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Effect of cassava wastewater on physicochemical characteristics and fatty acids composition of meat from feedlot-finished lambs/ Efeito da manipueira sobre as caracteristicas fisico-quimicas e composicao de acidos graxos da carne de cordeiros terminados em confinamento.

Introduction

Sheep farming in northeastern Brazil is characterized as a secondary subsistence activity of frequently very low profitability; for this reason, technologies that increase the yields from this activity are demanded. Furthermore, food options must be broadened to compose diets for the different animal categories, especially foods that provide better animal performance and a higher return to the farmer. The use of alternative foods has emerged as a good energy source to feed ruminants (Cunha, Carvalho, Gonzaga, & Cezar, 2008).

Some by-products from agribusiness such as those generated from cassava flour production (cassava peel, cassava meal, etc) have the potential and availability to beused as energy sources in ruminant nutrition (Pereira et al., 2012). The cassava wastewater, a yellowish liquid resulting from the pressing of cassava to produce the flour and starch, is an example of such energy sources (Curcelli, Bicudo, Abreu, Aguiar, & Brachtvogel, 2008).

On average, the cassava root processing results in approximately 30% of wastewater, which is improperly eliminated, contaminating the soil and groundwater (Almeida, Silva, Lima, Almeida, & Zacharias, 2009). The cassava wastewater disposed in the environment has a high polluting potential due to the amounts of organic material and cyanide compounds, which hare toxic to most aerobic microorganisms (Meneghetti & Domingues, 2008).

As an alternative food, two important considerations about cassava wastewater are note worthy: it may cause serious environmental damage if disposed in the environment and it is a by-product from the cassava root that is rich in sugar and starch, characterizing it as an energy source. Therefore, its use in animal nutrition can reduce the costs involved in the livestock activity while reducing the disposal of this waste in the environment.

Different food sources may change the composition and quality of meat. Studies have shown the effect of including cassava and its byproducts on the lipid content and fatty acid composition of lamb meat (Faria et al., 2014; Guimaraes et al., 2016). On this basis, cassava wastewater is a potential alternative food for the modulation of meat quality.

However, there is no consensus about the use of cassava wastewater in animal nutrition and meat quality despite the wide use of this by-product as raw material in agriculture. Furthermore, research about cassava wastewater in animal feed in gisscarce. The present study was thus conducted to evaluate the effect of cassava wastewater supplementation on the physicochemical characteristics and fatty acid composition of meat from feedlot-finished lambs.

Material and methods

This study was conducted at Embrapa Tabuleiros Costeiros, located in Frei Paulo, SE, Brazil, and at Universidade Estadual de Maringa (UEM), in Maringa, Parna State, Brazil. Thirtytwo uncastrated male Santa Ines lambs (167 days of age and 24.8 [+ or -] 3.00 kg bodyweight) were randomly distributed into one of four treatment groups, with eight animals per group differentiated by the inclusion of cassava was tewater. Treatments corresponded to cassava wastewater offered to the animals at the levels of 0.0, 0.5, 1.0, or 1.5 L [animal.sup.-1] [day.sup.-1].

The basal diet (150 g [kg.sup.-1] crude protein [CP]) was formulated according to Nuclear Regulatory Commission (NRC, 2007), to provide an average daily gain of 0.150 kg per finishing lamb. This diet contained Tifton 85 hay (Cynodon spp.) (900 g [kg.sup.-1] dry matter [DM], 108 g [kg.sup.-1] CP, 786 g [kg.sup.-1] neutral detergent fiber [NDF], and 530 in vitro dry matter digestibility [IVDMD]), corn screenings (901 g [kg.sup.-1] DM, 55 g [kg.sup.-1] CP, 731 g [kg.sup.-1] NDF, and 461 IVDMD), ground corn, soybean meal, limestone, and a mineral supplement. The roughage feeds (700 g [kg.sup.-1] DM) used were Tifton 85 hay and corn screenings (350 g [kg.sup.-1] DM). The basal diet was offered as a total mixed ration (Table 1).

