logo Bangladesh Agricultural University (BAU)
Dr. Mohammed   Kamruzzaman
Dr. Mohammed Kamruzzaman

Professor Contact No : 01849113583
Department of Food Technology and Rural Industries Email : mohammed.kamruzzaman@bau.edu.bd
Faculty of Agricultural Engineering & Technology ResearchGate Google Scholar
 
Research Interest:   Hyperspectral imaging, NIR spectroscopy, VNIR spectrsocopy, FTIR spectroscopy, Machine Learning, Multivariate Analysis, Image Processing, Computer Vision, Meat and Food Quality and Authenticity.  
PhD    - 2013
University College Dublin (UCD)
Ireland
MSc    - 2009
Dublin Institute of Technology (DIT)
Ireland
Post-doc    - 2016
University of California, Davis (UC Davis)
USA
BSc    - 2003
Bangladesh University of Engineering & Technology (BUET)
Bangladesh
JSPS Post-doc    - 2015
The University of Tokyo
Japan
MS    - 2005
Bangladesh Agricultural University
Bangladesh
No Research information available..
No training information available..
Assistant Professor
06 Jun, 2006 - 28 Feb, 2013
Professor
16 Jun, 2017 -
Lecturer
29 Feb, 2004 - 05 Jun, 2006
Associate Professor
01 Mar, 2013 - 15 Jun, 2017
Total Number:  24
 

1.      Kamruzzaman, M., Takahama, S., & Dillner, A. M. (2018). Quantification of amine functional groups and their influence on OM/OC in the IMPROVE network. Atmospheric Environment. 172, 124-132. (IF=3.629)

2.      Kamruzzaman, M., Makino, Y., & Oshita, S. (2016). Rapid and non-destructive detection of chicken adulteration in minced beef using visible near-infrared hyperspectral imaging and machine learning. Journal of Food Engineering. 170, 8-15. (IF=2.771).

3.      Kamruzzaman, M., Makino, Y., & Oshita, S. (2016). Parsimonious model development for real-time monitoring of moisture in red meat using hyperspectral imaging. Food Chemistry, 196, 1084-1091. (IF=3.391).

4.      Kamruzzaman, M., Makino, Y., & Oshita, S. (2016). Hyperspectral imaging for real-time monitoring of water holding capacity in red meat. LWT-Food Science and Technology, 66, 685-691. (IF=2.416).

5.      Kamruzzaman, M., Makino, Y., & Oshita, S. (2016). Online monitoring of red meat color using hyperspectral imaging. Meat Science. 116, 110-117. (IF=2.615).

6.      Kamruzzaman, M., Makino, Y., & Oshita, S. (2015). Non-invasive analytical technology for the detection of contamination, adulteration, and authenticity of meat, poultry, and fish: a review. Analytica Chimica Acta. 853, 19-29. (IF=4.513). 26 citations

7.      Kamruzzaman, M., Makino, Y., Oshita, S. & Liu, S. (2015). Assessment of visible near-infrared hyperspectral imaging as a tool for detection of horsemeat adulteration in minced. Food & Bioprocess Technology. 8, 1054-1062. (IF=2.691). 30 citations

8.      Pu, H.-B., Kamruzzaman, M., Sun, D.-W. (2015). Selection of feature wavelengths for developing multispectral imaging systems for quality, safety and authenticity of muscle foods-a review. Trends in Food Science and Technology, 45, 86-104. (IF=4.651).

9.      Kamruzzaman, M., Makino, Y., & Oshita, S. (2015). Hyperspectral imaging in tandem with multivariate analysis and image processing for non-invasive detection and visualization of pork adulteration in minced beef. Analytical Methods7, 7496-7502. (IF=1.821).

10. Hongbin, P., Anguo, X., Sun, D.W. Kamruzzaman, M., & Ji, M. (2014). Application of wavelet analysis to spectral data for categorization of lamb musclesFood and Bioprocess Technology. 8, 1-16. (IF=2.691)

11. Hongbin, P., Sun, DW., Ma, J., Liu, D., & Kamruzzaman, M. (2014). Hierarchical variable selection for predicting chemical constituents in lamb meats using hyperspectral imaging. Journal of Food Engineering, 143, 44-52. (IF=2.771).

12.  Kamruzzaman, M., Sun, D-W., ElMasry, G., & Allen, P. (2013). Fast detection and visualization of minced lamb meat adulteration using NIR hyperspectral imaging and multivariate image analysis. Talanta, 103, 130-136. (IF=3.545). 70 citations

13.  Kamruzzaman, M., ElMasry, G., Sun, D-W., & Allen, P. (2013). Non-destructive assessment of instrumental and sensory tenderness of lamb meat by NIR hyperspectral imaging. Food Chemistry. 141, 389-396. (IF=3.391). 89 citations. One of the most cited articles (24/25).

