INFORM May 2026

EXTRACTS & DISTILLATES INFORM 33

secoiridoids in VOO by measuring oleacein, oleuropein, oleuropein glucoside, and ligstroside aglycone in fruits. Significant correlations ( p -value<0.05, r > 0.5) were found between volatiles in fruits and oils, which are associated with “green” and “ripen” fruitiness in VOOs. Lastly, no differences were found in the content of predominant FAs, palmitic and oleic acid; in contrast, linoleic acid content was significantly lower in VOOs than in fruits due to its role as a substrate in the lipoxygenase pathway, which is activated during VOO extraction and promotes the formation of volatiles responsible for fruitiness attributes. MACHINE LEARNING ASSISTED RAMAN SPECTROSCOPY FOR NON DESTRUCTIVE ANALYSIS OF CRUDE PALM OIL QUALITY Adade, S.YS. S., et al. , npj Science of Food , 10, 41, 2026. Quality assessment of crude palm oil remains a critical challenge globally, particularly in resource-poor areas where traditional methods are time consuming and destructive. This study explores machine learning assisted Raman spectroscopy for non-destructive assessment of peroxide value (PV) and iodine value (IV) in palm oil. Raman spectra were collected from 200 samples from five Ghanaian markets, with second derivative preprocessing significantly enhancing feature resolution. Twelve predictive models were developed by combining three variable selection algorithms (CARS, GA, UVE) with three regression methods (PLS, SVM, RF). The genetic algorithm-random forest (GA-RF) model demonstrated exceptional prediction accuracy for both PV (Rp = 0.9831, RPD=7.7397) and IV (Rp = 0.9752, RPD=6.3927). Key spectral regions associated with unsaturation (1287-1657cm ⁻ ¹) and oxidation (1748-1840 cm ⁻ ¹) were identified as crucial predictors. This approach enables rapid, non destructive quality assessment with potential applications throughout the palm oil value chain.

safety, promoting commercial viability. Continued research and technological innovations will facilitate the integration of insect-derived ingredients into mainstream food systems, supporting global food security and sustainable production. STANDARDIZATION OF SOLVENT TYPE AND EXTRACTION TIME FOR LIPID EXTRACTION FROM BREWERS’ SPENT GRAIN (BSG) BY SOXHLET METHOD Karuppuchamy, V. and Campanella, O., Food Science & Nutrition , 14, 1, 2026. Brewers’ spent grain (BSG)’s potential use as a food ingredient is being evaluated, and thus, an accurate characterization of its proximate composition, particularly lipids, becomes essential. While the Soxhlet method is a widely recognized official standard test used for lipids measurement in food products, inconsistencies in solvent selection have led to variable and often no comparable results across studies. This is the first study that attempts to address that gap by systematically evaluating the impact of solvent type and extraction time on lipid yield from BSG. Five solvents and solvent mixtures, including acetone, ethanol, hexane, petroleum ether, and n-hexane, were used for lipid extraction. In the initial phase, 5 g BSG was extracted using 125mL of various solvents over 5h. Lipid yields from BSG varied from 4.54% to 8.44% depending on the solvent type, in which ethanol yielded the highest lipid content. Based on these results, ethanol was selected for further studies on the effect of extraction time. Soxhlet extractions were performed using ethanol and it’s binary mixtures with hexane and n-hexane for 3, 5, and 7h. The lipid yield from BSG varied from 7.66% to 8.44%, while the statistical analysis indicated no significant difference in lipid yield across the time range under studied conditions. Based on the findings from the study, it is recommended to use ethanol as a single solvent for 3-h extraction, as the method balances efficiency and resource use. The results from this

study is beneficial for the laboratories to choose the proper solvent and extraction time for measuring lipids in BSG using the Soxhlet method.

Thais Lomonaco Teodoro da Silva teaches and conducts food

science research at the Federal University of Lavras (UFLA), Brazil. Her research is focused on oleogels, lipid

crystallization, and sonocrystallization.

Ensuring the quality of oils from diverse origins necessitates the development of robust and sensitive analytical techniques. As the global supply chain expands, detecting adulteration and verifying authenticity become increasingly complex. Advanced methodologies, that can even predict quality in the crops before oil extraction, or predict very small changes in composition are under development and can change the whole oil crop chain. These tools combined with highly sensitive analysis will be essential for maintaining safety standards, guaranteeing nutritional value, and protecting consumer trust in the food and industrial sectors. LAB-ON-A-FRUIT: AN APPROACH FOR CHEMICAL EVALUATION OF OLIVE OIL COMPOSITION PRIOR TO EXTRACTION Cabanas-Garrido, E.C., et al. , Food Chemistry , 508, Part A, 148422, 2026. Three chemical families (fatty acids, phenols, and volatiles) can be used to differentiate virgin olive oil (VOO) based on its health benefits, organoleptic features, and oxidative stability. We propose a lab-on-a fruit approach to characterize these families in olives, providing qualitative and quantitative information on VOO composition prior to extraction. We developed a 100% accurate model to predict the predominant