COMPARATIVE ANALYSIS OF NITROGEN-TO-PROTEIN CONVERSION FACTORS FOR DETERMINING NET PROTEIN CONTENT IN SIX SUPERFOODS

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February – March 2020, vol. 9, no. 4
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Article type: Food Sciences of Food Sciences
DOI: 10.15414/jmbfs.2020.9.4.856-860
Abstract: The true protein content of plant foods is best assessed directly by analyzing amino acids quantitatively or indirectly by using a nitrogen-to-protein conversion factor (NPCF) that is computed based on sums of amino acids. The practical way of determining protein in plant foods is by multiplying its total nitrogen (TN) value with a reliable plant-specific NPCF. In this study, three kinds of NPCFs were evaluated for measuring the net-protein content of chia, rye, quinoa, spelt, flax, and hemp. A universal factor of 6.25 was considered NPCF1, while NPCF2s and NPCF3s were based on the sum of amino acids with amide-nitrogen and computed quantities of Asn and Gln using a ratio method, respectively. The TN was minimal in rye (1.34% w/w) and maximal in flax (5.57% w/w). The values of NPCF2 ranged from 5.18 – 5.90 and from 5.45 - 6.22 for NPCF3. The net protein values obtained by NPCF2 were close to the values of direct quantitative analysis of amino acids as compared to other NPCFs. The use of computed Gln and Asn quantities incorrectly increased the amount of available nitrogen in the amino acids, especially in spelt, flax, and hemp; it was about 4% higher than the corresponding TN values, suggesting that the use of the computed method is not appropriate for these plants. NPCF1 overestimated the protein content in all the samples. The degree of overestimation is likely due to the inclusion of non-protein nitrogen in the calculation, which ranged from 5% - 22% in the samples tested.
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COMPARATIVE ANALYSIS OF NITROGEN-TO-PROTEIN CONVERSION FACTORS FOR DETERMINING NET PROTEIN CONTENT IN SIX SUPERFOODS


AUTHORS

Vennela Gosukonda, Hari Singh, Ramana Gosukonda

ABSTRACT

The true protein content of plant foods is best assessed directly by analyzing amino acids quantitatively or indirectly by using a nitrogen-to-protein conversion factor (NPCF) that is computed based on sums of amino acids. The practical way of determining protein in plant foods is by multiplying its total nitrogen (TN) value with a reliable plant-specific NPCF. In this study, three kinds of NPCFs were evaluated for measuring the net-protein content of chia, rye, quinoa, spelt, flax, and hemp. A universal factor of 6.25 was considered NPCF1, while NPCF2s and NPCF3s were based on the sum of amino acids with amide-nitrogen and computed quantities of Asn and Gln using a ratio method, respectively. The TN was minimal in rye (1.34% w/w) and maximal in flax (5.57% w/w). The values of NPCF2 ranged from 5.18 – 5.90 and from 5.45 - 6.22 for NPCF3. The net protein values obtained by NPCF2 were close to the values of direct quantitative analysis of amino acids as compared to other NPCFs. The use of computed Gln and Asn quantities incorrectly increased the amount of available nitrogen in the amino acids, especially in spelt, flax, and hemp; it was about 4% higher than the corresponding TN values, suggesting that the use of the computed method is not appropriate for these plants. NPCF1 overestimated the protein content in all the samples. The degree of overestimation is likely due to the inclusion of non-protein nitrogen in the calculation, which ranged from 5% - 22% in the samples tested.


KEYWORDS

Amino acids, nitrogen-to-protein conversion factor, superfoods, net protein, non-protein nitrogen

INTRODUCTION

Cereal protein is an important component in both animal feed and human diets, constituting approximately 16 to 45 grams per capita per day (Hackler, 1985). It represents 70% of the total dietary protein in some areas of the world, thus underscoring the need for an accurate knowledge of the protein concentration of cereals.  Lately, seeds of chia (Salvia hispanica), rye (Secale cereale), quinoa (Chenopodium quinoa), spelt (Triticum spelta), flax (Linum usitatissimum), and hemp (Cannabis sativa) have gained the status of superfoods and are often used as dietary supplements as a rich source of energy, fiber, high quality protein, macro-and-micronutrients, and other bioactive compounds (Friedman, 1996; Multari et al., 2016; Pihlanto et al., 2017).  Consumption of plant-based protein is healthier than that of animal protein, as intake of high amounts of animal protein has been linked to an increased risk of type II diabetes, cardiovascular disease, colorectal cancer, and early death (Chan et al., 2011; Pedersen et al., 2013), whereas consumption of superfoods has been linked to greater health benefits. However, there are still gaps and inconsistencies in basic knowledge about the true protein content of these superfoods; thus, it is imperative to gain a deeper understanding of protein quantity and quality in superfoods.

