AIMC Topic: Pollination

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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...

Wearable Sensors Assess the Effects of Human-Robot Collaboration in Simulated Pollination.

Sensors (Basel, Switzerland)
Pollination for indoor agriculture is hampered by environmental conditions, requiring farmers to pollinate manually. This increases the musculoskeletal illness risk of workers. A potential solution involves Human-Robot Collaboration (HRC) using weara...

Deep SE-BiLSTM with IFPOA Fine-Tuning for Human Activity Recognition Using Mobile and Wearable Sensors.

Sensors (Basel, Switzerland)
Pervasive computing, human-computer interaction, human behavior analysis, and human activity recognition (HAR) fields have grown significantly. Deep learning (DL)-based techniques have recently been effectively used to predict various human actions u...

A search and rescue robot search method based on flower pollination algorithm and Q-learning fusion algorithm.

PloS one
Search algorithm plays an important role in the motion planning of the robot, it determines whether the mobile robot complete the task. To solve the search task in complex environments, a fusion algorithm based on the Flower Pollination algorithm and...

Shape classification technology of pollinated tomato flowers for robotic implementation.

Scientific reports
Three pollination methods are commonly used in the greenhouse cultivation of tomato. These are pollination using insects, artificial pollination (by manually vibrating flowers), and plant growth regulators. Insect pollination is the preferred natural...