scholarly journals First report of Stemphylium lycopersici causing leaf spot on Polygonatum kingianum in China

Plant Disease ◽  
2021 ◽  
Author(s):  
Jianxin Chen ◽  
Yuqian Wei ◽  
Zejia Lv ◽  
Qingli Han ◽  
Yuan Zheng ◽  
...  

Polygonatum kingianum, a member of the Liliaceae, is valued in traditional medicine and as a vegetable food crop. In July 2019, more than 50% of P. kingianum growth was suppressed in several field nurseries in Simao, Mojiang, Jingdong and Lancang County, Puer City, China. At the early stage of infection, symptoms manifested as a small circular brown spot. As the lesion matured, the spot gradually enlarged, forming an oval to irregular lesion with reddish-brown and dark green borders. In serious cases, the leaves were withered, and became brittle with cracks. The infected plants were collected from six major fields. The tissues of diseased leaves were soaked in 75% ethanol for 10 s, 0.1% mercuric chloride for 2 min, rinsed with sterilized water, and placed on potato dextrose agar (PDA) at 25℃ for 7 days. On PDA, four strains were isolated, and the colony was gray to dark yellowish-brown, flocculent, regular with concentric growth rings. Strain PKLS06 produced a dark red to brown pigment in the agar medium. On lesions, the conidiophores were solitary or in fascicles, straight or slightly curved, brown, with a conical apex, with three to five septa. The conidiogenous cells were pale-brown and swollen at the apex. On PDA, spores were solitary, oblong, bluntly rounded or sometimes with a point at the apex, with two to five transverse septa and one to two longitudinal septa with contractions at the main transverse septum. Morphological characteristics were consistent with published descriptions of Stemphylium lycopersici (Kee et al. 2017; Xie et al. 2018). For molecular identification, rDNA internal transcribed spacer (ITS) and the glyceraldehyde-3-phosphate dehydrogenase (gpd) gene were amplified and sequenced (ITS accessions: MW243098, MW243099, MW243100, MW243101; gpd accessions: MW246803, MW246804, MW246805, MW246806) using published primers (White et al. 1990; Câmara et al. 2002). A phylogenetic tree was developed by Maximum Parsimony (MP), Maximum Likelihood (ML) and Bayesian inference (BI). These four isolates fall into the S. lycopersici clade with strong support and all isolates were distinguished clearly from other species. Pathogenicity tests were performed using these four isolates. Each isolate was cultured on PDA and shake-cultured in V-8 juice broth (Nasehi et al. 2014). Conidia were resuspended in sterilized water (1×106 conidia/mL) and inoculated on intact leaves with injury of 1-year-old P. kingianum. The plants were incubated at 25℃ with a 12 h photoperiod and 90% humidity. A small spot began to appear after 3 days, and symptoms were similar to the those observed in the nursery after 10 days. Interestingly, the pathogenicity of strain PKLS06 was relatively weaker. Control plants treated with sterile water showed no disease symptoms. Re-isolated strains had the same morphological characteristics and the same ITS and gpd sequences as the original isolates, thus fulfilling Koch’s postulates. S. lycopersici, an important pathogen, is widely distributed, and can cause a variety of plant diseases. It is noteworthy that the disease was observed on a plant in the Liliaceae, expanding the host range of S. lycopersici, which previously was reported to primarily infect plants in the Solanaceae. Based on the results presented above, P. kingianum is a new host plant of S. lycopersici in China. This disease is a threat for nursery production of P. kingianum, leading to a reduction in yields and economic losses. References Kee, Y. J., et al. 2017. Plant Disease 102 (2): 445–446 Xie, X. W., et al. 2019. Canadian Journal of Plant Pathology-Revue Canadienne De Phytopathologie 41 (1): 124–128 White, T. J., et al. 1990. PCR Protocols: A Guide to Methods and Applications PCR Protocols: A Guide to Methods and Applications 18: 315–322 Câmara M. P. S., et al. 2002. Mycologia 94 (4): 660–672 Nasehi A., et al. 2014. Archives of Phytopathology & Plant Protection, 47 (14): 1658-1665.

2020 ◽  
Vol 8 (10) ◽  
pp. 1463
Author(s):  
Ivana Pajčin ◽  
Vanja Vlajkov ◽  
Marcus Frohme ◽  
Sergii Grebinyk ◽  
Mila Grahovac ◽  
...  

