PDCNN: FRAMEWORK for Potato Diseases Classification Based on Feed Foreword Neural Network

The economy is exceptionally reliant on agricultural productivity. Therefore, in domain of agriculture, plant infection discovery is a vital job because it gives promising advance towards the development of agricultural production. In this work, a framework for potato diseases classification based on feed foreword neural network is proposed. The objective of this work is presenting a system that can detect and classify four kinds of potato tubers diseases; black dot, common scab, potato virus Y and early blight based on their images. The presented PDCNN framework comprises three levels: the pre-processing is first level, which is based on K-means clustering algorithm to detect the infected area from potato image. The second level is features extraction which extracts features from the infected area based on hybrid features: grey level run length matrix and 1st order histogram based features. The attributes that extracted from second level are utilized in third level using FFNN to perform the classification process. The proposed framework is applied to database with different backgrounds, totally 120 color potato images, (80) samples used in training the network and the rest samples (40) used for testing. The proposed PDCNN framework is very effective in classifying four types of potato tubers diseases with 91.3% of efficiency.

Inventory of the potato diseases and impact on growth and yield traits in far North Cameroon

Potato (Solanum tuberosum L) production in the Far North Region of Cameroon is faced with scarcity or inequality of rains and with diseases that affect yields. To improve the production a study was conducted in the production area of Mogode subdivision with the objective of identifying potato diseases and pathogens agents. The experimental design was in complete randomized blocks. The plant material used was a local variety of potato (Dosa). Diseases and pathogens have been identified on a base of symptoms and morphological characteristics. The incidence, severity and rainfall were assessed. Yield, number of stems and diameter of the tubers were evaluated. The diseases identified are fungal (late blight, Alternaria or early blight and Fusarium wilt), viral (Virosis M, Rust stain and Potato leaf roll (PLR) and bacterial (Bacterial wilt and Common scab). Conidia of Phytophthora infestans, and Alternaria spp. were found.Whatever the site and disease, the incidence has remained below 25%. Late blight was more present in the Gouria site, Alternaria and virosis M more present in the Mouvou site. The yield was roughly the same at the two sites, around 3 t/ha. The highest number of stems was obtained at Gouria, 18 ± 0.75. The potato is attacked by several diseases. The results of this study represent an important baseline data for the implementation of integrated disease management in Cameroon.Keywords: Solanum tuberosum, diseases, pathogens, incidence, severity, yield.

Ground control and state of elite potato seed breeding in the Central region of Russia and adjacent regions according to its data

The article sets out information on the conduct of soil control of the potato elite, provides information on the state of elite seed production of potatoes in the Central region of Russia according to the data of soil control - which regions participated in its implementation, how many samples and varieties of potatoes were provided for soil control in different years, what were the main varieties, which potato diseases were taken into account.

USE OF PREPARATIONS CONTAINING COLLOID SILVER IN POTATO DISEASE CONTROL

The paper presents the results of four-ear trials of preparations with silver nanoparticles Zerox,Zeromiks, and Zerebra Agro on varieties with varying degrees of resistance to the main potato diseases. The four-ear trials made it possible to conclude that preparations with silver nanoparticles were effective in protecting potatoes from rhizoctoniosis and alternariosis, comparable to the effectiveness of chemical treaters (Maxim and Celeste Top) and fungicides used in the treatment of vegetative plants (Abiga Peak and Ridomil Gold MC). The biological effectiveness of preparations with silver nanoparticles was lower than that of Abig Peak by an average of 49.8% against late blight on the unstable Ilyinsky variety. The biological effectiveness of Zerebra Agro was low (24.6%) in relation to late blight on the Sante variety in the epiphytotic year. It was high (65.7%) in the non-epiphytotic year, and it was not much worse than chemical fungicides (30.4 and 78.1%, respectively) in both the epiphytotic and non-epiphytotic years.In 2018, when the effectiveness of the preparations was high for all major potato diseases,the yield increase was significantly higher than the check. In the standard version, it exceeded the check by 26.4%, in the variant with Zerebra Agro – by 27.1%. No significant difference was found between the standard variant and Zerebra Agro.

Potato diseases and measures to control them in the conditions of the middle Urals

The objective of this research is to study the manifestation of the main diseases of potato during the vegetation period of plants and storage of tubers. The research was carried out on the experimental field of the educational and experimental farm “Uralets” of the Ural State Agrarian University (USAU), the village “Studencheskiy”, during 2016-2018 in the climatic zone of the Middle Urals. According to the results of the research carried out, it was found that with the use of the optimal feeding area and the fungicide shirlan in the fight against pathogens, it was possible to obtain a yield of 36.6 t/ha, which is 31.1% higher than the control (factor A). At the same time, the cost price amounted to 4,446 rubles/ton, profit – 269,172 rubles/ha, and profitability – 165.43%.