Different Types Of Pollen Research Articles

Pollen recognition through an open-source web-based system: automated particle counting for aerobiological analysis

Airborne pollen is produced by plants for their sexual reproduction and can have negative impacts on public health. The current monitoring systems are based on manual sampling processes which are tedious and time-consuming. Due to that, pollen concentrations are often reported with a delay of up to one week. In this study, we present an open-source user-friendly web application powered by deep learning for automatic pollen count and classification. The application aims to simplify the process for non-IT users to count and classify different types of pollen, reducing the effort required compared to manual methods. To overcome the challenges of acquiring large labelled datasets, we propose a semi-automatic labelling approach, which combines human expertise and machine learning techniques. The results demonstrate that our approach significantly reduces the effort required for users to count and classify pollen taxa accurately. The model achieved high precision and recall rates (>96%\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\varvec{>96\\%}$$\\end{document} mAP@0.5), enabling reliable pollen identification and prediction.

Specific functions of single pistil S-RNases in S-gene homozygous Pyrus germplasm

Gametophytic self-incompatibility (SI) is regulated by S-allele recognition; that is, pollen in a style with the same S-genotype will undergo programmed cell death and stop growing so that it is unable to complete double fertilization, ultimately resulting in the SI response. S-RNase is the female determinant of SI in pear (Pyrus). In the Pyrus genome, there are two different S-RNase alleles at the S-locus, which generate two different S-RNase products in the pistil. The extracted S-glycoprotein is actually a protein complex. In this study, artificial self-pollination was conducted at the bud stage to overcome SI in ‘Huanghua’ (S1S2) pear. Seven plants homozygous for S1-RNase and four homozygous for S2-RNase were selected from the selfed progeny of ‘Huanghua’ by S-gene molecular identification biotechnology. We investigated the function of single S-RNases isolated from the pistils of S-gene homozygous Pyrus germplasm. The pollen of ‘Huanghua’ could smoothly pass through the style of the S-gene homozygous germplasm and complete fertilization. S-RNases were extracted from flower styles of different genotypes and used to treat different types of pollen. The S-RNase from ‘Huanghua’ completely inhibited the growth of S1S2, S1S1, and S2S2 pollen, while the S-RNase from homozygous germplasm allowed some S1S2 pollen and different single genotypes of pollen to continue growing. These results further validate the core events of SI including cytoskeleton depolymerization and programmed cell death. By iTRAQ-based proteomic analysis of style proteins, a total of 13 S-RNase-related proteins were identified. In summary, we have created reliable S-RNase gene homozygous germplasm, which will play a crucial role in further research on SI in pear and in the development of the pear industry.

Automatic pollen recognition using convolutional neural networks: The case of the main pollens present in Spanish citrus and rosemary honey

The automation of honey pollen visual sorting overcomes the limitations of the conventional procedure helping the specialist in this time-consuming task. In this work, a novel and comprehensive Ground Truth of almost 19,000 images (from optical microscopy) of the 16 most abundant types of grains/pollen particles present in citrus and rosemary honey from Spain was constructed. This task was assisted by a HoneyApp (also developed herein) for the labelling and annotation process. Subsequently, the effectiveness of different pre-existing automatic pollen recognizers based on convolutional neural networks (CNN) (VGG16, VGG19, InceptionV3, Xception, ResNet50, DenseNet201, MobileNetV2 and EfficientNetV2M) was tested together with a new network proposed in this paper (PolleNetV1). The extreme complexity of those pre-existing CNN and extensive use of millions of parameters makes this new proposal especially promising. Although with a slightly lower accuracy (average 96%) in determining the relative frequencies of different types of pollen grains/particles, it has considerable advantages such as simplicity and ability to be included in the future functionality to automate pollen recognition in honey. This is the first step to finally achieving an objective tool that allows the correct labelling of any types of pollen in honey, thus contributing to its transparency in the market.

Pollination, pollen tube growth, and fertilization independently contribute to fruit set and development in tomato.

