AIMC Topic: Plant Physiological Phenomena

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Deep Learning for Plant Stress Phenotyping: Trends and Future Perspectives.

Trends in plant science
Deep learning (DL), a subset of machine learning approaches, has emerged as a versatile tool to assimilate large amounts of heterogeneous data and provide reliable predictions of complex and uncertain phenomena. These tools are increasingly being use...

Machine learning modeling of plant phenology based on coupling satellite and gridded meteorological dataset.

International journal of biometeorology
Changes in the timing of plant phenological phases are important proxies in contemporary climate research. However, most of the commonly used traditional phenological observations do not give any coherent spatial information. While consistent spatial...

Discrimination of plant root zone water status in greenhouse production based on phenotyping and machine learning techniques.

Scientific reports
Plant-based sensing on water stress can provide sensitive and direct reference for precision irrigation system in greenhouse. However, plant information acquisition, interpretation, and systematical application remain insufficient. This study develop...

A plant-inspired robot with soft differential bending capabilities.

Bioinspiration & biomimetics
We present the design and development of a plant-inspired robot, named Plantoid, with sensorized robotic roots. Natural roots have a multi-sensing capability and show a soft bending behaviour to follow or escape from various environmental parameters ...

Hybrid Artificial Root Foraging Optimizer Based Multilevel Threshold for Image Segmentation.

Computational intelligence and neuroscience
This paper proposes a new plant-inspired optimization algorithm for multilevel threshold image segmentation, namely, hybrid artificial root foraging optimizer (HARFO), which essentially mimics the iterative root foraging behaviors. In this algorithm ...

PPDB: A Tool for Investigation of Plants Physiology Based on Gene Ontology.

Interdisciplinary sciences, computational life sciences
Representing the way forward, from functional genomics and its ontology to functional understanding and physiological model, in a computationally tractable fashion is one of the ongoing challenges faced by computational biology. To tackle the standpo...

AdapTree: Data-Driven Approach to Assessing Plant Stress Through the AI-Sensor Synergy.

Sensors (Basel, Switzerland)
This study investigates plant stress assessment by integrating advanced sensor technologies and Artificial Intelligence (AI). Multi-sensor data-including electrical impedance spectroscopy, temperature, and humidity-were used to capture plant physiolo...

Machine learning and its applications in plant molecular studies.

Briefings in functional genomics
The advent of high-throughput genomic technologies has resulted in the accumulation of massive amounts of genomic information. However, biologists are challenged with how to effectively analyze these data. Machine learning can provide tools for bette...

Effects of Plant Species, Insecticide, and Exposure Time On the Efficacy Of Barrier Treatments Against .

Journal of the American Mosquito Control Association
The effect of 5 plant species (arborvitae [], boxwood [ sp., Japanese honeysuckle [], rhododendron [ sp.], and zebra grass []) and 2 rates of lambda-cyhalothrin (3.13 ml and 6.25 ml active ingredient [AI]/liter) on knockdown (1 h) and mortality (24 h...