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Dryad

Data from: Nutlet morphology in the tribe Elsholtzieae (Lamiaceae)

Cite this dataset

Jeon, Yun-Chang; Hong, Suk-Pyo; Jang, Tae-Soo (2020). Data from: Nutlet morphology in the tribe Elsholtzieae (Lamiaceae) [Dataset]. Dryad. https://doi.org/10.5061/dryad.pnvx0k6jj

Abstract

A comprehensive study on nutlet morphology on 46 taxa from the tribe Elsholtzieae was conducted using stereomicroscopy, light microscopy, and scanning electron microscopy. The objectives were to evaluate the nutlet characteristics in a systematics context and to provide additional evidence for taxon delimitation. The nutlet shape varied from elliptical, widely elliptical, spheroidal, and ovate to pyriform. The size ranged from 0.50 to 2.70 mm in length and 0.34 to 2.65 mm in width. The three types of trichomes included simple non-glandular trichomes (Collinsonia punctata), clavate non-glandular trichomes (Elsholtzia cephalantha), and peltate glandular trichomes (Mosla grosseserrata and M. chinensis). We also report the presence of mucilaginous reaction in nine species of the genus Elsholtzia in Elsholtzieae. Four types (undulate, papillae-like projection, thorn-like pattern, and reticulate) and three subtypes (reticulate, reticulate-cellular, and supra-reticulate) of nutlet surface patterns in the mid-ventral region were recognized in Elsholtzieae based on the differences in cell outline, outer periclinal walls, and dentations of the anticlinal walls. These nutlet micromorphological results may serve as a reference for future hypotheses on the classification of the tribe Elsholtzieae.

Methods

A total of 68 specimens from 46 taxa (44 species and 2 varieties) from 6 genera (Collinsonia 4 spp.; Elsholtzia 25 spp.; Keiskea 3 spp.; Mosla 8 species and 1 variety; Perilla 3 spp. and 1 variety; Perillula 1 sp.; Table 2, Suppl. Table S1) in Elsholtzieae were sampled from the collections of the following herbaria: GH, KB, KH, KHUS, MO, NY, S, TNM, and UPS (herbarium abbreviations according to Thiers 2020, and continuously updated). All data, including species authorship, collector, and herbarium acronyms from the list of all of the taxa and specimens investigated, are summarized in Supplementary material Table S1. Although the nutlets of Ombrocharis dulcis Hand.-Mazz., which is natively distributed in Hunan Province in central China (Li and Hedge 1994, Wu et al. 2007, Manchester et al. 2009), were not sampled from herbarium collections, we nevertheless decided to include nutlet morphological data of this species for comparison (Table 2) from the previously published data by Chen et al. (2016). Nutlet morphological observations focused primarily on the general shape following the overall plane or two-dimensional shape (Simpson 2010), size (length and width), mucilage production (Ryding 1992a), and the features of the exocarp, involving general sculpturing patterns, projections of the outer periclinal walls, and dentations of the anticlinal walls (Moon et al. 2009a). The minimum-maximum range and mean nutlet size were measured on at least 10 randomly chosen individuals from each taxon. The terminology for nutlet sculpturing patterns and pericarp structure was mostly adopted from Ryding (1992a), Budantsev and Lobova (1997), and Moon et al. (2009a).

Fully matured nutlets were directly mounted onto aluminum stubs with double adhesive tape and coated using an ion-sputtering device (JEOL, JFC-1100E, Japan) prior to observation using a scanning electron microscope (JEOL, JSM-5200, Japan) at 20 kV. To check for the absence and presence of myxocarpy, one to five nutlets were treated with distilled water and first examined using a light microscope (Olympus, BX-41, Japan). Production of mucilage was noted and classified as functionally non-myxocarpic (<0.01 mm) and strongly myxocarpic (>0.5 mm) following Ryding (2001) and Moon et al. (2009a).

One-way analysis of variance (ANOVA) and Tukey's HSD test were used to compare the differences in nutlet morphological measurements among studied taxa at the sectional or generic level. All statistical analyses were performed using the statistical program R (version 3.5.0, 2018).

Funding

National Research Foundation of Korea, Award: NRF-2018R1D1A1A09083715