Traditionally, the quantification of proteins in foods is based on the total nitrogen (TN) content being multiplied by a 6.25 nitrogen-to-protein conversion factor (NPCF), as it was assumed that protein contains approximately 16% nitrogen (100/16 = 6.25) (Jones, 1931).  This technique assumes that all nitrogen originates from protein, even though nitrogen exists in non-protein nitrogen (NPN) compounds such as nitrates, nitrites, chlorophyll, nucleic acids, and free amino acids (Lourenco et al., 1998).  Furthermore, depending on the source, the composition of amino acids varies in foods and the nitrogen content of specific amino acids also varies according to the molecular weight and the number of nitrogen atoms it contains. Consequently, when the single conversion factor is applied for all protein sources, significant errors are introduced in protein estimation. Specifically, the application of a single factor to foods that are rich in NPN compounds (foods made of leaves or fruits) will result in an overestimation of the protein content (Milton and Dintzis, 1981; Sedinger, 1984; Izhaki, 1993; Levey et al., 2000).

The Food and Nutrition Board (1989) recommended that net protein (NP) be determined as the total amount of 20 bound and free amino acids.  The advantage of this approach is that it eliminates the problems associated with the use of the single NPCF 6.25, as it does not require the NPN content of the food or its relative proportions of specific amino acids (Magomya et al., 2014).  Food-specific NPCFs have been determined for plants (Tkachuk, 1969), edible insects (Janssen et al., 2017), animal feeds (Boisen et al., 2000), and processed dietary foods (Salo-Vaananen and Kovistoinen, 1996). The results of these studies have demonstrated that the food-specific NPCFs were much lower (ranging from 3.24 to 5.51) than the traditionally used factor of 6.25.

The true nature of NPCF is the ratio of actual seed protein to total nitrogen recovered from 20 protein forming anhydrous amino acids (NAAA) (Mosse, 1990).  Because the amino acids Asparagine (Asn) and Glutamine (Gln) are often hydrolyzed during the chemical process, it is recommended that the amide-nitrogen of Gln and Asn be determined separately and be included in the calculation of the NPCF.  However, Ibegbulem et al. (2013) used the ratios of 5.3/4.3 for Asp (Aspartic acid) to Asn, and 6.3/4.2 for Glu (Glutamic acid) to Gln, respectively, for estimating the likely amounts of Gln and Asn in a given amino acid profile. These ratios were based on the observation that the amino acids Asp, Asn, Glu, and Gln have average percentage occurrences of 5.3, 4.3, 6.3, and 4.2, respectively, in 1150 proteins of known amino acid sequences (Nelson and Cox, 2008).

Since the value of the NPCF may vary with the concentration of nitrogen in grains, this study investigated 1) the amount of nitrogen recovered from anhydrous amino acids (NAAA) that included either amide-nitrogen or nitrogen from the computed quantities of Asn and Gln using a ratio method, 2) the universal factor of 6.25 (NPCF1) along with the plant-specific NPCFs based on NAAA with amide-nitrogen (NPCF2) or nitrogen from the computed Asn and Gln (NPCF3), for reliably estimating the NP content in six superfoods, and 3) net protein amounts obtained from TN x NPCF1 (NP1), TN x NPCF2 (NP2), and TN x NPCF3 (NP3).

MATERIALs AND METHODS

Preparation of plant samples

Seeds of six superfoods, Salvia hispanica (chia), Secale cereale (rye), Chenopodium quinoa (quinoa), Triticum spelta (spelt), Linum usitatissimum (flax), and Cannabis sativa (hemp) were commercially obtained. These seeds were ground using an electric grinder (Cyclotec 1093 Sample Mill) and the samples were then stored in tightly sealed containers prior to analysis.

