Metabarcoding airborne pollen from subtropical and temperate eastern Australia over multiple years reveals pollen aerobiome diversity and complexity.

eDNA metabarcoding is an emergent tool to inform aerobiome complexity, but few studies have applied this technology with real-world environmental pollen monitoring samples. Here we apply eDNA metabarcoding to assess seasonal and regional differences in the composition of airborne pollen from routine samples collected across successive years. Airborne pollen concentrations over two sampling periods were determined using a continuous flow volumetric impaction air sampler in sub-tropical (Mutdapilly and Rocklea) and temperate (Macquarie Park and Richmond), sites of Australia. eDNA metabarcoding was applied to daily pollen samples collected once per week using the rbcL amplicon. Composition and redundancy analysis of the sequence read counts were examined. The dominant pollen families were mostly consistent between consecutive years but there was some heterogeneity between sites and years for month of peak pollen release. Many more families were detected by eDNA than counted by light microscopy with 211 to 399 operational taxonomic units assigned to family per site from October to May. There were 216 unique and 119 taxa shared between subtropics (27°S) and temperate (33°S) latitudes, with, for example, Poaceae, Myrtaceae and Causurinaceae being shared, and Manihot, Vigna and Aristida being in subtropical, and Ceratodon and Cerastium being in temperate sites. Certain genera were observed within the same location and season over the two years; Chloris at Rocklea in autumn of 2017-18 (0.625, p ≤ 0.004) and 2018-19 (0.55, p ≤ 0.001), and Pinus and Plantago at Macquarie Park in summer of 2017-18 (0.58, p ≤ 0.001 and 0.53, p ≤ 0.003, respectively), and 2018-19 (0.8, p ≤ 0.003 and 0.8, p ≤ 0.003, respectively). eDNA metabarcoding is a powerful tool to survey the complexity of pollen aerobiology and distinguish spatial and temporal profiles of local pollen to a far deeper level than traditional counting methods. However, further research is required to optimise the metabarcode target to enable reliable detection of pollen to genus and species level.

Effects of heterospecific pollen on stigma behavior in Campsis radicans: Causes and consequences.

PREMISE: Pollinator sharing of co-flowering plants may result in interspecific pollen receipt with a fitness cost. However, the underlying factors that determine the effects of heterospecific pollen (HP) are not fully understood. Moreover, the cost of stigma closure induced by HP may be more severe for plants with special touch-sensitive stigmas than for plants with non-touch-sensitive stigmas. Very few studies have assessed HP effects on stigma behavior. METHODS: We conducted hand-pollination experiments with 10 HP donors to estimate HP effects on stigma behavior and stigmatic pollen germination in Campsis radicans (Bignoniaceae) at low and high pollen loads. We assessed the role of phylogenetic distance between donor and recipient, pollen size, and pollen aperture number in mediating HP effects. Additionally, we observed pollen tube growth to determine the conspecific pollen-tube-growth advantage. RESULTS: Stigma behavior differed significantly with HP of different species. Pollen load increased, while pollen size decreased, the percentage of permanent closure and stigmatic germination of HP. Stigmatic HP germination increased with increasing aperture number. However, HP effects did not depend on phylogenetic distance. In addition, conspecific pollen had a pollen-tube-growth advantage over HP. CONCLUSIONS: Our results provide a good basis for understanding the stigma-pollen recognition process of plant taxa with touch-sensitive stigmas. We concluded that certain flowering traits drive the HP effects on the post-pollination period. To better understand the impact of pollinator sharing and interspecific pollen transfer on plant evolution, we highlight the importance of evaluating more factors that determine HP effects at the community level.

A chemometric approach for the differentiation of 15 monofloral honeys based on physicochemical parameters.

