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Premise of the Study Innovative approaches to specimen collection and curation are needed to maximize the utility of natural history collections in a new era of data use. Associated data, such as digital images from the field, are routinely collected with recent herbarium specimens. However, these data often remain inaccessible and are rarely curated alongside the associated physical specimens, which limits future data use. Methods and Results We leveraged the widely used citizen science platform, iNaturalist, to permanently associate field‐collected data to herbarium specimens, including information not well preserved in traditional specimens. This protocol improves the efficiency and accuracy of all steps from the collecting event to specimen curation and enhances the potential uses of specimens. Conclusions iNaturalist provides a standardized and cost‐efficient enhancement to specimen collection and curation that can be easily adapted for specific research goals or other collection types beyond herbaria.

Premise of the study: Hyb-Seq, the combination of target enrichment and genome skimming, allows simultaneous data collection for low-copy nuclear genes and high-copy genomic targets for plant systematics and evolution studies. Methods and Results: Genome and transcriptome assemblies for milkweed (Asclepias syriaca) were used to design enrichment probes for 3385 exons from 768 genes (>1.6 Mbp) followed by Illumina sequencing of enriched libraries. Hyb-Seq of 12 individuals (10 Asclepias species and two related genera) resulted in at least partial assembly of 92.6% of exons and 99.7% of genes and an average assembly length >2 Mbp. Importantly, complete plastomes and nuclear ribosomal DNA cistrons were assembled using off-target reads. Phylogenomic analyses demonstrated signal conflict between genomes. Conclusions: The Hyb-Seq approach enables targeted sequencing of thousands of low-copy nuclear exons and flanking regions, as well as genome skimming of high-copy repeats and organellar genomes, to efficiently produce genome-scale data sets for phylogenomics.

The quantification of plant drought resistance, particularly embolism formation, within and across species, is critical for ecosystem management and agriculture. We developed a cost-effective protocol to measure the water potential at which 50% of hydraulic conductivity ( ) is lost in stems, using affordable and accessible materials in comparison to the traditional optical method. Our protocol uses inexpensive USB microscopes, which are secured along with the plants to a pegboard base to avoid movement. A Python program automatized the image acquisition. This method was applied to quantify in an exotic species ( ) and native species ( ) of the Mediterranean vegetation in Baja California, Mexico. The intra- and interspecific patterns of variation in stem of and were obtained using the low-cost optical method with widely available and affordable materials that can be easily replicated for other species.

Premise of the Study Image‐based phenomics is a powerful approach to capture and quantify plant diversity. However, commercial platforms that make consistent image acquisition easy are often cost‐prohibitive. To make high‐throughput phenotyping methods more accessible, low‐cost microcomputers and cameras can be used to acquire plant image data. Methods and Results We used low‐cost Raspberry Pi computers and cameras to manage and capture plant image data. Detailed here are three different applications of Raspberry Pi–controlled imaging platforms for seed and shoot imaging. Images obtained from each platform were suitable for extracting quantifiable plant traits (e.g., shape, area, height, color) en masse using open‐source image processing software such as PlantCV. Conclusions This protocol describes three low‐cost platforms for image acquisition that are useful for quantifying plant diversity. When coupled with open‐source image processing tools, these imaging platforms provide viable low‐cost solutions for incorporating high‐throughput phenomics into a wide range of research programs.

Premise of the study: The Compositae (Asteraceae) are a large and diverse family of plants, and the most comprehensive phylogeny to date is a meta-tree based on 10 chloroplast loci that has several major unresolved nodes. We describe the development of an approach that enables the rapid sequencing of large numbers of orthologous nuclear loci to facilitate efficient phylogenomic analyses. Methods and Results: We designed a set of sequence capture probes that target conserved orthologous sequences in the Compositae. We also developed a bioinformatic and phylogenetic workflow for processing and analyzing the resulting data. Application of our approach to 15 species from across the Compositae resulted in the production of phylogenetically informative sequence data from 763 loci and the successful reconstruction of known phylogenetic relationships across the family. Conclusions: These methods should be of great use to members of the broader Compositae community, and the general approach should also be of use to researchers studying other families.

