AIMC Topic: Stress, Physiological

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Predicting plant stress using SAM-L: novel self-adaptive-meta learner with XAI based on soil moisture and chlorophyll analysis.

Scientific reports
Recent advancements in precision agriculture have introduced innovative approaches to addressing plant stress, a critical factor influencing crop productivity and agricultural sustainability. Accurate, real-time prediction of plant stress has become ...

Perspectives on morphology, physiology, genetic polymorphism and machine learning in cucumber grafting under zinc toxicity.

BMC plant biology
BACKGROUND: Heavy metal contamination in agricultural soils disrupts plant growth and metabolism. Although zinc (Zn) is a necessary element, concentrations above 50 ppm can be toxic to plants. Grafting has emerged as a potential strategy to mitigate ...

Harnessing multi-omics and genome-editing technologies for climate-resilient agriculture: bridging AI-driven insights with sustainable crop improvement.

Plant molecular biology
Environmental challenges such as drought, salinity, heavy metal contamination, and nutrient deficiencies threaten global agricultural productivity and food security. These stressors drastically reduce crop yields, necessitating innovative solutions. ...

Biomarker genes for model-based prediction of drought-stress perception levels in rice.

BMC plant biology
BACKGROUND: Drought is a global challenge that severely restricts crop yields and threatens food security. Plants respond to drought stress by modulating gene expression before visible phenotypic changes occur. However, most studies of drought resist...

Integrative machine learning and RT-qPCR analysis identify key stress-responsive genes in Thermus thermophilus HB8.

Genetica
Bacteria are constantly exposed to diverse environmental stresses, necessitating complex adaptive mechanisms for survival. Thermus thermophilus, a thermophilic extremophile, serves as an excellent model for investigating these responses due to its re...

An effective multi-modality analysis for stress classification: A signal-to-image conversion using local pattern techniques.

Computers in biology and medicine
Stress is an intensified reaction that occurs when humans experience challenges(stressors) due to complex and nonlinear responses. The study proposes a pattern-driven framework that combines signal and image-based modalities, incorporating Local Bina...

An explainable vision transformer with transfer learning based efficient drought stress identification.

Plant molecular biology
Early detection of drought stress is critical for taking timely measures for reducing crop loss before the drought impact becomes irreversible. The subtle phenotypical and physiological changes in response to drought stress are captured by non-invasi...

A machine-learning-powered spectral-dominant multimodal soft wearable system for long-term and early-stage diagnosis of plant stresses.

Science advances
Addressing the global malnutrition crisis requires precise and timely diagnostics of plant stresses to enhance the quality and yield of nutrient-rich crops, such as tomatoes. Soft wearable sensors offer a promising approach by continuously monitoring...