Recent approaches for the quantitative analysis of functional
oligosaccharides used in the food industry: A review

UREAP Report
Summer 2020

Name: Karizza Catenza
Supervisor: Dr. Kingsley Donkor
Date of Project: May – August 2020
Date of Submission: August 28, 2020

Highlights
•
•
•
•

Quantitative analysis developed for the determination of functional oligosaccharides in
food matrices are discussed (2015 – 2020).
Structural properties of different oligosaccharides are highlighted.
Sample preparation techniques for specific oligosaccharides and sample matrices are
reviewed.
Applications of functional OS in food products are generalized.

Abstract
Functional oligosaccharides (OS) are diverse groups of carbohydrates that confer several health
benefits stemming from their prebiotic activity. Commonly used oligosaccharides,
fructooligosaccharides and galactooligosaccharides, are used in a wide range of applications
from food ingredients to mimic the prebiotic activity of human milk oligosaccharides (HMOs)
in infant formula to sugar and fat replacers in dairy and bakery products. However, while
consumption of these compounds is associated with several positive health effects, increased
consumption can cause intestinal discomfort and aggravation of intestinal bowel syndrome
symptoms. Hence, it is essential to develop rapid and reliable techniques to quantify OS for
quality control and proper assessment of their functionality in food and food products. The
present review will focus on recent analytical techniques used for the quantification of OS in
different matrices such as food and beverage products.

1

Introduction
Functional oligosaccharides (OS) are diverse groups of carbohydrates consisting of monomers
present in varying degrees of polymerization (DP) ranging between 3 to 10 units (Ibrahim,
2018). Currently, fructooligosaccharides (FOS) and galactooligosaccharides (GOS) are the
most utilized functional OS in the food industry, however other OS groups such as agroresidue derived xylooligosaccharides (XOS), and pectic oligosaccharides are also being
considered due to their relatively inexpensive production cost (Babbar et al., 2015; Moreno et
al., 2017; Samanta et al., 2015). Technological properties of OS, such as gel-forming ability,
water holding capacity, and thickening ability can improve sensory and physicochemical
characteristics of food products hence, leading to increased application of OS in the food
industry (Balthazar et al., 2017, 2015; Farias et al., 2019). They are commonly used as a partial
replacement for fat and sugar, and as bulking agents in dairy and bakery products; they are
also incorporated as food fortifying agents in various food products such as infant formulas,
ice cream, cereal products, etc., to improve their nutritional functionality (Ibrahim, 2018;
Nobre et al., 2015; Zhao et al., 2017).
The study of functional OS has been a growing field of interest in both the food and
pharmaceutical industry mainly due to their activity as prebiotics – commonly defined as
“non-digestible compounds that beneficially affect the host by selectively stimulating the
growth and activity of one or a limited number of bacteria in the colon” (Cezar et al., 2017;
Samanta et al., 2015; R. D. Singh et al., 2015; Vandenplas et al., 2015). Selective promotion
of the growth of Bifidobacteria spp. and Lactobacillus spp. by prebiotics allows the liberation
of metabolites such as short-chain fatty acids (acetate, propionate, butyrate, lactate, etc.) which
are associated with reduced risk of hypercholesterolemia (Bali et al., 2015), and control of
several physiological processes such as mucosal proliferation, inflammation, colorectal
carcinogenesis, mineral absorption and elimination of nitrogen compounds (Flores-Maltos et
al., 2016). Furthermore, several studies have reported a positive effect of consumption of
prebiotic OS with increased absorption of Ca, Mg, and Fe, and against diseases such as
cardiovascular disease, cancer, obesity, and type 2 diabetes (Bali et al., 2015; Gómez et al.,
2016; Sánchez-Martínez et al., 2020; R. D. Singh et al., 2015; Zhao et al., 2017). Toxicity
studies of FOS and GOS have shown that consumption of up to 9 g/kg body weight and 2g/kg
body weight per day for FOS and GOS, respectively, had no adverse effects in Wister rats
(Jain et al., 2019; Y. Zhou et al., 2017). However, several studies have been published on the
association of increased consumption of OS, specifically FOS, with aggravation of irritable
bowel syndrome symptoms (Charoenwongpaiboon et al., 2019; B. Chen et al., 2017;
Huazano-garcía & López, 2017; Mellado-Mojica et al., 2016). Consumption of FOS of
greater than 15 g/day was reported to cause intestinal discomfort, bloating, and flatulence
(Kumar et al., 2018). Hence, the development of rapid and sensitive techniques for
quantitation of functional OS, along with their increasing application in the food industry, is
warranted. In this review, recently developed techniques over the last five years for the
quantitative determination of functional OS in different food matrices will be discussed.