The liquid residue from the extraction of flour and starch was obtained from the same flour manufactory. The cassava wastewater had the following composition: 43.4 g [kg.sup.-1] DM, 28.1 g [kg.sup.-1] ash, 6.6 g [kg.sup.-1] ether extract [EE], 11 g [kg.sup.-1] starch, 16.2 jig HCN [mL.sup.-1] cyanogenic compounds, 6.5 Brix total soluble solids (1[degrees] Brix is equal to 1 g of sugars per 100 [micro]g of solution), acidity of 0.23 (expressed as molar concentration of acids), and pH 4.91.Cassava wastewater does not contain significant amounts of CP, NDF, oracid detergent fiber (ADF).

Before the beginning of the experiment, the animals received anti-parasitic drugs and the effectiveness of control was determined by parasitological examination. Subsequently, they were housed in individual stalls with access to an automatic drinker and an individual feeder.

Lambs were fed daily, at 9 and 16h. The amounts supplied were weighed daily and adjusted according to the animal intake from the previous days, thus ensuring ad libitum feeding (1% to 20% orts). The cassava wastewater (0.0, 0.5, 1.0, or 1.5 L) was supplied in buckets attached to the individual stalls, once daily, in the morning. Before being offered, the cassava wastewater was homogenized to distribute the decanted starch evenly throughout the liquid.

All the cassava waste water used in the trial originated from the same flour manufactory. It was stored in plastic drums (200 L) and left at rest for about 10 days for volatilization of hydrocyanic acid (Pereira et al., 2012).

Samples of basal diet were collected and ground through a 1-mm-sieve screen to evaluate the following components: DM, ash, CP, EE, and IVDMD as described by Silva and Queiroz (2002); NDF and ADF contents as described by Van Soest, Robertson and Lewis (1991); NDF without the use of sodium sulfite and with the inclusion of heat-stable [alpha]-amylase (alpha-amylase Termamyl 2x, Tecnoglobo[R], Curitiba, Parana State, Brazil); and organic matter (OM), and total carbohydrates (TC) using equations described by Sniffen, O'connor, Van Soest, Fox and Russell (1992).

Cassava wastewater samples were analyzed to determine DM, ash, and EE as described by Silva and Queiroz (2002). Total cyanide was analyzed by the enzymatic method described by Essers, Bosveld, Grift, Van der Grift and Voragen (1993). The pH, titratable acidity, total soluble solids, and starch were determined according to methods described by Adolfo Lutz Institute (Zenebon, Pascuet, & Tiglea, 2008).

Animals were slaughtered after 70 days in the feedlot at an average body weight of 34.6 and an average age of eight months. After 12 hours of fasting, lambs were transported to a commercial slaughterhouse where they were slaughtered following the usual practices of the Brazilian meat industry after being stunned by an electric shock.

Carcasses were chilled to 4[degrees]C for 24 hin a cold room. Afterwards, they were split lengthwise along the spine and the longissimus dorsi (6th to 10th thoracic vertebra) was separated to measure the physical and chemical composition of the meat. The pH was measured after slaughter (initial pH = 6.55) on the hot carcass and after 24 hin the refrigerator at 1[degrees]C (final pH = 5.60) with a pH meter with penetration electrode (HI 996163, Hanna Instruments[R], Woonsocket, Rhode Island, USA).

Color values were measured on the longissimus dorsi muscle using a portable colorimeter (Chroma Meter CR-410, Konica Minolta[R], Osaka, Japan). The samples were allowed to bloom for 30 min. prior to the measurements. The parameters L*, a*, and b*, representing lightness, redness, and yellowness, plus the chroma (C*) and the hue (h*),were measured in five locations of each sample, and the average was recorded.

