levels of cu, mn, fe and zn in cow serum and cow … 1190.pdfnormally, fat makes up from 3.5 to 6.0%...

Acta Scientiae Veterinariae, 2014. 42: 1190.

RESEARCH ARTICLE Pub. 1190

ISSN 1679-9216

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Received: 15 December 2013 Accepted: 12 May 2014 Published: 23 May 2014

1Engineering and Technology Research Center of Traditional Chinese Veterinary Medicine of Gansu Province, Key Lab of New Animal Drug Protection of Gansu Province, Key Lab of Veterinary Pharmaceutical Development of Ministry of Agriculture, Lanzhou Institute of Husbandry and Pharmaceutics Sciences of Chinese Academy of Agricultural Sciences, Lanzhou, Gansu, P.R. China. 2Institute of Agro-Products Processing Science and Technology, Chinese Academy of Agricultural Sciences, Beijing, P.R. China. CORRESPONDENCE: H. Wang [[email protected] - Tel.: +86 (931) 211-5263]. Lanzhou Institute of Husbandry and Pharmaceutics Sciences of Chinese Academy of Agricultural Sciences. No 335, Qilihe, Lanzhou, 730050, China.

Levels of Cu, Mn, Fe and Zn in Cow Serum and Cow Milk:

Relationship with Trace Elements Contents and Chemical Composition in Milk

Hui Wang1, Zhiqi Liu2, Yongming Liu1, Zhiming Qi1, Shengyi Wang1,

Shixiang Liu1, Shuwei Dong1, Xinchao Xia1 & Shengkun Li1

ABSTRACT

Background: Milk can be considered a source of macro- and micronutrients, together with bioactive substances, and also contains a number of active compounds that play a signifi cant role in both nutrition and health protection. Data on milk chemical composition provide information on milk quality alterations and cow health status but is also useful in planning feeding and breeding. Animals living use changes in the photoperiod to adapt to seasonal changes in the environment. The composition of milk is of great importance for the dairy industry and there is great interest in changing the composition of milk. Dairy cow breeding in China has always been restricted by species, management, nutrient supply, seasonal variation and other factors, which cause the quality of raw milk is unsteady. The transition element cations have concentrations in blood, tissues and milk that are largely independent of the intake, as they relate to regulation of gut absorption and chang-ing metabolic demands. Thus, the main objective of this study was to investigate the possible effects of nature month and physiological variables on chemical composition in milk and trace element levels in Chinese Holstein Friesian cows.Materials, Methods & Results: In this paper, cow milk samples were collected from 180 consecutive milkings during 6 month. For the fi rst time, Pearson phenotypic correlations and hierarchical cluster analysis (HCA) were used for analyzing milk chemical composition and trace elements levels in milk and serum. Linear regression was used to predict the value of the continuous dependent variable based on the value of the independent variable. The results showed milk chemical composition and trace elements vary considerably throughout the test period. HCA classifi ed samples into three main groups on the basis of the measured parameters. The fi rst group was composed of fat, total solids, Mn, Fe, and Zn; the second cluster included solids non fat, freezing point, total protein, density, lactose, and acidity; and the last cluster consisted of Cu alone. Stepwise linear regression analysis showed that milk Mn was signifi cantly correlated with serum Mn (r = 0.388, P = 0.008 < 0.05), but milk Cu, Fe and Zn levels were not positively associated with serum (r = 0.013, P = 0.933 > 0.05; r = –0.235, P = 0.087 > 0.05; r = 0.217, P = 0.081 > 0.05, respectively).Discussion: These observations suggest that the concentration of Cu, Mn, Fe and Zn in serum and milk did not remain stable during lactation period. Nature month variations have to be taken into consideration for the correct interpretation of milk chemical composition and trace elements status in cow. HCA is an effective way to comprehensively evaluate the characterization of milk, which not only could avoid the bias and the instability of single factor analysis, but also refl ect the relationship between different chemical composition and trace elements related characterization and quality in milk better. The newborn infant is dependent on an adequate supply of trace elements for optimal nutrition and health. The mammary gland has a remarkable capacity to adapt to maternal defi ciency or excess of trace elements and to homeostatically control milk concentrations of these essential nutrients such as Cu, Mn, Fe and Zn. However, the content of milk Cu, Fe, and Zn is not suitable for refl ect the states of the corresponding nutrients in serum.

Keywords: milk, chemical composition, trace elements, relationship, serum.

