International Journal on Science and Technology

E-ISSN: 2229-7677   •   Impact Factor: 9.88

A Widely Indexed Open Access Peer Reviewed Multidisciplinary Bi-monthly Scholarly International Journal

Call for Paper Volume 17 Issue 3 July-September 2026 Submit your research before last 3 days of September to publish your research paper in the issue of July-September.
Submit Research Paper Join as a Reviewer

Plagiarism is checked by the leading plagiarism checker TurnItIn

Call for Paper

Volume 17 Issue 3
July-September 2026

Submit your research paper

Indexing Partners
Academia Advanced Sciences Index Bielefeld Academic Search Engine CiteSeer DRJI Google Scholar Independent Search Engine & Directory Network ISI (International Scientific Indexing) Issuu Mendeley Research Networks
RefSeek ResearcherId - Thomson Reuters ResearchGate Scirus Scribd Semantic Scholar UTeM - Universiti Teknikal Malaysia Melaka Wiki for Call for Papers WorldCat Zenodo

Development of Leaf Extract Spectral Database for Plant Species Classification Using Liquid Light Guide Spectroscopy

Author(s) Gaju S. Chavan, Dr. Sonali B. Kulkarni, Simran N. Maniyar
Country India
Abstract Plant species identification is crucial in agriculture, conservation of biodiversity, forestry, medicinal plant authentication and precision farming. The traditional identification using morphological features is often time consuming, requires expert knowledge and has limitations due to environmental changes and seasonal variations. In this study, developed a standard library of leave extracts spectra for automatic plant species identification using transmission spectroscopy. Fresh, healthy leaves were used to prepare leaf extracts which were developed spectral library using the ASD FieldSpec4 spectroradiometer with Liquid Light Guide (LLG) over the spectral range of 350–2500 nm in the visible (VIS), near infrared (NIR), and short-wave infrared (SWIR) spectral regions. Several biological samples were taken for each plant species and 10 spectra were recorded for each sample after calibration with dark and blank samples to increase the reliability of the measurements. The recorded spectra were averaged and prepared in a hierarchical spectra database based on species, biological material and repeated spectrum acquisition. Proposed transmission spectroscopy is a different method to conventional reflectance spectroscopy, which is able to measure biochemical signatures related to pigments, water, carbohydrates, proteins and other metabolites in leaf extracts. This spectral database will be use as a credible basis for the spectral pre-processing, machine learning and plant species classification based on artificial intelligence. This effort provides a standardized dataset that facilitates the development of strong, repeatable and non-destructive plant identification systems for future use in the agricultural and environmental domains.
Keywords : Liquid Light Guide, Spectral Transmission, biodiversity, Plant Species, Spectroscopy.
Field Computer Applications
Published In Volume 17, Issue 3, July-September 2026
Published On 2026-08-02
View / Download PDF File

Share this


CrossRef

Crossref DOI prefix of IJSAT is 10.71097/IJSAT

Downloads
Research Paper Format Copyright Permission Form and Undertaking Form Cover Page Vol 17 Isu 2Cover Page Vol 17 Isu 1Cover Page Vol 16 Isu 4

All research papers published on this website are licensed under Creative Commons Attribution-ShareAlike 4.0 International License, and all rights belong to their respective authors/researchers.

CC-BY-SA Open Access

About IJSAT
Fees & Payment
Current Issue
Publication Archive 		Submit Research Paper
Track Submission Status
Publication Guidelines
Publication Ethics 		Join as a Reviewer
Editors & Reviewers
Get Reviewer Membership Certi. 		Website/Journal Policies
Usage Policy
Content Policies
Privacy Policy
Contact Us Message on WhatsApp +91-9687-182-185 editor@ijsat.org