Food Processing and Food Products

### **Chapter 2**

## Chemistry of Camel Milk Proteins in Food Processing

*Roua Lajnaf, Hamadi Attia and Mohamed Ali Ayadi*

### **Abstract**

Camel milk and its extracted protein fractions were found to provide various potential techno-functional properties which can be used in the food industry. This chapter summarizes existing knowledge on camel milk protein's chemistry to explain the different reactions and their control for the major processes utilized by the modern milk processing industry. The composition and chemical properties of camel milk proteins including caseins and whey proteins are investigated. The effect of processing upon denaturation, aggregation, and destabilization of milk proteins is updated. Technological consequences of thermal processing as well as techno-functional properties of camel milk proteins are also described in different techno-functional properties including foaming, emulsifying, and gelling properties. This chapter aims to improve camel milk production and consumption worldwide not only in the arid countries and the hot regions.

**Keywords:** camel milk, food industry, caseins whey proteins, food processing, thermal processing

### **1. Introduction**

According to recent statistics by the statistics of Food and Agriculture Organization [1], the total population of camels in the world is estimated to be about 38.6 million, with Chad having the largest herd worldwide (8.8 million) followed by Somalia (7.3 million), Sudan (4.9 million), and Kenya (4.7 million) [1]. Camels live mainly in the vast pastoral areas in Asia and Africa, they are divided into two different species belonging to the genus Camelus. Dromedary camels (*Camelus dromedaries*) with one-humped and Bactrian camel (*Camelus bactrianus*) with two-humped [2]. Overall, dromedary camels mainly live in desert arid areas including the Middle East, North and East Africa, South West Asia and Australia while Bactrian camels prefer living in cooler areas such as East to Northern China, West Asia, and Southern Russia (Mongolia and Kazakhstan) [2]. Camels are usually considered to be a good source of milk and meat, meanwhile they are used for other purposes such as sports racing and transportation [3].

Camel milk plays a key role in human nutrition, especially in hot regions and arid countries. Indeed, this milk contains all the essential nutrients already found in bovine milk [4, 5]. According to the latest FAO statistics, camel milk production (both species) in the world is reported to be about 3.11 million tons per year representing

0.34% of the total milk production of the world, whereas the cow milk production represents 81.2% of total milk production (746 million tons per year) [6].

In Tunisia, total camel milk production is estimated to be around 1099.64 tons per year, representing only 0.1% of total milk production in Tunisia [1, 7]. Camel milk is popular in Tunisia and consumed as fresh milk as a treatment for a series of diseases such as cancer diseases. The produced camel milk in Tunisia is also dedicated to scientific research in various laboratories and research centers. Indeed, recently, camel milk was also reported to be an efficient treatment for other diseases, such as dropsy, tuberculosis, jaundice, hepatitis, asthma, and leishmaniasis [8]. Camel milk has also other potential therapeutic properties, such as anti-carcinogenic, anti-diabetic, and anti-hypertensive and has been recommended to be consumed by children who are allergic to bovine milk [9–14].

Unfortunately, camel milk has not been given as much attention in research compared with cow milk because of its relatively limited production and consumption despite its health benefits and therapeutic properties. Most of the research conducted on camels in the past was mainly focused on their physicochemical features. However, recent studies have mainly concentrated on the compositional, characteristics and technological properties of camel milk and its derived proteins. This review covers the recent works on camel milk properties with an emphasis on camel milk proteins. The aim of this chapter is to review the currently available information on Dromedary camel milk properties, composition as well as camel milk proteins: extraction processes, biochemical, and techno-functional properties.

### **2. Protein composition of camel milk**

Overall, milk proteins represent a significant nutritional intake (source of essential amino acids). These proteins represent also a source of important technofunctional properties for the conservation and processing of milk into dairy products for human consumption [15].

The total protein content in camel milk ranges from 21.5 to 49 g/L with an average of 31 g/L of milk [16]. This variation in the composition of camel milk proteins depends not only on the race of the producing female but also on seasonal conditions [17]. For instance, protein contents in camel milk, which was collected from the same breed, were found to vary significantly depending on seasons ranging between 24.8 g/L of proteins in summer to 29 g/L in winter [18].

As with other milk of different mammalian species, dairy proteins are commonly classified according to their solubility in two fractions: caseins (insoluble in acidic medium) and whey proteins (called soluble proteins) (**Table 1**). Indeed, the caseins precipitate at their isoelectric pH which is 4.6 and 4.3 for bovine and camel milk, respectively, while whey proteins remain soluble in these pH values [19–22].

### **2.1 Caseins**

Camel caseins are phosphoproteins that represent the most abundant protein fraction of milk. They occupy 61.8–88.5% of all camel proteins with an average of 75.4% (w/w) against an average content of 80% (w/w) for cow's milk [23].

Compositionally, caseins in bovine milk are composed of four caseins including αS1-, αS2-, β-, and κ-caseins with a molar ratio of approximately 4:1:4:1 in bovine milk [22].


### **Table 1.**

*Composition of camel milk in comparison with cow's milk.*

On the other hand, camel caseins consist of the known four sub-fractions including αS1-, αS2-, β-, and κ-caseins with proportions approximately being 22, 9.5, 65, and 3.5%, respectively in bovine milk (**Figure 1**) [25]. Recently, Lajnaf et al. [26] found that camel sodium caseinates contain four caseins at different percentages 1.1, 45.5, and 53.4% for κ-, α-, and β-caseins, respectively. The caseins of camel milk are homologous to bovine caseins with identity levels that range between 44.6% (αS1-casein) and 67.2% (β-casein) [27]. The α- and β-caseins are known as calcium-sensitive caseins or "sensitive calcium caseins" due to their precipitation at a calcium concentration estimated at 30 mM, while κ-casein remains in solution under these conditions.

### **Figure 1.**

*Proportions of the different caseins αS1-, αS2-, β and ĸ of the total caseins of cow's milk (a) and camel's milk (b) [24]. Abbreviation: CN: casein.*

Camel milk is distinguished by the low contents of κ-casein as reported by various authors. In the same way, Lajnaf et al. [28] found that no peaks were detected for the κ-casein due to its low concentration which probably makes it obscured by other caseins.

Overall, the comparison of camel and bovine properties revealed that camel milk caseins are less phosphorylated than their bovine counterparts and less negatively charged at neutral pH when compared to bovine caprine caseins [29, 30].

### *2.1.1 α-Casein*

The α-casein, which includes both αS1- and αS2-caseins, is the most abundant protein in cow's milk and its concentration in milk is estimated at 12.8 ± 2.3 g/L. However, the concentration of this protein is lower in camel milk (7.6 g/L) [25, 31, 32].

The αS1-casein, whose concentration is round of 9.5 and 5.3 g/L in bovine and camel milk, respectively, representing 38 and 22% of total bovine and camel caseins, respectively. Bovine αS1-casein contains 199 amino acid residues with a molecular weight (MW) estimated at 22.9 kDa, while camel αS1-casein is slightly bigger with 215 amino acids and a MW of 25.8 kDa. The isoelectric point (pI) is estimated to be around 4.26 and 4.40 for the bovine and camel αS1-caseins, respectively [25, 33]. The differences between camel and bovine αS1-caseins result in identity and similarity indexes which are around 44.6 and 59.7%, respectively [27]. Bovine αS1-casein is characterized by the absence of cysteine residues. However, it contains 8 serine residues in phosphorylated form. Due to the presence of a large number of proline residues (9.2 and 8.5% proline respectively for camel and bovine αS1-caseins, respectively) [33].

The content of αS2-casein in camel milk is similar to that of cow's milk. It represents 10 and 9.5% of the caseins of bovine and camel caseins, respectively [34]. Recently, this content has been reported as 0.3–3.9 g/L as reported by Mohamed et al. [35]. The primary structure of αS2-bovine casein has 207 amino acid residues with an MW of 24.4 kDa, while camel αS2-casein has a lower MW of 22 kDa as it contains 178 residues of amino acids. The pI is estimated respectively at 4.78 and 4.58 for both bovine and camel αS2-caseins [33].

It is well known that the αS2-casein is the most hydrophilic of the other caseins. It has 11 residues of phosphorylated serines and is characterized by the presence of two cysteine residues (residues 36 and 40) forming intramolecular disulfide bridges. This casein is found in partly milk in dimeric form, the two polypeptide chains of which are connected by two disulfide bridges [25]. Its secondary structure contains 32% α-helix and 30% β-sheets leading to a more organized and structured conformation when compared to those of αS1-casein. Similarly to other milk proteins, the differences between camel and bovine αS2-caseins result in identity and similarity indexes which are around 58.3 and 69.2%, respectively [27].

### *2.1.2 β-Casein*

The β-casein is the main protein in camel milk with a concentration that ranges between 12.8 and 15 g/L representing 65% of the total caseins of camel milk according to Kappeler et al. [34]. However, recent works noted a minimization of its proportion to 53.4% [26], 44.8%, and even 30% according to Felfoul et al. [36] and Ereifej et al. [23], respectively.

The β-caseins of cow's and camel's milk showed differences in their structures and physicochemical characteristics. In fact, bovine β-casein is composed of 209 amino

acid residues with an MW of 23.5 kDa and a pI of 4.49, while camel β-casein is slightly bigger than its bovine counterpart as it contains 217 amino acids leading to an MW of 24.9 kDa and a pI of 4.66. The rates of similarity (84.5%) and identity (67.2%) of the β-caseins are higher than those found for other caseins as reported by Lajnaf et al. [27] and Barzegar et al. [37].

The β-casein, the most hydrophobic of all the caseins, is characterized by a very high amphipolar character. Indeed, it has a C-terminal part (residues 136–209) which is very rich in hydrophobic amino acids, while its N-terminal part is hydrophilic and contains phosphorylated residues (residues 1–40) providing additional negative charges to the molecule. This protein is also characterized by the absence of disulfide bridges, which gives it significant resistance to heat treatment. β-Casein is classified as an intrinsically unstructured protein thanks to the large number of proline residues (16.7%) preventing the formation of secondary structures. Due to its particular structure (unordered, high hydrophobicity, relatively low molecular mass and absence of disulfide bridges), this casein is often at the origin of the properties sought in "stabilizing" protein food ingredients used in the dairy industry [38].

### *2.1.3 κ-Casein*

The κ-casein is the key milk protein that is involved in the rennet coagulation process of milk. Among caseins, the concentration of κ-casein (4.4 ± 0.3 g/L) was found the lowest representing 13% of bovine caseins. However, it is found in camel milk at a content four times lower than that of cow's milk varying from 0.1 to 2.4 g/L representing 3.5% of caseins or even 1.1% [26, 29, 35]. Bovine κ-casein has 169 amino acid residues with an MW of 18.9 kDa and a pI of 3.97, while camel κ-casein is composed of 162 amino acids with a molecular mass of 18.2 kDa and a pI of 4.11 [33]. These differences between both camel and bovine κ-caseins result in similarity and identity of 58.4 and 66.3%, respectively.

Similarly to β-casein, κ-casein has a particular amphipolar structure with a C-terminal part that contains highly hydrophilic residues and a hydrophobic N-terminal part. It is also characterized by a low calcium binding capacity due to the presence of a single phosphorylation site at position 149.

It is well known that the partial hydrolysis of bovine κ-casein by chymosin takes place at the peptide bond 105(Phe)-106(Met) leading to the release of a very hydrophilic peptide: the caseinomacropeptide (64 amino acids—molecular mass 6.7 kDa) and the formation of paracasein κ, which is very hydrophobic and insoluble. The cleavage site of camel κ-casein by chymosin is located at position 97(Phe)-98(Ile) (**Figure 2**) and leads to the release of a macropeptide with a molecular mass of 6, 77 kDa which is comparable to bovine macropeptide [29].

