I search for applications about recommender systems.
The Idea in general is to use algorithms which gives according to historical data of the classifications of soil. then make a mapping spell between the existing data of soil, weather and crops and an input entered, user to know the type of crop adapted to his soil in addition to that the amount of appropriate fertilizer.
If you have research/review articles comparative studies or support it will be very helpful .
Regardless of different techniques used for fertilizer recommendation in any crop , soil test -crop repsonse based fertlizer recommendation stands out to be best....unfortunately this issue is under-stressed in fruit crops .
India is an agricultural country with second highest land area of more than 1.6 million square-kilometres under cultivation. Most of the Indian population is involved in agriculture hence the economy is largely dependent on agriculture. India possesses a power potential to be a superpower in the field of agriculture. Agriculture promotes poverty upliftment and rural development. Today in India agriculture is being neglected which has led to losing hope of farmers in agriculture which has led to rise in the number of farmer suicides. There is no such universal system to assist farmers in agriculture. In India agricultural is carried out from ages and thus we have a rich collection of agricultural past data which can used for recommendation. Data mining techniques and algorithms can be used for recommending crops and also the fertilizers. These techniques can be implemented on android operating systems on the smart phones. And the recommendation will be based on Nitrogen(N), Phosphorous(P), Potassium(K) values. This paper focuses on the development of various algorithms which can help in building an efficient recommendation system. The system which recommends the crops and the fertilizers to the farmers thereby increasing their crop production. Also it allows the farmers to purchase the suggested fertilizers from the application itself
Supervised Learning techniques both Classification and Regression can be used for prediction of crop yield, fertilizer recommendation and related works.
you can also check this article link
https://ieeexplore.ieee.org/document/8273722
hope it will be helpful
Soil test for the location will be prerequisite for recommendation of a crop/fertilizer. After, one acquire the desired information regarding soil and climate, then the crop schedule can be easily planned
You are on the spot Shourov. Everything in agriculture production starts with the soil condition. It is crucial that soil nutrients on which the crop is to be grown is known to ascertain the fertilizer requirements!
You can use machine learning techniques for building fertilizer/crop recommendation systems provided you have a historical dataset about crop production at particular location, soil NPK measures and crop growth stage and npk requrements of crop based on growth stage. You can use fuzzy logic along with data mining techniques to build recommendation systems.
We still need basic data , which will come from crop-nutrient repsonse studies in field or the basic dataset in field need to be subjected to machine learning duly cross validated in order to set right the suitability for practical application in filed...
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