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H. Wang, Z. Liu, Y. Liu, et al. 2014. Levels of Cu, Mn, Fe and Zn in Cow Serum and Cow Milk: Relationship with Trace Elements Contents and Chemical Composition in Milk. Acta Scientiae Veterinariae. 42: 1190.

INTRODUCTION

Milk can be considered a source of macro- and micronutrients, together with bioactive substances, and also contains a number of active compounds that play a signifi cant role in both nutrition and health protection [34]. The main components of milk from cow not only refl ect the hereditary character, milk secretion char-acter and nutritional status of cow, but also refl ect the seasonal changes [29,30]. Animals living use changes in the photoperiod to adapt to seasonal changes in the environment [26]. The composition of milk is of great importance for the dairy industry and there is great interest in changing the composition of milk. The scope for increasing concentration of micronutrients in milk is limited by the complex and co-coordinated biochemical mechanisms of animal homeostasis [27]. Dairy cow breeding in China has always been restricted by species, management, nutrient supply, seasonal vari-ation and other factors, which cause the quality of raw milk is unsteady [41]. Trace elements play a versatile function in the human body ranging from developing immunity to provide antioxidant defense [33,43,44]. The transition element cations have concentrations in blood, tissues and milk that are largely independent of the intake, as they relate to regulation of gut absorption and changing metabolic demands [9,39]. The correla-tion among chemical composition and trace elements in milk, and the relationship of trace elements between milk and serum were few analyzed. Thus, the main objective of this study was to investigate the possible effects of nature month and physiological variables on chemical composition in milk and trace element levels in Chinese Holstein Friesian cows.

MATERIALS AND METHODS

Milk sampling and analysis of milk composition

The milk samples analyzed in this study were obtained from Dingxi Tianchen animal husbandry co., LTD, with Chinese Holstein Friesian cows. The farm is located in Gansu province, northwest China, at lati-tude N35°32’27 and E104°26 33 , at 2010.08 m above sea level, with a continental Mediterranean climate, belongs to semi-arid temperate climate region, and a total of 350-500 mm precipitation per year.

A total of 180 individuals of Chinese Holstein Friesian cows were milk-sampled during the period from March 2012 to August 2012. The health condition

of the animals was supervised continuously, and any animal presenting any sign of disease was removed from the study. As concerns their feeding, the forage fraction of the diets was constituted of alfalfa hay and corn silage. Individual milk samples (1 per animal) were collected during the morning milking of a test day. After collection and with no preservative added, milk samples were stored in portable refrigerators (4°C) and transferred to the milk quality laboratory of the Lanzhou Institute of Husbandry and Pharmaceutics Sciences of Chinese Academy of Agricultural Sciences (Gansu, China).

Milk protein percentage (MPP), milk fat per-centage (MFP), total solids percentage (TSP), solids non fat (SNF), milk lactose percentage (MLP), milk density (MD), freezing point (FP), and acidity were obtained using a milk composition analyzer1.

Serum sampling

A total of 180 blood samples were collected during the experiment. Approximately 10 mL blood was drawn from each cow by jugular vein puncture, us-ing a plastic syringe fi tted with a stainless steel needle. The blood sample was collected into a metal-free plastic tube and allowed to clot at room temperature for half an hour and then centrifuged at 3,000 rpm/min for 15 min in a dust-free room. Serum samples were stored at -70°C and protected from light until analysis.

Analysis of copper, manganese, iron, and zinc

Milk (0.2 mL) and serum (0.2 mL) samples were placed in PTFE digestion tubes and 12 mL diacid mixture (HNO

3:HCl; 3:9) was added. The samples

were analyzed after microwave digestion using mi-crowave digestion system2. The optimal operating condition was developed as described in our previous publication [38]. The digested samples were cooled to room temperature, transferred to glass tube, 1 mL HClO

4 was added, and removed the diacid mixture until

1 mL was left using intelligent temperature controller in 110°C. The digested solution was transferred to volumetric fl ask, and volume made up to 10 mL with ultra pure water. A blank digest was carried out in the same way.

Four elements (Cu, Mn, Fe, Zn) were mea-sured by atomic absorption spectrophotometer (AAS)3 with a deuterium background corrector. The elements were determined by using air–acetylene fl ame. The procedure used for measuring concentrations of trace

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elements has been described previously [1]. Optimiza-tion of the instrument was done for higher sensitivity and lower detection limits. Multi-element calibration standards were prepared by appropriate dilution of 1000 µg/mL single-element standard solutions.