Determination of TN and net protein (NP1) using NPCF1

Total nitrogen (TN) content (% w/w) was measured via the combustion and Kjeldahl methods. Combustion was carried out by following AOAC Official Method 990.03 (2006) using a LECO TrueSpec C/N Analyzer, whereas the Kjeldahl method was performed according to AOAC 984.13 (A-D) (2006).  Results from the Kjeldahl method were used for the analysis as there was no difference in the amount of nitrogen produced by these two methods. The measured nitrogen values were then converted into % dry weight basis (w/w). To estimate NP1 from each sample, TN content was multiplied by NPCF1 (6.25).

Quantification of amino acids and crude protein (CP) in samples

Amino acid profiles for each sample were obtained according to AOAC Official Method 982.30 E (a,b,c), chp. 45.3.05, (2006) using ion-exchange chromatography (Hitachi Amino Acid Analyzer, Model L-8900).  However, this method could only quantify 18 out of the total 20 protein forming amino acids, as Asn and Gln were hydrolyzed during the process of chemical reaction.  The crude protein values were calculated as a sum of 18 protein-forming amino acids in each sample and were referred to as CP1 in this study. Furthermore, the likely amounts of Asn and Gln were estimated using the ratios of 5.3/4.3 for Asp to Asn, respectively, and 6.3/4.2 for Glu to Gln, respectively (Ibegbulem et al., 2013).  The crude protein values calculated with the computed amounts of Asn and Gln, along with all other protein forming amino acids, were referred to as CP2.

Determination of plant specific NPCFs for net protein (NP2 and NP3)

The total nitrogen from all amino acid residues (NAAA) was calculated by summing the quantities of nitrogen contributed by each amino acid, including that of amide-nitrogen (% w/w).  A residue is an anhydrous amino acid (AAA) that has the molecular weight of its own minus the molecular weight of H2O (i.e., 18g in 1M of each amino acid).  Amide-nitrogen was determined as percent ammonia (w/w) released via acid hydrolysis of ground samples for two hours with 3N hydrochloric acid (Mosse, 1990).  The released ammonia values (% w/w) were multiplied by 14/17 (atomic mass of nitrogen/atomic weight of nitrogen) in order to obtain the amide-nitrogen quantities. In addition, nitrogen from the computed amounts of Asn and Gln, instead of that from amide-nitrogen, was included in the calculation of NAAA and the effect on NPCFs was evaluated.

The upper (kA) and lower (kP) limits of the NPCF were calculated according to Mosse (1990). The upper limit (KA = ∑ Ei / ∑ Di) is defined as the ratio of actual seed proteins (that is total amino acid residue weight) to total nitrogen recovered from the amino acids and amide nitrogen (or nitrogen from predicted Asn or Gln values), where: Ei is the grams of the ith amino acid residue per 100 grams of sample, dry weight basis, and Di is the grams nitrogen of the ith amino acid per 100 grams of sample, dry weight basis.  The lower limit (KP = ∑ Ei / TN) is defined as the ratio of actual seed proteins to TN content in 100 grams of dry seed matter (TN was determined by Kjeldahl method), where: Ei is the grams of the ith amino acid per 100 grams of sample, dry weight basis, and TN is the grams of nitrogen per 100 grams of dry weight.

An appropriate NPCF for each sample was produced by taking the average of the upper and lower limits (NPCF = average (kA, kP)).  However, published reports suggest that the appropriate value for NPCF could vary as a function of nitrogen with possible deviations that plausibly do not exceed ± (kA – kP)/4.  Therefore, the maximum plausible error (k1) was calculated as k1 = (kA, kP)/2 + (kA, kP)/4, and the minimum plausible error (k2) was calculated as k2 = (kA, kP)/2 – (kA, kP)/4.  Two sets of plant specific factors were calculated: 1) NPCF2, which was based on NAAA with amide-nitrogen being included, and 2) NPCF3, which was based on NAAA that included nitrogen from the computed values of Asn and Gln amino acids.  Consequently, two sets of net protein values, NP2 and NP3, were obtained for each sample by multiplying its TN with NPCF2 and NPCF3, respectively.

RESULTS AND DISCUSSION

Table 1 shows the composition of various amino acids (grams of amino acid per 100 grams of dry sample) and crude protein based on the sum of the amino acids in each of the six superfoods.  The results indicate that the amounts of CP2 were, on average, 17.39% ± 1.51(mean ± SD) higher than those of CP1 due to the inclusion of Asn and Gln in CP2 (Table 1).  In general, CP1 was the highest in flax (38.78), followed by hemp (35.80) and chia (21.91). The lowest CP1 values were obtained in rye (9.13), followed by quinoa (13.48).  Amino acid analysis also indicated the presence of non-proteinogenic amino acids, such as taurine, lanthionine, and ornithine at lower levels (data not shown).

