extfieldsofstudy: Medicine Chemistry

text:
Effect of Omega-3 Microcapsules Addition on the Profile of Volatile Compounds in Enriched Dry-Cured and Cooked Sausages

The main goal of the present study was evaluating the effect of enriching meat products (cooked (C-SAU) and dry-cured sausages (D-SAU)) with monolayered (Mo) and multilayered (Mu) fish oil microcapsules on the profile of volatile compounds, with special interest in lipid oxidation markers. For that, Solid-Phase Microextraction (SPME) and Gas Chromatography-Mass Spectrometry (GC-MS) were used. Significant differences were found in the volatile compound profile between Mo and Mu, which was been reflected in the meat samples. Thus, in general, volatile compounds from lipid oxidation have shown higher abundance in Mo and C-SAU and D-SAU enriched with this type of microcapsule, indicating that the wall of Mu (chitosan-maltodextrine) might protect the encapsulated bioactive compounds more effectively than that of Mo (maltodextrine). However, this finding is not reflected in the results of previous studies evaluating the sensory perception and oxidation stability of C-SAU and D-SAU, but it should be considered since unhealthy oxidation products can be formed in the enriched meat products with Mo. Thus, the addition of Mu as an omega-3 vehicle for enriching meat products may be indicated.

Introduction
Numerous epidemiological studies suggest that a diet rich in omega-3 polyunsaturated fatty acids (ω-3 PUFAs), mainly eicosapentaenoic acid (EPA; C20:5 ω-3) and docosahexaenoic acid (DHA; C22:6 ω-3), has a marked influence in the avoidance and therapy of a series of chronic disorders [1], particularly coronary heart disease [2][3][4][5]. However, Western diets are poor in long chain ω-3 PUFAs and the liking of fish and seafood products (main sources of EPA and DHA) is currently static or declining [6]. Therefore, to improve the welfare state of the population, different professional organizations and health agencies have recommended the consumption of around 0.25 g EPA + DHA per person and day [7][8][9][10]. There also is a European Union law that sets up the minimum quantities of EPA + DHA (40 and 80 mg per 100 g and per 100 kcal) to label a food as a "source of ω-3 fatty acids" and "high in ω-3 fatty acids", respectively [11].
Nowadays, meat products are highly appreciated, with a habitual consumption of around 3-4 times per week [12], which is principally ascribed to the modern standards of life and the demand of "ready-to-eat" products. The content of high biological value proteins in meat products is valued; however, the percentage saturated fatty acids (SFA) and the ratio of ω-6/ω-3 PUFA is (Madrid, Spain), with a magnetic stirring overnight. Water was added until the mixture reached a total weight of 200 g. The mixture was homogenized (20,000 rpm, 10 min) using an Ultraturrax T-18 basic (IKA, Königswinter, Germany), with a primary emulsion that was homogenized at high-pressure (SPX, model APV-200a, Silkeborg, Denmark). The high-pressure homogenization conditions have been previously optimized: 1200 Ba and 3 passes for Mo and 1100 and 2 passes for Mu [29]. The next step was different for each type of emulsion: water (200 g) was blended with Mo, while 200 g of 1% of chitosan (w/w) with 95% of deacetylation (Chitoclear FG 95, kindly provided by Trades, Murcia, Spain) in acetic acid 1% were added to Mu. The mixtures were slowly agitated with a magnetic stirrer for 15 min. Finally, in Mo and Mu, 400 g of maltodextrin solution (120 g maltodextrin + 280 g water) with a dextrose equivalent of 12% (Glucidex 12, kindly provided Roquette, Lestrem, France) were added. Thus, feed emulsions (800 g) of Mo and Mu were obtained.
A laboratory-scale spray drier equipped with a 0.5-mm nozzle atomizer (Mini spray-dryer B-290, Buchi, Switzerland) was used to dry the feed emulsions, applying the following parameters (80% aspirator rate = 80%, feed rate = 1 L/h, inlet temperature = 180 • C, outlet temperature = 85-90 • C). During the spray-drying process, the emulsions were agitated in a magnetic stirrer at room temperature. The dried powders collected were refrigerated (4 • C) until they were added to the meat products. Quality characteristics of Mo and Mu emulsions and microcapsules have been previously analyzed [29].
C-SAU and D-SAU batches were formulated and manufactured in a meat industry (remain anonymous).

Analysis of Volatile Compounds
Microcapsules and minced meat products were sampled (1 g) into a 10 mL glass flask (Hewlett-Packard, Palo Alto, CA, USA) sealed with an aluminum cap and polytetrafluoroethylene (PTFE) butyl septum (Perkin-Elmer, Foster City, CA, USA). A solid-phase microextraction (SPME) method [34] was first applied for the volatile compound extraction. A cross-linked carboxen/polydimethylsiloxane fiber (10 mm long, 100 µm thick; Supelco, Bellefonte, PA, USA) was used. It was conditioned (220 • C, 50 min) in the gas chromatograph (GC) injection port before use. For the absorption of the volatile compounds of samples, the fiber was introduced in the sealed vial, being placed in a water bath a 40 • C, for 30 min. After that, SPME fiber was moved to the injection port and maintained for 30 min for desorption. Analyses were performed using a Hewlett-Packard 6890 series II GC coupled to a mass selective detector (HP 5973) (Hewlett-Packard, Wilmington, DE, USA). A 5% phenyl-95% polydimethylsiloxane column (30 m × 0.32 mm ID, 1.05 µm film thickness, Hewlett-Packard) was used, operating at 40 • C, with a column head pressure of 6 psi of and a flow of 1.3 mL min −1 . The mode of the injection port was splitless. The following temperature program was applied: isothermal for 15 min at 35 • C, increased to 150 • C at 4 • C min −1 , and then to 250 • C at 20 • C min −1 . Temperature of the transfer line to the mass spectrometer was 280 • C. The mass spectra were obtained using a mass selective detector by electronic impact at 70 eV, a multiplier voltage of 1756 V and collecting data at a rate of one scan over the m/z range of 30-550 u.m.a. The linear retention indexes (LRIs) of the volatile compounds were calculated by means of N-alkanes (Sigma R-8769), which were analyzed under the same conditions. Identification of volatile compounds of samples was done by comparison of mass spectra with databases (National Institute of Standards and Technology (NIST) and Wiley libraries) and by comparison of their LRI with those available in the literature [20,21,. Results from volatile analyses are provided in area units (AU).

Sampling Replication and Statistical Analysis
Replicate experimental samples (n = 3) of Mo and Mu microcapsules and of the three batches (Co, Mo and Mu) of meat products (C-SAU and D-SAU) were analyzed in triplicate. One-way analysis of variance (ANOVA) was applied to evaluate the addition of different types of fish oil microcapsules and the differences between microcapsules. In the case of being significant effects (p < 0.05), paired comparisons between means were conducted using Tukey's test. Furthermore, all volatile compounds that showed significant differences in the ANOVA analysis were included into a principal component analysis (PCA). The statistics were run using the program IBM SPSS Statistics v.22 (IBM, Armonk, NY, USA).

