• 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.

• Mycobiology
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• v.46 no.3
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• pp.278-282
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• 2018

Chrysanthemum coronarium is an economically important plant in Asia, and used medicinally, ornamentally and as a vegetable. In April 2017, leaf spot disease on C. coronarium was observed in Shiyan, Hubei, China. A single-spore isolate was obtained and identified based on morphology and sequence analysis using four regions (rDNA ITS, GAPDH, $EF-1{\alpha}$, and RPB2). The results indicated that the fungus is Alternaria argyranthemi. The pathogenicity tests revealed that the species could cause severe leaf spot and blight disease on the host. This is the first report of leaf spot disease on C. coronarium caused by A. argyranthemi in the world, which is also a new record of Alternaria species in China.

• The Plant Pathology Journal
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• v.21 no.2
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• pp.137-141
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• 2005

The effect of cotton leaf mosaic disease on morphology, yield and fibre characteristics was examined for a susceptible cotton candidate variety CRIS-168. Plants inoculated at most susceptible growth stage (six week) under screen house showed severe mosaic symptoms. There was a significant reduction in plant height and yield. Cotton leaf mosaic disease was found to produce severe effects on plant morphology with 24.1% reduction in plant height, 25% in internode length and 37.5% in number of sympodia on main stem. However no changes were observed against number of monopodial branches per plant. Inoculated plants showed 82% decrease in yield/plant, 80% in number of boll set/ plant, 12.1% in boll weight, 12.8% in lint weight, 10.8% in seed weight, and 6.8% in seed index. Cotton leaf mosaic disease also showed effects on fibre characteristics with 0.8% decrease in GOT and 1.6% in fibre length. In contrast, uniformity ratio, fibre fineness and maturity index was increased by 20.5%, 14.4% and 0.9%, respectively.

• 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 Information Processing Systems
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• v.17 no.6
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• pp.1115-1126
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• 2021

Plant disease is one of the most irritating problems for agriculture growers. Thus, timely detection of plant diseases is of high importance to practical value, and corresponding measures can be taken at the early stage of plant diseases. Therefore, numerous researchers have made unremitting efforts in plant disease identification. However, this problem was not solved effectively until the development of artificial intelligence and big data technologies, especially the wide application of deep learning models in different fields. Since the symptoms of plant diseases mainly appear visually on leaves, computer vision and machine learning technologies are effective and rapid methods for identifying various kinds of plant diseases. As one of the fruits with the highest nutritional value, apple production directly affects the quality of life, and it is important to prevent disease intrusion in advance for yield and taste. In this study, an improved deep residual network is proposed for apple leaf disease identification in a novel way, a global residual connection is added to the original residual network, and the local residual connection architecture is optimized. Including that 1,977 apple leaf disease images with three categories that are collected in this study, experimental results show that the proposed method has achieved 98.74% top-1 accuracy on the test set, outperforming the existing state-of-the-art models in apple leaf disease identification tasks, and proving the effectiveness of the proposed method.

• 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.

• 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.

• Mycobiology
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• v.48 no.1
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• pp.70-74
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• 2020

Sinowilsonia henryi is a rare and endangered plant, as well as an endemic species in China. In July 2018, leaf spot and blight disease was observed on S. henryi in Yichang, Hubei, China. A fungus isolated from disease tissues was identified as Gonatobotryum apiculatum based on morphology and sequence analyses of ITS and LSU regions. Phylogenetic analyses indicated that the species belongs to Dothioraceae (Dothideales). Morphologically, the species produced two distinct types of conidia from authentic media, both conidia were described here. Pathogenicity tests showed that the fungus is a pathogen causing leaf spots on S. henryi. This is the first report of leaf spot and blight disease on S. henryi caused by G. apiculatum in China.

• Proceedings of the Plant Resources Society of Korea Conference
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• 2021.04a
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• pp.18-18
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• 2021

Gomchwi using stuffed leaves is many cultivated for 'Gondalbi(Ligularia stenocephala)' among Gomchwi species. 'Gondalbi' species like to be cultivation on farm because of low the incense and the bitter taste, and high yield. But 'Gondalbi' caused to curtail yield that susceptibility of powdery mildew disease and shriveling and death of plant on summer season. To solve this problems, we crossed a Gomchwi and 'Handeari-gomchwi' to have resistance of powdery mildew disease and high yield. A new Gomchwi cultivar 'Jinmani' was bred by crossing between Gomchwi (Ligularia fischeri (Ledeb.) Turcz.) and Handaeri-gomchwi (Ligularia fischeri var. spiciformis Nakai). The selection and investigation of growth and yield characteristics were conducted from 2007 to 2020 in field and greenhouse of Highland Agriculture Research Institute, NICS, Rural Development Administration. The color of petiole ear was purple. trichome of petiole and leaf back non-existed, and luster of leaf back existed. Density of leaf vein was 4 degree among 1-5 degree in a newly developed cultivar 'Jinmani'. Plant height, leaf length, leaf width and petiole length were 55.7, 21.8, 22.2, and 33.9 cm, respectively in the 2nd year of growth characteristics. Plant size was similar with that of 'Gommany'. Bolting and flowering time were Aug. 5 and Sept. 5, respectively, and Bolting and flowering time of 'Gommany' showed similar to Aug. 8 and Sept. 1, respectively. 'Jinmani' showed higher number of leaves (202 ea.) per plant compared to 'Gommany' (159 ea.). Furthermore, yield was 67.9% higher in 'Jinmani' (2,569 g/plant) than in 'Gommany' (1,530 g/plant). 'Jinmani' showed lower leaf thickness (0.66mm) than 'Gommany' (0.69 mm), and consequently showed more hardness in leaf characteristics (25.1 kg/²) compared to 'Gommany' (24.3kg/cm²). 'Jinmani' showed similar strong resistance compared to 'Gommany' in the susceptibility of powdery mildew disease.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.8
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• pp.3312-3327
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• 2020

Plant diseases are a significant yield and quality constraint for farmers around the world due to their severe impact on agricultural productivity. Such losses can have a substantial impact on the economy which causes a reduction in farmer's income and higher prices for consumers. Further, it may also result in a severe shortage of food ensuing violent hunger and starvation, especially, in less-developed countries where access to disease prevention methods is limited. This research presents an investigation of Directional Local Quinary Patterns (DLQP) as a feature descriptor for plants leaf disease detection and Support Vector Machine (SVM) as a classifier. The DLQP as a feature descriptor is specifically the first time being used for disease detection in horticulture. DLQP provides directional edge information attending the reference pixel with its neighboring pixel value by involving computation of their grey-level difference based on quinary value (-2, -1, 0, 1, 2) in 0°, 45°, 90°, and 135° directions of selected window of plant leaf image. To assess the robustness of DLQP as a texture descriptor we used a research-oriented Plant Village dataset of Tomato plant (3,900 leaf images) comprising of 6 diseased classes, Potato plant (1,526 leaf images) and Apple plant (2,600 leaf images) comprising of 3 diseased classes. The accuracies of 95.6%, 96.2% and 97.8% for the above-mentioned crops, respectively, were achieved which are higher in comparison with classification on the same dataset using other standard feature descriptors like Local Binary Pattern (LBP) and Local Ternary Patterns (LTP). Further, the effectiveness of the proposed method is proven by comparing it with existing algorithms for plant disease phenotyping.