AgriCrop🌱

Abstract:
In today’s time technology is playing a vital role in different sectors to overcome the difficulties and to have better and maximum results. In India, the farming sector has a huge impact on Indian economy. Half of the country’s population is still employed in the agriculture sector. Agriculture industry is largely influenced by natural conditions of its surroundings and hence faces number of challenges in actual farming practices. Agriculture practices in the country are largely primitive and technological change in the sector is slow. Effective technology can be used to increase the yield and to reduce the maximum possible challenges in this field. Most of the times it is observed that farmers tend to sow the crop according to its market value and possible financial profits rather than taking factors like soil conditions, sustainability etc. in to the account. This may lead to undesirable results for farmers and for the nature of soil too. In today’s time, technologies like machine learning and deep learning can become game changers in such fields if they are used in a proper manner. This paper will represent an effective use of such technologies in order to provide maximum assistance to farmers in the area of crop recommendation.

Problem Statement☘️

Farming is one of the major sectors that influences a country’s economic growth.
In country like India, majority of the population is dependent on agriculture for their livelihood. Many new technologies, such as Machine Learning and Deep Learning, are being implemented into agriculture so that it is easier for farmers to grow and maximize their yield.
In this project, I present a website in which the following applications are implemented; Crop recommendation, Fertilizer recommendation and respectively.
I have also made some visuals about the production of a crop/fruit for the total year of production,and the states which are contributing the most for a particular crop/fruit
- In the crop recommendation application, the user can provide the soil data from their side and the application will predict which crop should the user grow.
- For the fertilizer recommendation application, the user can input the soil data and the type of crop they are growing, and the application will predict what the soil lacks or has excess of and will recommend improvements.

Data Collection🌿

Crop recommendation dataset (custom built dataset)
Fertilizer suggestion dataset (custom built dataset)
Disease detection dataset

Built with🌴

How to use🍃

Crop Recommendation system ==> For this go to the Predict section and then enter the corresponding nutrient values of your soil, Note that, the N-P-K (Nitrogen-Phosphorous-Pottasium) values to be entered should be the ratio between them. the crop Recommender system will suggest which type of crop/fruit to grow and will also suggest the fertilizer which must be used in order to increase production.