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.

Early detection of pine wilt disease in Pinus tabuliformis in North China using a field portable spectrometer and UAV-based hyperspectral imagery

Background:Pine wilt disease(PWD)is a major ecological concern in China that has caused severe damage to millions of Chinese pines(Pinus tabulaeformis).To control the spread of PWD,it is necessary to develop an effective approach to detect its presence in the early stage of infection.One potential solution is the use of Unmanned Airborne Vehicle(UAV)based hyperspectral images(HIs).UAV-based HIs have high spatial and spectral resolution and can gather data rapidly,potentially enabling the effective monitoring of large forests.Despite this,few studies examine the feasibility of HI data use in assessing the stage and severity of PWD infection in Chinese pine.Method:To fill this gap,we used a Random Forest(RF)algorithm to estimate the stage of PWD infection of trees sampled using UAV-based HI data and ground-based data(data directly collected from trees in the field).We compared relative accuracy of each of these data collection methods.We built our RF model using vegetation indices(VIs),red edge parameters(REPs),moisture indices(MIs),and their combination.Results:We report several key results.For ground data,the model that combined all parameters(OA:80.17%,Kappa:0.73)performed better than VIs(OA:75.21%,Kappa:0.66),REPs(OA:79.34%,Kappa:0.67),and MIs(OA:74.38%,Kappa:0.65)in predicting the PWD stage of individual pine tree infection.REPs had the highest accuracy(OA:80.33%,Kappa:0.58)in distinguishing trees at the early stage of PWD from healthy trees.UAV-based HI data yielded similar results:the model combined VIs,REPs and MIs(OA:74.38%,Kappa:0.66)exhibited the highest accuracy in estimating the PWD stage of sampled trees,and REPs performed best in distinguishing healthy trees from trees at early stage of PWD(OA:71.67%,Kappa:0.40).Conclusion:Overall,our results confirm the validity of using HI data to identify pine trees infected with PWD in its early stage,although its accuracy must be improved before widespread use is practical.We also show UAV-based data PWD classifications are less accurate but comparable to those of ground-based data.We believe that these results can be used to improve preventative measures in the control of PWD.

Pine wilt disease: a short review of worldwide research

This article summarizes the results of the research papers presented at the International Symposium on pine wilt disease （IUFRO Working Party Meeting 4.04.03） held in July 2009, at Nanjing, China. The general topics covered were on pine wilt disease （PWD）, its causal organism, the pinewood nematode （PWN） Bursaphelenchus xylophilus, plus other PWN-associated microorganisms that play a significant role in PWD such as bacteria （e.g. Pseudomonasfluorescens）. Most of the papers that are reviewed are based on work on PWD-PWN in East Asia and Russia. Specific topics covered include： 1） the fundamental conceptions of PWD development, 2） pathogenicity, 3） host-parasite relationships including the histopathology of diseased conifers and the role of toxins from bacteria-nematode ecto-symbionts, 4） PWN life cycle and transmission, 5） B. xylophilus dissemination models, 6） associations （with other nematodes）, 7） diagnostics, 8） quarantine and control of the PWN and 9） biocontrol of the PWN.

Biological Characteristics of 11 Wilt Disease Pathogens on Hybrid Bamboo

[Objective] The biological characteristics of 11 wilt disease pathogens on hybrid bamboo were studied. [Method] 11 F. oxysporum strains of hybrid bamboo were isolated from diseased bamboo tissue in the bamboo base of Guangxi Huajing Bamboo Development Co., Ltd.. Biological characteristics of these pathogens were studied. [ Result] The optimum growth medium and light conditions for 11 strains were different, the optimum growth temperature was 24 -28 ℃, the optimum pH value was 7.0 - 11.0, lactose and D-sorbitol were the best carbon sources, and yeast extract was the best nitrogen source. The optimum temperature for oonidia germination was about 24 -30 ℃3, the best carbon source were maltose, lactose and sucrose, the best nitrogen source was yeast extract and beef extract. The lethal temperature of conidia was 50 ℃ （10 min）. [ Cendusioal The study supplied good theoretical basis for the control of Fusarium wilt disease in hybdd bamboo.