To determine the cooking losses, samples of meat were cut and weighed (initial weight). Individual standardized 50-mm-thick pieces were cooked in an electric oven to a defined internal temperature (72[degrees]C). When the endpoint temperature was attained, the samples were removed from the electric oven and kept at room conditions until reaching room temperature. The meat was then taken from the plates and weighed. To determine the shear force according to Wheeler, Shackelford and Koohmaraie (2001), the sample was cut from a block of thawed or cooked meat and taken to avoid damage. Sample strips of a least 1-cm thickness were obtained from a 2.5-cm cross-section made parallel to the fiber direction. The sample was sheared at a right angle to the axis. The units of measurement were kg [cm.sup.-2]. The shear force was measured perpendicular to the orientation of muscle fibers with a Warner-Bratzler shear device, adapted to the TA.XT Plus model (Stable Mycro Systems, United Kingdom) and analyzed as the average of six readings of each sample. The samples were completely sheared at a speed of 20 cm [s.sup.-1].

Laboratory analyses of meat were carried out two months after sampling. The samples were thawed at room temperature (20[degrees]C), ground, homogenized, and analyzed in triplicate. The beef moisture and ash contents were determined according to Association of Official Analytical Chemists (AOAC, 1998). The crude protein content was obtained by the Kjeldahl method (AOAC, 1998).Total lipids were extracted using a chloroform : methanolsolution (2:1 v/v) (Bligh & Dyer, 1959).

Fatty acid methyl esters were prepared by triacylglycerol methylation according to International Organization for Standardization (ISO, 2000) method no. 5509 with KOH/methanol and n-heptane. Thereafter, the methyl ester composition of fatty acids were measured by gas chromatography (Trace GC Ultra, Thermo Scientific, USA) equipped with an auto sampler, a flame ionization detector at 240[degrees]C, and a fused-silica capillary column (100 m long, 0.25 mm internal diameter, and 0.20 m film thickness, Restek 2560[R]). Fatty acids were quantified as g 100 [g.sup.-1] lipids and compared with the retention times of methyl ester fatty acids from the tricosanoicacid methyl ester (23:0) sample standard (Sigma-Aldrich[R], Brazil). The column parameters were as follows: the initial column temperature of 65[degrees]C was maintained for 8 min., then increased at a rate of 50[degrees]C [min.sup.-1] to 170[degrees]C; this temperature was maintained for 40 min. and then increased at a rate of 50[degrees]C [min.sup.-1] to 240[degrees]C and maintained for 28.5 min. The injector and detector temperatures were 220 and 245[degrees]C, respectively. The gas flow was 1.5 Ml [min.sup.-1] for hydrogen (carrier gas), 30 mL [min.sup.-1] for [N.sub.2] (auxiliary gas), 35 mL [min.sup.-1] for [H.sub.2], and 350 mL [min.sup.-1] for compressed air. With amicroliter syringe, 2 Lof the samples were injected with a split ratio of 1:100. Fatty acid peaks were identified by comparison with the retention times of pure methyl ester standards (Sigma-Aldrich[R], Brazil).

Based on the fatty acids composition, we calculated the sum of saturated fatty acids (SFA), monounsaturated fatty acids (MUFA), polyunsaturated fatty acids (PUFA), and desirable and fatty acids (DFA = MUFA + PUFA + C18:0) and defined the PUFA:SFA and n-6:n-3 ratios. The following indices were also calculated: A9 desaturase 16 = 100 [(C16: 1cis9)/(C16 + C16 1cis9: 0)]; A9 desaturase 18 = 100 [(C18: 1cis9)/(C18: 1cis9 + C18: 0)]; elongase = 100 [(C18: 0 + C18: 1cis9)/(C16: 0 + C16: 1cis9 + C18: 0 + C18: 1cis9)]; atherogenicity = [C12: 0 + 4 (C14: 0) + C16: 0]/([summation]SFA [summation]PUFAI + [summation]MUFA)]; and thrombogenicity = [(C14: 0 + C16: 0 + C18: 0)/[(0.5 X [summation]MUFA) + (0.5 X [summation]n-6 + (3 X [summation]n-3) + ([summation]n-3/[summation]n-6)], according to Ulbricht and Southgate (1991). These parameters were used to determine the nutritional value of the lipid fraction of the longissimus dorsi muscle of Santa Ines lambs.

