Integration of textural and spectral features of Raman hyperspectral imaging for quantitative determination of a single maize kernel mildew coupled with chemometrics

2021 ◽  
pp. 131246
Author(s):  
Yuan Long ◽  
Wenqian Huang ◽  
Qingyan Wang ◽  
Shuxiang Fan ◽  
Xi Tian
Author(s):  
Amadeus Holmer ◽  
Christoph Homberger ◽  
Thomas Wild ◽  
Frank Siemers

The objective evaluation of scattering tissue and the discrimination of tissue types is an issue that cannot be solved with colour cameras and image processing alone in many cases. Examples can be found in the determination of freshness and ageing of meat, and the discrimination of tissue types in food technology. In medical applications tissue discrimination is also an issue, e.g. in wound diagnostics. A novel hyperspectral imaging setup with powerful signal analysis algorithms is presented which is capable of addressing these topics. The spectral approach allows the chemical analysis of material and tissues and the measurement of their temporal change. We present a method of hyperspectral imaging in the visible-near infrared range which allows both the separation and spatial allocation of different tissue types in a sample, as well as the temporal changes of the tissue as an effect of ageing. To prove the capability of the method, the ageing of meat (slices of pork) was measured and, as a medical example, the application of the hyperspectral imaging setup for the recording of wound tissue is presented. The method shows the ability to discriminate the different tissue components of pork meat, and the ageing of the meat is observable as changes in spectral features. An additional result of our study is the fact that some spectral features, which seem to be typical for the ageing of the meat, are similar to those observed in the necrotic tissue from wound diagnostics in medicine.


2016 ◽  
Vol 40 (3) ◽  
pp. e12446 ◽  
Author(s):  
Jun Sun ◽  
Xinzi Lu ◽  
Hanping Mao ◽  
Xiaohong Wu ◽  
Hongyan Gao

2015 ◽  
Vol 178 ◽  
pp. 339-345 ◽  
Author(s):  
Zhenjie Xiong ◽  
Da-Wen Sun ◽  
Anguo Xie ◽  
Hongbin Pu ◽  
Zhong Han ◽  
...  

2017 ◽  
Vol 20 (sup1) ◽  
pp. S1037-S1044 ◽  
Author(s):  
Xinzi Lu ◽  
Jun Sun ◽  
Hanping Mao ◽  
Xiaohong Wu ◽  
Hongyan Gao

2019 ◽  
Vol 157 ◽  
pp. 410-416
Author(s):  
Huazhou Chen ◽  
Hanli Qiao ◽  
Bin Lin ◽  
Gaili Xu ◽  
Guoqiang Tang ◽  
...  

1999 ◽  
Vol 96 (9/10) ◽  
pp. 1608-1615
Author(s):  
T. E. Malliavin ◽  
H. Desvaux ◽  
M. A. Delsuc

Planta Medica ◽  
2011 ◽  
Vol 77 (12) ◽  
Author(s):  
M Koşar ◽  
F Göger ◽  
N Kırımer ◽  
KHC Başer

Sign in / Sign up

Export Citation Format

Share Document