Statistical analyses

The SPSS software package4, was used for the statistical analyses of data. We performed initial descriptive statistics, including mean and standard deviation (SD). Signifi cance of difference between two groups was evaluated using Student’s t-test. For multiple comparisons, one-way analysis of variance (ANOVA) was used. Pearson’s correlation analyses were carried out among the contents of four trace elements and eight chemical compositions in milk, as well as to evaluate the trace elements relationships between the level of serum and milk. The p-values were two-tailed, and two signifi cant levels were using P = 0.05 and 0.01.

Hierarchical cluster analysis (HCA) is a sta-tistical technique used to group cases (individuals or objects) into homogeneous sub-groups based on Ward method by using of Euclidean distance crite-rion was performed for grouping of varieties. HCA calculates the distances (or correlation) between all samples, and was applied to the standardized data to investigate similarities between different samples and sample types [4]. Chemical composition and trace elements states of milk were analyzed by HCA of SPSS.

RESULTS

Gross composition of milk samples

Changes in gross composition (MPP, MFP, TSP, SNF, MLP, MD, FP, and Acidity) of Chinese Hol-stein Friesian cow milk during the lactation period are shown in Table 1. The line chart of Figure 1 describes the changes of chemical composition of milk too.

Milk protein is an important functional nutrient in bovine milk. Its content is also the capital parameter for assessing the quality of milk. The concentration of protein in milk varies from 3.0 to 4.0%. The percentage varies with the breed of the cow. There was a continu-ous reduction in protein content (MPP) from 3.366 to 2.889% between the months of March to July. And the value of MPP in July was lowest compared with other months (P < 0.05). It had a slight increase in August.

Normally, fat makes up from 3.5 to 6.0% of milk, varying between breeds of cattle. The majority of milk fat is in the form of triglycerides formed by the linking of glycerol and fatty acids. Milk fat contains predominantly short-chain fatty acids built from acetic acid units derived from fermentation in the rumen. The fat content of milk was instability during the experiment. Although its range from 3.112 to 4.851% during the months of March to July, the values were not signifi cant

Table 1. Composition of Chinese Holstein Friesian cow milk over 6 months of lactation.

Composition March April May June July August

MPP (%) 3.366±0.327a 3.232±0.501ab 3.083±0.315b 3.021±0.364b 2.889±0.535c 3.063±0.556b

MFP (%) 3.112±1.890bc 4.360±2.728ab 4.177±2.476ab 4.851±3.621ab 3.791±2.826b 5.495±3.018a

TSP (%) 11.996±1.811b 13.655±2.943a 12.929±2.297ab 13.090±3.076ab 12.687±2.799ab 13.972±2.622a

SNF (%) 8.948±0.642a 8.768±0.731ab 8.714±0.363ab 8.600±0.568ab 8.495±0.699b 8.436±0.772b

MLP (%) 4.442±0.470ab 4.401±0.335ab 4.508±0.182a 4.461±0.313a 4.498±0.276a 4.250±0.489b

MD (g/L) 1031.4±3.807a 1029.4±4.774a 1029.8±3.193a 1029.3±5.171ab 1029.2±5.281ab 1026.6±4.871b

FP (°C) –0.544±0.041 –0.536±0.029 –0.532±0.020 –0.529±0.026 –0.526±0.031 –0.529±0.042

Acidity (°T) 7.552±0.939a 7.050±1.122ab 6.882±0.841abc 6.747±1.142bcd 6.106±1.420d 6.206±1.418cd

a–d Means within a row with different superscripts differ (P < 0.05). MPP, milk protein percentage; MFP, milk fat percentage; TSP, total solids percentage; SNF, solids non fat; MLP, milk lactose percentage; MD, milk density; FP, freezing point.

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(P > 0.05). But the value reached 5.495% in August, and signifi cantly higher than it in March and July (P < 0.05).

Total solids percentage (TSP) of milk was basic stability in the range of 11.996 to 13.090%, except the months of April and August, which were a little higher than other months.

There was a decline in solids non fat (SNF) from 8.948 to 8.600% during the months of March to June. It continued decreasing gradually to reach 8.495 and 8.436% at July and August, respectively.

The principal carbohydrate in milk is lactose. Lactose is one of the components of milk which is synthesized in mammary gland and therefore will undergo changes when synthesis is impaired function. The concentration of lactose in the milk (MLP) is relatively constant and averages about 4.4%. Lactose concentration is similar in all dairy breeds and cannot be altered easily by feeding practices. The lactose content of milk fell below 4% may indicate an infl am-mation of the mammary gland.

In general, the freezing point (FP) is constant and is infl uenced by some factors such as variations in the growth medium, system growth, race, etc. FP was stability in the range of -0.53 to -0.54°C. There was no signifi cant difference among each month.

