Comparison of production performance and meat quality characteristics between Guizhou Black goats and F4 generation hybrids of South African Kalahari Goats

Abstract

This study spanned 6 years and 4 generations, involving the progressive crossbreeding of South African Kalahari Goat (SK) and Guizhou Black Goat (GB) over three generations, followed by cross fixation F3 with F1 in the fourth generation, accompanied by the use of molecular markers technology to select a high fertility population, resulting in the creation of a hybrid goat, BKF4 (11/16 SK lineage and 5/16 GB lineage). A comparative evaluation of the BKF4 hybrid breed and its parental breeds was conducted. Reproductive and production parameters of GB, SK, and BKF4 goat groups were monitored, including lambing rate (LR), survival rate (SR), daily weight gain at 3 months of age (DWG), and adult body weight (ABW) (n = 110, 106, 112 per group). In addition, dressing percentage (DP) (n = 12 per group) and analyses of amino acids (n = 8, 6, 10 per group) and fatty acids (n = 6 per group) were conducted to evaluate meat quality indicators. Results: (1) Reproductive and production performance: The index of LR reached 199%, significantly higher than GB and SK (p ≤ 0.001), with a SR of 95.0%, markedly higher than SK (p ≤ 0.001); DWG was 276.5 g, ABW reached 56.6 kg and with a dressing percentage (DP) of 54.5%, they are significantly surpassing GB (p ≤ 0.001). (2) Regarding meat quality: pH₄₅-value and crude protein content (CP) increased, while intramuscular fat content increased compared to GB and ash content decreased. The amino acid composition was similar to GB, but the taste was more similar to SK. However, there were some negative impacts on fatty acid composition and functionality. (3) PCA analysis revealed that: BKF4 exhibited superior meat quality compared to GB and SK, influenced by two key factors contributing 83.49% and 16.51% to the explained variance, respectively. The key factors affecting meat quality include intramuscular fat (IMF), nutrient index (NI), PUFAs/MUFAs, n-6FAs, and drip loss (DL).

Introduction

Goats are universally acknowledged as an important agricultural resource, furnishing meat and derivative products essential for human consumption^1,2. Their meat is particularly valued for unique nutritional qualities, composition, and sensory properties^3–7. Since the late twentieth century, globalization has facilitated the widespread crossbreeding of local goat breeds with genetically superior international breeds, aimed at enhancing production performance and increasing their economic, ecological, and social value^2,8–12. This crossbreeding strategy not only introduced desirable genetic traits but also preserved the adaptability and phenotypic characteristics of local breeds, thereby significantly improving the nutritional value and meat quality of goats^8,13. In the realm of molecular breeding, genes such as Bone Morphogenetic Protein 15 (BMP15), Growth Differentiation Factor 9 (GDF9), Dynein Axonemal Heavy Chain 1 (DNAH1), and Retinol Binding Protein 4 (RBP4) have been identified as significantly associated with reproductive traits in goats, providing promising markers for selecting individuals with enhanced reproductive capabilities^14–17.

This study employed molecular breeding and four-generation progressive crossbreeding between the native Guizhou Black goats (GB) of China and South African Kalahari goats (SK) to develop a high-quality hybrid breed, BKF4¹⁸. While significantly enhancing the reproductive and production performance of the parent breeds, the meat quality of the hybrids was rigorously evaluated. These efforts are crucial for the sustainable development of the goat meat industry and provide valuable insights for the strategic breeding of local goat crossbreeding¹².

Materials and methods

Animal management and experimental design

This section outlines the methodology used to manage and select animal subjects for the study. Step 1: Base Selection. Initial populations of high-reproductive-performance Guizhou Black Goats and South African Kalahari Goats were established using molecular techniques targeting the BMP15, GDF9, and RBP4 genes¹⁴. Step 2: Four generations of Crossbreeding Selection involved the breeding of Guizhou Black Goats (GB), South African Kalahari Goats (SK), and their crossbreeds, including BKF1 (1/2 SK ♀ × 1/2 GB ♂, m_a (♂) ≧ 45 kg, m_a (♀) ≧ 40 kg), BKF2 (3/4 SK ♀ × 1/4 GB ♂, m_a (♂) ≧ 45 kg , m_a (♀) ≧ 40 kg), BKF3 (7/8 SK ♂ × 1/8 GB ♀, m_a (♂) ≧ 50 kg, m_a (♀) ≧ 45 kg), and BKF4 (Crossover fixation BKF3 x BKF1: 11/16 SK × 5/16 GB, m_a (♂) ≧ 55 kg and m_a (♀) ≧ 50 kg )^8,19. Breeding criteria comprise high lambing rate, superior body size and quality, high meat yield, strong adaptability, and selecting individuals with stable hereditary traits verified through pedigree and lineage records. Breeding took place at the Guizhou Kalahari Goat Breeding Company in Qinglong County, Guizhou Province, China, and lasted for six years. Males and females were grazed separately, with natural pasture as the primary feed supplemented with meat goats feed purchased from the Yingmei Group. The developed BKF4 goats inherit characteristics from the specialized breeding line of Guizhou Black Goats and South African Kalahari Goats, exhibiting comparable environmental adaptability to the local Guizhou Black Goats. Ethical approval for the study was obtained from Guizhou University (EAE-GIU-2021-P009) and animal experimental ethics regulations were followed according to ARRIVE guidelines. All methods were performed in accordance with the relevant guidelines and regulations. Performance metrics such as lambing rate (LR), Survival rate (SR), daily weight gain at 3 months of age (DWG), and adult body weight (ABW) were meticulously recorded from 328 parallel samples, with group sample sizes of 110, 106, and 112 for GB, SK, and BKF4, respectively^12,20. All gexperimental samples were randomly chosen from healthy animals.