PREMISE A CO2 control system is important for investigating how elevated CO2 affects plant growth. Our automatic CO2 monitoring and control system offers an inexpensive and flexible way to make CO2‐enriched environments. METHOD AND RESULTS Using microcontrollers paired with non‐dispersive infrared CO2 sensors, relays, and valves, we developed a low‐cost system for monitoring and controlling CO2 levels in growth chambers. CONCLUSIONS Compared with existing commercially available CO2 control systems, Arduino‐based microcontrollers offer affordable access to the data logging of CO2 levels in growth chambers, thereby reducing budget limitations for creating growth conditions with highly controlled CO2 concentrations.

Premise Researchers adopting target‐enrichment approaches often struggle with the decision of whether to use universal or lineage‐specific probe sets. To circumvent this quandary, we investigate the efficacy of a simultaneous enrichment by combining universal probes and lineage‐specific probes in a single hybridization reaction, to benefit from the qualities of both probe sets with little added cost or effort. Methods and Results Using 26 Brassicaceae libraries and standard enrichment protocols, we compare results from three independent data sets. A large average fraction of reads mapping to the Angiosperms353 (24–31%) and Brassicaceae (35–59%) targets resulted in a sizable reconstruction of loci for each target set (x̄ ≥ 70%). Conclusions High levels of enrichment and locus reconstruction for the two target sets demonstrate that the sampling of genomic regions can be easily extended through the combination of probe sets in single enrichment reactions. We hope that these findings will facilitate the production of expanded data sets that answer individual research questions and simultaneously allow wider applications by the research community as a whole.

Premise of the study: Difficulties inherent in microscopic pollen identification have resulted in limited implementation for large-scale studies. Metabarcoding, a relatively novel approach, could make pollen analysis less onerous; however, improved understanding of the quantitative capacity of various plant metabarcode regions and primer sets is needed to ensure that such applications are accurate and precise. Methods and Results: We applied metabarcoding, targeting the ITS2, matK, and rbcL loci, to characterize six samples of pollen collected by honey bees, Apis mellifera. Additionally, samples were analyzed by light microscopy. We found significant rank-based associations between the relative abundance of pollen types within our samples as inferred by the two methods. Conclusions: Our findings suggest metabarcoding data from plastid loci, as opposed to the ribosomal locus, are more reliable for quantitative characterization of pollen assemblages. Furthermore, multilocus metabarcoding of pollen may be more reliable than single-locus analyses, underscoring the need for discovering novel barcodes and barcode combinations optimized for molecular palynology.

Premise of the Study An imaging system was refined to monitor the health of vegetation grown in controlled conditions using spectral reflectance patterns. To measure plant health, the single‐image normalized difference vegetation index (SI‐NDVI) compares leaf reflectance in visible and near‐infrared light spectrums. Methods and Results The SI‐NDVI imaging system was characterized to assess plant responses to stress before visual detection during controlled stress assays. Images were analyzed using Fiji image processing software and Microsoft Excel to create qualitative false color images and quantitative graphs to detect plant stress. Conclusions Stress was detected in Arabidopsis thaliana seedlings within 15 min of salinity application using SI‐NDVI analysis, before stress was visible. Stress was also observed during ammonium nitrate treatment of Eruca sativa plants before visual detection. Early detection of plant stress is possible using SI‐NDVI imaging, which is both simpler to use and more cost efficient than traditional dual‐image NDVI or hyper‐spectral imaging.

Premise Digitization and imaging of herbarium specimens provides essential historical phenotypic and phenological information about plants. However, the full use of these resources requires high‐quality human annotations for downstream use. Here we provide guidance on the design and implementation of image annotation projects for botanical research. Methods and Results We used a novel gold‐standard data set to test the accuracy of human phenological annotations of herbarium specimen images in two settings: structured, in‐person sessions and an online, community‐science platform. We examined how different factors influenced annotation accuracy and found that botanical expertise, academic career level, and time spent on annotations had little effect on accuracy. Rather, key factors included traits and taxa being scored, the annotation setting, and the individual scorer. In‐person annotations were significantly more accurate than online annotations, but both generated relatively high‐quality outputs. Gathering multiple, independent annotations for each image improved overall accuracy. Conclusions Our results provide a best‐practices basis for using human effort to annotate images of plants. We show that scalable community science mechanisms can produce high‐quality data, but care must be taken to choose tractable taxa and phenophases and to provide informative training material.