First Report of Brown Blight Disease on <i>Camellia sinensis</i> Caused by <i>Colletotrichum acutatum</i> in China

Chen, Yongji; Tong, Huarong; Xü, Wei; Yuan, Lian-Yu

doi:10.1094/pdis-07-15-0762-pdn

Cited by 15 publications

(5 citation statements)

References 5 publications

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“…Brown blight on tea leaves caused by Co. acutatum was reported by Chen et al. ( 2016 ; 2017 ), showing Co. acutatum is a suitable candidate pathogen to study climatic change and disease development on tea. The Co. acutatum species complex is known today as a destructive pathogen on fruits (including perennial crops), such as citrus ( Peres et al., 2008 ), apple ( Lee et al., 2007 ), olive ( Talhinhas et al., 2011 ), and blueberry ( Wharton and Schilder, 2008 ).…”

Section: Resultsmentioning

confidence: 86%

“…We includeed Co. acutatum because this species was treated as a regulated quarantine pest by the European and Mediterranean Plant Protection Organization (EPPO) for many years until 2011 ( EPPO, 2011 ). This species in a broad sense is a suitable candidate pathogen for modeling disease development on tea in the context of climate change because there are economically important pathogens in tea that infect tea leaves which is the most economically important part of tea ( Peres et al., 2005 ; Wharton and Schilder, 2008 ; Chen et al., 2016 ; Chen et al., 2017 ). In addition, several fungal pathogens on tea are shown in Supplementary Table S2 .…”

Section: Methodsmentioning

confidence: 99%

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Climate-Fungal Pathogen Modeling Predicts Loss of Up to One-Third of Tea Growing Areas

Tibpromma

Dong

Ranjitkar

et al. 2021

Front. Cell. Infect. Microbiol.

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Climate change will affect numerous crops in the future; however, perennial crops, such as tea, are particularly vulnerable. Climate change will also strongly influence fungal pathogens. Here, we predict how future climatic conditions will impact tea and its associated pathogens. We collected data on the three most important fungal pathogens of tea (Colletotrichum acutatum, Co. camelliae, and Exobasidium vexans) and then modeled distributions of tea and these fungal pathogens using current and projected climates. The models show that baseline tea-growing areas will become unsuitable for Camellia sinensis var. sinensis (15 to 32% loss) and C. sinensis var. assamica (32 to 34% loss) by 2050. Although new areas will become more suitable for tea cultivation, existing and potentially new fungal pathogens will present challenges in these areas, and they are already under other land-use regimes. In addition, future climatic scenarios suitable range of fungal species and tea suitable cultivation (respectively in CSS and CSA) growing areas are Co. acutatum (44.30%; 31.05%), Co. camelliae (13.10%; 10.70%), and E. vexans (10.20%; 11.90%). Protecting global tea cultivation requires innovative approaches that consider fungal genomics as part and parcel of plant pathology.

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Section: Resultsmentioning

confidence: 86%

Section: Methodsmentioning

confidence: 99%

Climate-Fungal Pathogen Modeling Predicts Loss of Up to One-Third of Tea Growing Areas

Tibpromma

Dong

Ranjitkar

et al. 2021

Front. Cell. Infect. Microbiol.

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“…Infected tea leaves were collected from the experimental tea garden of Anhui Agricultural University (Hefei, China). After surface sterilization of leaves [51], fungi were isolated from infected leaves and two of them were identi ed as B. dothidea and C. gloeosporioides. The isolated fungal colonies were grown on potato dextrose agar (PDA) and incubated at 28 ℃ in dark conditions.…”

Section: Pathogens Isolation and Culture Conditionsmentioning

confidence: 99%

Inhibition Mechanism of Caffeine in Tea Pathogenic Fungi Botryosphaeria Dothidea and Colletotrichum Gloeosporioides

