AIMC Topic: Flowers

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Identifying Cocoa Flower Visitors: A Deep Learning Dataset.

Scientific data Jul 28, 2025
Cocoa is a multi-billion-dollar industry but research on improving yields through pollination remains limited. New embedded hardware and AI-based data analysis is advancing information on cocoa flower visitors, their identity and implications for yie...
Animals Flowers Pollination Cacao China Insecta Deep Learning
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Optimization of a multi-environmental detection model for tomato growth point buds based on multi-strategy improved YOLOv8.

Scientific reports Jul 16, 2025
Tomato growing points and flower buds serve as vital physiological indicators influencing yield quality, yet their detection remains challenging in complex facility environments. This study develops an improved YOLOv8 model for robust flower bud dete...
Flowers Environment Agriculture Algorithms Solanum lycopersicum
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Optimizing drone-based pollination method by using efficient target detection and path planning for complex durian orchards.

Scientific reports Jul 1, 2025
Durian is a valuable tropical fruit whose pollination heavily relies on bats and nocturnal insects. However, environmental degradation and pesticide usage have reduced insect populations, leading to inefficient natural pollination. This study propose...
Agriculture Fruit Pollination Flowers Algorithms Animals
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Delayed flowering phenology of red-flowering plants in response to hummingbird migration.

Current biology : CB Apr 14, 2025
The radiation of angiosperms is marked by a phenomenal diversity of floral size, shape, color, scent, and reward. The multi-dimensional response to selection to optimize pollination has generated correlated suites of these floral traits across distan...
Pollination Color Animals Magnoliopsida Birds Seasons Animal Migration Pigmentation Flowers North America
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A machine learning approach fusing multisource spectral data for prediction of floral origins and taste components of Apis cerana honey.

Food research international (Ottawa, Ont.) Feb 25, 2025
This study explores the use of near-infrared (NIR), mid-infrared (MIR), and Raman spectral fusion for the rapid prediction of floral origins and main taste components in Apis cerana (A. cerana) honey. Feature-level fusion with the partial least squar...
Sugars Taste Flowers Machine Learning Bees Animals Amino Acids Spectrum Analysis, Raman Spectroscopy, Near-Infrared Honey Least-Squares Analysis
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Analysis of the genetic basis of fiber-related traits and flowering time in upland cotton using machine learning.

TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik Jan 24, 2025
Cotton is an important crop for fiber production, but the genetic basis underlying key agronomic traits, such as fiber quality and flowering days, remains complex. While machine learning (ML) has shown great potential in uncovering the genetic archit...
Phenotype Genome-Wide Association Study Machine Learning Cotton Fiber Gossypium Polymorphism, Single Nucleotide Quantitative Trait Loci Flowers
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Feedback regulation of mA modification creates local auxin maxima essential for rice microsporogenesis.

Developmental cell Jan 13, 2025
N-methyladenosine (mA) RNA modification and its effectors control various plant developmental processes, yet whether and how these effectors are transcriptionally controlled to confer functional specificity so far remain elusive. Herein, we show that...
Oryza Indoleacetic Acids Meiosis Adenosine Flowers Plant Proteins Gametogenesis, Plant Gene Expression Regulation, Plant Feedback, Physiological
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Integrated of Hyperspectral Imaging and Machine Learning Algorithms for Nondestructive Detection of Therapeutic Properties of Plants.

Chemistry & biodiversity Jan 13, 2025
The approaches used to determine the medicinal properties of the plants are often destructive, labor-intensive, time-consuming, and expensive, making it impossible to analyze their quality analysis online. Performance of hyperspectral imaging (HSI) i...
Flowers Hyperspectral Imaging Plant Roots Plants, Medicinal Machine Learning Support Vector Machine Plant Leaves Algorithms
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Characterizing Chinese saffron Origin, Age and grade using VNlR hyperspectral imaging and Machine learning.

Food research international (Ottawa, Ont.) Jan 2, 2025
Saffron (Crocus sativus L.), the dried stigma, is an extremely valuable spice and medicinal herb, whose economic value is affected by geographical origin, age and grade. In this study, we proposed a method to identify saffron from different Chinese o...
Crocus Spices Support Vector Machine Machine Learning Flowers Algorithms Spectroscopy, Near-Infrared Hyperspectral Imaging China
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Multitemporal monitoring of forest indicator species using UAV and machine learning image recognition.

Environmental monitoring and assessment Dec 2, 2024
In natural restoration, it is important to improve the efficiency of monitoring. Remote sensing using unmanned aerial vehicle (UAV) platforms plays a major role in improving monitoring efficiency. UAV platforms are particularly suited for monitoring ...
Remote Sensing Technology Rhododendron Forests Flowers Machine Learning Unmanned Aerial Devices Japan Environmental Monitoring
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