Volatile Compounds in Fish Oil Microcapsules
A total of 40 volatile compounds were identified in the Mo and Mu fish oil microcapsules, which were grouped in the following chemical families: aliphatic hydrocarbons, alcohols, aldehydes, ketones, furans and acids. Figure 1 shows the area percentage of each chemical family in Mo and Mu. In both types of fish oil microcapsules, aliphatic hydrocarbon was the major chemical family, followed in decreasing order by aldehydes, ketones, alcohols, furans and acids. This profile of volatile compounds is quite according to a previous study with double and multilayered fish oil microcapsules [35]. The percentage of aliphatic hydrocarbons has been used as an indicator of quality and stability of different commercial fish oils, from salmon, tuna, sardines and shrimp. Considering the relationship between the decrease in the percentage of this family of volatile compounds with an increase in lipid oxidation [51], the high percentage of aliphatic hydrocarbons in Mo and Mu may support the protective effect of the wall materials of these types of microcapsules, minimizing the contact and reactivity of fish oil with oxidizing promoters. Significant differences were detected in the percentage of the most chemical families of volatile compounds between the Mo and Mu of this study, showing Mo higher percentages of aldehydes (8.43% vs. 4.78%), ketones (3.82% vs. 2.65%), alcohols (1.97% vs. 1.10%) and lower of aliphatic hydrocarbon (87.89 vs. 90.43%) and acids (n.d. vs. 0.32%) than Mu. Accordingly, [59] also found significant differences in the percentage of chemical families of volatile compounds between different types of fish oil microcapsules.  Table 1 lists the individual volatile compounds of Mo and Mu, being expressed as AU × 10 6 . Hexane was the major volatile compound in Mo and Mu, followed by pentane, hexanal and 3hydroxy-2-butanone, and the rest of individual volatile compounds showed less than 1 AU × 10 6 . This agrees with results described for double and multilayered fish oil microcapsules [35]. From the 40 individual volatile compounds identified in the fish oil microcapsules of the present study, 9 of them were found in Mu but not in Mo (tridecane, 1,2,4-butanetriol, phenylethyl alcohol, 2-heptenal, 2octenal, 2-nonanone, 2-butyltetrahydrofuran, heptanoic and sorbic acid) and 7 were only detected in Mo (1-heptene, heptane, decane, 2-propanol, 4-hexen-1-ol, 1-heptanol and 2-hexenal).   Table 1 lists the individual volatile compounds of Mo and Mu, being expressed as AU × 10 6 . Hexane was the major volatile compound in Mo and Mu, followed by pentane, hexanal and 3-hydroxy-2-butanone, and the rest of individual volatile compounds showed less than 1 AU × 10 6 . This agrees with results described for double and multilayered fish oil microcapsules [35]. From the 40 individual volatile compounds identified in the fish oil microcapsules of the present study, 9 of them were found in Mu but not in Mo (tridecane, 1,2,4-butanetriol, phenylethyl alcohol, 2-heptenal, 2-octenal, 2-nonanone, 2-butyltetrahydrofuran, heptanoic and sorbic acid) and 7 were only detected in Mo (1-heptene, heptane, decane, 2-propanol, 4-hexen-1-ol, 1-heptanol and 2-hexenal).
Significant differences were found in most individual volatile compounds between Mo and Mu (Table 1). Regarding the aldehydes, which have been described as the most important indicators of fish oil oxidation [51], Mo showed significant higher levels of propanal, pentanal, hexanal, 2-hexenal, heptanal, octanal and nonanal compared to Mu. It has been described that propanal comes from the lipid hydroperoxides derived from ω-3 PUFA while hydroperoxides derived from ω-6 PUFA mainly generate hexanal, as consequence of the breakdown of the first double bond of the n position of the ω-3 and ω-6 fatty acids, respectively [60]. In addition, hexanal has been used in previous studies as a marker to measure the quality and oxidative stability of fish oil microcapsules [20]. On the other hand, Mu had a significant higher AU of 2-pentenal and 2-octenal than Mo, but these two volatile compounds have not been related to the oxidation of ω-3 PUFAs. In addition, other relevant indicators of fish oil oxidation, such as 2,4-heptadienal and 2,4-decadienal, which have been associated to the perception of rancid flavor [20,48,60], or other aldehyde volatile compounds related to rancid odors, such as decanal or 2-nonenal [20,48,61], have not been identified in Mo or Mu.
Most individual alcohols and ketones have shown significant differences between Mo and Mu, with higher AU in Mo in comparison to Mu in most cases. However, as is our knowledge, either of the ketones detected in Mo and Mu are associated with the lipid oxidation process. The most important ketones from lipid autoxidation reactions are 3,5-octadien-2-one and 1-octen-3-one [49]. In fact, they have been detected in mayonnaise and milk enriched with fish oil, being strongly correlated with the strength of the oxidation process [48,50]. However, these ketones were not detected in Mo or Mu. Regarding the alcohols, 1-penten-3-ol and 2-penten-1-ol have been described as one of the most characteristics oxidation markers for PUFA [48,49]. 1-penten-3-ol was detected in both types of microcapsules, with higher AU in Mo than in Mu, while 2-penten-1-ol was not found in these fish oil microcapsules. Another common oxidation product of ω-3 PUFA is 2-ethylfuran, which can be generated from the 12-hydroperoxide of EPA and 16-hydroperoxide of DHA [35,62]. This volatile compound has been identified in both types of microcapsules, Mo having significantly higher AU than Mu. Two volatiles compounds, heptanoic and sorbic acid, were found in Mu, but not in Mo. Heptanoic acid at high concentrations imparts unpleasant rancid odor, but the AU of this compound in Mu are very low. The higher AU in some individual volatile compounds related to lipid oxidation found in Mo in comparison to Mu could be explained by the different wall material of these fish oil microcapsules, being of maltodextrine and of chitosan plus maltodextrine, respectively. In fact, it has been described that chitosan increases the electrostatic force and viscosity of the layers [63], avoids the oxidative damage and could act as a free scavenger [64]. Thus, the Mu coating may be more effective than Mo to protect fish oil from oxidative damage. This aspect can be marked in the case of volatile compounds such as hexanal, 1-penten-3-ol and 2-ethylfuran, with low odor thresholds (4.5, 1 and 2.2 µg kg −1 oil, respectively) and associated with sensory defects [65,66].
Nevertheless, in comparison to the profile of volatile compounds in bulk fish oil, Mo and Mu have not shown to be polyunsaturated lipid oxidation products with rancid taste perceptions, such as 2,4-heptadienal, 2,4-decadienal, 2-nonenal, 3,5-octadien-2-one and 1-octen-3-one [51,67], which points out the effectiveness of the Mo and Mu microcapsules of the present study to minimize the contact and reactivity of fish oil encapsulated with oxidizing promoters.

