Fruit juice is one segment of the global non-alcoholic beverage market, which was estimated at $1.224 billion in 2023 and is expected to grow at a CAGR of 7.4% from 2024 to 2030. Increased consumer preference for healthy drinks and alternatives to alcoholic beverages is expected to increase the segment percentage of fruit juices in the global non-alcoholic market in coming years.
In the United States, the term “fruit juice” can only be legally used to label a product made of 100% fruit juice. A blend of fruit juice and other ingredients is referred to as a “juice cocktail” or “juice drink”. Labels can say “No Added Sugar” but products can have large amounts of naturally occurring sugars, which must be noted on the product label. The suffix “ade” indicates dilution with sugar or water if the natural juice is too sour, rich, or acidic to consume. Examples of this include lemonade and limeade.
Apples, oranges, cranberries, grapes, grapefruits, bayberries, grapefruits, tomatoes, and pineapples are among the fruits used to make fruit juice. The major components of fruit juice are water, sugars, and organic acids, with lesser amounts of amino acids, vitamins, and phenolic compounds. Some pure fruit juices can be blended together as well, making blend monitoring important to observe and measure to ensure proper taste and flavor.
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Sugar and acidity content are the most important constituents in fruit juice and are strictly regulated. Soluble Solids Content (SSC, expressed as °Brix), glucose, fructose, and sucrose are the most common sugar measurements. Titratable Acidity (TA) and pH are the most common acidity measurements. Improper or overly lengthy storage leads to oxidation, which can reduce nutritional value and even present potential health hazards.
The high value of many fruit juices makes them a primary target for adulteration. Common forms of fruit juice adulteration include water dilution, artificial sweetener addition, and the addition of lower quality products, including other types of fruit juice. SSC and pH tests can determine if fruit juice has been diluted with pure water. If the adulterant water is spiked with sugar and citric acid, standard methods may not detect the adulterant. New adulteration methods are always emerging, creating a need for the development of new methods for adulteration testing.
There is a need to measure and determine quality parameters at all stages of the fruit juice manufacturing process. Initial analysis of sugar and acidity parameters is required. Real-time monitoring during manufacturing offers great benefits but standard methods like HPLC are expensive, laborious, and time-consuming. They are ill-suited for process monitoring and can only measure one chemical or physical parameter of interest with a single test. A final quality check is required to ensure that fruit juices meet quality specifications, are being labeled and marketed properly, and are free of adulterants.
NIR spectroscopy offers a fast and cost-effective alternative to traditional testing methods for both quality control analysis and adulteration detection in fruit juices. Little to no sample preparation is required. Although the use of NIR spectroscopy does require the creation of chemometric models that correlate parameters of interest to NIR spectra, once models are created multiple parameters can be determined from a single measurement.
Advances in hardware and software in NIR spectroscopy have facilitated the use of it as a real-time quality control method during the manufacturing of fruit juices. In the sections below, an overview of the manufacturing of fruit juices and the use of NIR spectroscopy for quality control analysis is examined. Adulteration detection is also discussed as well as recent advances in the use of NIR spectroscopy in fruit juices quality control.
Fruit Juices Manufacturing
The first step in making fruit juice is to wash and sort the food source. The fruit is prepared by mechanically squeezing or macerating the fruit without applying heat or adding solvents. This process is often referred to as “cold-pressed”. Cold pressing is accomplished by one of two methods. The first uses two metal cups with sharp metal tubes that remove the peel of the fruit and force the flesh through the metal tubes. Small holds in the tubes allow the juice to escape and be collected. The other requires the fruit to be cut in half and the juice is extracted using reamers.
After extraction, most juices are filtered to remove fiber or pulp. One notable exception is orange juice, which can be sold pulp-free or at varying pulp levels. If the juice is to be concentrated, evaporators are used that heat the juice under a vacuum to remove water and cool it to around 13°C. About two-thirds of the water is removed during this process. Concentrated juice is easier to transport and has an increased shelf life. It can be reconstituted with water or sold directly in the concentrated state.
Pasteurization is used to inactivate enzymes and destroy any spoilage microbes. The continuous system consists of a heating zone, hold tube, and cooling zone, after which the juice is packaged. High intensity pulsed electric fields are an alternative to traditional pasteurization. Using this method results in better quality while performing the same tasks required for pasteurization.
Fruit Juices Quality Control Analysis
Sugar and acidity measurements are the most important quality control parameters in fruit juices. Glucose, fructose, and sucrose are all essential sugar measurements. SSC is one of the primary characteristics used to determine the sweetness and sensory attributes of fruit and processed fruit products. TA is directly related to organic acid contents. It is also a measure of color stability and shelf life in fruit and its processed products. Total phenolic content (TPC) is directly related to the antioxidant capacity of fruit juices.
