Abstract

The main employment and resource of our country is agriculture. In the upcoming days agriculture is going to be one of the important field .Agriculture plays a vital role in economical development of india. Half of the Indian population is mainly depended on agriculture. It is the source of living it is important in everyday life. Comparing to previous years Now-aday's Agriculture is in poor condition. The most important reasons for this is there is no proper guidance for the farmers.Outstanding to these problems, farming affects the yield of Coriander and lack of knowledge about the Coriander cultivation methodologies. And also season to cultivate the coriander and choosing which soil is the best to cultivate the particular Coriander based on the weather condition and also when to harvest the Coriander for the best yield. If the farmer is aware about the Coriander cultivation methodologies and harvesting it will more helpful for the people in the real world and also to increase the Coriander productivity. Data mining is the process of finding new template from large data sets, this technology which is in use in inferring useful knowledge that can be put to use from a vast amount of data. Climate is one of the meteorological data that is well-to-do by important knowledge. This paper presents a brief comparative study of various different techniques used for yield of coriander. The data mining techniques that are in use for the coriander yield estimation are K-Means.

Full Text
Published version (Free)

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call