### **Figure 2.** *Cleavage sites of camel and bovine κ-caseins by chymosin [15].*

### **2.2 Whey proteins**

Whey proteins represent the second protein milk fraction representing 20–25% (w/w) of total milk proteins depending on the milk origin [39]. Camel whey proteins accounted on average for 24.51% of the total protein ranging between 11.49 and 38.82% of total milk proteins [23]. Overall, extracted camel whey after acid precipitation of caseins at pH 4.3 has a white color compared to the yellowish color of bovine whey. This is due to the low content of riboflavine in camel whey [2].

Generally, the protein composition of whey varies according to the mammalian specie. For instance, the soluble fraction of cow's milk, the protein composition is thoroughly studied: β-lactoglobulin is the main protein (~55%), followed by α-lactalbumin (~25%), the albumin serum (SA) (15%), and finally the immunoglobulins (5%) (**Table 1**). Camel whey is distinguished by the total absence of β-lactoglobulin similar to human milk [28, 33, 34, 40]. Thus, α-lactalbumin is the major protein of camel whey 50–54% of all of the globular proteins in this milk, this protein is followed by camel serum albumin (CSA) (36%), lactoferrine (2%), and immunoglobulins (8%) (**Figure 3**) [33].

Several works have shown that camel whey contained other specific protein components such as the PGRP (Peptidoglycan Recognition Protein), lactophorine, Wap (Whey Acidic Protein), and CWBP (Camel Whey Basic Protein) [29, 33, 41].

### *2.2.1 α-Lactalbumin*

The α-lactalbumin (α-La) is the major protein in camel whey as the β-lactoglobulin which is the major protein in bovine whey is totally absent [27, 28, 36, 40, 43]. The concentration of this protein in camel milk is significantly higher than that of cow's milk (1.08 g/L) [32] as it ranges between 2.1 g/L according to Omar et al. [32] and 5 g/L according to El-Agamy [33].

The primary sequence of camel α-La was determined by Beg et al. [42]. As its bovine counterpart, camel α-La is composed of 123 amino acids, in which 39 residues are different when compared to bovine α-La. Consequently, the similarity and identity levels between these proteins according to the sequence alignment data are

### **Figure 3.**

*Proportions of the different whey proteins of cow's milk (a) and camel's milk (b) according to El-Agamy [33]. Abbreviations: β-Lg: β-lactoglobulin, α-La: α-lactalbumin, SA: serum albumin, Ig: immunoglobulins, Lf: lactoferrin.*

82.9 and 69.1%, respectively according to Salami et al. [24]. MW and pI of camel α-La (MW = 14.43 kDa and pI = 4.87) are slightly higher than those of bovine α-La [43, 44].

Similarly to its bovine counterpart, camel α-La has a high affinity for the Ca2+ ion with a higher exposure of hydrophobic groups upon calcium depletion than the bovine α-La [45, 46]. In terms of nutritional properties, several studies have shown that camel α-La is characterized by a higher digestibility than that of bovine milk, as well as greater antioxidant activity with respect to Ferric-reducing antioxidant power, iron chelating, and antiradical activities especially in their apo forms [44]. This protein presented in its apo form great antibacterial and antifungal properties toward various pathogenic species [43, 44].

### *2.2.2 Camel serum albumin*

Serum albumin (SA) protein is a whey protein characterized by its relatively high MW. Indeed, bovine serum albumin (BSA) consists of 583 amino acids with an MW of 66.4 kDa, its primary sequence was determined Hirayama et al. [47]. It has 17 intramolecular disulfide bridges and a free thiol group. On the other hand, camel serum albumin (CSA) was identified by SDS-PAGE as a similar protein to its bovine counterpart with the same MW (66 kDa) [15, 29].

BSA and CSA were reported to have similar concentrations ~0.4 g/L with different proportions among whey proteins (1.5 and 7% of total bovine and camel whey proteins fractions, respectively). However, the contents of CSA are higher in camel colostrum with concentrations greater than 3.4 g/L [48].

### *2.2.3 Minor camel whey proteins*

Lactoferrin is a glycoprotein that belongs to the transferrin family. It contains two binding sites for iron cations and more preferentially the ferric ion (Fe3+). This ability to scavenge iron persists even at low pH values in the stomach and intestines, to deplete free iron which could slow down bacterial growth in the intestines [29]. The concentration of lactoferrin in milk varies according to the producing animal species and according to the stage of lactation. Camel milk is very rich in lactoferrin compared to the milk of other mammalian species. This richness is a form of adaptation to difficult living conditions for young camels to make them more resistant to infections [49].

Camel lactoferrin is composed of 689 amino acids with an MW of 75.3 kDa. The primary sequence of camel lactoferrin has a similarity level of 91.6% with its bovine and human counterparts and 91.3% with porcine lactoferrin. It is a basic protein with a pI of around 8.14 (compared to a value of 8.18 for bovine lactoferrin) [33].

PGRP or "Peptidoglycan Recognition Protein" is part of a family of proteins described recently. It is known for its action on gram-positive bacteria as well as other microorganisms such as nematodes. This inactivation of pathogens is carried out by the binding of this protein to the peptidoglycan of the bacterial membrane, hence its name "Peptidoglycan recognition protein" or PGRP [50]. PGRP is a protein that is not detected in cow's milk. It was isolated from camel milk by Kappeller et al. [50]. It is a protein which is characterized by its low molecular mass (19.11 kDa) containing 172 amino acids. The PGRP of camel milk is a basic protein, it is very rich in Arg residues whereas it is poor in Lys. It is found in camel milk at a concentration of 1.74 g/L [32]. The pI of camel PGRP is 8.73 which is higher than that of human PGRP (pI = 7.94). The similarity level between PGRP in camel milk and human milk is around 91.2% [33]. The PGRP content

increases in camel milk in case of infection of the mammary glands. Also, the high level of PGRP in camel milk at the start of lactation contributes to the protection of the mammary gland as well as the transmission of immunity to the newborn [50].

Camel Whey Basic Protein or CWBP (Camel Whey Basic Protein) is also a protein specific to camel milk. It was identified from camel whey by SDS-PAGE electrophoresis [51] and by ion exchange chromatography [48]. This protein, of relatively low MW (20 kDa), has a unique structure and has no analogy with other dairy proteins. It has been demonstrated in the whey of camelids of the dromedary and bacterial species.

WAP or Whey Acidic Protein is a soluble protein found in the milk of certain mammalian species including rabbits, pigs, rodents, camelids and humans. WAP is a whey protein found at a concentration of 0.157 g/L in camel milk. It contains 117 amino acids with an MW of 12.56 kDa. WAP consists of two domains with four disulfide bridges with a pI of 4.5 [33]. Thus, camel milk contains the highest rate of natural bioactive components, which explains its long shelf life compared to cow's milk [33].

### **3. Effect of processing on chemistry of camel milk proteins**

Thermal treatments are important food processes including in most dairy industries to obtain bacteriologically safe final products and to extend their shelf life. However, a number of structural modifications have been reported and noted in the milk protein components depending on temperature time, and rate of heating. For instance, Singh [52] reported that a range of large heterogeneous protein aggregates of milk proteins occurred in heat-treated milk. Indeed, the association of heatinduced milk proteins which are occurring under different heating conditions has been extensively studied by various authors [53].

Overall, both caseins and whey proteins in heat-treated milk are engaged in protein denaturation. Furthermore, the formation of intermolecular disulfide bridges is mostly responsible for heat-induced protein association in milk. Thermal protein denaturation has been acknowledged as the first step of the reactions leading to the aggregation of the disulfide-linked milk proteins. The resulted thiol groups of cysteine residues which are appearing in unfolded proteins, can initiate thiol-disulfide exchange reactions within hydrophobically-linked protein aggregates. On the other hand, self-aggregation of heat-denatured β-lactoglobulin in cow's milk, and heatinduced association of various whey proteins and their aggregates with caseins have been investigated and explained according to this mechanism [54].

### **3.1 Effect of processing on caseins**

Similarly to cow's milk, camel milk proteins are significantly affected by thermal treatment processing. However, only few studies about the effect of heat treatments on camel milk proteins including caseins and whey proteins are available in the literature [55].

First, Felfoul et al. [36] found using LC-MS and SDS PAGE electrophoreses techniques that after heating camel milk at 80°C for 60 min, various significant modifications in protein composition were observed.

Indeed, these authors noted that fresh camel milk contains α-La, PGRP, CSA, and caseins proteins as major proteins. In the same way as bovine milk, the thermal treatment of camel milk at 80°C for 60 min caused various significant modifications in proteins including whey proteins and caseins. However, camel αS2-, β-, and γ-caseins

*Chemistry of Camel Milk Proteins in Food Processing DOI: http://dx.doi.org/10.5772/intechopen.111692*

concentrations have not been significantly modified by heat treatment similarly to bovine caseins. Other study revealed that the effect of the heating temperature increases on camel milk was mild on β-casein and both αS1- and αS2-caseins, whereas it was drastic on κ-casein. Indeed, electrophoretic bands of whey proteins including CSA and α-La as well as κ-casein decreased at 90°C [56].

On the other hand, Lajnaf et al. [26] investigated the effect of different heating temperatures on extracted camel sodium caseinates at neutral pH. RP-HPLC results of these authors showed that both bovine and camel caseins peaks including κ-casein, α-casein and β-casein remained almost intact upon heating at 70 and 80°C for 30 min. However, higher temperatures (90 and 100°C) significantly affected camel casein peaks especially α-casein and β-casein, which decreased significantly at these temperatures. Furthermore, the degradation of caseins is synchronized by the appearance of new protein fractions after heating at 90°C for 30 min. In the same way, new peptides were generated upon heating from the parent caseins. Thus, the heat treatment of camel caseinates solutions results in the degradation polymerization of proteins as well as the liberation of several peptides due to protein degradation [26].

### **3.2 Effect of processing on whey proteins**

The effect of processing on camel whey proteins especially thermal processing as well as the acidification process is being studied by many researchers in recent scientific works who are interested in the valorization of camel milk and its consumption as a new alternative of bovine whey especially due to the total absence of the β-lactoglobulin in camel milk.

First, the work of Felfoul et al. [21] was considered as the first study leading to understanding the chemistry of camel whey proteins upon heating and at different pH levels as they studied the effect of different heating temperatures on sweet and acid camel whey. These authors noted that protein denaturation started after heating whey for 30 min for all temperatures. The whole phenomenon happened during 30 min of heating. The obtained results by these authors have shown that heating both bovine and camel whey at 60°C does not generate any denaturation phenomena as it is already observed by Laleye et al. [40]. The electrophoresis patterns showed also that heating camel whey at 90°C during 30 min CSA band disappearance for both rennet and acid wheys. On the other hand, α-La concentration decreased as a function of heating temperature.

As previously reported, the major camel whey proteins are α-La, CSA, and PGRP [36, 41, 48, 50, 57]. These proteins were significantly affected by heat treatment at 80°C for 60 min as revealed by Felfoul et al. [36]. Indeed, the corresponding peak of CSA decreased significantly after heating at this temperature while camel α-La and PGRP have completely disappeared from the HPLC-UV chromatograms. Indeed, these authors found that the concentration of CSA in fresh camel milk was decreased by 42%, while PGRP concentration decreased by 68%, whereas, there was 100% of α-La disappeared from camel milk. Thus, the most heat-sensitive whey protein in camel milk obviously corresponds to camel α-La followed by PGRP and CSA [21, 36]. In the same way, Lajnaf et al. [28] found that the chromatographic peak of the α-La began to decline after the heat treatment at 70°C for 30 min, it decreased significantly when the heating temperature raises from 80 to 100°C for 30 min. Thus, the reduction of the chromatogram peaks is the consequence of the protein denaturation and aggregation upon heating [28]. However, for bovine milk, the peaks of the α-La and the β-Lg started immediately diminished after the heat treatment at 80°C for 30 min.

