Nutrient Deficiency and Syndrome Recognition in both Mango Leaf and Cotton Plant using K-means Clustering and BPNN

  Rumel M S Pir

Cotton is the most substantial fiber crop that displays very important role in social concern ofindividuals, particularly in India but if ailment known as Alternaria Leaf Spot and absence of definite chief nutrients goes unobserved in then it can decrease as much as 30% of overall manufacture. This will be slightly valuable for growers to upsurge the manufacturing of yield and have enhanced revenue out of it. Amongst dissimilar diseases, attention has been ended on ‘Alternaria Leaf Spot’ as it is the greatest hazardous and commonly found disease on cotton plants in India. We have used the K-means clustering technique for separation purpose and Back Propagation Neural Network (BPNN) technique for the classification of the mango leaf disease and Cotton Plant, and so it has been planned in this research paper. Procedures that give best consequences have been designated and adapted when desirable. Template matching and color histogram procedures have also been used for discovery. Complete examination and assessment has been ended with formerly used systems. After executing the code on huge quantity of cotton images and mango leaves taken from diverse places, result and conclusion has been completed. Results display how this investigation is more convenient and virtually more achievable than previous investigates.

Keywords- Cotton, Leaf, Image Processing, K-Means Clustering, Disease, Detection, Nutrient Deficiency, Color, BPNN, Mango

Unique Identification Number - IJEDR1601109
Page Number(s) - 636-642
Pubished in - Volume 4 | Issue 1 | March 2016
DOI (Digital Object Identifier) -   
Publisher - IJEDR (ISSN - 2321-9939)

  Rumel M S Pir,   "Nutrient Deficiency and Syndrome Recognition in both Mango Leaf and Cotton Plant using K-means Clustering and BPNN", International Journal of Engineering Development and Research (IJEDR), ISSN:2321-9939, Volume.4, Issue 1, pp.636-642, March 2016, Available at :http://www.ijedr.org/papers/IJEDR1601109.pdf