AIMC Topic: Pollen

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Semi-automated high content analysis of pollen performance using tubetracker.

Plant reproduction Jun 16, 2025
TubeTracker provides a method to partially automate analysis of pollen tube growth using live imaging. Pollen function is critical for successful plant reproduction and crop productivity and it is important to develop accessible methods to quantitati...
Image Processing, Computer-Assisted Germination Solanum lycopersicum Software Pollen Pollen Tube
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Pollen morphology, deep learning, phylogenetics, and the evolution of environmental adaptations in Podocarpus.

The New phytologist Jun 3, 2025
Podocarpus pollen morphology is shaped by both phylogenetic history and the environment. We analyzed the relationship between pollen traits quantified using deep learning and environmental factors within a comparative phylogenetic framework. We inves...
Phylogeny Deep Learning Altitude Temperature Biological Evolution Pollen Fossils Adaptation, Physiological Environment
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Digital image processing combined with machine learning: A novel approach for bee pollen classification.

Food research international (Ottawa, Ont.) Apr 22, 2025
The classification of bee pollen is crucial for ensuring product authenticity, quality control, and fraud prevention, particularly given the high commercial value of stingless bee pot-pollen. Although traditional pollen analysis methods are available...
Animals Image Processing, Computer-Assisted Color Bees Pollen Discriminant Analysis Machine Learning Algorithms
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Analytical and experimental solutions for Fourier transform infrared microspectroscopy measurements of microparticles: A case study on Quercus pollen.

Analytica chimica acta Feb 28, 2025
BACKGROUND: FTIR microspectroscopy is a popular non-destructive technique for chemical analysis and identification of microparticles, such as microplastics, pollen, spores, microplankton organisms, sediments and microfossils. Unfortunately, measured ...
Particle Size Quercus Algorithms Spectroscopy, Fourier Transform Infrared Pollen
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Modelling of pome fruit pollen performance using machine learning.

Scientific reports Feb 26, 2025
Agriculture, particularly fruit production, is considered a crucial industry with a significant economic impact in many countries. Extreme fluctuations in air temperature can negatively affect the flowering periods of fruit species. Therefore, it is ...
Germination Fruit Pollen Pollen Tube Citrus Machine Learning Temperature Neural Networks, Computer
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Imaging pollen using a Raspberry Pi and LED with deep learning.

The Science of the total environment Oct 19, 2024
The production of low-cost, small footprint imaging sensor would be invaluable for airborne global monitoring of pollen, which could allow for mitigation of hay fever symptoms. We demonstrate the use of a white light LED (light emitting diode) to ill...
Pollen Deep Learning Air Pollutants Environmental Monitoring Air Pollution
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Spatiotemporal modelling of airborne birch and grass pollen concentration across Switzerland: A comparison of statistical, machine learning and ensemble methods.

Environmental research Sep 20, 2024
BACKGROUND: Statistical and machine learning models are commonly used to estimate spatial and temporal variability in exposure to environmental stressors, supporting epidemiological studies. We aimed to compare the performances, strengths and limitat...
Betula Switzerland Spatio-Temporal Analysis Models, Statistical Poaceae Environmental Monitoring Machine Learning Air Pollutants Pollen
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Improved Classification Performance of Bacteria in Interference Using Raman and Fourier-Transform Infrared Spectroscopy Combined with Machine Learning.

Molecules (Basel, Switzerland) Jun 21, 2024
The rapid and sensitive detection of pathogenic and suspicious bioaerosols are essential for public health protection. The impact of pollen on the identification of bacterial species by Raman and Fourier-Transform Infrared (FTIR) spectra cannot be ov...
Least-Squares Analysis Support Vector Machine Discriminant Analysis Bacteria Machine Learning Pollen Spectroscopy, Fourier Transform Infrared Spectrum Analysis, Raman Algorithms
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Estimation of the amount of pear pollen based on flowering stage detection using deep learning.

Scientific reports Jun 7, 2024
Pear pollination is performed by artificial pollination because the pollination rate through insect pollination is not stable. Pollen must be collected to secure sufficient pollen for artificial pollination. However, recently, collecting sufficient a...
Pollen Pyrus Flowers Pollination Algorithms Deep Learning
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Local spatiotemporal dynamics of particulate matter and oak pollen measured by machine learning aided optical particle counters.

The Science of the total environment May 25, 2024
Conventional techniques for monitoring pollen currently have significant limitations in terms of labour, cost and the spatiotemporal resolution that can be achieved. Pollen monitoring networks across the world are generally sparse and are not able to...
Air Pollution Environmental Monitoring Machine Learning United Kingdom Quercus Particulate Matter Air Pollutants Pollen Spatio-Temporal Analysis
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