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Plant Leaves

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Transcripts and genomic intervals associated with variation in metabolite abundance in maize leaves under field conditions.

BMC genomics
Plants exhibit extensive environment-dependent intraspecific metabolic variation, which likely plays a role in determining variation in whole plant phenotypes. However, much of the work seeking to use natural variation to link genes and transcript's ...

In vitro antimicrobial and anticancer potentials of green synthesized luminescent carbon quantum dots derived from artichoke leaves.

Scientific reports
Naturally derived carbon quantum dots (CQDs) are novel carbon-based nanomaterials with excellent traits. It is highly demanded to develop CQDs from biowaste that have excellent photostability, a simple synthesis approach, and an appealing output so t...

Mitochondrial dysfunction and cell death induced by Toona sinensis leaf extracts through MEK/ERK signaling in glioblastoma cells.

PloS one
Toona sinensis, a kind of phytochemicals in traditional Chinese medicine widely used in South-East Asia, has been recognized for its anticancer properties, particularly against various types of cancer. We aimed to evaluate the effectiveness of T. sin...

Investigating endophytic fungi of Calotropis procera for novel bioactive compounds: molecular docking and bioactivity insights.

Microbial cell factories
BACKGROUND: The rising danger of antibiotic resistance and the increasing burden of cancer worldwide have highlighted the necessity for a constant supply of new antimicrobial drugs and anticancer therapies. Endophytic fungi, recognized as a rich supp...

Identification of medicinal plant parts using depth-wise separable convolutional neural network.

PloS one
Identifying relevant plant parts is one of the most significant tasks in the pharmaceutical industry. Correct identification minimizes the risk of mis-identification, which might have unfavorable effects, and it ensures that plants are used medicinal...

Optimized convolutional neural networks for real-time detection and severity assessment of early blight in tomato (Solanum lycopersicum L.).

Fungal genetics and biology : FG & B
Early blight, caused by Alternaria alternata, poses a critical challenge to tomato (Solanum lycopersicum L.) production, causing significant yield losses worldwide. Despite advancements in plant disease detection, existing methods often lack the robu...

AI-IoT based smart agriculture pivot for plant diseases detection and treatment.

Scientific reports
There are some key problems faced in modern agriculture that IoT-based smart farming. These problems such shortage of water, plant diseases, and pest attacks. Thus, artificial intelligence (AI) technology cooperates with the Internet of Things (IoT) ...

A novel hybrid fruit fly and simulated annealing optimized faster R-CNN for detection and classification of tomato plant leaf diseases.

Scientific reports
Modern agriculture increasingly relies on technologies that enhance farmers' efficiency and economic growth. One challenge is the accurate identification of disease-affected plants, whose characteristics like structure, size, texture, and color can v...

Segmentation-based lightweight multi-class classification model for crop disease detection, classification, and severity assessment using DCNN.

PloS one
Leaf diseases in Zea mays crops have a significant impact on both the calibre and volume of maize yield, eventually impacting the market. Prior detection of the intensity of an infection would enable the efficient allocation of treatment resources an...

Potato plant disease detection: leveraging hybrid deep learning models.

BMC plant biology
Agriculture, a crucial sector for global economic development and sustainable food production, faces significant challenges in detecting and managing crop diseases. These diseases can greatly impact yield and productivity, making early and accurate d...