Data-centric technology has not undergone widespread adoption in production agriculture but could address global needs for food security and farm profitability. Participants in the U.S. Department of Agriculture (USDA) National Institute for Food and Agriculture (NIFA) funded conference, “Identifying Obstacles to Applying Big Data in Agriculture,” held in Houston, TX, in August 2018, defined detailed scenarios in which on-farm decisions could benefit from the application of Big Data. The participants came from multiple academic fields, agricultural industries and government organizations and, in addition to defining the scenarios, they identified obstacles to implementing Big Data in these scenarios as well as potential solutions. This communication is a report on the conference and its outcomes. Two scenarios are included to represent the overall key findings in commonly identified obstacles and solutions: “In-season yield prediction for real-time decision-making”, and “Sow lameness.” Common obstacles identified at the conference included error in the data, inaccessibility of the data, unusability of the data, incompatibility of data generation and processing systems, the inconvenience of handling the data, the lack of a clear return on investment (ROI) and unclear ownership. Less common but valuable solutions to common obstacles are also noted.

中文翻译：

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会议报告，“识别农业大数据应用的障碍”

以数据为中心的技术尚未在生产性农业中得到广泛采用，但可以满足全球对粮食安全和农场盈利能力的需求。2018 年 8 月在德克萨斯州休斯顿举行的美国农业部 (USDA) 国家粮食和农业研究所 (NIFA) 资助的会议“识别农业大数据应用的障碍”的参与者定义了详细的场景，其中：农场决策可以受益于大数据的应用。参与者来自多个学术领域、农业行业和政府组织，除了定义场景外，他们还确定了在这些场景中实施大数据的障碍以及潜在的解决方案。本通讯是关于会议及其成果的报告。包括两个场景来代表常见障碍和解决方案的总体关键发现：“实时决策的当季产量预测”和“母猪跛足”。会议上发现的常见障碍包括数据错误、数据不可访问、数据不可用、数据生成和处理系统不兼容、处理数据不便、缺乏明确的投资回报 (ROI) 和不清楚所有权。还指出了针对常见障碍的不太常见但有价值的解决方案。数据生成和处理系统的不兼容、处理数据的不便、缺乏明确的投资回报 (ROI) 和所有权不明确。还指出了针对常见障碍的不太常见但有价值的解决方案。数据生成和处理系统的不兼容、处理数据的不便、缺乏明确的投资回报 (ROI) 和所有权不明确。还指出了针对常见障碍的不太常见但有价值的解决方案。