ArticleFoods (Basel, Switzerland)2026
Rapid and Non-Destructive Detection of Moisture Content in Dried Areca Nuts Based on Near-Infrared Spectroscopy Combined with Machine Learning.
Article in Foods (Basel, Switzerland), 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors.
Funding
Abstract
Moisture content is a key quality attribute in dried areca nuts, affecting subsequent processing performance and storage stability, yet routine measurement by oven-drying is time-consuming and destructive. This study developed a rapid and non-destructive method for determining moisture content in dried areca nuts by integrating near-infrared spectroscopy with chemometric and machine learning-assisted methodologies. Various spectral preprocessing methods, feature wavelength selection algorithms, and modeling approaches were compared. The results indicated that Multiplicative Scatter Correction (MSC) most effectively eliminated physical scattering interference. The Partial Least Squares Regression (PLSR) model established using full-wavelength spectra demonstrated optimal predictive performance. It achieved a coefficient of determination for the prediction set (Rp
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.