Milk density (MD) was stability in the months of March to July. It was slightly lower than other months (P < 0.05).

There was a sharp decline in Acidity from 7.552 to 7.050 within the fi rst month. It stabilized dur-ing April to June. It continued decreasing gradually to reach 6.106 at July, and further slightly increased to 6.206 at August.

Changes in the trace mineral content of the milk during the lactation period

To investigate the changes in the trace mineral content of the milk during the lactation period, the con-tent of Cu, Mn, Fe and Zn in milk was detected using AAS. The results were shown in Figure 2.

Figure 1. Changes in gross composition of Chinese Holstein Friesian cow milk during the lactation period. Milk was collected from 180 Chinese Holstein Friesian cows during the period from March 2012 to August 2012. The data were expressed as the ‘mean ± standard deviation (SD)’. MPP, milk protein percentage; MFP, milk fat percentage; TSP, total solids percentage; SNF, solids non fat; MLP, milk lactose percentage; MD, milk density; FP, freezing point.

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Figure 2. Amount of Cu, Mn, Fe and Zn in cow milk at different stages of lactation. The content of Cu, Mn, Fe and Zn in cow milk was detected using AAS. The data were expressed as the ‘mean ± standard deviation (SD)’ and statistically analyzed by ANOVA; **Signifi cant at 0.01 probability level, *Signifi cant at 0.05 probability level.

Copper

The mean concentration of Cu in cow milk was 1.167 ± 0.622 µg/mL at April, 0.610 ± 0.522 µg/mL at June, and 0.451 ± 0.183 µg/mL at August. The results indicated a signifi cant decline in the mean concentration of copper during the lactation period of June and August (Figure 2, P < 0.01).

Manganese

The mean concentration of Mn was 0.714 ± 0.049 µg/mL at April, 0.806 ± 0.052 µg/mL at June, and 0.817 ± 0.104 µg/mL at August. The mean concentra-tion increased slightly from April to June, and it was statistically signifi cant (Figure 2, P < 0.01).

Iron

The mean concentration of Fe was 5.789 ± 4.590 µg/mL at April, 8.57 ± 2.87 µg/mL at June, and 3.326 ± 0.867 µg/mL at August. The mean concentra-tion increased rapidly from April to June, and it was statistically signifi cant compared with August (Figure 2, P < 0.01).

Zinc

The mean concentration of Zn was 4.563 ± 0.715 µg/mL at April, 4.357 ± 0.697 µg/mL at June, and 4.554 ± 0.899 µg/mL at August. The concentra-tion of zinc at June was a little declined, but this change was not statistically signifi cant (Figure 2, P > 0.05).

Changes in the trace mineral content of the serum during

the lactation period

Copper

The mean concentration of Cu in cow se-rum was 0.365 ± 0.089 µg/mL at March, 0.421 ± 0.103 µg/mL at April, 0.432 ± 0.126 µg/mL at May, 0.429 ± 0.147 µg/mL at June, 0.740 ± 0.175 µg/mL at July, and 0.680 ± 0.107 µg/mL at August. The results indicated a significant increase in the mean concentration of copper during the lactation period of July and August in cow serum (Figure 3, P < 0.01).

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Manganese

The mean concentration of Mn was 0.665 ± 0.169 µg/mL at March, 0.873 ± 0.356 µg/mL at April, 1.015 ± 0.074 µg/mL at May, 1.313 ± 0.077 µg/mL at June, 0.540 ± 0.238 µg/mL at July, and 0.482 ± 0.119 µg/mL at August. There was a sharp increase from 0.665 to 1.313 µg/mL during the months of April to June (P < 0.01 or P < 0.05). It was sharp declined be-tween June to July (P < 0.01). Last it stabilized during July to August (Figure 3).

Iron

The mean concentration of Fe was 3.440 ± 1.514 µg/mL at March, 4.381 ± 1.955 µg/mL at April, 3.128 ± 1.878 µg/mL at May, 3.700 ± 1.659 µg/mL at June, 4.896 ± 1.274 µg/mL at July, and 5.321 ± 0.941 µg/mL at August. The mean concentration increased rapidly from March to April (P < 0.05), then declined from 4.381 to 3.128 µg/mL between April to May. It stabilized during May to June. It continued increasing gradually to reach 4.896 µg/mL at July, and further slightly increased to 5.321 µg/mL at August (Figure 3, P < 0.01).

