AIMC Topic: Least-Squares Analysis
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Production monitoring and quality characterization of black garlic using Vis-NIR hyperspectral imaging integrated with chemometrics strategies.
Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy
Sep 21, 2024
As a new deep-processing garlic product with notable health benefits, the accurate discrimination of processing stages and prediction of key physicochemical constituents in black garlic are vital for maintaining product quality. This study proposed a...
Fusion features of microfluorescence hyperspectral imaging for qualitative detection of pesticide residues in Hami melon.
Food research international (Ottawa, Ont.)
Sep 4, 2024
Pesticide residues are identified as a significant food safety issue in Hami melons, and their rapid and accurate detection is deemed critical for ensuring public health. In response to the cumbersome procedures with existing chemical detection metho...
Simultaneously predicting SPAD and water content in rice leaves using hyperspectral imaging with deep multi-task regression and transfer component analysis.
Journal of the science of food and agriculture
Sep 2, 2024
BACKGROUND: Water content and chlorophyll content are important indicators for monitoring rice growth status. Simultaneous detection of water content and chlorophyll content is of significance. Different varieties of rice show differences in phenotyp...
A nondestructive technique for the sex identification of third instar Cochliomyia macellaria larvae.
Journal of forensic sciences
Sep 2, 2024
Forensic entomology plays an important role in medicolegal investigations by using insects, primarily flies, to estimate the time of colonization. This estimation relies on the development of the flies found at the (death) scene and can be affected (...
Comparative study of machine-and deep-learning based classification algorithms for biomedical Raman spectroscopy (RS): case study of RS based pathogenic microbe identification.
Analytical sciences : the international journal of the Japan Society for Analytical Chemistry
Aug 29, 2024
One key aspect pushing the frontiers of biomedical RS is dedicated machine- or deep- learning (ML or DL) algorithms. Yet, systematic comparative study between ML and DL algorithms has not been conducted for biomedical RS, largely due to the limited a...
The development of machine learning approaches in two-dimensional NMR data interpretation for metabolomics applications.
Analytical biochemistry
Aug 24, 2024
Metabolomics has been widely applied in human diseases and environmental science to study the systematic changes of metabolites over diverse types of stimuli. NMR-based metabolomics has been widely used, but the peak overlap problems in the one-dimen...
Sugarcane disease recognition through visible and near-infrared spectroscopy using deep learning assisted continuous wavelet transform-based spectrogram.
Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy
Aug 22, 2024
Utilizing visible and near-infrared (Vis-NIR) spectroscopy in conjunction with chemometrics methods has been widespread for identifying plant diseases. However, a key obstacle involves the extraction of relevant spectral characteristics. This study a...
Real-time chlorophyll-a forecasting using machine learning framework with dimension reduction and hyperspectral data.
Environmental research
Aug 22, 2024
Since water is an essential resource in various fields, it requires constant monitoring. Chlorophyll-a concentration is a crucial indicator of water quality and can be used to monitor water quality. In this study, we developed methods to forecast chl...
Rapid estimation of soil water content based on hyperspectral reflectance combined with continuous wavelet transform, feature extraction, and extreme learning machine.
PeerJ
Aug 22, 2024
BACKGROUND: Soil water content is one of the critical indicators in agricultural systems. Visible/near-infrared hyperspectral remote sensing is an effective method for soil water estimation. However, noise removal from massive spectral datasets and e...
An initial exploration of machine learning for establishing associations between genetic markers and THC levels in Cannabis sativa samples.
Forensic science international. Genetics
Aug 9, 2024
Cannabis sativa, a globally commercialized plant used for medicinal, food, fiber production, and recreation, necessitates effective identification to distinguish legal and illegal varieties in forensic contexts. This research utilizes multivariate st...
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