Investigation and Analysis of Main Diseases of Landscape Plants in the Main Urban Area of Lu'an City

To figure out the disease occurrence of landscape plants in the main urban area of Lu'an City,the author investigated the disease occurrence of landscape plants in park green space,residential green space,unit attached green space and main road in the area under administration.The survey results showed that there were 29 species of urban landscape plant diseases,mainly powdery mildew and spot diseases.According to the characteristics of the diseases,the causes and problems of the diseases were analyzed,and the corresponding prevention and control measures were put forward.

Potential efficacy and mechanism of medicinal plants on chronic kidney disease-associated vascular calcification:a review

Vascular calcification is a crucial risk factor that affects the incidence and mortality of cardiovascular disease in chronic kidney disease patients.Modern medicine relies on calcium-phosphorus binding agents,calcium mimetics,active vitamin D,and hemodialysis to prevent and treat vascular calcification,however,their efficacy is unsatisfactory and adverse reactions often occur.Medical plant therapy can act as an integrative regulator in patients with chronic kidney disease-associated vascular calcification,which can significantly improve patients’symptoms,but its specific mechanism has not been fully elucidated yet.In this paper,we reviewed the domestic and international theoretical studies on the pathogenesis mechanism of chronic kidney disease-associated vascular calcification in recent years,summarized eight active ingredients of medicinal plants as well as four compound formulas for improving chronic kidney disease-associated vascular calcification,and explored the mechanism of action of herbal medicine,which will provide a new strategy for promoting the prevention and treatment of vascular calcification.

Fermentation, formulation and evaluation of PGPR Bacillus subtilis isolate as a bioagent for reducing occurrence of peanut soil-borne diseases

Four isolates of Bacillus subtilis coded,B4,B7,B8 and B10 were examined as biocontrol agents for their abilities and antagonistic effect on the in vitro growth of certain phytopathogenic fungi of peanut,Rhizoctonia solani and Sclerotium rolfsii.Bacillus subtilis isolate B4(GenBank accession no.EF150884)was the highly effective one for inhibiting the fungal mycelial growth.Batch fermentation of B.subtilis isolate B4 was carried out and the maximum biomass achieved was 4.53 g L-1 at 11 h.Bacillus subtilis isolate B4 was formulated and evaluated as a biofungicide to reduce peanut soil-borne diseases under greenhouse and field conditions at the side of Rizolex-T(fungicide)as standard.Treatments by formulated plant growth-promoting rhizobacteria(PGPR)B.subtilis B4 and Rizolex-T in a soil infested with R.solani,S.rolfsii and mixture of them were more effective in decreasing percentage of damping-off,root and pod rot disease incidence(%)in greenhouse and open field environment during the two seasons 2015 and 2016.Treatments by PGPR gave highly dry weight and number of healthy pods compared to control of fungi treatment which was nearby to dry weights of healthy pods achieved by treatments by Rizolex-T in a soil infested with S.rolfsii,R.solani and mixture of them.Formulated PGPR B.subtilis B4 gave higher increasing of yield percentage than treatment by Rizolex-T in the two evaluated seasons 2015 and 2016.It can conclude that the produced bioforumlated agent was more efficient as fungicide when compared with the other chemical synthesized fungicides,safe for human and the environment and economy.

Design and Research on Identification of Typical Tea Plant Diseases Using Small Sample Learning

Tea plants are susceptible to diseases during their growth.These diseases seriously affect the yield and quality of tea.The effective prevention and control of diseases requires accurate identification of diseases.With the development of artificial intelligence and computer vision,automatic recognition of plant diseases using image features has become feasible.As the support vector machine(SVM)is suitable for high dimension,high noise,and small sample learning,this paper uses the support vector machine learning method to realize the segmentation of disease spots of diseased tea plants.An improved Conditional Deep Convolutional Generation Adversarial Network with Gradient Penalty(C-DCGAN-GP)was used to expand the segmentation of tea plant spots.Finally,the Visual Geometry Group 16(VGG16)deep learning classification network was trained by the expanded tea lesion images to realize tea disease recognition.