The data were analyzed by analysis of variance, linear curve estimation, and quadratic regression equations ([alpha] = 0.05). Results were analyzed according to a completely randomized design using Statistical Analysis System (SAS, 2002). The criteria used to choose the model were the significance of the regression coefficients ([alpha] = 0.05) by the F test ([alpha] = 0.05)and the coefficient of determination ([R.sup.2], calculated as the ratio between the sum of squares of the regression and the sum of squares of treatments and biological phenomenon).

Results and discussion

The pH value of 5.6 at 24h after slaughter (final pH) was within the normal pH values for lamb meat and did not differ among treatments. Meats with pH values above 6.0 present an anomaly called DFD (dark, firm, dry). However, DFD is rarely observed in lamb meat, and, in this study, the animals were slaughtered in accordance with the animal welfare norms and thus the muscle glycogen reserves secured the right pH decline.

The inclusion of cassava wastewater decreases the cooking losses (%), shear force (kgf), and intensity of yellow while the meat fat content increases linearly (Table 2). Dhanda, Taylor and Murray (2003) pointed out that higher values of cooking losses are related to a low carcass pH, which could lead to PSE (pale, soft, exudative) meat. However, the pH in this study was within the normal range. Thus, the decrease in cooking losses might be related to other factors such as an increase in fat content. According to Lawrie and Rubensam (2005), the water retention capacity is directly related to the fat content; thus, a decrease in cooking losses is expected when the fat content increases.

The shear force, which is related to the muscular fiber resistance, decreased linearly with the increase in cassava wastewater inclusion. This might be related to the lower cooking losses observed. According to Aaslyng, Bejerholm, Ertbjerg, Bertram and Andersen (2003), a reduction of cooking losses implies juicier and tenderer meat because more water is within the fiber. However, for all treatments, the meat should be considered tender, because, according to Costa et al. (2009), meat is classified as tender when its shear force is [less than or equal to] 8 kgf [cm.sup.-2]; acceptable when shear force is between 8 and 11 kgf [cm.sup.-2]; and tough when shear force is > 11 kgf [cm.sup.-2]. Cassava wastewater inclusion increased the fat content of the meat, which is important, since the amount of fat is one of the major concerns related to slaughter age (Santos-Silva, Mendes, & Bessa, 2002).

The decrease in yellow intensity might be related to the amount and type of pigments of the fat in the carcass. Rodrigues and Andrade (2004) who compared meat from cattle and buffaloes and observed that the latter had a lower yellow intensity due to the lower amount of fat and carotenoid pigment contents in their meat. In addition, according to Dhanda et al. (2003) and Majdoub-Mathlouthi, Said, Say and Kraiem (2013), fat pigments can be influenced by the diet. High contents of carotenoids, the major pigments present in animal diets, especially in green forages, can be incorporated in fat tissues, increasing the yellowness of fat. The low amount of pigments in cassava waste water may be related to a lower ingestion of such pigments, resulting in whiter fat and decreasing the yellow intensity.

Recent research has demonstrated a diversity of results off atty acid composition in the meat; e.g., Juarez et al. (2008) concluded that the production system, associated with the breed and the diet, was the main factor explaining variations in the meat fatty acid profile. In fact, in this study, the inclusion of cassava wastewater changed the fatty acid composition of lamb meat. The amounts of myristic (14:0) (16:1n-7), stearic (18:0), and linoleic (18:2n6c) fatty acids; 20:4n-6; and total fatty acids were changed(Table 3).Among the ten fatty acids identified in the composition of lamb meat, those with highest representation were oleic (18:1n9c), palmitic (16:0), and stearic (18: 0), respectively (Table 3), similar to the reports of Barros et al. (2015).

