Hyperspectral imaging for nondestructive determination of some quality attributes for strawberry

By Gamal ElMasry, Ning-ning Wang, Adel Elsayed, Michael O. Ngadi. 2007

493 citations recorded by the source corpus.

Subfields: Analytical Chemistry, Biophysics, Industrial and Manufacturing Engineering

View Paper: https://www.semanticscholar.org/paper/df357ad5e1b40ea905e4857c2fd64128e6b131bd

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Analytical Chemistry

1. Da‐Wen Sun
2. Di Wu
3. M. Kamruzzaman
4. Hongbin Pu
5. Digvir S. Jayas
6. Jitendra Paliwal
7. N. White
8. S. Mahesh

In Biophysics

1. Da‐Wen Sun
2. Digvir S. Jayas
3. Jitendra Paliwal
4. N. White
5. S. Mahesh
6. Di Wu
7. Yidan Bao
8. Aoife A. Gowen

In Industrial and Manufacturing Engineering

1. Da‐Wen Sun
2. Paul Allen
3. Di Wu
4. M. Kamruzzaman
5. Gamal ElMasry
6. Colm O'Donnell
7. N. White
8. Jean-Michel Roger

Citations in the corpus

• Comparison of Partial Least Squares Regression (PLSR) and Principal Components Regression (PCR) Methods for Protein and Hardness Predictions using the Near-Infrared (NIR) Hyperspectral Images of Bulk Samples of Canadian Wheat (2014, methodology): “A set of orthogonal projection axes (W), also called as the PLS weights, and wavelength scores (T) were determined by the PLS algorithm (ElMasry et al. 2007). bY ¼ XW aβ ¼ Taβ ð2Þ W ¼ W P0 Wð Þ−1 ð3Þ where bY is the predicted value of the parameter of interest, P ′ is the wavelength loadings, W is…”
• Examination of the quality of spinach leaves using hyperspectral imaging (2013, background): “However 5 pre-processing could also destroy valuable information and therefore these methods6 should be applied carefully.7 Researchers are often interested in finding the most relevant few wavelengths that8 could influence the quality evaluation of the product (ElMasry et al., 2007).”
• Ripeness Classification of Astringent Persimmon Using Hyperspectral Imaging Technique (2014, unknown): “This means that unripe fruit contain higher local variations and more smooth texture (ElMasry et al., 2007).”
• Hyperspectral and multispectral imaging for evaluating food safety and quality (2013, unknown): “Strawberry Quality evaluation Line-scan reflectance 400–1000 ElMasry et al. (2007)”
• Nondestructive Measurement of Soluble Solids Content of Kiwifruits Using Near-Infrared Hyperspectral Imaging (2015, unknown): “It has the advantages of receiving spatially distributed spectral responses at each pixel of a fruit image (ElMasry et al. 2007).”