The peak of β-Lg totally disappeared after heating at 90 and 100°C for 30 min, unlike the β-Lg dimer peak that increased due to the creation of heat-induced disulfide-bonded dimers as intermediates in the whey proteins aggregation [28].

On the other hand, differential scanning calorimetry (DSC) thermograms of Felfoul et al. [21] showed that denaturation temperatures of camel α-La were 73.8°C in camel rennet whey and 60.5°C for camel acid whey. Atri et al. [45] noted that denaturation temperatures of purified camel α-La are 71.7 and 39.6°C in its holo (calcium loaded) and apo (calcium depleted) forms. Indeed, the absence of β-lactoglobulin in camel milk whose denaturation temperatures are 79.6 and 83.4°C in sweet and acid bovine wheys, respectively resulted from different denaturation and aggregation phenomena during heat treatment [21].

Other scientific works have shown that the combination of heating treatment and acidification of camel wheys induced an immediate disappearance of the α-La and the appearance of several intermediate protein species including dimers, trimers of α-La. These protein species were formed during heating and before aggregation [20]. These authors have found that acid wheys carried higher denaturation levels compared to sweet wheys regardless of heating temperature value. These findings confirmed that acid whey is characterized by a higher thermal sensitivity than the sweet one with the higher thermal sensitivity of camel whey proteins compared to bovine whey proteins especially at neutral conditions [20]. In the same way, Laleye et al. [40] noted that camel milk whey proteins are slightly more susceptible to heat denaturation than bovine whey proteins regardless of pH level. This behavior can be explained by the particular structure of camel α-La, especially in acidic conditions. Lajnaf et al. [41] reported that the open structure of the camel α-La molecule and the reduced electrostatic repulsion of this protein near its pI are all factors that could promote the creation of large aggregates. In the same way, Lajnaf et al. [57] observed that the purified camel α-La isolated from camel milk was more flexible in acidic conditions, regardless of heating temperature, due to the reduced negative charge of this protein and its molten globular state at low pH values.

Recently, Lajnaf et al. [43] reported that there are various structural differences between the camel and bovine α-La as a function of different denaturing conditions in food processing including pH, heating temperature, and guanidine hydrochloride mediated. Camel α-La showed higher stability toward thermal treatments and pH-mediated denaturation. However, it was less stable toward guanidine-mediated denaturation with a fast aggregation and a more disordered structure when compared to its bovine counterpart [43, 58].

### **4. Effect of processing on camel milk protein functionality**

### **4.1 Foaming properties**

The foaming and stabilizing properties of camel milk as well as its protein fractions were investigated by different authors [28, 41, 59–61]. First, Lajnaf et al. [26, 28] studied the effect of different heating temperatures ranging between 70 and 100°C on skimmed camel milk as well as extracted sodium caseinates. These authors noted that for the camel milk and sodium caseinates, heating improved significantly the foamability in comparison with that of bovine milk and bovine caseinates, with better foaming capacity achieved after a heat treatment at 90 and 100°C due to the presence of higher amounts of β-casein in camel milk. Indeed, this

### *Chemistry of Camel Milk Proteins in Food Processing DOI: http://dx.doi.org/10.5772/intechopen.111692*

protein is well known as a mobile disordered protein due to its particular flexible structure [62]. However, lower foam stability of camel milk and camel caseinates foams is observed due to the different protein composition of both milk proteins especially the absence of β-Lg and the lower amounts of κ-casein [26, 28]. On the other hand, the stability of foam formed from skimmed camel and bovine milk increased significantly with increasing preheating temperatures up to 90°C, above which lower foam stability is observed [28]. While for camel sodium caseinates, foam stability increased as a function of heating temperature even at 100°C [26]. The increase in foaming properties of camel milk is attributed to an increase in the hydrophobic interactions due to an exposure of hydrophobic groups, which are already buried inside the globular structure of whey proteins [28, 63]. Furthermore, this behavior can be explained by the increase in the adsorption velocity and the diffusion of milk proteins upon heating at the air-water interface as confirmed by Dickinson [64]. In the same way, heat treatment significantly ameliorated the foaming properties of camel and bovine sodium caseinates especially at hightemperature values (90 and 100°C for 30 min).

Parallely, the heating process affects the physicochemical properties of caseins including the increase of surface hydrophobicity due to the greater exposure of buried hydrophobic groups and the increase of the ability to reduce the interfacial tension at the air-water interface. The heating process also decreases the electronegative charge of proteins leading to a greater flexibility and hence, higher foaming properties of heated milk proteins [26].

The foaming properties of camel whey proteins are significantly affected by different stabilizing food processing, especially thermal processing and acidification. This behavior is mainly explained by scientists as camel milk is totally deficient in β-Lg because it is well-known that this protein plays a key role in the process of protein aggregation in bovine whey solution [60].

Camel whey foaming properties are reported to depend on both pH value and thermal treatments. Camel whey solutions showed the best foamability closed off the isoelectric point of camel α-La (around pH 4.3), regardless of heating temperature. Thermal treatments at 70°C significantly improved the foaming properties of both bovine and camel acid wheys. However, the stability of foam greatly increased upon heating only for the acid camel whey [41]. Acid camel whey is distinguished by its exceptional ability to create foams with the greatest foam stability if compared to other whey, with an increase of these properties after a heat treatment. Hence, the lack of β-Lg in camel whey leads to exceptional foaming properties of this whey, especially with the combination of preheating and preacidification before the creation of the foams [41]. In the same way, the foamability of camel α-La in solution was maximal in acid conditions, near its effective pI. Indeed, at this acid pH, the protonation of the negative groups decreased the electrostatic repulsions of the α-La and induced a partial denaturation with the release of its chelated calcium. The obtained molten globular state enhanced the foaming properties of this protein. Heating processes improved the stability of the foam which is created by camel α-La due to the presence of aggregated proteins at the air-water interface. Aggregates are reported to contribute to improving foam stability whereas, they slowed the adsorption of proteins and the creation of foam [43, 57]. In addition to the heating process, the effect of the spray drying process on the techno-functional of camel milk proteins was investigated by Zouari et al. [65] noted the low denaturation extent of camel and bovine milk proteins powders participated in the enhancement of their foaming capacity and stability [65].

### **4.2 Emulsifying properties**

Emulsification is a common food process in the food industry, it is encountered with mayonnaise sauces, cream, soups, butter, and margarine [66]. Overall, oil-inwater emulsions are produced by the homogenization process of oil and aqueous phases in the presence of emulsifiers which are adsorbed onto the surfaces of oildroplets leading to the reduction of the interfacial tension and emulsion creation. In the food industry, the most common emulsifiers used are milk proteins including caseins such as β-casein which is the most surface-active dairy protein, and whey proteins including β-Lg and α-La [62, 66]. The effect of food processing on the ability of camel milk proteins to create and stabilize emulsions was studied by different authors [20, 60, 67]. First, Lajnaf et al. [20] reported that camel whey emulsifying properties depended on both pH level and the degree of denaturation of these proteins after a heat treatment. Higher emulsifying activity stability was obtained for sweet whey especially the sweet camel whey due to the presence of electrostatic repulsive forces between proteins. However, acidification reduces these repulsive forces leading to the reduction of emulsifying properties of milk proteins.

Laleye et al. [40] reported the lower emulsifying properties of pre-acidified camel whey when compared to bovine whey due to the pronounced aggregation of camel whey protein molecules. Indeed, the aggregation behavior of camel whey proteins at lower pH values is associated to the high content of the α-La [40]. Furthermore, thermal treatments of camel whey proteins at 70 and 90°C improved the emulsifying properties of these proteins, especially in acidic conditions due to the denaturation and aggregation of proteins. Indeed, the size of whey proteins' aggregates is higher in acidic conditions than in neutral pH due to the minimized electrostatic repulsion between neigh-boring proteins molecules leading them to interact and aggregate. These aggregates are characterized by a greater ability to stabilize foam and emulsion compared to native proteins [20, 68].

Momen et al. [60] studied the effect of the heating process at 85°C for 15 min in a temperature-controlled water bath on the created emulsions. These authors noted that the emulsions prepared with camel whey proteins did not show any visible aggregation or gelation after heat treatment, whereas emulsions prepared by bovine whey proteins formed a gel-like structure in different protein concentrations. Indeed, the limited heat-induced modification in the conformational structure of camel whey proteins confirmed that these proteins are not very sensitive to heat-induced disulfide bridging and hydrophobic interactions. Thus, this study showed the technological viability of camel whey protein for the fabrication of high-protein emulsion. In the same way, the emulsifying properties of camel α-La were less sensitive to various thermal treatments at 95°C. This behavior was explained by the higher conformational flexibility of this protein which increased with temperature, contrary to its bovine homologous protein [67, 69]. Indeed, bovine α-La enhanced emulsion stability as a function of pH and heat treatment, due to hydrophobic interactions and a more rigid molecular structure compared to camel α-La [69]. Furthermore, a higher surface coverage of the oil droplets was obtained for camel apo α-La which carried the highest ability to reduce the surface tension values at the oil-water interface when compared to bovine α-La in its holo and apo states. The stability of the created emulsions seemed greatest at neutral pH due to the presence of the electrostatic repulsive forces between the adsorbed α-La molecules contrary to these molecules in acidic conditions. These conditions reduced these repulsive forces leading to the decrease of emulsifying properties of camel α-La [43, 44].

### *Chemistry of Camel Milk Proteins in Food Processing DOI: http://dx.doi.org/10.5772/intechopen.111692*

Ellouze et al. [70] reported that camel milk β-casein showed an enhanced ability to form softer emulsions and to stabilize oil droplets in acidic conditions, regardless of heat treatment compared to bovine β-casein. However, the heating process affects the interfacial properties of β-casein. Indeed, the ability of this protein to create emulsions did not show any effect upon heating, whereas, stabilization of emulsified oil droplets with β-casein is higher without the heating process as proteins retain their native structure with no thermal denaturation, which allows intramolecular hydrophobic interactions and hence, the maintenance of a stable protein film around the created oil droplets. On the other hand, surface pressure was higher in acidic conditions for camel β-casein and after a thermal treatment at 95°C. This phenomenon is explained by hydrophobic interactions and a relaxed structure allows proteins to be more cohesive under the applied treatments [70]. In the same way, emulsifying properties of camel β-casein solutions depended on pH level with or without thermal processing. Preacidification affects the physicochemical properties of camel β-casein by increasing the surface hydrophobicity and also decreasing the negative charge and the efficiency to reduce the interfacial tension. Therefore, casein precipitation decreases the emulsifying properties of camel β-casein and its ability to create and stabilize emulsions [70].

### **4.3 Gelling properties**

The effect of different food processing on gelling properties of camel milk was described by few scientific works. First, Zouari et al. [71] studied the effect of the acidification process on the gelation of camel milk and found that the gelation behavior of camel milk is mainly controlled by the pI and hydrophobic interactions. These authors found that the intermolecular interactions between different camel milk caseins are higher and stronger when compared with those in bovine milk. The effect of thermal processing on the quality of fermented camel milk products including yogurt and cheese is not completely investigated. The fermentation process of milk into yogurt requires pre-heating in order to denature the whey proteins and form disulfide bridges between these proteins and κ-casein, leading to improved yogurt structure. Manufacturing yogurt from camel milk is difficult and the yogurt curd produced from camel milk is fragile and has a thin consistency because of the presence of bioactive antimicrobial components including PGRP and lactoferrin [2]. Furthermore, the different compositions of camel milk whey proteins, such as its lack of β-lactoglobulin and the predominance of α-lactalbumin are also the reasons for the fragile structure of camel milk yogurt [72]. Pasteurization process of the camel at temperatures higher than 65°C for 30 min results in the manufacturing of camel cheeses with significantly weaker gels [73, 74]. Furthermore, high-pressure processing of milk at 350 MHz for 5 min produces harder cheese than pasteurization treatment at 65°C for 30 min [72]. Finally, further studies are needed to understand and to explain the effect of various food processing, especially thermal ones on gelling properties of camel milk.

