Near-Infrared Diffuse Reflection
Analysis of Fruit
Written by Yvette Mattley, PhD
Application Note
Keywords
• Fruit characteristics
• Noninvasive assessment
Techniques
• Diffuse reflection
• Near infrared spectroscopy
Applications
• Agricultural quality control
• Sugar and starch content
• Moisture determination
The quality of fruit and produce cannot be judged by appearance alone.
A colorful mango or vibrant avocado must do more than add a splash of
color to the plate. Taste and freshness are critical. Since it is not practical
to determine fruit quality by tasting each individual piece, an objective,
nondestructive measurement is needed to determine the quality of the
fruit hidden beneath the peel. In this application note, near-infrared
(NIR) diffuse reflection spectra are measured for avocados and mangoes
to demonstrate the power of NIR measurements for the noninvasive
assessment of fruit quality.
Background
Consumers use many techniques to assess fruit quality including smell,
firmness, sound, appearance and even intuition. Everyone has their
own special approach, with mixed results. While these qualitative
techniques are sufficient for consumers, commercial fruit growers
and packers require a quantitative approach to determining fruit
quality to ensure customer satisfaction and retain or expand market
share. Determination of critical quality parameters such as sugar,
starch and moisture content requires a rapid, noninvasive, online
measurement to test fruit prior to picking or packaging. NIR spectroscopy
meets these requirements.
NIR spectroscopy has been used since the 1970s for the analysis of
agricultural products. Spectral data for NIR light reflected from an
agricultural sample like grain or produce is acquired and compared
with a calibration model generated from spectral data acquired for
samples with known levels of the constituents of interest. For fruit or
produce covered by a peel, the longer wavelengths used for NIR analysis
are weakly absorbed so they pass through the peel, enabling sampling of
the fruit pulp beneath. The measurement of NIR reflection is rapid (no
sample preparation is required), quantitative (with the assistance of
carefully constructed calibration models) and nondestructive.
The NIR region extends from 780-2500 nm.
Absorption of light in this region causes molecules
to vibrate. These molecular vibrations result in
spectral data with features dependent on the
chemical composition of the sample. In the case of
agricultural samples, the NIR spectra are typically
composed of broad peaks due to overlapping
absorptions caused by overtones and combinations of
vibrational modes of organic functional groups like
C-H, O-H and N-H chemical bonds. The NIR spectrum
provides a snapshot of the sample with information
for multiple components available in a single NIR
spectrum. These characteristics and others make
modern NIR spectroscopy instrumentation ideal for
online monitoring and process control.
Starch and sugar (primarily fructose, glucose and
sucrose) are commonly measured to determine fruit
maturity and quality. While the peaks for these
constituents are located near one another, starch
has specific wavelengths that enable construction
of a multi-parametric model for determination of
fruit quality. An extended range NIR spectrometer
like the Ocean Optics NIRQuest256-2.5 is a great
option for these measurements because it can
detect critical starch peaks near 1722 nm, 2100 nm
and 2139 nm, as well as sugar peaks that occur
primarily between 900-1200 nm (some peaks also
occur >2100 nm). The NIRQuest256-2.5 enables
detection of these wavelengths in a single spectrum.
In addition to the spectrometer, a bright light
source like the Ocean Optics Vivo Light Source is
necessary. Vivo has four powerful tungsten halogen
bulbs and fibers that transmit light efficiently for
effective NIR measurements of fruit. Since much of
the light will scatter off the surface of the fruit, a
large core diameter fiber (600 microns) is recommended for these measurements to increase
throughput and improve sensitivity.
Sampling configuration is critical for these
measurements. In addition to the light lost by
scattering from the surface of the fruit, water in the
fruit will absorb NIR wavelengths. In addition, the
constituents of fruit (or any natural or agricultural
products) are not uniformly distributed within the
sample. Sampling over a large surface area of the
fruit is recommended to provide an average value
for the constituents in the fruit. A light source with
a large illumination area is a great option for sample
illumination when testing fruit and produce.
While the results reported here are qualitative, a
carefully constructed chemometrics model is
required for a multi-parameter, quantitative
assessment of fruit quality. With a good set of
reference spectra and PLS (partial least squares)
modeling, a calibration model can be developed to
measure multiple fruit parameters (sugar, starch and
other fruit constituents) for the prediction of fruit
quality. The ability to quantitatively measure multiple
parameters simultaneously makes NIR spectroscopy
a powerful tool for the agricultural industry.
Measurement Conditions
NIR spectra were measured for avocados and mangoes
using the NIRQuest256-2.5 NIR spectrometer
(900-2500 nm) and Vivo direct illuminated reflection
stage. A 2-meter VIS-NIR fiber with a 600 micron
core diameter arranged at a 45 degree angle relative
to the Vivo tungsten halogen bulbs was used for
the measurement of diffuse reflection from the
fruit. Reference measurements were made with a
diffuse reflection standard. The dark measurement
was made with the lamps turned on and an empty
optical stage. The stage was shielded from overhead
illumination during the dark measurement with a
black shroud. The setup used for the measurements
is shown in Figure 1.
