Short communication
Canonical correlation of milk immunoglobulins, lactoferrin concentration and Dairy Herd Improvement data of Chinese Holstein cows

https://doi.org/10.1016/j.livsci.2009.11.010Get rights and content

Abstract

In this study, canonical correlation analysis was applied to estimate the relationships of DHI data with milk Ig (IgG1, IgA, and IgM) and Lf concentrations. Specifically, we evaluated the relationships between two groups of variables: milk IgG1, IgA, IgM and Lf concentration as variables (y) and lactation number, stage of lactation, daily milk production, milk fat, protein, lactose, milk total solids and somatic cell score (SCS) as variables (x). The results indicated that four canonical variables were identified. The canonical correlations of the first and second pairs of canonical variables were 0.662 and 0.469 respectively, which were highly significant and accounted for 91.6% of the variability observed in the data. Stage of lactation, daily milk production, milk protein and SCS were the significant factors affecting milk Lf concentration in both canonical correlations and multiple correlation analysis, and lactation number was the significant factors affecting milk IgG1 concentration. The first standardized canonical variation combination could be regarded as a predictable measure of Lf concentration and the second as a predictor of IgG1 level. These results indicated that dairy producers could select cows for increased Ig and Lf production using DHI data directly.

Introduction

Mammary secretions and the mammary gland have major roles in immune defense. These antimicrobial properties of milk can be attributed to substances such as proteins, lipids, and vitamins (Benkerroum et al., 2004). Immunoglobulins (Igs), together with lactoferrin (Lf), lactoperoxidase and lysozyme form the very important antimicrobial system of bovine lacteal secretions. Immunoglobulins in milk have a multitude of functions including opsonization, complement fixation, prevention of adhesion of pathogenic microbes to endothelial lining, inhibition of bacterial metabolism by blocking enzymes, agglutination of bacteria and neutralization of toxins and viruses (Marnila and Korhonen, 2002). Lactoferrin has demonstrated potent antiviral, antifungal and antiparasitic activity, towards a broad spectrum of species (Jenssen and Hancock, 2009). It can inhibit bacteria by chelating iron, kill certain bacterial strains directly, or may weaken bacterial resistance by adhesion to the surface of bacteria (Bellamy et al., 1992). Thus, the immunoglobulins and Lf in milk have potential beneficial applications in human and animal healthcare and improved secretion or production in milk is an important area of research.

The Dairy Herd Improvement (DHI) data is very important for the dairy industry, because these data provided can assist dairy farmers in making selection and management decisions. However, few studies have examined the relationship between DHI data and milk Ig and Lf concentrations. Canonical correlation analysis as a classical tool in statistical analysis is typically used to examine the potential relationships between two multivariate data sets (SAS Institute, 1999). The objective of this research was to assess the relationship between DHI data and milk compositions, with an emphasis on milk Ig and Lf concentrations, using canonical correlation analysis.

Section snippets

Cows and DHI data

The study animals were 299 Chinese Holstein cows that were randomly chosen from more than 1600 animals in four dairy farms in the greater Beijing area. The farms that all belonged to Beijing Sanyuan Group Co., Ltd had the same breeding and management programs. All the cows, none of which had any sign of mastitis, were housed in the same type of free stall barns. All the cows were fed three times daily the same Total Mixed Ration (TMR) mixed at one location. The DHI data, including daily milk

Results and discussion

The milk Lf concentration was found to be positively correlated with lactation number (r = 0.163, P < 0.05), stage of lactation (r = 0.372, P < 0.01) and had a negative correlation with daily milk production (r =  0.333, P < 0.01) (Table 1). These results were consistent with the results reported by Harmon et al., 1975, Hagiwara et al., 2003. Milk Lf concentration tended to be proportional to the level of the SCS and was significantly higher in the milk from subclinical mastitis cows than from

Acknowledgments

This work was partly supported by Ministry of Science and Technology grants (2006BAD04A03; 2006DFB32160, 30871837), P. R. China. We are very grateful to Prof. Richard O. Kellems of Brigham Young University and Prof. ZhongtangYu of The Ohio State University for their assistance in the preparation of this manuscript.

References (14)

There are more references available in the full text version of this article.

Cited by (8)

  • Canonical correlation of technological innovation and performance in sheep's dairy farms: Selection of a set of indicators

    2019, Agricultural Systems
    Citation Excerpt :

    According to Toro-Mujica et al. (2015) indicators are used to a) anticipate and evaluate trends; b) provide advanced information to prevent damages; c) formulate strategies y d) support the decision making process. In the selection of a set of technological indicators, operational aspects, easy to obtain and simple to implement, must be considered (Liu et al., 2010; Mu et al., 2017). Besides, the protocol to collect information in the farm must be cooperative and based on the consensus with producers and rest of the agents that take part in the value chain (FAO, 2014).

  • A proteomics-based identification of putative biomarkers for disease in bovine milk

    2016, Veterinary Immunology and Immunopathology
    Citation Excerpt :

    Unfortunately, data on the cows‘ energy status was lacking in our study and a significant association between LF levels in milk and periparturient diseases was not observed (data not shown). In contrast to other studies, no association was observed between LF levels in milk and SCC (Chaneton et al., 2013; Cheng et al., 2008; Liu et al., 2010). However, we selected for cows with SCC below 250.000 cells/ml and excluded cows with annotations in the disease registration data in the month before and after sampling, thereby excluding an association with mastitis.

  • Association of polymorphisms of beta-2-microglobulin gene (β2m) with milk IgG1 content in Chinese Holstein dairy cows

    2012, Livestock Science
    Citation Excerpt :

    Consequently milk IgG levels are becoming increasingly important as new IgG enhanced milk products are being developed (Larson et al., 1980; Marnila and Korhonen, 2002). Concentration of IgG1 in milk has been shown to be influenced by a variety of factors, including genetic effects, hormonal regulation, age at calving, parity, nutritional status, premature parturition and stage of lactation (Liu et al., 2009, 2010). In fact IgG1 can be selectively transferred from serum into milk by a Fc receptor (FcRn) mediated mechanism found in mammary gland secretory epithelium (Anderson et al., 2006).

View all citing articles on Scopus
1

Guanglei Liu and Chunlin Zhang contributed equally to this work.

View full text