Final product quality control analysis includes testing for adulteration and ensuring that the final product is properly marketed and labeled. In the case of juice blends, this constitutes accurately analyzing blend profiles. A final check for sugar content, acidity parameters, proper blending, and the presence of adulteration can be conducted with a single reading using NIR spectroscopy. In the sections below, various applications and studies are examined to demonstrate how NIR spectroscopy can be used to replace time-consuming and expensive traditional analytical methods.
Glucose, Fructose, and Sucrose
Glucose, fructose, and sucrose are all important sugar parameters in fruit juice for determining quality as well as for detecting adulteration or contamination. Application studies using NIR spectroscopy for measuring proven parameters often focus on different sample methods and simplifying the process of creating chemometric models. One study used NIR spectra collected from different concentrations of stock solutions of glucose, fructose, and sucrose to see if the models could be used to predict these parameters in different kinds of fruit juices.
NIR spectra of stock solutions were collected using transmittance (light passing through the liquid sample), tranflectance (a probe with a gap is inserted into the liquid with the light passing through and reflecting off the bottom of the gap, doubling the pathlength the light passed through), and reflectance (liquid placed on a reflective surface). Chemometric models were created correlating each sugar parameter to the NIR spectra. High correlation was obtained for the transmittance and transflectance models.
Models for the three sugar parameters were validated by collecting NIR spectra of commercial samples of apple and orange juice. Spectra were collected after unsealing the sample, one week later, and after spiking samples with additional glucose, fructose, and sucrose. Prediction results using the chemometric models were accurate after comparison of results using High Performance Anion-Exchange Chromatography. The study proved that chemometric models created using NIR spectra of stock solutions of glucose, fructose, and sucrose could be used to predict these parameters from the NIR spectra of different types of commercial fruit juice.
A more specific study used bayberry juice to examine the feasibility of using NIR spectroscopy to measure glucose, fructose, and sucrose. Bayberry juice is cultivated in Southeast China and is processed into many forms, such as sweets, jams, juice, wine, and canned syrup. It is known for its health benefits and especially for treating gastrointestinal issues.
Samples were collected from various bayberry species for the study. Standard procedures were followed to collect NIR spectra of samples, perform reference tests for glucose, fructose, and sucrose using HPLC, and creation of calibration models to correlate the NIR spectra to the sugar parameters. Model statistics showed strong correlation. Validation prediction results were accurate, proving the feasibility of the application and models.
SSC, pH, and TA
SSC and TA are two important taste parameters in fruit juices. The SSC/TA ratio is related to overall taste and is used as an index of sensory acceptability of fruit taste. Apple juice was used to examine the feasibility of measuring these parameters using NIR spectroscopy. Different types of apple juice from different producers were used to incorporate variation. Samples also included both clear and cloudy juices reconstituted from concentrated form, direct juices that were pasteurized, and freshly squeezed juices.
Standard procedures were followed for collecting NIR spectra and reference values for the samples. Chemometric models showed good correlation between the reference values and predicted values obtained from the NIR spectra. Predictive ability was lower for TA compared to SSC, but this was because of a smaller range of reference values, smaller concentration, and lower spectral sensitivity of acids. Results should improve using individual models for the different types of apple juices.
Orange juice is one of the most important and highly consumed fruit juices. SSC expressed as °Brix and pH are two essential chemical parameters. Acids are important sources of nutrition and freshness. These include citric, tartaric, and malic acids. pH is important for variation of color, microbial control, taste, and authentication of food.
NIR spectroscopy is a valid method for measuring SSC and pH in orange juice. One study examined measuring these parameters in eight commercially available brands of orange juice. Samples were procured and some samples were diluted using water to change the SSC and pH values. After collection of NIR spectra and testing for reference values using standard methods, calibration models were created to correlate the spectral data to SSC and pH. Correlation was excellent and prediction results proved the validity of the models.
Quality Assessment and Product ID
NIR spectroscopy can be used for different types of quality assessment in fruit juices. Examples include authenticity determination, quality assessment in terms of oxidation and reduced shelf-life, pure vs. synthetic, and adulteration detection, identification, and quantification. The paragraphs below provide an overview of some applications for assessing quality in fruit juices using NIR spectroscopy.
Tomatoes are the second most consumed vegetable in the world. Tomato juice is rich in organic acids, sugars, vitamins, and natural pigments. It is very high in Vitamin C concentration. Vitamin C is easily oxidized with exposure to air, which reduces the nutritional components in juice. NIR spectroscopy can be used as a classification method to classify between fresh tomato juice and tomato juice that has been shelved.