Slaughter and assessment of meat quality

Standard commercial procedures were adhered to for goat slaughter to ensure consistency in data collection. Dressing percentage (DP) was assessed following the protocol established by Reynolds et al.²¹, and based on the average of 12 replicates. Muscle samples (approximately 300 g each) were precisely taken from the longissimus dorsi muscle (LD) between the 12th and 13th thoracic vertebrae within 30 min post-mortem for analysis of meat quality and nutrient content²². The pH₄₅-value was measured according to Martins J.M et al. by using a Testo-205 pH meter (TESTO, Testo Group, Germany)^12,22. Drip loss, expressed as the percentage weight decrease, was determined by comparing the weights of samples before and after storage at 4 °C for 48 h²³. Moisture was obtained after drying samples in an oven at 105 °C for 24 h, while Crude protein content (CP) was determined by Kjeldahl-nitrogen × 6.25. Ash content was determined after incineration at 550 °C for 6 h. Intramuscular fat (IMF) was determined gravimetrically after Soxhlet lipid extraction using a SoxtecTM 2055 automated system (FOSS, Denmark). Amino acid analysis was conducted using the S-433D Amino Acid Analyzer (SYKAM, Germany), while fatty acid analysis utilized the Agilent Technologies 7890A Gas Chromatograph (Agilent Technologies, USA). The methods described by Ali Mahabbat et al. and Śmietana Natalia et al. were followed^24,25. Each type of analysis was conducted with a minimum of three replicates per sample.

Amino acid analysis

In this study, the sums of Essential Amino Acids (EAAs), Conditionally Essential Amino Acids (CEAAs), Non-Essential Amino Acids (NEAAs), Amino Acids with Pharmacological relevance (PAAs, tagged with “#”), Branched-Chain Amino Acids (BCAAs, the collective levels of Ile, Leu, and Val), and Total Amino Acids (TAAs) were calculated. Additionally, the ratios of PAAs/TAAs, EAAs/TAAs, and EAAs/NC (NC = NEAAs + CEAAs) were also determined. Using the FAO/WHO amino acid scoring model, the Ratio of Amino Acids (RAA), Ratio Coefficient (RC), Relative Standard Deviation (RSD), Score of Ratio Coefficient (SRC), Essential Amino Acid Index (EAAI)²⁶, Biological Value (BV), Nutritional Index (NI) and Protein Efficiency Ratio (PER) were calculated for all samples. The calculation formulas are as follows: RAA = amount of a specific essential amino acid/recommended amount; RC = RAA of a specific essential amino acid/mean RAA of all essential amino acids; SRC = 100—RSD × 100, where RSD represents the relative standard deviation of RC; $EAAI=\sqrt[n]{RA{A}_1\times RA{A}_2\times \cdots RA{A}_{\text{n}}}$; BV = [(1.09 × EAAI − 11.7]²⁷; NI = (EAAI × Protein (%)/100), n represents the number of essential amino acids, n ≦ 8^26,28; PER = − 0.468 + 0.454( Leu) − 0.105 (Tyr)²⁹. The taste attributes of amino acids, including ‘umami (U)’, ‘bitter (B)’, ‘sweet (S)’, and ‘aromatic flavor (A)’, were evaluated according to established literature, with the respective threshold values (TV) listed in Table 1^25,30.

Table 1.

Taste threshold value of amino acids.

Taste	Umami				Bitter				Sweet				Aromatic				Sweet and bitter
Amino acid	Asp	Glu	Asn	His	Met	Val	Arg	Ile	Phe	Trp	Leu	Tyr	Ala	Gly	Ser	Thr	Phe	Thr	Lys	Pro
TV(mg/dL)	3	5	100	20	30	40	50	90	90	90	190	ND	60	130	150	260	90	260	50	300

The taste attributes of amino acids, including “umami (U),” “bitter (B),” “sweet (S),” and “aromatic flavor (A),” were evaluated based on the literature by Śmietana Natalia, Nishimura Toshihide, et al., with the corresponding threshold values (TV) listed in Table 1.