### **5. Conclusion**

Camel milk is different in its composition from that of cow's milk including fats, minerals, lactose, and proteins. The main differences in camel milk proteins composition are the total absence of the β-Lg and the low amount of κ-casein, leading to confirm

that β-casein and α-La are the major proteins in colloidal and soluble fractions of camel milk, respectively. Camel milk proteins show different behavior when compared to bovine proteins. For instance, previous studies noted that heating treatment of milk significantly affects α-La followed by PGRP and CSA, with a relative thermal sensitivity of whey proteins when compared to caseins. However, thermal treatment of camel caseinates leads to the degradation and denaturation of individual caseins including α-casein and β-casein which is probably associated with liberation of resulted peptides. Different techno-functional properties of camel milk proteins are significantly affected by food processes including thermal processes and nonthermal such as acidification. For instance, the combination of acidification and thermal treatments improves the foaming properties of whey proteins, while these processes reduced emulsifying properties of camel whey proteins.

Finally, this chapter investigates the interesting techno-functional properties and the chemical of camel milk proteins as a function of different food processes. Hence, this could confirm the strong potential of camel milk for potential applications in the food, pharmaceutical, and cosmetic industries.

## **Author details**

Roua Lajnaf1,2\*, Hamadi Attia1 and Mohamed Ali Ayadi3

1 Alimentary Analysis Unit, National Engineering School of Sfax, Sfax, Tunisia

2 Montpellier University, UMR IATE, Montpellier, France

3 Department of Food Technology, University of Liege—Gembloux Agro-Bio Tech, Gembloux, Belgium

\*Address all correspondence to: roua\_lajnaf@yahoo.fr; roua.lajnef@enis.tn

© 2023 The Author(s). Licensee IntechOpen. This chapter is distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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### **Chapter 3**

## Physicochemical Characterization of Mesquite Flour (*Prosopis laevigata*), Particle Size Distribution, Morphology, Isosteric Heat, and Rheology

*Sadoth Sandoval Torres, Larissa Giovana Reyes López, Lilia Leticia Méndez Lagunas, Luis Gerardo Barriada Bernal and Juan Rodríguez Ramirez*

### **Abstract**

Mesquite pods were dried and milled. The physicochemical properties of mesquite flour were characterized. The pods were dried at 60°C, 15% RH, and 2 m/s airflow. After drying, two types of milling were applied: (1) industrial blade mill and (2) Blender, and the nutritional composition was determined. The sorption isotherms were obtained at 30, 35, 40, and 45°C for a range of water activity of 0.07–0.9. The particle size distribution and the average particle size of the flours were characterized by means of diffraction of blue laser light; furthermore, the morphology was analyzed by (SEM). The powders were also analyzed by DSC. Alveography was applied to study the rheology of the flour. Mesquite powders are highly hygroscopic, and the (GAB) model displays a good description of the experimental data. Flours expose different morphologies depending on the milling technique; a more homogeneous powder was obtained from the industrial blade mill. Rheological characterization indicates that mesquite flour decreases the tenacity and extensibility of the flour mixture. According to DSC, the flours are very stable over a wide temperature range from 0 to 120°C, and the thermograms indicate a transition of proteins affected by high-molecular-weight carbohydrates and moisture content.

**Keywords:** ethnic food, drying, milling, powder properties, nutritional

### **1. Introduction**

Mesquite (*prosopis spp*) trees grow in dry environmental conditions, counting 44 species in the world [1, 2]. Mesquite tree appertains to genus *Prosopis* and is present in semiarid lands of America [3]. It has been documented that *Prosopis* pods have been

food intakes of people from arid and semiarid regions in South America [4], and according to [5], the *Prosopis* pods are highly palatable to humans.

In Mexico, mesquite is found in different regions of the country. In the past, the native people utilized mesquite pods as food, to prepare flour, syrups, and bread [6]; nevertheless, the pod's morphology varied substantially across different regions [7].

According to [1], mesquite pods have a complex morphological structure; the important protein content and the sucrose content reveal a potential for the production of new ethnic foods. As a raw material mesquite pods can be used for baking, snack food, sweetener, gum, and protein concentrate.

*Prosopis pallida* and *Prosopis juliflora are varieties with especially large and sweet fruits, and* were studied by [8]. The authors explored different applications for every component of the fruit (exocarp, mesocarp (pulp), and endocarp), the episperm, endosperm, and cotyledon of the seed. They affirm sucrose is the main sugar component in the pulp; galactomannan is the most important polysaccharide in the endosperm, and glutamic acid, arginine, aspartic acid, leucine, proline, and serine were identified in the seed cotyledon. In the pulp, vitamin C, nicotinic acid, and calcium pantothenate were identified. In other study [9], authors characterize the phenolic antioxidants occurring in the pod mesocarp flour of Chilean *Prosopis*; they conduct an HPLC-MS/MS analysis identifying the presence of eight anthocyanins and 13 phenolic compounds including flavonol glycosides, C-glycosyl flavones, and ellagic acid derivatives. The antioxidant activity and the phenolic composition of this product reveal its potential as a functional food.

The structural and functional properties of *P. alba, P. chilensis, and P. flexuosa* were assessed by other author [10]*.* The flours were characterized by granulometric analyses, water absorption, oil absorption, solubility, and color. Drying and milling process allows ultrastructural changes, modifying the membranes of proteins and changing their capacity to absorb water. The values of solubility reveal flours can be used for the elaboration of liquid foods and candies. According to [2], *Prosopis* mesocarp flour contributes to the browning, color, aroma, and flavor of baked products.

In other work [11], the authors studied the fruits of *Prosopis alba* and *P. pallida*. A drying process was applied at 60°C for 60 h, then a hammer milling process was used. The findings reveal proteins, calcium, iron, dietary fiber, and sugars as the principal constituents of the pulp. The efficiency of the milling and sieving for *P. alba* and *P. pallida* were 54.5% and 55%, respectively. The total sugar content was higher in *P. alba* than *P. pallida* and protein content was higher in *P. pallida* than *P. alba*.

In another study, the authors investigated the particle size, morphology, rheology, physicochemical, and mineral composition of *Proposis julifrora* [3]. Drying at 60°C was applied, after that the pods were analyzed. Sieves with a meshing of 32–150 were used. The flour exhibited an important concentration of fibers, calcium, and phosphorous. The results of rheology indicated that mesquite flour is suitable for cookie production.

In other work, the genotoxicity of *prosopis* flour was addressed [4]. The authors affirm sucrose constitutes the main sugar in flours obtained from *P. alba* and *Prosopis nigra*. *Prosopis* extracts did not reveal any mutagenic effect with and without metabolic activation. The authors conclude *Prosopis* flour is a rich source of antioxidant compounds that could avoid pathologies related to oxidative stress.

For the elaboration of bakery products and/or confectionery, it is indispensable the use of flours with the ideal characteristics that can satisfy the culinary necessities and that in turn can be conserved [10]. Currently, the use of mesquite pods in the food industry is uncommon [2, 5]. Then, the aim of this work was to assess the physicochemical and rheological characteristics of mesquite flours (*Prosopis laevigata*)

harvested in Oaxaca State (Southern of Mexico) in order to develop foods with important nutritional value without gluten and take advantage of the agro-food resources of semiarid zones. The particle size distribution, the particle morphology, the isosteric heat of sorption, and the thermal stability were also studied.

### **2. Materials and methods**

Pods of *P. laevigata* were harvested between April and August 2016 in the community of Santiago Sulchiquitongo (Oaxaca, Mexico). Three stages of maturation were identified [12]. Pods in stage three of maturity were used for drying. The drying process of pods was performed using a convective tunnel dryer [13]. The drying conditions were as follows: an airflow at 60°C, with a relative humidity of 15%, and an air velocity of 2.0 m/s. After drying, pods were stored in a desiccator.

The pods reached a final moisture content of 0.12 g of water/g dry matter. Once dried, the mesquite was milled by implementing two techniques; 1) an Osterizer blender, model 465–15 for 20 seconds and 2) a mill blade pulverizer Model HC-2000Y, for 20 seconds. The mesquite powder was passed through # 60 (0.250 mm) and # 80 (0.177 mm) sieves and each mill was stored in low-density polyethylene bags in a vacuum desiccator for 24 hours. A more homogeneous material was obtained from the mill blade pulverizer, then, powders from this milling technique were subsequently analyzed.

### **2.1 Chemical characterization of flours**

The chemical-proximal and nutritional composition of the flours were obtained. The moisture content, the total raw protein content, the reducing and direct sugars, the total fat extraction, the raw fiber, and the ash were determined by methods published in [12].

### **2.2 Particle size distribution**

The size distribution of a particulate product is dependent on the shapes of its particles [13, 14]. The particle size distribution determines the critical chemical and physical properties of particulate systems [15]. Particle size induces many properties of powder materials and is a significant indicator of quality and performance. For this reason, the particle size distribution of mesquite flours was analyzed using the principle of blue laser light diffraction measurement [16]. For this purpose, we use a Microtrac Blueray M3551-1 W-BU00 in a humid medium, with a measuring range of 10 nm up to 2000 microns. The method is presented in [12].

### **2.3 Morphology of flour particles**

Images from samples of mesquite flour were obtained. A scanning electron microscope (SEM) JEOL brand, model JIB-4601F, with a spatial resolution of 1.2 nm, a focused ion beam, and a digital camera (CIIDIR-Oaxaca, Mexico), was used in this work. The flour samples were placed in small graphite plates and introduced into the SEM vacuum chamber. In our analysis, a secondary electron detector E-T (Everhart-Thornley) and a backscattered electron detector were used. A range of magnification from 50x to 2500x was used for the images.

### **2.4 Sorption isotherms**

According to [17], powder processing must be conducted under controlled relative humidity and temperature in order to enhance the storage, handling, and processing. As the relative humidity of the surrounding air is increased, powders tend to absorb water, which may form liquid bridges between powder particles and result in greater powder cohesion. The sorption isotherms of mesquite powders (*Prosopis Laevigata*) were assessed by the gravimetric static method with water activities ranging from 0.07 to 0.97 at four temperatures: 30, 35, 40, and 45°C. The salts used in this work were the following: NaCl, MgCl2 � 6H2O, KOH, KCl, KI, K2SO6, and Mg NO ð Þ<sup>3</sup> <sup>2</sup> � 6H2O [18, 19] The details of this method are presented in [12]. Experimental data was fitted to the (GAB) (Guggenheim-Anderson-Deboer) model (Eq. (1)). The theoretical fundamental for the GAB sorption isotherm is the assumption of localized physical adsorption in multilayers without lateral interactions [20]. The parameters for this model were estimated by implementing the equation in excel (GRG nonlinear).

$$\text{Xeq} = \frac{\text{Xm} \cdot \text{C} \cdot \text{k} \cdot \text{aw}}{(1 - \text{k} \cdot \text{aw}) \cdot (1 - \text{k} \cdot \text{aw} + \text{C} \cdot \text{k} \cdot \text{aw})} \tag{1}$$

where *Xeq* is the equilibrium moisture content (g H2O/g dry basis), Xm is the monolayer moisture content (g H2O/g dry basis), and C is a heat-related constant of the monolayer, *k* is a constant related to the sorption heat of the multilayer, and *aw* is the water activity.

