美国农业部发起 AI 育种挑战赛,利用种质资源数据加速作物育种

人工智能正在重塑现代种业的研发范式。美国农业部计划于 2026 年下半年推出全国 AI 专项挑战赛，依托国家级算力平台，面向跨学科团队征集 AI 分析工具，深度挖掘海量种质与遗传数据集。项目旨在缩短育种周期，培育高产、抗病、抗气候胁迫的作物品种。

注：第一部分为英文文章及音频，第二部分为中英双语文章

（本文仅用于学习用途，For non-commercial educational use only）

英文文章及音频：（530 Words）

USDA to launch AI challenge for faster crop breeding using germplasm data

From: AgroSpectrumAsia

The U.S. Department of Agriculture (USDA) is preparing to launch a nationwide artificial intelligence initiative aimed at transforming crop breeding by enabling researchers to extract insights more rapidly from the agency's extensive germplasm and plant genetics datasets. Expected to be introduced later in 2026, the Agricultural National Science and Technology Challenge will encourage researchers, technology developers and interdisciplinary teams to create AI-powered tools capable of accelerating plant breeding and crop improvement.

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中英双语文章：

USDA to launch AI challenge for faster crop breeding using germplasm data

美国农业部将推出 AI 挑战赛，利用种质资源数据加速作物育种

来源：AgroSpectrumAsia

The U.S. Department of Agriculture (USDA) is preparing to launch a nationwide artificial intelligence initiative aimed at transforming crop breeding by enabling researchers to extract insights more rapidly from the agency's extensive germplasm（种质资源） and plant genetics datasets. Expected to be introduced later in 2026, the Agricultural National Science and Technology Challenge will encourage researchers, technology developers and interdisciplinary（跨学科的） teams to create AI-powered tools capable of accelerating plant breeding and crop improvement.

美国农业部（USDA）即将推出一项全国人工智能专项行动，旨在改变作物育种工作：让研究人员可以从该机构海量的种质资源与植物遗传数据集中，更快挖掘有效科研信息。农业国家科技挑战赛预计将于 2026 年下半年正式启动，该赛事鼓励科研人员、技术开发团队以及跨学科研究小组开发 AI 工具，以此加快植物育种与作物改良进程。

The initiative forms part of the federal government's broader effort to integrate advanced computing and artificial intelligence into agricultural research to strengthen food security, improve crop productivity and enhance resilience（韧性、抗逆性） to climate-related stresses.

该专项行动是美国联邦政府宏大规划的一部分，目标是把先进计算与人工智能融入农业科研，夯实粮食安全基础，提升作物产能，增强作物应对气候胁迫的抗逆能力。

AI to Unlock Value from Complex Agricultural Data

人工智能挖掘复杂农业数据的内在价值

Under the proposed challenge, participating teams will develop analytical platforms capable of processing multiple forms of agricultural data simultaneously（同时地）. The AI systems are expected to combine information from crop imagery, field observations, laboratory analyses and germplasm datasets to identify valuable genetic traits（遗传性状） and plant characteristics with greater speed and accuracy than conventional research methods.

按照挑战赛的方案，参赛团队需要开发分析平台，可同时处理多种类型的农业数据。这套人工智能系统需要整合作物影像、田间观测记录、实验室分析结果、种质资源数据集，相比传统科研手段，能够更快、更精准挖掘出具备价值的遗传性状与植物特征。

By improving the interpretation（解析） of complex biological data, the initiative aims to shorten breeding cycles（育种周期） and help scientists identify promising crop traits more efficiently, supporting the development of higher-yielding, disease-resistant and climate-resilient crop varieties. The USDA believes advanced AI models could significantly reduce the time required to translate genetic information into practical breeding outcomes for agricultural producers.

该项目希望通过优化复杂生物数据的解析能力，缩短育种周期，帮助科研人员更加高效筛选优良作物性状，助力培育高产、抗病、气候适应性强的作物品种。美国农业部认为，先进 AI 模型可以大幅缩短从遗传信息转化为可供农业生产者实际使用育种成果的时间。

National Research Infrastructure to Support Participants

国家级科研基础设施为参赛团队提供支撑

Teams selected for the competition will receive access to the American Science and Security Platform, a national scientific infrastructure led by the U.S. Department of Energy. The platform connects high-performance computing resources, advanced research facilities, scientific datasets and artificial intelligence tools, providing participants with large-scale computational capabilities for analysing complex agricultural information.

竞赛入选团队可访问美国科学与安全平台，这是一套由美国能源部牵头搭建的国家级科研基础设施。该平台整合高性能计算资源、尖端科研设施、科研数据集以及人工智能工具，为参赛队伍提供大规模算力，用于解析复杂农业信息。

The infrastructure is designed to encourage collaboration among federal laboratories, universities, research institutions and private-sector technology companies working on next-generation scientific applications.

这套基础设施旨在推动联邦实验室、高校、科研机构与私营科技企业开展协作，共同开发下一代科学应用。

Part of the Federal Genesis Mission

隶属于联邦 “创世纪计划”

The AI challenge will be delivered（实施、承办） through the Agriculture Advanced Research and Development Authority (AgARDA) in collaboration with the federal Genesis Mission, an initiative established by executive order（行政命令） in November 2025 to accelerate scientific discovery through advanced computing and cross-sector collaboration. The Genesis Mission seeks to apply artificial intelligence and high-performance computing across multiple scientific disciplines, with agriculture emerging as one of its priority application areas.

本次 AI 挑战赛由农业高级研究与开发局（AgARDA）承办，并联动联邦创世纪计划（Genesis Mission）共同推进。创世纪计划是 2025 年 11 月通过行政命令设立的国家级项目，目标依靠先进计算与跨行业协作加速科学发现。创世纪计划致力于在多个科学领域落地人工智能与高性能计算，农业是其重点应用方向之一。

For crop science, the programme is expected to strengthen the integration of computational biology, genomics（基因组学） and plant breeding, enabling researchers to analyse increasingly complex biological datasets that were previously difficult to process at scale.

在作物科学领域，该项目将强化计算生物学、基因组学与植物育种之间的融合，让研究人员能够解析以往难以大规模处理的复杂生物数据集。

Competition Details Expected Later This Year

竞赛更多细节将于今年晚些时候公布

While the USDA has confirmed plans to launch the competition during 2026, additional programme details—including funding levels, eligibility（资格） criteria, submission requirements and application timelines—have yet to be announced. The department is expected to release further information as the challenge moves toward implementation（落地实施）.

尽管美国农业部已经确认将在 2026 年举办本次竞赛，但项目其余细节，包括经费规模、参赛资格、提交要求与申报时间尚未对外发布。随着挑战赛筹备推进，农业部预计会对外公布更多相关信息。

As governments worldwide increasingly invest in AI-driven agricultural innovation, the USDA's planned initiative highlights the growing role of machine learning and advanced data analytics in modern plant breeding. By combining large-scale germplasm resources with next-generation computational tools, the programme aims to accelerate the development of crop varieties capable of meeting future food production and climate resilience challenges.

全球各国政府都在持续加大对 AI 驱动农业创新的投入，美国农业部本次计划的专项行动，也凸显机器学习与高级数据分析在现代植物育种中发挥越来越重要的作用。通过把大规模种质资源和新一代计算工具相结合，该项目希望加快作物品种研发，以此应对未来粮食生产与气候抗逆的各类挑战。

- 词汇盘点 -

germplasm、interdisciplinary、resilience、simultaneously、genetic traits、interpretation、breeding cycles、deliver、executive order、genomics、eligibility、implementation

|来源：双语智慧农业LearnSomeAgtech