22 NIR Imaging
525
and potentially threaten public health. Vis–NIR spectral imaging has been demonstrated for pre-harvest detection of symptoms of viral infection and fungal growth
on plants and cereals such as maize and wheat [13].
Many studies have focused on the detection of fecal contamination on a wide
variety of food products, including fresh produce, meat or poultry surfaces. For
example, Vis–NIR imaging (450–851 nm) has been shown to be capable of detecting
fecal contamination on apples using with high accuracy levels, suggesting that just
two NIR wavebands (748 and 851 nm) could be used for detection [14]. Insect infestation is another example of contamination in the food processing chain detectable
by NIR imaging. One of the earliest reported studies in this area showed the possibility of using NIR imaging to detect insects inside wheat kernels [15]. In that study,
the authors demonstrated that subtraction of single wavelength images at 1300 nm
from those at 1202 nm resulted in an image in which infested kernels could be
distinguished from sound ones.
22.3.3 Food Authentication
In order to ensure compliance with labeling, legislation and consumer demand in
an ever expanding and global food supply chain, authentication and traceability
of food ingredients are critical. Due to the sensitivity of vibrational spectroscopy
to molecular structure and the development of advanced multivariate data analysis
techniques such as chemometrics, near- and mid-infrared spectroscopies have been
successfully used in authentication of the purity and geographical origin of many
foodstuffs, including honey, wine, cheese and olive oil. Spectral imaging, having the
added spatial dimension, has been used to analyze nonhomogeneous samples, where
spatial variation could improve information on the authentication or prior processing
of the food product, for example, in the detection of fresh and frozen-thawed meat
or in adulteration of flours [16].
22.3.4 Food Quality Control
NIR spectral imaging has been applied in a wide range of food quality control issues,
such as bruise detection in mushrooms, apples and strawberries and in the prediction
of the distribution of water, protein or fat content in heterogeneous products such
as meat, fish cheese and bread [17]. Typically, when observing the NIR spectrum of
high-moisture foods, the dominant spectral feature is a wide peak, centered at around
1450 nm, corresponding to the overtone and combination vibrations of fundamental -
OH stretching and bending vibrations within the food matrix. The shape and intensity
of this peak are sensitive to the local environment of the food matrix and can provide
information on changes in the water present in food products. This is useful since
525
and potentially threaten public health. Vis–NIR spectral imaging has been demonstrated for pre-harvest detection of symptoms of viral infection and fungal growth
on plants and cereals such as maize and wheat [13].
Many studies have focused on the detection of fecal contamination on a wide
variety of food products, including fresh produce, meat or poultry surfaces. For
example, Vis–NIR imaging (450–851 nm) has been shown to be capable of detecting
fecal contamination on apples using with high accuracy levels, suggesting that just
two NIR wavebands (748 and 851 nm) could be used for detection [14]. Insect infestation is another example of contamination in the food processing chain detectable
by NIR imaging. One of the earliest reported studies in this area showed the possibility of using NIR imaging to detect insects inside wheat kernels [15]. In that study,
the authors demonstrated that subtraction of single wavelength images at 1300 nm
from those at 1202 nm resulted in an image in which infested kernels could be
distinguished from sound ones.
22.3.3 Food Authentication
In order to ensure compliance with labeling, legislation and consumer demand in
an ever expanding and global food supply chain, authentication and traceability
of food ingredients are critical. Due to the sensitivity of vibrational spectroscopy
to molecular structure and the development of advanced multivariate data analysis
techniques such as chemometrics, near- and mid-infrared spectroscopies have been
successfully used in authentication of the purity and geographical origin of many
foodstuffs, including honey, wine, cheese and olive oil. Spectral imaging, having the
added spatial dimension, has been used to analyze nonhomogeneous samples, where
spatial variation could improve information on the authentication or prior processing
of the food product, for example, in the detection of fresh and frozen-thawed meat
or in adulteration of flours [16].
22.3.4 Food Quality Control
NIR spectral imaging has been applied in a wide range of food quality control issues,
such as bruise detection in mushrooms, apples and strawberries and in the prediction
of the distribution of water, protein or fat content in heterogeneous products such
as meat, fish cheese and bread [17]. Typically, when observing the NIR spectrum of
high-moisture foods, the dominant spectral feature is a wide peak, centered at around
1450 nm, corresponding to the overtone and combination vibrations of fundamental -
OH stretching and bending vibrations within the food matrix. The shape and intensity
of this peak are sensitive to the local environment of the food matrix and can provide
information on changes in the water present in food products. This is useful since