14.  Kamruzzaman, M., ElMasry, G., Sun, D-W., & Allen, P. (2012). Prediction of some quality attributes of lamb meat using near infrared hyperspectral imaging and multivariate analysis. Analytica Chimica Acta. 714, 57-67. (IF=4.513). 185 citations. One of the most cited articles (7/25).

15.  Kamruzzaman, M., ElMasry, G., Sun, D-W., & Allen, P. (2012). Non-destructive prediction and visualization of chemical composition in lamb meat using NIR hyperspectral imaging and multivariate regression. Innovative Food Science and Emerging Technologies, 16, 218-226. (IF=3.273). 111 citations. One of the most cited articles

16.  Kamruzzaman, M., ElMasry, G., Sun, D-W., & Allen, P. (2012). Potential of hyperspectral imaging and pattern recognition for categorization and authentication of red meat. Innovative Food Science and Emerging Technologies. 16, 316-235. (IF=3.273). 56 citations. One of the most cited articles (15/25)

17.  ElMasry, G., Kamruzzaman, M., Sun, D.-W., & Allen, P. (2012). Principles and applications of hyperspectral imaging in quality evaluation of agro-food products: a review. Critical Reviews in Food Science and Nutrition. 52, 999-1023(IF=5.176). 142 citations.

18.  ElMasry, G., Sun, D-W., Kamruzzaman, M., Douglas Barbin & Allen, P. (2012). Hyperspectral imaging-A new era of applications in non-destructive sensing of meat quality. NIRNews, 23, 9-14.

19.  Kamruzzaman, M., ElMasry, G., Sun, D-W., & Allen, P. (2011). Application of NIR hyperspectral imaging for discrimination of lamb muscles. Journal of Food Engineering. 104, 332-340. (IF=2.771). 167 citations.

20.  Kamrul, N, Kamruzzaman, M., & Islam, M. N. (2007). Water sorption isotherm and dehydration kinetics of raw and parboiled paddy. Bangladesh Journal of Agricultural Engineering. 18, 73-80

21.  Rahman, M., Kamruzzaman, M., & Islam, M. N. (2007). Osmotic dehydration of hog-plum and product development. Journal of Bangladesh Agricultural University. 5, 399-406.

22.  Kamruzzaman, M., & Islam, M. N. (2006). Kinetics of dehydration of aroids and developed dehydrated aroids products. Journal of Chemical Engineering, Institute of Engineer’s Bangladesh. 24, 19-24.

23.  Kamruzzaman, M., Islam, M. S. & Muyen, Z. (2005). Textile Dyeing Waste Treatment: Comparison Between two treatment plants. Bangladesh Journal of Progressive Science & Technology. 3, 119-122.

24.  Ahmed, B. Kamruzzaman, M., Ahammed, M. Z & Hossain, I. (2005). Production of high temperature refractory bricks from rice husk ash. Journal of Bangladesh Society of Agriculture Science Technology. 2, 45-48.

 

 

1.      Kamruzzaman, M., Takahama, S., & Dillner, A. M. (2018). Quantification of amine functional groups and their influence on OM/OC in the IMPROVE network. Atmospheric Environment. 172, 124-132. (IF=3.629)

2.      Kamruzzaman, M., Makino, Y., & Oshita, S. (2016). Rapid and non-destructive detection of chicken adulteration in minced beef using visible near-infrared hyperspectral imaging and machine learning. Journal of Food Engineering. 170, 8-15. (IF=2.771).

3.      Kamruzzaman, M., Makino, Y., & Oshita, S. (2016). Parsimonious model development for real-time monitoring of moisture in red meat using hyperspectral imaging. Food Chemistry, 196, 1084-1091. (IF=3.391).

4.      Kamruzzaman, M., Makino, Y., & Oshita, S. (2016). Hyperspectral imaging for real-time monitoring of water holding capacity in red meat. LWT-Food Science and Technology, 66, 685-691. (IF=2.416).

5.      Kamruzzaman, M., Makino, Y., & Oshita, S. (2016). Online monitoring of red meat color using hyperspectral imaging. Meat Science. 116, 110-117. (IF=2.615).

6.      Kamruzzaman, M., Makino, Y., & Oshita, S. (2015). Non-invasive analytical technology for the detection of contamination, adulteration, and authenticity of meat, poultry, and fish: a review. Analytica Chimica Acta. 853, 19-29. (IF=4.513). 26 citations

7.      Kamruzzaman, M., Makino, Y., Oshita, S. & Liu, S. (2015). Assessment of visible near-infrared hyperspectral imaging as a tool for detection of horsemeat adulteration in minced. Food & Bioprocess Technology. 8, 1054-1062. (IF=2.691). 30 citations

8.      Pu, H.-B., Kamruzzaman, M., Sun, D.-W. (2015). Selection of feature wavelengths for developing multispectral imaging systems for quality, safety and authenticity of muscle foods-a review. Trends in Food Science and Technology, 45, 86-104. (IF=4.651).