### **2.5 Isosteric heat of sorption**

The estimation of energy consumption during drying needs the knowledge of the enthalpy of water sorption in the entire range of moisture contents. Certainly, the use of the enthalpy of vaporization of pure water can give inaccurate results [21]. The isosteric heat of sorption is a useful expression, notably in the design of drying operations, as heats of sorption rise well in excess of the heat of vaporization of water as food is dried to low moisture contents [22]. The net isosteric heat of sorption measures the binding energy of the forces between the water vapor molecules and the solid phase [23]. It gives information for the comprehension of the sorption mechanism [20]. The gap between the amount of energy necessary to remove water from the flour and the amount of energy needed for normal water vaporization is defined as the net isosteric heat of sorption. The isosteric heat of sorption (Q*st*) was estimated by using the equation derived from Clausius Clapeyron [22–24]; in order to calculate the enthalpy change associated with the sorption process (Eq. (2)).

$$
\left[\frac{\partial \ln \left(a\_w\right)}{\partial (\mathbf{1}/T)}\right]\_{\rm{CHE}} = -\frac{Q\_{st} - \lambda}{R} = -\frac{q\_{st}}{R} \tag{2}
$$

where qst is the isosteric heat of sorption, R is the universal constant of the gases (0.00831 Joules/K�mol), *aw* is the water activity, T is the temperature (K), and λ is the latent heat of vaporization of pure water at room temperature. For

isosteric heat of sorption, we used the experimental information of the sorption isotherms.

### **2.6 Differential scanning calorimetry (DSC)**

The scanning calorimetry provides a direct estimate of the overall enthalpy change of transitions without requiring knowledge of the thermodynamic mechanism; moreover, the sample preparation is minimal [25]. Four samples of mesquite flours (*P. laevigata*) previously conditioned at a relative humidity of 7%, 32%, 51%, and 67% were prepared for a DSC analysis (TA Instruments, model Q2000). 17 mg of flour was placed inside hermetic aluminum capsules and sealed by a press. The experimental conditions consisted in running the samples at an initial temperature of 0.0°C, followed by a heating rate of 2°C/min up to an end temperature of 250°C. The thermograms were analyzed by using the TA Instruments DSC software.

### **2.7 Alveography**

Alveograph method is useful to estimate the potential performance of flours [26]. The Alveograph test provides a test sample of dough, which, under air pressure, forms a bubble. The test recreates the deformation of a dough when is subjected to carbondioxide during fermentation [27].

Alveographic characteristics were analyzed for three mixtures of wheat/mesquite flour. Experiments were conducted in triplicate in alveographic equipment (Chopin Technologies, France), following the AACC Method 54–30.02 [28], quantifying the following parameters: tenacity (P), extensibility (L), and dough deformation energy (W).

The tenacity is the capacity to resist deformation, extensibility is the maximum volume of air that the bubble is able to enclose, and deformation energy corresponds to the dough baking strength.

### **3. Results and discussion**

The pods show different shades of color during maturity; these changes are accompanied by variations in the organoleptic and physical properties. According to [12], pods reveal three stages of maturity: pods in stage 1 showed a green coloration, in stage 2 the pods were brighter with a reddish coloration, and in stage 3 the pods increased in brightness compared to the previous stages, reddish and yellow coloration was still observed, cream color is characteristic of this last stage. For the study, we used exclusively pods in stage 3 of maturation.

### **3.1 Chemical composition of flours**

The nutritional composition of mesquite flours is shown in (**Table 1**). The nutritional compositions of mesquite flours present a complete composition of macronutrients. Some differences according to the type of milling were observed, the fiber content was higher for milling with a blade mill; however, the proteins decreased slightly. Both flours are suitable for use as complement flour or as a natural supplement.


**Table 1.**

*Nutritional composition of mesquite flour (*Prosopis laevigata*) obtained by two different grindings.*

### **3.2 The particle size distribution**

In **Figure 1** we show the size distribution of the flours. During the procedure, the aggregates were dispersed with the help of the sample dispersion accessory, and a power of 30 watts was applied for 30 s.

For the flour obtained from the blender (**Figure 1a**), two oblations were identified. Particles of 1.291 microns with 95% up to 657 microns and a cumulative 10% of particles of 28.93 microns were measured.

For the blade mill (**Figure 1b**), the particle size distribution showed a smooth and unique Gaussian distribution. The sample was dispersed very nicely with the simple agitation of the circulatory without forming aggregates. The fine particles are presented from 28.53 microns with a cumulative 10% of particles of 64.23 microns. There are particles as large as 497 microns, with a cumulative 95% of 302.5 microns. The powders showed a homogeneous distribution with adequate particle size. Mesquite flour can be used for the elaboration of baking and confectionery products.

### **3.3 Morphology of flour particles**

The (SEM) images of flour particles are shown in **Figure 2**. The two methods of milling produce different morphologies of powders. Diverse shapes and sizes of mesquite particles with irregular surfaces are identified, and the smooth and striated parts are shown.

**Figure 1.**

*(a) Particle size distribution – Blender; and (b) Particle size distribution – Blade mill pulverizer.*

*Physicochemical Characterization of Mesquite Flour (*Prosopis laevigata*)… DOI: http://dx.doi.org/10.5772/intechopen.105902*

### **Figure 2.**

*(a) Micrographs of mesquite flour (Blender), 330; and (b) Micrograph of mesquite flour (Blade mill), 1500 .*

**Figure 2a** shows the morphology of powders obtained from the blender. It shows a slight agglomeration and striated parts forming a tortuous, irregular, and rocky agglomerate. It can be observed the presence of some cavities that can allow the moisture adsorption. **Figure 2b** shows the morphology of powders obtained by blade mill. It reveals the surface of a particle with a rounded structure, better defined, with smooth surfaces without forced cuts.

### **3.4 Sorption isotherms**

The experimental information and the simulations of the GAB model at 30, 35, 40, and 45°C are shown in **Figure 3**, which display a Type II isotherm shape, and indicate a likely small adsorption force in the monolayer [29, 30]. This type of isotherm has been presented in materials containing fibers and polysaccharides of cereals (wheat,


### **Table 2.**

*Estimated parameters for the GAB model.*

rice), tubers (potato, cassava), proteins (soybean, maize), and starches, these components are present in the mesquite flour. In the experimental curves, it was observed that the equilibrium moisture content notably increases for aw = 0.67–0.97. The GAB model correctly represented the experimental data for all experimental conditions, giving a %Error of 10–15%. **Table 2** shows the parameters estimated from the GAB model.

According to [20], parameter C indicates the strength of binding of water to the primary binding sites. The larger the C, the stronger water is bound in the monolayer, and the larger the difference in enthalpy between the monolayer molecules and multilayer molecules. In the case of parameter K, when it approaches one (our case), there is almost no divergence between multilayer molecules and liquid molecules. In that case, the water molecules beyond the monolayer are not structured in a multilayer, but have the same characteristics as the molecules in the bulk liquid, as discussed by [31].

### **3.5 Isosteric heat of sorption**

**Figure 4** shows the evolution of isosteric heat (Qst) versus the moisture content (Xw) of mesquite flour (*Prosopis laevigata*). We observe Qst decreased rapidly with the increase of Xw; being the lowest value of Qst at 47.69 kJ/mol at 0.25 of Xw. This situation indicates a low availability of active sites and liaison forces on the surface of the powder [23]. When the moisture content is 0.15 g of water/g of dry matter, the heat needed to evaporate the water from mesquite flour would be 57.03 kJ/mol., without affecting the stability of the powder. The net isosteric heat of sorption estimates the binding energy of the forces between the water vapor molecules and the solid phase. It allows a better comprehension of the sorption mechanism.

**Figure 4** depicts positive quantities, manifesting the endothermic behavior of desorption. The isosteric heat of sorption decreases as moisture content increases. This fact refers to the intermolecular attraction forces between sorptive sites and water vapor.

The higher the moisture content, the less energy is necessary to remove water molecules from the flour. As drying continues sorption will perform at active sites demanding higher interactive energies [20].

### *3.5.1 Differential scanning calorimetry (DSC)*

Since food powders are complicated mixtures of compounds, it is regularly difficult to identify their phase's transitions accurately. **Figure 5** shows the DSC curves for *Physicochemical Characterization of Mesquite Flour (*Prosopis laevigata*)… DOI: http://dx.doi.org/10.5772/intechopen.105902*

**Figure 4.** *Isosteric heat of sorption.*

mesquite flours exposed at four RH (6.3, 31.8, 48.5, and 66.1%). If it is true that flour contains protein, the heat denaturation temperatures of proteins *in solution* are normally below 100°C; nevertheless, proteins become stable toward heat when the moisture content is low. A clear example of moisture effect on protein denaturation is published in [32]. A DSC thermogram for wheat flour is presented by [17]; in this work, a crystallization peak was observed near 190°C, which is referred by the authors as a decomposition of the flour. In our work, the glass transition (Tg) of the mesquite flour was not observed, due to possible flexibility and mobility of the glucose and fructose chains, provoked by the increase of moisture content of the powders when exposed at different RH (6.3, 31.8, 48.5, and 66.1%). According to [33], the glass transitions of high molecular weight carbohydrates and proteins arise well above 100°C and approach thermal decomposition temperatures of the food powder. Moreover, the plasticization effect of water leads to depression of the glass transition temperature causing noticeable changes in the physicochemical and crystallization properties of the material.

The transitions shown in **Figure 5** display a first-order behavior. The transition phase that was observed in all the flour samples was the crystallization peaks (Tc) from 140–157°C. Likewise, the heat flow of the endothermic transitions increased as the moisture of the flours increased, corroborating the effect of the relative humidity in the modification of the structure of the flours. It is also well-known sugars affect the protein thermal properties [25]. The thermograms of mesquite flour showed significant endotherms in the range of 130–180°C, being associated with a melting of the simple sugars present in the flour.

According to Barba de la Rosa et al. [34], sugars such as glucose, maltose, L-arabinose, and sucrose are found in high proportion in mesquite pods, so the transitions for this food can be related to a binary water-carbohydrate system.

The thermograms in **Figure 5** show the transition of proteins affected by high molecular weight carbohydrates and moisture content of powders.

**Figure 5.** *DSC curves of mesquite flours (*Prosopis laevigata*).*

### **3.6 Alveography**

The water absorption of mesquite flour can significantly affect the rheological properties of a mixture. According to our results (**Table 3**), the dough's tenacity ranged 18–83 mmH2O, decreasing with the increase of mesquite flour content of 0–15% (wt). According to [35], tenacity values for standard wheat quality range 60– 80 mm H2O, and very good wheat quality 80–100 mm H2O, then mesquite flour decrease the quality of the mixture, for this reason, it should be mixed at low concentrations for baking applications.

Extensibility characterizes the average length of the alveogram from the point at which the bubble starts to inflate to the point at which the bubble breaks. Extensibility (L) decreases as mesquite content increases, so mesquite flour impacts the handling properties of the dough. According to [3], when the concentration of mesquite flour is increased, tenacity and extensibility are reduced, and this fact can be explained by the weakening of glutenin protein (a protein responsible for elasticity and extensibility), and also due to a lower water absorption due to the high fiber content of mesquite flour. The higher the addition of mesquite flour with wheat flour, the dough may have a lower capacity to retain the gas generated during fermentation and rising of the bread. The energy of deformation (W) ranged 2.6–4.2, indicating that as mesquite


**Table 3.** *Results of the alveography.*

*Physicochemical Characterization of Mesquite Flour (*Prosopis laevigata*)… DOI: http://dx.doi.org/10.5772/intechopen.105902*

proportion increases the baking strength decreases. W is frequently referred to as flour strength, dough strength, baking strength, or flour protein strength [36]. W is one of the industrially most applied alveograph parameters, as it is used for prediction of processing behavior of flour cultivars [35]. For example, according to [37] bread flours are characterized by larger W values compared to biscuit flours. W is positively related to the water absorption of the flour [38]. According to our results, an increase in mesquite flour content reduces water absorption, then, this effect should be considered on the type of application, either in baking or as biscuits.

