Characterization of Amino Acid Composition, Nutritional Value, and Taste of Fruits from Different <i>Actinidia arguta</i> Resources

He, Yanli; Qin, Hongyan; Wen, Jinli; Wang, Lin; Cao, Weiyu; Fan, Shutian; Lu, Wenpeng; Li, Jiaqi; Li, Changyu

doi:https://doi.org/10.1155/2024/1005194

Journal of Food Quality

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Abstract Introduction Materials and Methods Results and Discussion Conclusion Data Availability Conflicts of Interest Acknowledgments References Copyright Related Articles

Research Article | Open Access

Volume 2024 | Article ID 1005194 | https://doi.org/10.1155/2024/1005194

Characterization of Amino Acid Composition, Nutritional Value, and Taste of Fruits from Different Actinidia arguta Resources

Yanli He,¹Hongyan Qin,¹Jinli Wen,¹Lin Wang,²Weiyu Cao,¹Shutian Fan,¹Wenpeng Lu,¹Jiaqi Li,¹and Changyu Li¹

Academic Editor: Sultan Zahiruddin

Received10 Jul 2023

Revised27 Dec 2023

Accepted02 Feb 2024

Published29 Feb 2024

Abstract

The nutritional value and flavor and texture characteristics of fruits from different Actinidia argute resources were scientifically evaluated and compared. Using 35 A. arguta fruits as materials, the amino acid composition and content were determined by an automatic amino acid analyzer, and differentiation analysis, amino acid nutritional value evaluation, TAV flavor analysis, correlation analysis, PCA comprehensive evaluation, and cluster analysis were conducted to clarify the diversity of A. arguta resources in terms of amino acid content, composition, and flavor characteristics. Analysis of differential results showed that the A. arguta resource fruits contained 17 amino acids with a total amino acid content of 384.20∼2590.56 mg/100 g. The results of the nutritional value evaluation showed that the Leu of the fruits of the A. arguta resources all conformed to the ideal model proposed by FAO/WHO, and the Leu content of all the resources exceeded the human body’s needs, and it was also found that the first limiting amino acid of the Actinidia argute resources was Ile and the second limiting amino acid was Lys. TAV of the flavor-presenting amino acids was calculated to evaluate the flavor-presenting taste characteristics, and the amino acids that influenced the flavor of A. arguta fruit were Glu and Cys. PCA showed that the 2 principal components could better reflect the comprehensive information of amino acids in A. arguta, and the cumulative variance contribution rate was 87.88%, which could represent the main trend of amino acids in A. arguta. A comprehensive amino acid evaluation model was established, and the composite scores indicated that the top 5 excellent resources were S4, S10, S18, S25, and S30. Hierarchical cluster analysis classified the 35 A. arguta resources into 4 categories, which better reflected the differences in amino acid content and composition, nutritional value, and taste characteristics among A. arguta fruits from different collection sites.

1. Introduction

The Actinidia argute ((Sieb. & Zucc) Planch. ex Miq.) belongs to the kiwifruit family (Actinidiaceae Gilg & Werderm.), the kiwifruit genus (Actinidia Lindl), alias soft jujube, kiwifruit, and kiwifruit pear, which is a large deciduous vine [1, 2]. Its wild germplasm resources are mainly distributed in China, Japan, the Korean Peninsula, and the Russian Far East [3, 4], and in China, it is distributed in the northeast, north, and northwest of China in the Yangtze River Basin as well as in Taiwan [5, 6]. Its fruits are crisp, juicy, and tasty when eaten fresh and are rich in nutrients such as vitamin C, protein, amino acids, minerals, and dietary fiber [2, 7]. In addition to this, it is also of extremely high medicinal value, and its fruits are rich in active ingredients such as polysaccharides, polyphenols, alkaloids, volatile oils, and proanthocyanidins [8], which are antitumor, antiradiation, antioxidant, antiaging, hypoglycemic, anti-inflammatory, insomnia inhibitor, immunity enhancement, laxative, and other effects [9–12]. Wojdylo and Nowicka [13] found that A. arguta polyphenolic compounds could play a role in the treatment of diabetes after an in vitro antidiabetic experimental study. Xu [14] et al. found that A. arguta can significantly improve the constipation caused by montelukast in mice and increase the amount of food intake and the number of defecation, with a laxative effect. Nowadays, A. arguta is loved by the public and welcomed by the market because of its rich nutritional and medicinal value, and its fruit is often used to make processed foods such as dried fruit, dried fruit, fruit wine, fruit jam, canned food, fruit juice, fruit vinegar, or pectin oral liquid [15].

