Calcium: A comprehensive review on quantification, interaction with milk proteins and implications for processing of dairy products

✅ 全文

钙：关于其定量分析、与乳蛋白的相互作用及其对乳制品加工影响的综述

作者 Giovanni Barone; Saeed Rahimi Yazdi; Søren K. Lillevang; Lı́lia Ahrné 期刊 Comprehensive Reviews in Food Science and Food Safety 发表日期 2021 ISSN 1541-4337 DOI 10.1111/1541-4337.12844 类型原创研究 (Original Research)

📄 中文摘要 Chinese Abstract

中文

钙（Ca）是一种对人体健康至关重要的微量营养素，尤其在骨骼形成中发挥关键作用。乳制品因其高钙含量和生物利用度而成为主要的膳食钙来源。在牛乳中，钙以多种形态存在——离子态（Ca²⁺）、与柠檬酸根或磷酸根络合，或以胶体磷酸钙（CCP）形式结合——并在胶体（胶束）相与血清相之间动态分配。这种分配受pH值、温度、离子强度和加工条件的影响，进而影响乳制品的理化性质、蛋白质相互作用以及整体加工性能。

📋 英文结构化总结 English Structured Summary

全文整理

Background:

Calcium (Ca) is an essential micronutrient critical for human health, particularly in bone formation, and dairy products are a primary dietary source due to their high Ca content and bioavailability. In bovine milk, Ca exists in multiple forms—ionic (Ca²⁺), complexed with citrate or phosphate, or bound as colloidal calcium phosphate (CCP)—and partitions dynamically between the colloidal (micellar) and serum phases. This partitioning is influenced by pH, temperature, ionic strength, and processing conditions, affecting milk’s physicochemical properties, protein interactions, and overall processability during dairy manufacturing.

Methods:

N/A – Review article. The paper synthesizes existing literature on Ca in dairy systems, covering phase separation techniques (e.g., ultracentrifugation, ultrafiltration, dialysis, acidification), analytical methods for quantifying total and ionic Ca (including titration, ion-selective electrodes, ion-exchange chromatography, AAS, ICP-OES, XRF), and approaches to study Ca–protein interactions (such as DSC and ITC). It also reviews how processing parameters alter Ca speciation and distribution.

Results:

The review highlights that Ca speciation—especially the balance between ionic Ca²⁺ and CCP—is highly sensitive to processing steps like heating, cooling, acidification, and concentration. For example, heating reduces serum-phase Ca by promoting CCP formation, while acidification solubilizes CCP, increasing ionic Ca in the serum. Analytical challenges arise from matrix effects; for instance, proteins interfere with AAS unless removed, and ion activity (aCa²⁺) must be distinguished from concentration ([Ca²⁺]) using ionic strength corrections. Techniques like ITC reveal that Ca binding to whey proteins is entropically driven and occurs via charge neutralization, aggregation, and Ca²⁺-bridging mechanisms.

Data Summary:

Total Ca in liquid milk ranges from ~1010 to 1922 mg/L depending on the analytical method (e.g., titration: 1010–1360 mg/L; ICP-OES: 1078–1922 mg/L; AAS: 1118–1461 mg/L). Ionic Ca ([Ca²⁺]) in milk is typically 1.07–2.60 mM, with activity (aCa²⁺) around 0.42–1.00 mM at pH 6.2–7.0. In cheeses, total Ca varies widely (570–1700 mg/100 g), and ionic Ca ranges from 0.85 to 1.52 mM. Milk powder ingredients contain 882–1506 mg Ca/100 g (ICP-OES) or 1272–1350 mg/100 g (ICP-MS).

Conclusions:

Understanding Ca partitioning and speciation is crucial for optimizing dairy processing, improving product functionality (e.g., heat stability, texture, yield), and minimizing losses such as fouling or sedimentation. Accurate quantification requires method selection based on sample type and required specificity (total vs. ionic Ca). The dynamic equilibria between Ca forms are central to both nutritional quality and technological performance of dairy products, necessitating integrated kinetic models for process control.

Practical Significance:

This knowledge enables the dairy industry to fine-tune processing parameters (e.g., temperature, pH, filtration) to enhance product quality, reduce waste, and develop value-added, Ca-fortified dairy products with improved stability and functionality, directly supporting innovation in functional foods and infant nutrition.

📋 中文结构化总结 Chinese Structured Summary

中文

背景:

方法:

不适用——综述文章。本文综合了现有关于乳制品体系中钙的文献，涵盖相分离技术（如超速离心、超滤、透析、酸化）、总钙和离子钙的定量分析方法（包括滴定法、离子选择性电极法、离子交换色谱法、原子吸收光谱法、电感耦合等离子体发射光谱法、X射线荧光光谱法），以及研究钙-蛋白质相互作用的方法（如差示扫描量热法和等温滴定量热法）。本文还综述了加工参数如何改变钙的形态和分布。

结果:

本综述强调，钙的形态——尤其是离子态Ca²⁺与CCP之间的平衡——对加热、冷却、酸化和浓缩等加工步骤高度敏感。例如，加热通过促进CCP的形成而降低血清相中的钙含量，而酸化则溶解CCP，增加血清中的离子钙。分析挑战源于基质效应；例如，除非去除蛋白质，否则蛋白质会干扰原子吸收光谱法的测定，且必须通过离子强度校正来区分离子活度（aCa²⁺）与浓度（[Ca²⁺]）。等温滴定量热法等技术揭示了钙与乳清蛋白的结合是熵驱动的，并通过电荷中和、聚集和Ca²⁺桥接机制发生。

数据摘要:

液态乳中的总钙含量因分析方法不同而异，范围为约1010～1922 mg/L（如滴定法：1010～1360 mg/L；ICP-OES：1078～1922 mg/L；AAS：1118～1461 mg/L）。乳中的离子钙（[Ca²⁺]）通常为1.07～2.60 mM，在pH 6.2～7.0条件下，活度（aCa²⁺）约为0.42～1.00 mM。在奶酪中，总钙含量变化较大（570～1700 mg/100 g），离子钙范围为0.85～1.52 mM。乳粉原料含钙量为882～1506 mg/100 g（ICP-OES）或1272～1350 mg/100 g（ICP-MS）。

结论:

理解钙的分配和形态对于优化乳制品加工、改善产品功能特性（如热稳定性、质地、得率）以及减少结垢或沉淀等损失至关重要。准确测定需要根据样品类型和所需特异性（总钙与离子钙）选择合适的方法。钙形态之间的动态平衡是乳制品营养品质和技术性能的核心，需要建立综合动力学模型以实现过程控制。

实践意义:

这些知识使乳制品行业能够精细调控加工参数（如温度、pH值、过滤），以提升产品质量、减少浪费，并开发具有改善稳定性和功能特性的高附加值钙强化乳制品，直接支持功能性食品和婴幼儿营养领域的创新。

📖 英文全文 English Full Text

Received: 31 March 2021 Revised: 1 September 2021 Accepted: 2 September 2021

DOI: 10.1111/1541-4337.12844 C O M P R E H E N S I V E R E V I E W S I N FO O D S C I E N C E A N D FO O D SA F ET Y

Calcium: A comprehensive review on quantification, interaction with milk proteins and implications for processing of dairy products

Giovanni Barone1 Saeed Rahimi Yazdi2 Søren K. Lillevang2

Lilia Ahrné1 1 Department of Food Science, Ingredients and Dairy Technology, University of

Copenhagen, Frederiksberg, Denmark 2 Arla Foods Amba, Aarhus N, Denmark

Correspondence Lilia Ahrné,Department of FoodScience,

Ingredients andDairy Technology,Univer- sity of Copenhagen,Rolighedsvej 26,1958,

Fredericksberg,Denmark.

Email:Lilia@food.ku.dk Abstract Calcium (Ca) is a key micronutrient of high relevance for human nutrition that also influences the texture and taste of dairy products and their processability.

In bovine milk, Ca is presented in several speciation forms, such as complexed with other milk components or free as ionic calcium while being distributed between colloidal and serum phases of milk. Partitioning of Ca between these phases is highly dynamic and influenced by factors, such as temperature, ionic strength, pH, and milk composition. Processing steps used during the manufac- ture of dairy products, such as preconditioning, concentration, acidification, salt- ing, cooling, and heating, all contribute to modify Ca speciation and partition, thereby influencing product functionality, product yield, and fouling of equip- ment. This review aims to provide a comprehensive understanding of the influ- ence of Ca partition on dairy products properties to support the development of kinetics models to reduce product losses and develop added-value products with improved functionality. To achieve this objective, approaches to separate milk phases, analytical approaches to determine Ca partition and speciation, the role of Ca on protein–protein interactions, and their influence on processing of dairy products are discussed.

K E Y WO R D S Dairy | Calcium, Quantification, Processing, Protein-calcium interactions

1 INTRODUCTION Calcium (Ca) is considered an essential nutritional micronutrient for the development and maintenance of skeletal tissue during the life cycle, as together with phos- phate, it can form hydroxyapatite (Ca10(PO4)6(OH)2), the main component of human bones (Bonjour, 2011). Dairy products are considered the ideal vehicle for achieving sufficient daily dietary intake of Ca. This is due to the highly complex dairy products composition containing macro- and micro-nutrients that enhance Ca bioavailabil- ity (Christensen et al., 2009; Skibsted, 2016). Generally, Ca in bovine milk (∼1200 mg kg−1; 29.4 mM) is partitioned between two phases, two-third in the colloidal phase (∼800 mg kg−1; 20 mM) and the rest in the serum phase (∼400 mg kg−1; 9.4 mM), respectively (Gaucheron, 2005). The prin- cipal colloidal constituent, caseins, can bind Ca (and gen- erally cations) in their phosphoserine cluster residues in this order αs2 > αs1 > β > κ-casein, due to different levels of phosphorylation and number of ester groups present in each specific casein (O’Mahony & Fox, 2013).

