欧亚国际

丹麦DTU大学、丹麦肉品研究院与Videometer的科学家将通用的色度计与新型多光谱成像技术在肉色测量的应用上做了比较，取得了令人满意的效果.

对新鲜和加工肉的肉色测量研究显示采用多光谱成像技术，例如 VideometerLab系统，结合基于CIE标准的色彩模型，是一种有效替换标准色度计的方法。研究揭示出两种方法评估颜色的不同，特别是对鲜肉测量应用实例中。就这些样品而言，研究揭示出特殊反射会影响色度测量的色差分量，导致其与亮度分量L*的相关性增加。使用漫射照明的成像系统可考虑作为可行的替换标准测量方法的替代方案。除了对整个样品进行客观测量以及捕捉色彩差异，多光谱还有其它测量特性，如成份测量、尺寸形态测量等，在食品行业质量控制或研究领域具有多功能的优势。产品详细介绍参见链接。

A Comparison of Meat Colour Measure-ments From a Colorimeter andMultispectral Images.

C       H.  Trinderupa,  A      L.      Dahla,  K.      Jensenb,  J   M.  Carstensena,c,  and  K. Conradsena

aDTUCompute,TechnicalUniversityofDenmark,Matematiktorvet,Building303B,2800Kgs.Lyngby,Denmark

bDanishMeatResearchInstitute,Maglegårdsvej2,4000Roskilde,Denmark

cVideometerA/S,LyngsøAllé3,2970Hørsholm,Denmark

Correspondingauthor:ctri@dtu.dk

Introduction

Consumers select products based on colour, especially withfresh  products,  such  as  fruit,  vegetables,  and  meat  (Francis,1995). This choice is associated  with their earlier experiences, and acceptance relies on these (MacDougall & Hutchings, 2002). Consistent   and   objective   colour   assessment   is   therefore important in the fields of research, product development, and quality  control  (Wu  &  Sun,  2013).  Within  food  science  the CIELAB colour space is often applied for colour evalsuation. This colour space corresponds well with the colour perception by humans (León et al., 2006), which is advantageous when comparing with results of a sensory panel.

This study focuses on the assessment of meat colour. Thestandard instruments for colour measurement are colorimeters and spectrophotometers. A colorimeter is a so-called tristimulus instrument that employs filters in order to obtain colour values (Hunt et al., 1991). The colorimeter is a handheld instrument, where the operator  measures  a sample at a number of sites. These sites are chosen depending on the sample, e.g. to avoid meat tendons and intramuscular fat. This makes the measurements subjective and hard to reproduce (Larraín et al.,2008).  Furthermore,  these  site  measurements  do  not  alwaysreflect  the  colour  variation  of  the  entire  sample  (Mancini  & Hunt, 2005).

To overcome some of the limitation of the colorimeter we suggest  using  a  multispectral  imaging  system.  We  map  the detailed images to the CIELAB colour space using a photometric imaging model. We compare the colour assessment of our visual system  with  a standard  colorimeter  for  different  meat  types using the CIELAB values. Unlike the colorimeter, the imaging system measures the spatial colour variation across the entire sample.

Food  colours  have  previously  been  assessed  using  visual

systems by converting RGB images to sRGB images and then to CIELAB values (Larraín et al., 2008; Mendoza et al., 2006; Blasco et al., 2003; Chen et al., 2002; O’Sullivan  et al., 2003; Yam &Spyridon,  2004).  Wu  &  Sun  (2013)  emphasize  that  the  RGB

images, amongst other issues, are dependent on the sensitivity of the camera employed, and cannot be directly transformed to sRGB in a consistent manner. As a result, the reproducibility and objectivity   of   the   colour   assessment   is   compromised.   By applying a multispectral vision system, the advantage of more spectral information is achieved, but also the robustness and consistency that is needed for colour assessment. In addition, mapping by the photometric  imaging model is a direct way of obtaining the CIELAB values. We therefore chose to use multispectral images for our colour assessment.

Yagiz  et  al.  (2009)  reported  a  study  similar  to  ours  ondifferences  in colour measurements  from a colorimeter  and a RGB vision system for fresh salmon fillet colour. The study revealed that despite the fact that similar results were obtained from calibration plates for the two assessment methods, the measured colour of fresh salmon differed. The colour recorded by the vision system closely resembled the perceived colour of the fillets, whereas the colorimeter returned grayish colours.

In this study we investigated meats from livestock animalsand poultry, both fresh and processed types. Working with these two types ofproduct under the same conditions made it possible to investigate how the processing of the meat influenced the colour assessment. The basis of the analysis was a variance component analysis considering all of the possible effects influencing   the  colour  assessment.   First  and  foremost   the analysis established that the two methods assessed the colour components  differently,  especially  the chromatic  components, a* and b*. The difference depended on the type of the sample, since the measurements of processed and fresh meat showed different   behaviours.   This   indicated   that   the   reflectance properties of the samples influence the colorimeter more than the multispectral  vision system. The results are in accordance with   the   results   of   Yagiz   et  al.  (2009)   and   support   the advantages  of using  a vision  system  for colour assessment  in food science.

This  study  on  the  measurement  of  meat  colour  of  bothfresh and processed meat types have shown that employing a multispectral imaging system, such as  the VideometerLab in combination with a colour model based on the CIE standards is a valid  alternative   to  the  standard  colorimeter.   The  analysis revealed differences in the assessment of colour by the two methods, especially in the case of samples of fresh meat. For these samples  the analysis  indicated  that specular  reflectance can influence the colorimeter measurements of the chromatic components, giving rise to a dependency on the lightness component L*. The use of a vision system with diffuse lightning is therefore considered to be a practicable alternative to the standard measurement method. Besides offering objective measurement and capture of colour variation across a sample, it offers  other  possibilities  that  can  be  of  advantage  in  quality control or research within food science.