Pepper bacterial spot is one of the most severe plant diseases in terms of infection persistence and economic losses when it comes to fresh pepper fruits used in nutrition and industrial processing. In this study, Bacillus velezensis IP22 isolated from fresh cheese was used as a biocontrol agent of pepper bacterial spot, whose main causal agent is the cosmopolitan pathogen Xanthomonas euvesicatoria. After optimization of the cultivation medium composition aimed at maximizing of the antimicrobial activity against X. euvesicatoria and validation of the optimized medium at the scale of a laboratory bioreactor, in planta tests were performed. The results have showed significant suppression of bacterial spot symptoms in pepper plants by the produced biocontrol agent, as well as reduction of disease spreading on the healthy (uninoculated) pepper leaves. Furthermore, HPLC-MS (high pressure liquid chromatography–mass spectrometry) analysis was employed to examine antimicrobial metabolites produced by B. velezensis IP22, where lipopeptides were found with similar m/z values compared to lipopeptides from fengycin and locillomycin families. The bioprocess solution developed at the laboratory scale investigated in this study represents a promising strategy for production of pepper bacterial spot biocontrol agent based on B. velezensis IP22, a food isolate with a great perspective for application in plant protection.


Plant Disease ◽  
2021 ◽  
Author(s):  
HaiYan Ben ◽  
JianFei Huo ◽  
YuRong Yao ◽  
Wei Gao ◽  
WanLi Wang ◽  
...  

Watermelon (Citrullus lanatus) is an important cucurbit crop in China. During September 2020, an unknown leaf spot disease was observed on watermelon in two greenhouses (640m2 per greenhouse) of Sangzi town, Jizhou district, in Tianjin, China (117°10’E, 39°55’N), where approximately 10% of plants were infected. Disease symptoms began as small, circular, brown spots on leaves. As these spots increased in size, they developed confluent, irregular lesions surrounded by dark brown edges. Severely affected plants had many wilted leaves followed by defoliation. Ten symptomatic leaves were collected for pathogen isolation. Diseased tissues (3×3 mm) were cut from the margins of lesions and surface disinfected with 1% NaClO for 1 min, rinsed three times with sterile distilled water and then placed on potato dextrose agar (PDA) at 25±2°C with a 12-h photoperiod for 7 to 10 days. Seven morphologically similar isolates were obtained from the ten infected leaves and purified by single-spore culturing for further study. The initial growth of the isolates on PDA appeared grayish white in obverse and bright yellow pigmentation in reverse. Colony color gradually deepened to grayish brown in obverse and brownish red in reverse. Conidia (n=50) were solitary, light brown, oblong to long elliptic, pointed or obtusely rounded at the top, constricted at the transverse septum, with verrucous processes on the surface, 36.3 to 64.2×16.6 to 25.1 μm, and the L/W ratio of conidia was 1.5–2.5. All characteristics were consistent with the description of Stemphylium lycopersici (Ellis 1971; Woudenberg et al. 2017). Total genomic DNA was extracted from a representative isolate (XG2-2) using a Fungal DNA Kit (GBCBIO, Guangzhou, China). The internal transcribed spacer (ITS) and translation elongation factor 1-α (EF1-α) genes (Sun et al. 2015) were amplified and sequenced with the primer pairs ITS1/ITS4 (5'-TCCGTAGGTGAACCTGCGG-3'/5'-TCCTCCGCTTATTGATATGC-3') and EF-1α-F/EF-1α-R(5'-TCACTTGATCTACAAGTGCGGTGG-3'/5'-CGATCTTGTAGACATCCTGGAGG-3'), respectively. The two sequences of strain XG2-2 (GenBank Accession No. MW362344 and MW664941) showed 100% and 99% identity to S. lycopersici strain 01 and strain KuNBY1 (GenBank Accession No. KR911814 and AB828256) respectively. The phylogenetic analysis using MEGA7 based on the sequences of ITS and EF1-α regions showed that the isolate XG2-2 was clustered with S. lycopersici isolates (strain 01 and strain KuNBY1). For the pathogenicity test, a spore suspension (1×106 spores/ml) in sterile distilled water from a 7-day-old culture of the fungus grown on PDA and counted with a hemacytometer was sprayed on leaves and stems of five healthy watermelon plants, grown for 2 months in the greenhouse at 25 to 30 °C, with 85% relative humidity. Conditions remained the same for inoculation experiments. Negative controls were healthy plants inoculated with sterile distilled water. The experiment was repeated twice. Six days after inoculation, typical leaf spot symptoms were observed on inoculated leaves, whereas control leaves remained symptomless. To satisfy Koch's postulates, the causal fungus was re-isolated from the lesions of inoculated plants, with morphological and cultural characteristics identical with the original isolate. Stemphylium lycopersici is a common fungus with a relatively extensive host range (Kee et al. 2018). In recent years, new host plants infected by S. lycopersici have been reported in Asia including Physali (Yange et al. 2020), common bean (Li et al. 2019), and potato (Kee et al. 2018). To our knowledge, this is a new host record for S. lycopersici causing leaf spot on watermelon in China. Sangzi watermelon is a special local product in the Jizhou district of Tianjin. At present the cultivated area in 1000 ha including 667 ha in controlled conditions and 333 ha of field-grown plants with a total annual output of 45000 Mg. In this survey, we found the disease caused by S. lycopersici on watermelon only in these two greenhouses, but cannot rule out the possibility of large-scale spread in the future. Therefore, integrated management strategies for this fungus need to be developed to reduce economic losses in commercial cultivation.