Zinc

The mean concentration of Zn was 1.641 ± 0.313 µg/mL at March, 1.874 ± 0.353 µg/mL at April, 2.044 ± 0.604 µg/mL at May, 1.925 ± 0.377 µg/mL at June, 1.638 ± 0.218 µg/mL at July, and 2.248 ± 0.551 µg/mL at August. The concentration of zinc increased gradually to reach 2.044 µg/mL at May (P < 0.01), then declined to 1.638 µg/mL at July, and further increased to 2.248 µg/mL at August (Figure 3, P < 0.01).

Correlations among the contents of chemical composition and four trace elements in milk

To investigate the relationships among chemi-cal composition and four trace element contents in milk, Pearson correlation analyses were performed for the accessions (Table 2). Among the chemical composition and trace elements, closely positive as-sociations were recognized between the contents of MPP and SNF or MD or FP or Acidity or Cu; between the contents of MFP and TSP or Zn; between the contents of TSP and FP; between the contents of SNF and MLP or MD or FP or Acidity or Cu; between the contents of MLP and MD or FP or Acidity; between

Figure 3. Amount of Cu, Mn, Fe and Zn in cow serum at different stages of lactation. The serum Cu, Mn, Fe and Zn levels in cow were measured using AAS. The data were expressed as the ‘mean ± standard deviation (SD)’ and statistically analyzed by ANOVA; **Signifi cant at 0.01 probability level, *Signifi cant at 0.05 probability level.

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the contents of MD and FP or Acidity; or between the contents of FP and Acidity or Cu (P < 0.01).

There were significantly positive correla-tions between the contents of MFP and Fe; between the contents of MD and Cu; between the contents of Acidity and Cu; or between the contents of Fe and Zn (P < 0.05), whereas no close correlations were found between Mn content and the other chemical composi-tion or the other mineral elements (P > 0.05).

The relationships between MPP and MFP or TSP; between MFP and SNF or MLP, MD or Acidity;

between TSP and SNF or MLP or MD or Acidity; or

between Acidity and Fe were indicated that there were

very signifi cantly negative associations (P < 0.01),

and visibly positive correlations were recognized

between MLP and Fe; between Acidity and Fe (P <

0.05) [Table 2].

These results suggested that high Cu content

might be accompanied with high MPP and SNF con-

tents of milk; high Zn content might be accompanied

with high MFP.

Table 2 . Pearson phenotypic correlations among milk chemical composition and milk trace elements.

MFP TSP SNF MLP MD FP Acidity Cu Mn Fe Zn

MPP –0.432** –0.328** 0.820** –0.057 0.551** 0.604** 0.856** 0.419** –0.123 0.037 –0.123

MFP 0.930** –0.515** –0.251** –0.836** –0.094 –0.516** –0.122 0.229 0.399* 0.422**

TSP –0.431** –0.291** –0.814** 0.045 –0.455** –0.225 0.219 0.285 0.119

SNF 0.525** 0.823** 0.796** 0.795** 0.390** –0.052 –0.171 –0.175

MLP 0.631** 0.476** 0.349** 0.027 0.086 –0.329* –0.107

MD 0.422** 0.695** 0.319* –0.126 –0.384* –0.231

FP 0.544** 0.363* 0.028 –0.060 –0.180

Acidity 0.347* –0.195 –0.419** –0.244

Cu –0.284 –0.070 –0.003

Mn 0.308 –0.048

Fe 0.309***Signifi cant at 0.01 probability level. *Signifi cant at 0.05 probability level. MPP, milk protein percentage; MFP, milk fat percentage; TSP, total solids percentage; SNF, solids non fat; MLP, milk lactose percentage; MD, milk density; FP, freezing point.

Hierarchical cluster analysis (HCA)

With the hierarchical cluster analysis three clus-ters have been distinguished for the well data. The result of cluster analysis as a tree diagram was shown in Figure 4, in which three well-defi ned clusters were visible. Samples were grouped in clusters in terms of their nearness or similarity. Cluster analysis (CA) used less information (distances only). It was interesting to observe what kind of classifi cation can be made on the basis of distances only. The fi rst group of samples (A) was clearly discernible which was composed of MFP, TSP, Mn, Fe, and Zn. The second cluster (B) included SNF, FP, MLP, MD, MPP, and Acidity, and the last cluster (C) consisted of Cu alone. The tendencies to form natural sample groupings arising from common analytical characteristics were clear in this data analysis procedure.

Serum trace elements status in relation to milk trace ele-ments status

Copper, zinc, iron, and many dietary essential elements are desired trace constituents of the healthy

tissues of humans and animals. Cu, Zn, Mn and Fe are found as key components in a multitude of enzymes and play an important role in many physiological func-tions of humans and animals.