An influence of cassava wastewater was also observed on the amounts of saturated fatty acids (SFA), polyunsaturated fatty acids (PUFA), and desirable fatty acids (DFA) (Table 3). The quantities off at ty acids were studied to assess and identify the risk factor of the food to increase the human blood cholesterol level.

The concentration of desirable fatty acids is expressed by the sum of the PUFA and stearic acid. Despite being saturated, stearic acid is considered a neutral fatty acid (Prado, 2004) because it can be converted to oleic acid in the human body, and oleic acid is known to be a reducer of cholesterol and low-density lipoproteins. Thus, cassava wastewater has the ability to increase the stearic acid content, consequently improving the nutritional quality of lamb meat.

A quadratic effect of cassava wastewater was also observed on n-6:n-3 ratio and on the nutritional indices [DELTA]9 desaturase 16, elongase, and atherogenicity, while thrombogenicity showed a linear effect (Table 3).

According to Garcia et al. (2008), the n-6:n-3 ratio can be influenced by the diets. For animals finished in the feedlot, the ratio ranges from 6.0 to 10 because the grains are rich in 18:2n-6 (Boufaied et al., 2003). These results were confirmed by this study, in which the n-6:n-3 ratio was influenced by the inclusion of cassava wastewater (quadratic effect), with values ranging from 5.92 to 9.11.

Lower atherogenicity and thrombogenicity indices lead to a greater potential to prevent coronary heart diseases. Cassava wastewater changed the atherogenicity index (quadratic effect). Thus, this effect should be better studied to elucidate the capacity of cassava wastewater to improve the fatty acid profile of lamb meat. However, Arruda et al. (2012) reported no effect of diets on nutritional quality indices of lamb meat, showing mean atherogenicity and thrombogenicity indices of 0.60 to 0.67 and 1.31 to 1.46, respectively.

The results observed in this study show that cassava wastewater has sufficient amounts of fatty acids to change the fatty acid composition of meat. However, new studies should be conducted to determine the fatty acid composition of this product. Moreover, the chemical composition of cassava wastewater has not yet been defined and neither has it been determined whether this by-product can be included in animal feed, considering its broad use as raw material in agriculture and the fact that research on animal feed is still in early stages.

Conclusion

Cassava wastewater changes the physical and chemical characteristics of lamb meat, increasing the lipid contents, reducing cooking losses and shear force, and changing the fatty acid composition and nutritional quality indices. Further studies should be carried out to determine the fatty acid composition of cassava wastewater to elucidate its use in animal nutrition.

Doi: 10.4025/actascianimsci.v39i4.35180

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Received on February 2, 2017.

Accepted on April 24, 2017.

Jose Adelson Santana Neto (1) *, Evandro Neves Muniz (2), Gladston Rafael de Arruda Santos (1), Francisco de Assis Fonseca de Macedo (1), Jose Henrique de Albuquerque Rangel (2) and Ludmila Couto Gomes (1)

(1) Departamento de Zootecnia, Universidade Federal de Sergipe, Av. Marechal Rondon, s/n, 49100-000, Sao Cristovao, Sergipe, Brazil. (2) Empresa Brasileira de Pesquisa Agropecuaria, Embrapa Tabuleiros Costeiros, Aracaju, Sergipe, Brazil. *Author for correspondence. E-mail: adelson@zootecnista.com.br
Table 1. Ingredients and chemical composition of experimental
diets.