Amino acids, as an important compound in the body, are mainly involved in protein synthesis, metabolism, and immune response. In addition, it is an important bioactive component that can be used as a pharmacological component to regulate various physiological activities, and it has been shown that amino acids not only have a role in cancer metabolism but also have important roles such as redox balance, energy regulation, and homeostasis maintenance [16], and even preventive and therapeutic functions, and they can also act in coordination with hormones and play an important role in the control of gene expression [17–20]. For example, alanine, aspartate, and glutamate play a variety of roles as the main substrates for glucose synthesis in the liver, influencing the immune function in humans and animals [21]. Proline is an essential component of collagen and extracellular matrix and plays an important role in gene expression, cellular signaling, cellular redox, synthesis of polyamines, glutamate, and collagen [22], and it plays an important role in the regulation of dehydration stress, redox, and cell proliferation [23]. Glycine is a potent antioxidant that scavenges free radicals required for leukocyte proliferation and antioxidant activity, reducing inflammatory responses and pathogens in animals [24]. Amino acids often exist in two forms in plants: one is in the form of a bound state in peptides and proteins; the other is in the form of a free state [25], which can help plants to form organs and a variety of active substances during the growth process [26]. At the same time, plant amino acid crops, components of plant-based proteins, are an important source of dietary protein for humans and are recognized as a continuous source of nutrients to meet human needs, and the intake of plant-based proteins has potential benefits for the health of the human organism in terms of lowering the risk of chronic diseases, reducing deaths due to disease, and increasing the intake of plant proteins may also slow down unhealthy aging. Among them, free amino acids can be directly absorbed by the human body, and their content and composition can not only reflect the nutritional value of food, which is an important indicator for evaluating the nutritional value of food; they also have a close relationship with the flavor quality of food [27, 28]. At present, there have been some studies on the amino acids of A. arguta fruits, but they are mainly focused on their contents and components [29, 30], and there are almost no reports on the evaluation of their nutritional value and flavor characteristics; at the same time, there is a lack of systematic and rigorous statistical and comprehensive evaluation of amino acids of A. arguta resource fruits. Therefore, in-depth research on the types and contents of amino acids and their nutritional value of A. arguta resources is not only of great significance to the systematic and comprehensive evaluation of A. arguta resources but also of theoretical significance to the development of functional products that are beneficial to human health.

At present, for the analysis of fruit amino acid detection and analysis of commonly used methods are ninhydrin colorimetric method, HPLC, GC, GC-MS, near-infrared spectroscopy, amino acid analyzer, and electrochemical analysis [31–36]. The amino acid analyzer is a fully automated special analytical instrument for amino acid separation, derivatization, and detection, using cations in the exchange column separation, postcolumn ninhydrin derivatization, and diode photometer detection, with the ability to be able to be equipped in the general laboratory, good selectivity, specificity, high sensitivity, easy to operate, separation and reproducibility of the better, simple sample pretreatment, and the ability to carry out the advantages of batch testing [37–39]. Methodology for statistical analysis of data such as principal PCA modeling, TAV, and HCA is commonly used when testing and analyzing fruit amino acids using an amino acid analyzer. PCA is based on the principle of KL transformation, and through the way of dimensionality reduction, multiple variables are simplified into a few composite variables, so that the existing few composite variables can directly reflect the information of the original variables [40]. TAV can be used to assess the contribution of individual components to the flavor, and compounds with a TAV value greater than 1 can be regarded as components that contribute significantly to the overall flavor [41, 42]. HCA is the process of calculating the similarity between samples by means of criteria that have been determined, simplifying and combining them by means of the degree of correlation, and dividing the similar analyzed samples into different groups for a comprehensive evaluation based on their respective characteristics [43]. Currently, amino acid analyzer testing combined with PCA, TAV, and HCA multiple regression analysis has been widely used for amino acid testing and comprehensive evaluation of food quality [27, 44–47]. Jian [48] et al. used PCA to analyze the hydrolyzed amino acids and free amino acids of five edible mushroom powders and established a comprehensive evaluation model, and the comprehensive evaluation found that the comprehensive amino acid quality of the edible mushroom powder of tea tree mushroom was the best. Lin [49] et al. used PCA and HCA to analyze the free amino acids of the fruits of 15 hybrid citrus varieties, and the results showed that the results of the two analytical methods were basically the same and could better reflect the variability of amino acid fractions among varieties.

