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.

Motivated to make sensible interpretations of the massive volume of data from the Australian Microbiome Initiative (AusMic), we characterize the soil mycota of Australia. We establish operational taxonomic units (OTUs) from the data and compare these to GenBank and a data set from the National Herbarium of Victoria (MEL), Melbourne, Australia. We also provide visualizations of Agaricomycete diversity

Apple orchards in the United States are under constant threat from a large number of pathogens and insects. Appropriate and timely deployment of disease management depends on early disease detection. Incorrect and delayed diagnosis can result in either excessive or inadequate use of chemicals, with increased production costs and increased environmental and health impacts.

The standardization of plant names is a critical step in various fields of biology, including biodiversity, biogeography, and vegetation research. The WorldFlora package is introduced here to help achieve this goal by matching lists of plant names with a static copy from World Flora Online (WFO), an ongoing global effort to complete an online flora of all known vascular plants and bryophytes by 2020

Precise pollen collection methods are necessary for crop breeding, but anemophilous pollen is notoriously difficult to capture and control. Here we compared a variety of methods for the controlled capture of cannabis pollen, intended to ease the process of cross‐fertilization for breeding this wind‐pollinated plant, and measured the utility of light spectroscopy for quantifying relative pollen yield

Clearing leaves is a highly useful practice for many taxonomic, ecological, physiological, and eco‐physiological aspects of research. Using traditional methods, the procedure for clearing a leaf (referred to as diaphanization) can take several days or even weeks. In our laboratory we developed a technique, originally used for dissociating wood, that yields excellent epidermal and leaf venation preparations

The measurement of the characteristics of living organisms is referred to as phenotyping (Singh et al., 2016). While the use of phenotyping in plant biology and genetics can be traced back at least to Gregor Mendel sorting and counting peas by shape and pod color 160 years ago, addressing current questions in plant biology, genetics, and breeding often requires increasingly precise phenotyping of a

Aerial imagery from small unmanned aerial vehicle systems is a promising approach for high‐throughput phenotyping and precision agriculture. A key requirement for both applications is to create a field‐scale mosaic of the aerial imagery sequence so that the same features are in registration, a very challenging problem for crop imagery.

Maize yields have significantly increased over the past half‐century owing to advances in breeding and agronomic practices. Plants have been grown in increasingly higher densities due to changes in plant architecture resulting in plants with more upright leaves, which allows more efficient light interception for photosynthesis. Natural variation for leaf angle has been identified in maize and sorghum

AVP1 (H+‐pyrophosphatase) and MIOX4 (myo‐inositol oxygenase) are genes that, when overexpressed individually, enhance the growth and abiotic stress tolerance of Arabidopsis thaliana plants. We propose that pyramiding AVP1 and MIOX4 genes will further improve stress tolerance under water‐limited and salt‐stress conditions.

Black Sigatoka is one of the most severe banana (Musa spp.) diseases worldwide, but no methods for the rapid early detection of this disease have been reported. This paper assesses the use of hyperspectral images for the development of a partial‐least‐squares penalized‐logistic‐regression (PLS–PLR) model and a hyperspectral biplot (HS biplot) as a visual tool for detecting the early stages of black

Plant mechanical failure, also known as lodging, is the cause of significant and unpredictable yield losses in cereal crops. Lodging occurs in two distinct failure modes—stalk lodging and root lodging. Despite the prevalence and detrimental impact of lodging on crop yields, there is little consensus on how to phenotype plants in the field for lodging resistance and thus breed for mechanically resilient

In our paper, “Maximizing human effort for analyzing scientific images: A case study using digitized herbarium sheets,” Figure 2 was published without the legend. We apologize for the error. The published article (full‐text and PDF) has been corrected. Figure 2 Open in figure viewerPowerPoint Predicted accuracy of in‐person volunteers (A) and Notes from Nature volunteers (B) given the plant genus and

Advancements in machine learning and the rise of accessible “big data” provide an important opportunity to improve trait‐based plant identification. Here, we applied decision‐tree induction to a subset of data from the TRY plant trait database to (1) assess the potential of decision trees for plant identification and (2) determine informative traits for distinguishing taxa.

