayer distribution near the wellbore at an extremelylow cost. The reliability of the model is verified using effective oilfield examples.展开更多
Cross-cultural storytelling is a primary way for humankind to seek mutual recognition of value orientations between cultures,which facilitates the ability to jointly address the problems of human existence in the cont...Cross-cultural storytelling is a primary way for humankind to seek mutual recognition of value orientations between cultures,which facilitates the ability to jointly address the problems of human existence in the context of globalization.In this study,we conducted an interview survey of 6,130 respondents who were college students or graduates from 107 countries.The results show that there were a number of cross-cultural values embodied in China’s stories seen by the respondents as part of a common vision for the future of humankind and widely identified guidance on collaborative responses to global challenges.These cross-cultural values are common prosperity,ecological harmony,individual-collective integration,the urgency of global peace,as well as respect for multicultural and indigenous development paths.展开更多
Bovine tuberculosis (bTB) is an endemic zoonosis significantly affects animal health in Burkina Faso. The primary causative agent is Mycobacterium tuberculosis (M. tuberculosis) complex, mainly M. bovis. Cattle are co...Bovine tuberculosis (bTB) is an endemic zoonosis significantly affects animal health in Burkina Faso. The primary causative agent is Mycobacterium tuberculosis (M. tuberculosis) complex, mainly M. bovis. Cattle are considered as natural reservoir of M. bovis. However, in Burkina Faso, the circulation of these strains remains poorly understood and documented. This study aimed to identify and characterize Mycobacterium strains from suspected carcasses during routine meat inspection at Bobo-Dioulasso refrigerated slaughterhouse. A prospective cross-sectional study was conducted from January 2021 to December 2022 on cases of seizures linked to suspected bovine tuberculosis. Microbiological and molecular analyzes were used for mycobacterial strain isolation and characterization. Out of 50 samples, 24% tested positive by microscopy and 12% by culture. Molecular analysis identified 6 strains of Mycobacteria, exclusively Mycobacterium bovis specifically the subspecies bovis (Mycobacterium bovis subsp bovis). In conclusion, M. bovis subsp bovis is the primary agent responsible for bovine tuberculosis in Bobo-Dioulasso. Continuous monitoring of mycobacterial strains is therefore necessary for the effective control of this pathology in the local cattle population.展开更多
[Objectives]To establish a TLC and content determination method of Pileostegia tomentellal,with umbelliferone as the indicator component.[Methods]TLC identification was performed by silica gel G thin layer plate with ...[Objectives]To establish a TLC and content determination method of Pileostegia tomentellal,with umbelliferone as the indicator component.[Methods]TLC identification was performed by silica gel G thin layer plate with n-hexane-ethyl acetate(4:3)as the developing agent,and the plate was examined by UV lamp(365 nm).The umbelliferone content was determined by HPLC:Inertsil ODS-3 C 18 column(4.60 mm×250 mm,5μm);mobile phase acetonitrile-0.2%phosphoric acid gradient elution;detection wavelength 320 nm,flow rate 1.0 mL/min,column temperature 30℃,injection volume 10μL.[Results]The chromatogram of P.tomentellal showed the same color spot in the same position as that of reference medicinal material,and the spot was clear with good specificity.Umbelliferone showed a good linear relationship when the injection volume was 2.63-131.27μg/mL(R^(2)=0.9997).The average recovery of umbelliferone in the low,middle and high adding groups of P.tomentellal was 99.57%and the RSD was 2.15%.[Conclusions]The method can effectively identify Yao medicine P.tomentellal and accurately determine the content of umbelliferone in medicinal materials,which will provide a scientific basis for the development and utilization of medicinal resources of Yao medicine P.tomentellal.展开更多
[Objectives]To conduct the pharmacognostic identification of Hedyotis auricularia and Mitracarpus villosus in Guangxi and provide a scientific basis for their identification.[Methods]The characteristics of original pl...[Objectives]To conduct the pharmacognostic identification of Hedyotis auricularia and Mitracarpus villosus in Guangxi and provide a scientific basis for their identification.[Methods]The characteristics of original plants were studied by origin identification method;the properties and characteristics were studied by character identification method;and the microscopic features of the roots,stems,leaves and medicinal powder of H.auricularia and M.villosus in Guangxi were studied by paraffin method and powder slicing method.[Results](i)Origin identification.H.auricularia:Leaves leathery,apex acuminate,base cuneate;petiole shorter;cyme axillary;corolla hairy at throat;fruit indehiscent at maturity;testa black after drying.M.villosus:Leaf apex short pointed,base attenuate,blade sessile;flowers small,clustered in axillary;fruits dehiscent by lid at or below middle at maturity,seeds dark brown.(ii)Character identification.Fracture surface of H.auricularia uneven,white in outer layer and sepia in inner layer.Fracture surface of M.villosus hollow,uneven and white.(iii)Microscopic identification.H.auricularia:Root phloem thick,cambium visible,duct cells quasi-polygonal,large;rays obvious.Stem transection quasi-circular square,often with non-glandular hairs on epidermis;calcium oxalate raphides present in leaf parenchymal cells.Power grayish brown,starch granules single-grained;calcium oxalate raphides frequent,calcium oxalate clustered crystals occasional;catheter spiral,rarely annular,stomata infinitive.M.villosus:Root parenchyma cells with scattered calcium oxalate raphides,calcium oxalate clustered crystals and brownish red substances visible.Stem transection quasi-square,edge angle with 4 short narrow wings.Powder brown,simple starch granules numerous,compound starch granules also present;calcium oxalate raphides numerous,calcium oxalate clustered crystals and calcium oxalate square cubic crystals also present;catheter spiral,stomata paracytic.[Conclusions]The above transaction microscopic characteristics of the roots,stems and leaves and powder characteristics can be used as the identification features of H.auricularia and M.villosus.展开更多
