• Korean Journal Plant Pathology
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• v.10 no.3
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• pp.169-174
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• 1994

A new unidentified pear leaf spot disease presumed to first occur in the late 1970's has recently become prevalent over the pear growing areas, and caused the greatest problem for pear production in Korea. The disease began to develop on pear leaves at mid- to late May, peaked at mid- to late une, but stopped further development until September in cool climate. Leaf lesions are 0.9∼2.5 mm in diam., oval or irregular to rectangular in shape, first appeared reddish purple, later changed to dark brown, and to whitish grey in the late season. Lesions were limited to appear only on the mature, hardened leaves, initially from leaf margin or near the leaf veins, and later scattered over the leaf surface. Individual lesions usually did not enlarge, but often coalesced each other, commonly causing shot holes and eventual early falling. The disease was most severe on the major pear cultivars Niitaka and Okusankichi ranged with 4 to 100% infections in trees, depending on the orchards, but not on the cultivar Chojuro. Damages from the disease included lower fruit weight, and higher acid and less sugar content in fruits, resulting in lowering the overall fruit quality. Etiology of the disease including identification of the causal organism is in a separate paper.

• Research in Plant Disease
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• v.10 no.4
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• pp.209-216
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• 2004

The circular leaf spot of persimmon is occurred almost every place where persimmon is cultivated, especially the disease outbreak severely in southern part of Korea. The disease reveals unusually long incubation period after pathogen invade into leaf tissue and no practical control measure is available once the symptom has appeared. Most of the farmers just follow the suggested spray schedules calculated on the basis of weather condition of ordinary years. Therefore the damages due to circular leaf spot greatly differ year after year. In this article, we tried to describe and summarized the investigation on the circular leaf spot pathogen, Mycosphaerella nawae, related to disease outbreak such as overwintering of pathogen, inoculum formation and spread, incubation period after infection, and secondary inoculum. With the summary of these results, we suggest the disease cycle of circular leaf spot of persimmon. The pathogen overwinters in diseased leaves as mycelial form or pseudoperithecial premodium. The pseudoperitheria become matured in spring as the temperature raise and forms asci and ascospores. The maturation of pseudoperithecia are closely related to the temperatures during March and early April. The ascospores completely mature in early May and the ascospores released when the pseudoperithecia absorbed enough moisture after rainfall. The release of ascospores are diverse greatly with the variation of maturity of pseudoperithecia. Generally the spore start to release from middle of May to early of July. Duration of ascospore release is depend on the weather condition of particular year, especially amount and number of precipitation. The ascospores produced from pseudoperithecia is known to the only inoculum for circular leaf spot disease. But according to the results obtained from our investigations, the conidia formed on the lesions which incited by natural infection. This conidia are infectious to persimmon leaves and formed identical symptom as natural infection. The time of producing secondary inoculum of circular leaf spot of persimmon is considered too late to develop new disease. Generally the importance of secondary inoculum is low but the conidia produced in early September are competent to develop new disease and new infection also significantly affect to harvest of persimmon. The importance of circular leaf spot disease is recognized well to farmers. The approaches to control of the disease should be initiated on the basis of the knowledges of inoculum dynamics and ecology of disease development. The forecasting system for circular leaf spot is need to be developed.

• The Plant Pathology Journal
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• v.20 no.1
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• pp.67-74
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• 2004

A complete understanding of the epidemiological factors required for optimum for disease development facilitates the design of effective and reliable screening techniques and also disease prediction models. An attempt was made to study the effects of different temperatures ($15-35^{\circ}C$) and leaf wetness periods (4-24 h) on the development of late leaf spot (LLS) in three groundnut genotypes differing in their susceptibility to LLS infection. Irrespective of the genotype, the disease progress evaluated based on different components of resistance was maximum between $15-20^{\circ}C$ and minimum between $20-25^{\circ}C$. At temperatures $\geq$$30^{\circ}C$, LLS development was insignificant. The overall severity of LLS increased with an increase in the leaf wetness period from 4 h to 12 h a day. Further increase of wetness period to 16 h resulted in a rapid increase in the severity. Thereafter, the disease severity gradually decreased with an increase in the wetness period. The effect of temperature and wetness periods on the individual component of disease quantification was not uniform compared between genotypes with different levels of susceptibility/resistance to LLS infection. The results of this study indicate that temperature and leaf wetness period are critical in late leaf spot screening programs since the expression of disease symptoms measured from disease initiation till defoliation, varied differently in the test genotypes with respect to change in these two parameters.

