• International Journal of Computer Science & Network Security
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• 제22권10호
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• pp.257-261
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• 2022

Diseases of agricultural plants in recent years have spread greatly across the regions of the Kyrgyz Republic and pose a serious threat to the yield of many crops. The consequences of it can greatly affect the food security for an entire country. Due to force majeure, abnormal cases in climatic conditions, the annual incomes of many farmers and agricultural producers can be destroyed locally. Along with this, the rapid detection of plant diseases also remains difficult in many parts of the regions due to the lack of necessary infrastructure. In this case, it is possible to pave the way for the diagnosis of diseases with the help of the latest achievements due to the possibilities of feedback from the farmer - developer in the formation and updating of the database of sick and healthy plants with the help of advances in computer vision, developing on the basis of machine and deep learning. Currently, model training is increasingly used already on publicly available datasets, i.e. it has become popular to build new models already on trained models. The latter is called as transfer training and is developing very quickly. Using a publicly available data set from PlantVillage, which consists of 54,306 or NewPlantVillage with a data volumed with 87,356 images of sick and healthy plant leaves collected under controlled conditions, it is possible to build a deep convolutional neural network to identify 14 types of crops and 26 diseases. At the same time, the trained model can achieve an accuracy of more than 99% on a specially selected test set.

• Journal of Forest and Environmental Science
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• 제36권3호
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• pp.207-218
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• 2020

Ashwagandha is an important ancient medicinal crops, being affected with many diseases, among which leaf blight caused by Alternaria alternata has become the constraint resulting in huge yield losses. Continuous usage of chemical methods leads to environment, soil and water pollution. Whereas biological control of diseases is long lasting, inexpensive, eco-friendly and harmless to target organisms. In this context, it is aimed to evaluate five Trichoderma strains viz. Trichoderma virens IMI-392430, T. pseudokoningii IMI-392431, T. harzianum IMI-392432, T. harzianum IMI-392433 and T. harzianum IMI-392434 as bio-control efficacy against A. alternata and growth promoting effect in Ashwagandha. All the Trichoderma strains had varied antagonistic effects against the pathogen. In dual culture technique, the strain T. harzianum IMI-392433 showed maximum percentage inhibition of mycelial growth (54.89%) followed by T. harzianum IMI-392432 (53.83%), T. harzianum IMI-392434 (48.94%) and T. virens IMI-392430, (43.62%) against the pathogen, while the least inhibition percentage was observed with the T. pseudokoningii IMI-392431 (36.60%). The culture filtrate of the Trichoderma strain, T. harzianum IMI-392433 recorded highest inhibition on the mycelial growth (39.05%) and spore germination (80.77%) of pathogen and the lowest was recorded in T. pseudokoningii IMI-392431 (20.45 and 50%). Moreover, seeds treated with spore suspension of the strain T. harzianum IMI-392433 reduced the percentages of disease severity index significantly. The strain T. harzianum IMI-392433 also significantly increased seed germination %, seedling vigor and growth of Ashwagandha. The correlation matrix showed that root yield per plant of Ashwagandha had significant and positive correlation with plant height (r=0.726^⁎⁎), number of leaf (r=0.514^⁎⁎), number of primary branch (r=0.820^⁎⁎), number of secondary branch (r=0.829^⁎⁎), fresh plant weight (r=0.887^⁎⁎), plant dry weight (r=0.613^⁎⁎), root length (r=0.824^⁎⁎), root diameter (r=0.786^⁎⁎), root dry weight (r=0.739^⁎⁎) and fresh root weight (r=0.731^⁎⁎). The significant and negative correlation (r=-0.336^⁎⁎) was observed with the root yield and percentages of disease severity index. The study recognized that the T. harzianum IMI-392433 strain performed well in inhibiting the mycelial growth and reduced the percentages of disease severity index of pathogen as well as increased the plant growth in Ashwagandha.