Amino acid analyzer assay combined with PCA, TAV, and HCA multiple regression analysis has rarely been reported in the detection and evaluation of amino acids in A. arguta resource fruits. Therefore, in this study, the amino acid analyzer was used to isolate and detect the amino acids of 35 different A. arguta resource fruits, to analyze the differences in their contents, to evaluate the changes in their nutritional value by using the amino acid ratio coefficient method, and to analyze and comprehensively evaluate the amino acid quality indexes by using the taste activity value (TAV), correlation analysis, PCA, and HCA, to compare the differences between the different resources in the nutrient composition and taste characteristics of the fruits. The results of the study provide a scientific basis for revealing the nutritional value and taste characteristics of A. arguta, a theoretical reference for the screening of excellent A. arguta resources and product development and utilization.

2. Materials and Methods

2.1. Materials and Reagents

2.1.1. Materials

The 35 resources selected for this study were harvested in September 2022 at the fruit ripening stage from the National Forest Germplasm Resource Bank of A. arguta and Schisandra chinensis. About 300 g of fruit was picked from each resource, and the samples were placed in separate corresponding sampling bags and transported back to the laboratory in an insulated box. After testing the relevant indexes on the same day, the remaining part of the sample was frozen and ground into powder with liquid nitrogen and then stored at −80°C in ultralow temperature for amino acid testing.

2.1.2. Reagents

The reagents are hydrochloric acid, phenol, and sodium citrate analytical purity (Shanghai, Sinopharm Chemical Reagent Co., Ltd.), sodium hydroxide and sodium chloride superior purity (Beijing, Beijing Beihua Fine Chemicals Co., Ltd.), and 17 kinds of L-amino acid mixed standards (Wako, Japan).

2.2. Instruments and Equipment

Instruments and equipment are as follows: DFT-50A 50 g portable high-speed pulverizer (Wenling Linda Machinery Co., Ltd.); L-8900 amino acid auto-analyzer (Hitachi, Japan); MS204S electronic analytical balance (Mettler Toledo, Switzerland); DZF6090 vacuum drying oven (Shanghai Pudong Rongfeng Scientific Instrument Co., Ltd.); DHG-9240A temperature drying oven (Shanghai Yihang Science & Technology Co., Ltd.); Milli-Q Advantage A1 ultrapure water apparatus (Millipore Corporation, U.S.A.).

2.3. Methodology

2.3.1. Chromatographic Detection Conditions

Column is 4.6 mm × 60 mm ion exchange column; flow rate is 0.40 mL/min (pump1) and 0.35 mL/min (pump2); detection wavelengths are 570 nm and 440 nm; column temperature is 135°C; injection volume is 20 μL, mobile phase eluted according to the gradient table (Table 1), and analysis time is 40.2 min.

2.3.2. Amino Acid Assay of A. arguta Samples

Refer to GB/T 5009.124-2016 [50]. Accurately weighed 2.50 g of A. arguta sample, added 20 mL of hydrochloric acid solution with a concentration of 6 mol/L, and hydrolyzed in a constant temperature oven at 110°C for 22 h. Then, all the hydrolyzed solution was transferred to a 50 mL volumetric flask, and the volume was fixed with primary water. After taking 2 mL of the above solution and evaporating it under reduced pressure, it was dissolved with 2 mL of hydrochloric acid solution at a concentration of 0.02 mL/L and then filtered through an aqueous filter membrane of 0.22 μm and analyzed. Each sample was separated and detected by an L-8900 amino acid autoanalyzer, and all samples were repeated three times.

