Advancing Controlled Environment Agriculture (CEA) with Dynamic LED Lighting Systems and Artificial Intelligence

利用动态 LED 照明系统和人工智能推进受控环境农业 (CEA)

• 批准号: BB/Z514330/1
• 负责人: Hail Rihan
• 金额: $ 97.6万
• 依托单位: Plymouth University
• 依托单位国家: 英国
• 项目类别: Research Grant
• 财政年份: 2024
• 资助国家: 英国
• 起止时间: 2024 至 无数据
• 项目状态: 未结题
• 来源: https://gtr.ukri.org/projects?ref=BB%2FZ514330%2F1
• 关键词: Advancing; Controlled; Environment; Agriculture; CEA

Controlled Environment Agriculture (CEA) holds significant commercial importance in modern agriculture. Among the key factors for CEA to succeed is the use of LED (Light Emitting Diode) light fittings which can be adjusted to reflect natural environments. LEDs allow the manipulation of light wavelengths, enabling light to be customised for specific crop needs. By tailoring light, CEA growers can optimise plant growth, enhance photosynthesis and influence various plant characteristics, such as taste, colour, and nutritional content. This level of control improves crop yield, quality and consistency, making CEA an attractive option for commercial growers seeking sustainable and efficient methods to meet increasing global food demand and those interested in health and medical markets.We aim to advance the field of CEA by integrating dynamic LED lighting systems and artificial intelligence (AI) techniques. By leveraging cutting-edge technology we seek to optimise plant growth, increase productivity and enhance the resource efficiency of CEA.Our lighting system will be connected to a net of spectrophotometers (instruments which measure the intensity and spectra of light) distributed across the canopy above the plants. This will be coupled to advanced software that processes data from the sensors and manages the light output. This will help to optimise photosynthesis and growth patterns, resulting in improved plant health and increased crop yields and qualities. We will use AI to analyse real-time environmental data within the CEA facility. By integrating sensors, we will gather data on light levels and spectra and other relevant parameters. We will also collect data on plant responses to lighting conditions, for example, how they absorb and reflect light. The AI system will then make data-driven decisions to adjust the environmental conditions, specifically lighting but also other environmental conditions (temperature and CO2). This will determine if we can maximise light absorbance and minimising to maximise the rate of photosynthesis. Additionally, our proposed system will enable us to detect the chemical profile of plants based on their reaction to various light treatments (spectroscopy techniques). By precisely tailoring environmental conditions we can reduce energy usage and achieve better resource allocation, resulting in cost savings and environmental sustainability.The proposed project will have numerous scientific and commercial applications. It will benefit grow light manufacturers by providing an advance control system that is able to control the light spectrum, regardless of ambient conditions. Through this research we will contribute to the next generation of LED grow lights. It will help growers by providing sustainable lighting that promote plant growth and quality and save energy. The proposed project will also have a substantial impact on the potential use of plants in the pharmaceutical industry and will thus be of benefit to pharmaceutical companies as well as growers. The benefits of the systems developed will not be limited to the CEA but will apply also to the greenhouse industry, since stabilising lighting conditions (intensity and spectra) through the proposed system will help to stabilise the chemical profile of plants grown in greenhouse conditions.

受控环境农业（CEA）在现代农业中具有重要的商业重要性。 CEA成功的关键因素之一是使用LED（发光二极管）光配件，可以调整以反映自然环境。 LED允许操纵光波长，从而可以根据特定的作物需求定制光。通过调整光，CEA种植者可以优化植物的生长，增强光合作用并影响各种植物特征，例如味道，颜色和营养含量。这种控制水平提高了农作物的产量，质量和一致性，使CEA成为寻求可持续和有效的方法来满足全球粮食需求以及对健康和医疗市场感兴趣的商业种植者的吸引人选择。我们旨在通过整合动态LED照明系统和人工智能（AI）技术来推进CEA领域。通过利用最先进的技术，我们试图优化植物的生长，提高生产率并提高CEA的资源效率。我们的照明系统将连接到分布在植物上方整个冠层的分光光度计计（测量光强度和光谱的仪器）的网。这将与高级软件结合起来，该软件从传感器中处理数据并管理光输出。这将有助于优化光合作用和增长模式，从而改善植物健康，并提高农作物的产量和品质。我们将使用AI分析CEA设施中的实时环境数据。通过集成传感器，我们将收集有关光级，光谱以及其他相关参数的数据。我们还将收集有关植物对照明条件的反应的数据，例如，它们如何吸收和反射光。然后，AI系统将做出数据驱动的决策，以调整环境条件，特别是照明以及其他环境条件（温度和CO2）。这将确定我们是否可以最大化光吸光度并最小化以最大程度地提高光合作用速度。此外，我们提出的系统将使我们能够根据植物对各种光处理（光谱技术）的反应来检测其化学特征。通过精确调整环境条件，我们可以减少能源的使用并获得更好的资源分配，从而节省成本和环境可持续性。拟议的项目将具有许多科学和商业应用。它将通过提供能够控制光谱的预先控制系统（无论环境条件如何），从而使生长制造商受益。通过这项研究，我们将为下一代LED型灯光做出贡献。它将通过提供可持续的照明来帮助种植者，从而促进植物的生长和质量并节省能源。拟议的项目还将对制药行业中植物的潜在使用产生重大影响，因此对制药公司和种植者有益。开发的系统的好处将不仅限于CEA，但也将适用于温室行业，因为通过拟议的系统稳定照明条件（强度和光谱）将有助于稳定在温室条件下生长的植物的化学轮廓。