Results 71 to 80 of about 475,966 (276)

Comment on 'Evolutionary transitions between beneficial and phytopathogenic Rhodococcus challenge disease management' [PDF]

open access: yes, 2018
I would like to report significant issues of concern regarding this paper (Savory et al., 2017)
Vereecke, Danny
core   +2 more sources

Phosphatidylinositol 4‐kinase as a target of pathogens—friend or foe?

open access: yesFEBS Letters, EarlyView.
This graphical summary illustrates the roles of phosphatidylinositol 4‐kinases (PI4Ks). PI4Ks regulate key cellular processes and can be hijacked by pathogens, such as viruses, bacteria and parasites, to support their intracellular replication. Their dual role as essential host enzymes and pathogen cofactors makes them promising drug targets.
Ana C. Mendes   +3 more
wiley   +1 more source

Improving YOLO-Based Plant Disease Detection Using αSILU: A Novel Activation Function for Smart Agriculture

open access: yesAgriEngineering
The precise identification of plant diseases is essential for improving agricultural productivity and reducing reliance on human expertise. Deep learning frameworks, belonging to the YOLO series, have demonstrated significant potential in the real-time ...
Duyen Thi Nguyen   +3 more
doaj   +1 more source

The role and implications of mammalian cellular circadian entrainment

open access: yesFEBS Letters, EarlyView.
At their most fundamental level, mammalian circadian rhythms occur inside every individual cell. To tell the correct time, cells must align (or ‘entrain’) their circadian rhythm to the external environment. In this review, we highlight how cells entrain to the major circadian cues of light, feeding and temperature, and the implications this has for our
Priya Crosby
wiley   +1 more source

Exploring the advances of biosensing technology for the detection of plant pathogens in sustainable agriculture

open access: yesFrontiers in Bioengineering and Biotechnology
Plant pathogens, including fungi, bacteria, viruses, and nematodes, remain major constraints to global agricultural productivity, threatening food security and ecosystem sustainability. Conventional diagnostic methods such as culture-based assays, ELISA,
Sneha Shikha   +9 more
doaj   +1 more source

Application of Copper Fungicide and Row Covers to Control Phytophthora Seedling Blight Disease on Cocoa [PDF]

open access: yes, 2016
Phytophthora seedling blight disease is one of the important diseases in cocoa. The disease is caused by the fungus of Phytophthora palmivora belongs to class Oomycetes. The aim of this research was to determine the effectiveness of the use of row covers
Aini, F. N. (Febrilia)   +2 more
core   +3 more sources

Interplay between circadian and other transcription factors—Implications for cycling transcriptome reprogramming

open access: yesFEBS Letters, EarlyView.
This perspective highlights emerging insights into how the circadian transcription factor CLOCK:BMAL1 regulates chromatin architecture, cooperates with other transcription factors, and coordinates enhancer dynamics. We propose an updated framework for how circadian transcription factors operate within dynamic and multifactorial chromatin landscapes ...
Xinyu Y. Nie, Jerome S. Menet
wiley   +1 more source

Distributed Deep Learning in IoT Sensor Network for the Diagnosis of Plant Diseases

open access: yesSensors
The early detection of plant diseases is critical to improving agricultural productivity and ensuring food security. However, conventional centralized deep learning approaches are often unsuitable for large-scale agricultural deployments, as they rely on
Athanasios Papanikolaou   +4 more
doaj   +1 more source

CentralMaizeGuard: Enhanced deep learning model for maize disease detection and management [PDF]

open access: yesArchives of Control Sciences
The detection of maize plant leaf diseases is a critical aspect of agricultural management, necessitating accurate and efficient methodologies. The field of maize plant leaf disease detection encounters several challenges that hinder the development of ...
Fathe Jeribi   +4 more
doaj   +1 more source

Automatic plant pest detection and recognition using k-means clustering algorithm and correspondence filters [PDF]

open access: yes, 2013
Plant pest recognition and detection is vital for food security, quality of life and a stable agricultural economy. This research demonstrates the combination of the k-means clustering algorithm and the correspondence filter to achieve pest detection and
Birch, Philip   +5 more
core   +1 more source

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