Effects of glandular bacterial infection and stage of lactation on milk clotting parameters: Comparison among cows, goats and sheep

Abstract

Effects of glandular bacterial infection and stage of lactation on milk quality were compared among cows, goats and sheep. These parameters affected milk quality in all three species: sheep were most affected by bacterial infection and goats by stage (particularly end) of lactation. The study highlighted the effectiveness of lactose level as a predictor of milk quality; in all three species, the correlation between lactose level and curd firmness (CF) was higher than those between casein as a percentage of total protein and CF, or between somatic cell count and CF. In all three species, lactose concentrations ≤4% were associated with non-clotting milk. A model that describes the simultaneous and close association between reductions in lactose concentration and milk yield, on the one hand, and reductions in lactose concentration and milk quality on the other hand, is presented.

Introduction

High-quality raw milk constituents are required to obtain high yields and good quality of dairy products such as yoghurt and cheese. However, there are variations in milk yield and composition, not only between, but also within species, because of diversity among genotypes, management practices, stage of lactation, etc., and also interactions among these factors. One of the most common problem influencing production in dairy animals is mastitis, in both its clinical and its subclinical forms (Halasa et al., 2007, Leitner et al., 2004a, Leitner et al., 2006, Leitner et al., 2004b). Subclinical mastitis, which is generally unnoted, results in impaired quality of milk intended for yoghurt and cheese production (Forsback et al., 2009, Merin et al., 2008). Nevertheless, cows with subclinical mastitis are frequently associated with moderate increase in somatic cell counts (SCCs) (Auldist et al., 1996, Lindmark-Mansson et al., 2006) and thus may contribute to overall lower quality of bulk tank milk, which indicates that SCC level is not a predictive factor for quality in milk with low SCC (Forsback et al., 2010, Leitner et al., 2008b). It is rare that all the glands of a given animal are subclinically infected with bacteria. Therefore, it could be worthwhile to separate the low-quality milk obtained from individual infected glands, because this may be of economic importance in modern dairy farming, in which milk payment is dependent on bulk milk SCC (Forsback et al., 2010).

Another major factor that affects milk quality is stage of lactation: milk composition changes markedly during lactation, with regard to its basic components, micelle structure, and salt equilibrium and, consequently, its technological and physicochemical properties (Coulon, 1994, Lucey and Fox, 1992). Thus, these changes affect the yield and quality of the resulting cheese (Kefford et al., 1995, Lucey, 1996). Early-lactation milk tends to have good coagulability by rennet (White & Davies, 1958) whereas, in contrast, late-lactation milk is considered less suitable for cheese manufacture, mainly because of defects in syneresis of the curd (O’Keeffe, 1984).

Many of the animals that carry subclinical chronic infections or are close to the end of the lactation are not identified because there are no recognizable symptoms and the milk appears normal. Routine milk testing, such as California mastitis test (CMT) on the farm or more advanced laboratory techniques such as use of sophisticated cell counters enable identification of subclinically infected animals soon after they acquire the infection. However, these methods are laborious and/or require special equipment; also, in many cases, they identify the infected animals long after they become infected. Thus, the possibility of taking a real-time rational decision to separate low-quality milk would depend on availability of on-line technology to recognize such changes.

Modern dairy farms are characterized by a high level of computerized data acquisition, which provides on-line information on each cow’s milk yield, milk composition etc. (Katz et al., 2007). In particular, the AfiLab milk analyzer provides information on SCC, lactose, and total protein. This information has been found to be relevant in classifying the quality of milk at the individual gland and the whole animal udder level, with regard to milk clotting properties and cheese production (Leitner et al., 2004a, Leitner et al., 2004b, Merin et al., 2008).

The aim of the present study was to evaluate the influence of the stage of lactation and udder condition on milk quality by defining the influence of SCC and milk constituents on milk clotting parameters. It comprised a comparative study that addressed cows, goats, and sheep.