Statistical methods used by most morphologists to validate species boundaries (such as principal component analysis [PCA] and non‐metric multidimensional scaling [nMDS]) are limiting because these methods are mostly used as visualization methods, and because the groups are identified by taxonomists (i.e., supervised), adding human bias. Here, we use a spectral clustering algorithm for the unsupervised

The automated recognition of Latin scientific names within vernacular text has many applications, including text mining, search indexing, and automated specimen‐label processing. Most published solutions are computationally inefficient, incapable of running within a web browser, and focus on texts in English, thus omitting a substantial portion of biodiversity literature.

X‐ray microcomputed tomography (microCT) can be used to measure 3D leaf internal anatomy, providing a holistic view of tissue organization. Previously, the substantial time needed for segmenting multiple tissues limited this technique to small data sets, restricting its utility for phenotyping experiments and limiting our confidence in the inferences of these studies due to low replication numbers

High‐resolution cameras are very helpful for plant phenotyping as their images enable tasks such as target vs. background discrimination and the measurement and analysis of fine above‐ground plant attributes. However, the acquisition of high‐resolution images of plant roots is more challenging than above‐ground data collection. An effective super‐resolution (SR) algorithm is therefore needed for overcoming

Recent advances in sequencing and informatic technologies have led to a deluge of publicly available genomic data. While it is now relatively easy to sequence, assemble, and identify genic regions in diploid plant genomes, functional annotation of these genes is still a challenge. Over the past decade, there has been a steady increase in studies utilizing machine learning algorithms for various aspects

Weed removal in agriculture is typically achieved using herbicides. The use of autonomous robots to reduce weeds is a promising alternative solution, although their implementation requires the precise detection and identification of crops and weeds to allow an efficient action.

Trichomes are hair‐like appendages extending from the plant epidermis. They serve many important biotic roles, including interference with herbivore movement. Characterizing the number, density, and distribution of trichomes can provide valuable insights on plant response to insect infestation and define the extent of plant defense capability. Automated trichome counting would speed up this research

Machine learning approaches are affecting all aspects of modern society, from autocorrect applications on cell phones to self‐driving cars to facial recognition, personalized medicine, and precision agriculture. Although machine learning has a long history, drastic improvements in these application areas recently have been driven by improvements to computational infrastructure; increased computing

Seed germination over time is characterized by a sigmoid curve, called a germination curve, in which the percentage (or absolute number) of seeds that have completed germination is plotted against time. A number of individual coefficients have been developed to characterize this germination curve. However, as germination is considered to be a qualitative developmental response of an individual seed

Herbarium specimens represent an outstanding source of material with which to study plant phenological changes in response to climate change. The fine‐scale phenological annotation of such specimens is nevertheless highly time consuming and requires substantial human investment and expertise, which are difficult to rapidly mobilize.

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.

Digitized images of herbarium specimens are highly diverse with many potential sources of visual noise and bias. The systematic removal of noise and minimization of bias must be achieved in order to generate biological insights based on the plants rather than the digitization and mounting practices involved. Here, we develop a workflow and data set of high‐resolution image masks to segment plant tissues

Despite the economic significance of insect damage to plants (i.e., herbivory), long‐term data documenting changes in herbivory are limited. Millions of pressed plant specimens are now available online and can be used to collect big data on plant–insect interactions during the Anthropocene.

Equisetum is a distinctive vascular plant genus with 15 extant species worldwide. Species identification is complicated by morphological plasticity and frequent hybridization events, leading to a disproportionately high number of misidentified specimens. These may be correctly identified by applying appropriate computer vision tools.

Plant biodiversity is threatened, yet many species remain undescribed. It is estimated that >50% of undescribed species have already been collected and are awaiting discovery in herbaria. Robust automatic species identification algorithms using machine learning could accelerate species discovery.

