#646_TATEO_bozza


	

Ital. J. Food Sci., vol 29, 2017 - 233 

PAPER 
 
 
 
 
 

TRIGLYCERIDES VARIABILITY IN DONKEY MILK 
 
 
 

M. BONONI1*, F. TATEO1 and A. TATEO2 
1Department of Agricultural and Environmental Science, University of Milan, Via Celoria 2, Milan, Italy 

2Department of Veterinary Medicine, University “Aldo Moro” of Bari, Valenzano, Ba, Italy 
*Corresponding author. Tel.: +39 0250316538 

E-mail address: monica.bononi@unimi.it 
 
 
 
 
 
 

ABSTRACT 
 
The distribution of triacylglycerols (TAGs) in donkey milk and of fatty acids in the 
glycerol backbone affect assimilation and lipolysis, so the utility of analytical methods to 
characterise fat fractions is proved. In this study an optimised gas chromatography/on-
column injector method was used to study the TAG variability of various milk species. 
This method is useful for quality control aimed at standardising formulated donkey milk 
and was used to compare the TAG composition of lyophilised donkey milk distributed on 
the Italian market. Three TAG groups, based on variability degree, were detected and the 
most characterising TAG fraction was identified. 
 
 
 
 
 

Keywords: donkey milk, GC-OCI technique, quality control, triglycerides variability 
 



	

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1. INTRODUCTION 
 
The use of donkey milk for human consumption is justified by various nutritional values 
and its tolerability (BARŁOWSKA et al., 2011; DO NASCIMENTO RANGEL et al., 2015; 
MALISSIOVA et al., 2016 POLIDORI and VINCENZETTI, 2013). The presence of bioactive 
and functional components has been largely reviewed (MARTINI et al., 2014; SALIMEI et 
al., 2004; SALIMEI, 2011; SALIMEI and FANTUZ, 2012;). Moreover, the consumption of 
donkey milk is an alternative when there is an intolerance to cow’s milk (HØST and 
HALKEN, 2004; LARA-VILLOSLADA et al., 2005; MONTI et al., 2007; RESTANI et al., 
2009). Previous studies (CHIANESE et al., 2010; GUO et al., 2007; MARCONI and 
PANFILI, 2002; SUMMER et al., 2004) support the optimisation of infant formula milk and 
the production of nutraceutical compounds in donkey milk for the following reasons: (1) 
the lipid content in donkey milk is essentially lower than in milk from humans or cows; (2) 
the carbohydrate content in donkey milk is comparable with human milk but higher than 
in cow’s milk; and (3) the protein content in donkey milk is higher than in human milk but 
lower than in cow’s milk. This research is part of a larger project concerning the industrial 
formulation of humanised milk and nutraceutical compounds using lyophilised donkey 
milk. The standardisation of these commercial products is possible only if they are derived 
from ingredients characterised by standard parameters. 
Groups have analysed the triacylglycerol (TAG) composition to identify the fatty acids in 
the glycerol backbones (GASTALDI et al., 2010), but the analytical methods used for this 
aim are not suitable for routine industrial quality control. Some authors also reported 
comparative results for the fatty acid and TAG compositions of various milks species 
(BLASI et al., 2008; BRECKENRIDGE and KUKSIS, 1967; CHIOFALO et al., 2011; 
COSSIGNANI et al., 2011; DUGO et al., 2005; GANTNER et al., 2015GASTALDI et al., 2010; 
JENSEN, 1999; MARTEMUCCI and D’ALESSANDRO, 2012; ZOU et al., 2013). There is 
often not ideal peak resolution in TAG analysis using high performance liquid 
chromatography with an evaporative light scattering detector (HPLC/ELSD) (ZOU et al., 
2013) and there are difficulties with TAG analysis when using HPLC/atmospheric 
pressure chemical ionisation (APCI)/mass spectrometry (MS) techniques with correction 
factors to estimate the proportion of the different TAGs in each type of milk (GASTALDI 
et al., 2010).  
Various authors reported comparative results concerning the fatty acid composition and 
TAG distribution of the fatty acids in the glycerol backbone of various milk species, but 
the analytical methods used for TAG analysis are not useful for routine quality control 
(BLASI et al., 2008; BRECKENRIDGE and KUKSIS, 1967; CHIOFALO et al., 2011; 
COSSIGNANI et al., 2011; DUGO et al., 2005; GANTNER et al., 2015; GASTALDI et al., 
2010; JENSEN, 1999; MARTEMUCCI and D’ALESSANDRO, 2012; ZOU et al., 2013). 
This paper discusses the advantages of adopting a rapid gas-chromatography (GC) 
method based on the identification sequence of peaks, with each one representing the total 
carbon number (CN) of a single TAG, in order of increasing molecular weight.  
The triglyceride composition of lyophilised donkey milk products available on the Italian 
market was compared and the characterisation of donkey milk by this easy method was 
useful for the purposes of industrial quality control and to determine the fat variability 
composition in these lyophilised donkey milk.  
 