Volatile Compounds in Dry-Cured and Cooked Sausages Enriched with Fish Oil Microcapsules
A total of 53 and 60 volatile compounds were identified in D-SAU and C-SAU of the present study, respectively, which were grouped in the following chemical families: aliphatic hydrocarbons, alcohols, aldehydes, furans, ketones, terpenes, acids, esters, aromatics, cyclic hydrocarbons and pyrazines. Figure 2A,B show the percentages of these chemical families of volatile compounds in D-SAU and C-SAU as affected by type of fish oil microcapsule addition, respectively. The most abundant families in all batches of D-SAU were acids and aldehydes, followed far behind by terpenes and esters. Minor percentages were found for aliphatic hydrocarbons, aromatics, ketones, cyclic hydrocarbons, alcohols and furans. This profile is quite in concordance with previous studies in fermented sausages [53,58]. Moreover, significant differences were detected in the chemical families of volatile compounds between the D-SAU batches of this study, with Mo showing higher percentages of aldehydes and terpenes (16.03 and 8.2) than Co and Mu batches, and Mu having a higher percentage of acids (69.63) and lower percentages of esters (5.58) than Co and Mo.
In C-SAU, the major family of volatile compounds was aldehydes, followed by aliphatic hydrocarbons, cyclic hydrocarbons and alcohols, while minor abundance was detected for terpenes, acids, esters, aromatics, ketones, furans and pyrazines. This agrees with the profile of volatile compounds previously reported in other studies in cooked sausages [42,46]. Moreover, significant differences were found in the chemical families of volatile compounds between the C-SAU batches of this study, showing in C-SAU-Mo higher percentages of aldehydes and alcohols than in C-SAU-Co and C-SAU-Mu; C-SAU-Mu obtained a higher percentage of acids and esters and a lower percentage of aliphatic hydrocarbons than C-SAU-Co and C-SAU-Mo, and the percentage of cyclic hydrocarbons was higher in C-SAU-Co than in the enriched batches. Thus, at first, considering the results on the percentage of volatile compounds, the differences between microcapsules are reflected in the bathes of meat products. Taking a step forward, the individual volatile compounds of the control and enriched batches of the meat products of the present study are analyzed in the following sections. Table 2 lists the individual volatile compounds of D-SAU as affected by the type of fish oil microcapsule added. Acetic acid was the major volatile compound in all batches, followed by hexanal, methyl hexanoate, β-myrcene, pentanoic acid, butanoic acid and heptanal, the rest of the individual volatile compounds showing less than 10 AU × 10 6 . This profile is quite in concordance with previous studies in dry fermented sausages [53,55]. The high content of acetic acid would be related to microbial fermentation of carbohydrates [55,68]. Others compounds also typical of carbohydrate fermentation, such as 3-hydroxy-2-butanone, were also detected in D-SAU batches [57]. The high AU of β-myrcene in these samples is also noted, which may be ascribed to the addition of species [69]. In C-SAU, the major family of volatile compounds was aldehydes, followed by aliphatic hydrocarbons, cyclic hydrocarbons and alcohols, while minor abundance was detected for terpenes, acids, esters, aromatics, ketones, furans and pyrazines. This agrees with the profile of volatile compounds previously reported in other studies in cooked sausages [42,46]. Moreover, significant differences were found in the chemical families of volatile compounds between the C-SAU batches  The enrichment effect with Mo and Mu fish oil microcapsules significantly influence the volatile compounds of most chemical groups (Table 2), excluding esters, aromatics and cyclic hydrocarbons. Only 13 in 53 volatile compounds identified in D-SAU showed significant differences among batches: C-SAU-Mo showed higher AU in six volatile compounds (1-propanone, 1-penten-3-ol, 1-octen-3-ol, pentanal, 3,5-octadien-2-one and acetic acid) and lower in one (butanal) in comparison to C-SAU-Co and C-SAU-Mu; C-SAU-Mu obtained higher abundance in two volatile compounds (heptane and β-mycene) and lower in one (3-hydroxy-2-butanone) than in C-SAU-Co and C-SAU-Mo, and C-SAU-Co showed higher AU in one volatile compound (2-penthyl-furan) and lower in two (1-propanol and 2-ethylfuran) in comparison to the enriched batches. Figure 3a represents the score plots of the PCA of volatile compounds data from the D-SAU samples. The first principal component (PC1) comprised 55.48% of the total variance, and the second principal component (PC2) accounted for 29.47%. The score plot indicates a clear differentiation of samples as affected by the addition of fish oil microcapsules: those with high positive PC1 scores (D-SAU-Mo), those with high positive PC2 scores (D-SAU-Mu) and those with high negative PC2 scores (D-SAU-Co). Several volatile compounds (3,5-octadien-2-one, 1-propanol, pentanal, 1-octen-3-ol, 1-penten-3-ol, acetic acid, 2-ethylfuran, 1-propene, allyl sulphide) are located in the right quadrants (upper and lower), which correspond to high positive charges in PC1, associated with D-SAU-Mo batch. On the other hand, there were a few volatile compounds allocated in the PC2: heptane, β-myrcene, and butanal in the left upper quadrant, and 2-pentyl-furan and 3-hydroxy-2-butanone in the left lower quadrant, related to D-SAU-Mu and D-SAU-Co, respectively. Thus, in comparison to C-SAU-Co and C-SAU-Mu, C-SAU-Mo are more related to typical volatiles compounds of fatty acid oxidation, such as 1-propanol, 1-octen-3-ol and pentanal [45], and to characteristic oxidation markers for PUFA oxidation, such as 1-penten-3-ol, 2-ethyl-furan and 3,5-octadien-2-one, which have been previously observed in mayonnaise and chicken nuggets enriched with fish oil [23,48], and are correlated with the strength of the oxidation process [48,50]. The low odor thresholds some of these volatile compounds, such as 1-octen-3-ol and 3,5-octadien-2-one (1 and 0.45 µg kg −1 of oil, respectively) [70,71], would lead to the perception of anomalous odor and/or flavor, which may have a negative impact in the products enriched with Mo. Nevertheless, in a previous study carried out with the D-SAU samples of the present work [28], no significant differences in acceptability were found among Co, Mo and Mu samples. So, the influence of the fish oil microcapsules addition on the profile of volatile compounds does not seem to be reflected in the consumer's perception of D-SAU.  Table 3 showed the individual volatile compounds of C-SAU as affected by the type of fish oil microcapsule added. α-thujene was the major volatile compound in all batches (around 6.07 AU × 10 6 ), followed by pentanal (around 4.84 AU × 10 6 ), β-thujene (around 3.52 AU × 10 6 ), hexanal (around 3.5 AU × 10 6 ), 1-octen-3-ol (around 3.40 AU × 10 6 ), gamma-terpinene (around 3.20 AU × 10 6 ) and heptanal (around 3.15 AU × 10 6 ), and the rest individual volatile compounds showed less than 3 AU × 10 6 . In previous studies in cooked sausages, hexanal has been identified as the most abundant volatile compound, followed by heptanal, pentanal and volatiles compounds from the chemical  Table 3 showed the individual volatile compounds of C-SAU as affected by the type of fish oil microcapsule added. α-thujene was the major volatile compound in all batches (around 6.07 AU × 10 6 ), followed by pentanal (around 4.84 AU × 10 6 ), β-thujene (around 3.52 AU × 10 6 ), hexanal (around 3.5 AU × 10 6 ), 1-octen-3-ol (around 3.40 AU × 10 6 ), gamma-terpinene (around 3.20 AU × 10 6 ) and heptanal (around 3.15 AU × 10 6 ), and the rest individual volatile compounds showed less than 3 AU × 10 6 . In previous studies in cooked sausages, hexanal has been identified as the most abundant volatile compound, followed by heptanal, pentanal and volatiles compounds from the chemical families of alcohols (1-pentanol and 1-octen-3-ol) and terpenes (limonene, β-myrcene, and gamma-terpinene) [39,40,42], which is quite in agreement with the findings of the present study. However, in these previous works α-thujene and β-thujene were identified but with lower AU than in the present work. These compounds are associated with spicy flavor and have been found in a wide variety of medicinal herbs, essential oils, flavorings and spices such as nutmeg [72]; therefore, its abundance in the present study could be related to the addition of spices in the meat product formulation. In C-SAU, the addition of Mo and Mu fish oil microcapsules significantly influenced the volatile compounds of most chemical families (Table 3), excluding terpenes and pyrazines, finding significant differences in 27 volatile compounds. Higher abundance was found in two volatile compounds in C-SAU-Mo (1-pentanol and 2-decenal) than in C-SAU-Co and C-SAU-Mu. A total of nine volatile compounds (hexane, heptane, decane, tridecane, 1-hexanol, phenyl ethyl alcohol, acetic acid, nonanoic acid, methyl propanoate and methyl propanoate) obtained higher AU in C-SAU-Mu than in C-SAU-Co and C-SAU-Mo. On the contrary, C-SAU-Mu showed lower abundance for 2-octene, nonane, 1-octen-3-ol, 2-methyl-propanal, 3-heptanone, 2-buthyl-furan and octanoic acid than C-SAU-Co and C-SAU-Mo. In comparison to the enriched batches, C-SAU-Co showed higher AU for six volatile compounds (pentanal, 2-heptanone, 2-methyl-furan, pentanoic acid, β-thujene and α-thujene) and lower for three (dodecane, 4-hexen-1-ol and 1-heptanol). A score plot of PCA of volatile compounds data from the C-SAU samples is shown in Figure 3b. The PC1 accounted for 54.78% of the total variance, and the PC2 comprised 34.19%. The score plot allowed a clear separation of the samples: those with high positive PC1 scores (C-SAU-Mu), those with high positive PC2 scores (C-SAU-Mo) and those with negative PC2 scores (C-SAU-Co). 2-decenal, 2-buthylfuran, 3-heptanone, 1-pentanol, 4-hexen-1-ol, 1-octen-3-ol, dodecane, nonane and methyl-propanoate were grouped and allocated in the upper quadrants (left and right), which correspond to the C-SAU-Mo batch, while 2-heptanone, pentanal, 2-methylpropanal, β-thujene, α-thujene, 2-methylfuran and hexane, heptane, decane, 1-hexanol, 1-heptanol, phenyl-ethyl-alcohol were in the lower left and right quadrants, related to C-SAU-Co and C-SAU-Mu, respectively. Thus, in C-SAU, Mo enriched batches also showed a close relation with volatile compounds from lipid oxidation, such us 2-decenal, a characteristic volatile compound of ω-3 PUFA oxidation, and in 1-pentanol, 4-hexen-1-ol and 1-octen-3-ol, described as typical lipid oxidation products [42,46]. 2-decenal has been related in previous studies to rancid odors in fish oil enriched mayonnaise [48] and fish oil microcapsules [20]. These volatile compounds have a fatty and fishy aroma [71] with a low odor threshold, around 10 µg kg −1 oil [73], which may be detrimental the acceptability of the meat products added with Mo. However, as occurred in D-SAU, similar scores in the acceptability analysis have been found by [28] in the three batches of C-SAU, the differences in the profile volatile compounds not being reflected by the sensory results.
It is worth noting that the differences found in the present study in the profile volatile compounds depend on the type of fish oil microcapsules added. Anyway, a major protection of the microencapsulated fish oil against lipid oxidation when Mu are added could be indicated. This can be ascribed to the different wall material in Mo (maltodextrine) and Mu (chitosan plus maltodextrine). Thus, the multilayer structured of chitosan-maltodextrine may protect the encapsulated material more effectively than the simple coating of maltodextrine. Indeed, chitosan improves the emulsion stability, increasing the electrostatic force and viscosity of the layers, and can also act as an antioxidant [63,64]. Moreover, a high oxidative stability has been found in microcapsules with chitosan [33]. So, although no marked effects on sensory or oxidation stability have been previously found [28], differences in the volatile compounds should be considered since they could release to unhealthy oxidized products [74]. This can be the case of furans, such us 2-ethylfuran, 2-butylfuran, 2-acetylfuran, 2-pentylfuran, 2-furfural and furfural alcohol, which have been found in different fish products [75,76], and have revealed toxicity in animals and humans [77,78]. In fact, 2-ethylfuran and 2-buthylfuran were closely related to the D-SAU-Mo and C-SAU-Mo samples in this study. Considering this aspect, more studies should be conducted in this sense, for evaluating the formation of contaminants in different omega-3 enriched meat products.

Conclusions
The type of fish oil microcapsules influences its profile of volatile compounds and that of the enriched meat products. The use of multilayered microcapsules with chitosan-maltodextrine walls may be more protective to the formation of lipid oxidation products, especially from omega-3 fatty acids, than microcapsules with a maltodextrine layer. Thus, the use of multilayered fish oil emulsions to elaborate omega-3 microcapsules for enriching meat products may be indicated.


extfieldsofstudy: Biology Medicine

provenance: AgriculturalAndFoodSciences,2019-2020-Agricultural And Food Sciences-2020.jsonl.gz.gz

text:
Identification and Characterization of Bluetongue Virus Serotype 14 in Russia

This paper reports a case of bluetongue virus (BTV) infection in the Smolensk and Kaluga regions of Russia in 2011–2012. The virus was initially detected in heifers transferred in Russia from Germany through Poland and Belarus in 2011. On day 27 of quarantine, RNA and infectious viruses of BTV were detected in four heifers, but five were serologically positive. However, on day 3 before shipment, all heifers were seronegative and PCR-negative for BTV. Thus, a few animals from this consignment were viremic without any evident subclinical infection. Based on Seg-2 (VP2 gene) and Seg-5 (NS1 gene) sequencing, the recovered virus had 99.86–100% nucleotide identity with BTV-14-like viruses such as the vaccine BTV-14 strain RSArrrr/BTV 14 and the BTV-14 isolates detected in Lithuania and Poland in 2012. Subsequently, BTV-14 was also reported in local animals in two regions of Russia. During the monitoring survey, 1623 local animals within a 300-km radius were tested, of which 471 tested positive by ELISA and 183 by PCR for BTV-14 RNA. No other serotypes were identified in either imported or aboriginal animals within that radius. The Culicoides midges trapped at the site of the outbreak in May 2012 tested positive for the BTV-14 genome, indicating that the possible mechanism of spread most likely occurs via vector bites. However, further investigation is required to confirm this hypothesis, which would provide an improved understanding of the circulation and overwintering of BTV in northern latitudes.