Obtaining phenotypic data from herbarium specimens can provide important insights into plant evolution and ecology but requires significant manual effort and time. Here, we present LeafMachine, an application designed to autonomously measure leaves from digitized herbarium specimens or leaf images using an ensemble of machine learning algorithms.

The generation of morphological data in evolutionary, taxonomic, and ecological studies of plants using herbarium material has traditionally been a labor‐intensive task. Recent progress in machine learning using deep artificial neural networks (deep learning) for image classification and object detection has facilitated the establishment of a pipeline for the automatic recognition and extraction of

Nuclear microsatellite markers were developed for Linum bienne, the sister species of the crop L. usitatissimum, to provide molecular genetic tools for the investigation of L. bienne genetic diversity and structure.

Young plant roots share a common architecture: a central vascular cylinder surrounded by enveloping cylinders of ground and dermal tissue produced by an apical promeristem. Roots with closed apical organization can be studied to explore how ontogeny is managed. The analysis of transverse and longitudinal sections has been the most useful approach for this, but suffers from limitations. We developed

Atractylodes japonica (Asteraceae) is endemic to East Asia, where its rhizomes are used in traditional medicine. To investigate the genetic diversity of this species, we developed polymorphic microsatellite markers.

Camellia reticulata, which is native to southwestern China, is an economically important plant belonging to the family Theaceae. We developed expressed sequence tag–simple sequence repeat (EST‐SSR) markers for C. reticulata, which can be used to investigate its genetic diversity, population structure, and evolutionary history.

Physiological processes may vary within leaf laminae; however, the accompanying heterogeneity in leaf venation is rarely investigated because its quantification can be time consuming. Here we introduce accelerated protocols using existing software to increase sample throughput and ask whether laminae venation varies among three crop types and four subspecies of Brassica rapa.

Putatively single‐copy nuclear (SCN) loci, which are identified using genomic resources of closely related species, are ideal for phylogenomic inference. However, suitable genomic resources are not available for many clades, including Melastomataceae. We introduce a versatile approach to identify SCN loci for clades with few genomic resources and use it to develop probes for target enrichment in the

We present a low‐cost, battery‐operated, portable pump, “FloPump,” which allows regulated air sampling for the study of volatile organic compounds (VOCs). VOCs are routinely investigated in applications such as atmospheric chemistry, agriculture, and fragrance biology.

Plant ecologists in the Anthropocene are tasked with documenting, interpreting, and predicting how plants respond to environmental change. Phenology, the timing of seasonal biological events including leaf‐out, flowering, fruiting, and leaf senescence, is among the most visible and oft‐recorded facets of plant ecology. Climate‐driven shifts in plant phenology can alter reproductive success, interspecific

Counting chromosomes is a fundamental botanical technique, yet it is often intimidating and increasingly sidestepped. Once mastered, the basic protocol can be applied to a broad range of taxa and research questions. It also reveals an aspect of the plant genome that is accessible with only the most basic of resources—access to a microscope with 1000× magnification is the most limiting factor.

The ability to sequence genome‐scale data from herbarium specimens would allow for the economical development of data sets with broad taxonomic and geographic sampling that would otherwise not be possible. Here, we evaluate the utility of a basic double‐digest restriction site–associated DNA sequencing (ddRADseq) protocol using DNAs from four genera extracted from both silica‐dried and herbarium tissue

In the ferns, cell size has been explored with spores, which are largely uniform within species, produced in abundance, and durable. However, spore size and shape have been variously defined, and the relationship of these traits to genome size has not been well established. Here, we explore the variation in fern spore size and shape by ploidy level and genome size.

Seed oil is an economically important trait in Brassica oilseed crops. A novel method was developed to isolate Arabidopsis thaliana seeds with altered oil content.

We developed a novel low‐cost method to visually phenotype belowground structures in the plant rhizosphere. We devised the method introduced here to address the difficulties encountered growing plants in seed germination pouches for long‐term experiments and the high cost of other mini‐rhizotron alternatives.