BACKGROUND: Although the main method for authentication of monofloral honey is pollen analysis, other classification approaches have been also applied. However, the majority of the existing classification models so far have utilized a few honey types or a few honey samples of each honey type, which can lead to inaccurate results. Aiming at addressing this, the goal of the present study was to create a classification model by analysing in total 250 honey samples from 15 different monofloral honey types in ten physicochemical parameters and then, multivariate analysis [multivariate analysis of variance (MANOVA), principal component analysis (PCA) and multi-discriminant analysis (MDA)] was applied in an effort to distinguish and classify them. RESULTS: Electrical conductivity and colour were found to have the highest discriminative power, allowing the classification of monofloral honey types, such as oak, knotgrass and chestnut honey, as well as the differentiation between honeydew and nectar honeys. The classification model had a high predictive power, as the 84.4% of the group cases was correctly classified, while for the cases of chestnut, strawberry tree and sunflower honeys the respective prediction was correct by 91.3%, 95% and 100%, allowing further determination of unknown honey samples. CONCLUSION: It seems that the characterization of monofloral honeys based on their physicochemical parameters through the proposed model can be achieved and further applied on other honey types. The results could contribute to the development of methodologies for the determination of honey's botanical origin, based on simple techniques, so that these can be applied for routine analysis. © 2021 Society of Chemical Industry.

A Comprehensive Study of the Genus Sanguisorba (Rosaceae) Based on the Floral Micromorphology, Palynology, and Plastome Analysis.

Sanguisorba, commonly known as burnet, is a genus in the family Rosaceae native to the temperate regions of the Northern hemisphere. Five of its thirty species are distributed in Korea: Sanguisorba officinalis, S. stipulata, S. hakusanensis, S. longifolia, and S. tenuifolia. S. officinalis has been designated as a medicinal remedy in the Chinese and Korean Herbal Pharmacopeias. Despite being a valuable medicinal resource, the morphological and genomic information, as well as the genetic characteristics of Sanguisorba, are still elusive. Therefore, we carried out the first comprehensive study on the floral micromorphology, palynology, and complete chloroplast (cp) genome of the Sanguisorba species. The outer sepal waxes and hypanthium characters showed diagnostic value, despite a similar floral micromorphology across different species. All the studied Sanguisorba pollen were small to medium, oblate to prolate-spheroidal, and their exine ornamentation was microechinate. The orbicules, which are possibly synapomorphic, were consistently absent in this genus. Additionally, the cp genomes of S. officinalis, S. stipulata, and S. hakusanensis have been completely sequenced. The comparative analysis of the reported Sanguisorba cp genomes revealed local divergence regions. The nucleotide diversity of trnH-psbA and rps2-rpoC2, referred to as hotspot regions, revealed the highest pi values in six Sanguisorba. The ndhG indicated positive selection pressures as a species-specific variation in S. filiformis. The S. stipulata and S. tenuifolia species had psbK genes at the selected pressures. We developed new DNA barcodes that distinguish the typical S. officinalis and S. officinalis var. longifolia, important herbal medicinal plants, from other similar Sanguisorba species with species-specific distinctive markers. The phylogenetic trees showed the positions of the reported Sanguisorba species; S. officinalis, S. tenuifolia, and S. stipulata showed the nearest genetic distance. The results of our comprehensive study on micromorphology, pollen chemistry, cp genome analysis, and the development of species identification markers can provide valuable information for future studies on S. officinalis, including those highlighting it as an important medicinal resource.

Identification of pollen taxa by different microscopy techniques.

Melissopalynology is an important analytical method to identify botanical origin of honey. Pollen grain recognition is commonly performed by visual inspection by a trained person. An alternative method for visual inspection is automated pollen analysis based on the image analysis technique. Image analysis transfers visual information to mathematical descriptions. In this work, the suitability of three microscopic techniques for automatic analysis of pollen grains was studied. 2D and 3D morphological characteristics, textural and colour features, and extended depth of focus characteristics were used for the pollen discrimination. In this study, 7 botanical taxa and a total of 2482 pollen grains were evaluated. The highest correct classification rate of 93.05% was achieved using the phase contrast microscopy, followed by the dark field microscopy reaching 91.02%, and finally by the light field microscopy reaching 88.88%. The most significant discriminant characteristics were morphological (2D and 3D) and colour characteristics. Our results confirm the potential of using automatic pollen analysis to discriminate pollen taxa in honey. This work provides the basis for further research where the taxa dataset will be increased, and new descriptors will be studied.

