Results 91 to 100 of about 12,027 (208)

Multi-Way Fluorescence Technique Combined with Four-Way Calibration for the Determination of Thiabendazole and Carbaryl in Apple

Chemosensors
In this study, an excitation–emission–pH multi-way fluorescence technique coupled with a third-order calibration method based on an alternating quadrilinear decomposition (AQLD) algorithm was proposed for the simultaneous determination of thiabendazole ...
Haiyan Chang, Hailong Wu, Tong Wang, Xiaozhi Wang, Ruqin Yu   +4 more
doaj   +1 more source

A Spectral Matching Algorithm Based on the Wasserstein Metric

Journal of Chemometrics, Volume 40, Issue 6, June 2026.
ABSTRACT Through visual inspection, scientists can easily judge the similarity of pairs of spectra from different sources, whether they are experimental measurements, spectra libraries, or spectra calculations. Spectral similarity is recognized when the peak patterns appear similar, even if the peak positions are shifted or the peak amplitudes are ...
Klaus Neymeyr, Baoxin Zhang, Christoph Kubis, Mattis Brinker, Lukas Prestin, Tomass Andersons, Mathias Sawall, Jan Hellwig   +7 more
wiley   +1 more source

Protocol for survival assay of Caenorhabditis elegans to Pseudomonas aeruginosa PA14 infection

STAR Protocols
Summary: The nematode Caenorhabditis elegans is a powerful model organism for studying the molecular and cellular mechanisms of innate immunity governed by the intestine. Here, we present a protocol to perform C.
Junqiang Liu, Ming Lei, Mengqi Wang, Shu Chen, Haijun Tu   +4 more
doaj   +1 more source

kNNPC (k‐Nearest Neighbor Algorithm Per‐Class): Classification Method Predicting Extrapolation Regions With Reasonable Probability

Journal of Chemometrics, Volume 40, Issue 6, June 2026.
ABSTRACT In classification tasks, predicted class probabilities are often overconfident for samples outside the training distribution, which can lead to unsafe decision‐making. kNNPC, a k‐nearest neighbor algorithm per class, is proposed to mitigate such overconfidence under extrapolation or distribution shift.
Hiromasa Kaneko
wiley   +1 more source

Robust Constrained Partial Least Squares: A Robust Integrated Algorithm for Multivariate Regression in the Presence of Outliers, Interfering Analytes, and Structured External Influences

Journal of Chemometrics, Volume 40, Issue 6, June 2026.
ABSTRACT Partial least squares (PLS) regression is widely used for multivariate calibration in high‐dimensional and collinear settings. However, classical PLS relies on least squares optimization and is therefore sensitive to anomalous observations, leverage points, and structured spectral interferences.
Puneet Mishra
wiley   +1 more source

Performance of NIR‐Based Regression Models for Hyperforin Quantification in St. John's Wort Under Temporal Validation

Journal of Chemometrics, Volume 40, Issue 6, June 2026.
ABSTRACT This study investigates the performance of near‐infrared (NIR)‐based partial least squares (PLS) regression models for quantifying hyperforin in Hypericum perforatum L., with particular emphasis on temporal validation and robustness analysis. Dried and ground Hypericum samples were analyzed using three different NIR spectrometers: one benchtop
Nele‐Elin Schröter, Knut Baumann
wiley   +1 more source

From Design of Experiments to Analysis of Variance of Multivariate Data: A Tutorial Review on ANOVA Simultaneous Component Analysis

Journal of Chemometrics, Volume 40, Issue 6, June 2026.
ABSTRACT ANOVA simultaneous component analysis (ASCA) is the current state‐of‐the‐art chemometric tool for analyzing and interpreting high‐dimensional experimental data from a design of experiments (DoE). Being a multivariate extension of the ANOVA, ASCA makes a perfect tandem with DoE.
José Camacho, Jokin Ezenarro, Daniel Schorn‐García, Johan A. Westerhuis   +3 more
wiley   +1 more source

Conceptual Differences Between Hyperspectral Unmixing, PCA, and Clustering: A Practical Demonstration Using Single‐Cell Raman Imaging

Journal of Chemometrics, Volume 40, Issue 6, June 2026.
ABSTRACT Hyperspectral unmixing is a well‐established approach for analyzing spectroscopic images by recovering chemically interpretable component spectra and their spatial distributions. Despite its distinct analytical objective, unmixing is frequently discussed alongside or directly compared with more familiar multivariate techniques such as ...
Rustam R. Guliev, Ute Neugebauer
wiley   +1 more source

Benchtop NMR Spectroscopy of Pyrolysis Oils From Mixed Plastic Waste: Parameter Optimization for Oil Characterization and Detection of Heteroatom‐Containing Compounds

Chemistry–Methods, Volume 6, Issue 6, June 2026.
In this article, benchtop‐NMR spectroscopy was evaluated as an analytical method for the characterization of plastic waste derived pyrolysis oils. The signal‐to‐noise ratio was enhanced via measurement parameter optimization and optimization of postacquisition parameters.
Anika Goecke, Jonas Vogt, Salar Tavakkol, Shahram Mihan, Volker Fraaije, Ricardo Kurz, Diana Dötsch, Dieter Stapf, Manfred Wilhelm   +8 more
wiley   +1 more source

Artificial Intelligence in the Food Industry: Transforming Safety, Efficiency, and Sustainability From Farm to Fork

eFood, Volume 7, Issue 3, June 2026.
This review synthesizes AI advancements in food systems, leveraging machine learning, computer vision, robotics, and IoT for 96%–100% accurate quality inspection, 30% reduced downtime, and enhanced traceability from farm to fork. It highlights transformative potential in sustainability and SDGs while addressing data, ethical, and scalability challenges
Muhammad Waqar, Mariyam Shahid, Manat Chaijan, Worawan Panpipat, Djilali Benabdelmoumene, Ahmed Mediani, Abdifetah Ibrahim Omar, Sabrin R. M. Ibrahim, Qudrat Ullah, Temesgen Anjulo Ageru   +9 more
wiley   +1 more source