Feasibility of Manufacturing a Variety of Soft Cheeses from Milk Separated According to its On-Line Measure of Curd Firmness from Large Sized Commercial Dairy Farms

The modern dairy industry produces a variety of products including drinking milk, fermented products and a large variety of cheeses. Thus, animal breed, nutrition and management do not focus on production of specific or product-designated milk, but rather on maximizing milk volume to maximize revenue in respect to existing payment schemes. The major responsible factors that affect low quality of cheese-milk is associated with tramammary infection with different bacteria species, post intramammary infection, days in milk, stage of lactation, i.e., late or early lactation and estrus [1-3]. However, other factors such as non coagulating milk were also associated with low quality milk for cheese making. It was reported that about 8% and 13% of Finnish Ayrshire cows produced non coagulating milk owing to various genetic traits [4,5]. Moreover, studies showed that about 8-9% of milk samples that did not coagulate and that 17-20% of the milk coagulated poorly due to κ-casein and β-lactoglobulin genotypes [6] and that 2% of Danish Holstein and 16% of Swedish Red cows were classified as producing non coagulating milk, which was due to various genotypes [7].

In recent years our team has introduced and presented experimental results on the potential on-line segregation of milk for cheese manufacturing according to its coagulation properties without any addition or alteration of the milk [8,9]. In a later publication, we have discussed the options of making cheese from milk separated in different ratios [10] and recently, we further presented the higher cheese yields obtained from separated milk and discussed the validation of van Slyke's yield equation for calculating cheese yield by the dairy industry [11].The main results have shown that the level of milk constituents changes throughout the milking session along with the milk's coagulation properties. Installing the on-line milk channeling system (Afimilk MCS, Afimilk, Afikim, Israel) enabled separation of milk according to its measured coagulation properties (Afi-CF) and made it possible to divert high-clotting milk into a designated tank and thus to increase cheese yield [10,11]. The Afmilk MCS system is installed in every stall in the milking parlor and segregates every 200 mL pull into high- or low-clotting milk with the cutoff level being decided according to the volume and products to be later produced by the dairy. The system relies on a set of two reception raw milk tanks that are fed by two separated milk lines [8,9]. Despite the need for higher volumes of water and additional labor to handle, clean and haul the milk of the AfiMilk MCS system, economical calculations performed, show a major saving in the total energy consumption owing to higher cheese yield [12].

The current work presents data that show the feasibility of manufacturing a variety of cheeses on a large scale from milk segregated for increased cheese yield. Since the process and yield data are the propriety of the dairy (which was not released to us), only the result of the skimmed milk cheese prepared according to the dairy manufacturing protocol and the protein efficiency for Cottage cheese (5%) or an Israeli variety of soft cheese with 5% or 16% percent fat are presented, in addition to results of cheese made from the same milk on a laboratory scale.

Farms and milk collection

Study layout

Experiment 1

Experiments 2 & 3

Cheese making at the laboratory (Laboratory cheese)

A univariate model was designed with a logistic model statement using the MIXED procedure of SAS [14], with result outcome as the dependent variable. Three experiments were conducted. The first experiment was analyzed in four steps: 

a) The independent variable MROUND levels of percent separation (20,30,40,50,60) was analyzed using data from HCM group (n=574) of milk type with the general form: dependent variable (fat, protein, lactose, SCC (x10³, % casein (percent casein from protein), RCT, CF60)=Mround + error.
b) The independent variable Mround levels of percent separation (40,50,60,70&80) was analyzed using data from LCM group (n=574) of milk type with the same model as above. 
c) The entire data set (n=686 + 574 +574) was analyzed for differences between milk type groups in all variables using the model described above. Two models were conducted: the 1^st analyzed the differences for all variables using data from HCM and NSM group milk type and the 2^nd analyzed the differences for all variables using data from LCM and NSM group milk type.

A second experiment analyzed the pasteurized skimmed milk prepared by the dairy for Cottage cheese (5%), in two steps: 

A) The independent variable of percent on-line separation (30,40,50) was analyzed using data from HCM group milk type (n=120), with the general form: dependent variable of milk (fat, protein, lactose, SCC (x10³), % casein, RCT, RCT+Ca, CF60, CF60+Ca, curd at 1h and curd at 24h (% moisture, dry matter (g)) or protein efficiency=levels of percent separation (30,40,50) + error.
B) The entire data set (n=208) was analyzed for differences between HCM and NSM, separately for 2013 and 2014, for all variables described in step A by using the model described in the first experiment.