2

Analysis of Oligosaccharides

2.1

Fructooligosaccharides
Fructooligosaccharides (FOS) are composed of fructosyl units linked together via β(2 – 1) or
β(2 – 6) glycosidic bonds with a glucose residue linked via α(1 – 2) glycosidic bond at the
reducing end; commonly used FOS in fortified food products are 1-kestose (GF2), nystose
(GF3), and fructofuranosyl nystose (GF4) (S. P. Singh et al., 2017; Vega & Zuniga-Hansen,
2015). FOS are naturally present as reserve phytochemicals in a variety of plants such as
Jerusalem artichoke, bananas, tomatoes, onion, asparagus, chicory, leek, garlic, asparagus,
wheat, honey, and yacon (Caetano et al., 2016; Flores-Maltos et al., 2016) with the highest
concentrations reported in Jerusalem artichoke, chicory, and yacon (Caetano et al., 2016; Guo
et al., 2016).
Currently, high-performance liquid chromatography (HPLC) methods often coupled with
refractive index detector (RID) and evaporative light scattering detector (ELSD) are
commonly used for the routine analysis of OS in food products and for monitoring OS
synthesis (Bersaneti et al., 2017; Ko et al., 2019; Prokopov et al., 2018; Trollope et al., 2015;
Vega & Zuniga-Hansen, 2015; Weiß & Alt, 2017). In a study conducted by dos Santos Lima
et al. (2019), FOS present in wine and grape juices such as GF2, GF3, and raffinose was
quantified using reversed-phase HPLC-RID. A RP-C18 column with polar endcapping was
used to provide better separation and stability for highly polar compounds such as
oligosaccharides. Before injection, wine samples were diluted with ultra-pure water and then
filtered through a 0.45µm PTFE membrane. The method showed high specificity with
minimal interference from common refraction detection interferences such as sugar, ethanol,
and organic acids. Also, the method provided good linearity, recovery (GF2: 90.3% and GF3:
108.8), and sensitivity with LOD values 0.090 g/L (GF2) and 0.074 g/L (GF3), hence is a
promising method for the routine detection of FOS in wine and grape juices. In another study,
a simplified sample treatment of milk and milk-related products before the detection of FOS
using HPLC-RID was developed and evaluated (Rodríguez-Gómez et al., 2015). A
precipitating solution (495 mM zinc acetate dihydrate, 18 mM phosphotungstic hydrate, and
5.8% (v/v) glacial acetic acid) was added into homogenized samples in a 5:1
sample/precipitation solution ratio resulting in the precipitation of protein and fat. The results
of the analysis demonstrated high precision (%RSD < 3.5%) and high sensitivity with LOD
values of 0.5, 0.4, and 0.6 µg/mL for GF2, GF3, and GF4, respectively. Hence, the sensitivity
of the method coupled with short analysis time (< 20 min) makes it a suitable technique for
the routine analysis of common FOS in milk and milk products.
However, RID can be susceptible to baseline drift because of temperature variation and
gradient elution. Subsequently, detection by ELSD provides better sensitivity characterized
by great baseline stability due to gradient elution compatibility and temperature independence
(Costa & Conte-Junior, 2018; Duan et al., 2018; Zhuang et al., 2019). Zhuang et al. (2019)
developed a technique for simultaneous quantification of FOS (DP 3-15) present in
Atractylodis rhizome using HPLC-ELSD. Due to a lack of available standards, the authors
used FOS standards that were extracted and purified in their laboratory. A reflux extraction
method using 60% ethanol optimized at a 20 fold solvent to sample ratio for 2.5 h was