Ca in the colloidal phase is primarily associated with phosphate and forms the so-called colloidal Ca phosphate (CCP; Ca3(PO4)2), having an average diameter of ∼2.5 nm.

15414337, 2021, 6, Downloaded from https://ift.onlinelibrary.wiley.com/doi/10.1111/1541-4337.12844 by Tsinghua University Library, Wiley Online Library on [04/11/2022]. See the Terms and Conditions (https://onlinelibrary.wiley.com/terms-and-conditions) on Wiley Online Library for rules of use; OA articles are governed by the applicable Creative Commons License calcium in dairy products ⋯

5617 It is well established that CCP acts as the “building blocks” of casein micelles to reassemble the rheomorphic struc- ture of caseins in a supramolecular structured rearrange- ment called casein micelles (Holt, 1997; De Kruif et al.,

2012). However, in dairy products, CCP has a very complex structure, as it can have different stoichiometry with phos- phate (e.g., Ca/phosphate ratio) and different structure, such as amorphous or crystalline, thereby resulting in a different extent of interaction with phosphoserine residue of caseins (McGann et al., 1983; Xu et al., 2016). In the serum phase, Ca can be divided in complexed (chemically bounded) and free in ionic form (Ca2+), but precipitation can occur under some conditions. At pH of milk (∼6.70),

Ca primarily forms complexes with citrate (∼8.2 mM in serum; pKa3 = 6.40; Cit2−↔Cit3−), followed by inorganic serum phosphate (pKa2 = 7.20; H2PO4−↔HPO42−) and chloride (Gaucheron, 2005; Koutina et al., 2014). The low content of Ca in the serum phase, when compared to the colloidal phase of bovine milk, is attributable to these salts having low solubility, especially Ca phosphate, which has an inverse solubility namely, more soluble at low temper- atures. Therefore, when temperature increases, Ca pre- cipitation is often observed at typical heating processing conditions (Kezia et al., 2017). Serum proteins (whey pro- teins) can bind Ca as well, such as α-lactalbumin, which can bind Ca in a specific Ca-binding pocket located in the intramolecular structure, forming a Ca-protein complex with a stoichiometry value of N = 1 (Hendrix et al., 2000).

The noncomplexed free Ca in the serum phase of milk is in the ionic form ([Ca2+] = 1.5–2.5 mM). However, their charges are often shielded by anions (e.g., chloride), with a small subset having no shield of charge, often called ionic

Ca activity, whose concentration is strongly depended on the ionic strength (Jiang et al., 2021). It is essential to high- light that although [Ca2+] represents a tiny fraction of the total Ca in bovine milk, it has a complex relationship with

CCP of milk, and thus small changes in its equilibria can result in marked changes in the physicochemical proper- ties of milk (Christiansen et al., 2020; M. J. Lewis, 2011).

In relatively simple terms, the equilibrium of [Ca2+] and phosphate in bovine milk can be described by Equation 1:

3Ca2+ + 2HPO2− 4 ↔Ca3(PO4)2 ↓+ 2H+ (1) In agreement with Equation 1, [Ca2+] concentration increases by: (1) adding hydrogen ions (e.g., acidification process of milk, due to CCP solubilization); (2) adding sol- uble calcium salts (e.g., fortified dairy products), and (3) decrease in temperature due to the inverse solubility prop- erties of phosphate (more soluble at low temperatures).

Milk is not fluid in thermodynamic equilibrium, as many reactions, especially those involving Ca, are in a metastable state (Wang et al., 2020). For example, the amount and speciation form of Ca in the serum and colloidal phases of milk are influenced by several environ- mental conditions. Such conditions are often encountered during the processing of dairy products, that is heating, cooling, pH changes, salts addition, and fractionation or concentration by membrane filtration. Ca-phosphate represents the major component of total Ca in bovine milk (both organic and inorganic, associated with caseins and in the serum phase, respectively). Depending on envi- ronmental factors (mainly pH and temperatures), it can dissociate or re-associate thus influencing [Ca2+] levels in the two phases. To better understand Ca-phosphate in bovine milk, the dissociation properties such as the function of temperature and pH have been studied using a relatively simple mineral solution, simulated milk ultra-filtrate (SMUF) (Dumpler et al., 2017; Kezia et al.,

2017; Little & Holt, 2004; Mekmene et al., 2010; Tanguy et al., 2016). In bovine milk and during processing, the complexity dramatically increases as several reactions co-occur with different orders of response, which have not been fully investigated. Overall, it is known that cooling increases Ca phosphate solubility, thereby increasing the total Ca content in the serum phase. In contrast, heating, at a temperature equal to, or higher than, 60◦C caused Ca content to increase in the colloidal phase, and consequently decreasing in the serum phase, as well as a decrease in milk pH, due to hydrogen ions released from the phosphate (Anema, 2009; Schmitt et al., 1993; Wang

& Ma, 2020). Acidification of milk, essential to produce acid curd, solubilize CCP causing a significant increase of Ca in the serum phase, mostly in ionic form (Salaün et al., 2005); however, the acidification kinetics at different temperatures are still poorly investigated.

Therefore, it is highly challenging to determine the Ca content in dairy products due to the partition and spe- ciation of Ca between the colloidal and serum phases of milk. However, understanding of the dynamics and kinet- ics of Ca along with its interactions with dairy proteins is essential for three main reasons: (i) the physicochemical properties of milk and dairy products (e.g., heat stability, viscosity, texture, and techno-functionality) are remark- ably dependent on the Ca speciation form (i.e. ionic and complexed); (ii) the content of Ca in the serum and asso- ciated with caseins is affected by processing and influ- ences processability (e.g., fouling, viscosity, and curd yield) as well as storage (e.g., gelation, sedimentation, and floc- culation); (iii) dairy proteins can interact with different forms of Ca that impair nutritional value and functionality.

Thus, understanding these interactions can be exploited to reduce product losses by fine-tuning adjustments of processing parameters (e.g., filtration and drying) and develop added-value products with improved functional- ity or tailored applications (e.g., Ca-fortified dairy-based

5618 calcium in dairy products ⋯ products) (Barone et al., 2020a; Barone, O’Regan, et al.,

2020; Joyce et al., 2017; Jeurnink et al., 1996; Pandalaneni et al., 2018).

The impact of Ca on the physicochemical characteristics of milk and dairy products has been the scope of several studies for many years (Barone et al., 2020a; Davis et al.,

2001; Herwig et al., 2011; Kindstedt & Kosikowski, 1985; M.

Lewis et al., 2011; Ntailianas & Whitney, 1964; Pandalaneni et al., 2018; Robison & Hlynka, 1947; Sood et al., 1979; Sem- mons & McHenry, 1946; Thybo et al., 2020; Wu et al., 2012).

Massotti et al. (2020) reviewed the analytical advances in determining calcium in bovine milk and dairy products.

However, to the authors’ knowledge, a comprehensive review regarding Ca content, dynamics of partitioning between colloidal and serum phases, its interactions with dairy proteins, and implications for the processing of dairy products has not been reported in the literature. This review aims to provide a better understanding of the key factors affecting calcium partition and speciation in milk to support the development of kinetics models to reduce product losses and develop added-value products with improved functionality. The review includes a discussion about the importance of Ca in bovine dairy systems by emphasizing quantification methods, interaction with dairy proteins, and implications of Ca partitioning during the processing of dairy products.

2 BACKGROUND From the early 1930s until the 1960s, researchers were interested in how Ca and milk minerals generally influ- enced casein micelles structure (Fox & Brodkorb, 2008). It was of high interest, and still is, how the partitioning of milk salts, including Ca, influences physicochemical prop- erties during common processing practices. For example,

Fox and Hoynes (1975) investigated the influence of dif- ferent CCP content on the heat stability of milk at differ- ent pHs. They found that removing 40% of CCP resulted in a very high heat stable milk, in contrast to 60% of CCP removal, which impaired the heat stability of milk at every pH used. Holt (1982) studied the mineral profile of CCP, demonstrating that the ratio Ca: phosphate is ∼1.60; it was also showed that CCP contained trace amounts of cit- rate (CCP: citrate ∼0.1). Holt and Muir (1979) found that an inversely proportional relationship between ionic Ca [Ca2+], and citrate content was shown in bovine milk, thus highlighting the importance of citrate content in the equi- libria of [Ca2+] in the serum phase of milk.

Nowadays, standardized methods for quantifying Ca content in milk and dairy products are readily available to generate worldwide consistency of data by adopting the same procedures. International bodies such as Inter- national Dairy Federation (IDF), the International Orga- nization for Standardization (ISO), and AOAC Interna- tional (AOAC) develop, validate, and publish such meth- ods. Indeed, Poitevin (2016) reviewed such official meth- ods for determining major (Ca included) and minor min- erals in dairy matrices. Furthermore, Masotti et al. (2020) examined and criticized some of the current methods for quantifying Ca in dairy products and dairy-based nutri- tional products.

3 APPROACHES FOR SEPARATING MILK PHASES The partition of Ca between colloidal and serum phases influences milk physicochemical properties and process- ability. The main constituents of the colloidal phase of milk are casein micelles, which is considered a high-hydrated supramolecular association of protein (caseins), with an average diameter of 150 nm and sterically repulsed at the surface level through the κ-casein “hairy layer” (Anema &

Klostermeyer, 1996; Corredig et al., 2019; Huppertz et al.,

2017; Zhao et al., 2015). In contrast, the main constituents of the serum phase are whey proteins, carbohydrates, and minerals. The major whey protein, such as β-lactoglobulin (β-lg) and α-lactalbumin (α-lac), compared to caseins, have a defined tertiary structure (globular), a smaller hydrody- namic volume (10–32 nm), and a lower molecular weight (18–14 kDa) (Foegeding et al., 2002; Joyce et al, 2018; Love- day et al., 2013).