Compounds from African Medicinal Plants with Activities Against Selected Parasitic Diseases:Schistosomiasis,Trypanosomiasis and Leishmaniasis

Parasitic diseases continue to represent a threat on a global scale,particularly among the poorest countries in the world.This is particularly because of the absence of vaccines,and in some cases,resistance against available drugs,currently being used for their treatment.In this review emphasis is laid on natural products and scaffolds from African medicinal plants(AMPs)for lead drug discovery and possible further development of drugs for the treatment of parasitic diseases.In the discussion,emphasis has been laid on alkaloids,terpenoids,quinones,flavonoids and narrower compound classes of compounds with micromolar range activities against Schistosoma,Trypanosoma and Leishmania species.In each subparagraph,emphasis is laid on the compound subclasses with most promising in vitro and/or in vivo activities of plant extracts and isolated compounds.Suggestions for future drug development from African medicinal plants have also been provided.This review covering 167 references,including 82 compounds,provides information published within two decades(1997-2017).

Prevention and Control Technology of Potato Soil-borne Diseases

In recent years,potato soil-borne diseases have occurred severely.The investigation shows that potato Fusarium wilt greatly affects potato yield,leading to a yield reduction rate of 21.8%.Potato powdery scab shows very mild symptoms on potato tuber,basically with no symptoms in some plots,but shows obvious symptoms on the root system.A large number of nodules which are produced on one side of the root system seriously affect water and fertilizer absorption function of the potato root system.Potato tubers expand slowly,leading to small potato tuber,low yield and low commodity rate.The fungus can survive in soil for more than 10 years.Potato soil-borne diseases are harmful and are difficult to control.Susceptible plants can be detected by high definition chromatographic control method and pathogen detection.For prevention and control of potato soil-borne diseases,first of all,disease-resistant varieties should be chosen and virus-free potato seeds are used for sowing.Secondly,metham and dazomet can be used to treat soil in order to prevent and control potato soil-borne diseases.The results showed that the dead seedling rate treated by metham was reduced from 35%to 12.5%compared with the blank control,and the yield was increased by 44.09 kg/ha,with an increase rate of 18.2%.Compared with the blank control,the dead seedling rate treated by dazomet was decreased from 35%to 7.5%,and the yield was increased by 38.10 kg/ha,with an increase rate of 15.7%.The soil treatment received obvious yield increase effect.

Ethnomedicinal plants used in the treatment of skin diseases in Hyderabad Karnataka region,Karnataka,India

Objective:To document traditional medicinal plants knowledge used in treating skin diseases at Hyderabad Karnataka Region.Methods:The information on the use of medicinal plants in the treatment of skin diseases was gathered from traditional herbal healers and other villagers through interviews.Results:A total of 60 plants species belonging to 57 genera and 34 families were found useful and herewith described them along with the method of drug preparation,mode of administration,probable dosage and duration of treatment.Several new findings on the traditional rural practices were reported.Conclusions:The present study revealed that the Hyderabad Kamataka rural people is primarily dependent on medicinal plants for treating skin diseases.

Recent Progress in Elucidating the Structure, Function and Evolution of Disease Resistance Genes in Plants

Plants employ multifaceted mechanisms to fight with numerous pathogens in nature. Resistance （R） genes are the most effective weapons against pathogen invasion since they can specifically recognize the corresponding pathogen effectors or associated protein（s） to activate plant immune responses at the site of infection. Up to date, over 70 R genes have been isolated from various plant species. Most R proteins contain conserved motifs such as nucleotide-binding site （NBS）, leucine-rich repeat （LRR）, Toll-interleukin-1 receptor domain （TIR, homologous to cytoplasmic domains of the Drosophila Toll protein and the manamalian intefleukin-1 receptor）, coiled-coil （CC） or leucine zipper （LZ） structure and protein kinase domain （PK）. Recent results indicate that these domains play significant roles in R protein interactions with effector proteins from pathogens and in activating signal transduction pathways involved in innate immunity. This review highlights an overview of the recent progress in elucidating the structure, function and evolution of the isolated R genes in different plant-pathogen interaction systems.

Screening of Two Biocontrol Strains of Bacillus subtilis against Ginseng Soil-borne Disease and Their Antifungal Activities

[ Objective] The paper was to obtain biocontrol strains with good control effects against ginseng soil-borne disease through screening. [ Method] Dilu- tion plate method and plate confrontation culture method were used to isolate and screen biocontrol bacteria from the rhizosphere soil of diseased ginseng. The strains were identified through morphology, physiological and biochemical characteristics and 16S rDNA. [ Result ] With Rhizoctonia solani, Fusarium oxysporum and Fu- sarium solani as the indicator strains, two biocontrol strains B59 and X1 with strong antagonistic effects were screened from the rhizosphere soil of diseased ginseng in Tieli farm of Heilongjiang Province, and they were identified to be Bacillus subtilis. The inhibition rates of two biocontrol strains against eight different fungi were all greater than 90%. The primary study indicated that B59 and X1 strains could secrete antifungal active substances. [ Conclusion] Two biocontrol Bacillus subti- lis strains 1359 and X1 all had strong antagonistic effect against ginseng soil-borne disease, which had certain potential for development and utilization.