In flowering plants, pollination, pollen tube growth, and fertilization are regarded as the first hierarchical processes of producing offspring. However, their independent contributions to fruit set and development remain unclear. In this study, we examined the effect of three different types of pollen, intact pollen (IP), soft X-ray-treated pollen (XP) and dead pollen (DP), on pollen tube growth, fruit development and gene expression in "Micro-Tom" tomato. Normal germination and pollen tube growth were observed in flowers pollinated with IP; pollen tubes started to penetrate the ovary at 9h after pollination, and full penetration was achieved after 24h (IP24h), resulting in ~94% fruit set. At earlier time points (3 and 6h after pollination; IP3h and IP6h, respectively), pollen tubes were still in the style, and no fruit set was observed. Flowers pollinated with XP followed by style removal after 24h (XP24h) also demonstrated regular pollen tubes and produced parthenocarpic fruits with ~78% fruit set. As expected, DP could not germinate and failed to activate fruit formation. Histological analysis of the ovary at 2 days after anthesis (DAA) revealed that IP and XP comparably increased cell layers and cell size; however, mature fruits derived from XP were significantly smaller than those derived from IP. Furthermore, there was a high correlation between seed number and fruit size in fruit derived from IP, illustrating the crucial role of fertilization in the latter stages of fruit development. RNA-Seq analysis was carried out in ovaries derived from IP6h, IP24h, XP24h and DP24h in comparison with emasculated and unpollinated ovaries (E) at 2 DAA. The results revealed that 65 genes were differentially expressed (DE) in IP6h ovaries; these genes were closely associated with cell cycle dormancy release pathways. Conversely, 5062 and 4383 DE genes were obtained in IP24h and XP24h ovaries, respectively; top enriched terms were mostly associated with cell division and expansion in addition to the 'plant hormone signal transduction' pathway. These findings indicate that full penetration of pollen tubes can initiate fruit set and development independently of fertilization, most likely by activating the expression of genes regulating cell division and expansion.

Virtual Impactor-Based Label-Free Pollen Detection using Holography and Deep Learning.

Exposure to bio-aerosols such as pollen can lead to adverse health effects. There is a need for a portable and cost-effective device for long-term monitoring and quantification of various types of pollen. To address this need, we present a mobile and cost-effective label-free sensor that takes holographic images of flowing particulate matter (PM) concentrated by a virtual impactor, which selectively slows down and guides particles larger than 6 μm to fly through an imaging window. The flowing particles are illuminated by a pulsed laser diode, casting their inline holograms on a complementary metal-oxide semiconductor image sensor in a lens-free mobile imaging device. The illumination contains three short pulses with a negligible shift of the flowing particle within one pulse, and triplicate holograms of the same particle are recorded at a single frame before it exits the imaging field-of-view, revealing different perspectives of each particle. The particles within the virtual impactor are localized through a differential detection scheme, and a deep neural network classifies the pollen type in a label-free manner based on the acquired holographic images. We demonstrated the success of this mobile pollen detector with a virtual impactor using different types of pollen (i.e., bermuda, elm, oak, pine, sycamore, and wheat) and achieved a blind classification accuracy of 92.91%. This mobile and cost-effective device weighs ∼700 g and can be used for label-free sensing and quantification of various bio-aerosols over extended periods since it is based on a cartridge-free virtual impactor that does not capture or immobilize PM.

PollenDetect: An Open-Source Pollen Viability Status Recognition System Based on Deep Learning Neural Networks.

Pollen grains, the male gametophytes for reproduction in higher plants, are vulnerable to various stresses that lead to loss of viability and eventually crop yield. A conventional method for assessing pollen viability is manual counting after staining, which is laborious and hinders high-throughput screening. We developed an automatic detection tool (PollenDetect) to distinguish viable and nonviable pollen based on the YOLOv5 neural network, which is adjusted to adapt to the small target detection task. Compared with manual work, PollenDetect significantly reduced detection time (from approximately 3 min to 1 s for each image). Meanwhile, PollenDetect can maintain high detection accuracy. When PollenDetect was tested on cotton pollen viability, 99% accuracy was achieved. Furthermore, the results obtained using PollenDetect show that high temperature weakened cotton pollen viability, which is highly similar to the pollen viability results obtained using 2,3,5-triphenyltetrazolium formazan quantification. PollenDetect is an open-source software that can be further trained to count different types of pollen for research purposes. Thus, PollenDetect is a rapid and accurate system for recognizing pollen viability status, and is important for screening stress-resistant crop varieties for the identification of pollen viability and stress resistance genes during genetic breeding research.

