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...
Software Solanum lycopersicum Pollen Pollen Tube Image Processing, Computer-Assisted Germination
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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 ...
Pollen Particle Size Quercus Algorithms Spectroscopy, Fourier Transform Infrared
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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 ...
Neural Networks, Computer Citrus Pollen Germination Fruit Machine Learning Pollen Tube Temperature
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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...
Deep Learning Air Pollution Pollen Environmental Monitoring Air Pollutants
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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 Poaceae Pollen Environmental Monitoring Models, Statistical Air Pollutants Switzerland Machine Learning Spatio-Temporal Analysis
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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...
Machine Learning Algorithms Bacteria Spectrum Analysis, Raman Pollen Least-Squares Analysis Discriminant Analysis Support Vector Machine Spectroscopy, Fourier Transform Infrared
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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 Algorithms Flowers Pollination 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...
United Kingdom Machine Learning Quercus Spatio-Temporal Analysis Environmental Monitoring Pollen Air Pollution Air Pollutants Particulate Matter
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Identifying influence factors and thresholds of the next day's pollen concentration in different seasons using interpretable machine learning.

The Science of the total environment May 21, 2024
The prevalence of pollen allergies is a pressing global issue, with projections suggesting that half of the world's population will be affected by 2050 according to the estimation of the World Health Organization (WHO). Accurately forecasting pollen ...
Environmental Monitoring Beijing Air Pollutants Seasons Pollen Machine Learning Air Pollution Allergens
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Pollen identification through convolutional neural networks: First application on a full fossil pollen sequence.

PloS one Apr 30, 2024
The automation of pollen identification has seen vast improvements in the past years, with Convolutional Neural Networks coming out as the preferred tool to train models. Still, only a small portion of works published on the matter address the identi...
Pollen Neural Networks, Computer Fossils Machine Learning
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