Over 3000 species of plants and animals release toxic hydrogen cyanide (HCN) gas when their tissues are crushed. To investigate the role of cyanogenesis in Passiflora–herbivore interactions, we developed an inexpensive, rapid, sensitive method for measuring HCN emissions from crushed tissues.

A portable, simple, yet efficient method was developed for the rapid extraction of xylem sap from the stems and petioles of tomato plants for diagnostic and quantification assays of the xylem‐colonizing wilt bacterium Ralstonia solanacearum.

High‐throughput sequencing technologies have revolutionized the study of plant‐associated microbial populations, but they are relatively expensive. Molecular fingerprinting techniques are more affordable, yet yield considerably less information about the microbial community. Does this mean they are no longer useful for plant microbiome research? In this paper, we review the past 10 years of studies

The reduced cost of high‐throughput sequencing and the development of gene sets with wide phylogenetic applicability has led to the rise of sequence capture methods as a plausible platform for both phylogenomics and population genomics in plants. An important consideration in large targeted sequencing projects is the per‐sample cost, which can be inflated when using off‐the‐shelf kits or reagents not

Polymorphic microsatellite markers were developed to study genetic diversity and genetic structure of populations of the locally endangered species Tofieldia calyculata (Tofieldiaceae).

New sequencing technologies have facilitated genomic studies in green microalgae; however, extracting high‐quality DNA is often a bottleneck for long‐read sequencing.

Pollen dispersal plays a critical role in gene flow of seed plants. Most often, pollen dispersal is measured using paternity assignment. However, this approach can be time‐consuming because it typically entails genotyping all pollen donors, receptors, and offspring at several molecular markers.

Large‐scale efforts to digitize herbaria have resulted in more than 18 million publicly available Plantae images on sites such as iDigBio. The automation of image post‐processing will lead to time savings in the digitization of biological specimens, as well as improvements in data quality. Here, new and modified neural network methodologies were developed to automatically detect color reference charts

A novel set of microsatellite markers was developed for Juglans sigillata (Juglandaceae), an endemic walnut species in southwestern China, to facilitate cultivar identification and future investigations into the genetic structure and domestication history of this species and its close relatives.

The common sowthistle, Sonchus oleraceus (Asteraceae), is a globally invasive weedy species. In order to investigate its genetic diversity, population genetic structure, and evolutionary history, we developed and characterized nuclear simple sequence repeat markers (SSRs or microsatellites).

Drought‐induced tree mortality is an emergent threat to forests worldwide, particularly to large trees. Drought‐manipulation experiments involving throughfall exclusion (TFE) tend to focus on large plots that can be expensive to establish and maintain and may be unsuitable for large trees or indigenous forests. We set out to establish a relatively inexpensive TFE method in a natural forest with large

A set of polymorphic nuclear microsatellite loci was developed and tested for use in population genetic analyses of Anthericum ramosum (Agavaceae) and related species.

Flowers of the Apocynaceae (milkweed family) have complex structures and pollination mechanisms. Pollen removal and deposition in Angadenia, Pentalinon, and Echites are similar, with anthers releasing pollen onto the sterile style head. The mid‐style head excretes a glue that coats the mouthparts of vistors to aid in the transfer of pollen. Subsequent probes may deposit pollen on the receptive stigmatic

The Climate Reconstruction Analysis using Coexistence Likelihood Estimation (CRACLE) method utilizes a robust set of modeling tools for estimating climate and paleoclimate from vegetation using large repositories of biodiversity data and open access R software.

Ferula sadleriana (Apiaceae) is a polycarpic, perennial herb with a very limited range and small populations. It is listed as “endangered” on the IUCN Red List of Threatened Species. Microsatellite markers can contribute to conservation efforts by allowing the study of the genetic structure of its shrinking populations.

Pteroceltis tatarinowii (Ulmaceae), the only species of the genus Pteroceltis, is an endangered tree in China. Here, novel expressed sequence tag–simple sequence repeat (EST‐SSR) markers were developed to illuminate its genetic diversity for conservation and assisted breeding.