The microbiological quality of fresh bee pollen during the harvesting process

In recent years, bee pollen has been widely used as a dietary supplement due to its high nutritional value. However, the quality of the final product is strongly affected by the practices followed by beekeepers during the collection process. In Greece, bee pollen is mostly marketed and consumed in fresh form. In the present study, the harvesting period under different environmental conditions, the use of different types of pollen traps [outdoor front (A), indoor bottom (B) and indoor roof (C)] and the time staying in them (0,1,2 days) were evaluated as possible sources of contamination of the final product. Microbial load variability was studied for Mesophilic Total Viable Count (MTVC), Yeasts and Moulds (Y&M), Enterobacteriaceae (ENT), Lactic Acid Bacteria (LAB) and Escherichia coli. The results of the study highlight the advantages of using indoor traps and suggest avoiding early spring collection. Delayed harvesting had an impact on the microbial load of pollen, especially on the growth of MTVC and ENT, with values higher than 5 and 2 log cfu/g, respectively, exceeding the market limits as defined in food hygiene standards. Indeed, the highest counts of MTVC and ENT were detected after 2 days of pollen staying in outdoor front traps (5.98 and 4.81 log cfu/g, respectively). The results of the study will be a helpful guide in giving the appropriate beekeeping practices for the production of fresh pollen with microbial load harmonized with hygienic standards.

Millennial scale erosion and sedimentation investigation in karst watersheds using dating and palynology

The sedimentary sequence deposited in a depression provides good opportunity for karst watershed soil loss reconstruction. Extensive sediment dating and soil loss estimation in karst areas of Southwest China have been carried out in the past few decades. Unfortunately, most studies only revealed soil loss over the last 50–100 years by using 137Cs and/or 210Pb. This study attempts to reconstruct soil erosion in a watershed over the past millennium using sediment dating combined with palynological techniques. In this study, two karst watersheds with different degrees of rocky desertification were selected, and soil profile samples were collected from the depressions to determine pollen taxa, 137Cs and soil organic carbon, and then, the optically stimulated luminescence (OSL) and radiocarbon were used to date the sediments in the two profiles. The results showed that erosion rate characteristics in the Liaojiawodang (LJWD, severe rocky desertification) and Dajutang (DJT, mild rocky desertification) watersheds were markedly different over the last 1000 years. On average, the erosion rates of the LJWD and DJT watersheds were 0.13 Mg ha−1 yr−1 and 1.28 Mg ha−1 yr−1, respectively. Overall, the erosion rate in the areas with severe rocky desertification was obviously small in the past millennium, and there was no serious soil loss. This result indicated that rocky desertification developed at least 1000 years ago. Pollen analysis indicated that soil erosion changes in both watersheds over the past 1000 years were well correlated with the change in crop pollen indicating human farming activities. Based on changes in the content of different types of pollen in sediments, the change in soil erosion can be linked to the change in land use and vegetation landscape. Overall, this work improves our understanding of the relationship between soil erosion and agricultural activities and vegetation landscape change in karst watersheds.

Desenvolvimento de colônias de abelhas sem ferrão uruçu alimentadas com o suplemento aminoácido vitamínico

ABSTRACT This study proposes to investigate the influence of a vitamin-amino acid supplement on the weight of colonies of uruçu stingless bees (Melipona scutellaris). The experiment was carried out with 24 colonies and three treatments, which consisted of a solution of different proportions of supplement (0, 3, and 5 mL) diluted in syrup (water and sugar). Although this supplement is effective and indicated for other species of domestic animals, analysis of variance with repeated measures over time did not reveal a significant effect (P > 0.05) of its dose on the weight of the hives, showing that the supply of the vitamin-amino acid supplement does not meet the nutritional requirements of the colony. The use of this product did not have a positive effect on the development of the uruçu bee colonies, so it should not be employed as a major source of amino acids and vitamins in the diet of bees. Beekeepers are suggested to provide uruçu bees with an abundant diversity of plants so that they have access to different types of pollen as a source of nutrients.

