• Korean Journal Plant Pathology
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• v.3 no.2
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• pp.131-136
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• 1987

Rates of lesion development over time and disease gradients over distance for blast disease on the two rice varieties, Brazos and M-20 1 were significantly affected by two different cultural conditions, upland and flooded conditions. Flooding rice field plots lowered the rates of lesion increase and flattened the disease gradients for both varieties. Despite absence of statistically significant differences in the rate of lesion increase between four sampled distances from infection focus, rate of lesion development tended to be slightly greater as distance from the infection focus increases. Rate of lesion increase was greater with more susceptible variety M-201 than with Brazos. Disease gradient was steeper for M-201 than for Brazos. As blast disease progressed, disease gradients became flattened regardless of variety due to the infections originated from secondary foci. Between two empirical disease gradient models examined, Kiyosawa & Shiyomi model was fitted better over Gregory model. Rates of blast isopath movement under upland conditions were calculated as approximately 0.2m/day and 0.4 m/day for Brazos and M-201, respectively. The results in this study suggest that differences in varietal resistance to blast could be detected by measuring disease gradient as efficiently as by measuring infection rate.

• Korean Journal Plant Pathology
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• v.11 no.4
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• pp.338-343
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• 1995

Incidence of blast caused by Pyricularia grisea on five new cultivars and four elite lines (C/L) of rice was investigated at different locations, Icheon, Chuncheon, Jecheon and Naju, 1992 to 1994. Disease indices of leaf blast on the tested C/L except Juanbyeo and Keumnambyeo ranged from 0 to 6 in the blast nursery. Under the field conditions, percentages of diseased leaf area of Kuemnambyeo were 6.5% in Jecheon and 2.8% in Icheon in 1993. The incidence of panicle blast on the C/L except Suweon 394 and Milyang 117 differed depending on the locations and years. In case of Unjangbyeo, panicle blast was rarely observed n the fields in Icheon and Naju, but the disease incidences were 21.8% in Jecheon in 1993 and 16.4% in Chuncheon in 1994. Race distribution of the blast fungus was variable according to the locations. The major race in the Jecheon site was KI-197, which was recently identified.

• Korean Journal Plant Pathology
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• v.10 no.2
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• pp.123-128
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• 1994

Incidence of blast caused by Pyricularia grisea Sacc. on 21 leading cultivars and elite lines of rice was investigated in different locations such as Icheon, Chuncheon, Jecheon, and Naju during three years from 1991 to 1993. Disease index of leaf blast of Dongjinbyeo was high in the blast nursery with range 4 to 9 at Naju, but low at other locations with range 1 to 4. Percentages of diseased leaf area of Joryungbyeo and Daelipbyeo 1 were 4.3 and 12%, respectively in the fields at Jecheon in 1993, but were much lower in the other locations during three years. The incidences of leaf blast of Daelipbyeo 1 were 0.3 and 12.0% at Chuncheon and Jecheon, respectively in 1993, but no disease occurred at Naju during three years. Percentage of diseased panicles of Joryungbyeo was 100% at Icheon and Jecheon in 1993, 92.4% in Suweon 390 at Icheon on 1991 and 100% in Jinbu 15 at Jecheon on 1993. Race distribution of rice blast fungus at Icheon and Jecheon was more varied than that of the other locations.

• The Plant Pathology Journal
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• v.38 no.4
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• pp.395-402
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• 2022

To predict rice blast, many machine learning methods have been proposed. As the quality and quantity of input data are essential for machine learning techniques, this study develops three artificial neural network (ANN)-based rice blast prediction models by combining two ANN models, the feed-forward neural network (FFNN) and long short-term memory, with diverse input datasets, and compares their performance. The Blast_Weathe long short-term memory r_FFNN model had the highest recall score (66.3%) for rice blast prediction. This model requires two types of input data: blast occurrence data for the last 3 years and weather data (daily maximum temperature, relative humidity, and precipitation) between January and July of the prediction year. This study showed that the performance of an ANN-based disease prediction model was improved by applying suitable machine learning techniques together with the optimization of hyperparameter tuning involving input data. Moreover, we highlight the importance of the systematic collection of long-term disease data.

• Korean Journal Plant Pathology
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• v.13 no.2
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• pp.79-84
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• 1997

Incidence of rice blast on new rice cultivars and elite lines was observed from 194 to 1996 in Icheon, Chuncheon, Jecheon and Naju areas. The observations were made in the nuseries and in the fields. In the nurseries, only cultivars Daesanbyeo and Hyangmibyeo 2 showed moderate levels of resistance to leaf blast, with the disease index 0 to 6. From the field observations, it was found that cultivars Hyangmibyeo 2 and Suwon 414 were highly resistant to leaf blast, but susceptible to neck blast. the fields, leaf blast was not observed. In general, there was great yearly and regional variation in the incidence of neck blast within the same cultivars, some times ranging from 0 to 100% of incidence. However, the range of fluctuation in the disease incidence were relatively small in the cultivars Daejinbyeo (0∼17.5%), Daesanbyeo (0∼4.0%), Donganbyeo (0∼21.4%) and Hwasambyeo (0∼13.9%). Hyangmibyeo 2 and Seojinbyeo were rarely infected with neck blast in Chuncheon and Naju all of the years, the same cultivars were severely infested with neck blast; 45.1 and 45.5%, respectively, in Jecheon in 1995. The occurrence of different races of rice blast fungus were different at different areas. However, it was found that in Icheon, Chuncheon, Jecheon and Naju areas, the dominant races were KI-409, KJ-201 and KJ-301.