2.3.3. Nutritional Evaluation of Amino Acids

According to the International Standard Reference Model for the needs of older children, young people, and adults aged >3 years proposed by the Food and Agriculture Organization of the United Nations (FAO) and World Health Organization (WHO) in 2013 [51], E/T (%) = EAA/TAA, E/N (%) = EAA/NEAA [52], E/N (%) = EAA/NEAA [53], E/T (%) = EAA/TAA, E/N (%) = EAA/NEAA [52], M/T (%) = MAA/TAA, BC/E (%) = BCAA/EAA, and BC/A = BCAA/AAA [21].

The amino acid ratio coefficient method was proposed by Shengtao and Kun [53] to calculate the ratio of amino acid (RAA), the ratio coefficient of amino acid (RC), and the score of RC and SRC [51].Eq: CV is the coefficient of variation of the RC and CV = standard deviation/average number.

2.3.4. Taste-Presenting Amino Acid Analysis

Taste-presenting amino acids can be classified as fresh, sweet, bitter, and aromatic amino acids, and taste active value (TAV) refers to the ratio of the value of the content of taste-presenting substances to the taste threshold of taste-presenting substances [54].

2.4. Statistical Analysis of Data

The experimental data were organized for statistics using Excel 2016, and ANOVA, principal component analysis, was performed using SPSS (version 23.0, IBM, Armonk, NY, USA). PCA, correlation analysis, and HCA were performed using Origin 2021 and OmicShare tools.

3. Results and Discussion

3.1. Chromatographic Analysis

According to the chromatographic detection conditions, the chromatographic separation of 17 amino acid standards using amino acid autoanalyzer is shown in Figure 1. Chromatogram of 17 amino acid standard samples, proline, was measured at the wavelength of 440 nm, and the rest of 16 amino acids were measured at the wavelength of 570 nm, and the 17 amino acids achieved a very good separation effect under the separation conditions. The samples to be tested were processed for amino acid determination as shown in Figure 2. Amino acid chromatogram of A. arguta, a comparison of the chromatographic separations of the samples with those of the amino acid standards, revealed that the A. arguta fruit samples contained 17 amino acid species.

3.2. Analysis of Amino Acid Composition and Content of Fruits of Different A. arguta Resources

The different amino acids of 35 A. arguta resources were statistically analyzed, and the results are shown in Table 2. Amino acid composition and content of different resources ofA. arguta mg/100 g. All 35 A. arguta contained 17 amino acids, including 7 EAAs, 10 NEAAs, 2 CEAAs, and 9 MAAs. The 7 EAAs are Thr, Val, Met, Ile, Leu, Phe, and Lys, the 10 NEAAs are Asp, Ser, Glu, Gly, Ala, Cys, Tyr, His, Arg, and Pro, the 2 CEAAs are His and Arg, and the 9 MAAs are Asp, Glu, Gly, Met, Ile, Lue, Phe, Lys, and Arg. The variation of standard deviation of 17 amino acids was 9.68∼146.87, and the coefficient of variation was 40.94%∼77.74%, which indicated that the content of different amino acids differed significantly among resources, among which the coefficient of variation of Pro was the largest, and the coefficient of variation of Gys was the smallest, and at the same time, the results of the analysis of variance showed that each amino acid differed significantly among most of the A. arguta resources; the variation of the mean value was 18.16∼222.22 mg/100 g, with the lowest content of Met and the highest content of Glu. Glu, as an indispensable amino acid during the critical period of life, including the period of fast-growing newborns, has the ability to enhance the immune function of the immune cells [55], and it can also be used to treatment of liver-related diseases such as hepatic coma and hepatic insufficiency [56], and glutamine, which is formed by combining with blood ammonia, also contributes to the repair of traumatized organisms and the treatment related to peptic ulcers [57], so appropriate consumption of A. arguta fruits can improve immunity, while, in the future, it can be developed as a healthcare product for liver protection and repair of ulcers.