### **4. Conclusions**

Dried pods were milled by two milling techniques. The two techniques of milling produce different morphologies of powders. Particles from the blade mill were more homogeneous, they showed a smooth and unique Gaussian distribution, and SEM images reveal a rounded structure, better defined, without rocky parts nor forced cuts. The flour from blade mill has an adequate particle size to be used as flour for baking and confectionery products. Flours from the two different grindings have an important content of protein, sugar, and fibers. Mesquite flours showed a type II isotherm for the three experimental temperatures, indicating a possible small adsorption force in the monolayer. Flours are notably hygroscopic, and this phenomenon is related to the sugar content and the powder's microstructure. The isosteric heat reveals the endothermic behavior of desorption and the energy required to remove the water molecules from the powder.

The calorimetric data of the flours showed thermal stability in a wide temperature range; however, for temperature > 130°C crystallization peaks (Tc) were observed (from 140–157°C), which show the transition of proteins affected by sugars and moisture content.

Our results confirm that, as the mesquite flour proportion increases in the mixture, the flour became poorer. Tenacity values for standard wheat quality range 60–80 mm H2O, whilst our mixtures showed lower values. According to the values for extensibility, the presence of mesquite flour affects the handling properties of the dough. The values of deformation energy show mesquite flour develop a weak baking strength, then it should mix at low concentrations for baking applications since an increase in mesquite flour content reduces water absorption. The nutritional composition of the flour releases useful attributes for many applications in food industry, however, this information should be carefully studied, depending on the application of mesquite flour, either in baking or as biscuits.

### **Acknowledgements**

Authors express special thanks to Conacyt for the scholarship granted to Larissa G. Reyes López and Daniel López Cravioto, and the Instituto Politénico Nacional (Mexico) for SIP funding 20161016, 20170755, 20180678, and 20195013.

The authors are particularly grateful for the assistance given by Administración Profesional de Servicios Xoluciona S.A. de C.V. for the technical assistance in the analysis of particle size distribution and the use of Microtrac Blueray M3551-1 W-BU00.

### **Funding**

This work was supported by the Instituto Politécnico Nacional and CONACYT.

### **Author details**

Sadoth Sandoval Torres<sup>1</sup> \*, Larissa Giovana Reyes López1 , Lilia Leticia Méndez Lagunas<sup>1</sup> , Luis Gerardo Barriada Bernal<sup>2</sup> and Juan Rodríguez Ramirez<sup>1</sup>

1 Instituto Politécnico Nacional, CIIDIR Unidad Oaxaca, Oaxaca, México

2 Consejo Nacional de ciencia y Tecnología. Instituto Politécnico Nacional, Oaxaca, México

\*Address all correspondence to: ssandovalt@ipn.mx

© 2022 The Author(s). Licensee IntechOpen. This chapter is distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

*Physicochemical Characterization of Mesquite Flour (*Prosopis laevigata*)… DOI: http://dx.doi.org/10.5772/intechopen.105902*

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### **Chapter 4**

## Development and Optimization of Flakes from Some Selected Locally Available Food Materials

*Samuel Tunde Olorunsogo and Bolanle Adenike Adejumo*

### **Abstract**

Flakes are one of the most popular ready-to-eat breakfast cereals meals. Most traditional instant breakfast meals are from mono-cereals. This work aims to develop, characterize and optimize value-added instant cereal breakfast flakes using flours of rice, sorghum, and soybean. A three-component constrained optimal (custom) mixture experimental design was employed for the formulation. The formulation design constraints were: rice flour (30%–35%), sorghum flour (20%–25%), and soybean flour (5%–10%). Other ingredients were water (19%), sugar (8%), malt (2%), egg (3%), sweet potato (3%), ginger (2%) and moringa seed powder (3%). The formulated samples were analysed and evaluated based on standard procedures for quality characteristics. Numerical optimization gave the optimal product's overall desirability index of 0.519 obtained from 31.9 % rice flour, 22% sorghum flour, and 6.05% soybean flour; with quality properties as follows: 3.67% moisture content, 3.18% fat content, 3.08% ash content, 1.44% crude fibre, 30.0% crude protein, 58.6% nitrogenfree extract, 384 kcal energy value, and 7.28 overall acceptability. The result of the study showed that the nutritional qualities of cereal flakes can be improved through food-to-food composite formulations, employing numerical optimization technique.

**Keywords:** instant flakes, multigrain, breakfast cereals, optimization, development

### **1. Introduction**

The food manufacturing process is the transformation of raw ingredients into edible end products for human consumption. It has been a popular method of producing convenient and accessible food since ancient times. Knowing the formulation and processing profile of a food or beverage and how it quantitatively relates to consumer perceptions opens up a world of development, quality, and marketing opportunities for a food manufacturer. Methodical exploration of product features, known commonly as "response surface methodology" (RSM) is vital to manufacturing of quality products.

Cereals are the basis of many staple foods and have been used in flaking for over a century. They provide over half of the dietary energy globally and are a major source

of carbohydrates in the diet. Most traditional instant breakfast meals are produced from mono-cereals and these mono-cereals consist of carbohydrate as its major constituent. The nutritional and energy level gotten from the consumption of these monocereals is minimal. Besides, the production involves many processes and during these processes, nutrient losses occur therefore reducing its nutritional content. Major constituents of breakfast cereals are whole or broken cereal kernels (flaked, cracked) or ground (flours or meals). Importantly, new technology, like extrusion, enabled higher production rates and lowered manufacturing costs, but ended up having an impact on where cereals are today [1, 2].

Flakes are convenient and relatively shelf stable breakfast cereals, primarily produced from corn, wheat, rice, and/or oats, and processed with added flavor and fortified with vitamins and minerals. Flaking process is a relatively simple process of cooking fragments of cereal grains (or in some cases whole grains) with water, flattening the particles between large steel rollers and toasting the resultant flake at high temperature. In flaking the starch in gelatinized and probably slightly hydrolyzed. The particle then undergoes dextrinization and caramelization.

There are other grains that can be used but are presently unexploited. Soybean contains about 40% protein; it is higher than other legumes in protein. Sorghum is rich in carbohydrates and fiber. Moringa greens (leaves) are an excellent source of protein. Dry, powdered leaves indeed are a much-concentrated source of many quality amino acids. Sweet potatoes contain a wealth of orange-hued carotenoid pigments, it has been shown to be a better source of bioavailable beta-carotene than green leafy vegetables, has a high amount of Vitamin A, Vitamin B5, Vitamin B6, Thiamin and Riboflavin. Corn flakes, wheat flakes, and rice flakes are typical examples of flaked cereals. Extruded flakes differ from those made by the traditional process in that the grit for flaking is formed by extruding mixed flour ingredients through a die hole and cutting off pellets of the dough in the desired size [1, 2].

Ready-to-eat breakfast cereals are increasingly gaining acceptance in most developing countries due to their convenience, ease of preparation, and nutritional values. There is an increasing demand for convenient foods and variety as well as nutritional quality and affordability. Nutritional properties and health relevance are a key driving force in flakes manufacturing, the nutritional quality depends both on their composition and structure. The market is further driven by changing food habits, consumers want more transparency on food sourcing, and are increasingly looking for more convenience and healthier options that are instant, high in fiber or protein, low in carbohydrates, and free of artificial colors and flavors. Governments globally are also tightening regulations on nutrition. The flaked cereals business needs to meet consumer expectations in terms of nutrition, health, and taste. Population growth continues and the rate of consumption of instant breakfast is on the increase. New ways will need to be discovered to sustainably grow more breakfast cereals that promotes health, convenient, and meet consumer's nutritional needs [2].

The traditional method used to prepare flaked cereals involves direct cooking of intact grain kernels or parts of kernels with water and flavor in a steam cooker. The basic raw material for the traditionally cooked corn flake comes from the dry milling of regular field corn. The second method involves cooking of finer materials, such as grain flour, in an extruder where mechanical energy is applied for the formation of the grits for flaking [3–7]. There is a current trend of using non-traditional grains, novel ingredients for production of flakes; scientific research into the use of multigrain and fiber is on the increase [8–12]. Unfortunately, practical application in these areas remains proprietary information to each food manufacturer.

*Development and Optimization of Flakes from Some Selected Locally Available Food Materials DOI: http://dx.doi.org/10.5772/intechopen.109820*

Due to changes in lifestyle and urbanization, the consumption of instant flaked cereals has increased in Nigeria. There is the need to formulate value added flakes so as to eliminate the issue of nutrient imbalance in flakes. Formulation of flakes from different grains is one of the ways to improve flasks quality. Hundreds of people have worked on the development of new cereals and the improvement of older ones. There have been new types of raw materials for cereal making introduced over the years [2]. In this study, nutritionally improved, value-added instant flakes were developed, characterized and optimized, via constrained optimal (custom) mixture experimental design, from blends of rice, sorghum, soybean, sweet potato, moringa seed powder and ginger.

### **2. Materials and methods**

### **2.1 Materials**

The major components used for the formulation of the flakes were rice, sorghum and soybean which comprises 60% of the mixture. The other ingredients were water, sugar, malt, egg, sweet potato, ginger and moringa seed powder. All these materials were purchased from Kure Market, Minna, Nigeria.

### *2.1.1 Processing of the rice, sorghum, and soya beans into flours*

Properly clean rice and sorghum grains were milled until fine flour is achieved using a bore mill. Cleaned, sorted soybeans grains were roasted until a golden brown color was observed, and the roasted soybeans were dehulled in a commercial attrition mill, winnowed manually, milled into flour. The flours were sieved using a laboratory sieve mesh of 0.75–1 mm.

### **2.2 Methods**

### *2.2.1 Experimental design for flakes grits formulation*

A three-component constrained optimal (custom) mixture experimental design, with 30 randomized experimental runs, was employed. The formulation design constraints were: rice flour 30% ð Þ ≤*x*<sup>1</sup> ≤35% , sorghum flour 20% ð Þ ≤*x*<sup>1</sup> ≤25% , and soybean flour 5%ð Þ ≤ *x*<sup>1</sup> ≤ 10% . These major components comprise 60% of the total mixture and other ingredients were water (19%), sugar (8%), malt (2%), egg (3%), sweet potato (3%), ginger (2%) and moringa seed powder (3%). The design matrix used for the formulation experiment were presented in **Table 1**. The samples or runs were prepared based on the design matrix. The other minor components were added to each of the 30 samples and mixed together thoroughly, to obtained homogeneous mixture. The samples were then subjected to an electrical steam pressure cooking at temperature of 80°C for 1 hours and then the samples were removed and allowed to cool down for 5 minutes. Each of the samples were then rolled or pressed into flat, thin flakes using a rolling pin, and then were subjected to an electrical oven drying at temperature of 66°C for 1 hours. On removal from the toasting machine, the flakes were allowed to cool down and later packaged in different clean transparent, plastic packaging containers.