employed. Results showed excellent linearity (R2 > 0.9993) for all FOS of interest, as well as
high sensitivity with reported LOD values ranging from 0.04 – 0.14 mg/mL. Simultaneous
quantification of 13 FOS in Morinda officinalis was also published in another study using
UHPLC-ELSD using am ethylene-bridged hybrid (BEH) amide column with gradient elution
(Hao et al., 2019). The authors demonstrated that using a weakly basic (pH < 12) mobile phase
improves analyte separation by reducing peak tailing, increasing peak resolution, maintaining
a neutral charge on the analytes, and eliminating co-elution of salts. The method was validated
and presents several advantages in that it is rapid (< 10 min), sensitive (LOD: 10.78-33.44
µg/mL; LOQ: 35.94-124.81 µg/mL), and precise (%RSD < 4.76).
High-performance anion-exchange chromatography with pulsed amperometric detection
(HPAEC-PAD) was also used for the routine analysis of FOS (Charoenwongpaiboon et al.,
2019; Huazano-garcía & López, 2017; Mellado-Mojica et al., 2016; Menéndez et al., 2019;
Porras-domínguez et al., 2017). Pöhnl et al. (2017) compared the performance of HPAECPAD and UHPLC-ELSD for the determination of FOS in Allium cepa (onion). Results of the
study showed that HPAEC-PAD was superior to UHPLC-ELSD in that it has better sensitivity,
a wider range of quantifiable FOS (up to DP of 18) and was able to baseline separate
constitutional isomers. Also, the UHPLC-ELSD method was limited by the solubility of
higher molecular weight FOS in organic solvents, while solubility issues are insignificant with
HPAEC-PAD. These results were in agreement with another study for the detection of FOS
in milk and milk products (Rodríguez-Gómez et al., 2015). However, UHPLC-ELSD still
presents suitable results for low to medium molecular weight FOS analysis with shorter run
time compared to HPAEC-PAD; hence, it could still be applied for routine analysis in the food
industry.
Other cited methods for FOS analysis include gas-liquid chromatography mass spectrometry
(GLC-MS), high-performance capillary electrophoresis with laser-induced fluorescence
detection (HPCE-LIFD), and matrix-assisted laser desorption ionization time of flight mass
spectrometry (MALDI-TOF MS) (Rodríguez-Gómez et al., 2015; Zhao et al., 2017) however,
recent studies focused on the evaluation, and further development of these methods were not
available.
2.2

Galactooligosaccharides
Galactooligosaccharides are carbohydrates that are commonly composed of two to five
galactose units linked via various glycosidic bonds (i.e. β(1 – 2), β(1 – 3), β(1 – 4), β(1 – 6))
with an N-glucose residue at the end forming a lactose terminal within the molecule (Azcarateperil et al., 2016; Figueroa-Lozano et al., 2020; Solaiman et al., 2020). GOSs are found
naturally in foods like banana, artichoke, onion, garlic, and honey; however, industrial GOS
are commonly derived from industrial by-products (i.e. cheese whey and whey permeate)
through the enzymatic transgalactosylation of lactose by β-galactosidase (EC 3.2.1.23)
(Aburto et al., 2018; Chanalia et al., 2018; Rad et al., 2018; Vera et al., 2016). While they are
structurally less complex, GOSs are reported to have similar structure and function with
human milk oligosaccharides (HMO) hence they are commonly used to mimic the function of
HMO in infant formulas and dairy products (Aburto et al., 2018; X. Y. Chen & Michael, 2017).

Recent studies on GOS were focused on their synthesis, purification and production (Chanalia
et al., 2018; Sabater et al., 2019; G. Wang et al., 2020) while quantitation studies have been
limited. Currently, the AOAC 2001.02 method is the only validated method for the
determination of GOS in raw materials and food products (Blanco-morales et al., 2018;
Kaczynski et al., 2019; Lans et al., 2018). This method describes an indirect measurement of
GOS by enzymatic hydrolysis of GOS to glucose and galactose, which are then quantified
using HPAEC-PAD (X. Wang & Rastall, 2018). However, the presence of high levels of free
lactose in the sample matrix dramatically reduces the accuracy of the method; thus, it is not
suitable for GOS analysis in high-lactose products (Gill et al., 2016; Yang & Xu, 2018).
Subsequently, this method was improved by Lin et al. (2018). Galactose and glucose were
measured in the same chromatographic run, thus eliminating the need to determine a
correction factor required in the AOAC 2001.02 method. Also, the degree of conversion of
lactose was taken into consideration and applied to the formula for calculating GOS content.
However, while this method was validated for GOS raw materials, further evaluation is
required for its suitability in GOS analysis in high lactose food products.
Quantification of GOS by gas chromatography – flame ionization detector (GC-FID) in infant
formula was reported (Sabater et al., 2016). Prior to analysis, GOS samples were derivatized
to trimethyl silylated oximes (TMSO). Furthermore, the authors demonstrated that the
hydrolysis of maltodextrins with α-amyloglucosidase reduced interferences and improved
peak resolution of GOS peaks, thus allowing quantification. This method showed good
repeatability (%RSD < 12.3%) and allowed the quantification of GOS with a degree of
polymerization (DP) up to 7. The same method was recently used to analyze the composition
of the reaction mixture from the synthesis of GOS by propionibacteria from lactose and
lactulose alongside HPLC-RID (Sabater et al., 2019). For HPLC-RID, GOS were quantified
through an external calibration method using universal standards (i.e. raffinose for
trisaccharides and stachyose for tetrasaccharides), and their concentration was expressed as
the percentage of the total carbohydrate content. Hence, the previous methods presented
several advantages over the AOAC 2001.02 method in that GOSs were quantified without
prior hydrolyzation to glucose and galactose, thus simplifying GOS content calculation and
minimizing lactose interference. However, quantitation was not the primary aim of these
studies; hence these methods were not validated.