The common used approaches for the separation of col- loidal and serum phases used in laboratory analytical pro- cedures or industrially in the manufacturing of dairy prod- ucts are (a) centrifugation, (b) filtration, (c) coagulation or acidification, and/or (d) combinations thereof. Separation by gravity often requires ultracentrifugation conditions, such as 50,000 g for 2 h but preferably 100,000 g for 1 h (De

La Fuente et al., 1996; ; Lundh, 1980; Pepper, 1972). Usually, after ultracentrifugation, a formation of compact sediment representing the colloidal phase of milk can be observed, while the obtained supernatant contains the principal con- stituents of the serum phase, including whey protein (Par- ris & Baginski, 1991; Lucey et al., 1998).

Separation using membrane filtration can be performed at both lab- and industrial-scale. Generally, UF (ultra- filtration) using a molecular weight cut-off (MWCO) less than or equal to 10 kDa is sufficient for retaining the colloidal phase and all the major whey proteins, while the permeate contains minerals, carbohydrates, nonpro- tein nitrogen, and peptides (Barile et al., 2009; Wong et al.,

1978). Besides, the UF temperature needs to be consid- ered as organic (CCP), and inorganic Ca-phosphate has inverse solubility, ultimately influencing Ca content in the permeate (Zulewska et al., 2018). For further removal of

5619 soluble components (e.g., minerals) from the colloidal to the serum phase of milk, dialysis can also be applied. It can be performed by membrane filtration at MWCO lower than 5 kDa followed by dilution with ultra-pure or distilled water. De La Fuente et al. (1996) determined the mineral profile of milk diffusate obtained after dialysis using a 3.5 kDa MWCO membrane following a 10 times fold dilution using distilled water. Although dialysis is relatively easy to implement at a labscale compared to other approaches, the time, temperature, and volume of water used significantly influence the mineral content of the resulting streams, including milk composition, if the volume used is higher than milk. Such variation is due to the re-equilibration between the Ca from the colloidal phase (CCP) and the diluent (water) as driven by different osmotic pressure (e.g., ionic strength of the diluent), temperature, and time (Brule & Fauquant, 1981; Roig et al., 1999).

Coagulation or acidification of milk for separating the colloidal and serum phases is commonly used in cheese production and can be achieved by (1) renneting or (2) direct acidification. Coagulation of milk by rennet addi- tion is an essential step in cheese making. It is caused by cleavage of κ-casein at Phe105 and Met106, resulting in decreased viscosity, and reduction of particle size diame- ter and decreased ζ-potential of casein micelles (Fox et al.,

2017). At the same time, the serum phase is being physi- cally separated from the curd material (which is often used as raw material for the production of whey-based ingredi- ents), although caseinomacropeptide is released after ren- neting in the serum phase, increasing the protein pro- file complexity of the serum phase (Svanborg et al., 2016).

However, renneting of milk does not always result in a con- sistent separation of the two milk phases in terms of com- positions and physicochemical properties due to intrinsic factors such as temperature, rennet addition content, and innate [Ca2+] (De La Fuente et al., 1996; Grassi et al., 2019).

The temperature of renneting considerably influences the rate of coagulation and rheological properties of the gels formed. Dalgleish (1983) and Horne and Lucey (2014) both examined the effect of temperature [Ca2+] and ionic strength on milk gels properties produced by renneting.

The results showed that at temperatures higher than 30◦C, the coagulation rate constant was higher compared to ren- net gels produced at lower temperatures. Such rate con- stants were positively influenced by increased [Ca2+], even at low temperatures. Indeed, the changes in [Ca2+] influ- enced by the incubation temperature showed that the acti- vation energy of gel formation was not linear. This means that the temperature influences the type of interactions (e.g., electrostatic interaction and hydrophobic attraction) between the fully-renneted casein micelles and Ca equilib- ria (mainly the dissociation constant of Ca-phosphate).

In contrast, acidification of bovine milk close to the isoelectric point of casein micelles (pI 4.60) results in κ-casein brush to shrink until collapsing when the pI is reached, thereby decreasing the ζ-potential of casein micelles toward neutrality (De Kruif, 1997). The decrease in ζ-potential increases proximity between casein micelles resulting in aggregation, which facilitates the separa- tion from the serum phase. However, phase separa- tion using acidification significantly increases the Ca content in the serum phase as CCP is solubilized in the serum phase during acidification (Koutina et al.,

2014).

Combinations of these methods can be applied for effi- cient separation of colloidal and serum phases, especially at a labscale level. For example, the formation of a consis- tent pellet using acidification is not achieved as the aggre- gates are primarily hydrated with incorporated residual serum phase, and centrifugation after acidification may therefore be recommended (Hekmat & McMahon, 1998;

Law & Leaver, 1998). A more suitable option, confined at a labscale level, is a combination of centrifugation and fil- tration using commercially available membrane filtration tubes having a target molecular weight cut off. The com- bination of accelerated gravity and filtration implied for these tubes can be advantageous for efficient phase sep- aration when small volumes are required (Barone et al.,

2020b).

4 ANALYTICAL APPROACHES FOR DETERMINING CALCIUM IN DAIRY

PRODUCTS 4.1 Physicochemical methods to determine calcium in dairy products

4.1.1 Titration methods Titrations methods for determining total Ca content in milk and dairy products have been used for more than a century (Barthel, 1910). Titration methods are inexpen- sive, easy to carry out, and can potentially be applied for preliminary study with a small set of equipment (e.g., burette and few reagents). Generally, quantification of total Ca by titration can be performed using complexomet- ric titrations with ethylenediaminetetraacetic acid (EDTA) as a chelating agent together with different indicators such as purpuric acid salt (murexide), erio-chrome blue

S E (solochrome), and 2-hydroxy-l-(2-hydroxy-4-sulfo-l- naphthylazo)-3-naphthoic acid known as Patton-Reeder indicator (Kindstedt & Kosikowski, 1985; Tessier & Rose,

1958).

5620 calcium in dairy products ⋯ F I G U R E 1 Structure of ethylenediaminetetraacetic acid (ETDA)-calcium complex and relative color changing of

Patton-Reeder indicator during calcium complexometric titration

There are two critical points for determining Ca con- tent in milk using the complexometric method: (1) affinity constants of EDTA and (2) endpoint color determination.

EDTA is known to chelate not only Ca but several met- als with a different affinity constant (Kf); Ca is chelated by

ETDA at stoichiometry value of N = 1 along with magne- sium (Mg), although it has a low content of ∼130 mg/L in milk (Figure 1). The LogKf of EDTA values for Ca and Mg are 10.6 and 8.79, respectively, (Broekaert, 2015); therefore,

ETDA can be partially saturated with Mg during titration, resulting in low accuracy for Ca determination. To mini- mize the influence of Mg, Bird et al. (1961) proposed to pre- cipitate all the Mg in milk by using alkali in order to form insoluble magnesium hydroxide before the addition of the indicator. However, to avoid alkali addition to the sam- ple, ethylene glycol tetraacetic acid (EGTA) can be used as Ca chelating agent. Compared to EDTA, it has a lower affinity for Mg (LogKf of 5.30), and it is more specific for ionic Ca (Ca2+) with a slightly higher affinity constant for it (LogKf of 11.0) (Smith & Miller, 1985). For example, Card- well et al. (1990) used EGTA to determine total Ca content in whole bovine milk, with a value of 1325 mg/L, with such value being in excellent agreement with the atomic absorp- tion spectroscopy method (1360 mg/L). Another point is the color changing of the indicator strictly dependent on operator eyesight, especially during the transition from an excess of Ca to almost complexed Ca, as in the case for murexide (purple to pink) and Patton-Reeder (pink to blue) (Figure 1). Tessier and Rose (1958) and Rose and

Tessier (1959) determined ionic Ca concentration [Ca2+] using murexide indicator of ultrafiltration milk permeates at different temperatures. They found [Ca2+] from 2.5 to

3.4 mM with low temperatures to have a high [Ca2+]. This range was overestimated when compared to other methods specific for [Ca2+] (e.g., ion-exchange and selective elec- trodes) (Table 1).

4.1.2 Selective ion electrodes The application of selective electrodes for determining Ca content is restricted to a liquid system such as milk or reconstituted dairy-based ingredients/products, including viscous systems. Selective Ca electrodes can be used only for determining ionic Ca concentration [Ca2+], as when

Ca complexed with other compounds in milk (e.g., citrate, phosphate) are not available to produce a relevant electric output (mV) specific for Ca2+.

However, selective ion electrodes produce a signal (mV) relative to the calibration solutions used, and thus the preparation of calibrating solutions having similar physic- ochemical properties of the sample (e.g., ionic strength, concentration, and pH) is crucial for good quality data.

Generally, a combination of imidazole and potassium chlo- ride is used as a buffer for preparing known [Ca2+] cal- ibrating fluids applicable for dairy liquid systems (M. J.

Lin et al., 2006). Compared to other Ca quantification approaches, the application of selective ion electrode is not invasive, not destructive (sample is not subjected to physicochemical modification), simple (only standard cal- ibrating solutions need to be prepared), and relatively inex- pensive (the price of equipment can vary from 800 to

7000 USD).

In electrochemistry, to determine the [Ca2+], the Nernst equation (Equation 2) is used to relate the reduction poten- tial of an electrochemical reaction to the standard elec- trode potential, temperature, and activities of the chemical species.

𝐸= 𝐸0 −𝑅𝐾 𝑧𝐹𝑙𝑛𝑄 (2) where E is reduction potential; E0 is standard potential; R is universal gas constant; K is temperature (kelvin); z is ion charge (2 for Ca); F is Faraday constant; and Q is reaction quotient.