• The Plant Pathology Journal
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• v.18 no.1
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• pp.43-49
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• 2002

Direct effects of atmospheric ozone on conidia of the rice blast pathogen, Magnaporthe grisea, were investigated to evaluate ozone-induced effects on infection potential of the rice blast fungus. Acute ozone exposure (200 nl $1^{-1}$, 8 h $day^{-1}$3 days) during sporulation significantly affected conidial morphology, appressorium formation, and disease development on rice loaves. Ozone caused reduction in conidial size and change in conidial shape. Relative cytoplasmic volume of lipids and vacuoles were increased in ozone-exposed conidia. Inhibition of appressorium formation and simultaneous increase in endogenous levee of polyamines were found in ozone-exposed conidia. The inverse relationship between appressorium formation and level of polyamines implies that ozone-mediated increase in intracellular level of polyamines may inhibit appressorium formation in rice blast fungus. Furthermore, rice plants inoculated with ozone-fumigated conidia exhibited less severe disease development than those with unfumigated conidia. This result suggests that the anti-conidial consequence of acute ozone will eventually weaken the rice blasts potential for multiple infection cycle. This further suggests that consequently, rice blast can be transformed from an explosive disease to one that has limited epidemiological potential in the field.

• The Plant Pathology Journal
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• v.31 no.1
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• pp.12-24
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• 2015

Rice Blast is the most devastating disease causing major yield losses in every year worldwide. It had been proved that using resistant rice varieties would be the most effective way to control this disease. Molecular screening and genetic diversities of major rice blast resistance genes were determined in 192 rice germplasm accessions using simple sequence repeat (SSR) markers. The genetic frequencies of the 10 major rice blast resistance genes varied from 19.79% to 54.69%. Seven accessions IC337593, IC346002, IC346004, IC346813, IC356117, IC356422 and IC383441 had maximum eight blast resistance gene, while FR13B, Hourakani, Kala Rata 1-24, Lemont, Brown Gora, IR87756-20-2-2-3, IC282418, IC356419, PKSLGR-1 and PKSLGR-39 had seven blast resistance genes. Twenty accessions possessed six genes, 36 accessions had five genes, 41 accessions had four genes, 38 accessions had three genes, 26 accessions had two genes, 13 accessions had single R gene and only one accession IC438644 does not possess any one blast resistant gene. Out of 192 accessions only 17 accessions harboured 7 to 8 blast resistance genes.

• International Journal of Computer Science & Network Security
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• v.24 no.4
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• pp.211-221
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• 2024

Pakistan is a top producer and exporter of high-quality rice, but traditional methods are still being used for detecting rice diseases. This research project developed an automated rice blast disease diagnosis technique based on deep learning, image processing, and transfer learning with pre-trained models such as Inception V3, VGG16, VGG19, and ResNet50. The modified connection skipping ResNet 50 had the highest accuracy of 99.16%, while the other models achieved 98.16%, 98.47%, and 98.56%, respectively. In addition, CNN and an ensemble model K-nearest neighbor were explored for disease prediction, and the study demonstrated superior performance and disease prediction using recommended web-app approaches.

• Korean Journal of Agricultural Science
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• v.11 no.1
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• pp.61-67
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• 1984

In an attempt to obtain a basic information to develop methods of an effective chemical control and disease forecasting of panicle blast of rice, effects of conidial number of the causal fungus, Pyricularia oryzae, collected in different periods and the rate of leaf blast occurrence on the occurrence of panicle blast were investigated. Conidial number the fungus collected in 5 days before and after heading date were closely related with panicle blast occurrence. But no relationship was obtained between the occurrence rate of leaf blast and that of panicle blast. Considering the incubation period of the disease, we presume that the most effective application periods of chemicals are 5-10 days and 10-15 days before heading, when immediate effective chemicals and slow effective chemicals are applied, respectively.

• The Plant Pathology Journal
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• v.16 no.5
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• pp.257-263
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• 2000

Infection with rice blast fungus (Magnaporthe grisea) significantly reduced foliar net photosynthesis (A) of rice cultivars: Ilpoom, Hwasung, and Choochung in greenhouse experiments. By measuring the amount of diseased leaf area with a computer image analysis system, the relation between disease severity (DS) and net photosynthetic rate was curvilinearly correlated (r=0.679). Diseased leaves with 35% blast symptom can be predicted to have a 50% reduction of photosynthesis. The disease severity was linearly correlated (r=0.478) with total chlorophyll (chlorophyll a and chlorophyll b) per unit leaf area(TC). Light use efficiency was reduced by the fungal infection according to the light response curves. However, dark respiration (Rd) did not change after the fungal infection (p=0.526). Since the percent of reduction in photosynthesis greatly exceeded the percent of leaf area covered by blast lesions, loss of photosynthetic tissue on an area basis could not by itself account for the reduced photosynthesis. Quantitative photosynthetic reduction can be partially explained by decreasing TC, but cannot be explained by decreasing Rd. By photosynthesis (A)-internal CO$_2$ concentration (C$_i$ curve analysis, it was suggested that the fungal infection reduced ribulose-1,5-bisphosphate carboxylase/oxygenase (Rubisco) activity, ribulose-1,5-bisphosphate (RuBP) regeneration, and inorganic phosphate regeneration. Thus, the reduction of photosynthesis by blast infection was associated with decreased TC and biochemical capacity, which comprises all carbon metabolism after CO$_2$ enters through the stomata.