Construction of Early-warning Model for Plant Diseases and Pests Based on Improved Neural Network

By studying principles and methods related to early-warning model of plant diseases and using PSO method, parameter optimization was conducted to backward propagation neural network, and a pre-warning model for plant diseases based on particle swarm and neural network algorithm was established. The test results showed that the construction of early-warning model is effective and feasible, which will provide a via- ble model structure to establish the effective early-warning platform.

Development of Machine Learning Methods for Accurate Prediction of Plant Disease Resistance

The traditional method of screening plants for disease resistance phenotype is both time-consuming and costly.Genomic selection offers a potential solution to improve efficiency,but accurately predicting plant disease resistance remains a challenge.In this study,we evaluated eight different machine learning(ML)methods,including random forest classification(RFC),support vector classifier(SVC),light gradient boosting machine(lightGBM),random forest classification plus kinship(RFC_K),support vector classification plus kinship(SVC_K),light gradient boosting machine plus kinship(lightGBM_K),deep neural network genomic prediction(DNNGP),and densely connected convolutional networks(DenseNet),for predicting plant disease resistance.Our results demonstrate that the three plus kinship(K)methods developed in this study achieved high prediction accuracy.Specifically,these methods achieved accuracies of up to 95%for rice blast(RB),85%for rice black-streaked dwarf virus(RBSDV),and 85%for rice sheath blight(RSB)when trained and applied to the rice diversity panel I(RDPI).Furthermore,the plus K models performed well in predicting wheat blast(WB)and wheat stripe rust(WSR)diseases,with mean accuracies of up to 90%and 93%,respectively.To assess the generalizability of our models,we applied the trained plus K methods to predict RB disease resistance in an independent population,rice diversity panel II(RDPII).Concurrently,we evaluated the RB resistance of RDPII cultivars using spray inoculation.Comparing the predictions with the spray inoculation results,we found that the accuracy of the plus K methods reached 91%.These findings highlight the effectiveness of the plus K methods(RFC_K,SVC_K,and lightGBM_K)in accurately predicting plant disease resistance for RB,RBSDV,RSB,WB,and WSR.The methods developed in this study not only provide valuable strategies for predicting disease resistance,but also pave the way for using machine learning to streamline genome-based crop breeding.

Effects of medicinal plants on Alzheimer＇s disease and memory deficits

Alzheimer＇s disease is an age-related neurodegenerative disorder characterized by memory deficits. Various studies have been carried out to find therapeutic approaches for Alzheimer＇s disease. However, the proper treatment option is still not available. There is no cure for Alzheimer＇s disease, but symptomatic treatment may improve the memory and other dementia related problems. Traditional medicine is practiced world- wide as memory enhancer since ancient times. Natural therapy including herbs and medicinal plants has been used in the treatment of memory deficits such as dementia, amnesia, as well as Alzheimer＇s disease since a long time. Medicinal plants have been used in different systems of medicine, particularly Unani system of medicines and exhibited their powerful roles in the management and cure of memory disorders. Most of herbs and plants have been chemically evaluated and their efficacy has also been proven in clinical trials. However, the underlying mechanisms of actions are still on the way. In this paper, we have reviewed the role of different medicinal plants that play an important role in the treatment of Alzheimer＇s disease and memory deficits using conventional herbal therapy.

Assessing the Efficacy of Lemongrass (Cymbopogon citratus) and Sambong (Blumea balsamifera) Extracts in Combating Black Pod Disease: Sustainable Solutions for Controlling Phytophthora megakarya in Cameroon’s Cocoa Plantations