Detection of the Pine Wilt Disease Tree Candidates for Drone Remote Sensing Using Artificial Intelligence Techniques

Pine wilt disease(PWD)has recently caused substantial pine tree losses in Republic of Korea.PWD is considered a severe problem due to the importance of pine trees to Korean people,so this problem must be handled appropriately.Previously,we examined the history of PWD and found that it had already spread to some regions of Republic of Korea;these became our study area.Early detection of PWD is required.We used drone remote sensing techniques to detect trees with similar symptoms to trees infected with PWD.Drone remote sensing was employed because it yields high-quality images and can easily reach the locations of pine trees.To differentiate healthy pine trees from those with PWD,we produced a land cover(LC)map from drone images collected from the villages of Anbi and Wonchang by classifying them using two classifier methods,i.e.,artificial neural network(ANN)and support vector machine(SVM).Furthermore,compared the accuracy of two types of Global Positioning System(GPS)data,collected using drone and hand-held devices,for identifying the locations of trees with PWD.We then divided the drone images into six LC classes for each study area and found that the SVM was more accurate than the ANN at classifying trees with PWD.In Anbi,the SVM had an overall accuracy of 94.13%,which is 6.7%higher than the overall accuracy of the ANN,which was 87.43%.We obtained similar results in Wonchang,for which the accuracy of the SVM and ANN was 86.59%and 79.33%,respectively.In terms of the GPS data,we used two type of hand-held GPS device.GPS device 1 is corrected by referring to the benchmarks sited on both locations,while the GPS device 2 is uncorrected device which used the default setting of the GPS only.The data collected from hand-held GPS device 1 was better than those collected using hand-held GPS device 2 in Wonchang.However,in Anbi,we obtained better results from GPS device 2 than from GPS device 1.In Anbi,the error in the data from GPS device 1 was 7.08 m,while that of the GPS device 2 data was 0.14 m.In conclusion,both classifiers can distinguish between healthy trees and those with PWD based on LC data.LC data can also be used for other types of classification.There were some differences between the hand-held and drone GPS datasets from both areas.

Pine wilt disease detection in high-resolution UAV images using object-oriented classification

Pine wilt disease(PWD)is currently one of the main causes of large-scale forest destruction.To control the spread of PWD,it is essential to detect affected pine trees quickly.This study investigated the feasibility of using the object-oriented multi-scale segmentation algorithm to identify trees discolored by PWD.We used an unmanned aerial vehicle(UAV)platform equipped with an RGB digital camera to obtain high spatial resolution images,and multiscale segmentation was applied to delineate the tree crown,coupling the use of object-oriented classification to classify trees discolored by PWD.Then,the optimal segmentation scale was implemented using the estimation of scale parameter(ESP2)plug-in.The feature space of the segmentation results was optimized,and appropriate features were selected for classification.The results showed that the optimal scale,shape,and compactness values of the tree crown segmentation algorithm were 56,0.5,and 0.8,respectively.The producer’s accuracy(PA),user’s accuracy(UA),and F1 score were 0.722,0.605,and 0.658,respectively.There were no significant classification errors in the final classification results,and the low accuracy was attributed to the low number of objects count caused by incorrect segmentation.The multi-scale segmentation and object-oriented classification method could accurately identify trees discolored by PWD with a straightforward and rapid processing.This study provides a technical method for monitoring the occurrence of PWD and identifying the discolored trees of disease using UAV-based high-resolution images.

Theory and Practice of Controlling and Extinguishing Pine Wilt Disease

[Objective] This study was aimed to review the controlling experience of pine wilt disease in the past 25 years, explore the theories and methods of controlling pine wilt disease, and improve the scientific level of controlling techniques and the protection capacity of healthy pine trees. [Method] Eleven items of effects were used to refine the theory of clearing dead pine trees affected by pine wilt disease, namely, ＂1 priority＂, ＂2 objections＂, ＂3 principles＂, ＂4 measures＂, and ＂5 manage- ments＂. On the basis of comprehensive control and complete removal of the infect- ed pine trees, a variety of comprehensive and efficient controlling methods were developed to carry out targeted chemical ecology trapping, bionic pesticide killing and releasing natural enemies of Sclerodermus guani, Dastarcus helophoroides. High ef- ficient emamectin benzoate immune injection was developed to inject the healthy pine trees for prevention, so as to extinguish the pine wilt disease. [Result] The pine wilt disease dropped from the peak of 3.5 million dead trees with an infecting area of 28 273 hectares in 1999 to 0.068 million with an area of 4 333 hectares in 2012 gradually, reducing by 98.06% in number and 84.84% in area, respectively. On the basis of removal, Dastarcus helophoroides was also released, which could make the number of dead pines decrease more significantly than the control, and af- ter releasing for 5 consecutive years, the dead pine trees dropped to 0.511 plant/hm2 in 2012, with a mortality rate of 0.022 7%, which achieved the control effect, reaching extremely significant level. ＂Forest land removal＋infected trees isolation＋natural enemy release＂ could extinguish the pine wilt disease. The test of isolating 24 heaps of infected pine trees showed that there were 9 heaps of pine trees extinguished the pine wilt disease, which controlled the occurrence of pine wilt disease for 100%, accounting for 37.5% of the total, in which the number of those isolated using iron netting and nylon net were 4 for each, accounting for 88.9%, and there was one heap using polypropylene net, accounting for 11.1%. The invention of em- amectin benzoate immune injection laid the foundation for extinguishing pine wilt disease. The follow checking of the effects of emamectin benzoate immune injection on pine wilt disease found that the number of dead trees caused by pine wilt dis- ease decreased significantly after injecting, and became very small in October of the next year, and the disease was completely extinguished in the third year. [Conclusionl Pine wilt disease could be controlled and extinguished with positive control by using ＂comprehensive cleaning＋industrialized removal＂, ＂comprehensive cleaning＋ natural enemy release＂, ＂comprehensive cleaning＋infected trees isolation＋natural ene- my release＂ and ＂comprehensive cleaning＋emamectin benzoate immune＂.