One hundred fully ripened tomatoes were squeezed and centrifuged to make fresh tomato juice. Half the juice was used to make samples for immediate scanning with an NIR spectrometer. The remaining half was stored for a month in airtight bottles and refrigerated. After a month, the other samples were scanned using the same NIR spectrometer. Reference tests for SSC and pH were performed on all samples and the results showed that those parameters changed in the samples that were stored for a month.
The NIR spectra of all samples and a classification algorithm were used to examine the validity of classifying whether a sample was fresh or stored for a month from the NIR spectra. Modeling statistics showed that the classification was accurate and a validation sample set (NIR spectra originally collected for both sets but not used in the classification model) was correctly classified 100% of time. The results prove the feasibility of using NIR spectroscopy as a tool to examine and control the quality change of tomato juice during storage.
Blueberry juice is valuable and popular for its flavor, potential health benefits, and strong antioxidant properties. Identification of different varieties as well as determination of purity can be a complex and diverse process. Blueberry juice has no additives present while blueberry beverage or cocktail has additives present.
NIR spectroscopy can be used to classify pure blueberry juice and different types of blueberry beverage. In one study, NIR spectra of one variety of pure blueberry juice and three different varieties of blueberry beverage were used to build a classification model for classifying the four varieties. One hundred samples were used to build the classification model and forty samples were used as a validation set.
After collection of NIR spectra and application of various data preprocessing methods, a neural network classification algorithm was constructed using the processed spectra. The forty sample (ten samples of each variety) validation set was used with the algorithm for classification of the samples and 100% classification accuracy was achieved, proving the feasibility of the application.
Adulteration
Adulteration is a major problem in the food and beverage industry. New adulteration methods are always emerging, requiring the need for new detection methods as well. Adulteration of some chemical and physical parameters of interest are difficult to detect. One example of this is carbohydrates. There are a variety of commercially available sweeteners that match the concentration profile of major carbohydrates.
In some applications, NIR spectroscopy can be even more effective and accurate than traditional reference methods. One example of this is melamine adulteration in pet food and baby formula. Melamine is a chemical that mimics protein in the standard Kjeldahl testing method because of its high nitrogen content. Melamine cannot be distinguished from protein in traditional tests because the test is for nitrogen and not the actual protein. Some high-profile incidents in China involving melamine adulteration in both pet food and baby formula have led to research for detecting melamine in consumable products. Studies for various animal feed and dairy products have proven the feasibility to use NIR spectroscopy for detecting the presence of melamine, even at very low concentrations. While the threshold of detection of NIR spectroscopy is below these low concentrations, calibration models for melamine concentration were obtained and it is likely the presence of melamine is causing other chemical changes in the product which can be detected by NIR spectroscopy. Indirect correlations are acceptable but require extensive work to ensure that the correlation is valid before being applied in a real-time setting.
Likewise, NIR spectroscopy can detect saccharin adulteration in fruit juices when standard tests may not be able to detect it. One study examined spiking samples of six commercial fruit juices with varying amounts of saccharin. After NIR spectra were collected for all samples, two different types of chemometric models were created. The first was a classification model to detect when saccharin was present. The other quantified the amount of saccharin in a sample. Both types of models showed good correlation and accurate prediction results. The results are considered especially good considering that different types of fruit juices were used, showing the potential for creating a universal model for saccharin adulteration detection in many types of fruit juices.
Lime juice is a fruit juice that is in high demand for both direct consumption and as a cooking supplement. One potential type of adulteration in lime juice and other types of fruit juice is the use of synthetic products that can potentially result in health hazards for the consumer. NIR spectroscopy was examined for the purpose of classifying natural lime juice from synthetic lime juice. Samples of natural lime juice were created from fresh lime juice using a juicer machine and filtration. Synthetic lime juice refers to a liquid that replicates the taste and acidity of fresh lime juice but is not made from fresh limes. It is made from artificial ingredients like citric acid, malic acid, and tartaric acid. Salt is sometimes added to enhance flavor profile. Sample of synthetic lime juice were procured from a market for the study.
All samples were subjected to quality assessment by standard methods before the collection of NIR spectra. After NIR spectra collection, various pre-processing methods and classification algorithms were applied to the spectral data. The best results came from an advanced data modeling algorithm that analyzes specific features in the data for deviation reduction and then uses selective areas for classification analysis. Results using this algorithm classified the samples at a 97% accuracy rate, proving the feasibility of using NIR spectroscopy to classify natural and synthetic lime juice.
