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Whole milk powder is a standardized whole milk as raw material, pasteurized, evaporated, homogenized and spray dried dairy products
with high nutritional value.
According to the latest report released by the International Food and Agriculture Organization in April 2021, global international trade in whole milk powder reached nearly 2.
7 million tons in 2020, an increase of 1.
9% over 2019, of which EU exports increased by 11.
5% and Argentina exports increased by 53.
5%.
Flavor is a major factor influencing consumer acceptance of powdered milk products, so it's important to
understand and utilize volatile flavor components.
Ye Meixia, Li Rong*, Jiang Zitao* and others from the School of Biotechnology and Food Science of Tianjin University of Commerce used ultra-fast gas-phase electronic nose (UFGC E-nose) technology to identify the volatile flavor components of 24 kinds of infant, student, adult, middle-aged and elderly milk powder, used the relative odor activity value (ROAV) to evaluate the volatile components contributed by the key aroma in the milk powder, and drew the aroma radar map of milk powder of different ages, and also evaluated the aroma in milk powder of different ages through sensory evaluation.
Combined with multivariate statistical analysis methods such as linear discriminant analysis (LDA) and linear support vector machine (LSVM), the aroma characteristics of milk powder were classified and predicted
.
Establish classification and prediction models for milk powder of different ages, so as to achieve the purpose of fast and accurate classification
1.
Determine the best measurement parameters
Figure 1A shows that the number of chromatographic peaks increases with the increase of incubation temperature, but the difference between 70, 80, and 90 °C is small.
Figure 1B shows that R>1.
5 and the maximum value at 70 °C indicate that the chromatographic peak separation is complete at 70 °C; Taking into account the optimal incubation temperature
, 70 °C was selected.
It can be seen from Table 2 that when the heating procedure is 10, the sample chromatographic peak R reaches 1.
82, indicating that the sample chromatographic peak is basically separated, so it is selected as the best heating program
.
2.
Analysis of volatile components of milk powder
It can be seen from Figure 2 that the chromatograms of milk powder of the same age group are similar in strength, retention time and shape, while the chromatograms of milk powder of different ages are quite different
。 Table 3 shows that a total of 54 volatile flavor components were identified in UFGC E-nose, 44, 48, 47 and 44 in 4 age groups, including aldehydes (19 types), ketones (10 kinds), alcohols (5 kinds), esters (2 kinds), acids (2 kinds), lactones (6 kinds), sulfides (3 types), alkanes (2 types), aromatics (3 types) and heterocyclics (2 types), of which 37 volatile components were detected
in 4 types of milk powder 。 The volatile components in milk powder for middle school students and adult milk powder in 4 age groups are relatively rich, as can be seen from Table 1, which is caused by its high protein, fat and carbohydrate content
.
From Figure 3 and Table 3 (Table 3 can be viewed by clicking below to read the original text), it can be seen that the types and contents of volatile components in milk powder of different ages vary significantly, with the highest content of aldehydes, followed by ketones, acids, lactones, alcohols, heterocyclics, alkanes, sulfides, esters and aromatic substances with the lowest
content.
3.
Evaluation of the main volatile flavor components of milk powder of different ages
It can be seen from Table 4 that a total of 23 volatile components contribute aroma, and there are 12, 12, 12 and 14 key aroma contributing compounds in milk powder in 4 age groups, of which 10 are common
to milk powder in 4 age groups 。 Figure 4 shows that there are 7 common aromas in the milk powder of the four age groups, namely: 2,3-butanedione contributed milk aroma; Dimethyl sulfide, dimethyl disulfide, 3-(methylthio)propionaldehyde, 1-octen-3-one, dimethyl trisulfide, (E)-2-nonenal and (E,E)-2,4-decadienal contributed cabbage, potatoes, boiled mushrooms, cucumbers, coriander and other vegetable flavors; (Z)-3-Hexenal, phenylacetaldehyde, 2-ethyl-3,5-dimethylpyrazine, n-nonanaldehyde, γ-undecylidone contributed apple, berry, grape juice, citrus, apricot and other fruit flavors; Propionaldehyde, (E)-2-hexenal, n-hexanol, decarian, (E,E)-2,4-nonadienal contributed geranium and other floral fragrances; 2-undecone, hexanal contributed grass flavor; Caramel flavor contributed by 2-methylpropionaldehyde; Tar flavor
that contributes to cresol.
In addition, almond flavor is a characteristic odor in infant milk powder, which is contributed by valeraldehyde
.
00, 100.
00, 65.
69 and 64.
06
, respectively 。 The aroma degree of vegetable flavor in infant milk powder is more than 3 times that of milk powder of other ages, and the ROVA is 131.