The third experiment analyzed the pasteurized skimmed milk prepared by the dairy for each type of soft cheese with various percent fat; i.e., 5% or 16%. The dependent variable in pasteurized milk (fat, protein, lactose, SCC (x10³), % casein, RCT, RCT+Ca, CF60, CF60+Ca, curd at 1h and curd at 24h (% moisture, dry matter (g)) and protein efficiency were analyzed for differences between HCM of percent separation(40) (5% fat, n=24; 16% fat, n=32) and NSM (5% fat, n=19; 16% fat, n=28) using the model described in the first experiment. Other parameters in the study such as farm and amount of milk in batch were found with no significant effect and thus removed from the final model. Results are presented as LSmeans + SEM. Protein efficiency was calculated as: (0.83 x % protein in milk)/(1-% dry matter)/100).

Experiment 1

 Figure 1: Distribution of the protein of the collected bulk milk according to Non-Separated Milk (NSM - Δ) and separated high- (HCM - ?) and low-clotting milk (LCM - O).

Experiment 2

Experiment 3

Raw milk is produced to fit average production schemes rather than to maximize a specific product, since milk is used for a variety of products with different protocols of industrial manufacturing. For example, high level of protein in drinking milk is redundant vs. low level of protein in milk for cheese making, which leads to low cheese yield. In modern intensive dairy farms, milk is produced economically when genetics and management maximize milk yield and sold milk volume. Nevertheless, genetic variability among cows, time in lactation, time of milking and milk flow during milking have a great influence on milk constituents. By installing the AfiMilk MCS system that enables separating milk according to its coagulation properties, it was possible to divert part of the milk into a designated tank and thus to increase cheese yield [10,11]. In the first experiment, the AfiMilk MCS system performed at a high efficacy in separating the milk to the pre-decided cutoff level. Unlike earlier results [11] no significant differences in all the parameters tested were found in HCM or LCM milk according to the separation level, except for CF60 in HCM20, which was significantly higher than other HCM levels. The difference was probably related to the number of AfiMilk MCS units, the environment and management differences among farms and time of milk collection during the two years. On the other hand, fat, protein and CF60 in all the HCM target tanks were significantly higher (P<0.001) than in NSM and in all the LCM target tanks these same parameters were significantly lower (P<0.001) than NSM. Other parameters such as % casein, lactose and SCC did not differ significantly from NSM, indicating that the separation is directly related to fat and protein levels but not to the milk quality, which is related to non- and low-clotting milk etc. [4-7]. Percent casein is the calculation of casein from total protein; therefore, higher protein with similar % casein means higher casein in HCM. Thus, as shown and discussed earlier [11], it is possible to increase dairy cheese production yield by utilizing the same animals and volume of milk for higher profitability. It could be visualized that by using milk channeling systems in large dairy herds for producing HCM and obtaining increased cheese yield per vat volume could result in reducing the number of cows in the herds for producing the same tonnage of cheese.

Many of hard and soft cheeses are prepared from pasteurized milk after skimming the milk to a desired degree of fat to protein ratio. Moreover, in many products, powdered milk or ultrafiltration retentatesare added in order to increase protein content, which results in added costs of concentration and drying [15,16]. Implementation of advanced technological systems, such as the AfiMilk MCS in milking parlors, modifies not only the on-farm management but mostly the procedures practiced by the cheese making plant. Using targeted HCM enables the dairy factory that produces traditional cheeses to skip the standardization of the production formula and only to reduce the fat level in the cheese milk. These modifications broad about ~44% saving of energy usage and ~69% of the carbon dioxide emissions [12]. 

Due to the limitations of dairy intellectual property, the results of Cottage cheese (5%) (2nd experiment) or soft cheeses with various percent fat: 5% or 16% (3^rd experiment) are those to the laboratory tests, including laboratory cheese (48 h) produced from milk prepared by the dairy. The extra protein efficiency calculated by the dairy for the final products is also presented. In the second and third experiments, protein, CF60 and the weight of curd were significantly higher in all the HCM milk preparations for the three chesses. As a result, the calculation of the protein efficiency in the laboratory tests (+5%) as well as in the extra protein efficiency of the dairy final product was significantly higher (+7-12%). These results indicate that the potential benefit of the separated milk is manifested in a verity of products with different milk separation levels as was shown by Todde et al. [12].

The AfiMilk MCS system opens new avenues for cheese production plants. Despite the need of installing a second parallel milk line and an additional reception tank, the increased cost of milk hauling and milking parlor cleaning costs diminish when compared to the additional income from the increased cheese yield. As was summarized in regard to the whole scheme: “The implementation of PLF (Precision Livestock Farming) technologies increased energy requirement and carbon dioxide emissions in dairy farms and in the collection of milk, however, the large amount of energy saved in the cheese factory and the increase in cheese production yield make these technologies respectful to the natural resources and to the environment, avoiding about 2.65 MJ of primary energy for every 100 kg of processed milk” [12]. The essence of segregating milk on-line according to its composition and properties opens a new era of transition to dairy farms that produce high value-added product made of the same raw milk, while are also promising in the possibility of reducing the number of animals grown for the same cheese tonnage production.

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