[Objectives]The paper was to establish a TLC identification method for Ensete wilsonii.[Methods]Usingβ-sitosterol as the reference,the effects of preparation methods of test solutions,developing solvents,developing d...[Objectives]The paper was to establish a TLC identification method for Ensete wilsonii.[Methods]Usingβ-sitosterol as the reference,the effects of preparation methods of test solutions,developing solvents,developing distances and color developing agents on TLC analysis were investigated,and the best TLC conditions for E.wilsonii were determined.[Results]The test solution prepared with 90%methanol solvent was dotted on TLC silica gel G plate,and developed with dichloromethane-toluene-methanol=10:5:1.5 as the developing solvent.Then the plate was sprayed with 10%sulfuric acid ethanol solution,and dried with hot blast for color development.Finally,the plate was examined under an ultraviolet lamp at 365 nm.The TLC results of E.wilsonii obtained showed good separation and color development effect,and the spots were clear and characteristic.[Conclusions]This method is safe,specific,and easy to operate,and can be used as a TLC identification method for E.wilsonii.展开更多
[Objectives]To establish the quality standard of hospital preparation Jiedu Shengxue granules.[Methods]Scleromitrion diffusum and Prunella vulgaris in Jiedu Shengxue granules were qualitatively identified by thin laye...[Objectives]To establish the quality standard of hospital preparation Jiedu Shengxue granules.[Methods]Scleromitrion diffusum and Prunella vulgaris in Jiedu Shengxue granules were qualitatively identified by thin layer chromatography(TLC).A high performance liquid chromatography(HPLC)was established to determine the content of notoginsenoside R1 in the granule.[Results]The traditional Chinese medicinal materials in Jiedu Shengxue granules could be identified by TLC,and the characteristic spots were stable and clear.Notoginsenoside R1 had a good linear relationship in the range of 10.45-104.5μg/mL,with an average recovery of 98.52%and RSD=2.36%.[Conclusions]TLC and HPLC,as the quality control methods of Jiedu Shengxue granules,have high accuracy and good repeatability,which lays a foundation for the quality control of this mixture.展开更多
In this paper,a variety of classical convolutional neural networks are trained on two different datasets using transfer learning method.We demonstrated that the training dataset has a significant impact on the trainin...In this paper,a variety of classical convolutional neural networks are trained on two different datasets using transfer learning method.We demonstrated that the training dataset has a significant impact on the training results,in addition to the optimization achieved through the model structure.However,the lack of open-source agricultural data,combined with the absence of a comprehensive open-source data sharing platform,remains a substantial obstacle.This issue is closely related to the difficulty and high cost of obtaining high-quality agricultural data,the low level of education of most employees,underdeveloped distributed training systems and unsecured data security.To address these challenges,this paper proposes a novel idea of constructing an agricultural data sharing platform based on a federated learning(FL)framework,aiming to overcome the deficiency of high-quality data in agricultural field training.展开更多
Objective:To explore the relationship between organizational identification,occupational stress,and insomnia among nurses and to analyze the moderating role of organizational identification between occupational stress...Objective:To explore the relationship between organizational identification,occupational stress,and insomnia among nurses and to analyze the moderating role of organizational identification between occupational stress and insomnia.Methods:Through stratified sampling,720 nurses working in a tertiary A-level hospital in Shandong Province from March to May 2021 were surveyed using an effort-reward imbalance questionnaire,an organizational identification questionnaire,and the Athens Insomnia scale.Results:Organizational identification was negatively correlated with occupational stress and insomnia(r_(1)=-0.121,P_(1)<0.01;r_(2)=-0.144,P_(2)<0.01).Occupational stress was positively correlated with insomnia(r=0.379,P<0.01).Organizational identity significantly moderated nurses’occupational stress and insomnia(β=-0.192,t=-2.558,P<0.05).Conclusion:Occupational stress and organizational identification can predict insomnia.Organizational identification could negatively mediate the relationship between occupational stress and insomnia.Improving organizational identification may help alleviate insomnia symptoms by relieving occupational stress.展开更多
Modal and damage identification based on ambient excitation can greatly improve the efficiency of high-speed railway bridge vibration detection.This paper first describes the basic principles of stochastic subspace id...Modal and damage identification based on ambient excitation can greatly improve the efficiency of high-speed railway bridge vibration detection.This paper first describes the basic principles of stochastic subspace identification,peak-picking,and frequency domain decomposition method in modal analysis based on ambient excitation,and the effectiveness of these three methods is verified through finite element calculation and numerical simulation,Then the damage element is added to the finite element model to simulate the crack,and the curvature mode difference and the curvature mode area difference square ratio are calculated by using the stochastic subspace identification results to verify their ability of damage identification and location.Finally,the above modal and damage identification techniques are integrated to develop a bridge modal and damage identification software platform.The final results show that all three modal identification methods can accurately identify the vibration frequency and mode shape,both damage identification methods can accurately identify and locate the damage,and the developed software platform is simple and efficient.展开更多
