AIMC Topic: Photosynthesis

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Photosynthetic performance index (PIabs) and malondialdehyde (MDA) content determine rice biomass under combined salt stress and prohexadione-calcium treatment.

BMC plant biology Jul 2, 2025
BACKGROUND: Plant growth regulators (PGRs) have proven effective in alleviating salt stress damage in crops, yet the predictive hierarchy of physiological traits governing biomass under combined salt-PGR regimes remains unclear. In this study, we app...
Malondialdehyde Oryza Biomass Plant Growth Regulators Photosynthesis Salt Stress Hexanes Calcium Compounds
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Estimating Tea Plant Physiological Parameters Using Unmanned Aerial Vehicle Imagery and Machine Learning Algorithms.

Sensors (Basel, Switzerland) Mar 21, 2025
Tea ( L.) holds agricultural economic value and forestry carbon sequestration potential, with Taiwan's annual tea production exceeding TWD 7 billion. However, climate change-induced stressors threaten tea plant growth, photosynthesis, yield, and qual...
Machine Learning Plant Leaves Camellia sinensis Tea Algorithms Taiwan Unmanned Aerial Devices Remote Sensing Technology Photosynthesis
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Predicting the diversity of photosynthetic light-harvesting using thermodynamics and machine learning.

PLoS computational biology Mar 11, 2025
Oxygenic photosynthesis is responsible for nearly all biomass production on Earth, and may have been a prerequisite for establishing a complex biosphere rich in multicellular life. Life on Earth has evolved to perform photosynthesis in a wide range o...
Light-Harvesting Protein Complexes Algorithms Computational Biology Thermodynamics Photosynthesis Models, Biological Machine Learning
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Optimizing chickpea yield prediction under wilt disease through synergistic integration of biophysical and image parameters using machine learning models.

Scientific reports Feb 5, 2025
Crop health assessment and early yield predictions are highly crucial under biotic stress conditions for crop management and market planning by farmers and policy planners. The objective of this study was, therefore, to assess the impact of different...
Cicer Plant Diseases Photosynthesis Machine Learning Genotype Plant Leaves Crops, Agricultural
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Increased chloroplast occupancy in bundle sheath cells of rice hap3H mutants revealed by Chloro-Count: a new deep learning-based tool.

The New phytologist Dec 12, 2024
There is an increasing demand to boost photosynthesis in rice to increase yield potential. Chloroplasts are the site of photosynthesis, and increasing their number and size is a potential route to elevate photosynthetic activity. Notably, bundle shea...
Deep Learning Plant Leaves Photosynthesis Plant Proteins Mutation Chloroplasts Oryza
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Predicting photosynthetic bacteria-derived protein synthesis from wastewater using machine learning and causal inference.

Bioresource technology Oct 15, 2024
Causal inference-assisted machine learning was used to predict photosynthetic bacterial (PSB) protein production capacity and identify key factors. The extreme gradient boosting algorithm effectively predicted protein content, while the gradient boos...
Protein Biosynthesis Photosynthesis Bacterial Proteins Biological Oxygen Demand Analysis Machine Learning Algorithms Biomass Wastewater
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Machine learning reveals the transcriptional regulatory network and circadian dynamics of PCC 7942.

Proceedings of the National Academy of Sciences of the United States of America Sep 13, 2024
is an important cyanobacterium that serves as a versatile and robust model for studying circadian biology and photosynthetic metabolism. Its transcriptional regulatory network (TRN) is of fundamental interest, as it orchestrates the cell's adaptatio...
Gene Expression Regulation, Bacterial Machine Learning Photosynthesis Bacterial Proteins Transcriptome Synechococcus Circadian Rhythm Gene Regulatory Networks
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New Strategies for constructing and analyzing semiconductor photosynthetic biohybrid systems based on ensemble Machine learning Models: Visualizing complex mechanisms and yield prediction.

Bioresource technology Aug 31, 2024
Photosynthetic biohybrid systems (PBSs) composed of semiconductor-microbial hybrids provide a novel approach for converting light into chemical energy. However, comprehending the intricate interactions between materials and microbes that lead to PBSs...
Machine Learning Photosynthesis Semiconductors
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Plastic particles and fluorescent brightener co-modify Chlorella pyrenoidosa photosynthesis and a machine learning approach predict algae growth.

Journal of hazardous materials Aug 2, 2024
Global release of plastics exerts various impacts on the ecological cycle, particularly on primary photosynthesis, while the impacts of plastic additives are unknown. As a carrier of fluorescent brightener, plastic particles co-modify Chlorella pyren...
Water Pollutants, Chemical Plastics Machine Learning Photosynthesis Fluorescent Dyes Chlorella Polystyrenes
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Understanding the phytotoxic effects of organic contaminants on rice through predictive modeling with molecular descriptors: A data-driven analysis.

Journal of hazardous materials Jun 17, 2024
The widespread introduction of organic compounds into environments poses significant risks to ecosystems. Assessing the adverse effects of organic contaminants on crops is crucial for ensuring food safety. However, laboratory research is often time-c...
Organic Chemicals Machine Learning Oryza Soil Pollutants Oxidative Stress Photosynthesis
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