Biomarkers of rotted sugar beet: A low-temperature volatile organic compounds analysis framework using headspace gas chromatography-mass spectrometry

Authors: LI, SUJIA - North Dakota State University; CHRISTOPHER, ASHISH - North Dakota State University; LU, YU - North Dakota State University; BILL, MALICK - North Dakota State University; MONONO, EWUMBUA - North Dakota State University; SULAYMON, ESHKABILOV - North Dakota State University; BRAATEN, BENJAMIN - North Dakota State University; Kandel, Shyam; XU, MINWEI - North Dakota State University

Submitted to: Journal of Food Science
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 8/25/2025
Publication Date: N/A
Citation: N/A

Interpretive Summary: Sugar beet (Beta vulgaris L.) contributes nearly 60% of total sucrose (commonly known as table sugar) production in the US . In the US, sugar beet roots are typically stored in large outdoor piles and indoor sheds under ambient conditions until they are processed in the factory. Storage rot or postharvest disease often develops in these piles, resulting in significant sucrose loss during storage and factory processing. Early detection of storage rot can help mitigate sugar loss through timely interventions. Certain chemical compounds emitted from rotted or infected sugar beet roots may serve as biomarkers for the early monitoring of storage rot in sugar beet. In the current study, a sensitive and reliable low-temperature detection protocol was established to identify volatile organic compounds as early signals of storage rot in the pile. Ethanol and ethyl acetate were identified as two promising organic compounds for early detection of storage rot in sugar beet. This new technology provides a robust analytical foundation to integrate early signals with sensor and machine learning technologies which will be useful for real-time sugar beet storage rot monitoring and management. Implementing sensor and machine learning technologies capable of detecting storage rot early in the pile system would allow timely mobilizing of resources to manage storage rot and minimize the sucrose loss in postharvest sugar beet.

Technical Abstract: Sugar beet (Beta vulgaris L.) storage rots significantly reduce sugar quality and economic viability of the industry. Early storage rot detection can mitigate sugar loss through timely interventions, with volatile organic compounds (VOC) serving as potential biochemical markers. However, conventional headspace gas chromatography-mass spectrometry (HS-GC-MS) methods for VOC detection typically require elevated incubation temperatures, unsuitable for accurately replicating real storage conditions (4 - 20 °C), thus limiting their practical applicability. This study aimed to develop and optimize a low-temperature HS-GC-MS analytical method for accurate VOC profiling in stored sugar beets. A comparison between healthy and rotted sugar beet samples identified ethanol and ethyl acetate as two promising VOC markers for early detection of storage rots. Through systematic optimization of sample preparation, calibration strategies, and headspace sampling parameters, a sensitive and reliable low-temperature detection protocol was established. The optimized method effectively addressed matrix effects and enhanced analyte detection, yielding limits of detection of 0.03 ppm for ethyl acetate and 1.4 ppm for ethanol, with recovery rates of 105% and 101%, respectively. This optimized approach provides a robust analytical foundation essential for integrating VOC profiling with sensor and machine learning technologies, significantly advancing real-time sugar beet storage rot monitoring and management.