                         Cassava wastewater (L)

Ingredient (%)           0.0    0.5    1.0    1.5

Tifton 85 hay            35.0   35.0   35.0   35.0
Corn screenings          35.0   35.0   35.0   35.0
Soybean meal             18.0   18.0   18.0   18.0
Ground corn              12.0   12.0   12.0   12.0
Cassava wastewater (L)   0.0    0.5    1.0    1.5

                         Chemical composition (%)

Ingredient (%)            DM      CP    NDF    IVDMD

Tifton 85 hay            90.0    10.8   78.6   53.0
Corn screenings          90.1    5.5    73.1   46.1
Soybean meal             89.09   50.1          80.3
Ground corn              89.02   8.9           70.8
Cassava wastewater (L)   4.34

Table 2. Physical and chemical characteristics of lambs' meat fed
with different proportions of cassava wastewater.

                     Cassava wastewater (L)      CV      P-value

                     0.0    0.5    1.0    1.5    (%)       L       Q

Cooking losses (%)   16.4   12.2   11.7   11.6   19.7    0.04     0.12
Shear force (kgf)    2.46   2.40   2.20   2.15   17.0   < 0.01    0.09
Moisture (%)         73.8   73.8   73.8   73.8   1.03    0.09     0.07
Crudeprotein (%)     21.6   21.9   22.2   21.9   6.14    0.50     0.65
Lipid (%)            0.77   0.84   0.91   0.99   22.1    0.04     0.74
Ash (%)              3.89   3.64   3.68   3.72   4.87    0.15     0.15
Lightness            38.4   38.4   37.7   37.8   37.8    0.07     0.26
  ([L.sup.*])
Redness              13.5   13.5   13.2   13.2   12.2    0.09     0.40
  ([a.sup.*])
Yellowness           8.26   7.90   7.54   7.21   16.2    0.01     0.11
  ([b.sup.*])
Chroma               15.7   15.9   14.7   15.0   11.7    0.26     0.12
  (C[*.sup.*])
Tonality             31.3   31.6   29.8   28.9   13.0    0.22     0.63
  ([h.sup.*])

Regressionequations                                     [R.sup.2]

Cookinglosses (%)    Y = 15.2-2.99x                      0.70
Shear force (kgf)    [??] = 2.47-0.23x                   0.93
Lipid (%)            [??] = 0.78 + 0.14x                 0.71
Yellowness (b*)      [??] = 8.25-0.70x                   0.99

CV: coefficient of variation. L: linear equation. Q: quadratic
equation.

Table 3. Fatty acid composition of meat from lambs fed different
proportions of cassava wastewater.

Fatty acids (g 100             Cassava wastewater(L)       CV
[g.sup.-1])
                              0.00   0.50   1.00   1.50   (%)

10:0 (capric)                 0.09   0.09   0.09   0.10   7.62
12:0 (lauric)                 0.09   0.06   0.07   0.28   34.8
14:0 (myristic)               2.16   1.78   1.77   2.04   14.0
16:0 (palmitic)               21.4   21.0   21.7   21.6   2.64
16:1n-7                       1.82   1.46   1.55   2.13   18.7
18:0(stearic)                 17.3   23.2   21.8   23.8   9.59
18:1n9c(oleic)                31.7   30.4   35.7   29.7   9.75
18:2n6c(linoleic)             4.61   6.06   4.62   4.86   7.52
18:3n3(a-linolenic)           0.78   0.67   0.47   0.63   23.8
20:4n-6                       2.02   2.77   2.84   2.38   22.3
Total fattyacids              80.6   85.2   86.1   86.7   2.12

Conjugatedlinoleicacid        0.66   0.46   0.37   0.45   31.7
n-6:n-3                       5.92   9.11   7.67   7.83   15.8

