Abstract

India being an agriculture country, its economy predominantly depends on agriculture yield growth and agroindustry products. Data Mining is an emerging research field in crop yield analysis. Yield prediction is a very important issue in agricultural. Any farmer is interested in knowing how much yield he is about to expect. Analyze the various related attributes like location, pH value from which alkalinity of the soil is determined. Along with it, percentage of nutrients like Nitrogen (N), Phosphorous (P), and Potassium (K) Location is used along with the use of third-party applications like APIs for weather and temperature, type of soil, nutrient value of the soil in that region, amount of rainfall in the region, soil composition can be determined. All these attributes of data will be analysed, train the data with various suitable machine learning algorithms for creating a model. The system comes with a model to be precise and accurate in predicting crop yield and deliver the end user with proper recommendations about required fertilizer ratio based on atmospheric and soil parameters of the land which enhance to increase the crop yield and increase farmer revenue.

Index Terms—Artificial neural network, Random forest algorithm, Backpropagation algorithm, Prediction.

Existing System:

From ancient times agriculture has become the backbone of our country. Nowadays climatic conditions vary very often. So, it is hard to grow crops by understanding weather conditions. We need to use some technology to find or understand the crop details and guide the farmers to grow crops accordingly and moreover fertilizer also one of the major factors to grow crops accordingly. If fertilizer is used more or less in the field the soil may lose it fertility and crop may not give the expected yield. so, fertilizer also becomes the major factor in it. mostly understanding the temperature conditions is much necessary for India because we can improve the Indian economy with the help of the crop prediction because it plays a major role in the Indian economy.

Generally, machine learning algorithms will predict the most efficient output of the yield. Previously yield is predicted on the bases of the farmers prior experience but now weather conditions may change drastically so they cannot guess the yield . so, technology can help them to predict the yield of the crop weather to go for that crop or no. machine learning model will understand the pattern of the crop and yield based on the several conditions and predicts the yield of the area in which he is going to crop.

The challenge in it is to build the efficient model to predict the most efficient model to predict the output of the crop so try with the different algorithms and compare all the algorithms and which one has the less error and loss chose that model and predict the yield of that particular crop. From this paper, u can see the comparison of the two algorithms and predicting the output from the best model in those two.

Proposed System:

• Niketa et al, have indicated that the yield of the crop depends on the seasonal climate. In India, climate conditions vary unconditionally. In the time of drought, farmers face serious problems. So this taken into consideration they used some machine learning algorithms to help the farmers to suggest the crop for the better yield. They take various data from the previous years to estimate future data.
• Shruti Mishra et al, have indicated that applying the data mining techniques on historical climate and crop production data several predictions are made which increase the crop productivity. The decision support system has to be implemented for the farmers to take proper decisions about soil and crop to be cultivated. They have collected the dataset with attributes of the crop season, Area and production in hectares and analyzed with various algorithms in WEKA.
• Chlingaryana et al 2017,  indicated the major factor in the crop yield prediction is the nitrogen level in the soil. Nowadays remote sensing systems are mostly used in decision making. These remote sensing data is used to help the farmers to improve the crop yield. Huge remote sensing data is used to make a decision. Nitrogen is used to improve the crop yield and make the soil fertile.
• Dakshayini Patil at all, indicated that rice crop plays a major role in the economy. They used various data mining techniques to predict the yield of the rice crop. Rice crop is the sustainable security of India. In general, it contributes 40% to the general yield. High yield of the crop is based on the appropriate climatic conditions.

SYSTEM REQUIREMENTS
SOFTWARE REQUIREMENTS:
• Programming Language : Python
• Font End Technologies : TKInter/Web(HTML,CSS,JS)
• IDE : Jupyter/Spyder/VS Code
• Operating System : Windows 08/10

HARDWARE REQUIREMENTS:

 Processor : Core I3
 RAM Capacity : 2 GB
 Hard Disk : 250 GB
 Monitor : 15″ Color
 Mouse : 2 or 3 Button Mouse
 Key Board : Windows 08/10