Nernst equation implies that the activity of the species, such as Ca2+, is equal to its concentration. The difference in potential measured in millivolts (mV) from the selective electrode is generated from the cell, which is often made of a polymer (e.g., epoxy polymer) or solid-state (e.g., cation- glass). Geerts et al. (1983) estimated an increase of ∼29 mV for every 10 times [Ca2+] increase with this general rule still valid and used; indeed, a desirable calibration slope specifically for Ca2+ should be around 29 mV. It is impor- tant to discern [Ca2+] to its activity (aCa2+), as both may have been used interchangeably in the literature. [aCa2+] is a subset of the total [Ca2+] as detailed below (Equations 3 a–b): 𝑎𝐶𝑎2+ = 𝑦𝐶𝑎2+ × [

𝐶𝑎2+] (3a) 15414337, 2021, 6, Downloaded from https://ift.onlinelibrary.wiley.com/doi/10.1111/1541-4337.12844 by Tsinghua University Library, Wiley Online Library on [04/11/2022]. See the Terms and Conditions (https://onlinelibrary.wiley.com/terms-and-conditions) on Wiley Online Library for rules of use; OA articles are governed by the applicable Creative Commons License calcium in dairy products ⋯

5621 TA B L E 1 Total and ionic calcium values for a range of dairy products and the most commonly used analytical techniques for their determination

Product Technique Calcium content Reference (mg/L)

Total calcium Liquid milk Titration 1010–1360 Cardwell et al. (1990); Dolores Alvarez Jiménez et al. (1988)

ICP-OES 1078–1922 Murcia et al. (1999); Zwierzchowski and Ametaj (2019)

AAS 1118-1461 Cerbulis and Farrell (1976); ; Sowmya et al. (2015)

Milk powder ingredients (mg/100 g) ICP-MS 1272–1350

Chen and Jiang (2002); Herwig et al. (2011); Barone et al. (2020a)

ICP-OES 882–1506 McKinstry et al. (1999); Sikand et al. (2011)

AAS 960–1300 Noël et al. (2008); XFR 1070–1330 McCarthy et al. (2020)

Cheeses (mg/100 g) Titration 670–842 Kindstedt and Kosikowski (1985)

ICP-OES 570–1700 Bilandžić et al. (2015); Manuelian et al. (2017)

AAS 608–1107 Pollman (1991); Hassan et al. (2004) Ionic calcium

Liquid milk Molarity (mM) Titration 2.5–3.4 Rose and Tessier (1959)

Selective electrode 1.07–2.60 Augustin and Clarke (1990); M. J. Lin et al. (2006)

Ion-exchange chromatography 2.02–2.32 Christianson et al. (1954); Cataldi et al. (2003)

Cheeses Titration 0.85–1.52 Hassan et al. (2004); Wolfschoon-Pombo and

Andlinger (2013) Abbreviations: AAS, atomic absorption spectroscopy; ICP-OES, inductively coupled plasma-optical emission spectrometry; XFR, X-ray fluorescence; ICP-MS, inductively coupled plasma mass spectrometry. 𝑦𝐶𝑎2+ = log 𝑦2+ = −𝐴× 𝑧2 × ((

√ 𝐼 1 + √ 𝐼 ) −0.30 × 𝐼 ) (3b) where aCa2+ is ionic Ca activity concentration; yCa2+ is activity coefficient; A is Debye–Hükel constant; z is charge of the ion (2 for Ca); and I is ionic strength.

The activity coefficient (yCa2+) needs to calculate the activity that depends on the ionic strength (Equation 4) of the system. In ideal conditions (when only Ca ions are present), the activity coefficient is equal to 1, and thus [Ca2+] concentration is equal to [aCa2+]. Dairy matrices are far away from being diluted systems (not even whey permeates), as several minerals and macromolecules (e.g., protein, fat, and carbohydrates) are in diffusions/dispersed (Crowley et al., 2015).

𝐼= 1 2 𝑛 ∑ 𝑖=1 𝑐𝑖𝑧2 𝑖 (4) where ci is molar concentration of ion i (mol/L) and zi is charge number of that ion.

However, ion-exchange chromatography can be implemented to determine the ionic strength of liquid dairy-based systems, although it is expensive and time- consuming. A faster, easier, and indirect method to estimate ionic strength is by using conductivity measure- ment and consequently converting conductivity values (S/cm) to ionic strength (mM); however, such method cannot differentiate between each ionic species when compared to ion-exchange. According to Walstra et al. (2005), the ionic strength of milk is ∼80 mM resulting in yCa2+ of ∼0.4. Usually, yCa2+ decreases as a function of increased total solids content (e.g., evaporated milk and concentrated liquid dairy-based material), with values being less than or equal to 0.3 for high concentrate dairy liquid materials (Augustin & Clarke 1991). It is worth mentioning that the indirect relationship between decreasing yCa2+ and increasing total solids is related to the Davis equation (Equation 3 b); as the ionic strength is

5622 calcium in dairy products ⋯ F I G U R E 2 Schematic representation of atomic absorption spectroscopy (AAS) instrument propagating via square root, and thus the higher the ionic strength, the lower is yCa2+.

In this matter, noteworthy are the fundamental works of Augustin and Clarke (1990) and M. J. Lin et al. (2006), both outlining the different [Ca2+] and its yCa2+activity in bovine milk as a function of different pH values that are commonly used during processing of dairy materials (e.g., 6.2–7.0). It was found that [Ca2+] in that pH range oscillated from 2.60 to 1.07 mM (1.81 mM at innate pH of milk), while [aCa2+] from 1.00 to 0.42 mM (Table 1). Many dairy scientists have extensively used [Ca2+] determina- tion using selective ion electrodes. For the reader’s bene- fit, a concise and specific review regarding this method has been outlined by M. J. Lewis (2011).

4.1.3 Ion-exchange chromatography Another approach for determining ionic calcium concen- tration [Ca2+] in bovine milk or liquid dairy-based mate- rial is ion-exchange chromatography (IEX). The principle of IEX relies on the reversible interaction between the tar- get ion and the functional groups of the resins (groups that physically interact with the ions and are covalently attached to the stationary phase). For quantification of [Ca2+], cationic (negatively charged) IEX resins made of carboxylic or sulfonic resins are often used. Briefly, a sam- ple (e.g., milk) is left equilibrating with the IEX resin,

Ca2+ ions are bound to the resin, eluted using acids, and its concentration is determined by titration or conductiv- ity methods (Asada et al., 2017). An early and remark- able work using IEX for quantifying ionic calcium con- ducted by Christianson et al. (1954) found that an accu- rate range of [Ca2+] in bovine skim milk ranged from 2.0 to 2.3 mM (Table 1). Cataldi et al. (2003) measured [Ca2+] of whey streams using IEX coupled with a conductivity meter, establishing a very good limit of detection (LOD) of 0.06 mg/L for Ca2+ with values for bovine whey (575 mg/L) in line with values generated using different meth- ods. If deproteinization of bovine milk using perchloric acid is carried out, total Ca can also be measured using IEX, as showed by Asada et al. (2017). They compared values obtained by IEX (1077–1095 mg/L) to those generated with inductively coupled plasma-optical emission spectrome- try (ICP-OES), finding a good agreement between the two methods. The main advantage of IEX compared to selec- tive ion electrodes relies on the simultaneous determina- tion and quantification of different ions with high accu- racy; however, retention time waiting, sample preparation (in some cases), chemicals (eluents) may prolong the time of analysis, constricting the application of IEX for fast in- line and dynamic analysis of dairy liquid-based materials.

4.2 Atomic spectroscopy methods 4.2.1 Atomic absorption spectroscopy

Atomic absorption spectroscopy (AAS) is a common tech- nique used to quantify metals (such as Ca) and generally metalloids. AAS principle relies on the absorption radia- tion at a given frequency of free metal in a gas state (which is carried out by an atomizer). The atom (such as Ca) absorb ultraviolet (UV) or visible light and subsequently, the amount of absorbed energy released in the light is detected, with the intensity of such light being a function of the concentration. AAS is composed of five parts, as shown in Figure 2. Murthy and Rhea (1967) used AAS for quantification of the major cations in milk (i.e., Ca, magne- sium, potassium, and sodium) and compared their finding to those obtained by titration. Ca content was 1.183 mg/L in whole milk, with a significant but small difference com- pared to skim milk (1.242 mg/L). While in yoghurts, Ca content determined with AAS was not influenced by the fat content, as showed by De La Fuente et al. (2003). Cer- bulis and Farrell (1976) determined the three major min- erals (e.g., Ca, magnesium, and phosphorus) and relative ratios of seven dairy herds using AAS. The average Ca

5623 content was found to be 1.250 mg/L among the herds, with

Ayrshire and Jersey herds having the lowest and highest content, with values of 1.118 and 1.461 mg/L, respectively (Table 1).

Although AAS is relatively cheaper, faster, and simpler to operate, compared to other spectrometer-based tech- niques (e.g., ICP-MS/OES), some disadvantages need to be pointed out, such as (a) sample preparation and (b) spec- trum. For instance, sample preparation is the major limit- ing step, as proteins and phosphate constituents of dairy samples can significantly interfere with Ca absorbance.

For such reason, lanthanum is often used to minimize milk phosphorus interference, while proteins must be precip- itated by trifluoroacetic acid (∼24% w/v) (García Alonso et al, 2015). Another but more time-consuming option is reducing the sample to ash (e.g., 550◦C for 5 h or more) followed by dissolution in nitric acid. The analyzable spec- trum of AAS is the second major disadvantage. It is lim- ited to quantifying one mineral per time due to the hollow cathode lamp material that should match the analyte. Also, regarding sensitivity (e.g., limit of quantification), AAS is not suitable for determining the trace mineral elements of bovine milk (Gaines et al., 1990).