Amino acid profiles of flax and hemp were similar with the exception that flax had a higher concentration of glycine (2.08 % w/w) as compared to hemp (1.31 % w/w).  The bulk of CP2 in flax (56.00%) and hemp (56.48%) was constituted by the amino acids Asp, Asn, Glu, Gln, Leu, and Arg, whereas Glu and Gln dominated the amino acid profiles of chia, rye, quinoa, and spelt. The amino acid compositions obtained in this study for chia, rye, and quinoa were consistent with the values from published literature (FAO, 1981; Fujihara et al., 2008; Nitrayova et al., 2014).

In general, the amount of amide-nitrogen (%) that was retrieved from each sample was very small. While flax and hemp yielded the maximum amounts of % amide nitrogen (0.0238 and 0.03304, respectively), there was little variance among other samples.  In contrast, the nitrogen content (%) calculated from the computed Asn and Gln values of flax and hemp, was 1.37 and 1.17, respectively.  The variations in the amino acid composition and the choice of methods for obtaining nitrogen from Asn and Gln affected the available nitrogen and the subsequent calculations of the NPCFs in the six superfoods.

The results in Table 2 indicate that the average TN content per 100 grams of dry sample was 3.34 ± 1.84 grams among the six superfoods and ranged from 1.34 grams in rye to 5.57 grams in flax.  Inclusion of nitrogen from computed amounts of Asn and Gln instead of amide-nitrogen in the amino acid profiles increased 1) the total nitrogen recovery from amino acids by 22.91 ± 2. 81 %, and 2) the NPCF3 values, derived as the average of kA and kP, by 5.24 ± 0. 42 %, but decreased the variance between the values of kA and kP, and k1 and k2.  The reason could be that these values vary as a function of nitrogen, and the observed difference between NAAA and that of its TN obtained from a dry sample (Fig. 1 and Fig. 2) was negligible.  Because the amount of nitrogen recovered from amide was much smaller than the amount recovered from computed Asn and Gln, the NPCF2s obtained for the six superfoods were also lower as compared to the NPCF3s.  The plant-specific NPCFs obtained in this study were lower than that of traditionally used NPCF1 (6.25).  The results of this study corroborate the findings of Mosse (1990) that the NCPF for a given cereal grain or oil seed may not necessarily be an inverse of nitrogen percentages of total proteins.  For instance, low nitrogen content of rye (NAAA = 0.98%) resulted in the NPCF2 value of 5.65, while high nitrogen content of hemp (NAAA = 4.51%) produced an NPCF2 of 5.21.  In contrast, the low nitrogen content of quinoa (NAAA = 1.65 %) resulted in a low NPCF2 (5.18) for this plant.  The value of the NPCFs varied with the concentration of nitrogen in the grains; in general, the greater the difference between kA and kP values, the higher the NPCF values.  Similarly, in the study by Mosse (1990), the true NPCF for rice grains ranged from 5.1 (low nitrogen containing rice) to 6.0 (high nitrogen containing rice), whereas the NPCFs for barley, soybean, and sorghum were not affected significantly by the nitrogen content of grains.  The values of NPCF2 for quinoa were very close to the values reported by Fujihora et. al. (2008) for the same plant; however, the values of NPCF were higher for rye when compared to the values of NPCF2 of the current study. Also, the TN value reported for rye was higher (1.63%) than that of the TN value (1.34%) obtained in this study.

Table 1 Amino acid composition (grams/100 grams of protein) and amide-nitrogen (%) of six superfoods

