AIMC Topic: Plant Leaves

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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...

Establishing identifiable characteristic fingerprints of mulberry leaves: Integrating chemical composition and bioactivity through machine learning.

Journal of ethnopharmacology
ETHNOPHARMACOLOGICAL RELEVANCE: Mulberry leaves (Morus alba L.) are used in traditional Chinese medicine to clear the lungs and dispel wind-heat. Despite their common use, chemical reference substance rely solely on rutin, which may not reflect their...

Improvement method for tea leaf moisture content prediction using VIS-NIR spectrum based on transfer learning.

Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy
Moisture significantly affects tea plants' growth and quality. Traditional methods of leaf moisture detection are usually destructive to samples, slow and labour-intensive. In this study, visible-near infrared (VIS-NIR) spectroscopy was used to detec...

In situ foliar augmentation of multiple species for optical phenotyping and bioengineering using soft robotics.

Science robotics
Precision agriculture aims to increase crop yield while reducing the use of harmful chemicals, such as pesticides and excess fertilizer, using minimal, tailored interventions. However, these strategies are limited by factors such as sensor quality, w...

Mulberry leaf disease detection by CNN-ViT with XAI integration.

PloS one
Mulberry leaf disease detection is vital for maintaining the health and productivity of mulberry crops. In this paper, a novel approach was proposed by integrating explainable artificial intelligence (XAI) techniques with a convolutional neural netwo...

Assessing the performance of domain-specific models for plant leaf disease classification: a comprehensive benchmark of transfer-learning on open datasets.

Scientific reports
Agriculture and its yields are indispensable to human life all over the planet. It is an essential part of many countries' economies and without it the world's population can not be fed. As such, guaranteeing harvest with minimal loss is a primary ob...

Enhancing the dataset of CycleGAN-M and YOLOv8s-KEF for identifying apple leaf diseases.

PloS one
Accurate diagnosis of apple diseases is vital for tree health, yield improvement, and minimizing economic losses. This study introduces a deep learning-based model to tackle issues like limited datasets, small sample sizes, and low recognition accura...

Ecofriendly Extraction of Polyphenols from Leaves Coupled with Response Surface Methodology and Artificial Neural Network-Genetic Algorithm.

Molecules (Basel, Switzerland)
This study aimed to optimize a novel deep eutectic solvents (DESs)-assisted extraction process for polyphenols in the leaves of (AGPL) with response surface methodology (RSM) and a genetic algorithm-artificial neural network (GA-ANN). Under the infl...

Remote sensing-based detection of brown spot needle blight: a comprehensive review, and future directions.

PeerJ
Pine forests are increasingly threatened by needle diseases, including Brown Spot Needle Blight (BSNB), caused by . BSNB leads to needle loss, reduced growth, significant tree mortality, and disruptions in global timber production. Due to its severit...

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...