Physical Sensors for Quality Control during Processing 4512004 ; Hildrum et al. 2006 ; Reddy - Gangidi
and Proctor 2008 ) was reported.
Some commercialized sensors based on
infrared spectroscopy techniques already
exist. For example, the QualitySpec ® BT
system (ASD Inc, U.S.) utilizes NIR technol-
ogy in order to analyze beef carcasses for
predicting tenderness on - line. Other exam-
ples are the APIS Meat Optimizer ® (Prediktor
AS, Norway) or the DA7200 multi - purpose
NIR Analyser (Perten Instruments AB,
Sweden), which allow on - line analysis of
meat and meat product composition by using
NIR technology. Other sensors use the
FT - NIR to analyze the composition of meat
and poultry (Quadra Chem Lavoratories,
Ltd., U. K.). The FOP analyzer ® (Tecnilab,
Spain) utilizes the NIR with a fi ber - optic
probe for measuring proteins, moisture, and
fat in processed meats. Other sensors avail-
able for real - time measurements of fat, mois-
ture, and protein in meat products are the
in - line Foods Gauge (NDC Infrared
Engineering, U.S.) and the MCT 360 (Process
Sensors Corporation, U.S.).
In conclusion, NIR spectroscopy offers a
number of important advantages with regard
to traditional methods of determining meat
and meat product quality. This technique
allows for a fast, simple, nondestructive, and
noninvasive analysis (B ü ning - Pfaue 2003 ). It
requires minimal or no sample preparation
and offers accurate results (Niem ö ller and
Behmer 2008 ). Its greatest disadvantage is a
weak sensitivity to minor constituents and
the complicated spectra data interpretation
(Prevolnik et al. 2004 ).Conclusions
The improvement of meat products ’ quality
is one of the most important challenges for
the industry in order to satisfy human desires,
to minimize economic losses, and to opti-
mize meat plant processes. Meat quality can
be based on technological, sensory, andscopic structural changes of meat (Damez
and Clerjon 2008 ).
More efforts have been made in order to
investigate the ability of NIR to predict meat
quality and composition: in pork (Br ø ndum
et al. 2000 ; Forrest et al. 2000 ; Chan et al.
2002 ; Geesink et al. 2003 ; Meulemans et al.
2003 ; Gonz á lez - Martin et al. 2005 ; Barlocco
et al. 2006 ; Savenije et al. 2006 ; Ortiz -
Somovilla et al. 2007 ), in beef (Hildrum et
al. 1994, 1995 ; Thyholt and Isaksson, 1997 ;
Byrne et al. 1998 ; Park et al. 1998 ; R ø dbotten
et al. 2000, 2001 ; Liu et al. 2001, 2003 ;
Leroy et al. 2004 ; Shackelford et al. 2004,
2005 ; Andr é s et al. 2008 ; Naganathan et al.
2008a, b ; Ripoll et al. 2008 ; Sierra et al.
2008 ; ), in poultry meat (Valdes and Summers
1986 ; Cozzolino et al. 1996 ; Rannou and
Downey 1997 ; Ding et al. 1999 ; Fumi è re
et al. 2000 ; Lyon et al. 2001 ), in lamb
(Cozzolino et al. 2000 ; Andr é s et al. 2007 ),
in oxen (Prieto et al. 2006, 2008a, b ), and in
kangaroo (Ding and Xu 1999 ). The main
applications of this technique are for deter-
mining moisture, fat, protein, and in some
cases, minerals in meat and meat products
(Gonzalez - Martin et al. 2002a, b, 2005 ;
Alomar et al. 2003 ; Realini et al. 2004 ;
Barlocco et al. 2006 ; Sierra et al. 2008 ). It is
also used to determine meat quality, pH,
appearance and color, and muscle character-
istics, such as water - holding capacity, intra-
muscular fat, tenderness, and microbial
spoilage (Byrne et al. 1998 ; Br ø ndum et al.
2000 ; Geesink et al. 2003 ; Liu et al. 2003 ;
Garcia - Rey et al. 2005 ; Hoving - Bolink et al.
2005 ; Shackelford et al. 2005 ; Barlocco
et al. 2006 ; Savenije et al. 2006 ; Andr é s
et al. 2007 ; Rust et al. 2008 ). Moreover, NIR
is used to detect the adulteration of meat and
meat products and to identify frozen/thawed
meats (Downey and Beauch ê ne 1997a, b ;
McElhinney et al. 1999a, b ; Ding and Xu
2000 ; Lyon et al. 2001 ). An extensive over-
view of the applications of infrared spectros-
copy in foods (Ozaky et al. 2007 ) and in
meat and meat products (Prevolnik et al.