The results of the variance analysis showed that there were differences in the content of various amino acids among the different A. arguta resources. The resources with the highest content of Thr, Ser, Glu, Ala, Val, Ile, Tyr, Lys, His, and Arg were S4; the resources with the highest content of Phe were S4 and S27, and the resources with the highest content of Asp were S8; the resources with the highest content of Gly, Met, and Leu were S10; the resources with the highest content of Pro were S30; the resources with the highest content of Cys were S28 and differed from other resources. Leu content was S10; the highest Pro content was S30; the highest Cys content was S28, and it was significantly different from other resources. The TAA content was 384.20∼2590.56 mg/100 g, and the highest content was 674.27% of the lowest content. The resource with the highest TAA content was S4, and the resource with the lowest content was S34. The EAA content was 140.23∼901.54 mg/100 g, with a mean value of 391.48 mg/100 g; the NEAA content was 237.41∼1689.02 mg/100 g, with a mean value of 797.68 mg/100 g; the CEAA content was 47.89∼480.52 mg/100 g, with a mean value of 101.82 mg/100 g; the content of MAA was 219.81∼1640.16 mg/100 g, with a mean value of 741.23 mg/100 g; the content of BCAA was 78.86∼496.36 mg/100 g, with a mean value of 213.55 mg/100 g; the total amino acid content was 384.20∼2590.56 mg/100 g. In comparison, the mean contents of NEAA and MAA were higher than the others, so NEAA and MAA were the main components of TAA in A. arguta.

3.3. Evaluation of Amino Acid Nutritional Value of Fruits of Different A. arguta Resources

The WHO and FAO proposed a standard model for evaluating essential amino acids in food in 1973, and it has been suggested that the closer the variety of essential amino acids in the proteins of each substance and the ratio of their composition is to the FAO/WHO standard model of amino acids, the higher the nutritional value of proteins and the better the quality of the proteins in the substance, and vice versa, and the worse the nutritional quality [30]. Comparing the essential amino acids in 35 A. arguta resources with the amino acid pattern spectrum of FAO/WHO is shown in Table 3. Comparison of essential amino acids and FAO/WHO amino acid patterns in different resource fruits of A. arguta shows that the Leu of 35 A. arguta resources meets the ideal pattern proposed by FAO/WHO, and Leu, as an essential amino acid, is commonly used in the treatment of idiopathic hyperglycemia in young children, as well as liver disease, anemia, and muscular dystrophy caused by the imbalance of glucose metabolism accompanied by a decrease in bile secretion [58, 59], and therefore, studies on the regulation of glucose and lipid metabolism by the A. arguta may be carried out in the subsequent studies. There were 2 resources that did not fit the Val ideal model, 17 resources that fit the Met + Cys ideal model, 3 resources that fit the Ile ideal model, 10 resources that did not fit the Thr ideal model, 1 resource that did not fit the Phe + Tyr ideal model, and 24 resources that did not fit the Lys ideal model.

In accordance with the ideal amino acid composition proposed by WHO/FAO, EAA/TAA is 40%, EAA/NEAA is ≥60%, and BCAAs should account for 40% of the daily EAA requirement for adults, 41% for children, and 45% for infants [60–62].

Figure 3(a) shows the distribution range of amino acid nutritional value of different A. arguta resources, and it can be seen that the range of EAA/TAA of fruits of different A. arguta resources was 26.15%∼43.59%, among which there were three resources that met the EAA/TAA standard, with a value of 41%∼44%; meanwhile, Figure 3(b) shows the distribution range of amino acid nutritional value of different A. arguta resources and the range of EAA/NEAA ranged from 33.52% to 77.28%, among which there were five resources that met the EAA/NEAA standard, and S2 (A040103), S3 (A060902), and S35 (SH5) met the standard for both EAA/TAA and EAA/NEAA.

(a)

(b)

(c)

(d)

The higher the ratio of medicinal amino acids/total amino acids (MAA/TAA), the higher the medicinal value of the substance. Figure 3(c) shows the distribution range of amino acid nutritional value of different A. arguta resources, the MAA/TAA ratios of 35 A. arguta resources were all in the range of 51.30%∼69.06%, and the MAA/TAA ratios of 28 of the resources were more than 60%, which are the results that indicate that the A. arguta has a high medicinal value.

Branched-chain amino acids, collectively known as leucine, valine, and isoleucine, are not only important components of human proteins but also regulators of protein, glucose, energy metabolism, and brain functions [63]. Figure 3(d) shows the distribution range of amino acid nutritional value of different A. arguta resources, all the resources achieved ≥40% BCAA/EAA, the range is 48.63%∼64.20%, and three of the BCAA/EAA were more than 60%, which were 61.95% for S11, 60.80% for S19, and 64.20% for S26.

