AIMC Topic: Photosynthesis
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Machine learning in photosynthesis: Prospects on sustainable crop development.
Plant science : an international journal of experimental plant biology
Jul 18, 2023
Improving photosynthesis is a promising avenue to increase food security. Studying photosynthetic traits with the aim to improve efficiency has been one of many strategies to increase crop yield but analyzing large data sets presents an ongoing chall...
Detection of Tip-Burn Stress on Lettuce Grown in an Indoor Environment Using Deep Learning Algorithms.
Sensors (Basel, Switzerland)
Sep 24, 2022
Lettuce grown in indoor farms under fully artificial light is susceptible to a physiological disorder known as tip-burn. A vital factor that controls plant growth in indoor farms is the ability to adjust the growing environment to promote faster crop...
A photosynthetic rate prediction model using improved RBF neural network.
Scientific reports
Jun 10, 2022
A photosynthetic prediction rate model is a theoretical basis for light environmental regulation, and the existing photosynthetic rate prediction models are limited by low modeling speed and prediction accuracy. Therefore, this paper analyses effects...
PhotoModPlus: A web server for photosynthetic protein prediction from genome neighborhood features.
PloS one
Mar 17, 2021
A new web server called PhotoModPlus is presented as a platform for predicting photosynthetic proteins via genome neighborhood networks (GNN) and genome neighborhood-based machine learning. GNN enables users to visualize the overview of the conserved...
The proteome landscape of the kingdoms of life.
Nature
Jun 17, 2020
Proteins carry out the vast majority of functions in all biological domains, but for technological reasons their large-scale investigation has lagged behind the study of genomes. Since the first essentially complete eukaryotic proteome was reported, ...
Photosynthetic protein classification using genome neighborhood-based machine learning feature.
Scientific reports
Apr 28, 2020
Identification of novel photosynthetic proteins is important for understanding and improving photosynthetic efficiency. Synergistically, genome neighborhood can provide additional useful information to identify photosynthetic proteins. We, therefore,...
Machine learning models for net photosynthetic rate prediction using poplar leaf phenotype data.
PloS one
Feb 11, 2020
BACKGROUND: As an essential component in reducing anthropogenic CO2 emissions to the atmosphere, tree planting is the key to keeping carbon dioxide emissions under control. In 1992, the United Nations agreed to take action at the Earth Summit to stab...
Artificial plant optimization algorithm to detect heart rate & presence of heart disease using machine learning.
Artificial intelligence in medicine
Nov 8, 2019
In today's world, cardiovascular diseases are prevalent becoming the leading cause of death; more than half of the cardiovascular diseases are due to Coronary Heart Disease (CHD) which generates the demand of predicting them timely so that people can...
Optimization and control of the light environment for greenhouse crop production.
Scientific reports
Jun 17, 2019
Optimization and control of the greenhouse light environment is key to increasing crop yield and quality. However, the light saturation point impacts the efficient use of light. Therefore, the dynamic acquisition of the light saturation point that is...
Using artificial neural network to investigate physiological changes and cerium oxide nanoparticles and cadmium uptake by Brassica napus plants.
Environmental pollution (Barking, Essex : 1987)
Dec 12, 2018
Heavy metals and emerging engineered nanoparticles (ENPs) are two current environmental concerns that have attracted considerable attention. Cerium oxide nanoparticles (CeONPs) are now used in a plethora of industrial products, while cadmium (Cd) is ...
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