ItemBook Chapter

Bioinformatics Tools and Deep Learning for Plant High-Throughput Phenotyping and Phenomics

Title
Bioinformatics Tools and Deep Learning for Plant High-Throughput Phenotyping and Phenomics
Creator
Arthi, Gunasekaran; Loganathan, Murugesan; Abidharini, Jothi Dheivasikamani; Balamuralikrishnan, Balasubramanian; Arun, Meyyazhagan; Manikantan, Pappuswamy; Prabhu, Jeyabal Philomenathan Antony; Anand, Arumugam Vijaya
Description
High-throughput phenotyping and phenomics are essential for advancing plant research and improving crop performance. The integration of bioinformatics tools and deep learning methodologies has transformed the way data is processed and analyzed in these fields. Bioinformatics tools facilitate the management and interpretation of large-scale genomic and phenotypic data, enabling researchers to extract valuable insights. Deep learning algorithms, particularly convolutional neural networks, have shown significant promise in automating the analysis of complex plant images and enhancing trait identification and prediction. This synergy between bioinformatics and deep learning accelerates the identification of key traits, improves the precision of phenotypic assessments, and supports the development of more resilient and productive crops. This chapter highlights how these advanced technologies contribute to more effective and scalable plant phenotyping and phenomics efforts. 2025 selection and editorial matter, Jen-Tsung Chen; individual chapters, the contributors.
Source
Plant High-Throughput Phenotyping and Functional Phenomics;pp.1-18
Date
01-01-2025
Publisher
CRC Press
Coverage
Arthi G., Department of Human Genetics and Molecular Genetics, Bharathiar University Coimbatore, Tamil Nadu, India; Loganathan M., Department of Human Genetics and Molecular Genetics, Bharathiar University Coimbatore, Tamil Nadu, India; Abidharini J.D., Department of Human Genetics and Molecular Genetics, Bharathiar University Coimbatore, Tamil Nadu, India; Balamuralikrishnan B., Department of Food Science and Biotechnology, Sejong University, Seoul, South Korea; Arun M., Department of Life Science, CHRIST University, Karnataka, Bangalore, India; Manikantan P., Department of Life Science, CHRIST University, Karnataka, Bangalore, India; Prabhu J.P.A., Department of Human Genetics and Molecular Genetics, Bharathiar University Coimbatore, Tamil Nadu, India; Anand A.V., Department of Human Genetics and Molecular Genetics, Bharathiar University Coimbatore, Tamil Nadu, India
Rights
Restricted Access; Hardcopy may be available in the library
Relation
ISBN: 978-104036036-1; 978-103282181-8;
Format
online
Language
English
Type
Book chapter

Citation

Arthi, Gunasekaran; Loganathan, Murugesan; Abidharini, Jothi Dheivasikamani; Balamuralikrishnan, Balasubramanian; Arun, Meyyazhagan; Manikantan, Pappuswamy; Prabhu, Jeyabal Philomenathan Antony; Anand, Arumugam Vijaya, “Bioinformatics Tools and Deep Learning for Plant High-Throughput Phenotyping and Phenomics,” CHRIST (Deemed To Be University) Institutional Repository, accessed June 18, 2026, https://archives.christuniversity.in/items/show/24350.

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