*x*<sup>1</sup> ¼ *Rice flour* ð Þ % , *x*<sup>2</sup> ¼ *Sorghum flour* ð Þ % , *x*<sup>3</sup> ¼ *Soybean flour* ð Þ %

*ymc* ¼ *Moisture Content* ð Þ % *; ypc* ¼ *Protein Content* ð Þ % *; yfat* ¼ *Fat Content* ð Þ % *, yac* ¼ *Ash Content* ð Þ %

*ynfe* ¼ *Nitrogen Free Extract* ð Þ % *; yev* ¼ *Energy value k*ð Þ *=cal*

*yfc* ¼ *Fibre Content* ð Þ % *; yt* ¼ *Taste; yf* ¼ *Flavor; ys* ¼ *Sweetness; yc* ¼ *Colour; ytx* ¼ *Texture;*

*yo* ¼ *Overall acceptability*

**Table 1.**

*The design matrix, proximate compositions and the sensory evaluation average scores of the formulated flakes.*

*Development and Optimization of Flakes from Some Selected Locally Available Food Materials DOI: http://dx.doi.org/10.5772/intechopen.109820*

### *2.2.2 Proximate analysis and sensory evaluations*

The quality characteristic of the flakes which were determined using the method described by the Association of Analytical Chemist [13] include moisture content, ash content, fat content, crude fiber, crude protein, nitrogen free extract, and energy value. Sensory evaluations of the formulated flakes were also conducted using 30 trained panelists. A 9-point hedonic scale ranging from 9 = like extremely and 1 = dislike extremely was used to evaluate the samples for taste, flavor, sweetness, color, texture and overall acceptability. Table water was used for mouth rinsing intermittently to minimize the carry over effects.

### **3. Experimental results**

The proximate composition of the formulated flakes from rice, sorghum, and soy beans were presented in **Table 1**.

The photos of some of the formulated instant cereal breakfast flakes are presented in **Figure 1**.

**Figure 1.** *Figure of formulated flakes.*

### **3.1 Statistical analysis of experimental results**

The experimental data were analyzed and appropriate Scheffe canonical models were fitted to the mean proximate property data. The statistical significance of the terms in the Scheffe canonical regression models were tested using analysis of variance (ANOVA) for each response, and the adequacy of the models were evaluated by coefficient of determination, F-value, and model p-values at the 5% level of significance. The models were also subjected to lack-of-fit and adequacy tests. The fitted models for each of the response was used to generate 3-D response surface as well as the contour plots using the DESIGN EXPERT 13.0 statistical software.

### **3.2 Generating the optimal formulation**

A numerical optimization approach, exploiting the desirability function technique, was utilized to generate the optimal formulation with the anticipated responses. Optimization goals are assigned to parameters and these goals were used to construct desirability indices (di). Desirability index range from zero to one for any given response and individual desirability for all the responses, in the case of multi-response optimization, are combined into a single number known as overall desirability index. A value of one represents the case where all goals are met perfectly. A zero indicates that one or more responses fall outside the set desirable limits. Under this approach, each *ith* response is assigned a desirability function, *di*, where the value of *di*varies between 0 and 1. The function, is defined differently based on the objective of the response.

If the response is to be maximized, then *di* is defined by equation1. If the response is to be minimized, as in the case when the response is cost, is then *di* is defined by Eq. 2. There may be times when the experimenter wants the response to be neither maximized nor minimized, but instead stay as close to a specified target as possible. In such cases, the desirability function is defined by Eq. 3. Once a desirability function is defined for each of the responses, assuming that there are *m* responses, an overall desirability function is obtained by Eq. 4. The objective is to now find the settings that return the maximum value of *D:* The rationale for using a geometric rather than an arithmetic mean is that if any individual desirability di is equal to zero, then the overall desirability will also be equal to zero.

$$d\_i = \begin{cases} 0 & \mathcal{y}\_i < L \\ \left(\frac{\mathcal{y}\_i - L}{T - L}\right)^w & L \le \mathcal{y}\_i \le T \\\ 1 & \mathcal{y}\_i > T \end{cases} \tag{1}$$

where *T* represents the target value of the *ith* response, *yi* , *L*, represents the acceptable lower limit value for this response and *w* represents the weight. When *w* ¼ 1 the function is linear. If *w* >1 then more importance is placed on achieving the target for the response, *yi* . When *w* <1, less weight is assigned to achieving the target for the response, *yi* .

$$d\_i = \begin{cases} 1 & \chi\_i < T \\ \left(\frac{U-\chi\_i}{U-T}\right)^w & T \le \chi\_i \le U \\ 0 & \chi\_i > U \end{cases} \tag{2}$$

*Development and Optimization of Flakes from Some Selected Locally Available Food Materials DOI: http://dx.doi.org/10.5772/intechopen.109820*

where *U* represents the acceptable upper limit for the response.

$$d\_i = \begin{cases} \mathbf{0} & \mathbf{y}\_i < \mathbf{L} \\ \begin{pmatrix} \frac{\mathbf{y}\_i - L}{T - L} \end{pmatrix}^{w\_1} & \mathbf{L} \le \mathbf{y}\_i \le T \\ \begin{pmatrix} \frac{U - \mathbf{y}\_i}{U - T} \end{pmatrix}^{w\_2} & T \le \mathbf{y}\_i \le U \\ \mathbf{0} & \mathbf{y}\_i > U \end{cases} \tag{3}$$

$$D = \left(d\_1^{r\_1}.d\_2^{r\_2}.d\_3^{r\_3}\dots \dots \dots d\_m^{r\_m}\right)^{\dagger (r\_1+r\_2+r\_3+\dots \dots + r\_m)}\tag{4}$$

where the *ri*'<sup>s</sup> represent the importance of each response. The greater the value of *ri*, the more important the response with respect to the other responses.

Numerical optimization solutions are given as a list, in their order of desirability, detailing the components proportions and process variables values that satisfies the set criteria and the overall desirability. The numerical solution can be presented in the form of desirability contour and 3-D Surface plots, optimal bar graph and graphical optimization overlay contour plot; showing the optimized formulation compositions and/or regions that meet specifications [14–17].

### **4. Results of statistical analysis of experimental data and discussion**


The summary of the analysis of variance (ANOVA) for the formulated flake's proximate compositions and the energy value are presented in **Tables 2**–**8**.

### **Table 2.**

*ANOVA for moisture content of multigrain flakes.*


### **Table 3.**

*ANOVA for fat content of multigrain flakes.*


### **Table 4.**

*ANOVA for ash content of multigrain flakes.*

*Development and Optimization of Flakes from Some Selected Locally Available Food Materials DOI: http://dx.doi.org/10.5772/intechopen.109820*


### **Table 5.**

*ANOVA for crude fiber of multigrain flakes.*


### **Table 6.**

*ANOVA for crude protein of multigrain flakes.*


### **Table 7.**

*ANOVA for nitrogen free extract of multigrain flakes.*


### **Table 8.**

*ANOVA for Energy Value of multigrain flakes.*

*Development and Optimization of Flakes from Some Selected Locally Available Food Materials DOI: http://dx.doi.org/10.5772/intechopen.109820*

The moisture content fitted model in terms of L\_Pseudo Components is presented in Eq. (5):

$$\begin{aligned} \mathbf{y}\_{mc} &= 4.92\mathbf{x}\_1 + 2.1\mathbf{l}\mathbf{x}\_2 + 3.73\mathbf{x}\_3 - 1.09\mathbf{x}\_1\mathbf{x}\_2 - 1.97\mathbf{x}\_1\mathbf{x}\_3\\ &- 2.74\mathbf{x}\_2\mathbf{x}\_3 - 29.2\mathbf{x}\_1^2\mathbf{x}\_2\mathbf{x}\_3 + 89.3\mathbf{x}\_1\mathbf{x}\_2^2\mathbf{x}\_3 - 17.2\mathbf{x}\_1\mathbf{x}\_2\mathbf{x}\_3^2 \end{aligned} \tag{5}$$

The results of the analysis showed that the moisture content model of the formulated instant flakes is significant with F-value of 11.1 and p-value of 5.22E-06. The moisture content is significantly influenced, at 5% level of significance, by the proportions of rice, sorghum, and soybean flours in the formulations (with linear mixture F- and p-values of 36.6 and 1.45E-07, respectively). The moisture content is also significantly influenced, at 5% level of significance by the sorghum/soybean flours interaction (with F-value of 4.78 and p-value of 0.0403); and rice/the second order of sorghum/soybean flours interaction (with F-value of 11.4 and p-value of 0.00287). The Lack of Fit F-and p-value of 9.87E+03 and 2.31E-28 implies that the Lack of Fit is significant. The moisture content model R<sup>2</sup> and the Adjusted R2 are 0.8087 and 0.7359, respectively. The predicted R2 of 0.6566 is in reasonable agreement with the adjusted R2 of 0.7359; i.e. the difference is less than 0.2. Adequacy of precision ratio of 11.534 indicates an adequate signal. This model can be used to navigate the design space and can be used to make predictions about moisture content for given levels of each factor.

The fat content fitted model in terms of L\_Pseudo Components is presented in Eq. (6):

$$\begin{aligned} y\_{\text{fat}} &= 3.57 \mathbf{x}\_1 + 2.58 \mathbf{x}\_2 + 3.06 \mathbf{x}\_3 - 1.77 \mathbf{x}\_1 \mathbf{x}\_2 - 6.73 \mathbf{x}\_1 \mathbf{x}\_3 \\ &+ 1.29 \mathbf{x}\_2 \mathbf{x}\_3 - 67.4 \mathbf{x}\_1^2 \mathbf{x}\_2 \mathbf{x}\_3 + 77.2 \mathbf{x}\_1 \mathbf{x}\_2^2 \mathbf{x}\_3 + 97.0 \mathbf{x}\_1 \mathbf{x}\_2 \mathbf{x}\_3^2 \end{aligned} \tag{6}$$

The results of the analysis showed that the fat content model of the formulated instant flakes is significant with F-value of 14.2 and p-value of 7.02E-07. The fat content is not significantly influenced, at 5% level of significance, by the proportions of rice, sorghum, and soybean flours in the formulations (with linear mixture F- and p-values of 1.53 and 0.240, respectively). The fat content is significantly influenced, at 5% level of significance by the rice/soybean flours interaction (with F- value of 48.6 and p-value of 6.98E-07); the second order of rice/sorghum/soybean flours interaction (with F-value of 10.9 and p-value of 0.00339); rice/the second order of sorghum/soybean flours interaction (with F-value of 14.3 and p-value of 0.00108), and rice/sorghum/the second order of soybean flours interaction (with F-value of 22.7 and p-value of 0.000105). The Lack of Fit F-and p-value of 4.90E+03 and 8.93E-26 implies that the Lack of Fit is significant. The fat content model R<sup>2</sup> and the Adjusted R2 are 0.8437 and 0.7841, respectively. The predicted R2 of 0.7193 is in reasonable agreement with the adjusted R2 of 0.7841; i.e. the difference is less than 0.2. Adequacy of precision ratio of 10.715 indicates an adequate signal. This model can be used to navigate the design space and can be used to make predictions about the fat content for given levels of each factor.