4.2.2 Inductively coupled plasma Inductively coupled plasma (ICP) belongs to the family of emission spectroscopy that uses inductively coupled plasma to produce excited atoms and ions that emit elec- tromagnetic radiation at characteristic wavelengths. The plasma used can ionize the sample in its fundamental ele- ments; usually, argon is used to generate ICP plasma with temperatures typically ranging from ∼5500 to 6500 K. ICP can be coupled with spectroscopical methods such as opti- cal emission (OES) and also mass spectrometry (MS). ICP- MS has been applied to develop standard methods such as ISO 21424 and IDF 243 (2018)/AOAC Official method,

2015.06 to trace or ultra-trace minerals of dairy products as being more sensitive than OES (better limit of quan- tification) (Chevallier et al., 2015). Considering that milk and dairy products have a high content of Ca, ICP-OES (Figure 3) has been widely used compared to ICP-MS (Bilandžić et al., 2015; Ikem et al., 2002; Khan et al., 2014;

Luis et al., 2015; McKinstry et al., 1999; Toffanin et al., 2015).

In brief, Ca is highly excited by the ICP torch to reach a plasma state. The release of energy in the form of light by the excited Ca has a particular spectrum, which is detected, with the intensity of the released energy related to the con- centration. The main benefits associated with ICP-OES, when compared to AAS, are the simultaneous analysis of more mineral elements, high accuracy and low detection limit (0.1 µg/L) (for AAS, it is 1 µg/L). However, sample

F I G U R E 3 Schematic representation of inductively couple plasma coupled with optical emission spectroscopy (ICP-OES) preparation can substantially influence the correctness of the analysis, as organic dairy components (e.g., protein, and carbohydrate, lipids) can result in organic deposition and/or blockage of ICP torch (Masotti et al., 2020).

4.2.3 X-ray spectroscopy X-ray wavelengths (from 10 picometers to 10 nanometers) are high-energy photons, usually generated by accelerat- ing electrons into an anode with an energy level ranging from 10 to 50 kV (Elam et al., 2002). A material that has been excited by X-ray can emit secondary wavelengths or

X-ray fluorescence (XRF), which occurs when a knocked electron from an atom falls from a high electronic orbital to a lower one. During such a fall, energy is released in the form of a photon, and the material emits radiation.

The intensity of the emitted XRF is directly proportional to the concentrations of the target atom, and different levels of sensitivity such as 8.0 and 1.0 mg/kg, respec- tively, are expected depending on the detector used, such as wavelength-dispersive or energy-dispersive (Rossmann et al., 2016). XRF application for determining a mineral profile of dairy products is not very common compared to other methods such as ICP-OES or AAS, mainly ascrib- able to the high cost of the equipment (from 10.000 to

60.000 USD). However, the benefits of using XRF com- pared to AAS or ICP-OES rely on sample preparation, as direct analysis of samples (in all forms, e.g., solid, liq- uid, and gel) can be carried out in a concise time frame of analysis (∼60 s) without requiring organic solvents or acids (Pashkova, Aisueva, et al., 2018). Therefore, it can be easily applied for fast in-line mineral profile analysis of milk and dairy products (mainly powders), with values very consistent with those reported in the literature using different methods (Table 1) (W. P. McCarthy et al., 2020;

Pashkova, 2009; Pashkova et al., 2016; Pashkova, Aisueva, et al., 2018; Pashkova, Smagunova, et al., 2018). For exam- ple, Perring and Tschopp (2019) established and validated

5624 calcium in dairy products ⋯ a rapid method for quantifying the total ash content of

69 different powder milk-based ingredients using Energy

Dispersive-X-Ray Fluorescence (ED-XFR). Major minerals (including Ca) were identified in the energy region ranging from 1.0 to 4.5 keV. Murrieta-Pazos et al. (2013) investigated the mineral profile at particle surface of different dairy- based powder ingredients using Energy Dispersive-X-Ray (EDX). EDX was found to be a fast choice for determining particle surface mineral profile, although some repeata- bility challenges were highlighted in the study. For liquid dairy products, EDX was also used to determine Ca and other major minerals (potassium and phosphorus); how- ever, minor challenges may arise from X-ray background scatter, resulting in poor detection limits when compared to ICP methods (Ekinci et al., 2005).

5 ANALYTICAL METHODS FOR UNDERSTANDING CALCIUM–PROTEIN

INTERACTIONS IN DAIRY SYSTEMS Dairy proteins (casein and whey) can interact with them- selves (e.g., protein–protein interactions), with macro- (e.g., carbohydrates and fat) and micro- (e.g., minerals and vitamins) components (Corredig et al., 2011; Forrest et al.,

2005; Havea, 2006). Dairy proteins can interact with Ca to different extents, depending on the intrinsic protein chem- istry (e.g., whey proteins and caseins). The severity of the

Ca-protein interaction can influence the innate physico- chemical properties of the protein, meaning that at the macroscale level, the physicochemical characteristics of products such as Ca-fortified milks, dairy-based ingredi- ents, and dairy-based formulated products can be signifi- cantly altered, especially during processing but also influ- encing product quality, and storage stability (Pandalaneni et al., 2018; Philippe et al., 2003). Specifically, the ionic form of Ca (Ca2+) is known to induce greater proteins instability in terms of lowering net superficial charge and consequently inducing protein aggregation and increased hydrophobic interactions. Therefore, understanding Ca- protein interactions can be essential and advantageous for predicting physicochemical characteristics of dairy-based products before, during, and after processing.

5.1 Thermodynamic methods 5.1.1 Differential scanning calorimetry

Differential scanning calorimetry (DSC) is a thermo- analytical technique for measuring the thermal proper- ties of a material for establishing a relationship between temperatures and physical properties by determining the enthalpy associated. The exothermic or endothermic dif- ferences are detected, thereby generating parameters such as enthalpy and relative transition temperatures (e.g., glass, crystallization, and melting) (Leyva-Porras et al.,

2020).

Generally, DSC analysis of dairy proteins has been reported to show endothermic and exothermic peaks for denaturation and aggregation, respectively, with such peaks having a Gaussian distribution (Fitzsimons et al.,

2007). Ca has been observed to decrease the activation energy and enthalpy of dairy proteins, and as a conse- quence, protein unfolding and denaturation temperatures can occur at low temperatures (Petit et al., 2011). In the work of Kaushik et al. (2015), DSC was used to under- stand the thermal stability of Ca-enriched milk (500 mg/L

Ca) using four different salts (i.e., Ca-chloride, Ca-acetate,

Ca-hydroxide, and Ca-citrate) and showed that proteins were unfolding at a lower temperature when compared to a reference (non-Ca-fortified milk) with the excep- tion of Ca-citrate, which performed the best in terms of heat stability but caused an increase in viscosity. For whey proteins, DSC has been a powerful instrument for determining thermal characteristics (Anandharamakrish- nan et al., 2007; Bernal & Jelen, 1985; Chandrapala et al.,

2011; Fitzsimons et al., 2007; Gotham et al., 1992; Pauls- son & Dejmek, 1990; Taylor & Fryer, 1993). Noteworthy is the work of Simons et al. (2002) investigating posttransla- tional modification of β-lactoglobulin (β-lg) and the influ- ence of Ca. It was reported that molecular modification of β-lg such as succinylation and methylation influenced β-lg aggregation properties, as different available sites for

Ca were observed (carboxylates group). Thus, the relation- ship between net surface charge and available sites for Ca of β-lg modulated the aggregation properties understood by DSC.

The second major whey protein α-lactalbumin (α-lac) and its interactions with Ca were also studied using DSC.

Bernal and Jelen (1984) outlined the role of Ca2+ in ther- mal denaturation characteristics of α-lac in the pH region ranging from 2.5 to 6.5. It is known that α-lac binds Ca2+ (calcium depleted state) at the intramolecular level, result- ing in a transition from apo-α-lac to holo-α-lac (calcium bound state), with the latter possessing unique physico- chemical properties among dairy proteins (e.g., high heat stability). Using DSC, it was found that binding of Ca by α-lac increases the heat stability properties due to an increase of enthalpies level. An implication of this was exploited for the manufacture of an added-value whey pro- tein concentrated ingredient enriched in α-lac, an ingre- dient mainly used in the formulation of nutritional dairy- based products (e.g., infant formula). Moreover, Hendrix et al. (2000) investigated the influence of a gradually increasing level of [Ca2+] (0–10 mM) on the heat capac- ity of α-lac using DSC. It was established that the heat

5625 capacity of α-lac had a linear relationship with the increas- ing [Ca2+], with values ranging from 217 to 313 ΔH (kJ/mol); thus, the denaturation temperature of α-lac was observed to be as a function of the log [Ca2+]. Although

DSC has been shown to be a powerful tool for assessing Ca- protein interaction, the dynamic nature of the interactions in real-time can be considered a drawback. Information regarding the thermodynamic value inherently to equilib- rium properties cannot be generated with DSC.

5.1.2 Isothermal titration calorimetry A similar, but different approach to DSC, is isothermal titration calorimetry (ITC). Briefly, ITC is used to deter- mine the thermodynamic parameters according to Gibbs free energy in adiabatic conditions (constant temperature) (Equation 5). A ligand is injected into the substrate cell in a step-wise manner, and the energy involved during the. titration is recorded, and thus values such as stoichiometry and affinity constant of the reaction are generated (Archer

& Schulz, 2020).

Δ𝐺= Δ𝐻−𝑇Δ𝑆 (5) where ∆G is free Gibbs energy (kJ mol−1); ∆H is enthalpy (kJ mol−1); ∆S is entropy (J K−1 mol−1); and T is tempera- ture in Kelvin.