Amino acid Chia Rye Quinoa Spelt Flax Hemp
Alanine (Ala) 0.93 0.36 0.56 0.43 1.54 1.27
Arginine (Arg) 1.96 0.37 1.12 0.55 3.20 4.19
Aspartic acid (Asp) 1.64 0.62 1.10 0.63 3.23 3.16
Cysteine (Cys) 0.44 0.21 0.22 0.31 0.61 0.53
Glutamic acid (Glu) 3.04 1.75 1.86 3.56 6.41 4.94
Glycine (Gly) 0.91 0.36 0.67 0.49 2.08 1.31
Histidine (His) 0.53 0.18 0.38 0.29 0.72 0.90
Isoleucine (Ile) 0.75 0.29 0.53 0.46 1.50 1.32
Leucine (Leu) 1.28 0.50 0.85 0.85 1.99 2.08
Lysine (Lys) 1.10 0.34 0.76 0.37 1.36 1.21
Methionine (Met) 0.59 0.14 0.26 0.22 0.61 0.75
Phenylalanine (Phe) 1.01 0.35 0.54 0.58 1.64 1.46
Proline (Pro) 0.71 0.65 0.46 1.17 1.24 1.16
Serine (Ser) 0.93 0.32 0.51 0.50 1.38 1.45
Threonine (Thr) 0.72 0.28 0.47 0.36 1.28 1.11
Tryptophan (Try) 0.19 0.07 0.12 0.12 0.46 0.27
Tyrosine (Tyr) 0.63 0.14 0.34 0.31 0.89 1.23
Valine (Val) 0.95 0.39 0.60 0.55 1.75 1.61
Crude Protein 1 (CP1)

(total amino acids)

18.31 7.44 11.35 11.75 31.89 29.95
Asparagine (Asn)* 1.33 0.50 0.89 0.51 2.62 2.56
Glutamine (Gln)* 2.27 1.19 1.24 2.37 4.27 3.29
Crude Protein 2 (CP2) (CP1+Asn+Gln) 21.91 9.13 13.48 14.63 38.78 35.80
Amide-nitrogen (% w/w) 0.00224 0.00112 0.00306 0.00374 0.0238 0.03304

  *Asn and Gln contents were computed using the ratios of 5.3/ 4.3 for Asp and Asn, and 6.3/4.2 for Glu and Gln, respectively.

Table 2 Nitrogen-to-protein conversion factors (NPCF) of each superfood based on amino acid composition and total nitrogen content.

Plant Total nitrogen (% w/w) in sample (TN) Total AAA (%) in sample (Ei) Total nitrogen (%) in AAA (Di) kA

(∑ Ei / ∑ Di)

kP

(∑ Ei / TN)

k1 k2 NPCF (Average of kA & kP)
Chia 3.39 15.76 2.66 5.94 4.65 5.62 4.97 5.30*
18.92 3.37 5.61 5.58 5.60 5.59 5.59**
Rye 1.34 6.39 0.98 6.54 4.77 6.09 5.21 5.65*
7.87 1.31 6.0 5.87 5.97 5.90 5.93**
Quinoa 2.19 9.77 1.65 5.91 4.46 5.54 4.82 5.18*
11.62 2.07 5.59 5.31 5.52 5.38 5.45**
Spelt 2.01 10.12 1.50 6.76 5.04 6.33 5.47 5.90*
12.64 2.06 6.14 6.29 6.18 6.25 6.22**
Flax 5.57 27.43 4.55 6.03 4.93 5.75 5.20 5.48*
33.44 5.92 5.65 6.00 5.73 5.91 5.82**
Hemp 5.53 25.88 4.51 5.74 4.68 5.47 4.94 5.21*
30.97 5.68 5.45 5.60 5.49 5.56 5.52**

AAA = Anhydrous Amino Acid, kA = NPCF’s maximum upper limit, kP = NPCF’s minimum lower limit, k1 = NPCF’s plausible upper limit, k2 = NPCF’s plausible lower limit, NPCF was estimated as the average of kA and kP. *NPCF2 and **NPCF3

The results in Fig. 1 show that the average non-protein nitrogen (NPN) levels among the six superfoods were 13.26% ± 5.32% after NAAA (amide-nitrogen being included) amounts were subtracted from TN of the corresponding samples.  The average NPN value was more than the 7% reported in cereals by Fujihara et al. (2008).  Furthermore, the 5% NPN obtained in flax (amide-nitrogen included) in the current study was much lower than the 21.7% NPN reported by Singh et. al. (2011) for the same cereal.  However, when NAAA (including nitrogen from computed values of Asn and Gln) was subtracted from TN, low to negative levels of NPN were obtained (Fig. 2).  In the cases of spelt, flax, and hemp, negative NPN values were observed because their NAAA levels were 4% higher on average than their TN values (Fig. 2).  This suggested that the use of ratios for estimating amounts of Asn and Gln is not appropriate in measuring net protein in six superfoods, as the ratios accounted for higher amounts of Asn and Gln than is normally available in these plants.

Figure 1 Non-protein nitrogen (NPN) levels (% w/w) in six superfoods. NPN represents the difference between the TN obtained from 100 grams of dry sample and the nitrogen recovered from its NAAA (including amide-nitrogen).