Bee pollens originating from different species have unique effects on ovarian cell functions.

CONTEXT: The species-specific differences and mechanisms of action of bee pollen on reproduction have not been well studied. OBJECTIVE: We compared the effects of bee pollen extracts from different plants on ovarian cell functions. MATERIALS AND METHODS: We compared the effects of pollens from black alder, dandelion, maize, rapeseed, and willow at 0, 0.01, 0.1, 1, 10, or 100 µg/mL on cultured porcine ovarian granulosa cells. Cell viability was assessed with a Trypan blue test, the cell proliferation marker (PCNA), and an apoptosis marker (BAX) were assessed by immunocytochemistry. Insulin-like growth factor (IGF-I) release was measured by an enzyme-linked immunosorbent assay. RESULTS: Addition of any bee pollen reduced cell viability, promoted accumulation of both proliferation and apoptosis markers, and promoted IGF-I release. The ability of various pollens to suppress cell viability ranked as follows: rapeseed > dandelion > alder > maize > willow. The biological activity of bee pollens regarding their stimulatory action on ovarian cell proliferation ranked as follows: dandelion > willow > maize > alder > rapeseed. Cell apoptosis was promoted by pollens as follows: range > dandelion > alder > rapeseed > willow > maize. The ability of the pollens to stimulate IGF-I output are as follows: willow > dandelion > rapeseed > maize > alder. DISCUSSION: Bee pollen can promote ovarian cell proliferation by promoting IGF-I release, but it induces the dominance of apoptosis over proliferation and the reduction in ovarian cell viability in a species-specific manner. CONCLUSIONS: This is the first demonstration of adverse effects of bee pollen on ovarian cell viability and of its direct stimulatory influence on proliferation, apoptosis, and IGF-I release. The biological potency of bee pollen is dependent on the plant species.

Improving the taxonomy of fossil pollen using convolutional neural networks and superresolution microscopy.

Taxonomic resolution is a major challenge in palynology, largely limiting the ecological and evolutionary interpretations possible with deep-time fossil pollen data. We present an approach for fossil pollen analysis that uses optical superresolution microscopy and machine learning to create a quantitative and higher throughput workflow for producing palynological identifications and hypotheses of biological affinity. We developed three convolutional neural network (CNN) classification models: maximum projection (MPM), multislice (MSM), and fused (FM). We trained the models on the pollen of 16 genera of the legume tribe Amherstieae, and then used these models to constrain the biological classifications of 48 fossil Striatopollis specimens from the Paleocene, Eocene, and Miocene of western Africa and northern South America. All models achieved average accuracies of 83 to 90% in the classification of the extant genera, and the majority of fossil identifications (86%) showed consensus among at least two of the three models. Our fossil identifications support the paleobiogeographic hypothesis that Amherstieae originated in Paleocene Africa and dispersed to South America during the Paleocene-Eocene Thermal Maximum (56 Ma). They also raise the possibility that at least three Amherstieae genera (Crudia, Berlinia, and Anthonotha) may have diverged earlier in the Cenozoic than predicted by molecular phylogenies.

The suitability of native flowers as pollen sources for Chrysoperla lucasina (Neuroptera: Chrysopidae).

