rdf-syntax-grammar
mods:
  schema location: http://www.loc.gov/mods/v3 http://www.loc.gov/standards/mods/v3/mods-3-2.xsd
  title info:
    title: Machine learning for plant biology
  name:
    name part: Chen, Jen-Tsung
    role:
      role term: creator
    role:
      role term: author.
  type of resource: text
  genre: Electronic books.
  origin info:
    place:
      place term: nju
    date issued: 2026
    copyright date: 2026
    issuance: monographic
  language:
    language term: eng
  physical description:
    form: remote
    extent: 1 online resource
  abstract: A comprehensive and current summary of machine learning-based strategies for constructing digital plant biology Machine Learning for Plant Biology provides a comprehensive summary of the latest developments in machine learning (ML) technologies, emphasizing their role in analyzing complex biological networks of plants and in modeling the responses of major crops to biotic and abiotic stresses. The combinatorial strategies discussed in this book enable readers to further their understanding of plant biology, stress physiology, and protection. Machine Learning for Plant Biology includes information on: Intelligent breeding for stress-resistant and high-yield crops, contributing to sustainable agriculture, the Sustainable Development Goals (SDGs), and the Paris Agreement Interactions between plants, pathogens, and environmental stresses through omics approaches, functional genomics, genome editing, and high-throughput technologies State-of-the-art AI tools, including machine and deep learning models, as well as generative AI Applications include species identification, systems biology, functional genomics, genomic selection, phenotyping, synthetic biology, spatial omics, plant disease diagnosis and protection, and plant secondary metabolism Machine Learning for Plant Biology is an essential reference on the subject for scientists, plant biologists, crop breeders, and students interested in the development of sustainable agriculture in the face of a changing global climate.
  note: edited by Jen-Tsung Chen.
  subject:
    topic: Botany
    topic: Mathematical models
  subject:
    topic: Machine learning
  classification: QK46.5.M3 M33 2026
  classification: 580.28
  related item:
    identifier: (DLC) 2025027934
  identifier: 9781394329649
  identifier: 1394329644
  identifier: 9781394329632
  identifier: 1394329636
  identifier: 9781394329618
  identifier: 139432961X
  identifier: http://proxy.library.tamu.edu/login
  record info:
    record content source: NhCcYBP
    record creation date: 251112
    record change date: 20260215001245.3
    record identifier: in00005690556
    language of cataloging:
      language term: eng