Articles
Estimating solar light accumulation using peak sunshine and photoperiod
Article number
1425_50
Pages
389 – 396
Language
English
Abstract
Daily light integral (DLI) of photosynthetic photon flux density (PPFD) is a major determinant of crop yield and quality.
The most accurate measurement of DLI is via continuously integrating PPFD with a quantum sensor and data logger.
However, many small farmers lack weather stations and have limited climate sensors.
Quantitative models are available for estimating daily global radiation based on peak sunlight at solar noon and photoperiod.
Approximate conversions are also available for sunlight from shortwave radiation (W m‑2, 1X) to PPFD (μmol m‑2 s‑1, 2X) and visible light (lux, 108X) that allow use of lower-cost light sensors than a research-grade quantum sensor.
A published solar model used in ecological studies was calibrated with hourly historical climate data from eight weather stations in the USA, Guatemala City (Guatemala), Almería (Spain), and Cape Town (South Africa) using PPFD to compare the daily light integral (DLI, in mol m‑2 d‑1) from integrated hourly data DLImeasured versus a DLImodel based on peak radiation (W m‑2 converted to PPFD) at solar noon and the apparent sunrise and sunset times from the U.S. National Oceanic and Atmospheric Administration.
The coefficient of determination R2 for actual versus estimated data ranged from 0.47 to 0.94 for daily data from the eight sites, and 0.67 to 0.99 for weekly data.
The model was also successfully validated with historical data from Schiphol in The Netherlands (R2=0.99). The model is packaged for growers as a University of Florida IFAS decision-support system in a mobile app.
The tool is designed to estimate DLI using data where a grower measures daily peak radiation at solar noon using a light meter, and enters this data along with sunrise and sunset times.
The method is suitable for simple protected structures that have no or fixed shade, rather than moving screens, and without electrical lighting, and is most accurate in areas that do not have frequent storms or highly changeable daily weather.
The most accurate measurement of DLI is via continuously integrating PPFD with a quantum sensor and data logger.
However, many small farmers lack weather stations and have limited climate sensors.
Quantitative models are available for estimating daily global radiation based on peak sunlight at solar noon and photoperiod.
Approximate conversions are also available for sunlight from shortwave radiation (W m‑2, 1X) to PPFD (μmol m‑2 s‑1, 2X) and visible light (lux, 108X) that allow use of lower-cost light sensors than a research-grade quantum sensor.
A published solar model used in ecological studies was calibrated with hourly historical climate data from eight weather stations in the USA, Guatemala City (Guatemala), Almería (Spain), and Cape Town (South Africa) using PPFD to compare the daily light integral (DLI, in mol m‑2 d‑1) from integrated hourly data DLImeasured versus a DLImodel based on peak radiation (W m‑2 converted to PPFD) at solar noon and the apparent sunrise and sunset times from the U.S. National Oceanic and Atmospheric Administration.
The coefficient of determination R2 for actual versus estimated data ranged from 0.47 to 0.94 for daily data from the eight sites, and 0.67 to 0.99 for weekly data.
The model was also successfully validated with historical data from Schiphol in The Netherlands (R2=0.99). The model is packaged for growers as a University of Florida IFAS decision-support system in a mobile app.
The tool is designed to estimate DLI using data where a grower measures daily peak radiation at solar noon using a light meter, and enters this data along with sunrise and sunset times.
The method is suitable for simple protected structures that have no or fixed shade, rather than moving screens, and without electrical lighting, and is most accurate in areas that do not have frequent storms or highly changeable daily weather.
Authors
P.R. Fisher, B. MacKay
Keywords
Back Pocket Grower, daily light integral, decision support system, greenhouse, mobile app, solar noon
Groups involved
- Division Plant-Environment Interactions in Field Systems
- Division Precision Horticulture and Engineering
- Working Group Modelling in Fruit Research and Orchard Management
- Working Group Modelling Plant Growth, Environmental Control, Greenhouse Environment
- Division Greenhouse and Indoor Production Horticulture
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