2006 ◽  
Vol 59 ◽  
pp. 132-136 ◽  
Author(s):  
M. Braithwaite ◽  
C.F. Hill ◽  
S. Ganev ◽  
J.M. Pay ◽  
H.G. Pearson ◽  
...  

During 2003 and 2004 fortyfive randomly selected wholesale and retail plant nurseries were surveyed for plant diseases The plant families Agavaceae Annonaceae Arecaceae Bromeliaceae Cycadaceae and Musaceae were targeted Plants were examined in situ for disease symptoms as well as samples being collected for laboratory analyses Fungi were identified using morphological characteristics and where necessary with molecular techniques The survey resulted in a range of fungi being identified from the target plants These fungi ranged from saprophytes to plant pathogens some of which may have undesirable effects on New Zealands biodiversity or economy Many new host/pathogen records were observed and several fungi were detected for the first time in New Zealand This paper presents and discusses the results of these findings


EDIS ◽  
2006 ◽  
Vol 2006 (7) ◽  
Author(s):  
Kuang-Ren Chung ◽  
Ronald H. Brlansky

Citrus is susceptible to a large number of diseases caused by plant pathogens. Economic losses due to plant diseases can be severe, but fortunately, not all pathogens attacking citrus are present in Florida. Major citrus diseases currently present in Florida include: Alternaria brown spot, blight, citrus canker, greasy spot, melanose, Phytophthora-induced diseases (foot and root rot, brown rot), postbloom fruit drop (PFD), scab, and tristeza. An exotic, destructive disease called citrus greening (Huanglongbing) has recently been found in Florida. Any exotic diseases, if introduced, will increase production costs and decrease profitability for Florida growers. Exotic diseases affect the viability of the industry or the varieties that could be profitably grown. Background information for each exotic citrus disease will be presented in a series of fact sheets to: 1) provide a basis for evaluating exotic pathogens that may pose potential risks to Florida citrus; and 2) create a decision-making framework to prevent their introduction and spread. This paper will discuss Citrus tristeza virus-Stem Pitting (CTV-SP) disease. This article is written based on the materials used for the Workshops of the Exotic Citrus Pathogen Threat Project led by Drs. S. M. Garnsey and H. W. Browning, and approved for publication.


Plant Disease ◽  
2000 ◽  
Vol 84 (9) ◽  
pp. 1044-1044 ◽  
Author(s):  
A. Vicent ◽  
J. Armengol ◽  
R. Sales ◽  
J. García-Jiménez ◽  
F. Alfaro-Lassala

In 1998, a new disease of Fortune mandarin trees was detected in orchards in the eastern province of Valencia. This is one of the most important late-maturing cultivars grown in Spain. Symptoms were typical of Alternaria brown spot of citrus (2). Young leaves showed brown necrotic and irregular blighted areas with characteristic yellow halos. The necrosis had a tendency to follow the veins. On fruits, symptoms included light brown, slightly depressed spots to circular and dark brown areas on the external surface. Infected young fruits and leaves often fell and the mature fruits were unmarketable due to lesions, resulting in important economic losses. Isolations on potato dextrose agar supplemented with 0.5 mg/ml of streptomycin sulfate (PDAS) from affected leaves and fruits consistently yielded Alternaria alternata (Fr.:Fr.) Keissl., which was identified based on conidial morphological characteristics. Pathogenicity tests were conducted using 15 isolates from fruit and leaves by inoculating detached immature Fortune leaves with a sterile water suspension of 5 × 105 conidia per ml. Drops of this suspension (40 μl each) were placed on the lower surfaces of each leaflet using four leaves per isolate. Leaves were incubated in a moist chamber in the dark at 27°C (1). After 48 h, most of these isolates caused necrotic lesions on the leaves similar to those observed in the field, and the fungus was reisolated, confirming Koch's postulates. In 1999, the fungus spread to other citrus-growing areas, and to date the disease has been detected affecting Fortune and Nova mandarins and Minneola tangelo. This is the first report of Alternaria brown spot of citrus in Spain. References: (1) K. Kohmoto et al. Phytopathology 81:719, 1991. (2) J. O. Whiteside. Plant Dis. Rep. 60:326, 1976.


