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.

Quantifying the Impact of Light on Ascorbic Acid Content in Lettuce: A Model Proposal / Fasciolo, Benedetta; van Brenk, Jordan; Verdonk, Julian C.; Bakker, Evert-Jan; van Mourik, Simon. - In: SUSTAINABILITY. - ISSN 2071-1050. - 16:17(2024). [10.3390/su16177470]

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

Fasciolo, Benedetta;
2024

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.
2024
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11583/2992082