Sesame is Burkina Faso’s second essential agricultural export after cotton. It’s consequently a supply of income for producers and foreign exchange for the country. However, sesame production is characterized by low...Sesame is Burkina Faso’s second essential agricultural export after cotton. It’s consequently a supply of income for producers and foreign exchange for the country. However, sesame production is characterized by low average yields of about 538 kg·ha<sup>-1</sup> at the farmer’s field as compared to the potential yield of the improved varieties (1500 - 2000 kg·ha<sup>-1</sup>). Fungal diseases are some of the major constraints to sesame production in Burkina Faso. The present study contributes to the development of means to control pathogenic fungi of this crop, which are responsible for significant losses. The objective is to identify the fungi associated with diseased sesame plant samples. To this end, 149 samples of diseased sesame plants were collected from different production sites located in three agro-climatic zones of the country. The analysis of the samples according to the blotting paper method, based on the morphological characteristics of the fungi, allowed the identification of 18 genera with prevalence rates from 2.68% to 97.98%. The most frequently identified genera were Macrophomina (97.98%), Cercospora (86.57%), Fusarium (85.23%), Phoma (62.41%) and Colletotrichum (61.07%). The results also showed a variable distribution of fungi according to the agro-climatic zone with the predominance of Macrophomina in all three zones. Molecular identification by DNA sequencing of 120 isolates belonging to the different fungi detected allowed the identification of 25 species of which the most representative were Macrophomina phaseolina, Cercospora sesami, Corynespora cassiicola, Alternaria simsimi, Alternaria porri, Fusarium oxysporum, F. fujikuroi, F. equiseti, Colletotrichum capsici, and C. gloesporiodes. The present study showed that diseased sesame plants collected from different production sites in Burkina Faso housed several species of fungi. The fungi presence in diseased plants indicates the need to inform and raise the stakeholders’ awareness about the phytosanitary problems of sesame, but also to develop effective and appropriate control methods against these crop pathogens in Burkina Faso.展开更多
基金funded by the National Natural Science Foundation of China(41907175)the Open Fund of Key Laboratory(WSRCR-2023-01)the project of the China Geological Survey(DD20230459).
文摘Groundwater is an important source of drinking water.Groundwater pollution severely endangers drinking water safety and sustainable social development.In the case of groundwater pollution,the top priority is to identify pollution sources,and accurate information on pollution sources is the premise of efficient remediation.Then,an appropriate pollution remediation scheme should be developed according to information on pollution sources,site conditions,and economic costs.The methods for identifying pollution sources mainly include geophysical exploration,geochemistry,isotopic tracing,and numerical modeling.Among these identification methods,only the numerical modeling can recognize various information on pollution sources,while other methods can only identify a certain aspect of pollution sources.The remediation technologies of groundwater can be divided into in-situ and ex-situ remediation technologies according to the remediation location.The in-situ remediation technologies enjoy low costs and a wide remediation range,but their remediation performance is prone to be affected by environmental conditions and cause secondary pollution.The ex-situ remediation technologies boast high remediation efficiency,high processing capacity,and high treatment concentration but suffer high costs.Different methods for pollution source identification and remediation technologies are applicable to different conditions.To achieve the expected identification and remediation results,it is feasible to combine several methods and technologies according to the actual hydrogeological conditions of contaminated sites and the nature of pollutants.Additionally,detailed knowledge about the hydrogeological conditions and stratigraphic structure of the contaminated site is the basis of all work regardless of the adopted identification methods or remediation technologies.
文摘Background:Euphorbia prostrata Ait.is an annual herb widely distributed in the southern region of China with great medical values on Anti-inflammation,insect repellent,treatment of diarrhea.Despite its extensive uses as a traditional Chinese medicine,no systematic research on the identification of E.prostrata has been reported.Methods:The study aimed to establish an accurate identification system for E.prostrata through traditional pharmacognostical methods,including botanical origin,morphological characters,medicinal material characters,microscopic characters,physicochemical parameters determination,phytochemical screening,and DNA barcoding analysis.Results:Physicochemical results show that this plant likely contains flavonoids,anthraquinones,and other substances.The ITS loci of the nuclear genome and psbA-trnH loci of the chloroplast genome were selected and evaluated,which were the most variable loci.Conclusion:The findings of this study are expected to contribute to the development of species identification,as well as provide references for authenticity identification,genetic relationship analysis,and further utilization of E.prostrata.
