Application of NIR hyperspectral imaging for discrimination of lamb muscles

By M. Kamruzzaman, Gamal ElMasry, Da‐Wen Sun, Paul Allen. 2011

239 citations recorded by the source corpus.

Subfields: Analytical Chemistry, Animal Science and Zoology, Biomedical Engineering

View Paper: https://www.semanticscholar.org/paper/30e0e38a44d359e8e7ed7df34f3bb999d82b63f7

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. Hongbin Pu
3. Jun‐Hu Cheng
4. Ji Ma
5. Hui Huang
6. Li Liu
7. M. Kamruzzaman
8. Zhiwei Zhu

In Animal Science and Zoology

1. Da‐Wen Sun
2. Hongbin Pu
3. Ji Ma
4. Zhiwei Zhu
5. Jun‐Hu Cheng
6. M. Kamruzzaman
7. Dan Liu
8. Lu Wang

In Biomedical Engineering

1. Da‐Wen Sun
2. Hongbin Pu
3. Jun‐Hu Cheng
4. Ji Ma
5. Zhiwei Zhu
6. Lu Wang
7. M. Kamruzzaman
8. Michael O. Ngadi

Citations in the corpus

• Hyperspectral near-infrared imaging for the detection of physical damages of pear (2014, background): “Similarly, Kamruzzaman et al. (2011) discriminated 3 types of lamb muscles.”
• Recent Developments in Hyperspectral Imaging for Assessment of Food Quality and Safety (2014, background): “Mode Camera Product Spectral Coverage (nm) Analysis Type Image Processing Modeling Reference CCD Beef 400–1,000 Quantitative Co-occurrence matrix analysis, PCA Canonical discriminant [44] CCD Beef 400–1,100 Quantitative MLD Multi-linear regression (MLR) [70] CCD Beef 496–1,036 Quantitative MLD SMLR ”
• Application of Hyperspectral Imaging to Discriminate the Variety of Maize Seeds (2015, methodology): “On the other hand, hyperspectral imaging (HSI) technique (Gowen et al. 2007; Kamruzzaman et al. 2011; Cheng et al. 2014; Cheng and Sun 2015), an emerging technology in recent years integrating both computer vision or imaging (Wang and Sun 2002; Sun and * Da-Wen Sun dawen.”
• Combination of spectra and texture data of hyperspectral imaging for differentiating between free-range and broiler chicken meats (2015, unknown): “Ma, Liu, & Cheng, 2014), discrimination of lamb muscles (Kamruzzaman et al., 2011), and differentiation between fresh and frozen-thawed fish (Sone, Olsen, Sivertsen, Eilertsen, & Heia, 2012; Zhu, Zhang, He, Liu, & Sun, 2013).”
• Potential of hyperspectral imaging and multivariate analysis for rapid and non-invasive detection of gelatin adulteration in prawn (2013, unknown): “, 2012), lamb (Kamruzzaman et al., 2011), fish (Wu and Sun, 2013c, 2013d; Wu et al.”
• Application of Wavelet Analysis to Spectral Data for Categorization of Lamb Muscles (2014, methodology): “The detailed description of the hyperspectral imaging system and image acquisition was also described by Kamruzzaman et al. (2011).”
• Use of Hyperspectral Imaging to Discriminate the Variety and Quality of Rice (2015, background): “spectral requirements and thus has been applied for quality inspection, classification and evaluation of a wide range of agri-food products (Monteiro et al. 2007; Nakariyakul and Casasent 2011; Kamruzzaman et al. 2011).”
• Hyperspectral and multispectral imaging for evaluating food safety and quality (2013, background): “Lamb Lamb type discrimination Line-scan reflectance 900–1700 Kamruzzaman et al. (2011)”
• Rapid Quantification Analysis and Visualization of Escherichia coli Loads in Grass Carp Fish Flesh by Hyperspectral Imaging Method (2015, background): “…and Sun 2012; Gowen et al. 2007; Sun 2010), fruit and vegetables (Lorente et al. 2012), meat (Barbin et al. 2012; Elmasry et al. 2011a, b, 2012a, b; Kamruzzaman et al. 2011, 2012), agriculture and agro-food product (Liu et al. 2013) and fish and seafood (Cheng and Sun 2014; Menesatti et al. 2010).”