Linear regression as a statistical procedure was used to predict the value of the continuous de-pendent variable (Milk Cu) based on the value of the independent variable (Serum Cu). This study found no signifi cant correlation between serum Cu and milk Cu in their concentration values for dairy cows (r = 0.013, P = 0.933 > 0.05) [Figure 5A]. Manganese (Mn) is an essential mineral nutrient in humans and other animals and is required for normal amino acid, lipid, protein, and carbohydrate metabolism [40]. In this study, step-wise linear regression indicated that milk Mn levels were positively associated with serum Mn concentra-tions (r = 0.388, P = 0.008 < 0.05) [Figure 5B].

Iron is a part of both the oxygen-carrying system and iron–sulfur proteins, which play an important role in oxygen and carbon dioxide transport in vertebrates

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and in the electron transport system of mitochondria, respectively. The date in this study demonstrated a nega-tive correlation between milk iron and serum iron in their concentration values for cows, but did not reached sig-nifi cant level (r = -0.235, P = 0.087 > 0.05; Figure 5C). The correlation of Zn statistically no signifi cant evidence

was found between milk and serum in their concentration values for cows (r = 0.217, P = 0.081 > 0.05; Figure 5D).

DISCUSSION

Milk plays a tremendous role in building a healthy society and can be used as vehicle for rural de-

Figure 4. Dendrogram of hierarchical cluster analysis of milk chemical composition and milk trace elements.

Figure 5. Relationship between serum trace elements and milk trace elements. (A) Correlation between serum Cu and milk Cu (r = 0.013, P = 0.933). (B) Correlation between serum Mn and milk Mn (r = 0.388, P = 0.008). (C) Correlation between serum Fe and milk Fe (r = –0.235, P = 0.087). (D) Correlation between serum Zn and milk Zn (r = 0.217, P = 0.081).

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velopment, employment and slowing down the migra-tion of the rural population. The milk composition has changed during the past decades because of changes in the feeding regimen and breeding practices or other changes in dairy husbandry. The main objective of this study was to investigate the possible effects of nature month and physiological variables on composition of milk and trace element levels in cow, and the relation-ship between trace element contents and chemical composition in milk.

Nature month variation of chemical composition in milk

A systematic study on describes the varia-tions milk composition is of foremost importance to evaluate the milk production ability of a milking animal. The content of TSP (11.996 to 13.972%), MFP (3.112 to 5.495%), MPP (2.889 to 3.366%) and SNF (8.436 to 8.948%) in Chinese Holstein Friesian cow’s milk during lactation stages was found to be lower than that of sheep (17.48 to19.50, 8.0 to 9.6, 5.32 to 7.74 and 9.48 to 10.1%), goat (12.60 to 15.17, 3.9 to 5.7%, 3.3 to 3.7 and 8.53 to 9.47%), and buffalo (12.73 to 15.90%, 4.0 to 6.5%, 3.12 to 4.12% and 8.28 to 9.40%) [16]. The content of MLP (4.250 to 4.508%) was found to be comparable with that of buffalo (3.28 to 4.80%), cow (3.0 to 4.6%), goat (4.0 to 5.5%) and sheep (3.0 to 4.2%) [16]. In the present study, lactose content did not vary sig-nifi cantly throughout the lactation. Lactose is the main determinant of milk volume. A close relation-ship between lactose synthesis and the amount of water drawn into milk makes lactose a stable milk component [28].

Of the main milk components (lactose, fat, and protein), lactose had the smallest and fat the highest variation, with protein in between. This is in line with the general observation that fat is the most sensitive component of milk to dietary changes and lactose is the least sensitive, again with protein in between [14]. The variation trend is consistent with the literature reported [12]. The milk composition within the same animal breed not only depends on the state of lacta-tion, but also on genetic factors, nutritional status of the animals as well as the composition of feed and the environment [18].

Changes in the trace elements content of the milk and serum during the lactation period

Trace metal levels are important for human health. Milk is an excellent source of most minerals required for the growth of the young. Cu, Mn, Fe and Zn can be considered trace minerals with a central role in many metabolic processes throughout the body and are essential for correct growth and development of all animals. They predominantly act as catalysts in many enzyme and hormone systems which infl uence on growth, bone development, feathering, enzyme struc-ture and function, and appetite [31,35]. Fe is essential for maintaining proper cell functions and is normally tightly controlled by transporter and storage proteins [22]. The low Fe concentration in milk cannot meet the needs of the young, but this low level turns out to have a positive aspect because it limits bacterial growth in milk–iron is essential for the growth of many bacteria [3]. Zn is acting as a catalytic, structural, and regulatory ion. Moreover, Zn-binding protein (metallothionein) plays a key role in Zn-related cell homeostasis which, in turn, is relevant also against oxidative stress, includ-ing exposure to oxyradicals, infl ammation, infection, and immune responses [36].