Thangaraj

Deng

Cheng

et al. 2020

Preprint

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Background Caffeine acts as an antifungal agent; however, its underlying inhibition mechanism remains unclear. To investigate variations in caffeine antifungal activity, this study was evaluate the inhibition mechanisms of caffeine on phytopathogens Botryosphaeria dothidea and Colletotrichum gloeosporioides through transcriptomic analysis, which causes leaf necrosis and anthracnose on tea leaves, respectively.Results Our in vitro results shows that the antifungal activity of caffeine quite different between B. dothidea and C. gloeosporioides. Furthermore, microscopic observation and bioactivity assay results proved that caffeine destroyed the fungal protective layers (cell wall and cell membrane) and subcellular organelles. The transcriptomes of these two fungi exposed to different caffeine concentrations were analyzed by high-throughput sequencing and the results showed that caffeine repressed gene expression involved in the pathways of mRNA surveillance, ribosome biogenesis in eukaryotes, aminoacyl-tRNA biosynthesis, etc. Particularly, caffeine affected gene expression in melanin biosynthesis in C. gloeosporioides, resulting in the disturbances of melanin production and fungal pathogenicity. Manually infected tea leaves showed melanin pigment was important to appressorium development and fungal infection by histopathological observation and fungal biomass quantification. Besides, C. gloeosporioides successfully enters into the host tissue even plant could build multilayer defenses against the fungus, this might be due to the variation in pathogen targets and quantities of secondary metabolites by the host cells.Conclusions Overall, our findings indicate that caffeine in the environment can reduce the fungal growth and physiological activities. However, the genome-wide expression showed different transcriptional profiles between these fungal isolates. Thus, we believe that target of the caffeine varied among isolates and melanin may play a major role in fungus caffeine tolerance. Further in-depth research required to conclude this hypothesis.

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“…Brown blight has irregular ring lines, while target spots often show obvious concentric ring lines. Moreover, in most cases, these two diseases occur at the same time, often on one leaf, which increases the difficulty of manual identification (Chen et al, 2015(Chen et al, , 2018. Tea coal disease is caused by Ascomycete fungi.…”

Section: Introductionmentioning

confidence: 99%

Symptom recognition of disease and insect damage based on Mask R-CNN, wavelet transform, and F-RNet

Shi

et al. 2022

Front. Plant Sci.

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Brown blight, target spot, and tea coal diseases are three major leaf diseases of tea plants, and Apolygus lucorum is a major pest in tea plantations. The traditional symptom recognition of tea leaf diseases and insect pests is mainly through manual identification, which has some problems, such as low accuracy, low efficiency, strong subjectivity, and so on. Therefore, it is very necessary to find a method that could effectively identify tea plants diseases and pests. In this study, we proposed a recognition framework of tea leaf disease and insect pest symptoms based on Mask R-CNN, wavelet transform and F-RNet. First, Mask R-CNN model was used to segment disease spots and insect spots from tea leaves. Second, the two-dimensional discrete wavelet transform was used to enhance the features of the disease spots and insect spots images, so as to obtain the images with four frequencies. Finally, the images of four frequencies were simultaneously input into the four-channeled residual network (F-RNet) to identify symptoms of tea leaf diseases and insect pests. The results showed that Mask R-CNN model could detect 98.7% of DSIS, which ensure that almost disease spots and insect spots can be extracted from leaves. The accuracy of F-RNet model is 88%, which is higher than that of the other models (like SVM, AlexNet, VGG16 and ResNet18). Therefore, this experimental framework can accurately segment and identify diseases and insect spots of tea leaves, which not only of great significance for the accurate identification of tea plant diseases and insect pests, but also of great value for further using artificial intelligence to carry out the comprehensive control of tea plant diseases and insect pests.

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First Report of Brown Blight Disease on Camellia sinensis Caused by Colletotrichum acutatum in China

Cited by 15 publications

References 5 publications

Climate-Fungal Pathogen Modeling Predicts Loss of Up to One-Third of Tea Growing Areas

Climate-Fungal Pathogen Modeling Predicts Loss of Up to One-Third of Tea Growing Areas

Inhibition Mechanism of Caffeine in Tea Pathogenic Fungi Botryosphaeria Dothidea and Colletotrichum Gloeosporioides

Symptom recognition of disease and insect damage based on Mask R-CNN, wavelet transform, and F-RNet

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