• Korean Journal Plant Pathology
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• v.11 no.3
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• pp.224-229
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• 1995

Occurrence and incidences of major diseases of peach (Prunus persicae pv. vulgaris), leaf curl caused by Taphrina deformans, bacterial shot hole caused by Xanthomonas campestris pv. pruni, brown rot caused by Monilinia fructicola, and anthracnose caused by Glomerella cingulata in peach orchards in Cheongdo and Kyungsan areas of Gyeongbuk province, Korea, were investigated for four years from 1990 to 1993. In leaf curl and bacterial shot hole which mainly occurred on leaves, frist disease occurrences were dated from late April to early May. The maximum leaf curl incidence was dated in mid May, while dates of the maximum bacterial shot hole incidence varied from mid May to mid August depending on the years surveyed. In brown rot and anthracnose on fruit, the first disease occurrence dates ranged from early June to early August; however, the maximum disease incidences for both were invariably dated in late August. The disease incidences on the dates of the maximum incidences differed year by year, and the averages for the 4 years were 13.2%, 10.5%, 10.9% and 3.8% for leaf curl, bacterial shot hole, brown rot and anthracnose, respectively. Especially in the leaf curl disease, the first disease occurrence dates and the maximum disease incidences matched with the amounts of precipitation of rain up to April, suggesting that the disease occurrence may be related to the precipitation during the early season. The occurrence of leaf curl was somewhat higher in cultivar“Baekmi”than other cultivars. All of the major disease occurred more in hilly orchards than in plain ones.

• Journal of Korea Multimedia Society
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• v.23 no.10
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• pp.1250-1257
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• 2020

The early detection of diseases is important in agriculture because diseases are major threats of reducing crop yield for farmers. The shape and color of plant leaf are changed differently according to the disease. So we can detect and estimate the disease by inspecting the visual feature in leaf. This study presents a vision-based leaf classification method for detecting the diseases of tomato crop. ResNet-50 model was used to extract the visual feature in leaf and classify the disease of tomato crop, since the model showed the higher accuracy than the other ResNet models with different depths. We propose a new ensemble approach using several DCNN classifiers that have the same structure but have been trained at different ranges in the DCNN layers. Experimental result achieved accuracy of 97.19% for PlantVillage dataset. It validates that the proposed method effectively classify the disease of tomato crop.

• Research in Plant Disease
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• v.29 no.1
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• pp.60-63
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• 2023

During disease surveys from 2019 to 2021, the authors frequently encountered leaf spot symptoms on Fischer's ragwort plants growing at fields at six locations of Gangwon Province, Korea. The symptoms displayed brown to dark brown, circular or irregular spots on the plant leaves. The disease surveys at the six locations revealed 1-90% of diseased leaves of the plants. Phoma sp. was dominantly isolated from the diseased leaf lesions. Seven single-spore isolates of the fungus were selected and identified as Didymella ligulariae by investigation of their cultural, morphological, and molecular characteristics. Artificial inoculation test to Fischer's ragwort leaves was conducted with three isolates of D. ligulariae. The inoculation test revealed that the tested isolates cause leaf spot symptoms in the plants similar to the natural ones. The fungal pathogen has never been reported to cause leaf spot in Fischer's ragwort. Leaf spot of Fischer's ragwort caused by D. ligulariae is first reported in this study.

• The Plant Pathology Journal
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• v.24 no.2
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• pp.125-130
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• 2008