基金Supported by Guizhou Provincial Science and Technology Project[ZK(2022)-362](2022)4028+5 种基金ZK(2021)-554ZK(2023)-378]Science Foundation of Guizhou Health Commission(gzwkj2021-449)Innovation and Entrepreneurship Training Program for Undergraduates from China(202210660131)Science Foundation of Guizhou Education Technology(2022-064)Rural Economic Revitalization Research Project of Guizhou Medical University(GZYKDX-2022-002).
文摘[Objectives] To investigate the systematic evaluation of pharmacognostic identification of Polygonum capitatum . [Methods] 10 batches of P. capitatum cultivated in Guizhou were chosen for plant samples. Macroscopical identification was conducted on plant roots, stems, leaves, flowers and fruits. The P. capitatum powder was processed for physical and chemical distinction by FeCl 3 chromogenic reaction, hydrochloric acid magnesium powder reaction, AlCl 3 color development reaction and thin-layer chromatography.Microscope identification was carried out on the powder. Plant genome DNeasy Plant Kit was adopted for DNA molecular marker identification. [Results] The results showed that the stem of P. capitatum was tufted, the leaves were oval, 2 to 5 cm long, and 1 to 2 cm wide;the leaf apex was acute and cuneate at the base, the inflorescence was capitate, paired or solitary;the raceme was erect and nearly spherical, and the perianth was light red. Furthermore, for the chromogenic reaction of FeCl 3 ethanol extract of P. capitatum , appeared blue and turned to dark blue after long time storing at room temperature. For the reaction of hydrochloric acid magnesium powder, the alcohol extract of P. capitatum , exhibited deep red. In the color reaction of AlCl 3, the alcohol extract revealed yellow fluorescence under 360 nm UV lamp. Microscope identification of the powder displayed pollen grains, crystal sheath fibers, cellulose, vessels, starch grains, cork cells, and other characteristic fragments. In addition, DNA barcoding electrophoresis results showed that P. capitatum showed a clear and bright single band near 500 bp, and further sequencing results showed that the sequence differences were mainly concentrated in ITS1 and ITS2 region. [Conclusions] Systematic evaluation for the identification of P. capitatum is established, which combines with macroscopic identification, physicochemical identification, powder microscope identification, and DNA molecular identification. Finally, the original medicinal material is identified as P. capitatum Buch.-Ham. ex D. Don.
基金partially supported by the Natural Science Foundation of China (Grant Nos.62103052,52272358)partially supported by the Beijing Institute of Technology Research Fund Program for Young Scholars。
文摘This paper investigates the adaptive trajectory tracking control problem and the unknown parameter identification problem of a class of rotor-missiles with parametric system uncertainties.First,considering the uncertainty of structural and aerodynamic parameters,the six-degree-of-freedom(6Do F) nonlinear equations describing the position and attitude dynamics of the rotor-missile are established,respectively,in the inertial and body-fixed reference frames.Next,a hierarchical adaptive trajectory tracking controller that can guarantee closed-loop stability is proposed according to the cascade characteristics of the 6Do F dynamics.Then,a memory-augmented update rule of unknown parameters is proposed by integrating all historical data of the regression matrix.As long as the finitely excited condition is satisfied,the precise identification of unknown parameters can be achieved.Finally,the validity of the proposed trajectory tracking controller and the parameter identification method is proved through Lyapunov stability theory and numerical simulations.
基金supported by CNPC-CZU Innovation Alliancesupported by the Program of Polar Drilling Environmental Protection and Waste Treatment Technology (2022YFC2806403)。
文摘In petroleum engineering,real-time lithology identification is very important for reservoir evaluation,drilling decisions and petroleum geological exploration.A lithology identification method while drilling based on machine learning and mud logging data is studied in this paper.This method can effectively utilize downhole parameters collected in real-time during drilling,to identify lithology in real-time and provide a reference for optimization of drilling parameters.Given the imbalance of lithology samples,the synthetic minority over-sampling technique(SMOTE)and Tomek link were used to balance the sample number of five lithologies.Meanwhile,this paper introduces Tent map,random opposition-based learning and dynamic perceived probability to the original crow search algorithm(CSA),and establishes an improved crow search algorithm(ICSA).In this paper,ICSA is used to optimize the hyperparameter combination of random forest(RF),extremely random trees(ET),extreme gradient boosting(XGB),and light gradient boosting machine(LGBM)models.In addition,this study combines the recognition advantages of the four models.The accuracy of lithology identification by the weighted average probability model reaches 0.877.The study of this paper realizes high-precision real-time lithology identification method,which can provide lithology reference for the drilling process.
基金The National Natural Science Foundation of China under contract Nos 61890964 and 42206177the Joint Funds of the National Natural Science Foundation of China under contract No.U1906217.
