Measuring Photosynthetic Photon Flux Density in the Blue and Red Spectrum for Horticultural Lighting Using Machine Learning Methods
Abstract
This article presents development of a low-cost sensor to measure the light intensity for plant growth, referred to as photosynthetic photon flux density (PPFD), which is a quantum light measurement unit for horticultural LED lighting. The total PPFD is comprised of daylight and supplemental LED lights in the red and blue photosynthesis wavebands with peak wavelengths at 660 and 457 nm, respectively. To this end, a multiwaveband spectral light sensor is utilized along with an accurate spectroradiometer reference sensor for calibration. A comparative study of machine learning-based methods is presented to obtain the sensor coefficients for measuring the PPFD, indicating that the decision tree and random forest models exhibit low mean absolute percentage errors (MAPEs) of 0.01%–0.88% for red and blue channels, respectively; but may lead to data over-fitting in real-time applications because of their complexity. However, the simple multilinear regression method yields MAPEs of 0.98% and 0.84% for red and blue channels, respectively, which may be better suited for real-time applications. As a use-case scenario, the calibrated PPFD sensor was experimentally tested on a hydroponic testbed located inside a greenhouse facility. The system was exposed to natural and supplemental light emitting diode (LED) lighting, in the blue and red light spectra, under a daylighting feedback control scheme. Experiments demonstrate that daily light integral (DLI) values with less than 20% tracking errors can be achieved on the blue and red channels using the calibrated sensors.
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The AS7341 device, a more advanced spectral sensor covering eight visible light bands, enables more precise determination of pigment changes in microalgae under factors such as nutrient deficiency, oxidative stress, or excessive light exposure.
“The AS7341 device (ams AG, Premstätten, Austria), a more advanced spectral sensor covering eight visible light bands, enables a more precise determination of pigment changes in microalgae under factors such as nutrient deficiency, oxidative stress, or excessive light exposure [251].”
From Multi-Sensing Monitoring of the Microalgae Biomass Cultivation Systems for Biofuels and Added Value Products Synthesis—Challenges and Opportunities (2025) · cites this paper as [251]
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- Authors
- Mohagheghi, A., & Moallem, M.
- Affiliations
- Simon Fraser University (CA)
- Venue
- IEEE Transactions on Instrumentation and Measurement
- Published
- 2024
- Volume
- 73
- Pages
- 1-10
- ISSN
- 0018-9456 (ISSN-L)
- 1557-9662
- OpenAlex
- W4389104597
- Cited by
- 8
- References
- 34
- Citations by year
- 2026: 4 · 2025: 3 · 2024: 1
- FWCI
- 1.26
- Type
- journal article
- Language
- en
- Open access
- closed
- Licence
- Locations
- IEEE Transactions on Instrumentation and Measurement (publishedVersion)
- Funders
- Natural Sciences and Engineering Research Council of Canada
- MITACS
- Discovery and Accelerate programs
- Topics
- Life Sciences › Agricultural and Biological Sciences › Plant Science › Light effects on plants
- Life Sciences › Agricultural and Biological Sciences › Plant Science › Smart Agriculture and AI
- Physical Sciences › Physics and Astronomy › Atomic and Molecular Physics, and Optics › Color Science and Applications
- Keywords
- photosynthetic photon flux density, low-cost sensors, sensor calibration, multiple linear regression, random forest, decision tree, red and blue light, daily light integral, hydroponics, spectroradiometer
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