2.3

Milk Oligosaccharides
Milk oligosaccharides (MOS) are a group of carbohydrates composed of monomers glucose,
galactose, N-acetylglucosamine, fucose, sialic acid, and N-acetylneuraminic acid with a
fructose residue at the reducing end (Grabarics et al., 2017; Wei et al., 2018). Milk
oligosaccharides (MOS), especially those from human milk, are novel bioactives associated
with several physiological processes, including modulation of the gut microbiota, immune
regulation, and anti-pathogenic response in the gastrointestinal tract (Grabarics et al., 2017;
Walsh et al., 2020). Efforts have been placed into mimicking the composition of human milk
oligosaccharides (HMOs) through the addition of FOS and GOS into infant formulas (Ma et
al., 2019; Vandenplas et al., 2018) however, Walsh et al. (2020) recognized that these efforts
alone are insufficient in simulating the health benefits gained from actual human MOS. Hence,
to facilitate a better understanding of the effects of HMOs in infant health, and to properly

develop methods for synthesis of HMOs, various techniques for the accurate quantitation of
HMOs have been developed (Grabarics et al., 2017; Yan et al., 2017).
Simultaneous quantification of 16 acidic and neutral HMOs was achieved by Tonon et al.
(2019) using graphitized carbon liquid chromatography-electrospray ionization mass
spectrometry (GCLC-EIMS) with simple sample preparation. Briefly, centrifugation and
ultra-filtration were applied for the removal of lipids and proteins, respectively, and followed
by a reduction reaction to prevent the separation of anomers in the porous graphitized carbon
phase. The method showed promising results with excellent linearity (R 2 > 0.9999), high
sensitivity (LOQ = 0.039), and suitable recovery (89-110%). Also, the reported method
presents a couple of advantages in that it was able to extract and quantify both neutral and
acidic HMOs simultaneously. Furthermore, the simultaneous extraction and analysis of
HMOs in the same chromatographic run minimized the loss of HMOs due to lactose
precipitation and provided higher recovery values (89-110%) compared to another study using
graphitized-carbon solid phase extraction (GC-SPE) (19.5-20%) (Robinson et al., 2018).
Absolute quantitation HMOs were also reported by Xu et al. (2016) using ultraperformance
liquid chromatography tandem triple quadrupole mass spectrometry (UPLC-QqQMS) under
multiple reaction monitoring (MRM). The study also evaluated the feasibility of utilizing
pooled human milk samples for the construction of calibration standards. Briefly, pooled milk
samples were defatted and deproteinated by centrifugation and ethanol extraction, respectively.
Half of the extracted samples were serially diluted and injected into the system, and the total
response of HMOs in each diluted pool was determined by summing the peak areas of all of
the transitions. The other half was cleaned by PGC-SPE, lyophilized, and weighed to calculate
the concentration of HMOs in each diluted pool. Absolute concentrations of total, sialylated,
fucosylated and non-fucosylated neutral HMOs were determined using the universal
calibration curve constructed from pooled milk samples. The validity of the method was
evaluated using commercially available HMO standards and showed suitable results in terms
of sensitivity (LOD: 0.6 – 6.8 fmol) and linearity (R2 > 0.99). The same method was applied
by Zhang et al. (2019) for the separation and quantitation of 12 HMOs in human milk. Under
MRM mode in a triple quadrupole mass spectrometer, sensitivity is enhanced by applying two
stages of mass selectivity to minimize interferences from the background matrix. The method
was able to successfully quantify and separate 12 HMOs, including four HMO isomers
without the need for intricate sample pretreatment such as lactose removal and derivatization.
The same instrumental technique was also successfully applied for the investigation of
variation in HMO concentration due to lactational changes (Ma et al., 2018), and the analysis
of major milk OS content in formulated milk powders (Ma et al., 2019).
Bovine milk oligosaccharides (BMO) are also potential alternatives for HMOs. Several BMOs
have been identified to be structurally similar to HMOs (Vicaretti et al., 2018). Sialylated milk
oligosaccharides, present in both BMOs and HMOs, were analyzed and quantified by Yan et
al. (2018) via on-line solid-phase extraction – hydrophilic interaction chromatography tandem
mass spectrometry (SPE-HILIC-MS) in mammalian milk (i.e. goat, sheep, buffalo, cow,
donkey etc.). The authors utilized a dual gradient pump system used for purification (cleanup column) and analysis (analytical column), respectively, allowing direct injection of
defatted and deproteinated samples into the system. Sialylated OSs were separated from
neutral OSs and lactose based on their electrostatic differences using a zwitterionic SPE matrix.