2021 ◽  
Vol 12 ◽  
Author(s):  
Anna C. Hampf ◽  
Claas Nendel ◽  
Simone Strey ◽  
Robert Strey

Pathogens and animal pests (P&A) are a major threat to global food security as they directly affect the quantity and quality of food. The Southern Amazon, Brazil’s largest domestic region for soybean, maize and cotton production, is particularly vulnerable to the outbreak of P&A due to its (sub)tropical climate and intensive farming systems. However, little is known about the spatial distribution of P&A and the related yield losses. Machine learning approaches for the automated recognition of plant diseases can help to overcome this research gap. The main objectives of this study are to (1) evaluate the performance of Convolutional Neural Networks (ConvNets) in classifying P&A, (2) map the spatial distribution of P&A in the Southern Amazon, and (3) quantify perceived yield and economic losses for the main soybean and maize P&A. The objectives were addressed by making use of data collected with the smartphone application Plantix. The core of the app’s functioning is the automated recognition of plant diseases via ConvNets. Data on expected yield losses were gathered through a short survey included in an “expert” version of the application, which was distributed among agronomists. Between 2016 and 2020, Plantix users collected approximately 78,000 georeferenced P&A images in the Southern Amazon. The study results indicate a high performance of the trained ConvNets in classifying 420 different crop-disease combinations. Spatial distribution maps and expert-based yield loss estimates indicate that maize rust, bacterial stalk rot and the fall armyworm are among the most severe maize P&A, whereas soybean is mainly affected by P&A like anthracnose, downy mildew, frogeye leaf spot, stink bugs and brown spot. Perceived soybean and maize yield losses amount to 12 and 16%, respectively, resulting in annual yield losses of approximately 3.75 million tonnes for each crop and economic losses of US$2 billion for both crops together. The high level of accuracy of the trained ConvNets, when paired with widespread use from following a citizen-science approach, results in a data source that will shed new light on yield loss estimates, e.g., for the analysis of yield gaps and the development of measures to minimise them.


Biologija ◽  
2017 ◽  
Vol 62 (4) ◽  
Author(s):  
Kristina Raitelaitytė ◽  
Arvydas Rutkauskas ◽  
Jana Radzijevskaja ◽  
Judita Žukauskienė ◽  
Svetlana Markovskaja ◽  
...  

Fungal infections are the main cause of emerging infectious diseases in forest trees. Over the past decades, the number of invasive fungal pathogens in Europe has increased exponentially. In this paper the  fungal pathogens causing the  most common diseases in pines like Dothistroma needle blight, brown spot needle blight, Lophodermium needle cast, Scots pine blister rust, Scleroderris canker, and Pitch canker were analyzed. These diseases cause defoliation, increase susceptibility of plants to other diseases and pests, and tree mortality can also occur. As a result, the forest industry is suffering severe economic losses. The fungi species causing infection in forest trees have been described as serious pathogens across the  world including Europe, confirming a  fast spread of their ranges. Knowledge of pathogens distribution, life cycle and disease symptoms are essential for the diagnostic and control of pathogenic fungi. Human-driven species expansion has increased in the last century due to the growth of international travel and trade, resulting in huge disturbance to ecosystems. Most of the plant diseases are strongly influenced by environmental conditions. Climate change has important consequences on plants, pathogens, and the interaction between them, resulting in changes on diseases epidemics. Fungal infections of plants are difficult to control because pathogens populations are variable in time, space, and genotypes. The potential damage in the future may be large, and that is why we have to be aware of the problems and discuss some possible approaches to reducing the threats.


Sensors ◽  
2021 ◽  
Vol 21 (11) ◽  
pp. 3830
Author(s):  
Ahmad Almadhor ◽  
Hafiz Tayyab Rauf ◽  
Muhammad Ikram Ullah Lali ◽  
Robertas Damaševičius ◽  
Bader Alouffi ◽  
...  