Green lacewings (Neuroptera: Chrysopidae) are key biological control agents found in a broad range of crops. Given the importance of enhancing their presence and conservation, in this study, we aim to identify and to determine the relative importance of the pollen consumed by Chrysoperla lucasina (Lacroix, 1936) from 29 pollen types offered by 51 native plant species sown in an experimental farm in Villarrubia in the south of Spain. For the purposes of this study, C. lucasina specimens were captured in the late spring of 2016 and 2017. The pollen types and other components in the alimentary canal of C. lucasina were microscopically identified using the transparency method, which is a novel technique applied to green lacewings captured in the field. The results show that (i) C. lucasina feeds on over half of the pollen types offered by the sown plant species, with no differences in behaviour by sex or year; (ii) Capsella bursa-pastoris was the most frequently identified pollen type in the alimentary canal; (iii) the majority of pollen types identified correspond to sown native plant species and not to surrounding plant species; and that (iv) most of the adults studied also consumed honeydew. Our feeding study has important implications for the selection of plant mixtures for ground cover restoration and flower vegetation strips in Mediterranean agroecosystems, which complements our previous findings on how C. lucasina use native plant species as host and reproduction sites. The plant species Capsella bursa-pastoris and Biscutella auriculata, which are best suited to provide pollen, host and reproduction sites for C. lucasina in late spring, should consequently be included in the proposed plant mixtures for Mediterranean agroecosystems.

Bee-Plant Interaction Networks in a Seasonal Dry Tropical Forest of the Colombian Caribbean.

Mutualistic interactions between bees and flowering plants have been widely recognized as one of the most important for the maintenance of these communities throughout ecosystems. Consequently, understanding how these interactions occur is highly important, especially in seasonal dry tropical forest (SDTF), one of the most endangered ecosystems in northern South America. In this study, we analyzed the changes between interaction networks across two well-defined seasons, dry and wet, in a SDTF of the Colombian Caribbean in Taganga, Magdalena. We also determined changes in species composition and their role in interaction networks. To study this system, we compared two approaches: (1) networks constructed with data from direct collections in flowering plants, and (2) networks constructed with pollen data obtained from bees' bodies. A total of 44 species were collected in 18 species of flowering plants; also, we registered 16 additional plants presented in the records only as pollen types. We found that network metrics, connectance, nestedness, specialization (H2'), and interaction strength asymmetry remain stable through seasons. However, when the two types of approximations were compared, there were significant differences. Networks constructed with pollen data are more connected, less specialized, and with lower values of interaction strength asymmetry. The major difference between seasons relied on the interacting species composition, due to a high species turnover. Bee community was more diverse in dry season. Apidae family, mainly eusocial species, persisted in the community, being more abundant and relevant in wet season. For dry season, Megachile and other solitary species from Apidae and Halictidae families were better represented and relevant for the community. We found that Fabaceae is an important resource for bees in both seasons. In addition, herbaceous species from Asteraceae and Convolvulaceae were preferred in wet season, while shrub and tree species from Fabaceae and Polygonaceae were the main resource in dry season.

Pollen Grain Counting Using a Cell Counter.

The number of pollen grains is a critical part of the reproductive strategies in plants and varies greatly between and within species. In agriculture, pollen viability is important for crop breeding. It is a laborious work to count pollen tubes using a counting chamber under a microscope. Here, we present a method of counting the number of pollen grains using a cell counter. In this method, the counting step is shortened to 3 min per flower, which, in our setting, is more than five times faster than the counting chamber method. This technique is applicable to species with a lower and higher number of pollen grains, as it can count particles in a wide range, from 0 to 20,000 particles, in one measurement. The cell counter also estimates the size of the particles together with the number. Because aborted pollen shows abnormal membrane characteristics and/or a distorted or smaller shape, a cell counter can quantify the number of normal and aborted pollen separately. We explain how to count the number of pollen grains and measure pollen size in Arabidopsis thaliana, Arabidopsis kamchatica, and wheat (Triticum aestivum).

Precise automatic classification of 46 different pollen types with convolutional neural networks.

