The quality of human existence and economic standing are significantly impacted by agriculture. It is the foundation of a nation's economic structure. Therefore, early diagnosis of plant diseases is crucial in both the agricultural sector and in people's daily life. Hunger and starvation are caused by agricultural losses due to plant diseases, especially in less developed nations where access to disease-controlling measures is limited and yearly losses of 30 to 50 percent for main crops are not unusual. Due to inadequate diagnosis of plant diseases, many plants die. Initially, diagnosis of plant disease was performed using MATLAB and machine learning algorithms including SVM. But these diagnoses did not provide accurate results. Also, in previous works website has not been created. To overcome this problem, a CNN model has been proposed that detects plant diseases. This CNN model has been deployed to the website. On this website, the image can be uploaded, and the disease gets predicted according to the image. The detected disease gets displayed on the website. To the CNN model, 15 cases have been fed, including both healthy and unhealthy leaves. The proposed model achieves a greater accuracy of more than 95%. This work offers a major benefit to the farmers by helping them in detecting plant diseases without requiring any special hardware or software.
Soil physicochemical properties can be regarded as an important tool to assess soil health, which further form a base for biological activity in soil. These soil physicochemical properties are comparable in identical land-uses. However, the changes in land-use types and their effects on soil physicochemical properties are largely debates and rather unclear. Soil serves as an important thing in agriculture because this determines the plant growth and health. The present circumstance of industrialization and urbanization has taken a toll on environment, polluting the soil, air and water. Pollution as well as global warming has exhibited detrimental effects on our natural resources of soil becomes the inexplicable. Failing monsoon rains due to climatic changes, population explosion, and depletion of natural water and soil resources such as ground soil, agricultural soil as well as intentional man-made pollution of agriculture pesticide to soil scarcity. Even the scarcely available water is located by contaminants and pollutants which include mutagens, carcinogens, and pathogenic microbes affecting all the file forms affecting the ecological balance. Considering the above mentioned problem criteria, a part of the present work has been designed to analyze the quality of ground soil around the industrial premises. For this objective, we have collected different types of soil samples from various locations in and around sathyamangalam area in Erode District focusing on quite far away from industrial premises considering the concepts of leaching. Basic physio-chemical properties of soil colour, pH, chloride, sulphate, phosphate, silicate, nitrate, moisture, nitrogen, phosphorous, potassium using specific techniques used in laboratory for the samples have been analyzed by APHA standards. These analysis help in the addition of the nutrients of the soil and provide a nutritive indicator value of the sampling sites. Highest possibility of soil quality issues which affects the day to day consumption of soil samples for the domestic needs of the people has been emphasized.
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