SBIR Phase I: A real-time precision nutrient analysis and management system for hydroponic farming operations

SBIR 第一阶段：用于水培农业作业的实时精确养分分析和管理系统

• 批准号: 2210046
• 负责人: Carlos Hayden
• 金额: $ 25.6万
• 依托单位: ENVONICS LLC
• 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: 2023-02-15 至 2025-01-31
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2210046&HistoricalAwards=false
• 关键词: SBIR; Phase; real; time; precision

The broader impact of this Small Business Innovation Research (SBIR) Phase I project is to promote the viability and sustainability of small-to-medium indoor, urban, and controlled environment agriculture (CEA) farms. As the global population grows to 10 billion by 2050, the agriculture industry will need to produce 70% more food using only 5% more land. Indoor farming can make a significant contribution to meet this demand sustainably. Indoor farmers are also seasonally and geographically independent, which means they can help meet demands for locally produced fresh foods and are protected from extreme weather events. These farms primarily use soilless growing methods, such as hydroponics, that currently suffer from critical needs for efficient and affordable methods to monitor and manage nutrients and water in order to be financially viable and environmentally sustainable. The proposed project provides an innovative solution for nutrient management in hydroponic farming, thereby lowering the costs, increasing the yield potential, and supporting the viability of such farms. By supporting the expansion of the national hydroponics industry, this project will increase the local production of and expand access to fresh produce.This SBIR Phase I project will develop a nutrient management system to provide CEA farmers with real-time information about the nutrients in the growth solution of their crops. The proposed solution will utilize ion-selective electrode (ISE) technology and a decision support system powered by machine learning (ML). This project will focus on the critically needed engineering and data analytics research and development to de-risk major technical challenges in the development of the nutrient management system, providing proof-of-feasibility. The key objectives of this project are to: 1) design a special chamber for the sensors to minimize the interference and increase accuracy, 2) validate the feasibility and accuracy of this new design in a greenhouse setting, 3) develop a predictive algorithm to automatically calibrate the sensors, and 4) measure and predict deficiencies in leafy greens production: collecting empirical evidence of nutrient deficiency to train ML models to identify, and ultimately, predict a deficiency prior to when it is observable.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期项目的更广泛影响是促进室内，城市和受控环境农业（CEA）农场的可行性和可持续性。随着到2050年的全球人口增长到100亿，农业行业只需要使用5％的土地生产70％的食物。室内农业可以为可持续地满足这一需求做出重大贡献。室内农民在季节性和地理上都独立于室内，这意味着他们可以帮助满足对当地生产的新鲜食品的需求，并受到极端天气活动的保护。这些农场主要使用诸如水培法之类的Soilless生长方法，这些方法目前遭受了对高效且负担得起的方法监测和管理养分和水的关键需求，以便在财务上可行且在环境上可持续。拟议的项目为水培农业中的营养管理提供了创新的解决方案，从而降低了成本，增加了产量的潜力并支持此类农场的生存能力。通过支持国家水培工业的扩展，该项目将增加本地生产并扩大对新鲜农产品的访问。该SBIR I阶段项目将开发一种营养管理系统，为CEA农民提供有关其农作物增长溶液中营养的实时信息。 拟议的解决方案将利用离子选择电极（ISE）技术和由机器学习（ML）提供支持的决策支持系统。该项目将着重于急需的工程和数据分析研究和开发，以降低养分管理系统开发的主要技术挑战，从而提供可行性证明。该项目的关键目的是：1）设计一个特殊的室，以最大程度地减少干扰和提高准确性，2）在温室环境中验证这种新设计的可行性和准确性，3）3）开发一种预测性算法，以自动校准这些传感器，并为识别型号的型号训练和预测nutigy nutivicies nuty nutical of nutial semient of nutial sigri and forn groun：在可观察到的情况下，预测缺陷。该奖项反映了NSF的法定任务，并被认为是值得通过基金会的知识分子优点和更广泛影响的评论标准来评估值得支持的。