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Spectroscopy, Near-Infrared

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Study on the identification of resistance of rice blast based on near infrared spectroscopy.

Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy
Rice Blast is the most devastating rice disease which poses a serious threat to the safe production of rice. The most effective way to prevent rice blast is to cultivate the rice varieties that have resistance to the disease, however, traditional res...

Explainable artificial intelligence based analysis for interpreting infant fNIRS data in developmental cognitive neuroscience.

Communications biology
In the last decades, non-invasive and portable neuroimaging techniques, such as functional near infrared spectroscopy (fNIRS), have allowed researchers to study the mechanisms underlying the functional cognitive development of the human brain, thus f...

Deep learning multimodal fNIRS and EEG signals for bimanual grip force decoding.

Journal of neural engineering
Non-invasive brain-machine interfaces (BMIs) offer an alternative, safe and accessible way to interact with the environment. To enable meaningful and stable physical interactions, BMIs need to decode forces. Although previously addressed in the unima...

Early pregnancy diagnosis of rabbits: A non-invasive approach using Vis-NIR spatially resolved spectroscopy.

Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy
Pregnancy diagnosis is essential for rabbit's reproductive management. The early identification of non-pregnant rabbits allows for earlier re-insemination, increases the service rate, and reduces the laboring interval in commercial operations. The ob...

Predicting moisture content during maize nixtamalization using machine learning with NIR spectroscopy.

TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik
Moisture content during nixtamalization can be accurately predicted from NIR spectroscopy when coupled with a support vector machine (SVM) model, is strongly modulated by the environment, and has a complex genetic architecture. Lack of high-throughpu...

Determining soil particle-size distribution from infrared spectra using machine learning predictions: Methodology and modeling.

PloS one
Accuracy of infrared (IR) models to measure soil particle-size distribution (PSD) depends on soil preparation, methodology (sedimentation, laser), settling times and relevant soil features. Compositional soil data may require log ratio (ilr) transfor...

Machine learning applied to near-infrared spectra for clinical pleural effusion classification.

Scientific reports
Lung cancer patients with malignant pleural effusions (MPE) have a particular poor prognosis. It is crucial to distinguish MPE from benign pleural effusion (BPE). The present study aims to develop a rapid, convenient and economical diagnostic method ...

Fast discrimination and quantification analysis of Curcumae Radix from four botanical origins using NIR spectroscopy coupled with chemometrics tools.

Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy
Curcumae Radix (Yujin) is a multi-origin herbal medicine with excellent clinical efficacy. For fast discrimination and quantification analysis of Yujin from four botanical origins (Guiyujin, Huangyujin, Lvyujin and Wenyujin), near infrared (NIR) spec...

Classification of Greek Olive Oils from Different Regions by Machine Learning-Aided Laser-Induced Breakdown Spectroscopy and Absorption Spectroscopy.

Molecules (Basel, Switzerland)
In the present work, the emission and the absorption spectra of numerous Greek olive oil samples and mixtures of them, obtained by two spectroscopic techniques, namely Laser-Induced Breakdown Spectroscopy (LIBS) and Absorption Spectroscopy, and aided...

Prediction of specialty coffee flavors based on near-infrared spectra using machine- and deep-learning methods.

Journal of the science of food and agriculture
BACKGROUND: Specialty coffee fascinates people with its bountiful flavors. Currently, flavor descriptions of specialty coffee beans are only offered by certified coffee cuppers. However, such professionals are rare, and the market demand is tremendou...