INTRODUCTION
Historically, bluetongue (BT) was considered endemic within Africa and was first discovered after fine-wool sheep imported from Europe (1). The affected sheep exhibited the typical symptoms of swollen lips and tongue accompanied by a characteristic tongue cyanosis, giving a name to the disease (2).
BTV is endemic throughout Africa within the range of its primary vector Culicoides imicola. The virus was first confirmed outside Africa in India (20) and then in Australia, where the virus was isolated from Culicoides collected near Darwin in 1975 (21). The distribution of BTV has been substantially expanding, although historically, before 1998, its range was confined to regions between the latitudes of 35 • S and 40 • N (7).
BTV was never expected to reach areas far beyond its traditional northernmost latitude. That could be explained by the relatively cold climate and short period of seasonal midge activity preventing this virus from establishment [reviewed by (22)]. However, in 2008, BT arrived in northern Europe and caused unprecedented outbreaks (7). The arrival of BTV could be attributed to the movement of infected ruminants or the wind dispersal of infected midges (23). Notably, the key role in the transmission of BTV in northern Europe was played by novel Palaearctic vectors, the Obsoletus and Pulicaris complexes (24). Considering the abundance of vectors and the recent changes in climate, it is not surprising that new BTV strains have appeared. These strains include reassortants and serotypes from the Mediterranean region, which are now considered endemic, and new strains are expected to continue to regularly appear (18,25,26), putting Eastern Europe and the European part of Russia at risk.
In Russia, the first historical outbreak of BTV among sheep caused morbidity of 58.3% and mortality of 66.3% in 1993 in Eastern Siberia (Republic of Buryatia) (27). Vaccination successfully contained the outbreak. The serotype was identified as BTV16, which is related to the eastern topotype (unpublished data). Considering that Europe has recently experienced multiple incursions of different serotypes (25), the risks of BTV introduction into European Russia has increased dramatically owing to cattle trading between Russia and Europe. The first cases of BTV-8 infection were identified in cattle imported from Germany and the Netherlands in 2008 (28). Notably, BTV-8 was only isolated from imported animals. BTV-8 infection among local animals was prevented as all PCR and seropositive animals were immediately slaughtered (unpublished data). In addition, as reported here, in 2011 in the Smolensk region, another set of imported animals imported from Germany was identified as carrying the BTV genome and anti-BTV antibodies during the quarantine period, although the laboratory results obtained before shipment into Russia were negative. In this study, the BTV-14 strain isolated in the 2011 outbreak in the Smolensk region in Russia was characterized. Serotype/topotype analysis of the Russian BTV isolate relied on the comparison of Seg-2 and Seg-5 sequences and conventional serotyping. To determine the source of the infection and investigate its spread within the country, phylogenetic and evolutionary divergence data, as well as data from monitoring studies in the Smolensk region and neighboring areas, were analyzed. The farm "Smolensky Gallovei" is typical in that it has a barn with open windows and animals are grazed daily in the field and rounded up twice a day for milking.

Sample Collection
According to the BTV testing protocol, the animals were sampled for PCR and ELISA twice, at days 3 (05.09.2011) and 27 (29.09.2011) of the quarantine. Following the identification of infection, the quarantine was extended, and additional samples from the seropositive animals were collected on days 73, 104, 138, 189, and 207 ( Table 1).
As part of the study, in 2012, an additional 1623 serum and whole-blood samples were collected from clinically healthy cattle, sheep, and goats from different farms in the Kaluga and Smolensk regions within a radius of 300 km from the outbreak site (Figure 1).

Virus Isolation
Blood was used for the first round of virus isolation in 10-to 12-day-old chicken embryos, according to the protocol described by Clavijo et al. (29). The inoculation of embryonating chicken eggs is more sensitive than cell culture, allowing detection of BTV in samples containing a low viral concentration (30). The blood (1/10 dilution) was intravenously inoculated into an embryo vein, incubated at 33.5 ± 0.5 • C, and monitored daily for 7 days. Chicken embryos with pathological signs were further processed for downstream inoculation onto Vero cells, which were inoculated with filtered material in a T25 flask. Cytopathic effects (CPE) in the cell monolayers were used to detect the virus. The development of CPE was observed daily for up to 7 days post-inoculation. The virus was titrated by visualization of CPE in Vero and BHK-21/13 cell cultures. Titers were expressed as median tissue culture infectious dose (TCID50), according to the Reed-Muench method (31).

Laboratory Diagnosis and Virus Identification
Laboratory diagnosis of infection was performed using enzyme-linked immunosorbent assay (ELISA) and reversetranscription polymerase chain reaction (RT-PCR). Blood serum was tested for anti-VP7 antibodies by using an ID Screen Bluetongue Competition ELISA kit (IDVet, France) following the manufacturer's recommendations. The signal-to-noise ratio (S/N% = OD Sample/OD NC × 100) was calculated, and a sample with a ratio greater than or equal to 40% was considered negative, whereas a sample with a ratio less than 40% was considered positive. Then, serum samples with inconclusive results were retested.
Total RNA was extracted from the samples with TRIzol (Thermo Fisher Scientific, USA), precipitated with isopropanol, and washed with 75% ethanol, according to the manufacturer's protocol. Universal real-time RT-PCR directed against the nonstructural protein 3 (NS3) fragment of the BTV genome was initially used to detect virus dsRNA in blood samples (32). The serotype 14 was identified using serotype-specific RT-PCR for genome segment 2 (Seg-2) (33). For both assays, the cutoff was set at a Ct-value of 38.
To confirm the identified serotype, virus neutralization tests (VNT) against reference antisera to each of the 25 BTV serotypes (1-24, 26) were conducted. The VNT was performed using Vero and BHK-21/13 cell cultures as described by Koltsov (35).

Sequencing and Phylogenetic Analysis
The serotype was confirmed by sequencing of the cDNA amplicons and by phylogenetic comparisons with previously characterized reference strains of each serotype.
Then, the samples that were identified as positive by universal real-time RT-PCR were subjected to VP2 (Seg-2, 2,922 nt) and NS1 (Seg-5, 1,772 nt) sequencing. Seg-2 and Seg-5 were chosen as serotype-and topotype-determining genes. Seg-2, together with Seg-5, encodes the proteins that define the BTV serotype, with the major contribution coming from VP2 (36). The complete gene sequences of VP2 and NS1 were determined by amplification of overlapping PCR products (three for segment 2 and two for segment 5) in the PCR assay, as previously described (35).
The cDNA was synthesized with primers specific to the ends of the BTV genome segments, using the SuperScript First-Strand Synthesis System for RT-PCR (Invitrogen, USA). The PCR was performed using specific primers and Quick-Load R Taq 2X Master Mix (NEB, USA). The PCR products were purified using a MinElute Gel Extraction Kit (Qiagen, USA). Sanger sequencing was used to assemble the complete sequences of Seg-2 and Seg-5 from overlapping PCR amplicons. The sequencing was conducted using the same primers in both directions.
SeqScape R Software for Mutation Profiling v. 2.5 (Applied Biosystems, USA) was used to obtain a consensus sequence. The VP2 and NS1 gene sequences were aligned using ClustalX (37). The full-length VP2 and NS1 sequence data of a BTV isolate were subjected to blast analysis using the NCBI BLAST tool (https://blast.ncbi.nlm.nih.gov/Blast.cgi) and were compared with sequences of commonly used reference strains and other strains represented in the GenBank (https://www. ncbi.nlm.nih.gov/genbank). Phylogenetic trees were constructed using the maximum likelihood method in which phylogenetic distances were estimated using Kimura's two-parameter model (K2P) (38) in the MEGA 7 program (39).

Entomological Surveillance
Entomological investigations were conducted in the territory of the Smolensk region in 2012. Culicoides biting midges were collected in May from farms where BTV-14-infected animals were detected, and trapped using a CDC light trap with UV light (OVI traps) using a common technique. The trap was elevated 1.5 m above the ground near the cows and was operated from dusk (1800) to dawn (0800).
The collected midges were cooled, pooled, and morphologically identified into the Obsoletus and Pulicaris complexes using the keys described by Glukhova (40).
To identify the complexes at the species level, midge pools were tested using PCR assays based on mitochondrial cytochrome c oxidase subunit I gene amplification (41). RNA from insect pools (100 midges) was isolated using Trizol (Thermo Fisher Scientific, USA) according to the manufacturer's recommendations.

RESULTS
Blood and serum samples of the 71 heifers from the same consignment in the Smolensk region were tested for the BTV genome using real-time RT-PCR and for anti-BTV antibodies using ELISA at days 3, 27, 73, 104, 138, 189, and 207 of quarantine. At day 3 of quarantine, all the animals were tested negative by real-time RT-PCR and ELISA ( Table 1). At day 27, as well as at days 73, 104, and 138, antibodies were detected in five animals (nos. 01051, 01224, 75981, 94835, and 10055), four of which (the exception was no. 94835) were RT-PCR positive for the BTV genome at 138 days ( Table 1).
At days 189 and 207, BTV RNA was no longer detected in the blood of the five animals, although anti-BTV antibodies were still detected.

Virus Isolation
In the positive blood samples collected on day 27 of quarantine, the virus was isolated by inoculation into chicken embryos, followed by cultivation on Vero cells. After a 7-day incubation, the virus was harvested at 5.0 lg TCID50/cm 3 . A total of four BTV isolates were isolated.
The isolated BTV was capable of replication in different cell cultures (Vero, BHK-21/13, SK). The viral titer, depending on the cell line and the multiplicity of infection, ranged from 5.5 to 7.5 lg TCID50/cm 3 . Viral reproduction led to the destruction of the cell monolayer at 3-5 days post-infection.