The technique successfully separated 30 mono- and di-sialylated HMOs and was used for
profiling of other mammalian milk. Method validations on the established conditions showed
excellent linearity (R2 > 0.99) and average recovery for 3-sialyllactose (90%) and 6sialyllactose (106%). Sialylated OS was also determined in donkey milk using a fluorescent
detector (FLD) equipped UHPLC-MS (Licitra et al., 2019) by derivatizing samples using 2AB labelling agent (Dimethylsulfoxide/acetic acid (70/30) containing 1.05M 2aminobenzamide and 3M sodium cyanoborohydride). A calibration curve (R2 > 0.999; linear
range over 0.1 – 102.4 µg/mL) for 3-SL was used for quantifying other sialylated OS present
in donkey milk. The same method was applied for the detection of significant HMOs with a
few modifications, namely 1M of 2-methylpyridine borane was used instead of sodium
cyanoborohydride, and detection was done solely by FLD (Huang et al., 2019). A HILIC
column was also used. Labelling OSs with 2-AB increased hydrophobicity and enhanced
fluorescence absorption by adding a hydrophobic fluorophore group at the reducing end.
Furthermore, direct injection into the HILIC column eliminated a clean-up step that is often
required in milk OS analyses. The technique allowed the simultaneous quantitation of major
HMOs with the use of simple sample treatment, minimal sample volume (10µL) with decent
recovery rate (88-107%), and high sensitivity (LOD < 10 pg) for neutral and acidic HMOs.
Huang et al. (2019) also noted that centrifugation is appropriate for the determination of
HMOs occurring at high levels while ultrafiltration, such as membrane separation, provided
satisfactory results for the quantitation of trace BMOs. Suitability of capillary electrophoresis
for MOS quantitation was also evaluated (Monti et al., 2015). Micellar electrokinetic
chromatography – CE (MEKC-CE) showed promising results for the quantitation of sialylated
OS in milk samples with good linearity (R2 > 0.999). However, further method validation such
as recovery studies, and LOD and LOQ determination are warranted. Also, long analysis time
(< 1 hour) and time consuming sample preparation (extraction with ethanol for 24 h and drying
with N2 at room temperature) can be regarded as main disadvantages of this technique. CE
with laser-induced fluorescent detection (LIF) is also used (Difilippo et al., 2016; Vicaretti et
al., 2018). Normally, lactose-free OS are labelled with 8-aminopyrene-1,3,6-trisulfonic acid
(APTS) to establish a linear correlation between peak area and mole concentration (Difilippo
et al., 2016). Also, this allows efficient separation and resolution of both neutral and acidic
OS with response factors independent of structure (Vicaretti et al., 2018).
Furthermore, commercially available HMOs, 2-fucosyllactose (2-FL) and 3-fucosyllactose (3FL) were detected in milk, UHT milk, yogurt, ground cereal bar and infant formula using
HPLC-RID (Christensen et al., 2020). Notable sample preparation steps include centrifugation
and ultrafiltration for the removal of lipids and proteins, respectively. The mobile phase
composition, injection volume and column temperature were optimized to improve resolution.
Limits of detection were 0.1 mg/mL for 2-FL and 0.2 mg/mL for 3-FL in whole milk, while
LOD values of 0.6 mg/mL were observed for both 2-FL and 3-FL in infant formula and a
cereal bar. The method was successfully applied for stability studies due to the high sensitivity,
excellent linearity (R2 > 0.9995) and acceptable recovery for 2-FL (88-105%) and 3-FL (94112%). Furthermore, it can also be utilized for shelf-life studies as well as quality control of
2-FL and 3-FL in other food products and is a less expensive alternative for LC-MS.