46, 48.
10, 43.
04 and 33.
42 respectively in adult, middle-aged and elderly milk powder, and the ROVA is 131.
46, 48.
10, 43.
04 and 33.
42, respectively, mainly due to the high aroma degree of 1-octen-3-one in infant milk powder; In addition, (E,E)-2,4-Decadienal is a compound that contributes to the unique key aroma of student milk powder, and has the aroma of vegetables such as coriander
.
The fruit flavor was the highest in middle-aged and elderly milk powder, followed by student milk powder, and infant and adult milk powder were weaker, with ROVAs of 115.
06, 91.
23, 65.
70 and 64.
19
, respectively.
Floral fragrance according to the intensity of aroma for infants, adults, middle-aged and elderly people, student milk powder, student milk powder is only half of other milk powder, its ROVA is 48.
21, 44.
22, 40.
25, 24.
68, the difference is mainly caused by (E, E)-2,4-nonadienal content
.
4.
Sensory evaluation results
Table 5 shows that milk powder has obvious differences in sensory flavor among the four age groups, among which lactic sour taste and cereal taste are quite different.
The milk flavor scored the highest in all 4 age groups, indicating that it was fully reflected in the milk powder
.
The milk aroma, vanilla flavor and caramel flavor in student milk powder and adult milk powder are stronger than that of infant milk powder and middle-aged and elderly milk powder, while infant milk powder and middle-aged and elderly milk powder have a strong vegetable flavor and tar smell, and middle-aged and elderly milk powder also has a smoky taste, which may have a great impact on the odor in the sample, which comes from protein hydrolysis, Maillard reaction or lipid oxidation
during processing.
The above overall explanation shows that the flavor of student milk powder and adult milk powder is generally better than that of infant milk powder and middle-aged and elderly milk powder
.
5.
Classification of milk powder age based on LDA
Figure 5 shows that the sum of the discriminant functions 1 and 2 for the classification of milk powder in four age groups using LDA is 83.
9%, indicating that LDA can distinguish milk powder
from different age groups.
It can be seen from Figure 5 that when LD1 and LD2 are used as the distinguishing axis, the distance between students and adult milk powder is closer, and the distance between infant and middle-aged and elderly milk powder is farther from other milk powder
.
Table 6 shows that the average accuracy of LDA classification of milk powder in the four age groups was 93.
3%, of which all infant milk powder was correctly distinguished, while the accuracy of student milk powder classification was as low as 80.
0%.
。 The absolute value of the standardized discriminant function coefficient can be used to compare the relative contribution of categorical variables in the composition of the discriminant function, as can be seen from Table 7, (E)-2-hexenal, E-3-octen-2-one, n-nonanaldehyde, δ-nonanolactone contributed more in discriminant function 1, (E)-2-hexenal, 2-methylpropionaldehyde, n-hexanol, 1-propanol contributed more in discriminant function 2, and they had a greater
influence on the classification results 。 It can be seen from Table 3 that 1-propanol and n-hexanol are only not contained in infants, middle-aged and elderly milk powder, respectively; (E)-2-Hexenal, E-3-octen-2-one, n-nonanaldehyde, δ-nonanolactone, and 2-methylpropional were detected in four age groups, but the content difference was relatively large, which played an important role
in improving the classification accuracy of milk powder between different ages.
The successful differentiation of milk powder in the four age groups was mainly caused by the difference in nutrient content, the lactose content in infant and student milk powder was higher, and infant milk powder also contained docosahexaenoic acid, eicosatetraenoic acid, linoleic acid and other ingredients; Adult milk powder has higher protein and fat content; Middle-aged and elderly milk powder has a higher
protein content.
6.
Based on LSVM prediction of milk powder of different ages
Figure 6 shows that the predicted importance ranking results derived from the composition and content of volatile components of different types of milk powder are (E)-2-hexenal, n-nonanaldehyde, n-hexanol, dimethyl disulfide, (E,E)-2,4-nonadienal, (E)-3-octen-2-one, 2-methylpropionaldehyde, 1-propanol, (E)-2-hexen-1-ol, and δ-nonanolactone, which is consistent with the results in Table 7, indicating that the constructed LSVM model can quickly, effectively and accurately predict milk powder of different ages
。
Table 8 shows that the average accuracy of LSVM classification is 94.
2%.
Among them, infant milk powder was mistakenly divided into student milk powder 1 time; Student milk powder was mistakenly divided into infant milk powder once; Adult milk powder was mistakenly divided into middle-aged and elderly milk powder 1 time, middle-aged and elderly milk powder was mistakenly divided into student milk powder and adult milk powder 2 times, which may be caused by the close composition and content of protein, fat and carbohydrate in milk powder
.