The ash content fitted model in terms of L\_Pseudo Components is presented in eq. (7):

$$\begin{aligned} y\_{ac} &= 3.56\mathbf{x}\_1 + +3.56\mathbf{x}\_2 + 2.06\mathbf{x}\_3 + 0.194\mathbf{x}\_1\mathbf{x}\_2 - 2.76\mathbf{x}\_1\mathbf{x}\_3 \\ &+ 5.21\mathbf{x}\_2\mathbf{x}\_3 - 2.54\mathbf{x}\_1^2\mathbf{x}\_2\mathbf{x}\_3 - 74.9\mathbf{x}\_1\mathbf{x}\_2^2\mathbf{x}\_3 + 88.7\mathbf{x}\_1\mathbf{x}\_2\mathbf{x}\_3^2 \end{aligned} \tag{7}$$

The results of the analysis showed that the ash content model of the formulated instant flakes is significant with F-value of 18.3 and p-value of 7.84E-08. The ash content is significantly influenced, at 5% level of significance, by the proportions of rice, sorghum, and soybean flours in the formulations (with linear mixture F- and pvalues of 24.1 and 3.67E-06, respectively). The ash content is also significantly influenced, at 5% level of significance by the rice/soybean flours interaction (with Fvalue of 11.5 and p-value of 0.00273); sorghum/soybean flours interaction (with Fvalue of 41.2 and p-value of 2.30E-06); rice/the second order of sorghum/soybean flours interaction (with F-value of 19.1 and p-value of 0.000269); and rice/sorghum/ the second order of soybean flours interaction (with F-value of 26.8 and p-value of 3.94E-05). The Lack of Fit F-and p-value of 6.61E+03 and 7.01E-27 implies that the Lack of Fit is significant. The ash content model R2 and the Adjusted R2 are 0.8743 and 0.8264, respectively. The predicted R2 of 0.7743 is in reasonable agreement with the adjusted R<sup>2</sup> of 0.8264; i.e. the difference is less than 0.2. Adequacy of precision ratio of 13.05 indicates an adequate signal. This model can be used to navigate the design space and can be used to make predictions about ash content for given levels of each factor.

The crude fiber fitted model in terms of L\_Pseudo Components is presented in eq. (8):

$$\begin{aligned} y\_{fc} &= 1.82\mathbf{x}\_1 + 1.20\mathbf{x}\_2 + 1.20\mathbf{x}\_3 + 1.07\mathbf{x}\_1\mathbf{x}\_2 + 1.06\mathbf{x}\_1\mathbf{x}\_3\\ &+ 2.33\mathbf{x}\_2\mathbf{x}\_3 - 27.6\mathbf{x}\_1^2\mathbf{x}\_2\mathbf{x}\_3 - 4.33\mathbf{x}\_1\mathbf{x}\_2^2\mathbf{x}\_3 - 6.17\mathbf{x}\_1\mathbf{x}\_2\mathbf{x}\_3^2 \end{aligned} \tag{8}$$

The results of the analysis showed that the crude fiber model of the formulated instant flakes is significant with F-value of 2.53 and p-value of 0.0422. The crude fiber is significantly influenced, at 5% level of significance, by the proportions of rice, sorghum, and soybean flours in the formulations (with linear mixture F- and p-values of 3.55 and 0.0469, respectively). The crude fiber is also significantly influenced, at 5% level of significance by sorghum/soybean flours interaction (with F-value of 9.36 and p-value of 0.00596); The Lack of Fit F- and p-value of 9.03E+03 and 4.95E-28 implies that the Lack of Fit is significant. The crude fiber model R2 and the Adjusted R2 are 0.4908 and 0.29675, respectively. The predicted R2 of 0.0855 is not close to the adjusted R2 of 0.2967; i.e., the difference is more than 0.2. This indicates a possible problem with the fitted model. Adequacy of precision ratio of 4.227 still indicates an adequate signal. Thus, the model can still be used to navigate the design space and to make predictions about crude fiber for given levels of each factor.

The crude protein fitted model in terms of L\_Pseudo Components is presented in Eq. (9):

$$\begin{aligned} y\_{pc} &= 28.5\mathbf{x}\_1 + 28.8\mathbf{x}\_2 + 28.5\mathbf{x}\_3 - 12.6\mathbf{x}\_1\mathbf{x}\_2 + 4.48\mathbf{x}\_1\mathbf{x}\_3\\ &- 5.84\,\mathbf{x}\_2\mathbf{x}\_3 + 474.\mathbf{x}\_1^2\mathbf{x}\_2\mathbf{x}\_3 + 252.\mathbf{x}\_1\mathbf{x}\_2^2\mathbf{x}\_3 - 850.\mathbf{x}\_1\mathbf{x}\_2\mathbf{x}\_3^2 \end{aligned} \tag{9}$$

The results of the analysis showed that the crude protein model of the formulated instant flakes is significant with F-value of 7.56 and p-value of 9.49E-05. The crude protein is not significantly influenced, at 5% level of significance, by the proportions of rice, sorghum, and soybean flours in the formulations (with linear mixture F- and p-values of 2.65 and 0.0943, respectively). The crude protein is significantly influenced, at 5% level of significance by rice/sorghum flours interaction (with F- value of 4.35 and p-value of 0.0494); second order of rice/sorghum/soybean flours interaction (with F-value of 13.9 and p-value of 0.00125); and rice/sorghum/the

*Development and Optimization of Flakes from Some Selected Locally Available Food Materials DOI: http://dx.doi.org/10.5772/intechopen.109820*

second order of soybean flours interaction (with F-value of 44.8 and p-value of 1.28E-06). The Lack of Fit F-and p-value of 2.03E+04 and 5.00E-31 implies that the Lack of Fit is significant. The crude protein model R2 and the Adjusted R2 are 0.7423 and 0.6442, respectively. The predicted R2 of 0.5375 is in reasonable agreement with the adjusted R2 of 0.6442; i.e. the difference is less than 0.2. Adequacy of precision ratio of 9.972 indicates an adequate signal. This model can be used to navigate the design and can be used to make predictions about the crude protein for given levels of each factor.

The nitrogen free extract fitted model in terms of L\_Pseudo Components is presented in Eq. (10):

$$\begin{aligned} \mathbf{y\_{nfe}} &= \mathbf{57.6x\_1 + 61.7x\_2 + 61.5x\_3 + 14.5x\_1x\_2 + 5.79x\_1x\_3} \\ &- 0.42x\_2x\_3 - 351.x\_1^2x\_2x\_3 - 339.x\_1x\_2^2x\_3 + 686.x\_1x\_2x\_3^2 \end{aligned} \tag{10}$$

The results of the analysis showed that the nitrogen free extract model of the formulated instant flakes is significant with F-value of 6.07 and p-value of 0.000426. The nitrogen free extract is significantly influenced, at 5% level of significance, by the proportions of rice, sorghum, and soybean flours in the formulations (with linear mixture F- and p-values of 6.71 and 0.00558, respectively). The nitrogen free extract is also significantly influenced, at 5% level of significance by rice/sorghum flours interaction (with F-value of 5.31 and p-value of 0.0316); second order of rice/sorghum/soybean flours interaction (with F-value of 6.96 and p-value of 0.0154); rice/ second order of sorghum/soybean flours interaction (with F-value of 6.50 and p-value of 0.0187); and rice/sorghum/the second order of soybean flours interaction (with Fvalue of 26.7 and p-value of 4.04E-05). The Lack of Fit F-and p-value of 1.40E+04 and 1.19E-29 implies that the Lack of Fit is significant. The nitrogen free extract model R<sup>2</sup> and the Adjusted R2 are 0.6981 and 0.5831, respectively. The predicted R<sup>2</sup> of 0.4580 is in reasonable agreement with the adjusted R<sup>2</sup> of 0.5831; i.e. the difference is less than 0.2. Adequacy of precision ratio of 8.672 indicates an adequate signal. This model can be used to navigate the design space and can be used to make predictions about nitrogen free extract for given levels of each factor.

The energy value fitted model in terms of L\_Pseudo Components is presented in Eq. (11):

$$\begin{aligned} y\_{ev} &= 376\mathbf{x}\_1 + 386\boldsymbol{\omega}\_2 + 388\boldsymbol{\omega}\_3 - 11.9\mathbf{x}\_1\mathbf{x}\_2 - 20.2\mathbf{x}\_1\mathbf{x}\_3 \\ &- 12.1\mathbf{x}\_2\mathbf{x}\_3 + 172\mathbf{x}\_1\mathbf{x}\_2\mathbf{x}\_3 \end{aligned} \tag{11}$$

The results of the analysis showed that the energy value model of the formulated instant flakes is significant with F-value of 6.85 and p-value of 0.000288. The energy value is significantly influenced, at 5% level of significance, by the proportions of rice, sorghum, and soybean flours in the formulations (with linear mixture F- and p-values of 16.3 and 3.86E-05, respectively). The energy value is also significantly influenced, at 5% level of significance by rice/soybean flours interaction (with F-value of 4.37 and p-value of 0.0478); and rice/sorghum/soybean flours interaction (with Fvalue of 7.22 and p-value of 0.0132). The energy value model R<sup>2</sup> and the Adjusted R2 are 0.6413 and 0.5477, respectively. The predicted R<sup>2</sup> of 0.4912 is in reasonable agreement with the adjusted R2 of 0.5477; i.e. the difference is less than 0.2. Adequacy of precision ratio of 7.018 indicates an adequate signal. This model can be used to navigate the design space and can be used to make predictions about energy value for given levels of each factor.

*Development and Optimization of Flakes from Some Selected Locally Available Food Materials DOI: http://dx.doi.org/10.5772/intechopen.109820*

*The contours and 3-D plots for the proximate compositions, nitrogen free extract, and energy value of multigrain flakes.*


### **Table 9.**

*Optimization constraints for instant flakes formulation.*

The contours and 3-D plots for the proximate compositions (moisture content, fat content, ash content, crude fiber, crude protein, nitrogen free extract, and energy value) are summarized in **Figure 2**.

**Table 9** presents the summary of the optimization constraints employed in the optimization module. The five desirability solutions that were found are presented in **Table 10**. The numerical solution desirability contour plot and 3-D Surface were presented in **Figure 3**. The numerical solution, presented in the form of optimal flake's bar graph and the graphical optimization overlay contour plot, showing the optimized formulation compositions with the respective quality parameters, are summarized in **Figure 4**.

The result of the flakes optimization gave optimized multigrain instant flakes with overall desirability index of 0.519, based on the set optimization goals and individual quality desirability indices. Formulating instant flake with 31.9% rice flour, 22% sorghum flour, 6.05% soybean flour yielded an improved instant flake with optimal quality properties.

### **5. Conclusions**

Instant flakes were developed, characterized and optimized, via constrained optimal (custom) mixture experimental design, from blends of rice, sorghum and soybean. Some concluding observations from the investigation are given below.


**Table 10.**

*The desirability solutions found.*

### *Development and Optimization of Flakes from Some Selected Locally Available Food Materials DOI: http://dx.doi.org/10.5772/intechopen.109820*

### **Figure 3.**

*The numerical solution desirability contour plot and 3-D surface.*

### **Figure 4.**

*The bar graph and the graphical optimization overlay contour plot for the optimal formulated flake.*


The research has shown that composite food formulation is an excellent way to achieve nutrition revolution, the road to healthier diets and optimal nutrition in Africa: The continent is blessed with vast varieties of agricultural produce seasonally (tubers, roots, cereals, pulses, fruits, vegetables, etc.), yet hunger, malnutrition,

*Development and Optimization of Flakes from Some Selected Locally Available Food Materials DOI: http://dx.doi.org/10.5772/intechopen.109820*

dietary deficit, concurrent diseases and food insecurity persists. Additive food manufacturing and/or composite food formulation, dietary diversification, food fortification and increasing access to varieties of nutritionally adequate foods are vital strategies to tackle these lingering problems. However, this study encouraged that further study be carried out on formulation of instant flakes using other nutritionally rich blends (grains and legumes).

### **Declaration of interest**

The authors declare no conflicts of interest. The authors alone are responsible for the content and writing of the manuscript.

### **Funding source**

This research is self-sponsored and did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors.

### **Author details**

Samuel Tunde Olorunsogo\* and Bolanle Adenike Adejumo Department of Agricultural and Bioresources Engineering, School of Infrastructure, Process Engineering and Technology, Federal University of Technology, Minna, Nigeria

\*Address all correspondence to: solorunsogo@futminna.edu.ng

© 2023 The Author(s). Licensee IntechOpen. This chapter is distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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Section 3
