This dataset provides the boundary coordinate data of 960 stomata and the fitted results (including the estimated values of model parameters and the goodness of fit) using the superellipse and Gielis equations from the four Magnoliaceae species with 240 stomata for each species.

The following contents were cited from Li et al. (2023):

Leaf sampling 

Healthy fully-expanded mature leaves of four Magnoliaceae species [(Magnolia denudata Desr., Magnolia stellata (Siebold & Zucc.) Maxim., Michelia chapensis Dandy., and Michelia martini (H. Lév.) Finet & Gagnep. ex H. Lév] were collected between July and August 2022. Forty leaves were selected from each species. Magnolia denudata, M. chapensis, and M. martini were collected from the Nanjing Forestry University campus in Nanjing (32°4'41''N, 118°48'34''E), and M. stellata was collected from Nanjing Botanical Garden Mem. Sun Yat-Sen (32°3'17''N, 118°49'51''E). For convenience, we will refer to these species as Md, Mc, Mm, and Ms hereinafter.

Lamina section sampling and data acquisition

For each leaf, two lamina sections of approximately 0.5 cm × 0.5 cm were selected along the width axis of the leaf, one near the midrib and another section near the leaf left margin, respectively. Stomatal images (with a view-field area of 662 μm × 444 μm for each lamina section) were acquired by the segregation method (Jiao et al. 2021). An optical microscope (NE-620; Nanjing Yongxin Optics Co., Ltd, Nanjing, China) and ImageView software (version 4.11.17864; Shanghai Pooher Electro-Optical Co., Ltd, Shanghai, China) installed on a desktop Lenovo XiaoXinAir 15ITL 2021 computer (Lenovo Group Limited, China) were used to observe and capture images. Taking care to avoid major leaf veins during photographing, the exported images were saved as TIF files at 72 ppi resolution totally having 5440 × 3648 pixels (with actual size of 662 μm × 444 μm).

For each of the four Magnoliaceae species, 240 stomata were randomly selected from the images taken, resulting in a total of 960 stomata. The boundary of each stoma selected was manually redrawn using the Procreate software (version 5.2.9; Savage Interactive Pty Ltd, Hobart, TAS, Australia) on an iPad air3 (version 14.7.1; Adobe Systems Incorporated, Cupertino, CA, USA). First, the lamina section TIF files were imported into the Procreate software; second, a new layer was created for redrawing the boundary of a stoma randomly sampled; third, the studio brush in Procreate was selected, and the opacity of the studio brush was adjusted to be maximum; fourth, a stoma was randomly selected, and its boundary was redrawn using the studio brush on the newly built layer; fifth, the inside of the redrawn stomatal boundary was filled with black; sixth, the output files were saved in PSD format; seventh, the stomatal images were then cropped and converted to black and white BMP images using Adobe Photoshop 2021 (version 22.4.2; Adobe Systems Incorporated, San Jose, CA, USA); finally, the planar coordinates of the stomatal profile (i.e., the planar projection of the stoma) in the Cartesian coordinate system were extracted using a MATLAB program (Shi et al. 2018; Su et al. 2019 for details). The number of approximately equidistant data points forming, each stomatal perimeter was fixed at 500. To reduce the measurement error, two female graduate students with similar age (i.e., QL and LZ in the list of authors, who were 24 and 22 years old and came from the same province) were arranged to carry out the above operating procedures. Before formally carrying out the redrawing work, they were trained to perform the above operating procedures in the same manner as a pre-experiment.

References

• Jiao Y, Gao Z, Wang R. 2021. Application of segregation process in observing the leaf stomatal structure of Michelia plants. Anhui For Sci Technol. 47(1):26–29. doi: 10.3969/j.2095-0152.2021.01.009.
• Li Q, Niklas KJ, Niinennets Ü, Zhang L, Yu K, Gielis J, Gao J and Shi P. 2023. Stomatal shape described by a superellipse in four Magnoliaceae species. Bot Lett. In press. https://doi.org/10.1080/23818107.2023.2234443
• Shi P, Gielis J, Quinn BK, Niklas KJ, Ratkowsky DA, Schrader J, Ruan H, Wang L and Niinennets Ü. 2022. 'biogeom': An R package for simulating and fitting natural shapes. Ann NY Acad Sci 1516:123-134. doi: 10.1111/nyas.14862.
• Shi P, Ratkowsky DA, Li Y, Zhang L, Lin S, Gielis J. 2018. A general leaf area geometric formula exists for plants—evidence from the simplified gielis equation. Forests. 9(11):714. doi: 10.3390/f9110714.
• Su J, Niklas KJ, Huang W, Yu X, Yang Y, Shi P. 2019. Lamina shape does not correlate with lamina surface area: an analysis based on the simplified Gielis equation. Glob Ecol Conserv. 19:e00666. doi: 10.1016/j.gecco.2019.e00666.