The results of this research found that the con-centration of Cu, Mn, Fe and Zn in serum and milk did not remain stable during lactation period. Our fi nding is not similar with Erdogan et al. reported that seasonal changes had no signifi cant effect on manganese, cop-per, zinc, and iron concentrations on cows and their milk [7].

Characterization of chemical composition and trace ele-ments in milk based on genetic and herd parameters

Hierarchical cluster analysis (HCA) is an ex-ploratory tool designed to reveal natural groupings (or clusters) within a data set that would otherwise not be apparent, and it is a method for placing objects into more or less homogeneous groups so that the relation between the groups is revealed [13]. It is most useful when you want to cluster a small number (less than a few hundred) of objects. In HCA, samples were grouped on the basis of similarities, without taking into account the information about the class membership. Cluster analysis is a powerful exploratory technique, its results must be considered within the context of the selected input variables and the requirement of an adequate ratio between the sample size and the number of variables to be modeled [24].

However, thus far, there have been no reports using cluster analysis to comprehensively analyze

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chemical composition and trace elements in milk from cows. A cluster analysis was performed to visualize the chemical composition and trace elements in milk correlations in this study. It is clearly shown that three clusters have been distinguished for the well data. It is an effective way to comprehensively evaluate the characterization of milk by cluster analysis which

not only could avoid the bias and the instability of single factor analysis, but also refl ect the relation-ship between different chemical composition and trace elements related characterization and quality in milk better.

Milk trace elements status in relation to serum trace ele-

Figure 6. Model structure for trace elements transfer into milk. Trace elements (TE) present either as free (TEf) or bound (TEb) in the body. The letter ‘‘B’’ represents TE-binding capacity in the tissue. TE in diet were digested and absorbed in small intestine, and were inhaled into lung, respiratory nose and olfactory nose, then entered mammary gland, bone, liver, etc, through the circulation. Milk synthesis starts in the epithelial cells of the mammary gland at the end of pregnancy to support the nutrition and promote the health of the off-spring. Cu was transferred by copper transporters-1 (Ctr1), ATP7A, and ATP7B, Mn was transferred by transmmlganin (Tm), Fe was transferred by transferrin receptor (TR), divalent metal ion transporter 1 (DMT1), and ferroportin (Fp), and Zn was transferred by zinc import protein (Zip3) and zinc transporters (ZnT-1, ZnT-2, and ZnT-4) from mammary gland to milk [6,20,21,23,42]. In our research, the correlation of copper, manganese, iron and zinc between serum and milk was 0.013 (CuSr), 0.388 (MnSr), –0.235 (FeSr) and 0.217 (ZnSr), respectively. With the hierarchical cluster analysis (HCA) 3 clusters have been distinguished the trace elements contents and chemical composition in milk, and (A) was composed of MFP, TSP, Mn, Fe, and Zn, (B) included SNF, FP, MLP, MD, MPP, and Acidity, and the last cluster (C) consisted of Cu alone, respectively.

ments status

The newborn infant is dependent on an ad-equate supply of trace elements for optimal nutrition and health. The mammary gland is capable of regulat-ing concentrations of essential elements such as Cu, Mn, Fe and Zn in milk to protect the newborn infant against defi ciency and excess of these elements [23].

Cu is an essential trace element that partici-pates in the pathogenesis of numerous heart diseases [19]. Cu has a protective impact on cell membranes

against hydrogen peroxide and superoxide anion in-volved in pathogens of cardiovascular disorders by SOD as antioxidant enzymes [10,15]. Previous studies have shown that Cu plays an important role in lacta-tion performance in dairy cows [37]. Mammary gland copper metabolism is regulated by copper transporter 1 (Ctr1), ATP7A, and ATP7B [23] (Figure 6). Kelle-her and Lönnerdal used the rat as a model to study mechanisms regulating milk Cu levels during lacta-tion [17]. The possible mechanisms that the decrease