Within city spatiotemporal variation of pollen concentration in the city of Toronto, Canada

BackgroundThe exacerbation of asthma and respiratory allergies has been associated with exposure to aeroallergens such as pollen. Within an urban area, tree cover, level of urbanization, atmospheric conditions, and the number of source plants can influence spatiotemporal variations in outdoor pollen concentrations. ObjectiveWe analyze weekly pollen measurements made between March and October 2018 over 17 sites in Toronto, Canada. The main goals are: to estimate the concentration of different types of pollen across the season; estimate the association, if any, between pollen concentration and environmental variables, and provide a spatiotemporal surface of concentration of different types of pollen across the weeks in the studied period. MethodsWe propose an extension of the land-use regression model to account for the temporal variation of pollen levels and the high number of measurements equal to zero. Inference is performed under the Bayesian framework, and uncertainty of predicted values is naturally obtained through the posterior predictive distribution. ResultsTree pollen was positively associated with commercial areas and tree cover, and negatively associated with grass cover. Both grass and weed pollen were positively associated with industrial areas and TC brightness and negatively associated with the northing coordinate. The total pollen was associated with a combination of these environmental factors. Predicted surfaces of pollen concentration are shown at some sampled weeks for all pollen types. SignificanceThe predicted surfaces obtained here can help future epidemiological studies to find possible associations between pollen levels and some health outcome like respiratory allergies at different locations within the study area.

Pollen analysis of honeys from Yığılca region (Düzce), Turkey

The aim of this study is to determine the plant species preferred by Apis mellifera L., which is a valuable genotype in terms of vitality and high honey production. For this purpose, seven honey samples from Yığılca region in Düzce (Turkey) were examined for pollen analysis. As a result of the pollen analysis on these samples, it was determined that Yığılca local honeybee use pollen grains of 43 different taxa from 26 families. Six samples of honey were unifloral (> 45% pollen of one taxon in sample) with four being unifloral for Rhododendron ponticum and two for Castanea sativa. One sample of honey was classified as multifloral with the percentages of secondary and rare pollen groups. The honeys had contained 14 to 30 different types of pollen. The average number of pollen types per honey was 21. The dominant groups of pollen grains were determined as Rhododendron ponticum in 4 samples and Castanea sativa in 2 samples. Secondary pollen components were from 3 taxa: Fagus orientalis, Rhododendron ponticum and Quercus sp. Four pollen types occurred as ‘minor’ types and pollen grains of 37 taxa were in rare quantities. Asteraceae, Fabaceae, Fagaceae, Lamiaceae and Rosaceae were the most represented families in honey samples.

Spatial and Temporal Variations of Airborne Poaceae Pollen along an Urbanization Gradient Assessed by Different Types of Pollen Traps

Grass pollen allergy is widespread all around the globe. With an increasing number of people living in cities, the examination of grass pollen levels within cities and their surroundings has increased in importance. The aim of this study was to examine different temporal and spatial scales of grass pollen concentration and deposition across urban and semi-rural environments in the years 2019 and 2020. We installed different types of pollen traps in the city of Ingolstadt (Bavaria, Germany) and its surroundings: volumetric pollen traps at roof level to assess background pollen concentration and gravimetric pollen traps and portable volumetric traps at street level. We considered grass pollen concentration and deposition in the context of land use and management. Our data showed that the grass pollen season in 2020 was longer and more intense than in 2019. Background grass pollen concentration was generally higher at the semi-rural site in both years: peak values were eight times (2019) and more than four times (2020) higher, and Seasonal Pollen Index was more than four times and almost three times higher in 2019 and 2020, respectively. Analyses of spatial variations measured at street level revealed higher numbers for pollen deposition and concentrations at semi-rural than at urban sites. Recorded values were linked to local vegetation and the management of grass areas surrounding the traps. Analyses of diurnal variations at street level in June 2019 showed that pollen concentration for all sites, independent of their degree of urbanization, were highest at noon (22.2 pollen grains/m³ vs. 8.5 pollen grains/m³ in the morning and 10.4 pollen grains/m³ in the evening). Diurnal variations at roof level showed similarities for the same days but differed when considering the whole season. Our data suggest the importance of the management of grass areas as areas cut earlier have a decreased amount of emitted pollen.

Estimation of pollen counts from light scattering intensity when sampling multiple pollen taxa – establishment of an automated multi-taxa pollen counting estimation system (AME system)

Abstract. Laser optics have long been used in pollen counting systems. To clarify the limitations and potential new applications of laser optics for automatic pollen counting and discrimination, we determined the light scattering patterns of various pollen types, tracked temporal changes in these distributions, and introduced a new theory for automatic pollen discrimination. Our experimental results indicate that different pollen types often have different light scattering characteristics, as previous research has suggested. Our results also show that light scattering distributions did not undergo significant temporal changes. Further, we show that the concentration of two different types of pollen could be estimated separately from the total number of pollen grains by fitting the light scattering data to a probability density curve. These findings should help realize a fast and simple automatic pollen monitoring system.