文摘Marine oil spill emulsions are difficult to recover,and the damage to the environment is not easy to eliminate.The use of remote sensing to accurately identify oil spill emulsions is highly important for the protection of marine environments.However,the spectrum of oil emulsions changes due to different water content.Hyperspectral remote sensing and deep learning can use spectral and spatial information to identify different types of oil emulsions.Nonetheless,hyperspectral data can also cause information redundancy,reducing classification accuracy and efficiency,and even overfitting in machine learning models.To address these problems,an oil emulsion deep-learning identification model with spatial-spectral feature fusion is established,and feature bands that can distinguish between crude oil,seawater,water-in-oil emulsion(WO),and oil-in-water emulsion(OW)are filtered based on a standard deviation threshold–mutual information method.Using oil spill airborne hyperspectral data,we conducted identification experiments on oil emulsions in different background waters and under different spatial and temporal conditions,analyzed the transferability of the model,and explored the effects of feature band selection and spectral resolution on the identification of oil emulsions.The results show the following.(1)The standard deviation–mutual information feature selection method is able to effectively extract feature bands that can distinguish between WO,OW,oil slick,and seawater.The number of bands was reduced from 224 to 134 after feature selection on the Airborne Visible Infrared Imaging Spectrometer(AVIRIS)data and from 126 to 100 on the S185 data.(2)With feature selection,the overall accuracy and Kappa of the identification results for the training area are 91.80%and 0.86,respectively,improved by 2.62%and 0.04,and the overall accuracy and Kappa of the identification results for the migration area are 86.53%and 0.80,respectively,improved by 3.45%and 0.05.(3)The oil emulsion identification model has a certain degree of transferability and can effectively identify oil spill emulsions for AVIRIS data at different times and locations,with an overall accuracy of more than 80%,Kappa coefficient of more than 0.7,and F1 score of 0.75 or more for each category.(4)As the spectral resolution decreasing,the model yields different degrees of misclassification for areas with a mixed distribution of oil slick and seawater or mixed distribution of WO and OW.Based on the above experimental results,we demonstrate that the oil emulsion identification model with spatial–spectral feature fusion achieves a high accuracy rate in identifying oil emulsion using airborne hyperspectral data,and can be applied to images under different spatial and temporal conditions.Furthermore,we also elucidate the impact of factors such as spectral resolution and background water bodies on the identification process.These findings provide new reference for future endeavors in automated marine oil spill detection.
基金This work was supported by the Strategic Priority Research Program of Chinese Academy of Sciences(No.XDB34030000)the National Key Research and Development Program of China(No.2022YFA1602404)+1 种基金the National Natural Science Foundation(No.U1832129)the Youth Innovation Promotion Association CAS(No.2017309).
文摘Traditional particle identification methods face timeconsuming,experience-dependent,and poor repeatability challenges in heavy-ion collisions at low and intermediate energies.Researchers urgently need solutions to the dilemma of traditional particle identification methods.This study explores the possibility of applying intelligent learning algorithms to the particle identification of heavy-ion collisions at low and intermediate energies.Multiple intelligent algorithms,including XgBoost and TabNet,were selected to test datasets from the neutron ion multi-detector for reaction-oriented dynamics(NIMROD-ISiS)and Geant4 simulation.Tree-based machine learning algorithms and deep learning algorithms e.g.TabNet show excellent performance and generalization ability.Adding additional data features besides energy deposition can improve the algorithm’s performance when the data distribution is nonuniform.Intelligent learning algorithms can be applied to solve the particle identification problem in heavy-ion collisions at low and intermediate energies.
文摘The combination of structural health monitoring and vibration control is of great importance to provide components of smart structures.While synthetic algorithms have been proposed,adaptive control that is compatible with changing conditions still needs to be used,and time-varying systems are required to be simultaneously estimated with the application of adaptive control.In this research,the identification of structural time-varying dynamic characteristics and optimized simple adaptive control are integrated.First,reduced variations of physical parameters are estimated online using the multiple forgetting factor recursive least squares(MFRLS)method.Then,the energy from the structural vibration is simultaneously specified to optimize the control force with the identified parameters to be operational.Optimization is also performed based on the probability density function of the energy under the seismic excitation at any time.Finally,the optimal control force is obtained by the simple adaptive control(SAC)algorithm and energy coefficient.A numerical example and benchmark structure are employed to investigate the efficiency of the proposed approach.The simulation results revealed the effectiveness of the integrated online identification and optimal adaptive control in systems.
基金supported by the 2022 National Natural Science Foundation of China(No.62277002)the National Key Research and Development Program of China(2022YFC3303500).
