Tomato Leaf Disease Classification Using Supervised Learning Techniques: Contrasting Analysis

Presently hydroponic methods of growing different varieties of crops are acquiring acceptance in different parts of the world. It is a technique of growing plants with the help of water. Traditional methods of farming are facing different types of threats like lack of farming lands, expansion of urban areas, change in climatic conditions and extensive use of chemical fertilizers and toxicants which is exhausting the fertility of the soil and transforming cultivable lands into barren lands. With the tremendous growth of population nowadays it is quite difficult to supply all the human race with an adequate amount of food by growing them on the basis of traditional methods. The farming land is also changing in residential areas to meet the demand of the growing population in order to provide them a place for living. As a result, different methods of farming need to be adopted. In this study, hydroponic methods are explained with the help of machine learning algorithms. This system works on the principle of KNN and Lasso Regression algorithm to automatically provide them with nutrients dissolved in water with the help of roots. With the help of this technique, we can overcome the issues of food scarcity by growing an ample number of crops of different types, all year round. Hydroponics is a technique for the cultivation of plants without using soil. Earlier this method was practiced manually by keeping an eye on the nutritional needs of plants by maintaining a balance of various factors such as acidity or basic (pH), electrical conductivity (EC), temperature and the value of total dissolved solids(TDS). In this research Machine, Learning Methods are used that help us to measure pH, TDS, and nutrient temperature value in the nutrient film technique (NFT) by using some sensors. In this research, tomato is an object of an experiment, and Comparison is done using Machine Learning Algorithms to speculate the categorization of nutrient conditions for it.