Process Analytical Technology (PAT)
Process Analytical Technology (PAT) was first introduced by the FDA for the pharmaceutical industry but has proven to be effective as a modeling and control strategy for the food industry. There is vast potential to benefit fruit juice manufacturing and quality control processes by using the principles of PAT to ensure quality.
Inherent advantages of implementing PAT into fruit juice analysis include controlled and optimized utilization of raw materials, reduction in variation of the final product, waste reduction, minimization of process cycle time, and the replacement of slow, costly, and ineffective laboratory testing methods with newer and more reliable sensor technologies, such as NIR spectroscopy.
On-Line Analysis
While the feasibility of measuring fruit juice quality control parameters has been proved in both academic studies and real industrial applications, there are inherent challenges to using NIR spectroscopy as an on-line process control tool. Off-line analysis is easily attainable but does require the transfer of a sample to the instrument. While still much faster and more effective than traditional methods, laboratory instruments are not suitable for real-time analysis.
At-line analysis involves the placement of an instrument in a manufacturing environment and using a sampling system to pull a sample from the process to the instrument. Such methods are also effective but still do not provide real-time feedback and analysis to show both changes in sample parameters and differences in the homogeneity of samples in a process.
On-line analysis involves a sensor being placed either into or above the manufacturing process to provide real-time feedback for the parameters of interest. The nature of and changing physical characteristics of the components of fruit juice can make the hardware needed for monitoring very challenging. This is especially true before and during the juice filtration process, where the juice may not be porous enough to allow light to pass through a sample (transmittance) nor thick enough to allow light to reflect off it (reflectance). Mixed results from some studies for turbidity and viscosity in fruit juice have emphasized the inherent difficulties in sampling fruit juice for analysis at certain stages of the manufacturing process.
Advances in hardware, fiber optics, transflectance probes, diffuse reflectance mechanisms, and cleaning mechanisms have greatly contributed to the potential for using NIR spectroscopy as a real-time process control and monitoring tool. Software advances and the use of cloud-based systems have also contributed to the use of NIR spectroscopy as a tool for manufacturing monitoring.
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Recent Advances
Recent work on the use of NIR spectroscopy in fruit juices analysis has focused on in-line monitoring for optimization of flash pasteurization, measuring phenolic content, and using advanced machine learning algorithms and NIR spectra for adulteration detection. Optimization of flash pasteurization would be hugely beneficial to the fruit juice industry. Phenolic content is directly related to the oxidative stability of fruit juices. The evolving nature of adulteration requires constant research and discovery of new methods to detect it.
An excellent example of how fruit juices analysis can be used in a manufacturing environment was shown in a recent study that analyzed the in-line classification and characterization of seven fruit juice varieties using NIR spectroscopy. The purpose was to examine the potential for optimizing the flash pasteurization of not only fruit juices, but liquid foods in general.
Thermal pasteurization of fruit juices is challenging to manufacturers as a balance must be achieved between microbiological stability and sensory and nutritional quality. The thermal effect required to prevent spoilage by microorganisms is expressed in pasteurization units (PU). In simple terms, insufficient PU may leave the juice subject to spoilage while excessive PU may result in a reduction in quality.
While models and formulas do exist for PU calculation, any change in the quality parameters requires a change in the formula and obtaining the necessary feedback to make real-time adjustments is difficult using traditional analytical methods. NIR spectroscopy was examined for the purpose of classifying and analyzing quality control parameters in fruit juices to optimize PU in flash pasteurization.
NIR spectra were collected using an in-line probe of seven different types of fruit juice. Standard reference tests were performed for the following parameters of interest: Brix, pH, turbidity, and viscosity. Chemometric analysis showed that all seven types of fruit juices could be classified from the NIR spectra. Quantitative models showed that prediction results for Brix and pH were accurate enough to provide real-time feedback for practical process optimization and adjustment of optimal PU units for flash pasteurization.
This study is an excellent example of how technology has helped NIR spectroscopy evolve from laboratory use to a process control tool. Although the applications of fruit juice classification and quantitative analysis of parameters of interest have been proven many times before, this particular application demonstrates the potential of the vast benefits that can be achieved by optimization of flash pasteurization using NIR spectroscopy.
Soluble Solids Content (SSC) is a proven parameter for measurement using NIR spectroscopy. One important parameter which has not been extensively examined for spectroscopic analysis is Total Phenolic Content (TPC) in fruit juices. TPC is directly related to the antioxidant capacity of juices, which is of paramount importance for both health benefits and shelf-life.