 
 
 
 
 



	

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2. MATERIALS AND METHODS 
 
2.1. Experimental design 
 
A method that was able to produce a complete pattern of TAGs by direct injection was 
first reported in the Commission Regulation (EC) No 213/2001 to determine the 
genuineness of butter. Then, the Authors modified the operative conditions to produce the 
first repeatability data (BONONI et al., 2001) and adopted the modified method for the 
identification of synthesised TAGs used as support in butter flavours (TATEO and 
BONONI, 2003). The same method was also applied for quality control of vegetable and 
animal fats (TATEO and BONONI, 2002; TATEO and BONONI, 2004).  
Some Authors (LOZADA et al., 1995; MOLKENTIN and PRECHT, 1994; MOLKENTIN 
and PRECHT, 1995) quantitatively determined the TAG composition of milk using 
capillary columns. In the present paper, we used a Petrocol capillary column with bonded 
phase, hydrogen as the carrier gas, optimised operative conditions for an on-column 
injector (OCI), and programmed oven temperatures. The optimisation of the 
chromatographic conditions was necessary strictly to obtain repeatability data that were 
useful for various quality control aims.  
We used the proposed method to analyse a mass sample of donkey milk from a traditional 
farming Area of Martina Franca in Apulia (Italy) and the TAG data were compared with 
milk samples from humans, cows, sheep and goats obtained with the same method.  
The lyophilised donkey milk from the farming area of Martina Franca was compared with 
other lyophilised donkey milk products available from the specialised Italian market. 
 
2.2. Milk samples from different species 
 
First, five samples of milk from different species were compared to highlight the 
significant differences in the TAG composition of the fat fractions using the proposed 
method (described below). These samples were: 
 

a) Donkey milk from an autochthonous breed from the Apulia region (Martina 
Franca), produced by donkeys bred using a semi-extensive method at the farm 
“Masseria Lamacarvotta” in Laterza (Italy); 

b) Cow, sheep, and goat milk selected from Italian farms and collected at the mid 
lactation stage; 

c) Human milk kindly provided by the Neonatology Unit (Milkbank) at the Santa 
Chiara Hospital in Trento (Italy). 

 
All five samples were stored at 4°C strictly during the time to the laboratory and then 
were immediately frozen at -20°C before lyophilisation. Subsequently, the samples of milk 
were lyophilised using a ScanVac CoolSafe 110-4 Pro Freeze Dryer (Labogene) at -105°C.  
 
2.3. Lyophilised, commercially available donkey milk 
 
Four samples of lyophilised donkey milk, commercially available in Italy, were compared 
with the donkey milk produced from the Martina Franca breed and lyophilised in our 
pilot equipment, and also with a donkey milk available in Italy that was lyophilised in our 
laboratory using the same conditions adopted for the liquid samples presented in Table 1. 
This liquid donkey sample was sterilized by uperisation. 
 
 



	

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2.4. GC analysis of triglycerides 
 
For the analysis of the TAG profiles in donkey, human, cow, sheep, and goat milk fat, ~5 
mL of water was added to ~1-2 g of the lyophilised sample. The sample was vortexed for 1 
min, and then sonicated in an ultrasonic bath for 5 min with 2 mL of isooctane (Sigma 
Aldrich). The mixture was centrifuged at 4000 rpm for 5 min. The isooctane phase (2 mL) 
was introduced manually in the on-column injector (OCI) at 40°C. The TAG analyses were 
performed on a HRGC 5160 Mega Series (Carlo Erba Instruments) equipped with a 
bonded phase poly (dimethyl siloxane) Petrocol EX 2887 capillary column (Supelco) with 
dimensions of: 5 m x 0.53 mm i.d. and 0.1 μm film thickness. The oven temperature 
program was 150°C, increased to 200°C at a rate of 10°C min-1 and then increased to 340°C 
at a rate of 5°C min-1 (held for 30 min). The detector temperature (FID) was 350°C and the 
carrier gas was H2 at 20 kPa pressure. An anhydrous butter fat standard certified by the 
Community Bureau of Reference (CRM 519) was used for peak identification. 
 
