Hopf Alwin, Watson Jonathan A, Swisher Mickie, Brym Zachary, Hoogenboom Gerrit
Department of Agricultural and Biological Engineering, Institute of Food and Agricultural Sciences, University of Florida, Gainesville, FL, 32611, USA.
Department of Family, Youth and Community Sciences, Institute of Food and Agricultural Sciences, University of Florida, Gainesville, FL, 32611, USA.
J Cannabis Res. 2025 Aug 20;7(1):62. doi: 10.1186/s42238-025-00318-3.
The recent legalization of industrial hemp () in Florida and across the US has sparked interest among established farmers and newcomers alike. However, the nascent industry faces challenges due to limited location-specific cultivation knowledge, evolving regulations, and market uncertainties. Agriculture technology such as crop growth models and decision support systems (DSS) can support sustainable hemp production in new regions. However, the adoption of such technologies is limited and requires participatory work with and study of DSS users for the development of appropriate technology.
This study explores the knowledge landscape, information needs, and attitudes towards decision support systems among hemp farmers in Florida through a series of semi-structured qualitative interviews.
We identified distinct farmer profiles, including established farmers seeking diversification, out-of-state hemp growers exploring Florida’s climate, hemp practitioners from non-agricultural backgrounds focused on quality, and first-time farmers driven by personal interest. Each profile exhibited unique motivations, information-seeking behaviors, and resource constraints. Agronomic challenges, such as pest and disease management, cultivar selection and time of planting were common concerns across all groups. Regulatory uncertainties and market volatility further compounded these challenges. While interest in DSS exists, particularly for addressing agronomic issues and optimizing decision-making, barriers such as cost, trust in model accuracy, and utility remain significant. Farmers expressed a preference for tailored, locally relevant DSS that offer actionable recommendations and integrate seamlessly into their existing workflows.
The study underscores the importance of participatory DSS development, involving farmers in the design and validation process to ensure the tools meet their specific needs and build trust. Insights from this research will contribute to the ongoing development of a process-based crop growth model and DSS specifically designed for Florida’s hemp production.
The online version contains supplementary material available at 10.1186/s42238-025-00318-3.
佛罗里达州及美国其他地区近期将工业大麻合法化，这引发了老牌农场主和新进入者的兴趣。然而，由于特定种植地点的知识有限、法规不断变化以及市场不确定性，这个新兴产业面临着挑战。诸如作物生长模型和决策支持系统（DSS）等农业技术可以支持新地区的可持续大麻生产。然而，此类技术的采用有限，并且需要与DSS用户进行参与式合作并对其进行研究，以开发合适的技术。
本研究通过一系列半结构化定性访谈，探讨了佛罗里达州大麻种植户对决策支持系统的知识状况、信息需求和态度。
我们确定了不同的农户类型，包括寻求多元化的老牌农户、探索佛罗里达州气候的州外大麻种植者、专注于品质的非农业背景大麻从业者以及受个人兴趣驱动的首次种植农户。每种类型都表现出独特的动机、信息寻求行为和资源限制。诸如病虫害管理、品种选择和种植时间等农艺挑战是所有群体共同关心的问题。监管不确定性和市场波动进一步加剧了这些挑战。虽然对决策支持系统存在兴趣，特别是用于解决农艺问题和优化决策，但成本、对模型准确性的信任以及实用性等障碍仍然很大。农户表示更喜欢量身定制的、与当地相关的决策支持系统，这些系统能提供可操作的建议并无缝融入他们现有的工作流程。
该研究强调了参与式决策支持系统开发的重要性，让农户参与设计和验证过程，以确保工具满足他们的特定需求并建立信任。这项研究的见解将有助于正在进行的基于过程的作物生长模型和专门为佛罗里达州大麻生产设计的决策支持系统的开发。
在线版本包含可在10.1186/s42238-025-00318-3获取的补充材料。
