Analytical methods : advancing methods and applications
Feb 20, 2025
Ensuring food safety necessitates rapid identification of pesticide residues on fruits. Herein, we developed a shape-adaptable flexible surface-enhanced Raman scattering (SERS) substrate, combined with a deep learning algorithm, to quickly detect and...
In agriculture, promptly and accurately identifying leaf diseases is crucial for sustainable crop production. To address this requirement, this research introduces a hybrid deep learning model that combines the visual geometric group version 19 (VGG1...
Machine learning and deep learning are extensively employed in genomic selection (GS) to expedite the identification of superior genotypes and accelerate breeding cycles. However, a significant challenge with current data-driven deep learning models ...
Deep learning applications in agriculture are advancing rapidly, leveraging data-driven learning models to enhance crop yield and nutrition. Tomato (), a vegetable crop, frequently suffers from pest damage and drought, leading to reduced yields and f...
Tomato cultivation is expanding rapidly, but the tomato sector faces significant challenges from various sources, including environmental (abiotic stress) and biological (biotic stress or disease) threats, which adversely impact the crop's growth, re...
Recent advancements in hyperspectral imaging (HSI) for early disease detection have shown promising results, yet there is a lack of validated high-resolution (spatial and spectral) HSI data representing the responses of plants at different stages of ...
This research introduces a Computer-Aided Diagnosis-system designed aimed at automated detections & classification of tomato leaf diseases, combining traditional handcrafted features with advanced deep learning techniques. The system's process encomp...
The image-based detection and classification of plant diseases has become increasingly important to the development of precision agriculture. We consider the case of tomato, a high-value crop supporting the livelihoods of many farmers around the worl...
An electrocatalytic platform based on a novel nanocomposite integrated with a grid search-optimized neural network (GSNN) was proposed for intelligent sensing of tryptophan. The cuprospinel-decorated chitosan-functionalized carbon nanofibers (CuFeO/C...
This study develops a hybrid machine learning (ML) algorithm integrated with IoT technology to improve the accuracy and efficiency of soil monitoring and tomato crop disease prediction in Anakapalle, a south Indian station. An IoT device collected on...
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