Virus Identification
The highest neutralization index (3.0 lg) was observed when the viruses isolated from the four animals (01051, 01224, 75981, and 10055) tested positive for reference BTV serotype 14 antiserum in the VNT. Simultaneously, the neutralization indexes when testing the virus samples with other reference sera did not exceed 0.75 lg, indicating that only the one serotype was present in the field.
The BTV-14 genome was detected in all blood samples of infected animals, as well as in the samples of infected chicken embryos and cell cultures that previously tested positive by universal real-time RT-PCR based on the NS3 protein. In the serotype-specific RT-PCR testing, the results were negative for BTV 1,2,4,6,8,9,11,and 16. Thus, the virus isolated from the infected animals in the Smolensk region was identified as serotype 14 of BTV.

Molecular Characterization
The VP2 and NS1 gene sequences of the G244/11 strain were deposited in GenBank under the accession numbers KR233814.1 and MN746787, respectively. The Seg-2 and Seg-5 nucleotide sequences of the four isolated viruses were all identical. In the phylogenetic analysis based on Seg-2 sequences of the G244/11 strain and previously characterized reference strains, the result of virus typing by VNT and serotype-specific real-time RT-PCR was confirmed. Thus, in the maximum likelihood tree, the G244/11 strain was grouped with BTV strains of serotype 14 with a bootstrap confidence value of 54-100% (Figure 2). Phylogenetic inference was used to place the G244/11 strain in a group comprising serotypes 6, 14, and 21 (Nucleotype C).
The sequence of the VP2 gene (Seg-2) had 99.93% nucleotide identity with that of the VP2 of the RSArrrr/BTV 14 (AJ585135) strain that was part of a polyvalent vaccine preparation, which included serotypes 1, 4, 6, 12, and 14 (Onderstepoort Biological Products, South Africa). The Seg-2 sequence was also similar to the sequences of European BTV-14 strains SPA2012/01 (isolated in Spain from animals imported from Lithuania) and POL2012/01 (isolated in Poland), with nucleotide identity of 99.86 and 99.90%, respectively.

Monitoring Survey
In 2011, BTV-14 was detected for the first time in the Russian Federation. As described previously, the virus was isolated only from cattle imported from Germany, during the quarantine period. To evaluate the incidence of BTV-14 among local livestock, local cattle, sheep, and goats grazing within a 300-km

Region
Year Animals Number of animals radius were sampled. To assess the prevalence of BTV infection, a serological and virological survey was conducted in local cattle, sheep, and goats from farms in the Smolensk and Kaluga regions between 2011 and 2012 (Figure 1).
A serological survey was conducted between 2011 and 2012 for specific antibodies against BTV using ELISA. The results for the seroprevalence of BT among animals in these regions are presented in Table 2. The seropositivity of cattle, sheep, and goats for BTV was 29.02% (471 of 1,623 animals, 95% CI = 26.83-31.31%). The highest seroprevalence was among ruminants in the Kaluga region (51.08%; 285 of 558 animals, 95% CI = 46.85-55.29%). Additionally, the BTV-14 genome was detected in 183 of the serologically positive animals (Ct values ranged from 26.1 to 37.6) by serotype-specific real-time RT-PCR and by universal real-time RT-PCR, whose results were 100% correlated ( Table 2).
The negative results of the serotype-specific RT-PCR tests for BTV 1,2,4,6,8,9,11, and 16 eliminated the other serotypes and indicated that only the BTV-14 serotype was actively circulating in the populations of local animals in the studied regions.

Entomological Investigation
A total of 4,963 midges were collected, of which 366 (7.37%) belonged to the Obsoletus complex and 4,597 (92.63%) to the Pulicaris complex. Molecular analysis confirmed that the four species of the C. pulicaris complex (C. pulicaris s.s., C. punctatus, C. impunctatus, and C. grisescens) were present in the pools of biting midges.
Four pools of Obsoletus complex midges and 46 pools of Pulicaris complex midges were tested. Among them, only three pools of Pulicaris complex midges tested positive for BTV-14 RNA, with Ct values ranging from 31.3 to 33.9. The Obsoletus complex midges had no detectable BTV genome. When Seg-2 was sequenced, the sequences of the positive midge pools proved identical to those of the animals, indicating the same virus.

DISCUSSION
The key factors driving the incursions, transmission, and overwintering of BTV in Europe remain poorly understood (42). In particular, the unexpected incursions into new territories, of which the arrival of BTV-8 in Northern Europe is a good example (43), require elucidation.
The Russian territory bordering Europe experiences prolonged, cold winters followed by relatively short summers, which do not seem to favor the spread of BTV and make overwintering unlikely (44). Nevertheless, midges are abundant across the country (45). The first peaks of blood-sucking midge activity occur as early as late May, and secondary peaks, although less abundant, occur in July in Western Russia, dwindling dramatically in August (44,46). However, the genetics and vectorial capacity of Russian midges remain to be poorly understood to conduct a risk analysis.
Sequencing of the VP2 (Seg-2) and NS1 (Seg-5) genes resulted in the Russian BTV-14 strain being grouped with a vaccinelike BTV-14 strain used in African countries (Figure 2). In addition to these findings, a related BTV-14 strain was also documented in Poland in animals near the Polish-Belarusian and Polish-Lithuanian borders in 2012 (47). Notably, Russian strain G244/11, strain SPA2012/01 detected in cattle in Spain imported from Lithuania, and Polish strain POL2012/01 shared approximately 99.9% identity based on the VP2 gene. However, the Russian strain carried two non-synonymous substitutions at position 1622 (C/T) and position 2427 (A/G) that were missing from the Polish and Lithuanian strains. This observation indicates the circulation of a live BTV-14 vaccine strain that spread asymptomatically and evolved in the field, likely in midges, before its detection in the Russian territory in 2011. The different BTV-14 strains were likely derived from a common source. However, when compared with the North American strains BTV-14, CAR1982/04, and USA2003/FL, Seq-2 of G244/11 shared 87.4 and 87.2% identity, respectively.
According to data obtained from Rosselhosnadsor (Russia), there was no evidence of infection in local animals before 2011 or after 2012 (http://fsvps.ru/fsvps/iac/rf/reports.html). However, 58 seropositive animals were identified in the Kaluga region in 2010 during monitoring studies in Russia (n = 39,113 during 2009-2010) (http://fsvps.ru/fsvps/iac/rf/reports.html). In blood serum samples (n = 1963) collected in 2011 from different regions of Poland, antibodies against BTV were detected in 494 animals. However, no virus or viral genome was detected (47). Currently, no information is available on the prevalence of the disease in past decades in Belarus. Thus, the initial source of infection remains unclear.
Notably, the animals did not present with any clinical signs and remained asymptomatic throughout the outbreak, which significantly limited understanding of BTV epidemiology in the moderate continental climate. The third day of quarantine occurred in early September 2011, whereas the 27th day (when the virus could still be recovered) occurred in late September. The average temperature at dusk between the dates was 7-13 • C. This range comprised temperatures that include the minimum temperature or even outside the optimal range for flight activity of midges at this time of the year in Smolensk (44)(45)(46). In addition, little actual flight activity was recorded during this period. Thus, the entomological evidence does not support the hypothesis that the outbreak originated in Russia with the animals becoming infected during quarantine. Moreover, although the infectious virus was recovered in late September (day 27), for infection to occur, the midges had to be active and abundant, which was not the case in Smolensk in September 2011. Therefore, the most likely scenario is that the heifers were infected en route in Poland or Belorussia, which have a milder climate and where, from May to September, the highest midge activity is observed (47). The failure to detect the virus at day 3 of the quarantine may be attributable to the incubation period of the disease. In this study, BTV RNA could be detected for only 111 days (Table 1), although the maximum period for which RNA can be detected in infected animals is up to 160 days (48).
Due to this outbreak and the following report by Russia in 2011 (Ref. OIE: 11439, Report Date: 30/12/2011, Country: Russia), the attention of the World Organization for Animal Health (OIE) 1 was drawn and BTV-14 became the focus of attention in Eastern Europe beginning in 2012 (47,49). Although Russia was the first to report BTV-14, the report followed the import and testing of the consignment of heifers and therefore does not mean that the infection first appeared in Russia. The infection may have appeared elsewhere, and spread over a long distance via midges that are not bound by national borders.
Importantly, a live vaccine containing BTV-14 is not available on either the EU or the Russian market, which indeed suggests previous illegal use of a BTV-14-based vaccine. Although no evidence is available to support this contention, according to Nomikou et al. (49,50), whole-genome sequencing data suggest that BTV-14 strains that have spread in Europe and Russia are reassortants containing genome segments derived from different reference vaccine strains originating from South Africa (49,50). Nevertheless, although a possible vaccine incident is suggested as the source of the infection, consistent with the sequencing data presented herein, evidence of the illegal use of a live vaccine is lacking, as previously noted. Moreover, the use of a polyvalent vaccine preparation that included serotypes 1, 4, 6, 12, and 14 (Onderstepoort Biological Products, South Africa) does not seem logical, because the greatest threat to this area is associated with the BTV-8 serotype.
A possible alternative explanation for the present incidence is infection via BTV-contaminated fetal bovine serum, which is used as a semen extender for artificial insemination of cattle (51). Unfortunately, data on the extent of its use in the farming industry are not available. In addition, contaminated serum or other components may have been used to produce other live vaccines for cattle or small ruminants, which have already shown potential for contamination with BTV, as reported for a sheeppox vaccine (16). Following vaccination, the contaminating BTV can escape and begin to circulate in the field. This route seems most plausible for the reported case; however, this hypothesis lacks evidence on what type of vaccine may have been contaminated.
Collectively, the literature indicates that blood-sucking insects drive BTV transmission across countries (8,19). The reassortant nature of BTV-14 in Eastern Europe suggests that midges are most likely responsible for the BTV diversity (49,52). Nevertheless, the vector species for the virus in Western Europe remains to be determined.
Entomological surveillance conducted in the Smolensk and Kaluga regions in 2012 demonstrated detection of the BTV-14 genome in midges of the C. pulicaris complex but not in those of the C. obsoletus complex. This study is the first to show that midges in Russia can potentially serve as a vector for BTV. However, this claim is made with the following caveats. In this study, midges were not sorted into nulliparous and engorged midges, and the focus was only on PCR positivity. Therefore, the results could indicate a positive blood meal rather than infected midge heads. This finding warrants further study to determine whether Russian midges can potentially be infected and subsequently transmit BTV. Another interesting observation was that Pulicaris complex midges dominated the catch, although Sprygin et al. (44) reported that Obsoletus complex midges are very abundant in the Smolensk region. In addition, although BTV RNA was not detected in Obsoletus complex midges, only four pools were tested.
Another limitation of the current study is that archived samples approximately 1 year before importation of the animals could not be accessed. This information would have provided insight into the actual prevalence of BTV-14 in the area during that period.
To obtain an update on the epidemiology of BTV in Russia, including serotype 14, an annual monitoring survey has been conducted. According to published reports by Rosselhosnadsor, no infected animals were detected from 2013 to 2019 in Russia (n = 217,286) (http://fsvps.ru/fsvps/iac/rf/reports.html).
In summary, this study describes the detection of asymptomatic BTV-14 infection in cattle in the Smolensk region of Russia in 2011. The identified BTV strain was genetically related to a vaccine BTV-14 strain, based on Seg-2 sequencing. However, the origin of the outbreak remains speculative. Although the possible mechanism of spread seems to be via vector bites because the collected midges tested positive for BTV dsRNA, this assumption merits further investigation. Elucidation of the mechanism involved would provide crucial insights into the circulation and overwintering of BTV in northern latitudes.