Pollen calendars and regional gradients as information tools in the Extremadura pollen monitoring network (SW Spain)

Pollen allergies are one of the most important problems among respiratory diseases in today’s society. The creation and development of aerobiological information tools are useful to provide information to patients and doctors. In this work, we analysed the pollen spectrum of Extremadura to generate pollen calendars for Badajoz, Caceres, Don Benito, Plasencia and Zafra. Additionally, we analysed regional pollen gradients and plotted the main pollen season (MPS) characteristics (start date, peak date, end date and duration) in each city. In Extremadura, 35–40 different types of pollen are frequently identified, the most abundant of which (in decreasing order) belong to Quercus, Poaceae, Olea, Cupressaceae, Platanus, Plantago and Pinus. The dates when the highest accumulation of pollen occurs in the air are from mid-April to the end of May in Badajoz and Caceres; from mid-March to early June for Don Benito; from mid-April to early June for Plasencia; and from mid-April to 10 June for Zafra. Moreover, it could be confirmed that in the Extremadura region, the start date and the peak date occur earlier in the cities in the south of the region and that the duration of the pollen season is longer in these cities. The differences observed among cities may be due to the varieties of urban species and their management (pruning and irrigation), the influence of peri-urban landscapes, medium- and long-distance pollen transport and climate. The representation and geolocation of pollen calendars obtained using geographic gradients provide information in a simple, fast and visual way and can be of great interest to allergic patients and health professionals.

William Frankland: the “grandfather of allergy”

Photo credit: Imperial College London William Frankland (“Bill”), the British clinical allergist who transformed global understanding of allergies, has died aged 108. He developed the pollen count in order to...

Foraging preferences of honey bees Apis cerana in Dakshina Kannada, Karnataka, India

Honey bees visit flowers for collecting nectar and pollen. Pollen serves as a source of protein for the survival of honeybees. To understand the dependence and preference of the honey bee species Apis cerana on different pollen resources, we carried out a study to analyze the distribution of different types of pollen in honey in various regions of the coastal plains of the Western Ghats. Fourteen different honey samples from different sites ranging in elevation from 55m to 135m were collected and analyzed. Acetolysis and centrifugation were used for pollen extraction from different honey samples. The extracted pollen was mixed with glycerin jelly and transferred to a glass slide for microscopic analysis. The primary source of pollen as revealed by the current study were found to be Areca catechu, Cocos nucifera, Ixora coccinea, Mimosa pudica, and Psidium guajava. Morphotype analysis revealed 12 different plants to be the source of the pollen. Each honey sample collected from different locations, however, had only three to six types of pollen indicating that honeybees visit a narrow or a small number of pollen sources. Therefore, based on our study, we conclude that lesser types of pollen in each honey sample indicates that their food resources are getting limited. Therefore, it is necessary to conserve pollen resources for the better survival of honey bees and the environment.

High ambient levels of grass, weed and other pollen are associated with asthma admissions in children and adolescents: A large 5‐year case‐crossover study

Pollen is an important aeroallergen that triggers asthma exacerbations in children, but we know little about the impact of different pollen types in cities with varying climatic conditions and pollen seasons. We aimed to assess the role of ambient level of different types of pollen on a large time series of child and adolescent asthma hospitalizations in Sydney, Australia. Childhood asthma hospitalization and the daily ambient pollen concentrations of different species were collected in South-West Sydney. With a bidirectional case-crossover design, we fitted conditional logistic regression models to measure the associations between instantaneous and up to 3days lagged effects of pollen concentrations on asthma hospitalizations after controlling for potential confounders and testing for interactions. A total of 2098 children, more boys (59.7%) and 2-5years old (62.6%), were hospitalized due to asthma. The geometric mean concentration of Cupressus, 7.88 [5.02] grains/m3 , was the highest during the study period. The increase from 75th to 90th percentile of grass (OR=1.037, 95% CI 1.005-1.070), weed other than Plantago species (OR=1.053, 95% CI 1.009-1.098) and unclassified pollen (OR=1.034, 95% CI 1.010-1.058) were significantly associated with the odds of asthma hospitalizations. Boys were at greater risk of asthma exacerbations associated with grass (OR=1.046, 95% CI 1.003-1.090) and unclassified pollen (OR=1.041, 95% CI 1.010-1.073). There was evidence of effect modification by age groups for Cupressus, conifer, total tree and total pollen. Although boys are more vulnerable to grass pollen, weed, and other pollen are also important triggers of asthma exacerbations in all children and adolescents. These findings are important for urban green space planning and the development of pollen monitoring systems for families with children at risk of asthma exacerbations during peak pollen seasons.