Figure 1: An NIR spectrometer used with a powerful tungsten
halogen light source and optical stage provides a convenient
setup for diffuse reflection analysis of fruit.
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Diffuse Reflection Spectra of Ripe and Unripe
Avocado and Mango Samples
Reflection (%)
NIR diffuse reflection was measured for whole fruit
samples with measurements made at four different
locations on the fruit. The fruit was placed on the
magnetic ring of the optical stage to keep the fruit
from rolling off the stage. Multiple measurements
were made due to the variable nature of fruit – the
effects of bruising, non-uniformity in color and
differences in sugar content (due to differences in
sun exposure) all lead to NIR spectral differences. To
account for the inhomogeneity and variations in
the fruit surface, many more measurements should
be made at different points on the fruit surface.
Results
Notably, spectral features observed in these diffuse
reflection spectra arise from a combination of
phenomena depending on the amount of light
scattered from the surface of the fruit and the
penetration depth for NIR light into the sample.
Light that is not scattered by the surface of the
fruit passes through the peel and enters the fruit
where it can be absorbed based on chemical composition. While diffuse reflection measurements are
relatively straightforward to make, diffuse reflection from a variable rounded sample like a piece of
fruit results in a complicated spectrum requiring
carefully constructed interpretation models to
Figure 2: NIR diffuse reflection measurements of mangoes and
avocados reveal spectral variability from sample to sample.
Also, spectra for peeled versus unpeeled ripe avocados and mangoes were captured. In the case of the
avocado, spectral features were more pronounced
for the peeled avocado than the unpeeled avocado.
This may result from less reflection of light by the
peel, which increases absorption based on the
chemical composition of the avocado.
Diffuse Reflection Spectra of Peeled and Unpeeled Mangoes
Reflection (%)
NIR diffuse reflection measurements were made for
whole ripe and unripe mangoes and avocados. In
Figure 2, the average of the spectra measured at
four locations on each piece of fruit is shown for
two mangoes and two avocados. Multiple spectra
(n=4) were recorded for each piece of fruit to
account for the inhomogeneity of the fruit. These
spectra demonstrate that even spectra for the same
fruit type show variability across the spectral region,
with the avocado more consistent in the region
>~1100 nm. While the spectral features are similar
for both types of fruit, differences in magnitude
are observed throughout the spectra. Sampling
additional locations on the surface of the fruit
would help to average out variability for a given
piece of fruit and improve the accuracy and
repeatability of the results. Fortunately, the
speed of the NIR technique provides the option to
sample a larger surface area of the fruit with multiple
measurements without the need for lengthy
measurement times.
Wavelength (nm)
Wavelength (nm)
Figure 3: Differences in spectral features of peeled and
unpeeled ripened mangoes may result from less
reflection of the light by the peel.
For mangoes, the effect of peeling the fruit is similar
to the spectral differences observed for peeled and
unpeeled avocados. But the impact of removing the
peel is not as significant for the mangoes because
there is less smoothing due to light reflected from
the peel (Figure 3). The spectral differences observed
when an avocado or mango is peeled suggest that
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different fruit peels have different properties that
impact the overall fruit spectrum either through
chemical composition or reflection properties.
The degree of fruit ripening also can be observed in
NIR analysis. The spectra for ripe versus unripe
avocados and mangoes were captured. The unripe
avocado spectra are very consistent in the region
from ~1900-2500 nm; the spectrum for the ripe
avocado in this region flattens relative to the unripe
avocado (Figure 4).
While the spectral data shown here illustrate the
qualitative differences between avocados and
mangoes at different stages of maturity, more
quantitative information on fruit quality could be
extracted from these spectra using an appropriate
chemometric model and careful sampling to
account for the inhomogeneity of the fruit.
References
Near-infrared Spectroscopy in Food Analysis, Brian G.
Osborne, Encyclopedia of Analytical Chemistry, 1986
Reflection (%)
Diffuse Reflection Spectra of Peeled and Unpeeled Avocados
Wavelength (nm)
Figure 4: Spectral features for unripe avocado are very
consistent in the region from ~1900-2500 nm.
For mangoes, the ripe versus unripe sample spectra
are very similar with only very slight differences
occurring between ~1900-2500 nm. These differences
are most likely related to differences in sugar and
starch content as the fruit matures. While many of
the spectral changes are very subtle, a carefully
constructed calibration model and a good sampling
approach could be used to extract more quantitative
information on fruit maturity from these spectra.
Conclusion
NIR spectroscopy is a powerful measurement tool for
the characterization of agricultural samples. In the
case of fruit, long NIR wavelengths where absorption
is weak allow sampling through the peel of the fruit.
This also makes sample preparation unnecessary.
Combine these advantages with the ability to make
rapid measurements and NIR spectroscopy becomes
a great option for at-line measurement of fruit.
Contact us today for more information
on setting up your spectroscopy
system from Ocean Optics.
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