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Data from: The shape of aroma: Measuring and modeling citrus oil gland distribution

Cite this dataset

Amezquita, Erik J. et al. (2022). Data from: The shape of aroma: Measuring and modeling citrus oil gland distribution [Dataset]. Dryad.


From preventing scurvy to being part of religious rituals, citrus are intrinsically connected to human health and perception. From tiny mandarins to head-sized pummelos, citrus capability of hybridization provides a vastly diverse array of fruit sizes and shapes, which in turn corresponds to a diversity of flavors and aromas. These sensory qualities are tightly linked to oil glands in the citrus skin. The oil glands are also key to understanding fruit development, and the essential oils contained by them are fundamental in the food and perfume industries. We study the shape of citrus based on 3D X-ray CT scan reconstruction of 163 different citrus samples comprising 58 different species and cultivars, including samples of all fundamental citrus species. First, using the power of X-rays and image processing, we are able to compare and contrast size ratios between different tissues, such as the size of the skin compared to the rind or the flesh. Second, we model the fruit shape as an ellipsoidal surface, and later we study and infer possible oil gland distributions on this surface using principles of directional statistics. We finally compare and contrast these overall fruit shape models along their gland distributions across different citrus species. This morphological modeling will allow us later to link genotype with phenotype, furthering our insight on how the physical shape is genetically specified in DNA.


We selected 51 different citrus varieties with diverse morphologies and geographical origins for our analysis. 166 different individuals in total were sent for scanning at Michigan State University in December 2018 (details of the scanned varities attached) These 166 samples were arranged into 63 raw scans, one scan per citrus variety containing all the replicates. An exception were pummelos and citrons, where each sample was individually scanned due to the fruit size. The scans were produced using the North Star Imaging X3000 system and the included efX software, with 720 projections per scan, at 3 frames per second and with 3 frames averaged per projection. The data was obtained in continuous mode. The X‐ray source was set to a voltage ranging from 70 kV to 90 kV, current of 70 µA, and focal spot size of 7.5 microns. The 3D reconstruction of the citrus was computed with the efX-CT software, obtaining a final voxel size ranging from 18.6 to 110.1microns for different scans (resolution detailed is attached)

The air and debris were thresholded out of each raw scan, and individual replicates segmented into separate images. These images were further segmented into individual tissues based on their density and location within the fruit. For each fruit we thus obtained 3D voxel-based reconstructions of their central column, endocarp, mesocarp, exocarp, and oil glands. The exocarps for each fruit were further processed, isolating the separate, low-density spots in its interior corresponding to the oil glands. Low density spots of less than 3x3x3 voxel size were deemed as noise and discarded. Similarly, low density spots 3 times larger than the median size were broken into smaller separate pieces or discarded if separation was not possible. The center of each oil gland was calculated as the center of mass of the voxels composing such gland.  An in-house \texttt{scipy.ndimage}-based python script was used to process the images for all fruits and their tissues.

Usage notes

All the scans are provided as single 3D 8-bit TIFF files which can be manipulated as 3D arrays. Point clouds representing the center of citrus oil glands are attached as well. These point clouds can be later used to model the whole fruit shape.

Please read the README files included with the data for more details.


National Institute of Food and Agriculture

Michigan State University

National Science Foundation, Award: CCF-1907591

National Science Foundation, Award: CCF-2106578

National Science Foundation, Award: CCF-2142713

University of California, Riverside

Michigan State University