Saturated fatty acids (SFA)   41.0   46.2   43.3   47.8   5.68
Monounsaturated fatty acids   33.6   31.8   37.3   31.8   8.43
Polyunsaturated fatty acids   7.41   9.50   7.94   7.88   10.2
  (PUFA)
PUFA:SFA                      0.18   0.20   0.18   0.17   12.5
Desirable fatty acids         58.3   64.5   64.9   63.5   2.98
Nutritional quality index
[DELTA]9 desaturase 16        7.83   6.50   6.67   8.89   14.7
[DELTA]9 desaturase 18        64.7   56.7   64.4   55.2   7.08
Elongase                      67.9   70.4   70.4   69.3   1.96
Atherogenicity                0.62   0.51   0.56   0.53   2.46
Thrombogenicity               1.61   1.63   1.66   1.69   2.08
Regression equations
14:0.Myristic)                [??] = 2.16-1.05x + 0.65[chi square]
16:1n-7                       [??] = 1.92-1.19x + 0.93[chi square]
18:0 (Stearic)                [??] = 18.6 + 3.22x
18:2n6c (Linoleic)            [??] = 4.84 + 1.68x - 1.21[chi square]
20:4n-6                       [??] = 2.02 + 2.05x - 1.22[chi square]
Total fattyacids              [??] = 82.0 +3.15x
n-6:n-3                       [??] = 6.23 + 5.40x - 3.03[chi square]
Saturated fatty acids         [??] = 41.9 + 3.52x
Polyunsaturated fatty acids   [??] = 7.67 + 3.20x - 2.15[chi square]
Desirable fatty acids         [??] = 58.5 + 14.7x - 7.68[chi square]
A9desaturase 16               [??] = 7.86 - 4.67x + 3.56[chi square]
Elongase                      [??] = 68.0 + 6.31x - 3.65[chi square]
Atherogenicity                [??] = 0.61 - 0.17x + 0.09[chi square]
Thrombogenicity               [??] = 1.61 + 0.05x

Fatty acids (g 100                P-value
[g.sup.-1])
                                L        Q

10:0 (capric)                  0.22     0.12
12:0 (lauric)                  0.09     0.12
14:0 (myristic)                0.54     0.03
16:0 (palmitic)                0.32     0.40
16:1n-7                        0.18     0.01
18:0(stearic)                 > 0.01    0.40
18:1n9c(oleic)                 0.50     0.11
18:2n6c(linoleic)              0.45     0.01
18:3n3(a-linolenic)            0.08     0.10
20:4n-6                        0.37     0.04
Total fattyacids              < 0.01    0.01

Conjugatedlinoleicacid         0.06     0.08
n-6:n-3                        0.94     0.02

Saturated fatty acids (SFA)    0.01     0.78
Monounsaturated fatty acids    0.09     0.21
Polyunsaturated fatty acids    0.94     0.02
  (PUFA)
PUFA:SFA                       0.21     0.08
Desirable fatty acids         < 0.01   < 0.01
Nutritional quality index
[DELTA]9 desaturase 16         0.20     0.01
[DELTA]9 desaturase 18         0.06     0.78
Elongase                       0.20     0.02
Atherogenicity                < 0.01   < 0.01
Thrombogenicity                0.01     0.26
Regression equations
14:0.Myristic)                [r.sup.2] = 0.99
16:1n-7                       [r.sup.2] = 0.99
18:0 (Stearic)                [r.sup.2] = 0.46
18:2n6c (Linoleic)            [r.sup.2] = 0.27
20:4n-6                       [r.sup.2] = 0.99
Total fattyacids              [r.sup.2] = 0.64
n-6:n-3                       [r.sup.2] = 0.62
Saturated fatty acids         [r.sup.2] = 0.56
Polyunsaturated fatty acids   [r.sup.2] = 0.46
Desirable fatty acids         [r.sup.2] = 0.97
A9desaturase 16               [r.sup.2] = 0.99
Elongase                      [r.sup.2] = 0.97
Atherogenicity                [r.sup.2] = 0.54
Thrombogenicity               [r.sup.2] = 0.68

CV: coefficient of variation; L: linear equation;
Q: quadratic equation.
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Author:Neto, Jose Adelson Santana; Muniz, Evandro Neves; Santos, Gladston Rafael de Arruda; de Macedo, Fran
Publication:Acta Scientiarum. Animal Sciences (UEM)
Date:Oct 1, 2017
Words:5309
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