Current trends, limitations and future research in the fungi?

Fungal Diversity, Journal Year: 2024, Volume and Issue: 125(1), P. 1 - 71

Published: March 20, 2024

Abstract The field of mycology has grown from an underappreciated subset botany, to a valuable, modern scientific discipline. As this study grown, there have been significant contributions science, technology, and industry, highlighting the value fungi in era. This paper looks at current research, along with existing limitations, suggests future areas where scientists can focus their efforts, mycology. We show how become important emerging diseases medical discuss trends potential drug novel compound discovery. explore phylogenomics, its potential, outcomes address question phylogenomics be applied fungal ecology. In addition, functional genomics studies are discussed importance unravelling intricate mechanisms underlying behaviour, interactions, adaptations, paving way for comprehensive understanding biology. look research building materials, they used as carbon sinks, biocircular economies. numbers always great interest often written about estimates varied greatly. Thus, we needs order obtain more reliable estimates. aspects machine learning (AI) it mycological research. Plant pathogens affecting food production systems on global scale, such, needed area, particularly disease detection. latest data High Throughput Sequencing if still gaining new knowledge same rate before. A review nanotechnology is provided addressed. Arbuscular Mycorrhizal Fungi addressed acknowledged. Fungal databases becoming important, therefore provide major databases. Edible medicinal huge medicines, especially Asia prospects discussed. Lifestyle changes (e.g., endophytes, pathogens, and/or saprobes) also extremely trend special issue Diversity.

Language: Английский

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Artificial Intelligence: A Promising Tool for Application in Phytopathology

Horticulturae, Journal Year: 2024, Volume and Issue: 10(3), P. 197 - 197

Published: Feb. 20, 2024

Artificial intelligence (AI) is revolutionizing approaches in plant disease management and phytopathological research. This review analyzes current applications future directions of AI addressing evolving agricultural challenges. Plant diseases annually cause 10–16% yield losses major crops, prompting urgent innovations. shows an aptitude for automated detection diagnosis utilizing image recognition techniques, with reported accuracies exceeding 95% surpassing human visual assessment. Forecasting models integrating weather, soil, crop data enable preemptive interventions by predicting spatial-temporal outbreak risks weeks advance at 81–95% precision, minimizing pesticide usage. Precision agriculture powered optimizes data-driven, tailored protection strategies boosting resilience. Real-time monitoring leveraging discerns pre-symptomatic anomalies from environmental early alerts. These highlight AI’s proficiency illuminating opaque patterns within increasingly complex data. Machine learning techniques overcome cognitive constraints discovering multivariate correlations unnoticed before. poised to transform in-field decision-making around prevention precision management. Overall, constitutes a strategic innovation pathway strengthen ecological health amidst climate change, globalization, intensification pressures. With prudent ethical implementation, AI-enabled tools promise next-generation phytopathology, enhancing resilience worldwide.

Language: Английский

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Impact of Metabolites from Foodborne Pathogens on Cancer

Foods, Journal Year: 2024, Volume and Issue: 13(23), P. 3886 - 3886

Published: Dec. 1, 2024

Foodborne pathogens are microorganisms that cause illness through contamination, presenting significant risks to public health and food safety. This review explores the metabolites produced by these pathogens, including toxins secondary metabolites, their implications for human health, particularly concerning cancer risk. We examine various such as Salmonella sp., Campylobacter Escherichia coli, Listeria monocytogenes, detailing specific of concern carcinogenic mechanisms. study discusses analytical techniques detecting chromatography, spectrometry, immunoassays, along with challenges associated detection. covers effective control strategies, processing techniques, sanitation practices, regulatory measures, emerging technologies in pathogen control. manuscript considers broader highlighting importance robust policies, awareness, education. identifies research gaps innovative approaches, recommending advancements detection methods, preventive policy improvements better manage foodborne metabolites.

Language: Английский

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Portable solutions for plant pathogen diagnostics: development, usage, and future potential

Frontiers in Microbiology, Journal Year: 2025, Volume and Issue: 16

Published: Jan. 31, 2025

The increasing prevalence of plant pathogens presents a critical challenge to global food security and agricultural sustainability. While accurate, traditional diagnostic methods are often time-consuming, resource-intensive, unsuitable for real-time field applications. emergence portable tools represents paradigm shift in disease management, offering rapid, on-site detection with high accuracy minimal technical expertise. This review explores technologies' development, deployment, future potential, including handheld analyzers, smartphone-integrated systems, microfluidics, lab-on-a-chip platforms. We examine the core technologies underlying these devices, such as biosensors, nucleic acid amplification techniques, immunoassays, highlighting their applicability detect bacterial, viral, fungal diverse settings. Furthermore, integration devices digital technologies, Internet Things (IoT), artificial intelligence (AI), machine learning (ML), is transforming surveillance management. diagnostics have clear advantages speed, cost-effectiveness, user accessibility, challenges related sensitivity, durability, regulatory standards remain. Innovations nanotechnology, multiplex platforms, personalized agriculture promise further enhance efficacy diagnostics. By providing comprehensive overview current exploring directions, this underscores role advancing precision mitigating impact on production.

