METADATA
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Title of the dataset: 
Data from: ‘Selective reflection of near infrared radiation in shading screens for cooled greenhouses’

DOI: 10.4121/ffa1ec4f-8976-44e2-b96d-ab0b613b4029
URL: https://doi.org/10.4121/ffa1ec4f-8976-44e2-b96d-ab0b613b4029

Creators: 
David Katzin, Greenhouse Horticulture and Flower Bulbs, Wageningen Plant Research, Wageningen University and Research, Wageningen, The Netherlands. david.katzin@wur.nl
ORCID: 0000-0001-9571-8231

Cecilia Stanghellini, Greenhouse Horticulture and Flower Bulbs, Wageningen Plant Research, Wageningen University and Research, Wageningen, The Netherlands
ORCID: 0000-0003-2281-8711

Vida Mohammadkhani, Greenhouse Horticulture and Flower Bulbs, Wageningen Plant Research, Wageningen University and Research, Wageningen, The Netherlands

Silke Hemming, Greenhouse Horticulture and Flower Bulbs, Wageningen Plant Research, Wageningen University and Research, Wageningen, The Netherlands
ORCID: 0000-0001-6638-7453

Related publications: 
Katzin, D., C. Stanghellini, V. Mohammadkhani, and S. Hemming. (2025) “Selective Reflection of near Infrared Radiation in Shading Screens for Cooled Greenhouses.” Acta Horticulturae 1423, pp. 95–104. https://doi.org/10.17660/ActaHortic.2025.1423.13.

Short description of the research:
A dataset containing underlying data for Katzin et al., Selective reflection of near infrared radiation in shading screens for cooled greenhouses.

The dataset contains the results of greenhouse simulations which were performed in order to estimate the influence of radiometric properties of a shading screen on potential yield, water use (for cooling and irrigation), and water use efficiency. All simulations were performed for a sweet pepper greenhouse in Saudi Arabia, equipped with a pad and fan cooling system.

Keywords: 
Sweet pepper; Vegetative generative balance; Radiation temperature ratio; Greenhouse cooling; Greenhouse climate control; Greenhouse water use; Water use efficiency; Pad and fan

License: CC BY-SA 4.0

Funding: 
This study has been conducted within the Public-Private Partnership project Smart Materials II with the financial support of the Dutch top sector Horticulture and Starting Materials, financed by the Dutch Ministry of Agriculture, Nature and Fisheries, Glastuinbouw Nederland, FME, Lumiforte, RKW, Svensson, Saint-Gobain, BASF, LyondellBasell and Fujifilm.

METHODOLOGY
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Simulations were run on the KASPRO-INTKAM model, Wageningen Greenhouse Horticulture, using the software version of 21 March, 2023. The model uses input data of greenhouse settings and weather data, and provides an output describing timeseries data of various greenhouse climate and crop properties. The simulated greenhouse was a sweet pepper greenhouse in Riyadh, Saudi Arabia, equipped with a pad and fan cooling system and a shading screen. Weather data was recorded in Riyadh, Saudi Arabia, in 2021-2022.

For further information see the related paper, Katzin et al., Selective reflection of near infrared radiation in shading screens for cooled greenhouses.

DESCRIPTION OF THE DATA
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The folder "Simulation results" contains the output of the greenhouse simulations: time series data describing the outdoor weather, indoor climate, and crop behaviour.

   Each CSV files contains the following information regarding the simulated greenhouse, organized in columns:
      1. DateTime - time stamps of the data, in Excel format: number of days since 30 Dec 1899
      2. tOut - outdoor air temperature (°C)
      3. tIn - indoor air temperature (°C)
      4. rhIn - relative humidity of the indoor air (%)
      5. co2In - CO2 concentration of the indoor air (ppm)
	  6. padFanCooling - cooling provided by the pad and fan system (W/m2)
	  7. padFanWaterUse - amount of water used by the pad and fan system (liters/m2/s)
	  8. transpiration - crop transpiration rate (liters/m2/s)
	  9. parAboveCrop - amount of PAR radiation above the crop (µmol/m2/s)
	  10. iGlobOut - outdoor global solar radiation (W/m2)
      11. rhOut - relative humidity of the  outdoor air (%)
	  12. rtrTarget - target indoor temperature, according to RTR climate control (°C)
	  13. scrPos - position of the shading screen, 0 being an open screen (undeployed), 1 a closed screen (deployed)
	  14. LAI - crop leaf area index (m2 leaf / m2 floor)
      
   
   The data is organized in the following files:
	  1. pepper_standard_output.csv - simulation results of Case 1, "Reference screen"
	  2. NIR_reflecting_output.csv - simulation results of Case 2, "NIR reflecting screen"
	  3. NIR_reflecting_sameTauPAR_output.csv - simulation results of Case 3, "NIR reflecting, PAR transmitting"
	  4. NIR_reflecting_adjSWR_output.csv - simulation results of Case 4, "NIR reflecting, fewer hours"
	  5. NIR_reflecting_sameTauPAR_adjSWR_output.csv - simulation results of Case 5, "NIR reflecting, PAR transmitting, fewer hours"
	  6. no_screen_output.csv - simulation results of Case 6, "No screen"

    
The folder "Scripts" contains a MATLAB script used to generate the figures and tables in the publication.
   - plotLightSymSimulations.m was run on MATLAB R2021b on Windows 10, 64 bit
 
The folder "Figures" contains the figures and data generated by the plotLightSymSimulations script
   Folder "Figures\csv": figures and data in CSV format
   Folder "Figures\fig": figures and data in MATLAB fig format
   Folder "Figures\png": figures and data images in PNG format
   
   fig1dailyIndoorTemperature - Figure 1, daily average of achieved and target temperature
   tab1screen_hours - Table 1, number of screen use hours
   fig2AswrCrop_barchart - Figure 2A, shortwave radiation at crop level
   fig2BwaterUse_barchart - Figure 2B, yearly water use
   fig2CwaterUseEfficiency - Figure 2C, product water use


INFORMATION AND CONTACT
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This Readme was written in November 2024 (updated May 2025) by David Katzin, Greenhouse Horticulture and Flower Bulbs, Wageningen University and Research. david.katzin@wur.nl