Separation of different pollen types by chemotactile sensing in Bombus terrestris.

When tasting food, animals rely on chemical and tactile cues, which determine the animal's decision on whether to eat food. As food nutritional composition has enormous consequences for the survival of animals, food items should generally be tasted before they are eaten or collected for later consumption. Even though recent studies have confirmed the importance of, for example, gustatory cues, compared with olfaction only little is known about the representation of chemotactile stimuli at the receptor level (let alone higher brain centers) in animals other than vertebrates. To better understand how invertebrates may process chemotactile cues, we used bumblebees as a model species and combined electroantennographical (EAG) recordings with a novel technique for chemotactile antennal stimulation in bees. The recorded EAG responses to chemotactile stimulation clearly separated volatile compounds by both compound identity and concentration, and could be successfully applied to test the receptor activity evoked by different types of pollen. We found that two different pollen types (apple and almond; which were readily distinguished by bumblebees in a classical conditioning task) evoked significantly distinct neural activity already at the antennal receptor level. Our novel stimulation technique therefore enables investigation of chemotactile sensing, which is highly important for assessing food nutritional quality while foraging. It can further be applied to test other chemosensory behaviors, such as mate or nest mate recognition, or to investigate whether toxic substances, e.g. in pollen, affect neuronal separation of different food types.

CARACTERÍSTICAS POLÍNICAS DE MÉIS DE Apis mellifera L. (HYMENOPTERA, APIDAE, APINI) DA REGIÃO DO LITORAL NORTE, ESTADO DO RIO GRANDE DO SUL

The northern coastal of Rio Grande do Sul is filled with rare ecosystems and a biodiversity with a high environmental vulnerability, resulted especially by the urban development in this region. Nevertheless, there is still good part of the population in this region that keeps small farms, which have an intense apicultural activity, making this part of the state an important producer and exporter of honey. Honey is the final result of the flower's nectar transformation and dehydration process performed by the honeybees, and its characteristics depend mainly by the local existing vegetation. The objective of this work is to determine the floral origin of the different types of honey produced in the northern coastal plain of Rio Grande do Sul, identifying different types of pollen and plant species used by Apis mellifera for the honey production. In qualitative analyzes, the most frequent taxas were found in: Eucalyptus sp., Mimosa sp., Ilex sp., Hovenia dulcis Thunb. and Sebastiana brasiliensis Spreng.. The different types of honey were defined as poliflorals. The botanical families Myrtaceae, Fabaceae and Asteraceae were present in all samples, but at different quantitative standards.

Stigma Diversity in Tropical Legumes with Considerations on Stigma Classification

The great stigma diversity in angiosperms implies a choice of criteria for stigma classification, which nowadays is characterized as dry (= little or no secretory surface and exudate retained by the cuticle and/or protein pellicle), wet (= conspicuous secretory surface, abundant in fluid exudate) and semidry (exudate retained by cuticle and/or protein pellicle). Despite being a very species-rich family, whose representatives exhibit a wide floral variation, no comparative studies of stigma diversity have been done for the whole Leguminosae. In order to assess the stigma morphological diversity in legumes and to evaluate the criteria used in the main classifications of the stigma, we compared the stigma morphology in 15 distinct legume lineages. In addition, we evaluated the stigma classification in other 152 legume species whose morphology was already described in the literature. Stigmas were removed from floral buds and flowers and processed for analyses under scanning electron and light microscopes. The stigma of the study legumes exhibits quite variable morphology, mainly concerning the diameter, the occurrence of an orifice or a furrow, the coating, the cellular composition, and the occurrence, chemical nature and release mechanism of the exudate. This diversity appears to be related mainly to the evolutionary history of the group and also to the selective pressures exerted by different types of pollen and pollinator. More conflicting criteria for stigma classification lie in defining the semidry type, found mostly in papilionoids. For better stigma classification we suggest that stigma morphology be evaluated at the time prior to anthesis, when the cuticle is not yet broken and the exudate is not exposed or drained. In addition, several techniques should be employed for a better classification.