文摘The social transformation brought aboutby digital technology is deeply impacting various industries.Digital education products, with core technologiessuch as 5G, AI, IoT (Internet of Things),etc., are continuously penetrating areas such as teaching,management, and evaluation. Apps, miniprograms,and emerging large-scale models are providingexcellent knowledge performance and flexiblecross-media output. However, they also exposerisks such as content discrimination and algorithmcommercialization. This paper conducts anevidence-based analysis of digital education productrisks from four dimensions: “digital resourcesinformationdissemination-algorithm design-cognitiveassessment”. It breaks through corresponding identificationtechnologies and, relying on the diverse characteristicsof governance systems, explores governancestrategies for digital education products from the threedomains of “regulators-developers-users”.
文摘Almost all sandstone reservoirs contain interlayers. The identification and characterization of these interlayers iscritical for minimizing the uncertainty associated with oilfield development and improving oil and gas recovery.Identifying interlayers outside wells using identification methods based on logging data and machine learning isdifficult and seismic-based identification techniques are expensive. Herein, a numerical model based on seepageand well-testing theories is introduced to identify interlayers using transient pressure data. The proposed modelrelies on the open-source MATLAB Reservoir Simulation Toolbox. The effects of the interlayer thickness, position,and width on the pressure response are thoroughly investigated. A procedure for inverting interlayer parametersin the reservoir using the bottom-hole pressure is also proposed. This method uses only transient pressuredata during well testing and can effectively identify the interlayer distribution near the wellbore at an extremelylow cost. The reliability of the model is verified using effective oilfield examples.
基金The paper is a staged result of“Research on Narrative Strategy for Telling China’s Stories Well in the Cross-Cultural Context”(17XXW008),a program funded by the National Social Science Fund of China(NSSF).
文摘Cross-cultural storytelling is a primary way for humankind to seek mutual recognition of value orientations between cultures,which facilitates the ability to jointly address the problems of human existence in the context of globalization.In this study,we conducted an interview survey of 6,130 respondents who were college students or graduates from 107 countries.The results show that there were a number of cross-cultural values embodied in China’s stories seen by the respondents as part of a common vision for the future of humankind and widely identified guidance on collaborative responses to global challenges.These cross-cultural values are common prosperity,ecological harmony,individual-collective integration,the urgency of global peace,as well as respect for multicultural and indigenous development paths.
文摘Bovine tuberculosis (bTB) is an endemic zoonosis significantly affects animal health in Burkina Faso. The primary causative agent is Mycobacterium tuberculosis (M. tuberculosis) complex, mainly M. bovis. Cattle are considered as natural reservoir of M. bovis. However, in Burkina Faso, the circulation of these strains remains poorly understood and documented. This study aimed to identify and characterize Mycobacterium strains from suspected carcasses during routine meat inspection at Bobo-Dioulasso refrigerated slaughterhouse. A prospective cross-sectional study was conducted from January 2021 to December 2022 on cases of seizures linked to suspected bovine tuberculosis. Microbiological and molecular analyzes were used for mycobacterial strain isolation and characterization. Out of 50 samples, 24% tested positive by microscopy and 12% by culture. Molecular analysis identified 6 strains of Mycobacteria, exclusively Mycobacterium bovis specifically the subspecies bovis (Mycobacterium bovis subsp bovis). In conclusion, M. bovis subsp bovis is the primary agent responsible for bovine tuberculosis in Bobo-Dioulasso. Continuous monitoring of mycobacterial strains is therefore necessary for the effective control of this pathology in the local cattle population.
基金Supported by Self-funded Research Project of Administration of Traditional Chinese Medicine of Guangxi Zhuang Autonomous Region(GXZYA20220171)Young and Middle-aged Teachers Research Basic Ability Improvement Project of Colleges and Universities in Guangxi(2022KY0307)+5 种基金General Project of Guangxi University of Chinese Medicine(2022MS038)"Qingmiao Project"Talent Cultivation Program of Guangxi International Zhuang Medical Hospital(2022001)Key Project of Guangxi International Zhuang Medical Hospital(GZ2021010)High-level TCM Key Discipline(Zhuang Medical Science)Construction Project of State Administration of Traditional Chinese Medicine(zyyzdxk-2023165)Key Research and Development Project of Guangxi Provincial Department of Science and Technology(GK AB21196057)High-level Talent Cultivation Innovation Team Funding Project of Guangxi University of Chinese Medicine(2022A008).
文摘[Objectives]To establish a TLC and content determination method of Pileostegia tomentellal,with umbelliferone as the indicator component.[Methods]TLC identification was performed by silica gel G thin layer plate with n-hexane-ethyl acetate(4:3)as the developing agent,and the plate was examined by UV lamp(365 nm).The umbelliferone content was determined by HPLC:Inertsil ODS-3 C 18 column(4.60 mm×250 mm,5μm);mobile phase acetonitrile-0.2%phosphoric acid gradient elution;detection wavelength 320 nm,flow rate 1.0 mL/min,column temperature 30℃,injection volume 10μL.[Results]The chromatogram of P.tomentellal showed the same color spot in the same position as that of reference medicinal material,and the spot was clear with good specificity.Umbelliferone showed a good linear relationship when the injection volume was 2.63-131.27μg/mL(R^(2)=0.9997).The average recovery of umbelliferone in the low,middle and high adding groups of P.tomentellal was 99.57%and the RSD was 2.15%.[Conclusions]The method can effectively identify Yao medicine P.tomentellal and accurately determine the content of umbelliferone in medicinal materials,which will provide a scientific basis for the development and utilization of medicinal resources of Yao medicine P.tomentellal.
