Pollen Sorting
Pollen Sorting - Related Videos
06:34
A Component-resolved Diagnostic Approach for a Study on Grass Pollen Allergens in Chinese Southerners with Allergic Rhinitis and/or Asthma
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Cited by 4 •
2017
This work describes a protocol that uses a component-resolved approach to study sensitization to grass pollen allergens in a cohort of patients from southern China with allergic rhinitis and/or asthma.
08:11
Collection and Identification of Pollen from Honey Bee Colonies
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Cited by 8 •
2021
We describe methods for collecting corbicular pollen from honey bees as well as protocols for color sorting, acetolysis, and microscope slide preparation of pollen for taxonomic identification. In addition, we present pellet color and taxonomic diversity of corbicular pollen collected from five cropping systems using pollen traps.
10:31
A Visual Guide to Sorting Electrophysiological Recordings Using 'SpikeSorter'
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Cited by 6 •
2017
The article shows how to use the program SpikeSorter to detect and sort spikes in extracellular recordings made with multi-electrode arrays.
13:35
Fluorescence Activated Cell Sorting of Plant Protoplasts
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Cited by 91 •
2010
A method for isolating specific cell types from plant material is demonstrated. This technique employs transgenic marker lines expressing fluorescent proteins in particular cell types, cellular dissociation and Fluorescence Activated Cell Sorting. Additionally, a growth setup is established here that facilitates treatment of Arabidopsis thaliana seedlings prior to cell sorting.
06:31
Step-specific Sorting of Mouse Spermatids by Flow Cytometry
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Cited by 11 •
2015
We describe a sorting strategy for mouse spermatids using flow cytometry. Spermatids are sorted into four highly pure populations, including round (spermiogenesis steps 1-9), early elongating (spermiogenesis steps 10-12), late elongating (spermiogenesis steps 13-14) and elongated spermatids (spermiogenesis steps 15-16). DNA staining, size and granulosity are used as selection parameters.
FAQs
Sorting criteria determine what biological question the sample can answer. Size and shape help distinguish pollen types, while surface structure can provide additional identification or sample-separation information. Viability adds a functional dimension by separating grains according to reproductive condition. Selecting criteria that match the study reduces ambiguity and improves consistency when comparing mixed or repeated samples.
Microscopy and image analysis convert visible grain features into a classification process. Researchers can inspect size, shape, and surface structure, then use those observations to distinguish groups within a mixed population. This approach is especially useful when the goal is identification or measurement rather than physical recovery of individual grains. Consistent imaging and interpretation support more reliable comparisons among samples.
Physical separation and image-based classification answer related but different needs. Image analysis primarily identifies or categorizes grains within an observed sample, whereas physical separation is used when selected grains must be isolated for subsequent work. The choice depends on whether the study needs information about pollen characteristics, a selected subset, or both. Combining approaches can connect classification with downstream biological experiments.
A basic workflow starts with controlled sample preparation, followed by examination or separation using microscopy, image analysis, or a physical method. Researchers then classify or isolate grains according to the chosen traits and assess whether the resulting groups are sufficiently consistent for the study. This sequence helps prevent preparation differences from being mistaken for genuine variation in pollen characteristics.
Viability sorting is important because visually similar grains may differ in reproductive capacity. Separating or classifying grains by viability allows researchers to relate pollen condition to fertilization experiments and reproductive function, rather than relying only on appearance. The resulting groups can help distinguish whether an observed outcome reflects pollen traits, the proportion of viable grains, or variation in the original mixed sample.
In plant biology, sorted pollen samples support identification, dispersal studies, and investigations of plant diversity. The same organization is relevant to environmental-change research, where pollen patterns can be examined across samples, and to agriculture, where pollen traits may be connected with reproductive performance. By improving sample consistency, sorting helps researchers interpret relationships between pollen characteristics and broader biological outcomes.