The use of plant extracts as antifungal agents is gaining increasing attention, particularly for the control of black pod disease in cocoa. Despite extensive research, current strategies haven’t been entirely effective. This study evaluated the effectiveness of Cymbopogon citratus and Blumea balsamifora leaf extracts, both individually and in combination, against Phytophthora megakarya. We assessed the efficacy of the most promising combination (75% B. balsamifera, 25% C. citratus) after storage at room temperature for up to 9 days. Agar microdilution and in vivo bioassays were conducted to determine antifungal susceptibility and effectiveness. Blumea extract exhibited the highest overall inhibitory activity, with the lowest minimum inhibitory concentration (117 µl mL−1) while C. citratus had a narrower range of MIC (146 to 233 µl mL−1). The combination of C. citratus and B. balsamifera demonstrated a synergistic effect against P. megakarya, achieving growth inhibition on V8 media (92.72 ± 4.20% to 100%) and on artificially infected detached pod cortex (92.24 ± 4.53% to 98.75 ± 1.25%), which was not significantly different from the positive control (Ridomil). Furthermore, this combination maintained its effectiveness for up to 9 days at room temperature. These findings suggest that combining plant extracts can enhance their antifungal properties.

Classification of Citrus Plant Diseases Using Deep Transfer Learning

In recent years,the field of deep learning has played an important role towards automatic detection and classification of diseases in vegetables and fruits.This in turn has helped in improving the quality and production of vegetables and fruits.Citrus fruits arewell known for their taste and nutritional values.They are one of the natural and well known sources of vitamin C and planted worldwide.There are several diseases which severely affect the quality and yield of citrus fruits.In this paper,a new deep learning based technique is proposed for citrus disease classification.Two different pre-trained deep learning models have been used in this work.To increase the size of the citrus dataset used in this paper,image augmentation techniques are used.Moreover,to improve the visual quality of images,hybrid contrast stretching has been adopted.In addition,transfer learning is used to retrain the pre-trainedmodels and the feature set is enriched by using feature fusion.The fused feature set is optimized using a meta-heuristic algorithm,the Whale Optimization Algorithm(WOA).The selected features are used for the classification of six different diseases of citrus plants.The proposed technique attains a classification accuracy of 95.7%with superior results when compared with recent techniques.

Plant growth-promoting rhizobacteria(PGPR)and its mechanisms against plant diseases for sustainable agriculture and better productivity

Plant growth-promoting rhizobacteria(PGPR)are specialized bacterial communities inhabiting the root rhizosphere and the secretion of root exudates helps to,regulate the microbial dynamics and their interactions with the plants.These bacteria viz.,Agrobacterium,Arthobacter,Azospirillum,Bacillus,Burkholderia,Flavobacterium,Pseudomonas,Rhizobium,etc.,play important role in plant growth promotion.In addition,such symbiotic associations of PGPRs in the rhizospheric region also confer protection against several diseases caused by bacterial,fungal and viral pathogens.The biocontrol mechanism utilized by PGPR includes direct and indirect mechanisms direct PGPR mechanisms include the production of antibiotic,siderophore,and hydrolytic enzymes,competition for space and nutrients,and quorum sensing whereas,indirect mechanisms include rhizomicrobiome regulation via.secretion of root exudates,phytostimulation through the release of phytohormones viz.,auxin,cytokinin,gibberellic acid,1-aminocyclopropane-1-carboxylate and induction of systemic resistance through expression of antioxidant defense enzymes viz.,phenylalanine ammonia lyase(PAL),peroxidase(PO),polyphenyloxidases(PPO),superoxide dismutase(SOD),chitinase andβ-glucanases.For the suppression of plant diseases potent bio inoculants can be developed by modulating the rhizomicrobiome through rhizospheric engineering.In addition,understandings of different strategies to improve PGPR strains,their competence,colonization efficiency,persistence and its future implications should also be taken into consideration.

Towards Intelligent Detection and Classification of Rice Plant Diseases Based on Leaf Image Dataset

The detection of rice leaf disease is significant because,as an agricultural and rice exporter country,Pakistan needs to advance in production and lower the risk of diseases.In this rapid globalization era,information technology has increased.A sensing system is mandatory to detect rice diseases using Artificial Intelligence(AI).It is being adopted in all medical and plant sciences fields to access and measure the accuracy of results and detection while lowering the risk of diseases.Deep Neural Network(DNN)is a novel technique that will help detect disease present on a rice leave because DNN is also considered a state-of-the-art solution in image detection using sensing nodes.Further in this paper,the adoption of the mixed-method approach Deep Convolutional Neural Network(Deep CNN)has assisted the research in increasing the effectiveness of the proposed method.Deep CNN is used for image recognition and is a class of deep-learning neural networks.CNN is popular and mostly used in the field of image recognition.A dataset of images with three main leaf diseases is selected for training and testing the proposed model.After the image acquisition and preprocessing process,the Deep CNN model was trained to detect and classify three rice diseases(Brown spot,bacterial blight,and blast disease).The proposed model achieved 98.3%accuracy in comparison with similar state-of-the-art techniques.