3.4. Comparison of Amino Acid RAA, RC, and SRC in Fruits of Different A. arguta Resources

Amino acid balance theory suggests that the closer the amino acid composition of a food protein is to the pattern amino acid composition, the higher its nutritional value [51]. Based on the amino acid balance theory, RC and SRC were calculated to evaluate the quality of proteins based on the dispersion of various essential amino acids from the amino acid pattern, which is closer to the biological price [53, 54]. The RAA values of the fruits of different soft date kiwifruit resources are shown in Table 4. Values of RAA of different A. arguta resources and the RAA values of the two amino acids Leu and Val were greater than 1 in 35 resources. Whether the proportion of essential amino acids in a food conforms to the human essential amino acid pattern profile is closely related to the size of the RC, with RC = 1 conforming, whereas RC < 1 indicates a relative deficiency, and the amino acid with the lowest content is considered to be the limiting amino acid of the substance. Figure 4 shows the range of RC values of 9 amino acids, and the Leu of all 35 A. arguta resources is greater than 1, indicating that the content of this amino acid in A. arguta fruits exceeds the human body’s needs; the RC values of Ile and Lys are less than 1, and the content of Ile is lower than that of Lys, indicating that the first limiting amino acid of A. arguta resource fruits is Ile, and the second limiting amino acid is Lys, so when consuming A. arguta, it is necessary to eat food rich in isoleucine and lysine with it, such as spinach, potatoes, bean curd, soya bean milk, and eggs.

Modern scientific research has identified that amino acid deficiency can negatively affect the nutritional value of food. In order to measure whether the amino acid composition of a food is reasonable or not, the SRC value was introduced, which is a measure of how well the amino acids in a food match the model, and the closer the value is to 100, the closer the amino acid composition of the food is to the ideal model, and, therefore, the higher the nutritional value of the meal can be. Figure 5 shows the distribution of SRC value in different A. arguta resources. The SRC values of 35 A. arguta resources’ fruits were between 40 and 80, of which 20 resources had SRC values of 60∼70, which accounted for 57.14% of the samples supplied for testing, and three resources had SRC values of more than 70, with the highest score being S3.

3.5. Analysis of Taste-Presenting Amino Acids in Fruits of Different A. arguta Resources

3.5.1. Taste-Presenting Amino Acids Content and Radar Chart Analysis

A. arguta fruit has a unique sweet and sour taste when eaten fresh, which is closely linked to its rich amino acid content. Based on the flavor-presenting characteristics, the flavor-presenting amino acids can be classified into four groups, namely, fresh amino acids (Glu, Asp, and Lys), sweet amino acids (Thr, His, Ser, Pro, Gly, and Ala), bitter amino acids (Val, Met, Leu, Ile, and Arg), and aromatic amino acids (Cys, Tyr, and Phe) [49], and the contents of the four taste-presenting amino acids of different A. arguta resources are shown in Figure 6. Figure 6 shows the contents of flavored amino acids in different A. arguta resources mg/100 g, the variation of the fresh amino acid content was 116.24∼980.29 mg/100 g, the variation of the sweet amino acid content was 90.53∼687.23 mg/100 g, the variation of the bitter amino acid content was 98.95∼730.29 mg/100 g, and the variation of aromatic amino acid content was 33.19∼292.48 mg/100 g. The resource with the highest content of fresh, bitter, and aromatic amino acids was S4, and the resource with the highest content of sweet amino acids was S16.

Radar plot analysis of the flavor-presenting amino acids of different A. arguta resources shows that, as can be seen from Figure 7, those that contribute more to the flavor of A. arguta are fresh amino acids and sweet amino acids, and the larger area of the pattern plot of S4 compared with the other resources indicates that the content of flavor amino acids in S4 is generally higher than that of the other resources 7. Figure 7 shows the flavor amino acid radar map of different A. arguta resources, the greater contribution in the flavor of A. arguta was made by fresh taste amino acids and sweet taste amino acids, and the larger area of the pattern plot of S4 compared with other resources indicated that the taste amino acid content of S4 was generally higher than that of other resources. The unique flavor of A. arguta may be closely related to its high content of gustatory amino acids. The high percentage of fresh and sweet amino acids such as Glu, Asp, and Ala gives the A. arguta its fresh, sweet, and sour flavor characteristics, while effectively reducing the bitterness of the rind and alleviating the undesirable taste brought about by the rind.

