Metabolomics and molecular networking approach for exploring the effect of light intensity and quality on the chemical profile and accumulation of glucosinolates in broccoli microgreen

Authors: LI, YANFANG - Ohio University; SHAHKOOMAHALLY, SHRIN - Oak Ridge Institute For Science And Education (ORISE); Yang, Tianbao; Chen, Pei; ZHANG, MENGLIANG - Ohio University; Sun, Jianghao

Submitted to: Journal of Agriculture and Food Chemistry
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 2/18/2025
Publication Date: 2/25/2025
Citation: Li, Y., Shahkoomahally, S., Yang, T., Chen, P., Zhang, M., Sun, J. 2025. Metabolomics and molecular networking approach for exploring the effect of light intensity and quality on the chemical profile and accumulation of glucosinolates in broccoli microgreen. Journal of Agriculture and Food Chemistry. 73(10):6281-6291. https://doi.org/10.1021/acs.jafc.4c12826.
DOI: https://doi.org/10.1021/acs.jafc.4c12826

Interpretive Summary: Controlled environment agriculture (CEA) is an advanced form of agriculture where plants are grown under controlled environment conditions to optimize growth and resource utilization. Microgreens are high-value agricultural products that require delicate handling and are well-suited for CEA systems. Light is one of the most crucial that significantly affects the growth and development, as well as the accumulation of secondary metabolites in microgreens. However, there is limited data on the effects of far-red (FR) light and white light intensities on glucosinolate accumulation in broccoli microgreens. Metabolomics can be a great tool for holistic evaluation of nutrient profiles using different CEA growing conditions for microgreens. In addition, molecular networking is a promising tool using computational strategy to analyze complex data sets from mass spectrometry (MS). By integrating metabolomics with molecular networking, researchers can perform high-throughput characterization, identification, and visualization of metabolites in botanical samples. In the present study, non-targeted metabolomics and molecular networking approaches were exploited to analyze the phytochemical profiles of broccoli microgreens grown under different white LED light intensities, with and without far-red (FR) light. Chemometric analysis was employed to identify potential biomarkers. Additionally, targeted glucosinolate analysis was conducted using a fast and simple solid phase extraction-based method to confirm the effects of different white light intensities and FR light on glucosinolate accumulation. The results may provide valuable insights for selecting optimal LED light intensity and quality to enhance the nutritional quality of broccoli microgreens.

Technical Abstract: Light intensity is a crucial factor impacting the cost-efficiency of controlled environment agriculture (CEA). Broccoli microgreens were cultivated under different photosynthetic photon flux densities (PPFD): 50, 100, and 150 µmol Xm-2Xs-1 with white light-emitting diodes (LEDs), and an additional 80 µmolXm-2Xs-1 far-red (FR) light supplement at the 50 µmolXm-2Xs-1 intensity. This study examines how low light intensity influences the chemical profile and glucosinolate accumulation in broccoli microgreens through both non-targeted and targeted metabolomics with molecular networking analysis. The analysis identified 28 glucosinolates and 23 phenolic compounds, with targeted quantification of 12 glucosinolates. The results showed that FR light supplementation significantly increased total glucosinolate content compared to white light-only treatments, while similar glucosinolate levels were found across the different white light intensities. These findings provide valuable insights for optimizing LED light intensity to enhance glucosinolate accumulation in broccoli microgreens, thus promoting more efficient energy use in CEA.