In palynology, the visual classification of pollen grains from different species is a hard task which is usually tackled by human operators using microscopes. Many industries, including medical and pharmaceutical, rely on the accuracy of this manual classification process, which is reported to be around 67%. In this paper, we propose a new method to automatically classify pollen grains using deep learning techniques that improve the correct classification rates in images not previously seen by the models. Our proposal manages to properly classify up to 98% of the examples from a dataset with 46 different classes of pollen grains, produced by the Classifynder classification system. This is an unprecedented result which surpasses all previous attempts both in accuracy and number and difficulty of taxa under consideration, which include types previously considered as indistinguishable.

Pollen Load Spectrum of Tomato Pollinators.

Vibrating bees are the main pollinators of the tomato plant (Solanum lycopersicum L.). Knowledge of other alternative food resources for these bees is fundamental for pollinator management actions in agricultural areas. The objective of this study was to evaluate the plants used as food resources for the main pollinators Bombus morio (Swederus) and Exomalopsis analis Spinola in plantation areas. The study was conducted in 12 plantation areas in São José de Ubá, southeastern Brazil, during the flowering period of S. lycopersicum. The pollen material contained on the hind legs of 40 B. morio females and 72 E. analis females was analyzed and compared with the reference slides made from 155 flowering plant species (35 botanical families) sampled close to the plantations. The pollen material was submitted to acetolysis and mounted in glycerin gelatin and analyzed under optical microscope. From B.morio corbiculae were identified 188 pollen types (52 identified from reference slides) and 189 types from E. analis scopae (54 in reference slides). Besides tomato pollen, other most abundant types belong to Fabaceae (8%) in B. morio samples, and Hyptis and Solanum sp in E. analis samples. The trophic niche overlap was close to zero when the tomato pollen was disregarded, indicating that both pollinators use distinct sources. The results confirm the generalist character of tomato pollinators; in addition, the use of floral resources from several other plants, even at tomato flowering peak, emphasizes the importance of maintaining flowering plant composition around agricultural areas.

Pollen morphology of Polish species from the genus Rubus L. (Rosaceae) and its systematic importance.

The genus Rubus L. (Rosaceae) not been investigated satisfactorily in terms of palynology. This genus is taxonomically very difficult due to the large number of species and problems with their delimitation, as well as very different distribution areas of particular species. The aim of this study was to investigate pollen morphology and for the first time the ranges of intrageneric and interspecific variability of Rubus species, as well as verify the taxonomic usefulness of these traits in distinguishing studied taxa from this genus. The selected species of the genus Rubus were analysed for 11 quantitative pollen characteristics and the following qualitative ones: exine ornamentation, pollen outline and shape, as well as bridge structure. Analyses were conducted on a total of 1740 pollen grains, which represent 58 blackberry species belonging to a majority of subgenera and all the sections and series found in Poland. The most important characters included exine ornamentation (exine ornamentation type, width and direction of grooves and striae, number and diameter of perforations) and length of the polar axis (P). The arrangement of the examined species on the dendrogram does not corroborate division of the genus Rubus into subgenera, sections and series currently adopted in taxonomy. This fact is not surprising because the taxonomy of the genus was not based on pollen characters. Pollen features should be treated in taxonomy as auxiliary, because they fail to differentiate several (10) individual species, while the other ones create groups with similar pollen traits.

Stingless Bees (Melipona subnitida) Overcome Severe Drought Events in the Brazilian Tropical Dry Forest by Opting for High-Profit Food Sources.

