Quantifying the Impact of Light on Ascorbic Acid Content in Lettuce: A Model Proposal

Benedetta Fasciolo (), Jordan van Brenk, Julian C. Verdonk, Evert-Jan Bakker and Simon van Mourik
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Benedetta Fasciolo: Department of Management and Production Engineering, Politecnico di Torino, Corso Duca Degli Abruzzi 24, 10129 Torino, Italy
Jordan van Brenk: Horticulture & Product Physiology, Plant Sciences Group, Wageningen University & Research, Droevendaalsesteeg 1, 6708PB Wageningen, The Netherlands
Julian C. Verdonk: Horticulture & Product Physiology, Plant Sciences Group, Wageningen University & Research, Droevendaalsesteeg 1, 6708PB Wageningen, The Netherlands
Evert-Jan Bakker: Mathematical and Statistical Methods-Biometris, Plant Sciences Group, Wageningen University & Research, Droevendaalsesteeg 1, 6708PB Wageningen, The Netherlands
Simon van Mourik: Agricultural Biosystems Engineering, Plant Sciences Group, Wageningen University & Research, Droevendaalsesteeg 1, 6708PB Wageningen, The Netherlands

Sustainability, 2024, vol. 16, issue 17, 1-13

Abstract: Vitamin C, also known as ascorbic acid (AsA), is an essential organic compound that is crucial for both plants and animals. Due to the inability of humans and some other animals to synthesize AsA, it is essential for them to consume sufficient plant products, especially leaves and fruits, which are good sources of AsA. Numerous studies have attempted to understand how different environmental factors influence crop AsA development. However, a comprehensive understanding of how environmental conditions affect ascorbic acid development remains elusive. This challenge may be due, in part, to the inherent difficulty of accurately and consistently measuring plant AsA. Measurements vary significantly depending on the tools and techniques used to capture them, and consequently, comparing results from different studies is complex. To address this challenge, our study develops a regression model to predict the AsA content in lettuce based on different light conditions. By analyzing how the varying daily light integral (DLI) and the blue light spectrum affect AsA levels, the model provides actionable insights for optimizing light treatments. This model not only aids in enhancing the development of AsA in lettuce but also assists farmers in achieving more sustainable agricultural practices by identifying optimal light spectra and DLI, thus promoting efficient resource utilization.

Keywords: ascorbic acid; lettuce; light treatments; model; methodology; environmental factors (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2024
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