Real-Time Sensing and Control of Integrative Horticultural Lighting Systems

Dorukalp Durmus

doi:10.3390/j3030020

Abstract

Optical radiation, including light, plays a crucial role in the structural development of plants through photomorphogenesis and the response to environmental changes. However, plant sensitivity to optical radiation widely varies across species. While research efforts are currently underway to discover the fundamentals of plant physiology, light sources with preprogrammed light settings (light recipes) are offered to clients to expedite plant growth. Since horticultural lighting research is in its infancy, prescribed lighting conditions are not likely to address every plants’ needs in terms of the spatial and spectral distribution, intensity, and duration of the light sources. However, it is possible to imagine an intelligent horticultural lighting system that can diagnose plants through sensors, and adjust the light intensity, the spatial and spectral distribution for the specific plant species with active feedback. Such an advanced real-time horticultural lighting system would consist of sensors to detect physiological markers from plants and environmental factors and an artificial intelligence algorithm to adjust the output. While the underlying technology for a real-time optimization system exists, the implementation and training would require further research.

Highlights

The increasing food and energy demand, the need to control CO2 emission, and the catastrophic effects of climate change are major problems that humankind is facing today
Increasing the efficiency of food production while reducing energy demand requires a multidisciplinary effort encompassing agriculture, engineering, and biological and physical sciences. As part of this multidisciplinary effort, horticultural science focuses on cultivation, plant propagation, plant breeding, crop production, and plant physiology
Horticultural studies concentrate on fruits, vegetables, nuts, and ornamental plants [1], in contrast to agriculture, which contains large-scale crop production and animal husbandry

Summary

Introduction

The increasing food and energy demand, the need to control CO2 emission, and the catastrophic effects of climate change are major problems that humankind is facing today. The conversion efficiency of natural photosynthesis (i.e., solar energy to biomass) in green plants is surprisingly low, between 4.6% and 6% [2] This process can be increased by optimizing the lighting to meet the sensitivity curve of photosensitive pigments in plants [3]. To address the challenges in meeting horticultural lighting systems, here a connected lighting system is described that detects environmental and plant-related factors and adjusts the amount and spectrum of the light output in real time using machine learning techniques, improving the quality and quantity of the yield. Despite the initial efficiency of produce production (reduced product growth time), and reduced use of technical challenges and costs that are innate to any automated system, an integrative horticultural pharmaceuticals. Quality of produce should be the primary optimization goal for any sustainable system

Precision Agriculture

Light Optimization

Findings

Light Optimization for Horticulture