2.4

Xylooligosaccharides
Xylooligosaccharides (XOS) are derived from the hydrolysis of xylan by xylanase enzyme
and are composed of xylose units linked via β-1,4 glycosidic bonds. Depending on the source
of xylan and mode of production, the structure of XOS can vary greatly in terms of degree of
polymerization (2-10), side groups (i.e. acetyl groups, arabinofuranosyl residues, 4-O-methyl
derivative, and uronic acids.) and their substitution pattern in the xylose chain (Amorim,
Silvério, Prather, et al., 2019; de Freitas et al., 2019; Samanta et al., 2015). Apart from their
prebiotic activity, XOSs were reported to inhibit colon carcinogenesis (Aachary et al., 2015),
and exhibit anti-inflammatory, antiallergic (Nieto-domínguez et al., 2017), and antioxidant
properties (de Freitas et al., 2019). In addition, XOS presents a potential as food ingredients
due to their stability over a wide range of pH (2.5 – 8.0) and temperature (up to 100°C) as
well as their acceptable organoleptic properties and price competitiveness due to higher
bifidogenic activity compared to other prebiotics (Amorim, Silvério, Cardoso, et al., 2019;
Antov & Dordevic, 2017; de Freitas et al., 2019). Currently, much of the studies are focused
on developing a sustainable production process for XOS using lignocellulosic residues
(Amorim, Silvério, Prather, et al., 2019) such as corncobs (Boonchuay et al., 2018; H. Zhang
et al., 2017), sugarcane biomass (Avila et al., 2019; X. Zhou & Xu, 2019; X. Zhou et al., 2019),
hazelnut shells (Surek & Buyukkileci, 2017), almond shells (R. D. Singh et al., 2019), others.
Production efficiency and xylanase activity are commonly monitored by XOS determination
using HPAEC-PAD. In a study conducted by Cürten et al. (2017), a rapid automated detection
method for XOS in enzymatic hydrolyzates was developed. Optimization of column
temperature, and flow rate along with gradient elution of 200 mM sodium hydroxide solution
and 100 mM sodium hydroxide with 500 mM sodium acetate enabled sufficient elution and
separation of XOS of interest (i.e. xylobiose, xylotriose, xylotetraose, and xylopentose) within
a chromatographic run time of 10 mins. The method also demonstrated excellent linearity (R2
> 0.999) and sensitivity (LOD: 0.35 – 1.83 mg/L). Subsequently, HPAEC-PAD was applied
for stability studies of XOS in orange juice after high-intensity ultrasound processing (Silva
et al., 2020). Juice samples were diluted with ultra-pure water and filtered through a 0.22µm
PTFE syringe filter before column injection. XOSs were separated using gradient elution on
a Carbopac PA100 column, and their corresponding peaks were identified by comparing their
retention times with commercially available standards.
The application of HILIC-ELSD for the determination of XOS in enzymatic hydrolyzates was
recently proposed by Li et al. (2016). One advantage of HILIC is that highly polar samples
are separated with high selectivity using a polar organic-aqueous mobile phase and a polar
stationary phase. The authors extracted and purified XOS standards (DP 2-6) from a mixture
of XOSs using solid phase extraction, followed by semi-preparative liquid chromatography
using an HILIC column; hence demonstrating the feasibility of XOS purification using HILIC.
Increasing the column temperature to 60°C, and passing a mobile phase consisting of H2O and
acetonitrile over a diol column with weaker retention capacity, enabled complete separation
of XOS (DP 2-6) within a 20 min run time. Furthermore, method validation showed that the
technique is precise (%RSD < 4.8%), accurate (%recovery: 90.0% - 110.8%). However, this

method provided lower sensitivity (LOD: 0.1585 – 0.5259 µg/µL) compared to the HPAECPAD method that was previously discussed. A similar method was developed by (Pu et al.,
2017). A linear gradient elution of 75% - 50% acetonitrile (v/v) was applied to improve peak
resolution of short chain XOS (DP 2-4) and accelerate the elution of long chain XOS (DP >
4). The column temperature and flow rate were also modified to improve baseline separation,
and peak shape and resolution. The method was successfully applied for the simultaneous
separation and detection of non-substituted and acetylated XOS (DP 2-8) with comparable
sensitivity (LOD: 9.6 – 11.8 µg/mL) with previous studies over a 30 min run time.
Capillary electrophoresis with a photodiode array detector (CE-PDA) was also used for the
analysis of xylooligosaccharides and other wood-based oligosaccharides such as mannooligosaccharides and cellooligosaccharides (Hiltunen et al., 2016). Wood-based OSs
including diastereomers were successfully separated and analyzed using the method without
prior derivatization with the exception of cellohexose, xylotriose and xylotetraose. The
electrophoretic mobility of the analytes was adjusted using a highly concentrated background
electrolyte solution to improve peak resolution between the target analytes. However, this
increases analysis time hence presenting a drawback for this method.
Table 1
Overview of analytical methods for determination of functional oligosaccharides in different food and biological matrices.
Technique

Analytes of
Interest
FOS (DP 23)

Samples
Analyzed
Wine, and
grape juices

Sample preparation

LOD

Dilution and
filtration

HPLC-RID

FOS (DP 24)

Milk and
milk related
products

HPLCELSD

FOS (DP 315)

Atractylodis
sp. rhizome
powder

UHPLCELSD

FOS (DP 211)

Morinda
officinalis

UHPLCELSD

FOS (DP <
10)

