Sept. 11, 2020
Sept. 1, 2020
Consumers expect that the fruits and vegetables they buy are of the highest quality. Therefore, more in-depth quality control and sorting systems are increasingly being used to ensure that supplies reaching retailers meet the required standards. Most fruits and vegetables today are still sorted mostly on the basis of external features such as color, size, weight, and blemishes, but consistently meeting quality control demands is possible only when internal parameters are also examined.
Figure 1: Infrared is 40 times greater than the visible spectrum, Digital Earth Watch. (Image credits: https://sites.google.com/a/globalsystemsscience.org/digital-earth-watch/key-messages/near-infrared-and-the-electromagnetic-spectrum)
Light is made up of wavelengths. The visible range that the human eye can see (VIS; 400–700 nm) is only a small part of it; see Figure 1. To sort and control food quality, many parts of the infrared range are also used, including the near-infrared range (NIR; 700–1400 nm) and short wave infrared (SWIR; 1400–3000 nm).
Initially, spectroscopy based on the visible range was used for in-line sorting units, especially to estimate the color of fruits, as several of the pigments react to light in the visible range.
The infrared spectrum was used by biochemists to test organic compounds, and they were able to show images and characteristics that were not recorded by visible spectrum camera.
The advantage of using the NIR range is that this spectrum’s absorption is associated with the vibration of hydrogen bonds formed with other elements. Hence, they are suitable to identify and quantify biocompounds.
The NIR wavelengths are useful not only for prepared samples, but also for intact products because they can travel into the substances up to a few millimeters to centimeters deep; whereas, wavelengths over 2500 nm have an effective pathway of only micrometers. Since most of SWIR is within this range, they also have longer pathways into intact produce.
NIRs can be used in combination with the VIS or SWIR spectrum. SWIR spectrometers are as good as or more precise than VIS-NIR, but they are far more expensive and give fewer data points. So, VIS-NIR spectrometers are the preferred option.
Though spectroscopy and chemometrics have been worked out for a wide range of parameters, some issues remain that have to be fixed. Some factors that have to be considered in the use of in-line spectroscopy tools are as follows:
The combination of chemometrics and NIR spectroscopy is used to determine the quality and quantity of many internal parameters, such as total soluble sugars, dry matter, characteristic carotenoids, acidity, internal color, internal defects like browning, bruising, rots, stone cracking, and bitter pits. These parameters are widely used to fix harvest time and monitor quality throughout the supply chain.
However, all of them are not used during in-line sorting.
The parameters that are used for in-line commercial sorting are TSS, dry matter, internal defects, acids, and color.
The first commercial in-line tools sorted fruits according to total soluble solids (TSS). TSS remains one of the most widely used quality parameters for fruits, especially thin-skinned varieties. It is popular because it is an indicator of eating quality, as the TSS level rises as fruits and vegetables ripen.
The fresh produce where TSS can be reliably used in the decreasing order of accuracy are apple, stonefruit, mandarin, banana, melon, onion, tomato, and papaya.
These days, dry matter estimation is also gaining importance. Many supply chains are setting specifications for dry matter content at harvest time that are measured by NIR spectroscopy tools. In many cases, dry matter content at harvest is the best indicator of fully mature or ripened fruits; it is also a good predictor of final taste and eating quality of fruits. Usually, the aim is to maximize dry matter content so that packing houses can ensure their produce also meet these specifications.
According to Walsh et al. 2020, the detection of internal defects is the third most popular use of NIR spectroscopy during sorting. Changes in water core, internal composition, browning, frost damage, and moldy cores can be successfully detected by NIRS.
This parameter has varying importance. Titrable Acidity is being factored to estimate taste, as sweetness alone is not enough. However, fruits such as peaches, grapes, etc. will have a lower amount of citric acid equivalent than sour fruits, such as limes.
NIRS is good for color analysis and can provide objective measures of external and internal color; see Figure 2.
Figure 2: “Fig. 1. Absorption spectra of pigments,” Walsh et al. 2020. (Image credits: https://www.sciencedirect.com/science/article/pii/S0925521419303230)
NIR and VIS spectroscopy for in-line sorting have been available for nearly three decades.
A combination of TSS, dry matter, levels of organic acids, and skin characteristics will change the spectra within a fruit type. These parameters can be tested in-line to predict and sort fruits based on the difference in the following areas:
Often, a single NIRS tool can be used to detect more than one parameter. It is not possible to reliably estimate firmness with VIS-NIR spectroscopy.
Several sensors and probes are used in packing lines. The in-line quality assessment uses point measurement against area measurement for analysis.
Produce is checked and sorted in post-harvest at varying stages. Sorting is necessary not just for produce meant to be eaten as fresh fruit or vegetables, but also those meant for processing. For example, selecting the right grapes to make wine. If in-line monitoring is too expensive, portable tools can be used in other stages of the supply chain, where sorting is done by the farmers, retailers, or transporters to cull spoiled commodities.
Earlier VIS-NIR spectrometers were large and room-sized, but the hardware is steadily being miniaturized. With technological advances, these spectrometers were reduced to benchtop equipment, then to small palm-sized devices that can be attached easily to any part of a sorting line.
State of the art commercial spectroscopic systems can monitor fruits on a conveyor with a speed of one meter per second. They can simultaneously control multiple lanes and sort around 10 fruits per second. These systems use SWNIR spectrophotometers.
The in-line VIS-NIR tools have led to the development of small but equally powerful portable devices. For two decades now, the technology that was initially restricted post-harvest to commercial packing houses can now be used throughout the supply chain, even by small suppliers, transporters, and retailers.
A line of portable produce quality meters from Felix Instruments – Applied Food Science is based on NIR spectroscopy and can measure TSS, dry matter, titrable acidity, and external and internal color. Individual readings require only 4-5 seconds and are precise and non-destructive. The following devices can be used in sorting fresh produce in any part of the supply chain:
The last three are based on the F-750 and customized for specific fruits. All four tools are also useful to estimate harvest time on farms.
In-line VIS-NIR or SWIR-NIR systems have been in use for a long time. Developing technology increases the range of parameters they measure by fixing the issues currently holding back their wide adoption. These continuous advances are also likely to make the devices cheaper and easier to use, benefitting the stakeholders and food production in general.
Science Writer, CID Bio-Science
Ph.D. Ecology and Environmental Science, B.Sc Agriculture
Feature image courtesy of Liz West
Dixit, Y., Casado-Gavalda, M. P., Cama-Moncunill, R., Cama-Moncunill, X., Markiewicz-Keszycka, M., Cullen, P. J., & Sullivan, C. (2017). Developments and Challenges in Online NIR Spectroscopy for Meat Processing. Comprehensive Reviews in Food Science and Food Safety, 16(6), 1172-1187. doi:10.1111/1541-4337.12295
Schmilovitch, Z. (2018). Inline Application of NIR System in Produce Sorting Machines. Open Access Journal of Agricultural Research, 3(2). doi:10.23880/oajar-16000155
Walsh, K., Golic, M., & Greensill, C. (2004). Sorting of Fruit Using near Infrared Spectroscopy: Application to a Range of Fruit and Vegetables for Soluble Solids and Dry Matter Content. Journal of Near Infrared Spectroscopy, 12(3), 141-148. doi:10.1255/jnirs.419
Walsh, K. B., Blasco, J., Zude-Sasse, M., & Sun, X. (2020). Visible-NIR ‘point’ spectroscopy in postharvest fruit and vegetable assessment: The science behind three decades of commercial use. Postharvest Biology and Technology, 168, 111246. doi:10.1016/j.postharvbio.2020.111246