Crop Improvement with Artificial Intelligence : Methods and Applications

個数：
  • 予約

Crop Improvement with Artificial Intelligence : Methods and Applications

  • 現在予約受付中です。出版後の入荷・発送となります。
    （重要：表示されている発売日は予定となり、発売が延期、中止、生産限定品で商品確保ができないなどの理由により、ご注文をお取消しさせていただく場合がございます。予めご了承ください。）

    ●3Dセキュア導入とクレジットカードによるお支払いについて
  • 【入荷遅延について】
    世界情勢の影響により、海外からお取り寄せとなる洋書・洋古書の入荷が、表示している標準的な納期よりも遅延する場合がございます。
    おそれいりますが、あらかじめご了承くださいますようお願い申し上げます。
  • ◆画像の表紙や帯等は実物とは異なる場合があります。
  • ◆ウェブストアでの洋書販売価格は、弊社店舗等での販売価格とは異なります。
    また、洋書販売価格は、ご注文確定時点での日本円価格となります。
    ご注文確定後に、同じ洋書の販売価格が変動しても、それは反映されません。
  • 製本 Hardcover:ハードカバー版／ページ数 448 p.
  • 言語 ENG
  • 商品コード 9781394330454

Full Description

Guide to the application of AI for crop improvement, including deployment in plant biology and crop breeding

Advancing Crop Improvement with Artificial intelligence provides a comprehensive overview of the integration of AI into crop development and farm management, highlighting the latest advancements and applications in the field. The book offers an exhaustive review of recent progress and implementations of AI in agriculture, covering a wide range of topics crucial for understanding the innovative potential of AI in crop enhancement.

Beginning with an exploration of the documented factors and potential for innovation in agriculture, the book introduces readers to the fundamental concepts of AI and its transformative impact on advanced farming methods. It delves into the various applications of AI in plant biology and breeding, from data collection and pre-processing to predictive analytics for crop yield and disease resistance.

The book also addresses ethical considerations and challenges in AI-enabled crop improvement and delivers insights into the prospects of employing AI for crop enhancement, underscoring the significance of genetic diversity, resource optimization, and ethical considerations.

Advancing Crop Improvement with Artificial intelligence discusses sample topics including:

Utilization of LLMs to improve analysis of agricultural data by interpreting intricate datasets and providing insights to enhance decision-making
Generative AI's role in developing innovative solutions and predictive models for better crop management, pest control, and resource distribution
Current challenges such as data constraints, economic feasibility, and untested technologies
Integration of multi-omics data with the latest applications and technologies, including functional genomics, phenotyping, high-throughput imaging, and genomic prediction in plants, to analyze complex traits and advance plant transcriptomics

Advancing Crop Improvement with Artificial intelligence is an essential resource for scholars, researchers, academics, agronomists, policymakers, and all other readers interested in capitalizing AI to address the hurdles of worldwide food security and encourage sustainable agricultural implementation.