 
Table 1. Triacylglycerol composition (TAG expressed as % of peaks identified with total carbon number) of 
donkey milk produced in farm “Masseria Lamacarvotta” (Laterza, Italy) compared with human, cow, sheep 
and goat milk samples. 
 

TGA Donkey Human Cow Sheep Goat 
C22 0.01 n.d. 0.07 0.06 n.d. 
C24 0.49 0.34 0.56 0.65 0.36 
C26 0.21 n.d. 0.46 0.85 n.d. 
C28 0.65 n.d. 0.86 1.80 0.38 
C30 1.65 n.d. 1.27 2.93 0.89 
C32 2.72 n.d. 2.33 4.35 1.72 
C34 3.44 0.20 5.30 6.05 3.59 
C36 4.57 0.56 10.04 8.69 5.80 
C38 6.13 1.11 12.44 13.15 8.21 
C40 7.82 2.24 9.67 13.62 9.22 
C42 10.15 4.26 6.17 8.77 9.75 
C44 12.49 7.39 5.75 7.25 10.16 
C46 9.83 11.17 6.55 6.40 10.02 
C48 6.90 12.68 8.59 5.57 9.60 
C50 8.76 17.79 12.50 6.81 11.75 
C52 16.22 32.71 12.08 8.46 15.23 
C54 7.59 9.12 5.35 4.60 3.33 
C56 0.37 0.42 n.d. n.d. n.d. 

 
 
3. RESULTS 
 
The mean TAG compositions (Table 1) were derived from three replicate GC-OCI analyses 
of samples of donkey milk from the Martina Franca farm and of samples from other 
species. Examples of the GC-OCI traces of milk from donkey, human, cow, sheep and goat 
are shown in Fig. 1.  
 



	

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Figure 1. Examples of GC-OCI traces produced for fat fraction of milk of different species and expressed as 
total carbon number (CN). 
 
 
 

 
 
 
The NMKL Procedure No. 5 (Nordic Committee on Food Analysis, 1997) was used to 
evaluate the relative Repeatability Standard Deviation (RSDr) using three samples for each 
milk species, and the following results were obtained: 0.022 (donkey milk), 0.032 (human 
milk), 0.018 (cow milk), 0.034 (sheep milk), and 0.011 (goat milk). 
The TAG composition (Table 2) of four lyophilised samples present on the Italian market 
were compared with two lyophilised samples produced from the reference liquid donkey 
milk of Martina Franca and from the liquid donkey milk distributed in Italy. From these 
data, it is possible to deduce average data and to calculate Dmax values for each TAG class: 



	

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the Dmax values are simply derived from the minimum and maximum values identified in 
Table 2. To estimate the variability from the mean values, we defined three ranges (<0.3, 
0.3-0.6, and >0.6) deduced from the ratio “Dmax/mean” that identify TAG classes with low, 
medium, and high variability. 
 
 
Table 2. TAG composition of the fat fraction of four lyophilised donkey milk products distributed in Italy 
(A-D) compared with the Martina Franca donkey milk (E) and a donkey milk distributed in Italy (F) 
lyophilised in laboratory pilot equipment. 
 
