Abstract
The main aim of Crop rotation identification using NRC Algorithm project is to predict the crop rotation for various types of soil. Crop rotation is a method that is being used widely. One can identify the crops that can be farmed after another crop. For instance, rice will be cultivated within 7 months to 8 months. The remaining time the farm will not be left empty. Some other crops may be cultivated for the other 4 months. This calculation can be done through soil fertility, water level, fertilizer level, Climatic condition, etc.
India is an agriculture-based country. The nation’s economy is highly influenced by agriculture-based industries. In this paper Data Mining techniques are applied over agriculture land soil testing details to generate advisory reports which facilitate decision support to crop rotation, fertilizer requirements and harvesting procedures. The main aim is to reduce unnecessary fertilizer usage during the cultivation of lands and to increase soil vitality. With this approach, we can improve crop productivity as well as the nation’s economy.
In Crop rotation identification using NRC Algorithm proposed system a collection of soil testing reports is pre-processed to generate training data sets. The training data sets are subjected to data mining techniques like Grouping and clustering methods. Finally, decisions tracked based on group characterization rules implemented. The training data samples Mineral ratios, crop cultivation used to generate various interesting measures for decision support on cultivation.
Here two interfaces will be created, one for admin and another one for the user. Here the admin can upload the dataset for the data analytics process and the user can view all the analyzed data by the user-defined input. Now the farmer can predict the cultivation and rotation crop process for their field according to their live data.
All the suggestions and results will be shown in the graphical format for better data visibility.
Keywords:
Agriculture based project, NRC algorithm, Random Forest algorithm, Data mining projects, MCA projects, MSc Projects, CSE Projects, IT Projects.
Helpline:
Visual Studio – 2012 , ASP.NET, C#, SQL Server, Java Script.
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