ArticleFoods (Basel, Switzerland)2022
Real-Time Monitoring of the Quality Changes in Shrimp (
Article in Foods (Basel, Switzerland), 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
What it found
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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
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Who cites it
8 citing papers in PubMed, 24 citations in OpenAlex.
- Development of a Low-Sodium Soaking Solution for Shrimp Processing Using Potassium Phosphates (KTPP and TKPP) and L-Lysine: Impacts on Quality and Water-Holding Capacity.Foods (Basel, Switzerland) · 2026Article
- Transformative artificial intelligence integration in aquatic supply chains: synergizing precision aquaculture with intelligent logistics and data-driven consumption.Food chemistry: X · 2026Review
- Effects of Hot-Air Drying Conditions on Quality Attributes of Meat and Shell of Dried Shrimp.Foods (Basel, Switzerland) · 2025Article
- Heat and Mass Transfer in Shrimp Hot-Air Drying: Experimental Evaluation and Numerical Simulation.Foods (Basel, Switzerland) · 2025Article
- DietaryAquaculture nutrition · 2025Article
- Uncovering quality changes of shrimp (Food chemistry: X · 2024Article
- A two-dimensional correlation spectroscopy analysis-based approach for asymptomatic rot detection in stored potatoes using hyperspectral imaging.Food chemistry: X · 2024Article
- Fast Nondestructive Detection Technology and Equipment for Food Quality and Safety.Foods (Basel, Switzerland) · 2023Article
Corrections and comments
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Authors and funding
8 authors at 1 institution in 1 country.
Funding
Abstract
Hot air drying is the most common processing method to extend shrimp's shelf life. Real-time monitoring of moisture content, color, and texture during the drying process is important to ensure product quality. In this study, hyperspectral imaging technology was employed to acquire images of 104 shrimp samples at different drying levels. The water distribution and migration were monitored by low field magnetic resonance and the correlation between water distribution and other quality indicators were determined by Pearson correlation analysis. Then, spectra were extracted and competitive adaptive reweighting sampling was used to optimize characteristic variables. The grey-scale co-occurrence matrix and color moments were used to extract the textural and color information from the images. Subsequently, partial least squares regression and least squares support vector machine (LSSVM) models were established based on full-band spectra, characteristic spectra, image information, and fused information. For moisture, the LSSVM model based on full-band spectra performed the best, with residual predictive deviation (RPD) of 2.814. For
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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.