 A B C D E F     
TGA       average Dmax Dmax/average 
C22 0.15 0.03 0.02 0.04 0.01 0.68 0.16 0.67 4.32 *** 
C24 0.74 0.56 0.70 0.47 0.49 1.19 0.69 0.72 1.04 *** 
C26 0.13 0.25 0.24 0.32 0.21 0.20 0.23 0.19 0.84 *** 
C28 0.54 0.86 0.98 0.66 0.65 0.80 0.75 0.44 0.59 ** 
C30 1.67 2.31 2.54 1.72 1.65 1.87 1.96 0.89 0.45 ** 
C32 2.80 3.66 4.22 2.82 2.72 4.30 3.42 1.58 0.46 ** 
C34 3.79 4.72 5.16 3.65 3.44 4.07 4.14 1.72 0.42 ** 
C36 5.16 6.32 6.58 4.89 4.57 5.19 5.45 2.01 0.37 ** 
C38 6.75 8.21 8.23 6.40 6.13 6.89 7.10 2.10 0.30 * 
C40 8.54 10.54 9.83 8.19 7.82 8.82 8.96 2.72 0.30 * 
C42 11.39 13.61 11.69 10.78 10.15 11.55 11.53 3.46 0.30 * 
C44 12.61 14.96 12.71 12.41 12.49 12.94 13.02 2.55 0.20 * 
C46 9.06 9.52 9.13 9.13 9.83 9.43 9.35 0.77 0.08 * 
C48 6.93 7.14 6.10 6.79 6.90 6.75 6.77 1.04 0.15 * 
C50 10.41 6.02 7.10 9.80 8.76 8.92 8.50 4.39 0.52 ** 
C52 14.19 9.80 10.28 15.20 16.22 12.17 12.98 6.42 0.49 ** 
C54 4.99 1.45 4.36 6.50 7.59 4.23 4.85 6.14 1.27 *** 
C56 0.15 0.04 0.13 0.23 0.37 n.d. 0.18 0.33 1.79 *** 
 
The variability classes for TAG are expressed as the total carbon number (CN). Data for all samples were 
derived from five replicates. 
Dmax/average 
* < 0.3 little variability 
** from 0.3 to 0.6  medium variability 
*** > 0.6  high variability  
 
 
The TAGs characterised by the lower variability are included in six TAG classes from C38 
to C48. In each donkey milk sample, the classes with lower variability represented more 
than 50% of the total fat fraction. In particular, for five samples, the TAGs with lower 
variability represented 53-58% of the total TAG content, and for sample B they represented 
64% of the total fat.  
The TAGs characterised by the higher variability are included in four TAG classes (C24, 
C26, C54, and C56) that represented 5-9% of the total fat fraction for five samples and 2% 
of sample B, while the TAGs with medium variability (C28, C30, C32, C34, C36, C50, and 
C52) represented 34-39% of the total fat fraction. 



	

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Considering the identification of donkey milk fatty acids on glycerol backbone 
(GASTALDI et al., 2010) and data in Table 2, we deduced Table 3 that shows the TAGs 
composition of three variability classes. Table 4 reports fatty acid symbols and names used 
in Table 3. 
 
 
Table 3. TGA % composition with lower, medium and higher variability classes in six donkey milk samples 
of Italian market. 
 
Lower variability 
 

TGA A B C D E F  

C38 6.75 8.21 8.23 6.40 6.13 6.89 Bu-P-Ln, Cy-C-Me, C-La-Po, Co-P-P, C-La-P, La-La-M 

C40 8.54 10.54 9.83 8.19 7.82 8.82 C-La-Ln, Co-P-Ln, Cy-M-Ln, C-La-O, C-M-P, Cy-P-P 

C42 11.39 13.61 11.69 10.78 10.15 11.55 Cy-P-Ln, C-M-Ln, La-Ln-Ln, Cy-P-O, C-Po-P,  C-P-P 

C44 12.61 14.96 12.71 12.41 12.49 12.94 Cy-Ln-L, Cy-Ln-O, C-P-Ln, Cy-O-O, C-P-O,  La-P-P 

C46 9.06 9.52 9.13 9.13 9.83 9.43 C-Ln-Ln, C-Ln-L, C-Ln-O, C-L-O, La-P-Ln,  C-O-O, La-P-Pl, La-P-O-, M-P-P 

C48 6.93 7.14 6.10 6.79 6.90 6.75 La-Ln-O, La-L-O, Mo-P-L, M-P-L, M-Po-O,  M-P-O, M-P-S, P-P-P 
Σ 55.28 63.98 57.69 53.70 53.32 56.38  

