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.

这项小型企业创新研究（SBIR）I阶段项目的更广泛/商业影响是加速向更可持续的食品供应链过渡，这可以使获得健康食品的机会民主化，而粮食不安全感则更少。在气候变化的背景下，美国种植和分发新鲜食品的制度效率低下且不足。受控的环境农业（CEA）被视为一种潜在的革命性方式，可以用有限的资源提供食物需求。尽管有这样的承诺，但在封闭环境中创建照明和冷却以支持光合作用的高能量需求使CEA无法实现其承诺。在该项目中，提出了一种新的解决方案，以提高CEA农场的能源效率，其中使用高级光学，机器学习和计算机视觉来确保合成光源发出的所有光线都最佳地用于植物光合作用和生长。 The project offers a plausible way to create reliable profitable operations for CEA producers which would lead to enhanced access to fresh produce for consumers and developed reliability on conventional agreeable relationship to meet the world’s food needs.Within current commercial growth systems for controlled environment reform, a substantial portion of the photos are wasted as they are not incident onto photosynthetically active biomass and are absorbed by the surrounding growing rack and media.该项目将原型制作并系统地测试一个动态塑造光的光生产系统，以便仅将其渲染到植物的光合作用区域上。为此，该项目将开发和评估（在三种农作物变化中）一个闭环系统，以自主检测生长植物的三维形状，并动态调整光强度和投影面积，以优化功率效率和生物量的生长。成功完成该项目的工作将导致一项新型技术，该技术经过系统测试，以使用当前最新系统的能源消耗的一小部分产生类似的质量生产。这项技术的部署将有助于改善受控环境农业的单位经济学生产物品，并加速采用受控环境农业农业耕作实践，这些农业耕作实践可能减少水的水量，更有效地利用土地资源，并消除了对化学农药/除草剂的需求，这些奖项通过评估NSF的智力传播范围，以表现出众多的依据。 标准。