Onions

Protein
precipitation by
zinc and tungsten
salt in acidic media
and centrifugation
20-fold reflux
extraction with
60% (v/v) ethanol,
centrifugation, and
filtration
Ultrasonic
extraction with
50% (v/v)
methanol, and
filtration
Crude onion juice
extraction,
centrifugation,
dilution, and
filtration

0.074 –
0.090
g/L
60
µg/mL

HPAECPAD

FOS (DP up
to 18)

Onions

HPAECPAD

GOS

GOS syrup
and powder

GC-FID

GOS/FOS
(DP up to 7)

Infant
formula

RP-HPLCRID

Recoveries
(%)
90.3 –
108.8

RSD
(%)
1.79 –
2.14

Remarks

References

RP-C18 column
with polar
endcapping
Luna 5u NH2
column

(dos Santos
Lima et al.,
2019)
(RodríguezGómez et
al., 2015)

~ 100

2.0 –
2.5

0.01 –
0.04
mg/mL

83.16 –
99.66

< 2.66

Amide column
in gradient
elution mode

(Zhuang et
al., 2019)

12.87 –
37.44
µg/mL

98.59 –
102.72

0.41 –
2.85

UPLC BEH
amide C18
column

(Hao et al.,
2019)

7.87 –
9.07 ng
on
column

89.5 –
102.7

1.1 –
3.9
(CV)

(Pöhnl et al.,
2017)

Crude onion juice
extraction,
centrifugation,
dilution, and
filtration
Enzymatic
hydrolysis of GOS
into glucose and
galactose

0.80 –
2.29 ng
on
column

95.3 –
107.3

1.3 –
7.4
(CV)

0.3
µg/mL

95.5 - 107

< 3.65

Protein and fat
precipitation with
Carrez reagents;

-

-

< 12.3

UPLC BEH
amide column;
baseline
separation of
isomers was not
achieved
CarboPac PA200 column;
complete
separation of
isomers
CarboPac PA-20
column; AOAC
2001.02 method
calculation was
simplified
Results are
within the range
indicated in
package labels

(Pöhnl et al.,
2017)

(Lin et al.,
2018)

(Sabater et
al., 2016)

derivatization to
TMSO
Derivatization to
TMSO

GC-FID

GOS

Reaction
hydrolyzate

GCLC-MS

Neutral and
acidic HMO

Human milk

UPLCQqQMS

Total HMO

Human milk

UPLCQqQMS

HMO

Human milk

SPEHILIC-MS

Sialylated
milk OS

Mammalian
milk

UHPLCFLD

Neutral and
acidic
HMOs

Human milk

MEKC-CE

Sialylated
OS

Mammalian
milk

CE-LIF

Neutral and
acidic OS

Cow milk

HPLC-RID

Commercial
HMO

HPAECPAD

XOS (DP 2
– 5)

Infant
formula,
whole milk,
and cereal
bar
Reaction
hydrolyzate

HILICELSD

XOS (DP 2
– 6)

Reaction
hydrolyzate

Clean-up by SPE

HPLCELSD

XOS (DP 2
– 8)

Commercial
XOS

Dilution with
ultrapure water

CE-PDA

XOS (DP 2
– 6), celloOS

Birch kraft
pulp

Hot water
extraction (100 –
160 °C)

3

Conclusion

-

-

-

Commercial
fused silica
capillary column
PGC column and
electrospray
ionization

(Sabater et
al., 2019)

Centrifugation,
dilution,
homogenization,
ultrafiltration, and
reduction with
NaBH4
Dilution,
centrifugation,
protein
precipitation with
60% ethanol
Dilution,
centrifugation, and
ultrasonic protein
precipitation with
acetonitrile
Centrifugation,
freeze drying, and
extraction ethanol:
water (2:1)
10 to 100-fold
dilution with
ultrapure water,
centrifugation, and
fluorescent
labelling with 2-AB
Centrifugation,
extraction with
60% ethanol, and
drying with N2
Protein and fat
precipitation,
lactose removal by
SPE, and
derivatization with
APTS
Homogenization,
centrifugation, and
ultrafiltration

0.039 –
0.156
µg/mL
(LOQ)

89 - 110

<
13%

0.6 –
6.8 fmol

-

-

UPLC BEH
amide column
and electrospray
ionization in
MRM mode
UPLC amide
column and
electrospray
ionization in
MRM mode
On-line
zwitterionic
SPE, and amide
column
UPLC BEH
amide column

(Xu et al.,
2016)

-

89.3 –
110.29

< 8.64

-

90 – 106

-

0.8 –
7.6 pg

88 - 107

1.2 3.6

-

-

-

Uncoated
capillary;
detection at 205
nm
Rapid
characterization
of 33 milk OS

(Monti et al.,
2015)

