An integrated Approach Artificial Intelligence (AI) in Botany

Authors

  • Yogita S. Patil Department of Botany, M. P. H. Mahila Mahavidyalaya, Malegaon Camp, Nasik

Keywords:

Artificial Intelligence (AI), Botany

Abstract

Artificial Intelligence (AI) is progressively changing the field of botany by enabling quicker, more exact, and data-driven examination of plant systems. Through methods such as machine learning, deep learning, and computer vision, AI supports automated plant identification, disease and pest detection, phenotypic characteristic investigation, and prediction of plant development and efficiency. The integration of AI with inaccessible detecting, genomic information, and natural checking has upgraded exactness farming, accelerated plant breeding programs, and moved forward biological system management. Besides, AI-based models help in understanding plant reactions to climate change and in conserving endangered species by analyzing large-scale environmental datasets. In spite of challenges related to data quality, model interpretability, and availability, AI presents significant opportunities to advance botanical investigate and advance economical plant management.

Downloads

Download data is not yet available.

References

1. Bhoi, C., & Mahali, S. (2024). The Role of Artificial Intelligence Used in Plant Science: A Review. Asian Journal of Research in Botany, 7(2), 263-272.

2. Botany with Parul - Applications `of AI in Plant Phenotyping.Grace D Tan, Ushasi Chaudhuri, Sebastian Varela, Narendra Ahuja, Andrew D B Leakey, Machine learning-enabled computer vision for plant phenotyping: a primer on AI/ML and a case study on stomatal patterning, Journal of Experimental Botany, Volume75, Issue21,1November2024, Pages 6683-6703,

4. Gupta, D. K., Pagani, A., & Singh, A. K. (2024). AI-powered revolution in plant sciences: advancements. Exploration of Foods and Foodomics, 2, 443–45

5. Integrating AI in plant science: A review of applications and future prospects - Plant Gene (ScienceDirect, 2025).

6. Machine learning-enabled computer vision for plant phenotyping - Journal of Experimental Botany (2024).

7. MDPI Topical Collection: Application of AI in Plants — Plants (MDPI)..

Downloads

Published

2026-05-30

How to Cite

Yogita S. Patil. (2026). An integrated Approach Artificial Intelligence (AI) in Botany. International Journal of Life Sciences, 14(1A), 367–369. Retrieved from https://ijlsci.in/ls/index.php/home/article/view/1645

Issue

Vol. 14 No. 1A (2026): International Journal of Life Sciences

Section

Seed Science & Plant Physiology

License

Copyright (c) 2026 Author

Creative Commons License

This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license unless indicated otherwise in a credit line to the material. If the material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/ licenses/by/4.0/