ETHICS STATEMENT
An ethical review was not required for this study, according to local and national legislation, because this work does not contain any experiments on animals. Blood and serum samples from cattle, sheep and goats were collected using standard procedures to avoid the suffering of animals and followed the guidelines of the State Veterinary Service of the Russian Federation. Farmers consented for the participation of their animals in this study.

AUTHOR CONTRIBUTIONS
ST and DK contributed to the conception and the design of the study. AK conducted field and laboratory work. AG participated in epidemiological data analysis. ST, AK, and GK performed laboratory data analysis. GK and AK wrote and reviewed the manuscript. All authors read and approved the final manuscript.


extfieldsofstudy:
Medicine
Materials Science

text:
Changes in facial surface temperature of laying hens under different thermal conditions

Objective The purpose of this study was to identify through infrared thermal imaging technology the facial surface temperature (FST) of laying hens in response to the variations in their thermal environment, and to identify the regional differences in FST to determine the most stable and reliable facial regions for monitoring of thermoregulatory status in chickens. Methods Thirty Hy-Line Brown hens (25-week-old) were sequentially exposed to three different thermal conditions; optimal (OT, 22°C±2°C), low (LT, 10°C±4°C), and high temperature (HT, 30°C±2°C). The mean values of FST in five facial regions including around the eyes, earlobes, wattles, beak and nose, and comb were recorded through infrared thermography. The maximum FST (MFST) was also identified among the five face-selective regions, and its relationship with temperature-humidity index (THI) was established to identify the range of MFST in response to the variations in their thermal environment. Results Hens exposed to OT condition at 15:00 displayed a higher temperature at wattles and around the eyes compared to other regions (p<0.001). However, under LT condition at 05:00 to 08:00, around the eyes surface temperature showed the highest value (p<0.01). In HT, wattles temperature tended to show the highest temperature over almost time intervals. Main distribution regions of MFST were wattles (63.3%) and around the eyes (16.7%) in OT, around the eyes (50%) in LT, and wattles (62.2%) and comb (18.3%) in HT. The regression equation between MFST and THI was estimated as MFST = 35.37+ 0.2383×THI (R2 = 0.44; p<0.001). Conclusion The FST and the frequency of MFST in each facial region of laying hens responded sensitively to the variations in the thermal environment. The findings of this experiment provide useful information about the effect of the thermal conditions on the specific facial regions, thus offering an opportunity to stress and welfare assessment in poultry research and industry.

INTRODUCTION
Recently, global environmental temperature increase due to global warming and climate change are getting worse every year, and livestock cannot be free from the effects. Heat stress occurs when the net heat dissipation flowing from the body to its surrounding environment is less than the amount of heat energy produced by the body [1], and it causes serious losses in animal welfare and productivity. Heat stress reduces the feed intake, body weight, production efficiency and metabolic rate of animals [2,3]. In broilers, heat stress increased pale, soft and exudative meat, drip loss and lactate content in the muscle, whereas it reduced protein synthesis in the breast muscle, caused oxidative damage to skeletal muscle and had a harmful effect on meat color and pH value [4,5]. Heat stress not only caused a reduction in feed intake, body weight, dietary digestibility, dietary calcium, serum protein and calcium content but also caused reproductive problems, poor egg quality, impaired skeletal integrity, poor egg mass and poor egg production in laying hens [6,7]. Poor performance under heat stress is accompanied by not only drop in the growth performance but also increasing mortality of broilers [8].
The heat stress levels animals feel vary according to environmental factors, such as ambient temperature, relative humidity, solar radiation and wind speed, and animal management strategies, such as feed, water, environment modifications and handling changes. In addition, animal characteristics such as species, color, sex, age, temperament, previous exposure, body condition and current health could also affect the extent of heal stress [3,9]. Therefore, the heat stress from which animals suffer can be diagnosed accurately when a variety of measurement methods are combined to reflect animal-based criteria in addition to measuring environmental factors.
Ambient temperature is a crucial climatic factors that has a strong effect on maintaining the body temperature within the normothermic ranges in domestic fowls; therefore, their body temperature monitoring will provide useful information in regard to the intensity of thermal stressors on their thermoregulatory status [10,11]. The conventional methods directly measure the body temperature, and thus are associated with invasiveness, and being time consuming and laborintensive. Therefore, conventional methods would potentially result in measurement errors. In response to these shortcomings, infrared thermal imaging technology offers a fast, highly precise, non-invasive, and non-contact method for measuring the skin surface temperature [12]. Furthermore, this technology enables to continuously collect the data during the stress period, which eliminates the confounding effects associated with frequent capturing of animal and sampling [13].
A strong correlation has been reported between body temperature and facial surface temperature (FST) in chicken [11]; therefore, the variations in environmental temperature could rapidly be manifested in skin surface temperature, which makes it an important parameter in monitoring the comfort or thermal stress of chickens using infrared thermography [14][15][16]. For skin temperature measurement using infrared thermography in poultry studies, bare areas such as the eye, comb and wattle, earlobes, or nose are the potential zones for detection of temperature differences as thermal stressor intensity changes. Herborn et al [13] identified temperature differences in the skin surface of hens as thermal intensity shifted from a mild to a more severe acute stress. However, to our knowledge less is known about the contributions of different facial surface sites of laying hens when exposed to thermally comfortable or stressful conditions. Therefore, this study was aimed at identifying the regional differences in the FST of laying hens through infrared thermography technology in response to the thermal variations in the environment.

Animals and management
This experiment was implemented under the approval of the Institutional Animal Care and Use Committee of Konkuk University (IACUC No. KU 19003). Thirty 25-week-old Hy-Line Brown laying hens were placed in a 3×7 m experimental room. Three hens were placed in a battery cage with a stocking density of 420 cm 2 /hen, so whole hens were assigned to ten cages. Ambient temperature and relative humidity were maintained using a ventilation fan and a thermal insulation facility. The photoperiod was 16 L:8 D with lights on from 05:20 to 21:20 h, and the lighting was kept above 10 lux during the bright period. The feed for the early laying period (20 to 40 weeks of age) was given 150 g twice a day, morning (07:00 h) and afternoon (14:00 h). Freshwater was available freely through a nipple and feces were cleaned once a day.
Prior to data collection, hens were given a 15-d adaptation period to experimental conditions and stocking density (temperature = 22°C±2°C, mean±deviation; relative humidity = 44% -62%). After adaptation period, the data were collected under optimal temperature (OT, 22°C± 2°C) for 3 days. The temperature was then switched to low temperature (LT, 10°C±4°C; mean±deviation) and hens were kept in LT for 7 days (4 days of adaptation + 3 days of data recording). Hens were given a buffer period of 22°C±2°C for 7 days. The temperature was then switched to high temperature (HT, 30°C±2°C; mean±deviation) for a period of 7 days (4 days for adaptation and 3 days for data recording).

Facial surface temperature measurement
The FST data (n = 30) were collected at six intervals: 05:00 h, 08:00 h, 12:00 h, 15:00 h, 18:00 h, and 21:00 h during three collection days using infrared thermal camera (CX320; COX Co., Daejeon, Korea). Ambient temperature and relative humidity were also recorded five times a day, according to the infrared thermal imaging sampling time, using mercury thermometer YY-11 (Dong-myeong, Seoul, Korea) and the psychrometer TM0081 (TQC, Capelle aan den IJssel, Netherlands). The calibration of the thermometer and the psychrometer were guaranteed by the professional experts. The following equation was used for calculation of temperature-humidity index (THI) specified for laying hens [17]: Five distinct facial areas -around the eyes, earlobes, wattle, comb and beak and nose -were selected for FST measurements ( Figure 1). Three images were taken at each distinct facial area of each individual on each time interval, and the average temperature was determined using Thermal Imaging Analyzer software ver. A.8 (COX Co., Korea). The maximum FST (MFST) was defined as the maximum temperature among the five facial regions in individual hens. The individual MSFT values at each time point (n = 30) were collected and the mean value was calculated. The proportion of each facial region to MFST was also determined at each collection time for the three experimental group.