 
Medium variability 
 

TGA A B C D E F  
C28 0.54 0.86 0.98 0.66 0.65 0.80 Cy-Cy-La 
C30 1.67 2.31 2.54 1.72 1.65 1.87 Cy-C-La 
C32 2.80 3.66 4.22 2.82 2.72 4.30 C-C-La 
C34 3.79 4.72 5.16 3.65 3.44 4.07 Cy-Cy-Ln, C-C-M, Cy-C-P, C-La-La 
C36 5.16 6.32 6.58 4.89 4.52 5.19 Cy-Cl-Ln, Cy-C-Ln, Cy-C-O, Cy-La-P 

C50 10.41 6.02 7.10 9.80 8.76 8.92 M-Ln-Ln, Po-P-Ln, P-P-Ln, P-P-L, Po-P-O, P-P-O, P-P-S 

C52 14.19 9.80 10.28 15.20 16.22 12.17 P-Ln-Ln, P-Ln-L, Po-Ln-O, P-L-L, P-Ln-O,  Po-L-O, P-L-O, Po-O-O, P-O-O-, P-O-S 
Σ 38.56 33.69 36.86 38.74 38.01 37.32  

 
Higher variability 
 

TGA A B C D E F  
C22 tr. tr. tr. tr. tr. tr.  
C24 0.74 0.56 0.70 0.47 0.49 1.19 Bu-Bu-P 
C26 0.13 0.25 0.24 0.32 0.21 0.20 Cy-Cy-C 

C54 4.99 1.45 4.36 6.50 7.59 4.23 Ln-Ln-L, Ln-L-L, Ln-Ln-O, Ln-L-O, L-L-O,  Ln-O-O, L-O-O, O-O-O, O-O-S, P-O-Ga, O-S-S 
C56 0.15 0.04 0.13 0.23 0.37 n.d. P-O-Er 
Σ 6.01 2.30 5.43 7.52 8.66 5.62  

 
 
 
 



	

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Table 4. Fatty acid symbols used in Table 3. 
 

Symbol Notation Fatty acid 
Bu C4:0 Butyric acid 
Co C6:0 Capronic acid 
Cy C8:0 Caprylic acid 
Cl C10:1 Decenoic acid 
C C10:0 Capric acid 
La C12:0 Lauric acid 
Mo C14:1 Myristoleic acid 
M C14:0 Myristic acid 
Po C16:1 Palmitoleic acid 
P C16:0 Palmitic acid 
Ln C18:3 Linolenic acid 
L C18:2 Linolei acid 
O C18:1 Oleic acid 
S C18:0 Stearic acid 

Me C20:3 Eicosatrienoic acid 
Ga C20:1 Eicosaenoic acid 
Er C22:2 Docosaenoic acid 

 
 
4. CONCLUSIONS 
 
The determination of the amount of TAG, free fatty acids, and phospholipids in milk from 
various species has been the objective of many studies (CLAEYS et al., 2014; GANTNER et 
al., 2015; JENSEN et al., 1990) and the distribution of fatty acids in triglycerides and the 
glycerol backbone affects the assimilation and consequently the biochemical and the 
nutritional value (EMKEN et al., 2004; FILER et al., 1969; GASTALDI et al., 2010). 
Therefore, the influence of the TAG composition is confirmed.  
From an analytical point of view, a simple method based on the identification of TAG, 
expressed as CN, is very useful. The GC method described in this paper for the study of 
TAG content, expressed as CN, is optimised for the quantitative characterisation of TAG 
profiles and is useful for industrial quality control of donkey milk. Also, the GC-OCI 
profiles reported in this paper demonstrated there is a clear differentiation between 
different species of milk and the TAG pattern may be considered a fundamental 
characteristic of milk from all species. In this paper, the TAG fraction of donkey milk from 
the Martina Franca breed was compared with human, cow, sheep, and goat milk samples, 
and the proposed GC-OCI method produced good reproducible results and permitted an 
easy characterisation and comparison. 
Concerning the TAG composition of donkey milk, previous studies used different 
methods but not always included the TAG composition. Therefore, this paper gives a 
contribute to define the extremes of natural variability for donkey milk. We determined 
the variability of TAG composition, expressed as CN, in lyophilised donkey milk using 
our optimised method and we detected three degrees of variability for the different TAG 
classes.  
 
 
 
 



	

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ACKNOWLEDGEMENTS 
 
The Authors thanks Eurolactis Group SA for providing the donkey milk of its production. 
 
 
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Paper Received October 15, 2016  Accepted November 29, 2016