International Research Journal of Engineering and Technology (IRJET)
e-ISSN: 2395-0056
Volume: 09 Issue: 05 | May 2022
p-ISSN: 2395-0072
www.irjet.net
RECOMMENDATION OF CROP AND PESTICIDES USING MACHINE LEARNING J. Ignashya preetha1, N. Priyadharshini2, P. Mageshwari3, S. Rakshana4, Dr. S. Jeyalakshmi5 Department of IT, SRM Valliammai Engineering College, Tamil Nadu 603203 ---------------------------------------------------------------------***--------------------------------------------------------------------1,2,3,4,5
Abstract – The major resource for improving the economy
agriculture as a profitable business for farmers and satisfies the need of a nation, different kind of agricultural practices are carried out. In developing nation like India, sustainable agriculture is practised to manage the necessity of food. A lot of techniques were carried out to minimize the shortening of crop yield; but traditional agriculture having its own demerits. The demerits are further limited through precision farming. Other than that, some other factors affecting the yield of a plant are bacterial, fungal and viral diseases. The detailed explanation of various plant diseases occurring repeatedly in farms are given below:
of India is agriculture. From past farmers followed ancestral faming pattern and regularities within it. A single farmer cannot take action upon improving the crop yield of a nation and does not have enough potential to maximize the crop yield by adopting technical norms within plant growth and improving the yield in a large quantity. Severe change in climatic condition and several other pesticides attack cause shorting of crop yield and also led to food shortage. A simple misguided decision in farming can affect a farmer severe. In recent, there is lot of techniques applied by researchers and those techniques are available to raise the quantity of yield. This in turn changed traditional farming approach and introduced precision farming. Recently data mining performs vital role in identifying plant disease and providing solution prescribing pesticides to plant disease. But this study extends the application of data mining in agriculture to a greater extent. The cultivation of precious crop at right time is the major issues faced by farmer. This study proposes machine learning (ML) approach to resolve it and makes the farmer to choose right crop based on the nutrition content and quality of soil. The machine learning algorithms chosen for this study are Random forest, decision tree and K-nearest neighboring. Some of the factors mainly considered for recommendation of plant are humidity, rainfall, pH value, soil moisture. The recommended technique makes farmer to take decision on improving the crop yield; recommending crops as per climatic condition and quality of land.
Anthracnose: Mostly fungus is observed in genus collectotrichum and other regions; lesions occur on stem. The major reason for this disease is rotted waste and certain other wastages around it. During winter, the plants are affected by this disease and it is transmitted to nearest plant through watering and pollination. The dead tissues appear as anthracnose. Bacterial blight: Lesions are converted into dead spots in this; later elongated lesions are appeared as like linear streaks and it is turned into milky green colour. As like anthracnose, this disease will affect in winter season and transmission through insects and water. Alternaria alternate: A fungal disease found in different kinds of plants and the symptoms are observed as blights, leaf spot and rots. The spores in a leaf are created by conidia. Rainfall and humidity are the comfort zone for this disease.
Key Words: Agriculture, Crop Recommendation, Machine
Learning (ML), Random Forest, K-nearest Neighboring (KNN), Decision Tree
Cercospora leaf spot: This does not have sexual stage and its genus is mycospharella.
1. INTRODUCTION
Later data mining and ML techniques are used by researchers to bring revolution in the field of traditional agriculture to maximize the productivity by considering the necessity. ML can gain expertise without doing additional programming in a machine, so it maximizes the accomplishment of machine by differentiating and depict the consistency and format of drive data. In this research, combination of three different algorithms such as Random forest, KNN, decision tree algorithms were used to suggest crop, fertilizer and pesticides. As per the land condition, the proposed study will recommend crops and several other essentialities. This type of recommendation is carried out with the consideration of water level, moisture content, pH, temperature.
Agriculture is said to be the backbone of Indian economy and it utilizing 60% of nation land to fulfil the food needs around 1.2 million people. Farmer doesn’t have conquered knowledge about severe climatic changes and the soil moisture content. Mostly famers are difficult to understand those two factors. This in turn led to decrease in expected level of productivity. The selection of pesticide, usage of water and maintaining of it will make the crop growth even stronger. Every crop has special climatic factors. By precision farming technique, those factors are handled as per the crop planted. Precision farming not only focuses on productivity but also raising the yield rate of crop. To make
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