Figure 2 Non-protein nitrogen (NPN) levels (% w/w) in six superfoods. NPN represents the difference between the TN obtained from 100 grams of dry sample and the nitrogen recovered from NAAA (including nitrogen from the computed quantities of Asn and Gln).

Table 3 indicates that the protein content varies with the source of plant material, as it was the highest in flax and the lowest in rye.  The contents of NP1 were higher than those of NP2 in all superfoods, which ranged from 8.38% in rye to 34.57% in flax (Table 3).  The reason for such high values could be the use of the universal factor of 6.25 in the estimation of NP1 values.  On average, NP3 (TN x NPCF3) values were 5.24 ± 0.42% greater than NP2 (TN x NPCF2) values of a given plant (Fig. 3).  This observed difference in net protein levels of NP3 and NP2 corresponds to the average difference of 5.24 ± 0.42% between NPCF3 and NPCF2 (Table 2).  Similarly, CP1 levels were lower (17.40% ±1.51%) than the CP2 levels, which included additional Asn and Gln amino acids.  An array of protein values reported by published literature for each of the six superfoods (Dvoracek et al., 2002; Singh et. al., 2011; Nitrayova et al., 2014; Russo and Reggiani, 2015; Shen et al., 2018) was higher compared to CP1, CP2, NP1, NP2, or NP3 amounts obtained in this study (Table 3).

Table 3 Comparison of protein values from literature, crude protein, and net protein in six superfoods.

Plant sample Protein based on literature Crude Protein (sum of AA) Net Protein
CP1 CP2 NP1

(TN x NPCF1)

NP2

(TN x NPCF2)

NP3

(TN x NPCF3)

Chia 19 – 26% 18.31 21.91 21.19 17.97 18.95
Rye 10-14% 7.44 9.13 8.38 7.57 7.95
Quinoa 13 -16% 11.35 13.48 13.69 11.34 11.94
Spelt 13 -15% 11.75 14.63 12.57 11.86 12.50
Flax 20 -25% 31.91 38.78 34.81 30.52 32.42
Hemp 23 -35% 29.98 35.8 34.56 28.81 30.53

AA =Amino acids; CP1 is without Asn and Gln; CP2 is with Asn and Gln; NPCF1 value is 6.25.

Figure 3 Net protein content and percent protein differences between NP3 and NP2 among six superfoods.

In general, the summation of amino acid residues best represented the true protein content in a sample.  Though the values of NP2 in this study were comparable to those of CP1 values (Table 3), they were slightly higher than the sum of AAA values (Table 2) in each sample.  The differences could be due to the presence of NPN in significant amounts in these cereal grains (except flax) which may have slightly impacted the calculation of protein.  Otherwise, the net protein (NP2) obtained by NPCF2 in each sample would have been in good agreement with the sum of amino acid residues.  Furthermore, these results suggest that the use of amide nitrogen is more appropriate than the use of computed values of Asn and Gln in the determination of NPCFs.

Finding a perfectly accurate NPCF for reliably estimating the true protein content of a plant food is not possible as it is affected by the plant’s genotype, geographical location, and amino acid composition, as well the presence of NPN (%) in its total nitrogen (Misra, 2001).  Furthermore, it is a known fact that analytical procedures cannot accomplish 100% recovery of amino acids from a given sample (Fujihora et al., 2008).  Therefore, each NPCF varies from the average ratio of its kA and kP values.  In particular, the adjusted NPCFs may provide a better estimate of the protein content of plant foods that contains significant levels of non-protein nitrogen (Mosse, 1990).

CONCLUSION

In conclusion, the true protein values of these six superfoods should be based on the direct quantitative analysis of amino acids or indirect calculation of the NPCFs with a prerequisite that NPCFs be computed using sums of amino acids, including amide nitrogen.  The use of the ratio method for computing the amounts of Asn and Gln and subsequently using these values in the calculation of NPCF is not advisable as it may incorrectly estimate the amounts of Asn and Gln amino acids and their nitrogen content, resulting in an unreliable NPCF.  The use of the universal NPCF of 6.25 is not reliable either as it overestimates the true protein content in cereal grains.

Acknowledgment: This work was supported by the 1890 Capacity Building Grants [grant no. 2015-38821-24363/project accession no. 1007423] from the USDA National Institute of Food and Agriculture.

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