Surveillance of pine wilt disease by high resolution satellite

Pine wilt disease caused by the pinewood nematode Bursaphelenchus xylophilus has led to the death of a large number of pine trees in China.This destructive disease has the characteristics of bring wide-spread,fast onset,and long incubation time.Most importantly,in China,the fatality rate in pines is as high as 100%.The key to reducing this mortality is how to quickly find the infected trees.We proposed a method of automatically identifying infected trees by a convolution neural network and bounding box tool.This method rapidly locates the infected area by classifying and recognizing remote sensing images obtained by high resolution earth observation Satellite.The recognition accuracy of the test data set was 99.4%,and the remote sensing image combined with convolution neural network algorithm can identify and determine the distribution of the infected trees.It can provide strong technical support for the prevention and control of pine wilt disease.

Early Monitoring of Pine Wilt Disease in Pinus massioniana based on Hyperspectral Data

We selected healthy Pinus massioniana for pine wood nematode inoculation experiments to get the spectral reflectance of healthy and infected Pinus mas- sioniana in different infection stages via a ground spectrometer （ wavelength in 350 - 2 500 nm）, and analyzed the changes in chlorophyll content at various periods. The original spectral reflectance of healthy and infected P. massoniana was significantly different in the middle and late infection stages, and the reflection peak and absorption valley in visible light region and near infrared region gradually weakened and even disappeared to a straight line. There was significant correlation rela- tionship between chlorophyll content of infected plants and spectral reflectance at the wavelength of 1 405 nm, and the quantitative inversion model of chlorophyll content was correspondingly established as follows： Car = - 1.74（X1~ ）2 ＋ 4. 72X1,~ - 0. 76. Through first-order derivative spectra at the wavelength of 593 nm, combined with quantitative inversion of the corresponding chlorophyll content, we can discriminate whether P. massoniana is infected by pine lt disease or not, especially in the early stages before disease features are visible to the naked eyes it has a good quantitative monitoring effect.

Studies on Cotton Breeding Resistant to Fusarium and Verticillium wilt Diseases

Both Fusarium and Verticillium wilts are important soil-borne diseases,which can not be effectively controlled by chemical fungicides.The two diseases,especially Verticillium wilt,have

Identification of A Strain HN-1 against Banana Wilt Disease and Determination of Its Antagonism

[Objective] The paper was to identify strain HN-1 against banana wilt disease and to determine its antagonism. [Method] The strain HN-1 was ob- tained from the soil in fields heavily infected by Fusarium oxysporum f. sp. cubense （FOC）. Antagonism of the strain against F. oxysporum was tested via dual-cul- ture and inhibition test on spore germination. [Result] HN-1 effectively inhibited mycelial growth and spore germination of F. oxysporum, Strain HN-1 was identi- fied as BrevibaciUus brevis according to its characteristics in morphology, physiology and biochemistry and its 16S rDNA sequence. The strain showed high inhibition effect on 15 species of fungal pathogens in the dual-culture trials with fungal pathogens. [ Conclusion] The study provides theoretical basis for application of strain HN-1 in agricultural fields.