-

-

-

0.1 –
0.7
mg/mL

88 - 112

<5

UPLC BEH
amide column

(Christensen
et al., 2020)

Direct injection

0.35 –
1.83
mg/mL
91.6 –
315
mg/L

-

-

CarboPac PA100 column

(Cürten et
al., 2017)

95.0 -110.8

< 4.8

(Li et al.,
2016)

-

< 2.15

Lab-purified
standards by
SPE and semipreparative
HILIC system
Zwitterionic
HILIC column

9.6 –
11.8
µg/mL
3.8 –
6.0
mg/mL

-

<5

Fused silica
capillary;
detection at 270
nm

(Hiltunen et
al., 2016)

(Tonon et
al., 2019)

(W. Zhang
et al., 2019)

(Yan et al.,
2018)

(Huang et
al., 2019)

(Difilippo et
al., 2016;
Vicaretti et
al., 2018)

(Pu et al.,
2017)

Given the structural complexity and diversity of functional oligosaccharides depending on the
source and production process, the development of quantitative analysis for OS has been
challenging. Furthermore, the lack of available standards, especially for GOS, limits the
quantification of OS at an individual level; hence, OS contents are typically expressed as
relative abundance. However, recent studies demonstrated the feasibility of extracting and
purifying OS standards in the laboratory by SPE, preparative HPLC, or a combination of both
in place of commercially available standards.
Common drawbacks of conventional techniques used to analyze OS are long analysis time,
and complicated sample pretreatment such as SPE and derivatization. Hence, recent research
efforts have directed to simplifying sample pre-treatment through. The application of an online SPE system has simplified sample pre-treatment and automation, and enhanced recovery
rates and sensitivity compared with conventional off-line analysis. Furthermore, several
studies have demonstrated the suitability of extraction with organic solvents (i.e. acetonitrile,
methanol, and ethanol) coupled with centrifugation and ultrafiltration in the analysis of OS in
various food matrices.
Subsequently, several methods have been proposed and evaluated for the analysis of OS in
food and reaction hydrolyzates with each method having their own set of advantages and
disadvantages. Due the lack of chromophores in OS molecules, they are commonly detected
using refractive index (RID), evaporative light scattering detection (ELSD), pulsed
amperometric detection (PAD), and mass detection (MS). Liquid chromatographic methods
coupled with RID are commonly used owing to its convenience, and they are relatively less
expensive than other instrumental techniques. However, the incompatibility of RID with
gradient elution greatly limits LC-RID techniques in separating higher molecular weight OS
(DP > 4). Hence, they are commonly used for the analysis of low molecular weight OS while
higher molecular weight OS are detected by either ELSD or PAD. Detection by ELSD and
MS are commonly used for HILIC-based liquid chromatographic techniques. However,
HILIC-based techniques are limited by the differences in solubility of OS molecules. Hence,
among these techniques, quantification by HPAEC-PAD was the most promising due to its
higher sensitivity and specificity compared to other methods discussed in this review.
Moreover, HPAEC-PAD was not limited by solubility differences of target OS and was able
to present better separation between isomers and lower limits of detection and quantification
without the need for elaborate sample preparation. However, the relatively longer analysis
time was observed for this method; hence other methods discussed such as HPLC-RID and
HPLC-ELSD could still be more applicable for routine analysis of OS in food samples.

Abbreviations
OS – Oligosaccharides
DP – Degree of polymerization
FOS – Fructooligosaccharides
GOS – Galactooligosaccharides
XOS – Xylooligosaccharides
HMO – Human milk oligosaccharide
MOS – Milk oligosaccharide
BMO – Bovine milk oligosaccharide
HPLC – High performance liquid chromatography
UPLC – Ultra performance liquid chromatography
RID – Refractive index detector
ELSD – Evaporative light scattering detector
FLD – Flourescent detector
BEH – ethylene bridged hybrid
HPAEC-PAD – High performance anion exchange chromatography – pulsed
amperometric detection
TMSO – Trimethyl silated oximes
PGC-SPE – Porous graphitized carbon – solid phase extraction
MRM – Multiple reaction monitoring
HILIC – Hydrophilic interaction liquid chromatography
QqQMS – Triple quadrupole mass spectrometry
GC-FID – Gas chromatography fluorescence induced detection
CE-LIF – Capillary electrophoresis lased induced fluorescence
MEKC-CE – Micellar electrokinetic chromatography – capillary electrophoresis
CE-PDA – Capillary electrophoresis photodiode array detector
LOD – Limits of detection
LOQ – Limits of quantitation

4

Acknowledgements

The author acknowledges the financial support from Thompson Rivers University through their
Undergraduate Research Experience Experience Award Program (UREAP).
5

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