Statistical analysis
The data of FST were compared among the five face-selective regions and those of MFST to identify the regional differences in FST. Also, the MFST values were compared among the three experimental groups. The proportion data of each facial region to MFST was compared among the five regions for each experimental group to detect the most stable and reliable facial regions for monitoring of thermoregulatory status in laying hens. These data were analyzed by using analysis of variance (ANOVA) of the general linear model procedure in SAS ver. 9.1 (SAS Institute, Cary, NC, USA). When a statistically significant difference was identified, Duncan's multiple range test was used to detect statistical significance (p<0.05). The correlation and regression analysis between MFST and THI were also conducted to identify the range of FST of laying hens under different thermal environment. The correlation data were statistically analyzed by using Pearson's product-moment correlation and the regression data were analyzed by using ANOVA of the simple linear regression analysis in R studio ver. 1.3.1073 (R studio, Boston, MA, USA).

Facial surface temperature
Changes in FST of the five specific regions under different thermal conditions are presented in Table 1. Under OT exposure, wattle and MFST temperatures at 05:00 h were 38.31°C and 38.58°C respectively, which were higher than that of earlobes, beak and nose (p<0.001), but no significant difference was detected with comb and around the eyes regions. At 08:00 h, the MFST was 39.30°C, which was significantly higher than those of wattles, comb, beak and nose (p<0.001), but the significance with around the eyes and earlobes was not observed. At 12:00 h, the MFST and wattles were 40.35°C and 40.32°C respectively, which were higher than that of beak and nose (p<0.001), but no significant difference was detected with around the eyes, earlobes and comb regions. At 15:00 h, MFST, wattles and around the eyes recorded the highest temperature (mean = 41.66°C) among the other regions (p<0.001). At 18:00 h, MFST and wattles temperatures were 39.2°C and 39.01°C respectively, which were higher than all regions except around the eyes (p<0.001). At 21:00 h, the MFST, around the eyes and wattles were 41.05°C, 40.65°C, and 40.27°C respectively, which were higher than that of earlobes (p<0.001), but no significant difference was detected with comb, beak and nose regions. Under LT condition, the temperatures of MFST and around the eyes were 35.1°C and 34.8°C at 05:00 h, 37.7°C and 37.5°C at 08:00 h, respectively, which were the highest among all regions (p<0.001). At 12:00 h, MFST, wattles and around the eyes temperatures were 41.01°C, 40.7°C, and 40.1°C, respectively, showing significantly higher than the other areas (p< 0.001). At 15:00 h, the temperatures of MFST, around the eyes and wattle were 39.4°C, 38.72°C, and 38.68°C, respectively, which were the highest among the other regions (p< 0.001). At 18:00 h, MFST temperature was 37.6°C, which is significantly higher than other regions except for around the eyes (p<0.001). At 21:00 h, the temperature of MFST was 35.7°C, which is significantly higher than other regions except for around the eyes (p<0.01).
Hens exposed to HT displayed mean MFST and wattle temperatures of 39.8°C and 39.7°C at 05:00 h respectively, which were the highest value of all regions (p<0.001). At 08:00 h, the temperatures of MFST, wattle, comb, and around the eyes were 40.4°C, 40.2°C, 40.0°C, and 39.95°C, respectively, which were higher than the remaining regions (p<0.001). At , which were higher than that of earlobe, beak and nose (p< 0.05), but no difference was recognized with those of comb and around the eyes.

Maximum facial surface temperature
Changes in MFST distribution among the five facial regions in the laying hens exposed to optimal, low and high temperature are presented in Table 2. Compared with LT, HT-exposed hens recorded a significantly higher MFST at all collection times (p<0.001), and this difference was the highest at 21:00 h (41.61°C vs 35.68°C). Compared with OT, hens kept in HT condition exhibited higher MFST values from 5:00 h to 12:00 h (p<0.001). However, no significant difference existed between HT and OT at 15:00 h and 21:00 h. In general, hens that were exposed to OT exhibited values of MFST ranging from 38.58°C through 41.88°C, which were significantly higher than those obtained from LT-exposed hens in all time intervals, with the exception for 12:00 h (p<0.001) when LT group displayed a higher value (40.35°C vs 41.01°C). The proportion of each facial region to MFST in laying hens kept under different thermal conditions is shown in Table 3. In OT group, MFST was more frequently detected at wattle (63.3%) and around the eyes (16.7%) regions (p< 0.001), together contributing to 80% MFST values. In LT, MFST was frequently spotted at around the eyes (50%; p< 0.01). Around the eyes and wattles regions together contributed to 77.8% MFST values. In HT-exposed hens, MFST values were spotted in high proportion at wattle (62.2%) and comb (18.3%) regions (p<0.001), together comprising 80.5% of MFST values.
As illustrated in Figure 2, a significant correlation was observed between MFST and THI (r = 0.64, p<0.001). The regression equation between MFST and THI was estimated as MFST = 35.37+0.2383×THI (R 2 = 0.44; p<0.001).  OT, optimal temperature; LT, low temperature; HT, high temperature; SEM, standard error of the mean. a-c Means within a row without a common superscript differ (p < 0.05).

DISCUSSION
One of the notable features of the FST is that it is highly affected by dynamic environmental temperature changes. The core temperature in hens is regulated within the range of about 40.6°C to 41.7°C [18] but in this experiment, 10.27°C was the maximum difference of the mean MFST between the ambient temperature group of 6°C and 32°C. In addition, the standard error of the mean (SEM) associated with MFST tended to be smaller with the elevation of ambient temperature; however, higher values for SEM were obtained as ambient temperature declined. For FST measurements, the maximum surface temperature is an important parameter to indirectly measure the core temperature of animals as it more closely resembles the core temperature (Table 1). MFST, the result of body heat exchange, does not rise above the core temperature if the homeostasis of warm-blooded animals is maintained. At the proper temperature (OT), MFST ranged from 38.58°C to 41.88°C, which is generally close to the body core temperature in hens. This association demonstrates that the FST measurements using the thermal imaging camera is a suitable method in reflecting normal body temperature in hens when the environmental temperature is appropriate. On the other hand, the MFST value of 45.41°C recorded at 12:00 h in HT-exposed hens substantially exceeded the normal core temperature range (40.6°C to 41.7°C), which could possibly be explained by the inefficient body heat dissipation in laying hens when kept in heat stress situations. The ambient temperature at this time interval (12:00) was 32°C, which was the highest among the values recorded during HT experiment. A study with laying hens revealed that when THI increased from 25 to 29, hens experienced critical heat stress as evidenced by reductions in feed consumption and egg production, and increase in mortality rate [19]. This might provide an indication that in the current experiment, HT-exposed hens at 12:00 experienced a stressful situation as the mean THI was 27. Environmental temperature and relative humidity are the major factors that determine body surface heat exchange, and FST measurement using infrared thermography is be-lieved to reflect the rapid changes in body surface temperature. However, it is not enough to consider only ambient temperature and humidity as determinants in order to more sensitively detect changes in FST of laying hens. This is indicated by the fact that FST was measured high even though ambient temperature was not high, such as LT at 12:00 h or OT at 15:00 to 21:00 h. Heat stress results from an imbalance in the homeostasis of the animals, and the level of heat stress that an animal experiences is related to three main factors: the weather conditions, animal characteristics, as well as management protocols used [3,9]. Temperature, humidity, wind speed and solar radiation are important weather components involved in the extent of heat stress as animal experiences [3]. Therefore, several equations have been developed to help summarize these factors into a single usable number [20]. In laying hens, additional parameters such as laying age, the performance of laying, laying time, feeding time, active time, the diurnal rhythm of core temperature as well as species, color, sex, age, temperament, previous exposure, body condition, current health [9] should be considered for animal susceptibility. In addition, since core body temperature (CBT) is the body temperature that the animal maintains for body homeostasis, CBT measurements in the future studies and comparison with the CBT value with the body surface temperature value can specifically support the effect on the sensitivity of the animal [21]. To this end, further studies should be carried out to identify a correlation between each factor for hens' susceptibility and heat loss and production, and this effort will help detect more accurate and sensitive FST in laying hens.
Laying hen is a small animal, therefore, all regions of the face could easily be included in one photo, which results in MFST that incorporates the surface temperature values of the regions. However, infrared thermography can produce errors depending on the measurement distance or angle. Therefore, in order to minimize these errors, it is necessary to identify which facial region in the laying hen is the most reliable to record the highest distribution of MFST. Wattle surface temperature was the most stable part which showed the highest level of heat production at constant values under  any thermal variations. However, the MFST values were frequently identified at around the eyes region in LT-exposed hens. Therefore, wattles and around the eyes could be the most reliable regions for FST measurement in laying hens. However, depending on the environmental temperature, wattles and around the eyes, around the eyes and wattles, wattles could be more reliable at optimal, low, and high temperatures, respectively. In the present experiment, the poor correlation between MFST and THI and the coefficient of determination of the regression equation might be explained by the measurement method through infrared thermography. Since thermal images were measured manually by the attendant entering the experiment room at each measurement time, the laying hens could be affected by human access. In order to minimize interference due to human approach, the measurement distance of the thermal imaging camera was set at 1.5 m. In this experiment, however, the target subject for thermal image recording was the head of a small animal that is a very small area. Therefore, it is judged that the accurate temperature could not be sensitively detected because the size of the measurement object was small, and the distance was far. In actual farm situations, more accurate FST data will be obtained if the real-time automatic measurement systems could be installed at appropriate spots such as feed bins, water supply nipples, and egg laying boxes. In general, hens have a better ability to cope with low than high temperatures [18], and there is an increasing burden of long-term exposure to high temperatures in the summer, rather than the risk of exposure to low temperatures when managed in a henhouse. When the environmental temperature exceeds 30°C, the difficulty of body heat dissipation given to thick feathered hens increases, leading to high temperature stress. In this situation, the FST of laying hens has the advantage of being closer to the CBT [16] and being easier to access and measure than the surface temperature of other areas such as wings, legs, breast, and back.