Plant diseases can cause a considerable reduction in the quality and number of agricultural products. Guava, well known to be the tropics’ apple, is one significant fruit cultivated in tropical regions. It is attacked by 177 pathogens, including 167 fungal and others such as bacterial, algal, and nematodes. In addition, postharvest diseases may cause crucial production loss. Due to minor variations in various guava disease symptoms, an expert opinion is required for disease analysis. Improper diagnosis may cause economic losses to farmers’ improper use of pesticides. Automatic detection of diseases in plants once they emerge on the plants’ leaves and fruit is required to maintain high crop fields. In this paper, an artificial intelligence (AI) driven framework is presented to detect and classify the most common guava plant diseases. The proposed framework employs the ΔE color difference image segmentation to segregate the areas infected by the disease. Furthermore, color (RGB, HSV) histogram and textural (LBP) features are applied to extract rich, informative feature vectors. The combination of color and textural features are used to identify and attain similar outcomes compared to individual channels, while disease recognition is performed by employing advanced machine-learning classifiers (Fine KNN, Complex Tree, Boosted Tree, Bagged Tree, Cubic SVM). The proposed framework is evaluated on a high-resolution (18 MP) image dataset of guava leaves and fruit. The best recognition results were obtained by Bagged Tree classifier on a set of RGB, HSV, and LBP features (99% accuracy in recognizing four guava fruit diseases (Canker, Mummification, Dot, and Rust) against healthy fruit). The proposed framework may help the farmers to avoid possible production loss by taking early precautions.


2021 ◽  
Vol 8 (1) ◽  
Author(s):  
Ze Peng ◽  
Yanhong He ◽  
Saroj Parajuli ◽  
Qian You ◽  
Weining Wang ◽  
...  

AbstractDowny mildew (DM), caused by obligate parasitic oomycetes, is a destructive disease for a wide range of crops worldwide. Recent outbreaks of impatiens downy mildew (IDM) in many countries have caused huge economic losses. A system to reveal plant–pathogen interactions in the early stage of infection and quickly assess resistance/susceptibility of plants to DM is desired. In this study, we established an early and rapid system to achieve these goals using impatiens as a model. Thirty-two cultivars of Impatiens walleriana and I. hawkeri were evaluated for their responses to IDM at cotyledon, first/second pair of true leaf, and mature plant stages. All I. walleriana cultivars were highly susceptible to IDM. While all I. hawkeri cultivars were resistant to IDM starting at the first true leaf stage, many (14/16) were susceptible to IDM at the cotyledon stage. Two cultivars showed resistance even at the cotyledon stage. Histological characterization showed that the resistance mechanism of the I. hawkeri cultivars resembles that in grapevine and type II resistance in sunflower. By integrating full-length transcriptome sequencing (Iso-Seq) and RNA-Seq, we constructed the first reference transcriptome for Impatiens comprised of 48,758 sequences with an N50 length of 2060 bp. Comparative transcriptome and qRT-PCR analyses revealed strong candidate genes for IDM resistance, including three resistance genes orthologous to the sunflower gene RGC203, a potential candidate associated with DM resistance. Our approach of integrating early disease-resistance phenotyping, histological characterization, and transcriptome analysis lay a solid foundation to improve DM resistance in impatiens and may provide a model for other crops.


2021 ◽  
Vol 13 (10) ◽  
pp. 1975
Author(s):  
Lin Wang ◽  
Yuzhen Zhou ◽  
Qiao Hu ◽  
Zhenghong Tang ◽  
Yufeng Ge ◽  
...  

Woody plant encroachment into grasslands ecosystems causes significantly ecological destruction and economic losses. Effective and efficient management largely benefits from accurate and timely detection of encroaching species at an early development stage. Recent advances in unmanned aircraft systems (UAS) enabled easier access to ultra-high spatial resolution images at a centimeter level, together with the latest machine learning based image segmentation algorithms, making it possible to detect small-sized individuals of target species at early development stage and identify them when mixed with other species. However, few studies have investigated the optimal practical spatial resolution of early encroaching species detection. Hence, we investigated the performance of four popular semantic segmentation algorithms (decision tree, DT; random forest, RF; AlexNet; and ResNet) on a multi-species forest classification case with UAS-collected RGB images in original and down-sampled coarser spatial resolutions. The objective of this study was to explore the optimal segmentation algorithm and spatial resolution for eastern redcedar (Juniperus virginiana, ERC) early detection and its classification within a multi-species forest context. To be specific, firstly, we implemented and compared the performance of the four semantic segmentation algorithms with images in the original spatial resolution (0.694 cm). The highest overall accuracy was 0.918 achieved by ResNet with a mean interaction over union at 85.0%. Secondly, we evaluated the performance of ResNet algorithm with images in down-sampled spatial resolutions (1 cm to 5 cm with 0.5 cm interval). When applied on the down-sampled images, ERC segmentation performance decreased with decreasing spatial resolution, especially for those images coarser than 3 cm spatial resolution. The UAS together with the state-of-the-art semantic segmentation algorithms provides a promising tool for early-stage detection and localization of ERC and the development of effective management strategies for mixed-species forest management.


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