AIMC Topic: Poaceae

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Integration of reference data from different Rapid-E devices supports automatic pollen detection in more locations.

The Science of the total environment Aug 23, 2022
Pollen is the most common cause of seasonal allergies, affecting over 33 % of the European population, even when considering only grasses. Informing the population and clinicians in real-time about the actual presence of pollen in the atmosphere is e...
Allergens Atmosphere Pollen Reproducibility of Results Poaceae Neural Networks, Computer
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A deep learning approach for orphan gene identification in moso bamboo (Phyllostachys edulis) based on the CNN + Transformer model.

BMC bioinformatics May 5, 2022
BACKGROUND: Orphan gene play an important role in the environmental stresses of many species and their identification is a critical step to understand biological functions. Moso bamboo has high ecological, economic and cultural value. Studies have sh...
Amino Acids Poaceae Gene Expression Regulation, Plant Deep Learning
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Associations between trees and grass presence with childhood asthma prevalence using deep learning image segmentation and a novel green view index.

Environmental pollution (Barking, Essex : 1987) Jun 14, 2021
Limitations of Normalized Difference Vegetation Index (NDVI) potentially contributed to the inconsistent findings of greenspace exposure and childhood asthma. The aim of this study was to use a novel greenness exposure assessment method, capable of o...
Humans Trees Air Pollutants Air Pollution Environmental Exposure Poaceae Particulate Matter Prevalence Deep Learning Child Asthma Cross-Sectional Studies
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Using machine learning to examine street green space types at a high spatial resolution: Application in Los Angeles County on socioeconomic disparities in exposure.

The Science of the total environment May 8, 2021
BACKGROUND: Compared to commonly-used green space indicators from downward-facing satellite imagery, street view-based green space may capture different types of green space and represent how environments are perceived and experienced by people on th...
Parks, Recreational Socioeconomic Factors Trees Poaceae Humans Residence Characteristics Machine Learning Los Angeles
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Assessing alternative methods for unsupervised segmentation of urban vegetation in very high-resolution multispectral aerial imagery.

PloS one May 7, 2020
To analyze types and patterns of greening trends across a city, this study seeks to identify a method of creating very high-resolution urban vegetation maps that scales over space and time. Vegetation poses unique challenges for image segmentation be...
Parks, Recreational Poaceae Trees Cluster Analysis Models, Statistical City Planning Humans Water Resources Soil Philadelphia Cities Normal Distribution Data Accuracy Neural Networks, Computer
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Using machine learning to estimate herbage production and nutrient uptake on Irish dairy farms.

Journal of dairy science Aug 22, 2019
Nutrient management on grazed grasslands is of critical importance to maintain productivity levels, as grass is the cheapest feed for ruminants and underpins these meat and milk production systems. Many attempts have been made to model the relationsh...
Ireland Poaceae Milk Dairying Lactation Nutrients Female Animals Machine Learning Cattle Animal Feed Diet
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Testing the ability of unmanned aerial systems and machine learning to map weeds at subfield scales: a test with the weed Alopecurus myosuroides (Huds).

Pest management science May 21, 2019
BACKGROUND: It is important to map agricultural weed populations to improve management and maintain future food security. Advances in data collection and statistical methodology have created new opportunities to aid in the mapping of weed populations...
Machine Learning Plant Weeds United Kingdom Geographic Mapping Remote Sensing Technology Weed Control Poaceae
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Weed Growth Stage Estimator Using Deep Convolutional Neural Networks.

Sensors (Basel, Switzerland) May 16, 2018
This study outlines a new method of automatically estimating weed species and growth stages (from cotyledon until eight leaves are visible) of in situ images covering 18 weed species or families. Images of weeds growing within a variety of crops were...
Plant Leaves Poaceae Polygonum Neural Networks, Computer Image Processing, Computer-Assisted
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Integrating multiple vegetation indices via an artificial neural network model for estimating the leaf chlorophyll content of Spartina alterniflora under interspecies competition.

Environmental monitoring and assessment Oct 31, 2017
The invasive species Spartina alterniflora and native species Phragmites australis display a significant co-occurrence zonation pattern and this co-exist region exerts most competitive situations between these two species, competing for the limited s...
Chlorophyll Plant Leaves Poaceae Neural Networks, Computer Soil Environmental Monitoring
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Differentiating Thamnocalamus Munro from Fargesia Franchet emend. Yi (Bambusoideae, Poaceae): novel evidence from morphological and neural-network analyses.

Scientific reports Jun 23, 2017
Fargesia Franchet emend. Yi is closely allied with Thamnocalamus Munro but differs in many major morphological characteristics. Based on traditional morphological characters, it is difficult to differentiate these two genera. The current study measur...
Principal Component Analysis Neural Networks, Computer Models, Theoretical Ecotype Phylogeny Cluster Analysis Poaceae Inflorescence Geography
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