11


in serum Cu that occurs during lactation is partially responsible for decreasing milk Cu levels by reducing the supply of Cu to the mammary gland. Lönnerdal reported that the concentration of Cu in human milk is about 20-25% of that in serum [23]. But in our study, we found the concentration of Cu in milk was 0.451–1.167 µg/mL, in serum was 0.365–0.740 µg/mL. And the correlation between serum Cu and milk Cu was not signifi cant (r = 0.013, P = 0.933 > 0.05) [Figure 5A and Figure 6].Mn is an essential mineral nutrient in humans and other animals, and is required for normal amino acid, lipid, protein, and carbohy-drate metabolism [40]. Mn present in all tissues is crucial for immune function, regulation of cellular energy, antioxidant enzymes, reproduction, digestion, bone growth, and blood clotting [2,8,42]. In mam-malian tissues, Mn is found in only three important oxidation states: II, III and IV. Free Mn concentra-tions in plasma/serum. Mn has a tendency to bind to high molecular mass proteins, such as transmanganin, transferrin (Tf), albumin and α2-macroglobulin [42] (Figure 6). In our study, stepwise linear regression indicated that milk Mn levels were positively associ-ated with serum Mn concentrations (r = 0.388, P = 0.008 < 0.01) [Figure 5B]. This is in agreement with the knowledge that Mn content in human milk has been positively correlated with increased amount of Mn intake in lactating women [5].

Fe in serum is virtually exclusively bound to transferrin (Tf), and tissue Fe uptake is usually mediated by cellular transferrin receptors (TfRs). No correlation between milk Fe and mammary gland TfR expression has been found in animal models [32], which strongly suggests that regulation of milk Fe con-centrations occurs after uptake of Fe by the mammary gland. Lönnerdal reported the milk Fe concentration is ~20-30% of serum Fe in human [23]; and Zhang et al. reported the concentration of Fe in mouse milk is approximately 3 times that of the serum [45]. But in our research, the concentration of Fe in milk was 3.326-8.570 µg/mL, in serum was 3.128-4.896 µg/mL. And there was no statistically signifi cant correlation between milk Fe status and serum Fe concentration observed in this study (r = -0.235, P = 0.087 > 0.05) [Figure 5C and Figure 6].

Zn is an essential nutrient for carbohydrate metabolism, physiological processes, and many other biochemical reactions because this metal serves as

a catalytic or structural cofactor for many different proteins [6]. Zinc-dependent proteins are found in the nucleus, the endoplasmic reticulum, Golgi, secretory vesicles, and mitochondria. Zn homeostasis is complex, involving both Zn import protein (Zip3) and Zn trans-porters (ZnT-1, ZnT-2, and ZnT-4) [6,23] (Figure 5D and Figure 6). Milk Zn concentrations are considerably higher than in serum. Previous studies found no sig-nifi cant correlation between milk Zn concentration and serum Zn concentration or maternal dietary Zn intake [11,25]. The correlation of Zn was found no statistically signifi cant evidence between milk and serum in their concentration values for cows (r = 0.217, P = 0.081 > 0.05; Figure 5D).

CONCLUSION

In conclusion, Nature month variations have to be taken into consideration for the correct interpretation of milk chemical composition and trace elements status in cow. It is an effective way to comprehensively evalu-ate the characterization of milk by cluster analysis. The mammary gland has a remarkable capacity to adapt to maternal defi ciency or excess of Fe, Cu, Mn and Zn and to homeostatically control milk concentrations of these essential nutrients. However, the content of milk Cu, Fe, and Zn is not suitable for refl ect the states of the corresponding nutrients in serum. Our method, and of course other improved and enhanced methods, could be applied to construct a more comprehensive model or technology of animal behavior, and could be better serviced for people.

SOURCES AND MANUFACTURERS1Foss MilkoScanTM FT 120, Denmark.2MARS5, CEM Company, USA.3ZEEnit 700, Analytik Jena, Germany.4Version 17.0, SPSS Inc., Chicago, USA.

Acknowledgements. The fi nancial supports from the Central Public-interest Scientifi c Institution Basal Research Fund (NO. 1610322013003), National Key Technology Research and De-velopment Program of the Ministry of Science and Technology of China (NO. 2012BAD12B03), and Special Fund for Agro-scientifi c Research in the Public Interest (NO. 201303040-17) are greatly appreciated.

Ethical approval. All animal protocols have been reviewed and approved by the Institutional Animal Care and Use Committee of Lanzhou Institute of Husbandry and Pharmaceutics Sciences of Chinese Academy of Agricultural Sciences (Animal use permit: SCXK20009-0010).

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levels of cu, mn, fe and zn in cow serum and cow … 1190.pdfnormally, fat makes up from 3.5 to 6.0%...

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