Language: Английский

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Relevance of Advanced Plant Disease Detection Techniques in Disease and Pest Management for Ensuring Food Security and Their Implication: A Review

American Journal of Plant Sciences, Journal Year: 2023, Volume and Issue: 14(11), P. 1260 - 1295

Published: Jan. 1, 2023

Plant diseases and pests present significant challenges to global food security, leading substantial losses in agricultural productivity threatening environmental sustainability. As the world's population grows, ensuring availability becomes increasingly urgent. This review explores significance of advanced plant disease detection techniques pest management for enhancing security. Traditional methods often rely on visual inspection are time-consuming subjective. leads delayed interventions ineffective control measures. However, recent advancements remote sensing, imaging technologies, molecular diagnostics offer powerful tools early precise detection. Big data analytics machine learning play pivotal roles analyzing vast complex datasets, thus accurately identifying predicting occurrence severity. We explore how prompt employing enable more efficient concurrently minimize impact conventional practices. Furthermore, we analyze make future recommendations improve precision sensitivity current techniques. propose incorporating eco-evolutionary theories into research enhance understanding pathogen spread climates mitigate risk outbreaks. highlight need a science-policy interface that works closely with scientists, policymakers, relevant intergovernmental organizations ensure coordination collaboration among them, ultimately developing effective monitoring strategies needed securing sustainable production well-being.

Language: Английский

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Insights into the effects of elevated atmospheric carbon dioxide on plant-virus interactions: A literature review

Environmental and Experimental Botany, Journal Year: 2024, Volume and Issue: 221, P. 105737 - 105737

Published: March 15, 2024

Understanding and anticipating the impacts of climate change on plant-pathogen interactions are a major challenge for agriculture 21st century. Prediction models forecast an increase in atmospheric carbon dioxide (CO2) levels by 2100 that could reach 1045 ppm. Plant physiology is directly affected CO2 as plants living organisms consume through photosynthesis to produce organic matter. Since early days agriculture, plant diseases can alter not only quality productions but also be responsible important yield losses. viruses obligate, acellular pathogens cause serious epidemics agricultural crops with annual losses more than $ 30 billion. As elevated concentration (eCO2) modulates primary secondary metabolisms obligate pathogens, it likely eCO2 modulate molecular defenses viruses. In context, present review focuses effect physiological responses virus infections. First, we will compare different experimental methodologies used study impact enrichment plant-virus discuss designs applied experiments. We virus-infection parameters infected describe combined abiotic stresses, including temperature, interactions.

Language: Английский

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Artificial Intelligence: A Promising Tool for Application in Phytopathology

Published: Jan. 26, 2024

Artificial intelligence (AI) is revolutionizing approaches in plant disease management and phy-topathological research. This review analyzes current applications future directions of AI addressing evolving agricultural challenges. Plant diseases annually cause 10-16% yield losses major crops, prompting urgent innovations. shows aptitude for auto-mated detection diagnosis utilizing image recognition techniques, with reported accuracies exceeding 95% surpassing human visual assessment. Forecasting models inte-grating weather, soil, crop data enable preemptive interventions by predicting spa-tial-temporal outbreak risks weeks advance at 81-95% precision, minimizing pesticide usage. Precision agriculture powered optimizes data-driven, tailored protection strategies boosting resilience. Real-time monitoring leveraging discerns pre-symptomatic anomalies from environmental early alerts. These highlight AI's proficiency il-luminating opaque patterns within increasingly complex data. Machine learning techniques overcome cognitive constraints discovering multivariate correla-tions unnoticed before. poised to transform in-field decision making around pre-vention precision management. Overall, constitutes a strategic innovation pathway strengthen ecological health amidst climate change, globalization, agri-cultural intensification pressures. With prudent ethical implementation, AI-enabled tools promise next-generation phytopathology, enhancing resilience worldwide.Artificial Intelligence, Phytopathology, Emerging Disease, Climate Change, Control diseases.

Language: Английский

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Exploring metal and metal-oxide nanoparticles for nanosensing and biotic stress management in plant systems

Current Research in Biotechnology, Journal Year: 2024, Volume and Issue: 7, P. 100219 - 100219

Published: Jan. 1, 2024

Language: Английский

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Recent advances of microneedles biosensors for plants

Analytical and Bioanalytical Chemistry, Journal Year: 2023, Volume and Issue: 416(1), P. 55 - 69

Published: Oct. 23, 2023

Language: Английский

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Towards Pathogen-Free Coconut Germplasm Exchange

Plants, Journal Year: 2024, Volume and Issue: 13(13), P. 1809 - 1809

Published: June 30, 2024

Coconut (

Language: Английский

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