Harnessing Light Wavelengths to Enrich Health-Promoting Molecules in Tomato Fruits

Abstract

The tomato (Solanum lycopersicum L.) is one of the most consumed crops worldwide and a source of antioxidants. Given the role the latter play against oxidative stress and free radical-related diseases, enhancing tomato bioactive compound production would be appealing for a wide range of applications in the fields of nutrition, pharmacy, and biotechnology. This study explores a sustainable and innovative approach: the modulation of specific light spectra to boost the production of bioactive compounds in tomatoes (cultivar 'Microtom'). We investigated how three light regimes-white fluorescent (FL), full-spectrum (FS), and red-blue (RB)-influence the accumulation of polyphenols and other key nutraceuticals during plant growth. Our findings reveal that full-spectrum (FS) light significantly enhances the levels of polyphenols, flavonoids, tannins, ascorbic acid, and lycopene in tomato fruits, compared to those grown under RB or FL light. Interestingly, fruits from RB light-grown plants showed the highest carotenoid concentrations and antioxidant capacity. These results suggest that light quality actively modulates the expression of key enzymes in the phenylpropanoid and flavonoid biosynthetic pathways, shaping each fruit's unique metabolic fingerprint. Cluster analysis confirmed that RB, FL, and FS conditions lead to distinct polyphenolic profiles, each with notable health-promoting potential. Our results highlight a promising avenue: tailoring light environments to enhance the functional value of crops, bridging agriculture, nutrition, and biomedicine in a sustainable way.

Keywords: antioxidants; biofortification; functional food; human health; light quality; phenolic compounds; tomato.

Figure 1

Boxplots of biochemical marker levels across light treatments. Each facet displays a different marker, with individual sample points overlaid and medians highlighted in red. (a) total carotenoids, (b) total lycopene, (c) total anthocyanins, (d) total polyphenols, (e) total flavonoids, (f) total condensed tannins, (g) total ascorbic acid, (h) total antioxidant capacity, (i) DPPH radical scavenging activity, (j) total soluble proteins, (k) total carbohydrates. Letters indicate statistically significant groupings based on Dunn’s post hoc test following a Kruskal–Wallis analysis (p adjusted via Holm correction).

Figure 2

Heatmap summarizing the strongest treatment effects on biochemical markers. Tile color indicates percent change between the strongest and weakest treatment groups per marker, with values annotated. Only statistically significant differences (Dunn’s test, Holm-adjusted p < 0.05) are shown. AsA: Ascorbic Acid; DPPH: DPPH scavenging activity; FRAP: total antioxidant capacity; Antos: total anthocyanins; Carots: total carotenoids; Carbos: total carbohydrates; Flavos: total flavonoids; Lyco: total lycopene; PolyP: total polyphenols; Prots: total soluble proteins; Tanns: total condensed tannins.

Figure 3

Spectral reflectance curves for each sample, grouped by treatment. Arrows indicate wavelengths that are significantly correlated with biochemical marker levels (FDR-adjusted p < 0.05; Spearman correlation > 0.75). Upward and downward arrows represent strong positive and negative correlations, respectively. Solid lines indicate no significant correlation.

Figure 4

Hierarchical clustering heatmap of median-centered, scaled polyphenol profiles across light treatments. Rows represent individual polyphenols, and columns represent treatment groups. Clustering was performed using Manhattan distance and Ward’s linkage method to reveal treatment-driven patterns in metabolite abundance. A color gradient scale for Z-scores (mean-centered and standard deviation-scaled values) and dendrogram branch lengths are included to aid interpretation.