With a band selective pulse, the region between δ 13.0 and 8.0 ppm was selectively excited for the quantification of hydroperoxides and aldehydes, following Merkx et al.. The hydroperoxide signals resonate between δ 11.3 and 10.6 ppm, and the aldehydes resonate between δ 9.8 and 9.4 ppm. The calculations, including a factor that accounts for intensity loss during the selective pulse, are described elsewhere. The data were processed with the Bruker TopSpin 4.0.6 software. The emulsion samples were centrifuged for 5 min at 2,000 rpm, and the cream layer was taken. This procedure was used to prevent the droplets from moving during the CLSM measurement. A silicon gasket was fixed on the cleaned glass, and 2 µL of the cream phase was dripped into a well of a silicon gasket (CultureWell™, GRACEBIO-LABS). The well was then sealed with a glass plate to prevent the evaporation of water from the samples. Fluorescence images were recorded on a confocal laser scanning microscope (CLSM, Leica SP8) equipped with a 63 x NA = 1.2 water immersion objective (HC PLAPO CS2, Leica) and a white-light laser with user-selectable excitation wavelengths. The scanning format was 512 × 512 pixels (i.e., 62 µm × 62 µm), and the line-scanning speed was set to 100 Hz. For lipid oxidation measurements with BODIPY 665/676, the excitation wavelengths were set to 561 and 640 nm to detect oxidized and non-oxidized lipids, respectively. Detection ranges were set from 580 to 660 nm and 660 to 750 nm, respectively. For protein oxidation measurements with CAMPO-AFDye 647, the samples were excited at 640 nm with a detection range between 660 and 750 nm. BODIPY 581/591 C11 was excited at 561 and 488 nm to detect non-oxidized and oxidized BODIPY, respectively. The emission ranges were set from 580 to 660 nm and 500 to 560 nm, respectively. were summed and used for the segmentation of oil droplets in 2D StarDist. In the segmentation steps, the versatile (fluorescence nuclei) model was used for the neural network prediction. We set the percentile low and high values to 1 and 99.8, respectively. The probability/score threshold was set to 0.5, and the overlap threshold was 0.4. After the segmentation steps, the masks were applied to the raw image data for the analysis of the fluorescence intensity changes using MATLAB. The average intensity and radii were determined for each droplet by summing up the total number of pixels for each segmented region and assuming a circle for each region. Then the radius was calculated from the square root of the area divided by π with 1 pixel corresponding to an area of 0.12 by 0.12 µm.