9.      Kamruzzaman, M., Makino, Y., & Oshita, S. (2015). Hyperspectral imaging in tandem with multivariate analysis and image processing for non-invasive detection and visualization of pork adulteration in minced beef. Analytical Methods7, 7496-7502. (IF=1.821).

10. Hongbin, P., Anguo, X., Sun, D.W. Kamruzzaman, M., & Ji, M. (2014) Application of wavelet analysis to spectral data for categorization of lamb muscles. Food and Bioprocess Technology. 8, 1-16. (IF=2.691)

11. Hongbin, P., Sun, DW., Ma, J., Liu, D., & Kamruzzaman, M. (2014). Hierarchical variable selection for predicting chemical constituents in lamb meats using hyperspectral imaging. Journal of Food Engineering, 143, 44-52. (IF=2.771).

12.  Kamruzzaman, M., Sun, D-W., ElMasry, G., & Allen, P. (2013). Fast detection and visualization of minced lamb meat adulteration using NIR hyperspectral imaging and multivariate image analysis. Talanta, 103, 130-136. (IF=3.545). 70 citations

13.  Kamruzzaman, M., ElMasry, G., Sun, D-W., & Allen, P. (2013). Non-destructive assessment of instrumental and sensory tenderness of lamb meat by NIR hyperspectral imaging. Food Chemistry. 141, 389-396. (IF=3.391). 89 citations. One of the most cited articles (24/25).

14.  Kamruzzaman, M., ElMasry, G., Sun, D-W., & Allen, P. (2012). Prediction of some quality attributes of lamb meat using near infrared hyperspectral imaging and multivariate analysis. Analytica Chimica Acta. 714, 57-67. (IF=4.513). 185 citations. One of the most cited articles (7/25).

15.  Kamruzzaman, M., ElMasry, G., Sun, D-W., & Allen, P. (2012). Non-destructive prediction and visualization of chemical composition in lamb meat using NIR hyperspectral imaging and multivariate regression. Innovative Food Science and Emerging Technologies, 16, 218-226. (IF=3.273). 111 citations. One of the most cited articles

16.  Kamruzzaman, M., ElMasry, G., Sun, D-W., & Allen, P. (2012). Potential of hyperspectral imaging and pattern recognition for categorization and authentication of red meat. Innovative Food Science and Emerging Technologies. 16, 316-235. (IF=3.273). 56 citations. One of the most cited articles (15/25)

17.  ElMasry, G., Kamruzzaman, M., Sun, D.-W., & Allen, P. (2012). Principles and applications of hyperspectral imaging in quality evaluation of agro-food products: a review. Critical Reviews in Food Science and Nutrition. 52, 999-1023(IF=5.176). 142 citations.

18.  ElMasry, G., Sun, D-W., Kamruzzaman, M., Douglas Barbin & Allen, P. (2012). Hyperspectral imaging-A new era of applications in non-destructive sensing of meat quality. NIRNews, 23, 9-14.

19.  Kamruzzaman, M., ElMasry, G., Sun, D-W., & Allen, P. (2011). Application of NIR hyperspectral imaging for discrimination of lamb muscles. Journal of Food Engineering. 104, 332-340. (IF=2.771). 167 citations.

20.  Kamrul, N, Kamruzzaman, M., & Islam, M. N. (2007). Water sorption isotherm and dehydration kinetics of raw and parboiled paddy. Bangladesh Journal of Agricultural Engineering. 18, 73-80

21.  Rahman, M., Kamruzzaman, M., & Islam, M. N. (2007). Osmotic dehydration of hog-plum and product development. Journal of Bangladesh Agricultural University. 5, 399-406.

22.  Kamruzzaman, M., & Islam, M. N. (2006). Kinetics of dehydration of aroids and developed dehydrated aroids products. Journal of Chemical Engineering, Institute of Engineer’s Bangladesh. 24, 19-24.

23.  Kamruzzaman, M., Islam, M. S. & Muyen, Z. (2005). Textile Dyeing Waste Treatment: Comparison Between two treatment plants. Bangladesh Journal of Progressive Science & Technology. 3, 119-122.

24.  Ahmed, B. Kamruzzaman, M., Ahammed, M. Z & Hossain, I. (2005). Production of high temperature refractory bricks from rice husk ash. Journal of Bangladesh Society of Agriculture Science Technology. 2, 45-48.

 

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