Autumn reducing treatment against pear disease

В статье речь идет о том, что защита от болезни груши большое значение имеет осенняя искореняющая обработка садов и дает хороший результат. Нужно быть в курсе какие болезни распространены, описание этих болезней необходимо для того чтобы правильно организовывать последовательность мероприятий против болезни а также и против вредителей груши.

Autumn reducing treatment against pear disease

В статье речь идет о том, что защита от болезни груши большое значение имеет осенняя искореняющая обработка садов и дает хороший результат. Нужно быть в курсе какие болезни распространены, описание этих болезней необходимо для того чтобы правильно организовывать последовательность мероприятий против болезни а также и против вредителей груши.

Influencing factors analysis in pear disease recognition using deep learning

Influencing factors analysis plays an important role in plant disease identification. This paper explores the key influencing factors and severity recognition of pear diseases using deep learning based on our established pear disease database (PDD2018), which contains 4944 pieces of diseased leaves. Using the deep learning neural networks, including VGG16, Inception V3, ResNet50 and ResNet101, we developed a “DL network + resolution” scheme that can be used in influencing factors analysis and diseases recognition at six different levels. The experimental results demonstrated that the resolution is directly proportional to disease recognition accuracy and training time and the recognition accuracies for pear diseases are up to 99.44%,98.43%, and 97.67% for Septoria piricola (SP), Alternaria alternate (AA), and Gymnosporangium haracannum (GYM), respectively. The results also shown that a forward suggestion on disease sample collection can significantly reduce the false recognition accuracy.

Epidemiological Features and Trends of Brown Spot of Pear Disease Based on the Diversity of Pathogen Populations and Climate Change Effects

Brown spot of pear, caused by the fungus Stemphylium vesicarium, is an emerging disease of economic importance in several pear-growing areas in Europe. In recent years, new control strategies combining sanitation practices and fungicide applications according to developed forecasting models have been introduced to manage the disease. However, the pathogenic and saprophytic behavior of this pathogen makes it difficult to manage the disease. In addition, climate change can also result in variations in the severity and geographical distribution of the disease. In this study, ecological and epidemiological aspects of brown spot of pear disease related to inoculum characterization and climate change impact were elucidated. The pathogenic variation in S. vesicarium populations from pear orchards and its relationship to inoculum sources (air samples, leaf debris, and infected host and nonhost tissues) was determined using multivariate analysis. In total, six variables related to infection and disease development on cultivar Conference pear detached leaves of 110 S. vesicarium isolates were analyzed. A high proportion of isolates (42%) were nonpathogenic to pear; 85% of these nonpathogenic isolates were recovered from air samples. Most isolates recovered from lesions (93%) and pseudothecia (83%) were pathogenic to pear. A group of pathogenic isolates rapidly infected cultivar Conference pear leaves resulted in disease increase that followed a monomolecular model, whereas some S. vesicarium isolates required a period of time after inoculation to initiate infection and resulted in disease increase that followed a logistic model. The latter group was mainly composed of isolates recovered from pseudothecia on leaf debris, whereas the former group was mainly composed of isolates recovered from lesions on pear fruit and leaves. The relationship between the source of inoculum and pathogenic/aggressiveness profile was confirmed by principal component analysis. The effect of climate change on disease risk was analyzed in two pear-growing areas of Spain under two scenarios (A2 and B1) and for three periods (2005 to 2009, 2041 to 2060, and 2081 to 2100). Simulations showed that the level of risk predicted by BSPcast model increased to high or very high under the two scenarios and was differentially distributed in the two regions. This study is an example of how epidemiological models can be used to predict not only the onset of infections but also how climate change could affect brown spot of pear. [Formula: see text] Copyright © 2018 The Author(s). This is an open-access article distributed under the CC BY-NC-ND 4.0 International license .

Alternaria kikuchiana. [Descriptions of Fungi and Bacteria].

A description is provided for Alternaria kikuchiana. Information is included on the disease caused by the organism, its transmission, geographical distribution, and hosts. HOSTS: Pyrus serotina[Pyrus pyrifolia], the Japanese Pear. DISEASE: Pear black spot. Infections cause a serious disfigurement of fruit, but may also occur on leaves and young shoots. GEOGRAPHICAL DISTRIBUTION: Asia: Japan. TRANSMISSION: By wind dispersal of airborne conidia. Conidial production is favoured by warm and moist conditions.

Phytophthora heveae. [Descriptions of Fungi and Bacteria].

A description is provided for Phytophthora heveae. Information is included on the disease caused by the organism, its transmission, geographical distribution, and hosts. HOSTS: Hevea rubber, cacao, Brazil nut, Agathis australis, guava, mango, avocado pear. DISEASE: Pod rot and black stripe of rubber; pod rot of cacao; leaf blight of Brazil nut; avocado pear trunk canker. GEOGRAPHICAL DISTRIBUTION: Asia (Malaysia, India); Australia (Queensland, New South Wales); New Zealand; Papua New Guinea; North America (USA); Central America (Guatemala); South America (Brazil). (CMI Map 428, ed. 1, 1967). TRANSMISSION: Soil-borne. Isolated from forest soils (44, 1944); soil in rubber plantation (49, 2165); in Agathis australis stand (54, 3493); in Eucalyptus plantation (55, 4876).