Conclusion
A total of 54 volatile components were detected in milk powder of 4 different ages by UFGC E-nose technology, of which 37 common components were mainly propionaldehyde, acetone, hexanal and caproic acid.
Methyl propionate, 1-octen-3-one are only present in infant milk powder; (E,E)-2,4-Decadienal and γ-undecalactone are unique components of student milk powder; Heptal is only detected in adult milk powder; 2-Butanone and benzaldehyde are only contained
in milk powder for middle-aged and elderly people.
In addition, only infant milk powder was not detected 1-propanol, ethylbenzene, vanillin, δ-octanolactone; Only student and adult milk powder does not contain m-xylene; Only (E)-2-pentenal, butyl acetate, (Z)-2-hexen-1-ol, n-hexanol are not present in the milk powder of middle-aged and elderly people; δ-Decadecanolide was not detected in infants, middle-aged and elderly milk powder
.
The results of ROAV evaluation showed that a total of 23 volatile components contributed aroma, and the common aromas in milk powder were milk aroma, vegetable flavor, fruit flavor, floral flavor, grass flavor, caramel flavor and tar flavor.
In addition, almond flavor is a characteristic aroma in infant milk powder
.
There were differences in the aroma degree among different age groups, among which the milk aroma was higher in the milk powder of students and adults, and the lower degree of the milk powder of infants and middle-aged and elderly people.
The vegetable flavor and floral flavor had the highest aroma degree in infant milk powder; The fruit flavor was the highest among middle-aged and elderly milk powder, followed by student milk powder; Caramel flavor has a lower aroma level than other milk powders in student milk powder; Grassy and tar flavors differed less
among the 4 age groups.
The sensory evaluation results showed that the flavor of student and adult milk powder was generally better than that of infants, middle-aged and elderly milk powder, and the difference between it and the aroma radar chart results was obvious
.
LDA in multivariate statistical analysis could clearly distinguish different brands of milk powder in the same age group, with an average accuracy of 93.
3%.
The LSVM model can classify and predict milk powder of different ages, with an average accuracy of 94.
2%, and give the ranking of the importance of the prediction of volatile components before milk powder
.
The established UFGC E-nose detection and multivariate statistical analysis methods provide an important methodological basis
for the rapid and accurate classification of milk powder of different ages.
About the corresponding author
Jiang Zitao, male, second-level professor, doctoral supervisor, dean of the School of Food Engineering, Tianjin Tiens University; Professor
, School of Biotechnology and Food Science, Tianjin University of Commerce.
Bachelor/Master of Northeast Normal University, Ph.
D.
of Nankai University, Postdoctoral Fellow of Chinese University of Hong Kong; Member of the Organic Analysis Professional Committee of the Chinese Chemical Society, Standing Director of the Agricultural Products Storage and Processing Branch of the Chinese Society of Agricultural Engineering, and Director of the Agricultural Products Storage and Processing Branch of the Chinese Agricultural Society; Expert in the evaluation of science and technology and talent projects such as the National Natural Science Foundation of China, the Ministry of
Science and Technology, the Ministry of Education, Hebei Province, and Tianjin Municipality.
He used to be the director of the graduate department of Tianjin University of Commerce, the director of the science and technology division, the leader of the key discipline of Tianjin agricultural product processing and storage engineering, and the academic leader of the Tianjin Key Laboratory of
Food Biotechnology.
Main research directions: research and development of food additives, natural food resources, separation and analysis methods
of trace components.
Editorial Board Member, Analytical Chemistry Letters and International Journal of Food Processing Technology, Food Chemistry, Industrial Crops and Products, Food Analytical Methods, Journal of Agricultural and Reviewer
of more than 30 SCI journals such as Food Chemistry.
He has presided over and participated in the completion of more than 10 projects of the National Natural Science Foundation of China and provincial and ministerial projects
.
He has published more than 300 academic papers, including more than 100 papers in SCI/EI, and obtained 6 invention patents
.
First author bio
Ye Meixia, female, holds a master's degree from
the School of Biotechnology and Food Science, Tianjin University of Commerce.
Main research directions: food additives, volatile flavor component analysis of dairy products, food aroma analysis
.
This paper "Analysis and Classification Prediction of Volatile Flavor Components of Milk Powder of Different Age Groups" is from Food Science, Vol.
43, No.
16, 2022, pages 242-252, authors: Ye Meixia, Li Rong, Jiang Zitao, Wang Ying, Tan Jin, Tang Shuhua
.
DOI:10.
7506/spkx1002-6630-20210807-097
。 Click to view information about
the article.
