AIMC Topic: Pollination

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Deep Learning-Driven Discovery of Bee-Safe Isoxazoline Pesticide Candidates.

Journal of agricultural and food chemistry
Isoxazoline pesticides, such as fluxametamide, while effective against parasites and pests, pose a severe environmental threat due to their high toxicity to honeybees - critical pollinators essential for ecosystem health and food security. Existing p...

Robotic cross-pollination of genetically modified flowers.

Science robotics
Engineered tomato plants produced flowers with visible stigmas that a robot could detect and pollinate faster than a human.

Utilizing CNNs for classification and uncertainty quantification for 15 families of European fly pollinators.

PloS one
Pollination is essential for maintaining biodiversity and ensuring food security, and in Europe it is primarily mediated by four insect orders (Coleoptera, Diptera, Hymenoptera, Lepidoptera). However, traditional monitoring methods are costly and tim...

Identifying Cocoa Flower Visitors: A Deep Learning Dataset.

Scientific data
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...

Optimizing drone-based pollination method by using efficient target detection and path planning for complex durian orchards.

Scientific reports
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...

Delayed flowering phenology of red-flowering plants in response to hummingbird migration.

Current biology : CB
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...

Assessing foraging landscape quality in Quebec's commercial beekeeping through remote sensing, machine learning, and survival analysis.

Journal of environmental management
Honey bees (Apis mellifera) play an important role in our agricultural systems. In recent years, beekeepers have reported high colony mortality rates in several parts of the world. Inadequate foraging landscapes are often cited as a major factor dete...

Deep learning approach for detecting tomato flowers and buds in greenhouses on 3P2R gantry robot.

Scientific reports
In recent years, significant advancements have been made in the field of smart greenhouses, particularly in the application of computer vision and robotics for pollinating flowers. Robotic pollination offers several benefits, including reduced labor ...

Estimation of the amount of pear pollen based on flowering stage detection using deep learning.

Scientific reports
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...

Evaluation of Biomechanical and Mental Workload During Human-Robot Collaborative Pollination Task.

Human factors
OBJECTIVE: The purpose of this study is to identify the potential biomechanical and cognitive workload effects induced by human robot collaborative pollination task, how additional cues and reliability of the robot influence these effects and whether...