基金Supported by Collaborative Innovation Center of Zhuang and Yao Ethnic Medicines(GJKY[2013]20)Guangxi Key Laboratory of Zhuang and Yao Ethnic Medicines(GKJZ[2014]32)+3 种基金"Guipai Xinglin Young Talent"Project of Guangxi University of Chinese Medicine(2022C030)Ethnomedicine Resources and Application Engineering Research Center of Guangxi Zhuang Autonomous Region(GFGGJH[2020]2605)Guangxi Key Discipline of Traditional Chinese Medicine:Zhuang Pharmacology(GZXK-Z-20-64)Guangxi First-class Discipline:Traditional Chinese Pharmacology(Ethnic Medicine)(GJKY[2018]12).
文摘[Objectives]To conduct the pharmacognostic identification of Hedyotis auricularia and Mitracarpus villosus in Guangxi and provide a scientific basis for their identification.[Methods]The characteristics of original plants were studied by origin identification method;the properties and characteristics were studied by character identification method;and the microscopic features of the roots,stems,leaves and medicinal powder of H.auricularia and M.villosus in Guangxi were studied by paraffin method and powder slicing method.[Results](i)Origin identification.H.auricularia:Leaves leathery,apex acuminate,base cuneate;petiole shorter;cyme axillary;corolla hairy at throat;fruit indehiscent at maturity;testa black after drying.M.villosus:Leaf apex short pointed,base attenuate,blade sessile;flowers small,clustered in axillary;fruits dehiscent by lid at or below middle at maturity,seeds dark brown.(ii)Character identification.Fracture surface of H.auricularia uneven,white in outer layer and sepia in inner layer.Fracture surface of M.villosus hollow,uneven and white.(iii)Microscopic identification.H.auricularia:Root phloem thick,cambium visible,duct cells quasi-polygonal,large;rays obvious.Stem transection quasi-circular square,often with non-glandular hairs on epidermis;calcium oxalate raphides present in leaf parenchymal cells.Power grayish brown,starch granules single-grained;calcium oxalate raphides frequent,calcium oxalate clustered crystals occasional;catheter spiral,rarely annular,stomata infinitive.M.villosus:Root parenchyma cells with scattered calcium oxalate raphides,calcium oxalate clustered crystals and brownish red substances visible.Stem transection quasi-square,edge angle with 4 short narrow wings.Powder brown,simple starch granules numerous,compound starch granules also present;calcium oxalate raphides numerous,calcium oxalate clustered crystals and calcium oxalate square cubic crystals also present;catheter spiral,stomata paracytic.[Conclusions]The above transaction microscopic characteristics of the roots,stems and leaves and powder characteristics can be used as the identification features of H.auricularia and M.villosus.
基金Supported by Innovation Project of Guangxi Graduate Education of GXUCM(YCSY2022012)High-level Innovation Team and Outstanding Scholars Program of Universities and Colleges in Guangxi(GJR[2014]07)Guangxi Key Laboratory of Efficacy Study on Chinese Materia Medica(20-065-38).
文摘[Objectives]The paper was to establish a TLC identification method for Ensete wilsonii.[Methods]Usingβ-sitosterol as the reference,the effects of preparation methods of test solutions,developing solvents,developing distances and color developing agents on TLC analysis were investigated,and the best TLC conditions for E.wilsonii were determined.[Results]The test solution prepared with 90%methanol solvent was dotted on TLC silica gel G plate,and developed with dichloromethane-toluene-methanol=10:5:1.5 as the developing solvent.Then the plate was sprayed with 10%sulfuric acid ethanol solution,and dried with hot blast for color development.Finally,the plate was examined under an ultraviolet lamp at 365 nm.The TLC results of E.wilsonii obtained showed good separation and color development effect,and the spots were clear and characteristic.[Conclusions]This method is safe,specific,and easy to operate,and can be used as a TLC identification method for E.wilsonii.
基金Supported by Guangxi Hospital Preparation Quality Improvement Project of Zhuang and Yao Ethnic Medicines(GZZJ202015)Key Research and Development Plan of Guangxi Department of Science and Technology(GK AB21196057)+3 种基金High-level TCM Key Discipline(Zhuang Pharmacology)Construction Project of State Administration of Traditional Chinese Medicine(GZYYRJH[2022]226)Guangxi TCM Multidisciplinary Innovative Team Project(GZKJ2309)"Qingmiao Engineering"Talent Cultivation Project of Guangxi International Zhuang Medical Hospital(2022001)"High-level Talent Cultivation and Innovation Team"Project of Guangxi University of Chinese Medicine(2022A008).
