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NIR diffuse reflection analysis of fruit

Yvette Mattley of Ocean Optics describes the use of NIR spectroscopy to determine fruit maturity and sweetness.

 

NIR spectra comprise broad peaks resulting from molecular vibrations caused by interaction of molecules with light in the NIR wavelength region. A wealth of information can be extracted from these peaks for the quantitative determination of the chemical composition of various samples, including fruit and produce.

 NIR spectroscopy is especially effective for determination of fruit quality parameters, such as sugar, starch and moisture content. To evaluate this capability, we measured NIR diffuse reflection spectra of avocados and mangoes.

Background

Absorption of light in the NIR region (~780-2500 nm) 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 typically consist 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.

In the case of fruits and produce, starch and sugar (primarily fructose, glucose and sucrose) are commonly measured to determine fruit maturity and sweetness. While the spectral peaks for these constituents are located near one another, starch has some specific wavelengths that can be used to build a multi-parametric model for determination of fruit quality. An NIR spectrometer, like the Ocean Optics NIRQuest256-2.5, is effective for these measurements because it detects 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).

In addition to the spectrometer, NIR measurements require a bright light source. For our experiments, we used a source consisting of four high-output tungsten halogen bulbs, connected to optical fibers that transmit light efficiently for NIR measurements. Since much of the light scatters off the surface of the fruit, a large core diameter fibe (600 μm) is recommended to increase throughput and improve sensitivity.

Sampling configuration is critical for these measurements. In addition to the light lost by scattering off the surface of the fruit, water in the fruit will absorb NIR wavelengths. In addition, the constituents of fruit 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 measurements.

While the results reported here are qualitative, a chemometrics model would be required for a multi-parameter, quantitative assessment of fruit quality. With a good set of reference spectra and modeling, one can develop a calibration model to measure multiple fruit parameters as predictors of fruit quality.

Measurement conditions

NIR spectra were measured for avocados and mangoes using the NIRQuest256-2.5 NIR spectrometer (900-2500nm) and tungsten halogen light source mounted to an adjustable optical stage. A 2-meter length optical fiber with a 600 μm core diameter arranged at a 45 degree angle relative to the tungsten halogen bulbs was used for the measurement of diffuse reflection from the fruit.

 NIR diffuse reflection was measured for the samples at four different locations on the fruit. Multiple measurements were made due to the variable nature of fruit – bruising, non-uniformity in colour and differences in sugar content (due to differences in sun exposure) all lead to NIR spectral differences. 

Figure 1. NIR diffuse reflection measurements of avocados and mangoes reveal spectral variability from sample to sample.

 

Figure 2. Differences in the spectral features of peeled and unpeeled avocados may result from less reflection of the light
by the peel.

Results

NIR diffuse reflection measurements were made for whole ripe and unripe avocados and mangoes. In Figure 1, the average of the spectra measured at four locations on each piece of fruit is shown for two avocados and two mangoes. Multiple spectra (n=4) were recorded for each piece of fruit to account for the inhomogeneity of individual samples. 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 above ~1100 nm. While the spectral features are similar for both types of fruit, differences in magnitude are observed throughout the spectra. Measuring 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 makes multiple measurements of a larger surface area of the fruit possible in a manageable amount of time.

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, diffuse reflection from a variable rounded sample, like a piece of fruit, results in a complicated spectrum requiring interpretation models to extract quantitative information.

Spectra for peeled versus unpeeled ripe avocados and mangoes also 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 (Figure 2).

Similar effects were observed for peeled and unpeeled mangoes, although not as pronounced. This suggests that different fruit peels have different properties that affect the overall fruit spectrum either through chemical composition or reflection properties.

Conclusions

NIR spectroscopy is a powerful measurement tool for the characterisation of agricultural samples. In the case of fruit, long NIR wavelengths, where absorption is weak, allow sampling through the peel of the fruit. 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.

 

Contact

www.oceanoptics.com

info@oceanoptics.com

NL: +31-26-3190500

UK: +44-1865-811118

References

Near-infrared Spectroscopy in Food Analysis, Brian G. Osborne, Encyclopedia of Analytical Chemistry, 1986.

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