3.5.2. TAV Analysis

Different amino acids have different taste perception thresholds, so higher amino acid content does not necessarily contribute more to food flavor [54], further analysis of the effect of each presenting amino acid on fruit flavor quality by TAV values is needed, and the TAV of different A. arguta resources presenting amino acids is shown in Table 5. When TAV > 1 is present, then the amino acid contributes to flavor quality. As shown in Table 5, the amino acids with TAV values greater than 1 in all 35 A. arguta were Glu and Cys, the amino acids with TAV values less than 1 in all were Thr and Tyr, and the remaining amino acids had TAV values greater than 1 in some resources. Thus, Glu and Cys were the main contributors to the flavor of the 35 A. arguta resources, but in comparison, the mean TAV of Cys was greater than that of Glu, so Cys was the main influence on the flavor of A. arguta.

3.6. Correlation Analysis of Amino Acid Content of Different A. arguta Resources

The correlation analysis of 17 of the 35 A. arguta was carried out, and the results are shown in Figure 8. Correlation analysis of amino acid content in different A. arguta resources is shown in Figure 8. 17 amino acids were all highly significant and positively correlated, of which the correlation coefficient between Ser and Thr was as high as 0.99; the correlation coefficient between Cys and Pro was higher, 0.63, and the correlation coefficients with the other amino acids were all below 0.6; in short, the correlation of the amino acid fractions was strong, which was similar to the results of the study by Min et al. [64].

3.7. PCA Analysis

The PCA method can simplify multiple indicators with correlation into several relatively independent and representative indicators, retaining the vast majority of the original information, which is faster and more accurate compared with a single evaluation, and at the same time, it can also avoid the influence of correlation between traits on the evaluation results [65, 66], and it has been widely used in the evaluation of the quality of agricultural products such as jujube [21], A. arguta [19], black fungus [67], and peach [68]. PCA of the amino acids of different A. arguta resources is shown in Figure 9. PCA scores of amino acid content in different A. arguta resources revealed that S4, S10, S18, and S27 were located in quadrant 1, but all of them were located in scattered locations, indicating that the amino acid contents of these four resources were not similar; there were 10 resources located in quadrant 2, of which S8, S15, S22, S16, and S25 were closer to each other, indicating that the amino acid contents of these five resources were similar; S11, S12, S20, S21, S23, and S26 are located in quadrant 3; S1, S2, S5, S31, S32, S33, S34, and S35 are located in quadrant 4, but S35 is far away from the other resources, indicating that the amino acid content is similar among the resources except for S35; S6, S7, and S24 are located in the horizontal axis, which indicates that they are mainly influenced by PC1; S9 is located in the vertical axis, which indicates that it is importantly influenced by PC2.

3.8. Comprehensive Evaluation of Amino Acids of Different A. arguta Resources

As can be seen from Table 6, a total of 2 principal components were extracted using factor analysis, the contribution of the first principal component was 63.979%, the contribution of the second principal component was 24.083%, and the cumulative variance of the first 2 PCs reached 87.88%, Gly, Cys, and Pro were the principal component 2, and the remaining 14 amino acids were the principal component 1. Table 6 shows the factor loading matrix and contribution rate after rotation that a comprehensive evaluation of different A. arguta resources using the first 2 PCs is feasible.

With 17 amino acid indicators as the initial independent variables, the equation expressions for the three PC factors were finally derived by PCA as follows:

The relative contribution of the variance of the two PCs was used as the weight, and the PC scores of each resource and the corresponding weights were linearly weighted and summed to establish a comprehensive evaluation function F = 0.726F1 + 0.274F2. The comprehensive score of each A. arguta resource was calculated to reflect its comprehensive amino acid quality, and the higher the comprehensive score, the better the amino acid quality of the resource. As shown in Table 7, comprehensive evaluation results of amino acids of different A. arguta resources, the top 5 resources in terms of the overall score were S4, S10, S18, S25, and S30, indicating that these five A. arguta resources had relatively good overall amino acid evaluations.