文摘[Objectives]To establish the quality standard of hospital preparation Jiedu Shengxue granules.[Methods]Scleromitrion diffusum and Prunella vulgaris in Jiedu Shengxue granules were qualitatively identified by thin layer chromatography(TLC).A high performance liquid chromatography(HPLC)was established to determine the content of notoginsenoside R1 in the granule.[Results]The traditional Chinese medicinal materials in Jiedu Shengxue granules could be identified by TLC,and the characteristic spots were stable and clear.Notoginsenoside R1 had a good linear relationship in the range of 10.45-104.5μg/mL,with an average recovery of 98.52%and RSD=2.36%.[Conclusions]TLC and HPLC,as the quality control methods of Jiedu Shengxue granules,have high accuracy and good repeatability,which lays a foundation for the quality control of this mixture.
基金National Key Research and Development Program of China(2021ZD0113704).
文摘In this paper,a variety of classical convolutional neural networks are trained on two different datasets using transfer learning method.We demonstrated that the training dataset has a significant impact on the training results,in addition to the optimization achieved through the model structure.However,the lack of open-source agricultural data,combined with the absence of a comprehensive open-source data sharing platform,remains a substantial obstacle.This issue is closely related to the difficulty and high cost of obtaining high-quality agricultural data,the low level of education of most employees,underdeveloped distributed training systems and unsecured data security.To address these challenges,this paper proposes a novel idea of constructing an agricultural data sharing platform based on a federated learning(FL)framework,aiming to overcome the deficiency of high-quality data in agricultural field training.
文摘Objective:To explore the relationship between organizational identification,occupational stress,and insomnia among nurses and to analyze the moderating role of organizational identification between occupational stress and insomnia.Methods:Through stratified sampling,720 nurses working in a tertiary A-level hospital in Shandong Province from March to May 2021 were surveyed using an effort-reward imbalance questionnaire,an organizational identification questionnaire,and the Athens Insomnia scale.Results:Organizational identification was negatively correlated with occupational stress and insomnia(r_(1)=-0.121,P_(1)<0.01;r_(2)=-0.144,P_(2)<0.01).Occupational stress was positively correlated with insomnia(r=0.379,P<0.01).Organizational identity significantly moderated nurses’occupational stress and insomnia(β=-0.192,t=-2.558,P<0.05).Conclusion:Occupational stress and organizational identification can predict insomnia.Organizational identification could negatively mediate the relationship between occupational stress and insomnia.Improving organizational identification may help alleviate insomnia symptoms by relieving occupational stress.
文摘Modal and damage identification based on ambient excitation can greatly improve the efficiency of high-speed railway bridge vibration detection.This paper first describes the basic principles of stochastic subspace identification,peak-picking,and frequency domain decomposition method in modal analysis based on ambient excitation,and the effectiveness of these three methods is verified through finite element calculation and numerical simulation,Then the damage element is added to the finite element model to simulate the crack,and the curvature mode difference and the curvature mode area difference square ratio are calculated by using the stochastic subspace identification results to verify their ability of damage identification and location.Finally,the above modal and damage identification techniques are integrated to develop a bridge modal and damage identification software platform.The final results show that all three modal identification methods can accurately identify the vibration frequency and mode shape,both damage identification methods can accurately identify and locate the damage,and the developed software platform is simple and efficient.
文摘Sesame is Burkina Faso’s second essential agricultural export after cotton. It’s consequently a supply of income for producers and foreign exchange for the country. However, sesame production is characterized by low average yields of about 538 kg·ha<sup>-1</sup> at the farmer’s field as compared to the potential yield of the improved varieties (1500 - 2000 kg·ha<sup>-1</sup>). Fungal diseases are some of the major constraints to sesame production in Burkina Faso. The present study contributes to the development of means to control pathogenic fungi of this crop, which are responsible for significant losses. The objective is to identify the fungi associated with diseased sesame plant samples. To this end, 149 samples of diseased sesame plants were collected from different production sites located in three agro-climatic zones of the country. The analysis of the samples according to the blotting paper method, based on the morphological characteristics of the fungi, allowed the identification of 18 genera with prevalence rates from 2.68% to 97.98%. The most frequently identified genera were Macrophomina (97.98%), Cercospora (86.57%), Fusarium (85.23%), Phoma (62.41%) and Colletotrichum (61.07%). The results also showed a variable distribution of fungi according to the agro-climatic zone with the predominance of Macrophomina in all three zones. Molecular identification by DNA sequencing of 120 isolates belonging to the different fungi detected allowed the identification of 25 species of which the most representative were Macrophomina phaseolina, Cercospora sesami, Corynespora cassiicola, Alternaria simsimi, Alternaria porri, Fusarium oxysporum, F. fujikuroi, F. equiseti, Colletotrichum capsici, and C. gloesporiodes. The present study showed that diseased sesame plants collected from different production sites in Burkina Faso housed several species of fungi. The fungi presence in diseased plants indicates the need to inform and raise the stakeholders’ awareness about the phytosanitary problems of sesame, but also to develop effective and appropriate control methods against these crop pathogens in Burkina Faso.
