Mango Tree Research Paper

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CHAPTER 2

TECHNICAL KEYWORDS

2.1 AREA OF PROJECT

Digital Image Processing and Machine Learning

2.1.1 Technical keywords

1.Image Pre-Processing

a.Gaussian Filter

2.K-Means Algorithm

3.Image Segmentation

4.RGB Extraction

5.Classification

6.Image Acquisition

7.Thresholding

8.Nutrition Deficiency

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CHAPTER 3

INTRODUCTION

3.1 PROJECT IDEA proposed software product is the Leaf Deficiency Detection system which will be used to get the information from the leaves and then storing that data for future usage. The intentions of the system are to accurately determine the nutrient deficiency and its solution in given mango leaf. Requirements statements in this document are both functional and non-functional. Agriculture has become much more than just a way to

Also, India is largest producer of mango in the world , contributing to nearly 46 % of total world production.Despite all this the cultivators of mango are facing grave challenges leading to negative growth rate. Major reason for this negative growth rate is that farmers face immense difficulty to detect the precise deficiency of the plant and thus eventually leading to an unhealthy product. This issue can be rectified with the proposed work and thus an early detection of the deficiency can improve the growth rate of this product. We have considered four most common nutrient deficiencies which occurs in leaf i.e nitrogen, iron, potassium and copper.Lack of these nutrients affect a particular mango leaf in a different way. The potassium deficiency is identified when the scorching of leaf starts from the tip downwards,likewise,iron deficiency is identified when a leaf starts to loose the green color and turn white, copper and nitrogen deficiencies usually occur simultaneously when the terminal of the leaf starts to loose natural color.This paper contains a total of III sections. The next section will be about the methodology and algorithm of the work and finally section III will

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be the conclusion.