Occurrence and Effects of Pineapple Mealybug Wilt Disease in Central Uganda

Pineapple mealybug wilt disease （PMWD） is one of the latest outbreaks of diseases attacking pineapple in Uganda. However, its occurrence and effects have not been documented and quantified, yet the disease poses a serious threat to the pineapple industry. Therefore, the objective of this study was to assess the occurrence and effects of PMWD on pineapple in central Uganda. Semi-structured questionnaire was used to solicit information from 82 respondents consisting of farmers, opinion leaders, key informants, political and technical leadership during May 2011. PMWD was observed in all the fields surveyed but with varying incidences and severities. In addition, PMWD was more common during the dry seasons than the rainy seasons where higher incidences were associated with high mealybug populations. PMWD manifested as a syndrome characterized by yellowing of leaves, stunting, wilting and rotting of roots. The effects of PMWD were variable but yield reductions and low plant populations were widely reported. Although, the occurrence of PMWD was reported to the different level of authority in the districts, very little was done to curb its spread.

Vegetative Growth and Molecular Identification of Fusarium equiseti Isolated from Wilt Disease of Centella asiatica L. in Bangladesh

Centella asiatica (L.) is commonly known as Thankuni plant and has ethnobotanical importance in Bangladesh. Present experiment was conceded to investigate the wilt disease of C. asiatica, vegetative growth and molecular characterization of pathogenic fungi. Pathogenic fungus, Fusarium equiseti was identified as a causal agent of wilt disease in C. asiatica. The effect of culture media on the mycelial growth of F. equiseti showed the highest (89.25 mm) on potato dextrose agar (PDA) medium followed by carrot agar (CA) medium and the lowest growth (40.25 mm) was measured in HA medium. The optimal temperature and pH for mycelial growth of F. equiseti were 30°C and 7, respectively. The genetic variation of the selected species of fungi, the internal transcribed spacer (ITS) region was amplified using ITS4 and ITS5 primers and sequenced. The PCR product of the ITS region of F. equiseti was 535 bp. Phylogenetic tree of thirty-seven strains of Fusarium sp. based on the nucleotide sequences of the ITS region using the neighbor-joining method with 1000 bootstrapping indicated that 98% - 100% identity with MN886590.1 JUF0046 (F. equiseti). ITS sequences are generally constant, or show little variation within species, but vary between species in a genus. The ITS region is relatively short and can be easily amplified by PCR using universal single primer pairs. Genetic distance exhibited high level of similarity with identical ITS sequences. To date, no published research articles are found on the molecular identification of F. equiseti, the causal agent of fusarium wilt disease of C. asiatica in Bangladesh.

Pulse Roguing Strategy in a Pine Wilt Disease Epidemic Model with General Nonlinear Incidence Rate

In this study, we investigate a pine wilt transmission model with general nonlinear incidence rates and time-varying pulse roguing. Using the stroboscopic map and comparison theorem, we proved that the disease-free equilibrium is global attractive determined by the basic reproduction number R1 < 1, and in such a case, the endemic equilibrium does not exist. The disease uniformly persists only if R2 > 1.

Introduction of Bottle Gourd DNA into Watermelon by Soaking Embryo for Resistance to Wilt Disease

In order to utilize wilt disease resistance of bottle gourd,total DNA of bottle gourd was introduced into watermelon through the method of aoeking embryo.The DNA-introduced variant were cultured in contaminated soil to elect the wilt disease resistance for more than 3 genera- tions.2 high-resistant and 2 middle-resistant watermelon materials were obtained.

Fusarium wilt of banana:Current update and sustainable disease control using classical and essential oils approaches

Fusarium species were reported to produce biofilms.Biofilms are superficial societies of microbes bounded and endangered by being situated or taking place outside a cell or cells.The most destructive fungal diseases caused by phytopathogens are as a result of biofilms formation.Fusarium wilt of banana(Panama disease)is caused by a soil-borne pathogen called Fusarium oxysporum f.sp.cubense.Fusarium oxysporum occurs in a form of a species complex(FOSC)which encompasses a crowd of strains.Horizontal genetic factor transfer may donate to the observed assortment in pathogenic strains,while sexual reproduction is unknown in the FOSC.Fusarium wilt is a notorious disease on several crops worldwide.Yield loss caused by this pathogen is huge,and significant to destroy crop yields annually,thereby affecting the producer countries in various continents of the world.The disease is also resistant to various synthetic chemical fungicides.However,excessive use of synthetic fungicides during disease control could be lethal to humans,animals,and plants.This calls for alternative eco-friendly management of this disease by targeting the biofilms formation and finally suppressing this devastating phytopathogen.In this review,we,therefore,described the damage caused by Fusarium wilt disease,the concept of filamentous fungal biofilms,classical control strategies,sustainable disease control strategies using essential oils,and prevention and control of vegetables Fusarium wilt diseases.

