SBIR Phase I: Improving indoor agriculture grow light efficiency with adaptive light shaping

SBIR 第一阶段：通过自适应光整形提高室内农业种植光效率

• 批准号: 2304339
• 负责人: Andrew Rape
• 金额: $ 27.45万
• 依托单位: LEAFICIENT INC
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-08-01 至 2024-07-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2304339&HistoricalAwards=false
• 关键词: SBIR; Phase; Improving; indoor; agriculture

The broader/commercial impact of this Small Business Innovation Research (SBIR) Phase I project is in accelerating the transition to a more sustainable food supply chain, which could democratize access to healthy foods and lessen food insecurity. The US system for growing and distributing fresh food is inefficient and insufficient in the context of climate change. Controlled environmental agriculture (CEA) is seen as a potentially revolutionary way to supply food demands with limited resources. Despite this promise, the high energy requirements of creating lighting and cooling in enclosed environments to support photosynthesis has caused CEA not to realize its promise. In the project, a novel solution to improve energy efficiency in CEA farms is proposed where advanced optics, machine learning, and computer vision are used to ensure that all of the light that is emitted by synthetic light sources is optimally used for plant photosynthesis and growth. The project offers a plausible way to create reliably profitable operations for CEA producers which would lead to enhanced access to fresh produce for consumers and decreased reliance on conventional agriculture to meet the world’s food needs.Within current commercial grow systems for controlled environment agriculture, a substantial portion of the photons are wasted as they are not incident onto photosynthetically active biomass and are absorbed by the surrounding grow rack and media. This project will prototype and systematically test a light production system that dynamically shapes light such that it is rendered only onto the photosynthetic areas of the plant. To accomplish this, the project will develop and evaluate (within three crop varieties) a closed-loop system to autonomously detect the three-dimensional shape of the growing plant and dynamically adjust the light intensity and projection area to optimize power efficiency and biomass growth. Successful completion of the work in this project will result in a novel technology that is systematically tested to yield similar quality produce using a fraction of the energy consumption of current state-of-the-art systems. Deployment of this technology would help to improve the unit economics of controlled environment agriculture produce items and accelerate adoption of controlled environment agriculture farming practices that potentially consume less water, utilize land resources more efficiently, and eliminate the need for chemical pesticide/herbicide treatments.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

该小企业创新研究 (SBIR) 第一阶段项目的更广泛/商业影响是加速向更可持续的食物链供应的过渡，这可以使健康食品的获取民主化并减少美国生鲜种植和分销系统的食品不安全状况。在气候变化的背景下，受控环境农业（CEA）被视为一种潜在的革命性方式，可以用有限的资源满足粮食需求，但在封闭环境中创造照明和冷却的能源需求很高。支持光合作用导致 CEA 未能实现其承诺。在该项目中，提出了一种提高 CEA 农场能源效率的新颖解决方案，其中使用先进的光学、机器学习和计算机视觉来确保合成发出的所有光。该项目为 CEA 生产商创造可靠盈利的运营提供了一种可行的方式，这将增加消费者获得新鲜农产品的机会，并减少对传统农业的依赖，以满足世界粮食需求。当前的在用于受控环境农业的商业种植系统中，很大一部分光子被浪费，因为它们没有入射到光合活跃的生物质上，而是被周围的生长架和介质吸收。该项目将对动态塑造的光生产系统进行原型设计和系统测试。为了实现这一目标，该项目将开发和评估（在三种作物品种内）一个闭环系统，以自动检测正在生长的植物的三维形状并动态地检测。调整光强度和投影面积以优化电力效率和生物量增长，该项目工作的成功完成将产生一项新技术，该技术经过系统测试，可使用当前状态的一小部分能源消耗生产类似质量的产品。 -艺术系统的部署将有助于提高受控环境农产品的单位经济效益，并加速采用受控环境农业耕作方法，这些方法可能消耗更少的水，更有效地利用土地资源，并消除对化学农药的需求。除草剂处理。该奖项反映了通过使用基金会的智力价值和更广泛的影响审查标准进行评估，NSF 的法定使命被认为值得支持。