International Journal of Engineering and Advanced Technology (IJEAT) ISSN: 2249 – 8958, Volume-8 Issue-6, August 2019 2156 Retrieval Number F8578088619/2019©BEIESP DOI: 10.35940/ijeat.F8578.088619 Published By: Blue Eyes Intelligence Engineering & Sciences Publication Abstract: Indian economy is majorly influenced by Agriculture and its allied sectors. More than 50% of the population of India is dependent on agriculture and its allied sectors for their survival. According to the Report of Indian Council of Agricultural Research, 30-35% of the crop yield gets wasted due to disease. Using modern day remote sensing techniques plant health can be monitored and it can be specified whether a plant is diseased or healthy. Hyperspectral Remote Sensing is the technique by which fine and minute information of vegetation can be obtained with the help of narrow wavebands. Data of 80 leaf samples of Tomato crop collected in spectra form and text form using ASD FieldSpec4 spectroradiometer and ViewSpec PRO. This information of plant leaves was used to identify vegetation attributes and its status. Vegetation Indices are calculated using mathematical formulae published in the previous study. Random forest classification used to discriminate among Healthy and Diseased plants. Algorithm works with an accuracy of 93.75% with misclassification rate 0.0625. Along with Green wavelength range and Red edge of the spectrum, specific disrupted behavior was observed in Shortwave Infrared Region of the spectra. The research paper focuses on Spectral and Numerical study and analysis of Tomato Leaf disease with the help of ASD FieldSpec4. Keywords: ASD FieldSpec4 Spectroradiometer Hyperspectral Remote Sensing, Vegetation Indices, VNIR-SWIR Spectroscopy, I. INTRODUCTION Hyperspectral Remote Sensing is the technique nowadays majorly considered to study vegetation. Babadoost M. et al studied about it that encourages non-destructive methods of identifying plant behavior and its properties [1]. Crop yield faces severe issues due to the challenging environment. Pests cause crop loss in India and it is almost 10-30% of the total crop production. Sreekala G. Bajwa et al stated that In order to manage diseases effectively, Disease Detection is the multidisciplinary approach that integrates with cultural, biological, physical and chemical strategies [2]. In order to analyze and to detect changes in plant physiology and chemistry, Spectral Vegetation Indices and its use play a vital role. Indices are based on sensitive waveband information and their significance directly relates to the presence of Water Content, Leaf Area, and Pigmentation status. A.K. Mahlein et al. observed and concluded that Vegetation indices play a crucial role to detect whether the plant is infected with disease or not infected [3]. Application of Spectroscopy consists of emission of Revised Manuscript Received on August 05, 2019 Nikhil M. Sapate : M.Tech (CSE, Second Year), Department of CS and IT, Dr. BAMU, Aurangabad Dr. R. R. Deshmukh : Professor, Professor and Former Head, Dept. CS and IT, Dr. BAMU, Aurangabad. electromagnetic radiation which interacts with pigment content, leaf structure and water content. Photosynthetic pigments, mainly chlorophyll and carotenoids absorb the electromagnetic radiation in visible region causing less reflectance. Alfadhl Yahya Khaled et al discussed that in short-wave near-infrared region also lack of reflectance due to structural discontinuities occurred in leaf [4]. Benjamin Dechant et al presented a study which stated Chlorophyll which is useful pigment for a plant to perform photosynthesis occurs in red wavelength [5]. Another important factor is Carotenoids and it absorbs energy and protects chlorophyll from photo-damage. One of the key carotenoids is xanthophyll. It also protects the plant from excessive sunlight energy and prevents plants from further damage. A third and equally important factor in plants health is Canopy. It is an uppermost or topmost layer of trees or branches. Carotenoids and Chlorophyll incorporate with each other to minimize the impact of variable canopy structure which automatically results in good health of plants. T. Rumpf et al stated in a study that these factors are affected during pathogenesis and it can be recorded and can be studied using Hyperspectral remote sensing and Vegetation Indices are found to be highly correlated to these physiological parameters [6]. A previous study established the use of such vegetation attributes such as water pigments, nitrogen-rich compound, structural materials and Vegetation Indices that can predict about the health status of plants. The bands in green, red and NIR of the spectrum are considered to be useful for it. So-Ra Kim, Lammert Kooistra, R. Devadas et al. stated that changes in the pigment can be observed with the spectral characteristics and it emphasizes on health-related aspect of plants [7, 8, 9]. The objectives of this study was to Collect Hyperspectral Non- Imaging data of crop Tomato, to perform spectral and numerical analysis of this data, to study Vegetation Indices and to study its relation with pigmentation and health of plant, to discriminate healthy and diseased plant using spectral and numerical analysis. II. EXPERIMENT A. Design of Experiment The study has shown that disease detection in plants can be performed promisingly with the help of Spectroscopy. Sindhuja Sankaran et al presented Biotic and Abiotic stresses in plants can be identified using Spectroscopy [10]. To perform these components in vegetation, ASD FieldSpec4 is a spectroradiometer used for laboratory tests. Spectral Range of this device is highly resolving and covers wavelength of 350-2500 nm. It has a Spectral and Numerical Analysis of Hyper spectral Data using Vegetation Indices Nikhil M. Sapate, Ratnadeep R. Deshmukh