The binding of Ca2+ by dairy proteins can occur in a specific intramolecular site of the protein (Permyakov &

Berliner, 2000) or in a shell of polar hydrophilic residues (Dudev & Lim, 2003; Yamashita et al., 1990) via electro- static interactions. Generally, the binding process of metal by proteins occurs in a gradual step-wise manner, and the

ITC method can record endo- or exo-thermic phenom- ena involved during the gradual injection of the ligand (Figure 4).

However, a comprehensive study regarding the interac- tions of dairy protein and Ca using ITC was conducted by Canabady-Rochelle et al. (2009). The titration of skim milk with calcium chloride (CaCl2) had an endothermic nature (ΔH > 0) with favorable entropy (TΔS), suggest- ing that milk proteins interact with Ca2+ through entrop- ically driven forces, resulting in a total Ca2+ uptake of

8 mg/g of total protein. A similar study, with whey pro- teins, was conducted by Barone et al. (2020b), demonstrat- ing that depending on the manufacture approach used to produce whey protein-based ingredients enriched in α-lac, a different extension of Ca-binding was observed, which was also influenced by other secondary macro ingredi- ent constituents (e.g., lipids). The Ca-protein interactions, especially for whey proteins (without applied heating), occur in three main steps: (1) reduction of the superfi- F I G U R E 4

Example of data originated using isothermal titration calorimetry (ITC). (a) Raw data from the instrument with each peak representing the energy involved during each injection with the titrant; (b) elaborated data for calculating constant affinity (Kf), stoichiometry (N), and molar ratio cial charge of proteins induced by Ca2+ (Figure 5a), (2) increased intermolecular proximity and potential electro- static driven aggregation (Figure 5b), and (3) extensive interactions between proteins mediate by Ca2+ bridging at the carboxylic group of aspartic and glutamic amino acid residues of the protein, which also increases hydrophobic interaction due to increased proximity (Figure 5c) (Brit- ten & Giroux, 2001; Kaushik et al., 2015; Kulmyrzaev et al.,

2000).

The application of ITC for mineral-protein interaction has been limited in the literature compared to the DSC method, for the main reason that dairy systems are not simple, as other innate mineral constituents may inter- fere with the analysis (Arroyo-Maya & McClements, 2016).

However, ITC allows us to understand Ca-protein interac- tions in liquid dairy-based systems, and the data provided can be used for predicting and improving physicochemical properties of liquid dairy products.

5.2 Light scattering and electrokinetic method Light scattering occurs when small or very small parti- cles scatter the light in agreement with Maxwell’s equa- tion. The angle of scattering estimates the diameter of the particle, as larger particles generate a smaller angle of

5626 calcium in dairy products ⋯ F I G U R E 5 Schematic illustration of intermolecular attractive forces of whey proteins mediated by ionic calcium: (a) reduced surface potential of whey protein caused by calcium ions (red dots); (b) intermolecular association of whey proteins (aggregation); (c) detail of the whey protein–calcium interaction bridges between the carboxylic group of aspartic and glutamic amino acids of whey proteins, and attractive interaction between hydrophobic domains of protein (gray) scattering than small particles (Kaszuba et al., 2008). Gen- erally, static light scattering (SLS) techniques are often used for particles with a size diameter between 0.2 and

100 μm, such as emulsions, suspensions, rehydrated dairy material, and also dairy-based powders. In contrast, the dynamic light scattering (DLS) method can determine the particle size distribution (PSD) of macro- and nano- particles such as casein micelles, caseins, and whey pro- teins. Generally, the SLS method does not require sam- ple dilution, contrary to the DLS method, in which the sample often needs to be diluted. This is because DLS records the angle of scattering dynamically over a certain period of time, and samples with high scattering proper- ties are not suitable due to multiple scattering properties of overlaying particles, thereby generating artefacts. For example, the buffer used for diluting milk or dairy liquid products can significantly influence data quality, especially for determining casein micelles PSD. Beliciu and Moraru (2009) examined the influence of different buffers, namely ultra-pure water, SMUF, and UF permeated, on the PSD of casein micelles using DLS method. The dilution of milk with ultra-pure water was detrimental, as micelles were dissociating, in contrast to UF permeate (using a mem- brane with a nominal cut-off of 10kDa) that was shown to be highly suitable for PSD analysis of casein micelles.

However, in case UF permeate is not readily available, a good compromise for assessing PSD of casein micelles is a dilution buffer made of Ca-imidazole (composed of 20 mM imidazole, 5 mM CaCl2, 30 mM NaCl, and 1.5 mM of NaN3) (Tran Le et al., 2008).

Light scattering methods are often coupled with elec- trokinetic potential method (ζ-pot) to evaluate Ca’s sensi- tivity and influence on dairy proteins. ζ-Pot is the potential difference between the dispersion media and the station- ary layer of a fluid attached to the dispersed particle, with the electrical charge contained within the region bounded by the slipping plane (Figure 6). Usually, values for ζ-pot of dairy proteins and dairy protein-based emulsion, at neu- tral pH (6.70–7.00), can range from −30 to −20 mV (Kul- myrzaev et al., 2000; Loi et al., 2019).

Increasing the [Ca2+] in a dairy liquid system can increase the hydrodynamic volume of casein micelles while decreasing net ζ-pot from their innate value (∼25 mV); as a result, prominent proximity between micelles can occur, leading to aggregation driven via elec- trostatic interactions (De Kort et al., 2012; Jean et al.,

2006; Ye et al., 2012). Similarly, whey proteins are also sensitive to [Ca2+] levels, affecting particle size and ζ- pot, and generally leading to physicochemical instabil- ity (Barone et al., 2020b). A substantial amount of litera- ture underlines the importance of light scattering and ζ- pot methods for understanding Ca-protein interactions in dairy-based liquid matrices. N. A. McCarthy et al. (2014) evaluated the physicochemical stability of different dairy- based emulsions upon adding Ca2+, source as CaCl2, by combining SLS, DLS, and ζ-pot measurements. Studies showed that the native net ζ-pot of β-casein and lactoferrin (negative and positive at milk pH conditions, respectively), both used individually to produce a dairy-mediate emul- sion, influence the general emulsion sensitivity to [Ca2+], especially during heating. Barone, O’Regan, et al. (2020) demonstrated that heat-induced aggregation of nutritional dairy-based model system (e.g., infant formula) increased as a function of increasing [Ca2+], due to significant reduc- tion of ζ-pot of the proteins in diffusion and proteins at the fat globule interface.

5.3 Viscosity methods The Arrhenius equation (Equation 6) can be used to describe the effect of temperature on the rate constant of chemical and biochemical reactions. This approach has been used to describe the temperature-dependence

5627 F I G U R E 6 Representation of the electrokinetic layer of casein micelles and relative distance of each layer from the surface of the casein micelle. Red and gray spheres represent cations and anions, respectively of viscosity in food systems and specifically for modeling the denaturation kinetics of whey proteins (Blanpain-Avet et al., 2016; Wolz & Kulozik, 2015). 𝜂(𝑇) = 𝜂0 EXP [ 𝐸𝜂 𝑘𝐵𝑇

] (6) where η(T) is temperature-dependent viscosity; η0 is pre- exponential constant; Eη is activation energy; and kBT is

Boltzmann constant temperature-dependent.

Dairy products are generally, but not always, composed of whey proteins and caseins and processing temperatures higher than ∼75◦C may lead to increased viscosity (Joyce et al., 2017). This may cause challenges that impact process efficiency (e.g., poor heat transfer and fouling) and product quality (e.g., sedimentation and gelation) negatively (Joyce et al., 2017; Wijayanti et al., 2014). Usually, caseins are considered heat-stable proteins when compared to whey proteins, which can unfold their native compact globular structures, ultimately resulting in protein aggregation.

The influence of increased Ca addition and Ca salt (e.g., soluble and insoluble) on dairy products has been stud- ied mainly by monitoring the changes in apparent viscos- ity as a function of temperature using rheology methods.

The combination of viscosity measurements and quan- tification of Ca partitioning can be advantageous for pre- dicting and assessing physicochemical stability. For exam- ple, Acosta et al. (2020) investigated the influence of two different types of Ca salts (i.e., calcium chloride and lac- tate) on the rheological properties of reconstituted skim milk powder at three different Ca concentrations (i.e., 0,

5, and 30 mM). Concentrations of up to 30 mM of both salts used resulted in increased viscosity during heating compared to a reference (noncalcium added skim milk), with chloride being more pronounced on viscosity at a lower temperature (64◦C) than lactate (70◦C). In contrast,

Pandalaneni et al. (2018) gradually decreased the innate

Ca content (20% and 30% of Ca reduction) of milk pro- tein concentrate (MPC) solutions by using Ca binding salts (i.e., sodium hexametaphosphate), observing significant differences in viscosity; a reduction in Ca and specifically [Ca2+] of the modified MPCs solutions had a higher appar- ent viscosity than a nonmodified MPC solution. This was described to be caused by casein micelles dissociation as a consequence of CCP reductions, which increased water holding capacity of the free released caseins (and conse- quently viscosity), with very similar patterns as previously outlined by N. A. McCarthy et al. (2017). In Ca fortified yoghurts, G. Singh and Muthukumarappan (2008) estab- lished that the addition of Ca-lactate at four different levels (25, 50, 75, and 100 Ca/100 mL) increased apparent viscos- ity and reduced shear-thinning properties when compared to a nonfortified yoghurt, as extensive CCP cross-linking between casein micelles was observed. Ramasubramanian et al. (2008) studied the textural properties (e.g., smooth- ness, viscosity, and firmness) of a Ca fortified yoghurt using

CaCl2 and Ca potassium citrate at a concentration of 13.6 and 49.8 mM, respectively. They found that counteract- ing high Ca salt addition using a Ca-binding salt (sodium

5628 calcium in dairy products ⋯ citrate) decreases the viscosity properties of Ca-fortified yoghurts.