Expression of Fusion Lytic Peptides Promotes Fungal Disease Resistance in Transgenic Plants

Many organisms produce small proteins which exhibit antimicrobial activities. In recent decades, the biological role of antimicrobial peptides (AMP) has been recognized as the main factor in the defense mechanisms against a broad range of pathogenic microbes. The increased worldwide incidence of microbial resistance to antibiotics makes AMPs promising alternative for the control of microbial disease. Exploring the potential of AMPs in transgenic crops could lead to the development of new and improved cultivars which are resistant to various economically important diseases. In the present study, two fusion lytic peptide gene constructs coding for antimicrobial peptides were expressed in Nicotiana benthamiana tobacco plants and tested against three fungal pathogens, Sclerotinia sclerotiorum, Rhizoctonia solani, and Pythium sp. Detached-leaf bioassay was employed for the transgenic plants carrying the fusion lytic peptide constructs (ORF13 and RSA1), transgenic vector only control plants (1234), and wild-type control plants (WT) against the three fungal pathogens. Symptom area of each leaf was measured with high accuracy and data were recorded and processed by statistical analyses. The results showed that transgenic plant lines ORF13 and RSL1 have substantial resistance to Sclerotinia sclerotiorum infection, producing significantly smaller lesion areas compared to vector only plant line 1234 and wild type plants. These transgenic lines also provided resistance against Rhizoctonia solani, however, these lines were not effective against the other fungal pathogen Pythium sp.

Bioefficacy of indigenous plant products against pests and diseases of Indian forest trees:A review

This review discusses the bioefficacy of natural products（derived from neem and other tropical trees） which have been used against insect pests and diseases attacking forest trees in India.These products are effective,cheaper and eco-friendly and act as antifeedant,repellent,sterility inducing,toxic or regulate insect growth.Integration of these products in forest pest management strategies would enhance the sustainability of forests and prevent the deterioration of wood quality.

Editorial Board of Plant Diseases and Pests

Chief Editor: Lai Zhongxiong, male, born in December 1966, Ph.O., researcher, doctoral supervisor. Deputy dean of New Rural Development Research Institute. Fujian Agricultural and Forestry University: director of Horticultural Plant Bio-engineering Institute (Subtropical Fruit Research Institute): former deputy dean of College of Horticulture (2004- 2016);committee member of textbook construction expert committee, the Ministry of Agriculture (gardening group);ex-ecutive director of Chinese Society for Agricultural Biotechnology, vice chairman of plant tissue culture branch;aca-demic pacesetter of key construction discipline (Pomology) in Fujian Province;head of subtropical fruit trees and spe-cial economic crop germplasm resources sharing platform and fruit tree germplasm test-tube seedling bank of Fujian Province;vice chairman of Fujian Horticultural Society, vice chairman of Fujian Cell Biology Society;editorial board member of Chinese Journal of Tropical Crops, Journal of Forestry and Environment, Journal of Fujian Agriculture and Forestry University, Subtropical Plant Science, Subtropical Agriculture Research, Southeast Horticulture;member of the twelfth CPPCC national committee (agricultural community), member of the standing committee of the tenth and twelfth Fujian CPPCC.

South Asian medicinal plants and chronic kidney disease

Chronic kidney disease remains as one of the serious health issues in South Asia.The paucity of effective pharmacotherapy targeting the management of chronic kidney disease has led to a search for alternative pharmacologic therapies.The traditional knowledge of medicinal plants plays a key role in the discovery of novel nephroprotective agents.This review aims to present the use of such South Asian ethnomedicinal plants that have sufficient therapeutic potency for the management of kidney diseases.Medicinal plants are rich sources of bioactive compounds that have been reported to exert nephroprotective mechanisms,such as antioxidant,anti-inflammation,diuretic,and immunomodulation.Many South Asian medicinal plants have been detailed in traditional medicinal pharmacopoeias for the management of kidney-related diseases.Some have shown promising effects to address nephropathy in animal models and in vitro research.This information can be beneficial in the development of novel pharmaceutical agents targeting the management of kidney diseases and improvement of quality of life for chronic kidney disease patients by fulfilling the requirements for disease management unmet by modern allopathic medicine.