3.9. Hierarchical Clustering Analysis of Amino Acids in Different A. arguta Resources

The results of the hierarchical cluster analysis of 17 amino acids in 35 A. arguta resources are shown in Figure 10. All A. arguta resources could be classified into four categories when the transect line took the value of 300, category 1 contained S4 and S10, category 2 contained S30, S8, S16, and S18, category 3 contained S22, S25, S14, S15, S24, S27, S28, and S29, and the remaining 21 resources were all in category 4, among which S4 and S10 in category 1 had the highest amino acid content and better quality. The clustering results were consistent with the comprehensive evaluation results of PCA. Therefore, it can provide a good reference for the introduction and promotion of excellent resources of A. arguta, the development and utilization of products, and the evaluation of amino acid nutritional value.

4. Conclusion

In this study, an amino acid analyzer was used to separate and determine the amino acid composition and content of 35 A. arguta resource fruits from the Zuojia Town Actinidia arguta and Magnolia vine National Forest Germplasm Resource Bank in Jilin Province, and the results showed that A. arguta fruits contained 17 amino acids, with a total amino acid content of 384.20∼2590.56 mg/100 g and that the average contents of NEAA and MAA had higher average contents than others, which were the main components of TAA in A. arguta. The analysis of the variance results showed that the standard deviation of the 17 amino acids had a variance of 9.68∼146.87, the coefficient of variation was 40.94%∼77.74%, and the content of different amino acids differed significantly among resources, of which the coefficient of variation of Pro was the largest and the coefficient of variation of Gys was the smallest. Meanwhile, the amino acids varied significantly among most of the A. arguta resources, with mean values ranging from 18.16∼222.22 mg/100 g.Among them, the lowest content was Met, and the highest content was Glu. The results of amino acid nutritional value evaluation showed that the Leu of 35 A. arguta resources conformed to the ideal model proposed by FAO/WHO, and the RAA value of Leu of all resources was greater than 1, which indicated that the content of this amino acid in A. arguta fruits exceeded the human body’s needs; the RC values of Ile and Lys were both less than 1, and the content of Ile was lower than that of Lys, which indicated that the first limiting amino acid of the fruits of the A. arguta resources was Ile and the second limiting amino acid was Lys, and the SRC value of their fruits was in the range of 40∼80. The analysis of the results of flavor-presenting amino acids showed that Glu and Cys had the main contribution to the fruit flavor of A. arguta resources, and Cys was the main amino acid factor for A. arguta flavor in comparison. However, the effect of amino acids on fruit flavor was limited, and the volatile flavor components of the fruit need to be analyzed and determined at a later stage. The principal component analysis extracted 2 principal components from 17 amino acids, and the cumulative variance contribution rate was 87.88%, which better reflected the comprehensive information of amino acids in A. arguta. A comprehensive amino acid evaluation model was established, and the top 5 excellent resources with comprehensive scores were S4, S10, S18, S25, and S30. Hierarchical cluster analysis classified the 35 A. arguta resources into 4 categories, which better reflected the differences in amino acid content and composition, nutritional value, and taste characteristics among A. arguta fruits from different collection sites. This study provides a scientific basis for revealing the nutritional value and taste characteristics of A. arguta, a theoretical reference for the screening of excellent A. arguta resources and the development and utilization of products, and a theoretical basis for guiding people to establish a scientific and healthy dietary structure. Further research will test and analyze the volatile flavor quality of A. arguta and establish a more detailed evaluation system of A. arguta fruit quality by combining the nutritional quality, amino acid composition and content, and volatile flavor quality, to lay a theoretical foundation for the development of excellent A. arguta resources. In addition, we will further study the effects of amino acids of A. arguta on human health to provide a theoretical basis for the provision of a scientifically balanced diet for human beings and the development of A. arguta functional products.

Data Availability

The data used to support the findings of this study are included within the article.

Conflicts of Interest

The authors declare that they have no conflicts of interest.

Acknowledgments

This work was supported by the Innovation Project of Chinese Academy of Agricultural Sciences (CAAS-ASTIP-2023-ISAPS) and Changchun City Science and Technology Development Plan Project (21ZGN09).

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