5.4 Titration method A relatively simple method to assess Ca-protein interac- tions in dairy solutions is pH monitoring upon adding a soluble Ca salt. A decrease in pH of dairy-based solu- tions titrated with a soluble Ca salt (e.g., Ca chloride, glu- conate, and lactated) is often observed. Proteins that inter- act with Ca2+ by binding it can release protons from the interaction site, and consequently, the pH is reduced (Brit- ten & Giroux, 2001; Ogawa & Tanokura, 1984). For exam- ple, Kharlamova et al. (2018) studied the binding properties of soluble whey protein aggregates using the Ca-titration method. It was shown that by monitoring pH changes as a function of increasing [Ca2+], a reduction of pH was observed, with the reduction being independent of the pro- tein concentration of the whey solutions. Similarly, Barone et al. (2020b) showed that the strength and extent of the Ca- protein interaction of different whey protein-based solu- tions enriched with α-lac were proportionally related to the reduction in pH after a step-wise addition of 5 mM of [Ca2+] source as CaCl2.

However, titration methods for understanding Ca- protein interactions are limited to only low ash content solutions such as reconstituted whey or casein-based high protein ingredients (protein ≥80%; ash <4% w/w) due to inorganic calcium phosphate formation (Equation 1) dur- ing titration, interference with the innate soluble magne- sium and other salts (Gaucheron, 2005; Mekmene et al.,

2009).

6 PROCESSING OF DAIRY PRODUCTS:

IMPLICATIONS OF CALCIUM PARTITIONING Processing techniques used during the manufacturing of dairy products affect Ca partition between the col- loidal and serum phases, including its speciation, thereby influencing physicochemical, techno-functional proper- ties, product yield (e.g., cheese production), and process- ability (e.g., fouling). A comprehensive understanding of such Ca partitioning and relative speciation as a function of processing conditions can be beneficial for overcoming some of the challenges (e.g., fouling, protein aggregation, gelation, and sedimentation). For example, during ultra- high-temperature (UHT) treatment of milk and dairy prod- ucts (e.g., high-protein solution and creams), the Ca parti- tioning affects the running time of the heat exchangers due to an increased fouling layer and thus diminishing heat transfer coefficient (Anema, 2019). It also affects product rheology as increased viscosity induced by protein–protein interaction mediated by Ca2+ bridging can occur.

Above ∼60◦C, Ca-phosphate solubility, present in the serum and colloidal phases, significantly increases (Equa- tion 1), being more pronounced at a higher temperature such as those used for UHT processing. A fouling layer, composed primarily of Ca-phosphate and secondarily of proteins can be formed on the surface of heat exchang- ers, reducing the heat transfer coefficient, and resulting in a prolonged and extensive clean-in-place (Anema, 2019).

Sedimentation of milk components as a consequence of

UHT processing, is also a challenge. It was highlighted that indirect UHT processing increases the content of unsta- ble κ-casein-depleted casein micelles, highly sensitive to

Ca2+ induced aggregation, and thus precipitating at rela- tively low serum ionic calcium levels ([Ca2+] > ∼1.5 mM) (Anema, 2019; Gaur et al., 2018).

6.1 Dairy ingredients The partitioning of Ca during the manufacture of dairy- based ingredients influences the final ingredient physico- chemical and functional properties. This is primarily rele- vant for casein-based ingredients such as skim milk pow- ders (SMPs), MPC, milk protein isolates (MPI), or micellar casein concentrate (MCC) rather than whey-based ingre- dients (e.g., whey protein concetrates (WPC) and isolates (WPI)) (Anema & Li, 2003; Crowley et al., 2016). During the manufacture of the casein-based ingredients, the criti- cal steps affecting Ca partitioning are (1) temperature, such as heating and cooling; (2) concentration (e.g., evaporation and drying treatments); and (3) separation of milk com- ponents (e.g., membrane filtration). Heating is applied in several consecutive steps, such as pasteurization of raw material, evaporation, and at last, during spray drying.

Depending on the heating temperature and load, Ca is lost as Ca-phosphate deposits (fouling) and/or by mediating protein–protein interactions (whey–whey, whey–casein, and casein–casein) (Corredig & Dalgleish, 1999; Rosman- inho & Melo, 2008). During heating, at temperatures higher or equal to 90◦C, Ca phosphate precipitates (due to its inverse solubility) while it causes an irreversible accu- mulation of Ca in the colloidal phase (Figure 7a,b). In con- trast, cooling of milk increases Ca-phosphate solubility, resulting in high [Ca2+] levels in the serum phase (Fig- ure 7b) (Anema, 2009; Augustin & Clarke, 1991; Wahlgren et al., 1990). Excess of Ca-phosphate in the serum phase increases fouling in evaporators, heat exchangers and pipelines, causing reduction of heating efficiency (Visser

& Jeurnink, 1997), blockages and safety issues (e.g., poor clean-in-place practices and sediment in the final product).

5629 F I G U R E 7 Schematic representation of calcium partitioning during common processing practises of bovine milk such as (a) heating, (b) cooling, (c) membrane filtration, and (d) acidification

On the contrary, depending on the extent of protein– protein interactions (e.g., whey–whey, whey–casein, and casein–casein) mediated by Ca (Ca2+), different physic- ochemical and techno-functional properties of the final ingredient are observed, giving the possibility to tailor product functionality (Fang et al., 2012; Sharma et al.,

2012). An example is the production of SMP, which are classified as low-heat (75◦C for 20 s), medium-heat (85 ◦C for 1 min) or high-heat (135◦C for 2 min) (Pisecky, 2012;

Stewart et al., 2018) based on nondenatured whey protein nitrogen (WPN) content. Generally, WPN values for low- heat, medium-heat and high-heat powders are ≥6.00, 1.51–

5.99 and ≤1.50 mg WPN⋅g−1 powder, respectively (Schuck,

2002). As the heating load increases, Ca migrates from serum to colloidal phase, thereby decreasing [Ca2+] in the serum phase (Figure 7a) (Barone et al., 2020a; Y. Lin et al.,

2018), ultimately resulting in different powder functional- ity (e.g., rehydration, heat stability, foaming, and gelation) (Sharma et al., 2012). For example, low-heat SMP gener- ally shows better reconstitution properties but impaired heat stability compared to high-heat SMP. This is due to the higher level of [Ca2+] of low-heat SMP compared to high-heat SMP, which impairs casein micelles reconstitu- tion, while promoting protein–protein Ca-mediate interac- tions when heating is applied (Faka et al., 2009; Sharma et al., 2012; Silva & O’Mahony, 2017).

Membrane filtration of bovine milk (especially UF; pore size from 0.002 to 0.1 µm) is often used to concentrate

5630 calcium in dairy products ⋯ protein material prior to the manufacture of powders hav- ing from medium (50% w/w) to high-protein content (85% w/w) (Meena et al., 2017). During UF, most of the serum

Ca is discharged in the permeate, and as it passes through the membrane, it also influences filtration performance (fouling induced by Ca) (Figure 7c). In terms of fouling,

Ca contributes to (a) direct fouling and (b) indirect foul- ing. Direct fouling of membrane usually occurs at high filtration temperature (≥55◦C), a phenomenon previously described in which CCP and serum Ca phosphate precip- itated, and subsequently adhered to the membrane sur- face, which decreases transmembrane pressure and per- meability of the membrane (James et al., 2003; Zhang et al.,

2020). Indirect fouling mainly occurs at filtration tempera- ture equal to or less than 10◦C, due to increased solubil- ity of Ca-phosphate, which increases [Ca2+] level in the serum phase, which will promote Ca mediated protein– protein interactions, and consequently, build-up of protein deposits on the surfaces of the membrane (France et al.,

2021).

The functionality of dairy-based powders is also affected by the Ca partitioning, especially during UF and spray dry- ing process, in which uptake of Ca2+ by casein micelles can occur (Chandrapala et al., 2014). Therefore, powder functionality can be modulated, especially in terms of rehy- dration properties of casein-based ingredients, which is considered the primary limiting processing step (Crow- ley et al., 2016; Felix da Silva et al., 2018). UF processing displaces most of the serum Ca into permeate (H. Singh,

2007), reducing Ca content (mostly soluble Ca salts) of the respective retentate (Sikand et al., 2013) and, obviously, the ionic strength. To counteract this ionic strength reduction, which may stress casein micelles physical properties, some of the CCP is released into the serum phase (Figure 7c) (M. J. Lin et al., 2015) even though such release cannot fully recover the original ionic strength levels. For exam- ple, Silva and O’Mahony (2017) and Crowley et al. (2015) observed that the lower Ca content of MPCs powders com- pared to SMPs resulted in a slower release and lower levels of Ca2+ during reconstitution, impairing the overall rehy- dration characteristics of MPCs. The lower [Ca2+] and rela- tive slow-releasing kinetic is a consequence of MPC manu- facture (e.g., UF), which reduced the particle size diameter of casein micelles and its CCP content, ultimately impair- ing powder functionality.

However, a reduction in [Ca2+] after reconstitution of casein-based ingredients can positively influence heat sta- bility. During UF, [Ca+2] is reduced along with phos- phate, citrate, and lactose; therefore, heat stability can be improved as reduced protein–protein interactions are observed during and after heating processing, as described by Renhe et al. (2019), in which at rehydration pH >6.9 of

MPCs, the negative micellar casein charge increases while reducing κ-casein dissociation during heat treatment with similar findings also outlined by Crowley et al. (2014) and

Sunkesula et al. (2021).

6.2 Cheese manufacture Milk salts have an essential role for both nutritional and technological perspectives during cheesemaking. Under- standing Ca partitioning during cheesemaking, by direct acidification or rennet coagulation, is essential to improve cheese yield and cheese quality (Lucey & Singh, 2003).

