Agriculture Yield and Crop Prediction
Agriculture Yield and Crop Prediction
Price : 9000
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Abstract :
In general, agriculture is the backbone of India and also plays an important role in Indian economy by providing a certain percentage of domestic product to ensure the food security. In India agriculture contributes approximately 23% of GDP and employed workforce percentage is 59%. India is the second-largest producer of agriculture crops. the technological contribution may help the farmer to get more yield. But now-a-days, food production and prediction is getting depleted due to unnatural climatic changes, which will adversely affect the economy of farmers by getting a poor yield and also help the farmers to remain less familiar in forecasting the future crops. This research work helps the beginner farmer in such a way to guide them for sowing the reasonable crops by deploying machine learning, one of the advanced technologies in crop prediction. The main aim of machine learning is to instruct computers to use data or experience to solve a real-life problem. In this study, we will focus on the use of machine learning in agriculture to solve real-life problems.
So we proposed a system with the help of machine learning techniques and algorithms like Linear Regression, XGB Regressor and Random Forests Regressor to predict that crop yield and also advices the alternate crop can be grown to get more yield based on different parameters entered by the user in the front end.
Introduction:
From ancient days, agriculture is considered as the main source of supply to satisfy the daily needs of human lives. It is also considered a primary occupation, and also one of the India's major industrial sectors. The farmers are ought to follow a traditional naked eye observation and yielded healthy crops without the involvement of chemicals for animals and also to their cultivation land in order to keep healthy diversity. But nowadays, weather conditions are being rapidly changing against the elemental assets to deplete the food and increase the security. In meantime, the GDP in agricultural sector is keep on decreasing, where in 2005 it was about 17.2%, in 2012 it was 11.1, in 2018 it was 5% and in first quarterly year of 2109- 2020 it came down to 2%. Approximately 80 percent of farmers come from rural areas, and if the revenue from crop production goes down, their lifestyle would be influenced by the farms at industry level.
This makes sense to farmers in India to show some special concern towards effective and precision farming. In India there are multiple ways to rise the crop learn profit and improve the standard of the crops so as to keep up the economic growth within the field of agriculture. So, the deployment of one of the recent advancement in technology such as, Machine learning is one among the answer for predicting the crop with relation to atmospheric & soil parameter of the agricultural land. Since, now-a-day’s climatic conditions aren’t predictable like decades ago. It is changing day by day due to globalization. Hence, the farmers are facing difficulties in forecasting the weather and crops based on climate data. In recent years the advancement of Machine Learning plays a crucial role in every field including agriculture, here the crop prediction process done with consolidating the preceding data and the present data of a particular month to prove the accuracy of climatic data. Machine learning may be a methodology of analyzing information to automatize the given model and may be a branch of AI depend on the concept that systems will study from data to form selections with minimal human intervention. There may be a logical classifier, where a naive mathematician who predicts membership opportunities for each group, such as the possibility that knowledge belongs to a specific class.
So we proposed a system with the help of machine learning techniques and algorithms like Linear Regression, XGB Regressor and Random Forests Regressor to predict that crop yield and also advices the alternate crop can be grown to get more yield based on different parameters entered by the user in the front end.
Objective:
The main aim of this project to predict the yield and crop can be grown based on different parameters with good accuracy with help of machine learning techniques and algorithms.
Problem Definition:
In general, agriculture is the backbone of India and also plays an important role in Indian economy by providing a certain percentage of domestic product to ensure the food security. In India agriculture contributes approximately 23% of GDP and employed workforce percentage is 59%. India is the second-largest producer of agriculture crops. The technological contribution may help the farmer to get more yield by growing suitable crop on the particular location.
Proposed System:
We proposed a system with the help of machine learning techniques and algorithms like Linear Regression, XGB Regressor and Random Forests Regressor to predict that crop yield and also advices the alternate crop can be grown to get more yield based on different parameters entered by the user in the front end.