CONCLUSION
Overall, body surface temperature measurements using infrared thermal imaging cameras can be applied to a large number of subjects in a short time, significantly reducing the time and effort acting as a burden on managers who measure body temperature, and there is also no stress on the livestock, which is the measurement target. The findings of this study enabled a better understanding of the temperature differences in the facial regions of hens in response to the ambient temperature fluctuations. Such data could be viewed as potential markers for identification of thermal stress intensity, and thus a useful way to improve the welfare of hens during the high-temperature periods.

CONFLICT OF INTEREST
We certify that there is no conflict of interest with any financial organization regarding the material discussed in the manuscript.


extfieldsofstudy: Chemistry Physics

text:
Matoa pasteurized milk quality subjected to the different levels of alginate

The addition of alginate in pasteurized milk processing could improve the impact of using matoa leaf extract on pasteurized milk. Matoa leaf extract was acidic. The use of a certain amount of matoa leaf extract in the processing of milk pasteurization could affect the stability of the (colloidal) dispersion of the final product. Hence, alginate was known to have the ability to inhibit some pathogenic bacteria. The purpose of this study was to determine the level of alginate used in matoa pasteurized milk processing on the microbiological and physical quality of matoa pasteurized milk. The parameters measured were the inhibitory effect on Escherichia coli, organoleptic on viscosity, and preference of matoa pasteurized milk. This study used a completely random design. The treatment used was without the addition of alginate (0%) and the addition of 0.1%; 0.2% and 0.3% alginate. The results showed that the increasing use of alginate in matoa pasteurized milk showed an increase in the ability to inhibit E. coli and an increase in panelists’ assessment of viscosity, and changed the panelists’ preference for matoa pasteurized milk. The use of alginate levels between 0.1-0.2% in the processing of matoa pasteurized milk improved the quality of the final product.

Introduction
Pasteurized milk is one of the most popular processed milk products in the market. The addition of functional ingredients continued to be done, thereby increasing the superiority of dairy products at large [1]. Pasteurized milk with the addition of matoa leaf extract could prevent the bacteria Staphylococcus aureus and Escherichia coli [2]. The use of matoa leaf extract in the production of pasteurized milk could produce products with good functional (as antibacterial) properties.
Matoa leaf extract is acidic. The use of matoa leaf extract at a certain degree in the production of pasteurized milk changed the stability (consistency) of colloidal products. Stabilizers were materials that contribute to improving product consistency. Stabilizers could contribute to product consistency during processing and storage. Alginate was a type of stabilizer that can improve the decline in the quality of pasteurized milk due to the use of matoa leaf extract [3,4]. Alginate is a plant origin natural stabilizer. It could improve consistency, taste, and extend shelf life, and could be used for various purposes. Junianto [5] stated that alginate compounds function as thickening agents, balance regulators and emulsifiers in various industries, besides that alginates contain several compounds that can work as antibacterial agents such as flavonoids, terpenoids, steroids, coumarin and alkaloids, rich in bioactive substances polyphenols, phlorotannin, and tannin compounds [6]. The switch of constituent components in the processing of matoa pasteurized milk with the addition of alginate levels affected the panelist's assessment of the viscosity and the preference for the final product. On the other hand, the addition of alginate was allegedly able to increase the ability to prevent the milk pasteurization of matoa toward E.coli. Regarding the comprehension, it considered necessary to know the quality (inhibition of E.coli, viscosity, and preference) of matoa pasteurized milk with the addition of alginate levels.

Materials and methods
The ingredients used in this study were full cream milk powder, matoa (Pometia pinnata) leaf, alginate, E. coli culture. Media for bacterial growth were nutrient agar. Other ingredients used were 70% alcohol, NaCl, distilled water, 70% ethanol and NaOH (from Sigma aldrich), etc.
This study was analyzed using a completely randomized directional pattern design. The treatment in this study was without alginate (0%) and the use of different alginate levels (0.1%; 0.2% and 0.3%).

Research procedure
Selected matoa leaves were washed, dried, and aerated at room temperature. The dried matoa leaves then mashed, weighed, and distilled water was added. The maceration was carried out for 2×24 hours. Further, the maceration products were used as powder extract with the freeze-drying method [7].
Pasteurized milk was made from reconstituted milk from full cream milk powder with a concentration of 10% (w/v). The matoa leaf extract were added of 0.20% and the alginate concentrations ware added 0%, 0.1%, 0.2% and 0.3%, respectively. The solution was then pasteurized by the HTST method (± 72℃ for 15 seconds) [8].

Measured parameters
The parameter measured in this study was the inhibitory effect of pasteurized milk on E. coli (by agarwell diffusion method) and the panelist assessment of viscosity level. Twenty-five semi-trained panelists assessed the viscosity level on a scale of 1-6 (thin-thickened) and the preference level, also on a scale of 1-6 [9].

Data analysis
Inhibitory effect of E.coli and viscosity test data were analyzed and processed with SPSS 16.0 for windows, while hedonic data were analyzed descriptively.

Inhibition of E. coli
Escherichia coli was a pathogen, Gram-negative, motile, and not spherical bacteria. This bacteria was used as an indicator of contamination in food. The ability of matoa pasteurized milk with the addition of alginate to inhibit E. coli was presented in figure 1.
The results showed that 0%, 0.1%, and 0.2% of alginate in pasteurized milk did not significantly inhibit E. coli. However, the use of a concentration of 0.3% alginate in pasteurized milk experienced a significant ability in the inhibition of E. coli. The alginates derived from seaweed and had antibacterial properties [10]. Selim [10] suggested that alginate had the ability as an antioxidant, immunostimulant, and antibacterial activity. Hermund et al. [6] further expound that alginates contained secondary metabolite compounds in different forms such as terpenoids, steroids, coumarin, flavonoids, and alkaloids, rich in bioactive substances polyphenols, phlorotannin, and tannin compounds that could inhibit the activity of free radicals and absorb metals, and was able to be applied in food.

Panelists assessment on the viscosity of matoa pasteurized milk by addition of alginate
The addition of alginate in matoa pasteurized milk processing affected the panelists' assessments of viscosity. The viscosity of matoa pasteurized milk with the addition of alginate was assessed by panelists on a scale of 1-6 (thin-thickened). The results were presented in figure 2. Increasing the level of alginate addition in matoa pasteurized milk processing enhanced the panelist's assessment of the viscosity of the final product. Alginate bound the water present in the ingredients. The more alginate used, the more water was bound. Besides, alginate would stabilize changes in colloidal dispersion due to the use of matoa. Reis et al. [11] suggested that stabilizers could minimize the occurrence of syneresis. The stabilizers could form gels and were thermostable. Syneresis that occurred in food was closely related to the strength of the gel from the addition of alginate as a stabilizer. Unrestricted water in the food component causes syneresis. Higher syneresis caused lower ability of the material to bind water [12]; consequently, a lot of water in the product came out. Conversely, if the value of syneresis was low, the ability to bind water was higher and the gel formed became stronger.

Panelists assessment on the preference of matoa pasteurized milk
Panelist assessment on the preferences was an overall evaluation of matoa pasteurized milk for color, taste, flavor, and thickness. Soekarto [13] argued that in the preference test, panelists were asked for their personal responses concerning likes or dislikes. In the analysis, the preference scale was transformed into a numerical scale according to preference level. The preference level of panelists in matoa pasteurized milk with the addition of alginate was presented in figure 3.  Figure 3. Assessment on the preference of matoa pasteurized milk by addition of alginate The addition of 0.1% alginate level material in matoa pasteurized milk processing clearly showed the best panelist evaluation response. A total of 64% out of 25 panelists gave like responses and the rest gave rather-like responses. The use of alginate levels of 0.2 to 0.3% showed a slightly decreased panelist preference responses compared to the use of 0.1% alginate. However, in general, the response of using alginate in pasteurized milk processing was still better than without the use of alginate. This result indicated that the use of alginate improved physical quality. The use of alginate will improve the ability to bind water in matoa pasteurized milk raw material. Junianto [5] suggested that alginate compounds functioned as thickening agents, balance regulators, and emulsifiers in various food industries. Transformation in texture and taste of a food product derived from its constituent components and the combination of various ingredients other than processing affected the level of one's liking for the final product. Violisa et al. [14] further stated that the addition of alginate in food processing was useful not only as a stabilizer to improve texture, but also increase the product viscosity.

Conclusion
The increasing use of alginate in matoa pasteurized milk showed an increase in the ability to inhibit E. coli and an increase in panelists' assessment of viscosity. The assessment of preference showed that 0.1-0.2% of alginate in matoa pasteurized milk gave the most panelists preference. The use of 0.1-0.2% alginate in the processing of matoa pasteurized milk improved the quality of the product.