A recent study examined the feasibility of measuring SSC and TPC in both strawberry juice and whole strawberries. Standard procedures were used for collection of NIR spectra of both juice and fruit, obtaining reference values for SSC and TPC, and chemometric analysis to correlate the NIR spectra to the parameters of interest. Results showed that both SSC and TPC could be accurately predicted in strawberry juice and fruit from the NIR spectra and calibration models.
The evolving nature of adulteration requires methods for the detection of adulteration in fruit juice to evolve as well. One common method of adulteration is to add a cheaper juice to a more expensive one. A recent study examined the feasibility of using NIR spectroscopy to detect grape juice adulterant in apple, pineapple, and orange juices. Grape juice was added to each of the three juices at 5% intervals up to 50% adulterant concentration.
NIR spectra were collected for all samples and after various pre-processing algorithms were applied to the spectral data, different machine learning tools and algorithms were used to develop predictive models for juice quality control. The best results showed a predictive capability of nearly 98% for detection of grape juice adulterant in apple, pineapple, and orange juices. Advances in model development have facilitated such analysis, including the ability to further upgrade models by adding more samples and data to them, resulting in more accurate and robust predictions.
Galaxy Scientific
Galaxy Scientific is an industry pioneer in the use of optical Near Infrared Spectroscopy. Our QuasirIRTM family of NIR spectrometers uses Fourier Transform Near-Infrared (FT-NIR) technology for laboratory, field, and process applications.Our passion is innovation and our mission is to develop uniquely robust NIR instruments to solve critical analytical problems in numerous sectors, including butter manufacturing.
For more information about Galaxy Scientific and to contact one of our applications specialists, please visit our website at Galaxy Scientific Inc.
For more detailed discussion on the topics covered in this article, including advanced statistics, overview of the fruit juices manufacturing process, and a review of applications studies for fruit juices analysis using NIR spectroscopy, please visit the following sections on the Galaxy Scientific NIR spectroscopy for food analysis website:
Non-Alcoholic Beverages - NIR-For-Food
Fruit Juices Overview - NIR-For-Food
Fruit Juices Analysis - NIR-For-Food
Non-Alcoholic Beverages Adulterant Analysis - NIR-For-Food
- Rapid Analysis of Sugars in Fruit Juices by FT-NIR Spectroscopy—Rodriguez-Saona, Fry, McLaughlin, Calvey, Carbohydrate Research 336 (2001) 63–74. https://www.sciencedirect.com/science/article/abs/pii/S0008621501002440
- Quantification of Glucose, Sucrose, and Fructose in Bayberry Juice—Xie, Ye, Liu, Ying, Food Chemistry 114 (2009) 1135-1140. https://www.sciencedirect.com/science/article/abs/pii/S0308814608012958
- Evaluation of Quality Parameters of Apple Juices Using Near-Infrared Spectroscopy and Chemometrics—Wlodarska, Khmelinskii, Sikorska, Hindawi Journal of Spectroscopy, Volume 2018 Article ID 5191283. https://www.hindawi.com/journals/jspec/2018/5191283/58
- Use of Near-Infrared Spectroscopy and Least-Squares Support Vector Machine to Determine Quality Change of Tomato Juice—Xie, Ying, Journal of Zhejiang University Science B, 2009, 10(6):465-471. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2689559/
- Measurement of Soluble Solids Contents and pH in Orange Juice Using Chemometrics and Vis-NIRS—Cen, He, Huang, Journal of Agricultural and Food Chemistry, 2006, 54, 7437-7443. https://pubs.acs.org/doi/abs/10.1021/jf061689f
- Identification of Blueberry Beverage Using VIS/NIR Spectroscopy—Li, Wu, Ma, et al., MATEC Web of Conferences 139, 00050 (2017). https://www.researchgate.net/publication/321536402_Identification_of_Blueberry_Beverage_Using_VisNIR_Spectroscopy
- Applications of FT-NIRS Combined With PLS Multivariate Methods For the Detection & Quantification of Saccharin Adulteration in Commercial Fruit Juices—Mabood, Hussain, Jabeen, Food Additives and Contaminants: Part A, 2018, Vol. 35, No. 6, 1052-1060. https://tandfonline.com/doi/abs/10.1080/19440049.2018.1457802?
- Combined Data Mining/NIR Spectroscopy for Purity Assessment of Lime Juice—Shafiee, Minaei, Infrared Physics and Technology 91 (2018) 193-199. https://www.sciencedirect.com/science/article/abs/pii/S135044951730662X
This information has been sourced, reviewed and adapted from materials provided by Galaxy Scientific Inc.
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