In the Brazilian Tropical Dry Forest, the Caatinga, stingless bees (Apidae, Meliponini) need to adjust their foraging behavior to a very short and unpredictable blooming period. Melipona subnitida Ducke 1910 is one of the few meliponine species adapted to the environmental peculiarities of this biome. To get an insight into how these highly eusocial bees are able to maintain their perennial colonies despite extended periods of food scarcity, we asked the following questions: (1) At which plant species do colonies of M. subnitida collect their food during the rainy season? And (2) are there any plant species during the dry season, from which the colonies may profit for replenishing their food stores? During 1 year, we collected monthly honey and pollen samples from recently built storage pots of five colonies of M. subnitida and identified the botanical origin of the collected resources. In the course of our study, the colonies foraged at native trees, shrubs, and herbaceous species, demonstrating the importance of all plant strata for the bees' diet. Profitable plants, which bloom mainly during the rainy season and usually produce a great number of flowers, were frequently sampled in new pots throughout the entire study, even during the dry season. From our results, we compiled a list of the most important plant species providing floral resources for bees throughout the year, including periods of drought. We recommend these plants for restoration areas to improve the conservation of native bee species and local beekeeping in the Brazilian Tropical Dry Forest.

Community Assembly and Climate Mismatch in Late Quaternary Eastern North American Pollen Assemblages.

Plant community response to climate change ranges from synchronous tracking to strong mismatch. Explaining this variation in climate change response is critical for accurate global change modeling. Here we quantify how closely assemblages track changes in climate (match/mismatch) and how broadly climate niches are spread within assemblages (narrow/broad ecological tolerance, or "filtering") using data for the past 21,000 years for 531 eastern North American fossil pollen assemblages. Although climate matching has been strong over the last 21 millennia, mismatch increased in 30% of assemblages during the rapid climate shifts between 14.5 and 10 ka. Assemblage matching rebounded toward the present day in 10%-20% of assemblages. Climate-assemblage mismatch was greater in tree-dominated and high-latitude assemblages, consistent with persisting populations, slower dispersal rates, and glacial retreat. In contrast, climate matching was greater for assemblages comprising taxa with higher median seed mass. More than half of the assemblages were climatically filtered at any given time, with peak filtering occurring at 8.5 ka for nearly 80% of assemblages. Thus, vegetation assemblages have highly variable rates of climate mismatch and filtering over millennial scales. These climate responses can be partially predicted by species' traits and life histories. These findings help constrain predictions for plant community response to contemporary climate change.

Morphological, Physicochemical and FTIR Spectroscopic Properties of Bee Pollen Loads from Different Botanical Origin.

Bee pollen loads generally have a homogeneous and monospecific pollen content and assume a typical form and color, due to the typical bee foraging habits, thus having a typical composition related to the botanical origin. The present study aims to characterize bee pollen loads belonging to different botanical species using morphological, spectroscopic and color properties and to find relationships between these variables. IR spectra analysis allowed to have a reliable picture of the components present in the different samples; color and granulometry permits a visual identification of pollen load belonging to different species. Multivariate analysis enabled differentiation among the botanical origin of most of the bee pollen samples, grouping them according to the family and the genus and confirming the possibility to use IR and color measurements for the evaluative analysis and classification of bee pollen samples, to promote the consumption of this bee product as functional food.

A method for reconstructing temporal changes in vegetation functional trait composition using Holocene pollen assemblages.

Methods of reconstructing changes in plant traits over long time scales are needed to understand the impact of changing environmental conditions on ecosystem processes and services. Although Holocene pollen have been extensively used to provide records of vegetation history, few studies have adopted a functional trait approach that is pertinent to changes in ecosystem processes. Here, for woody and herbaceous fen peatland communities, we use modern pollen and vegetation data combined with pollen records from Holocene deposits to reconstruct vegetation functional dynamics. The six traits chosen (measures of leaf area-to-mass ratio and leaf nutrient content) are known to modulate species' fitness and to vary with changes in ecosystem processes. We fitted linear mixed effects models between community weighted mean (CWM) trait values of the modern pollen and vegetation to determine whether traits assigned to pollen types could be used to reconstruct traits found in the vegetation from pollen assemblages. We used relative pollen productivity (RPP) correction factors in an attempt to improve this relationship. For traits showing the best fit between modern pollen and vegetation, we applied the model to dated Holocene pollen sequences from Fenland and Romney Marsh in eastern and southern England and reconstructed temporal changes in trait composition. RPP adjustment did not improve the linear relationship between modern pollen and vegetation. Leaf nutrient traits (leaf C and N) were generally more predictable from pollen data than mass-area traits. We show that inferences about biomass accumulation and decomposition rates can be made using Holocene trait reconstructions. While it is possible to reconstruct community-level trends for some leaf traits from pollen assemblages preserved in sedimentary archives in wetlands, we show the importance of testing methods in modern systems first and encourage further development of this approach to address issues concerning the pollen-plant abundance relationship and pollen source area.