Pine wilt disease in Yunnan, China： Evidence of non-local pine sawyer Monochamus alternatus （Coleoptera： Cerambycidae） populations revealed by mitochondrial DNA

Monochamus alternatus （Hope） specimens were collected from nine geographical populations in China, where the pinewood nematode Bursaphelenchus xylophilus （Steiner et Buhrer） was present. There were seven populations in southwestern China in Yunnan Province （Ruili, Wanding, Lianghe, Pu＇er, Huaning, Stone Forest and Yongsheng）, one in central China in Hubei Province （Wuhan）, and one in eastern China in Zhejiang Province （Hangzhou）. Twenty-two polymorphic sites were recognized and 18 haplotypes were established by analyzing a 565 bp gene fragment of mitochondrial cytochrome oxidase subunit II （CO II）. Kimura two-parameter distances demonstrated that M. alternatus populations in Ruili, Wanding and Lianghe （in southwestern Yunnan） differed from the other four Yunnan populations but were similar to the Zhejiang population. No close relationship was found between the M. alternatus populations in Yunnan and Hubei. Phylogenetic reconstruction established a neighbor-joining （N J） tree, which divided haplotypes of southwestern Yunnan and the rest of Yunnan into different clades with considerable bootstrapping values. Analysis of molecular variance and spatial analysis of molecular variance also suggested significant genetic differentiation between M. alternatus populations in southwestern Yunnan and the rest of Yunnan. Our research suggests that non-local populations of M. alternates, possibly from eastern China, have become established in southwestern Yunnan. Key words mitochondrial DNA, non-local vector, pine wilt disease

The relative importance of soil moisture in predicting bacterial wilt disease occurrence

Soil-borne plant diseases cause major economic losses globally.This is partly because their epidemiology is difficult to predict in agricultural fields,where multiple environmental factors could determine disease outcomes.Here we used a combination of field sampling and direct experimentation to identify key abiotic and biotic soil properties that can predict the occurrence of bacterial wilt caused by pathogenic Ralstonia solanacearum.By analyzing 139 tomato rhizosphere soils samples isolated from six provinces in China,we first show a clear link between soil properties,pathogen density and plant health.Specifically,disease outcomes were positively associated with soil moisture,bacterial abundance and bacterial community composition.Based on soil properties alone,random forest machine learning algorithm could predict disease outcomes correctly in 75%of cases with soil moisture being the most significant predictor.The importance of soil moisture was validated causally in a controlled greenhouse experiment,where the highest disease incidence was observed at 60%of maximum water holding capacity.Together,our results show that local soil properties can predict disease occurrence across a wider agricultural landscape,and that management of soil moisture could potentially offer a straightforward method for reducing crop losses to R.solanacearum.

Mathematical modeling approach to the transmission dynamics of pine wilt disease with saturated incidence rate

The present paper investigates the dynamics of pine wilt disease with saturated incidence rate. The proposed model is stable both locally and globally. The local stability of the disease-free equilibrium is determined by the basic reproduction R0. The disease-free equilibrium is stable locally and globally whenever R0〈 1. If R0 〉 1, then the endemic state is stable both locally and globally. Further, a brief discussion with conclusion on the numerical results of the proposed model is presented.

Chitosan Oligosaccharide Induces Plant Resistance Gene Expression in Pinus massoniana

Chitosan oligosaccharides(COSs)are the main degradation products from chitosan or chitin and have been reported to induce resistance to diseases in herbaceous plants like cucumber and Arabidopsis.Concomitantly,pine wilt disease(PWD)is a devastating disease of conifer tree species.Here,we hypothesized that COSs induce plant resistance gene(PRG)expression in the woody plant Masson pine,Pinus massoniana.COSs were inoculated into P.massoniana seedlings and the BGISEQ-500 platform was used to generate transcriptomes from COSs-treated P.massoniana and control seedlings.A total of 501 differentially expressed genes(DEGs)were identified by comparing the treatment and control groups.A total of 251(50.1%)DEGs were up-regulated in the treatment relative to the control seedlings and 250(49.9%)were down-regulated.Inoculation of COSs induced the expression of 31 PRGs in P.massoniana seedlings and the relative expression levels of six of the PRGs were verified by RT-qPCR.This is the first study to demonstrate that COS induces the expression of PRGs in a tree species.These results provide important insights into the function of COSs and further the prospects of developing a COS-based immune inducer for controlling PWD.