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Fertilizer Prediction Through Big Data Analytics

Authors: K. K. Kannan, K. P. Porkodi
Publisher: Zenodo

Rights: Creative Commons Attribution 4.0 ; ; Open Access ; info:eu-repo/semantics/openAccess


Terms of Re-use: CC-BY
Content Provider: DataCite Metadata Store (German National Library of Science and Technology)

Objective: To predict a suitable fertilizer that yields profitable results for a given plant soil combination with the help of Big Data analytics. A fertilizer is any material of natural or synthetic origin that is applied to soils or to plant tissues to supply one or more plant nutrients essential to the growth of plants. It is the basic source of agricultural crops that helps most of the farmers yield profitable result. The type of soil and the plant plays a vital role in production. Every combination of soil and plant are unique and they require different form of nutrients. So the type of fertilizer required for them also vary. Farmers may not know the exact requirement by the soil or plant until they get the result. Hence, farmer in one region may end up with good yield due to the right selection of fertilizer while farmer in a different region with same type of soil and plant yield improper result. Though, the surveys are useful to find out the right type of fertilizer in some weeks or months, it is not possible to conduct the survey on every plant soil type combination. Hence there is a need to regularly keep track of the fertilizers used by the farmers and make decisions based on them.

Illustration Photo: Manure used as fertilizer is often spread on fields in excess of crop needs, leading to increased nutrient runoff. (credits: werktuigendagen / eutrophication&hypoxia / Flickr Creative Commons Attribution 2.0 Generic (CC BY 2.0))

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