Yoghurts and acid cheeses’ (e.g., paneer and queso blanco) quality properties can be modulated by varying acidifica- tion procedures (e.g., addition rate and acid concentration) and temperatures. Acid coagulation of milk is achieved by decreasing the pH close to the isoelectric point of casein micelles (pI 4.60). At the pI of casein micelles, the elec- trostatic repulsions between micelles, mainly provided by k-casein, have vanished, and thus a coagulum is formed; meanwhile, a part of the CCP is dissolved in the serum phase, ultimately increasing Ca content (mainly Ca2+) (Figure 7d; Equation 1). Also, internal bondings between caseins inside the casein micelles are extensively modi- fied, resulting in casein re-arrangements (Lucey & Fox,

1993; Ramasubramanian et al., 2013). The level of [Ca2+] released from CCP after acidification is dependent on the acid used (e.g., citrate, lactate, and glucolactone) and thus its potency. In addition, the influence of heating (temper- ature and heating load), if applicable (e.g., panner), also influences physicochemical properties and textural char- acteristics of the acid-induced heated curd, specifically: temperatures higher than 75◦C, whey protein denatura- tion content, total protein content, moisture, the extent of syneresis, and presence of polysaccharide (where applica- ble) (Lucey, 2016; 2017).

Rennet coagulation of milk can be summed up in three main stages: primary (enzymatic), secondary (aggrega- tion), and tertiary (structure arrangements). During these stages, Ca content and speciation can remarkably mod- ulate the extent of the aggregation rates, especially dur- ing the second phase (Sandra et al., 2012). The addition of chymosin to bovine milk induced cleavage of κ-casein at Phe105-Met106 bond resulting in loss of the hydrophilic component of κ-casein generally called caseinomacropep- tide, which provides stable electrostatic repulsion between casein micelles. κ-Casein cleavage induces greater proxim- ity and aggregation between casein micelles, forming a gel structure made of protein (Horne & Lucey, 2017). Differ- ent levels of [Ca2+] and CCP content can be modulated rennet coagulation time and the firmness of the protein gel, which influences textural properties. During cheese making practices, between 1.5 to 2.0 mM of Ca chloride (∼20g/100 L) is added for reducing renneting coagulation

5631 time and casein micelles aggregation (which also aims to enhance protein recovery and yield of product). For exam- ple, Tsioulpas et al. (2007) demonstrated that the time of renneting and the firmness of the formed gel was a func- tion of [Ca2+]. Indeed, it has now been established that a minimum level of Ca2+ is mandator for good cheese quality (Lucey, 2017), as the removal of both Ca2+ and partially CCP, using citrate or EDTA, completely inhibits rennet induced coagulation of bovine milk (Horne &

Lucey, 2017; Sandra et al., 2012; Udabage et al., 2001).

However, changes in the partitioning of Ca may occur within the cheese matrix during ripening, influencing the overall cheese properties (e.g., flavor, aroma, texture, and structure). Those changes are mainly influenced by the relationship between Ca and para-casein in the cheese matrix (Cooke & McSweeney, 2017; O’Mahony et al., 2005).

CCP incorporated in the cheese matrix during cheese manufacture can be solubilized during the first months of cheese ripening (Hassan et al., 2004). The equilibria between soluble to insoluble Ca can transition from a metastable state to a steady-state phase, and this is gener- ally called “the calcium equilibrium of cheese.” The equi- librium is influenced by milk composition, processing con- ditions such as pH, the addition of Ca salts, or Ca-binding salts (Lucey et al., 2003; O’Mahony et al., 2006). For exam- ple, the addition of soluble Ca salts (e.g., calcium chlo- ride and lactate) increased the Ca-para-casein interactions and thereby affected the cheese microstructure and texture (toward a hard and compact structure) (Ong et al., 2013).

In contrast, a low level of CCP in the cheese matrix often results in a softer texture with increased meltability prop- erties, especially during the first month of ripening; this is ascribable to a lower extent of Ca-para-casein interactions (O’Mahony et al., 2006). Therefore, understanding the ini- tial CCP total content of the cheese, the specific cheese- making condition and its equilibrium, especially during the cheese ripening stage, can be advantageous for tailored cheese or cheese-based products functionality.

7 CALCIUM–PROTEIN KINETICS IN BOVINE MILK Kinetic studies involving Ca in bovine milk are relatively limited and often associated with dairy proteins aggrega- tion (Anema & McKenna, 1996; Galani & Owusu Apen- ten, 1999; Halabi et al., 2020; Khaldi et al., 2018; Oldfield et al., 2005; Petit et al., 2011), gelation (Kharlamova et al.,

2018; Guyomarc’h et al., 2009; Vasbinder et al., 2003), or Ca induced fouling kinetic (van Kemenade & de Bruyn, 1987;

Khaldi et al., 2018).

Kinetic studies, especially those investigating individual protein–protein interactions mediated by Ca, established that such interaction follows a first-order kinetic. For example, Halabi et al. (2020) observed that in a complex system (i.e., infant formula), the kinetic order of whey pro- tein aggregation followed the first-order reaction (Anema

& McKenna, 1996). Interestingly, the activation energy (Ea) of whey protein denaturation as a function of protein com- position and profile was higher in infant formula (305 kJ/mol) compared to a single protein system (229 kJ/mol) (e.g., WPI and WPC) (Anema & McKenna, 1996) with the

Ca2+ influencing the rate constant of denaturation. Sim- ilar findings were outlined by Petit et al. (2011), studying the aggregation and fouling behavior of β-lactoglobulin as a function of [Ca2+]. It was found that the order of reac- tion of β-lactoglobulin unfolding and subsequent aggrega- tion was 1.5 with increasing [Ca2+] acting as catalyst agent especially during the aggregation phase.

In terms of gelation kinetic, Kharlamova et al. (2018) demonstrated that increasing [Ca2+], sourced as CaCl2, increased the kinetic gelation rate of whey protein but did not influence gel structure nor the elastic modulus. How- ever, at [Ca2+] higher than 25 mM, the gelation time, and thus gelation kinetic, was significantly accelerated with- out altering gel microstructure and networks properties.

In contrast, at [Ca2+] lower than 25 mM, the influence of gelation on mechanical and microstructural properties was slightly more pronounced when compared to higher [Ca2+] (>25 mM).

The fouling kinetics, mediated by Ca content, during processing of a whey-based material were described by

Khaldi et al. (2018). To understand the fouling layer proper- ties deposition on a heat exchanger, fouling kinetics were studied at different Ca to protein molar ratios (from 22.9 to 2.3 Ca/protein). The fouling material properties had a thin and dense structure toward low Ca/protein ratio while having a thicker and less dense structure when higher cal- cium/protein ratios were used.

However, due to the great complexity of bovine milk, in which multiple reactions co-occur, studies focusing on temperature Ca dependent kinetic on its partitioning in milk phases are lacking.

8 CONCLUSION Ca in bovine milk and dairy-based products has intrigued many dairy scientists for more than a century. Ca is an essential dietary mineral and critical to the struc- ture and integrity of the casein micelles. The parti- tioning of Ca in milk between colloidal and serum phases is a highly dynamic process that influences dairy products’ functionality, structural, and sen- sory properties, and is strongly influenced by dairy processing.

5632 calcium in dairy products ⋯ Identification of approaches for qualitative (speciation) and quantitative analysis of Ca in milk as a function of processing and storage, can represent a powerful tool for understanding, predicting and controlling dairy-based products’ quality and improve production efficiency. How- ever, a prerequisite for further understanding and deter- mining Ca partitioning between the two phases of milk (e.g., colloidal and serum) is a tailored procedure to sep- arate and quantify Ca in these two phases. Furthermore, the interaction of Ca with dairy proteins and other Ca bind- ing compounds is a known challenge in the dairy industry, affecting processing step (e.g., fouling, increased viscosity, extensive cleaning, and lines blockages), product quality (e.g., sedimentation, gelation, phase separation, and struc- ture), and acceptance characteristics (e.g., texture and fla- vor). Thus, a better understanding of Ca-protein interac- tions in dairy systems is needed to control processing and formulation.

This review provides a comprehensive study of the importance of Ca in milk and dairy products. Although much work has been performed regarding analytical tech- niques to quantify Ca in dairy systems, its partitioning and reactivity with dairy proteins is still an emerging research topic. The available methods are time-consuming, and the rates of partitioning reactions and speciation are to a large extent not studied, hindering the monitoring of Ca partitioning and speciation in-situ and in real-time during processing and storage. Ca partitioning is also of major importance during the manufacture of cheeses and dairy ingredients affecting cheese yield, cheese quality and functionality of dairy ingredients (e.g., thermal stability and rehydration). Comprehensive prediction models for understanding how the Ca partitioning in bovine milk and its interactions with dairy proteins modulate the extent of the different functional and physicochemical properties of the final dairy product need to be established.

AC K N OW L E D G M E N T S The authors would like to acknowledge the Danish

Dairy Research Foundation (project Procalcium - Calcium dynamics during manufacturing of cheese) for provid- ing financial support. The authors are also grateful to

Paraskevi Tsermoula and Thomas C. France for their con- structive discussions.

AU T H O R C O N T R I B U T I O N S Conceptualization, investigation, visualization, and writing-original draft: Giovanni Barone. Conceptualiza- tion and writing-review & editing: Saeed Rahimi Yazdi.

Conceptualization: Soren Lillevang. Funding acquisition, conceptualization, supervision, writing-review & editing, and project administration: Lilia Ahrné.

C O N F L I C T S O F I N T E R E S T The authors declare no conflict of interest.

O RC I D Giovanni Barone https://orcid.org/0000-0001-9740- 1035

LiliaAhrné https://orcid.org/0000-0003-4360-8684 R E F E R E N C E S

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