Various kinds of leaf spots and blights were found in kiwifruit (Actinidia deliciosa) orchards on 2006 in Korea. Disease incidences were quite variable between open-field and rain-proof shelter. Rate of diseased leaves was recorded as about 70% at open-field orchards in late season but use of rain-proof vinyl shelters alleviated the disease incidences by 20%. Angular leaf spots appeared at early infection stage on June and several other symptoms were also recognized as the disease developed afterward. On September, brown leaf blights were the most frequent, followed by grayish brown ring spots, silvering gray leaf blights, zonate leaf blights, dark brown ring spots and angular leaf spots at open-field orchards. Four fungal species were frequently isolated from the disease symptoms. Phomopsis sp. was the most predominant fungus associated with the leaf spot and blight symptoms on kiwifruit, followed by Glomerella cingulata, Alternaria alternata and Pestalo-tiopsis sp. Phomopsis sp. was commonly isolated from angular leaf spots, silvering gray leaf blights, and zonate brown leaf blights. G. cingulata, A. alternata and Pestalotiopsis sp. were isolated from grayish brown ring spots (anthracnose), brown ring spots and zonate dark brown leaf blights. Typical symptoms appeared on the wounded and unwounded leaves, which were inoculated by each of Phomopsis sp., G. cingulata, and Pestalotiopsis sp., but A. alternata caused symptoms only on the wounded leaves.

• Journal of Information Processing Systems
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• v.20 no.2
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• pp.149-158
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• 2024

Traditional manual identification of crop leaf diseases is challenging. Owing to the limitations in manpower and resources, it is challenging to explore crop diseases on a large scale. The emergence of artificial intelligence technologies, particularly the extensive application of deep learning technologies, is expected to overcome these challenges and greatly improve the accuracy and efficiency of crop disease identification. Crop leaf disease identification models have been designed and trained using large-scale training data, enabling them to predict different categories of diseases from unlabeled crop leaves. However, these models, which possess strong feature representation capabilities, require substantial training data, and there is often a shortage of such datasets in practical farming scenarios. To address this issue and improve the feature learning abilities of models, this study proposes a deep transfer learning adaptation strategy. The novel proposed method aims to transfer the weights and parameters from pre-trained models in similar large-scale training datasets, such as ImageNet. ImageNet pre-trained weights are adopted and fine-tuned with the features of crop leaf diseases to improve prediction ability. In this study, we collected 16,060 crop leaf disease images, spanning 12 categories, for training. The experimental results demonstrate that an impressive accuracy of 98% is achieved using the proposed method on the transferred ResNet-50 model, thereby confirming the effectiveness of our transfer learning approach.

• The Plant Pathology Journal
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• v.29 no.1
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• pp.10-16
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• 2013

Hevea brasiliensis is a natural source of rubber and an important plantation tree species in Malaysia. Leaf blight disease caused by Fusicoccum substantially reduces the growth and performance of H. brasiliensis. The aim of this study was to use a combination of both morphological characteristics and molecular data to clarify the taxonomic position of the fungus associated with leaf blight disease. Fusicoccum species were isolated from infected leaves collected from plantations at 3 widely separated locations - Selangor, Perak, and Johor states - in Peninsular Malaysia in 2010. All the isolates were identified according to their conidial patterns and DNA sequences generated from internal transcribed spacers (ITS1 and ITS2), the 5.8S rRNA, and an unknown locus (BotF15) containing microsatellite repeats. Based on taxonomic and sequence data, Neofusicoccum ribis was identified as the main cause of leaf blight disease in H. brasiliensis in commercial plantations in Malaysia. A pathogenicity trial on detached leaves further confirmed that N. ribis causes leaf blight disease. N. ribis is an important leaf pathogen, and its detection in Malaysia has important implications for future planting of H. brasiliensis.

• Journal of Climate Change Research
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• v.9 no.2
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• pp.133-142
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• 2018

Climate change will affect not only the crop productivity but also the pattern of rice disease epidemics in Korea. Impact assessments for the climate change are conducted using various climate change scenarios from many global climate models (GCM), such as a scenario from a best GCM or scenarios from multiple GCMs, or a combination of both. Here, we evaluated the feasibility of using a climate change scenario from the best GCM for the impact assessment on the potential epidemics of a rice leaf blast disease in Korea, in comparison to a multi?model ensemble (MME) scenario from multiple GCMs. For this, this study involves analyses of disease simulation using an epidemiological model, EPIRICE?LB, which was validated for Korean rice paddy fields. We then assessed likely changes in disease epidemics using the best GCM selected for individual agro?climatic zones and MME scenarios constructed by running 11 GCMs. As a result, the simulated incidence of leaf blast epidemics gradually decreased over the future periods both from the best GCM and MME. The results from this study emphasized that the best GCM selection approach resulted in comparable performance to the MME approach for the climate change impact assessment on rice leaf blast epidemic in Korea.