Morpho-palynological investigations of natural resources: A case study of Surghar mountain district Mianwali Punjab, Pakistan.

Surghar mountain belt has comparatively less natural resources of floral diversity because it is composed of minerals of different kinds making it less favorable for the growth of different vegetation. The pollen morphology of some selected plants from Surghar belt Mainwali has been evaluated. The pollen grains were measured and demonstrated using scanning electron microscopy (SEM). The examined plant specimens have a difference in size, shape, polarity, and their exine ornamentation. The pollen taxa show a huge variation in size and sculpture. Pollen fertility has also been estimated, shows that the selected plants are well-known in the Surghar belt. The need of the hour is to conserve these plants having a higher fertility rate to cope with the deforestation in an area. The conclusion does not favor theories in which deforestation results in fast growth in population. It shows that the irrational management and unlawful cutting down of woods neglected by the forest department are the main causes of deforestation in the mountain belt of Mianwali. The findings show the importance of morphological characteristics in the identification of natural resource species in the area.

Comparative light and scanning electron microscopy in authentication of adulterated traded medicinal plants.

The medicinal plants are utilized globally considering the cheap and chemical free source, but their correct identification and authentication is prerequisite for safety and efficacy of plant-based medicines. The present study encompassed traded medicinal plants (16) with high therapeutic value from diverse families like Brassicaceae, Berberidaceae, Malvaceae, Salicaceae, Myrtaceae, Papilionaceae, Ascelpiadaceae, Colchicaceae, Violaceae, and Vitaceae for detailed microscopic study of characters that is, morphology, pollen shape and sizes, P/E ratio, pore length and width, spine length, colpi dimensions, and exine sculpture pattern. The plants showed noteworthy differences in microscopy of Wattakaka volubilis having pollinia, translator and corpusculum like structures while pores were visible in Colchicum luteum, Alcea rosea, and Hibiscus syriacus. The spines were observed in Centipeda minima, A. rosea, and H. syriacus being dimorphic spines in A. rosea and monomorphic in H. syriacus. The exine sculpturing pattern was reticulate in mostly studied plants however distinctive exine pattern was noted in Berberis aristata and Berberis lyceum. The highest polar diameter, equatorial diameter and exine thickness among studied plants were observed in H. syriacus (161 µm), C. luteum (50 µm) and Vitis jacquemontii (1.10), respectively. Thus, microscopy of medicinal plants in addition to other taxonomic evidence offers a supportive skill in authentication, consequently utilization by local consumers and pharmaceutical industries.

DNA barcoding detects floral origin of Indian honey samples.

The unique medicinal and nutritional properties of honey are determined by its chemical composition. To evaluate the quality of honey, it is essential to study the surrounding vegetation where honeybees forage. In this study we used conventional melissopalynological and DNA barcoding techniques to determine the floral source of honey samples collected from different districts of the state of Mizoram, India. Pollen grains were isolated and genomic DNA was extracted from the honey samples. PCR amplification was carried out using universal barcode candidates ITS2 and rbcL to identify the plant species. Furthermore, TA cloning was carried out to screen the PCR amplicon libraries to identify the presence of multiple plant species. Results from both the melissopalynological and DNA barcoding analyses identified almost exactly the same 22 species, suggesting that both methods are suitable for analysis. However, DNA barcoding is easier and widely practiced. Hence, it can be concluded that DNA barcoding is a useful tool in determining the medicinal and commercial value of honey.