Fatty acid analysis

After Fatty Acids (FAs) identification, the sums of Saturated Fatty Acids (SFAs), Monounsaturated Fatty Acids (MUFAs), Polyunsaturated Fatty Acids (PUFAs), Essential Fatty Acids (EFAs, labeled with “#”), Unsaturated Fatty Acids (UFAs), Total Fatty Acids (TFAs) and the PUFAs/SFAs, PUFAs/MUFAs, UFAs/TFAs, n−6/n−3 ratios were calculated. Several indices were utilized in the quantification of fatty acids, including the Unsaturation index (UI), Atherogenic index (AI), Thrombogenic index (TI), Hypocholesterolemic Fatty Acids (DFA), Hypercholesterolemic Fatty Acids (OFA), and the hypocholesterolemic/hypercholesterolemic ratio (h/H). Calculation formulas for these indices are as follows: UI = 1 × ∑MUFA (%) + 2 × ∑DUFA (%) + 3 × ∑TUFA (%) + … n × ∑NUFA (%); AI = (C_12:0 + (4 × C_14:0) + C_16:0)/(∑MUFA + ∑PUFA_n−3 + ∑PUFA_n−6)³¹; DFA = UFA + C_18:0; OFA = C_12:0 + C_14:0 + C_16:0; TI = (C_14:0 + C_16:0 + C_18:0)/((0.5 × ∑MUFA) + (0.5 × ∑PUFA_n−6) + (3 × ∑PUFA_n−3) + ( ∑PUFA_n−3/∑PUFA_n−6))^25,32;(h/H) = [∑(C_18:1n−9, C_18:1n−7, C_18:2n−6, C_18:3n−3, C_20:3n−6, C_20:4n−6)]/[∑(C_14:0 + C_16:0)]; n₋6/n₋3 = ∑PUFA_n−3/∑PUFA_n−6^20,33,34. The AI and TI indices indicate the impact of fatty acids on cardiovascular risk, while the h/H ratio reflects the functional influence of fatty acids on cholesterol metabolism²⁵.

Statistical analysis

The collected data underwent statistical analysis using Excel for initial organization and SPSS version 21.0 for advanced computations. One-way ANOVA was used to assess differences among data sets, followed by Duncan's multiple range test for post-hoc comparisons. Results were presented as mean ± standard error (Mean ± SE) with significance levels set at *p ≤ 0.05 or **p ≤ 0.01, ***p ≤ 0.001. Significant differences were observed among values marked with different superscripts within the same row. Principal Component Analysis (PCA) was applied to evaluate meat quality indicators in all samples, generating a composite score to depict their impact and evaluation.

Ethical statement

Ethical review and approval were waived for this study, due to the compliance with national and/or European Regulations on animal husbandry and slaughter, as reported in the Materials and Methods section.

Results and analysis

Performance and carcass characteristics

Table 2 and Fig. 1A display the performance and carcass characteristics of the BKF4 hybrid, which resulted from molecular selection for high reproductive traits and hybrid breeding practices. BKF4 exhibited notable improvements in lambing rate, daily weight gain at 3 months, adult body weight and dressing percentage compared to the GB and SK groups (p ≤ 0.001). Notably, BKF4 demonstrated a lambing rate increase of over 45.5% and more than doubled the daily weight gain at 3 months compared to the purebred Guizhou Black Goat (GB). Moreover, BKF4 maintained the exceptional survival rate exceeding 95%, indicative of robust disease resistance. The hybrid also achieved a more than 15.5% increase in adult weight gain.

Table 2.

Effects of cross-breeding on performance and carcass characteristics.

Parameter	Genotype (Gen)			P-value
	GB (N = 110/12)	SK (N = 110/12)	BKF4 (N = 110/12)
Lambing rate (LR, %)	151.0 ± 20.6C	171.0 ± 32.0B	199.0 ± 26.4A	≤ 0.001***
Survival rate (SR, %)	95.4 ± 5.5A	87.1 ± 5.0B	95.1 ± 5.5A	≤ 0.001***
Daily weight gain at 3 months of age (DWG, g)	122.0 ± 23.6B	282.0 ± 28.2A	276.5 ± 25.4A	≤ 0.001***
Adult body weight (ABW, kg )	49.0 ± 8.5C	65.6 ± 9.0A	56.6 ± 8.4B	≤ 0.001***
Dressing percentage (DP, %)	40.4 ± 4.5B	60.4 ± 5.0A	54.5 ± 4.3A	≤ 0.001***

Figure 1.

Reproductive, production performance and meat quality indices of three groups of goats. (A) Performance and carcass characteristics. (B) Chemical Components. Notes: In this study, three groups of GB, SK, and BKF4 goats, each comprising of 110, 106, 112 individuals (totaling 328), were utilized to employed to evaluate reproductive and production performance. Additionally, thirty-six goats (12 individuals per group, totaling 36) were designated for the assessment of slaughter performance, while thirty-six goats (each with 12 individuals, totaling 36) were allocated for analyzing chemical components. The goats were reared under controlled conditions at Guizhou Kahara Goat Breeding Company in Qinglong County, Guizhou Province, China. Males and females were grazed separately, with natural pasture as the primary feed supplemented with meat goats feed purchased from the Yingmei Group. The developed BKF4 goats inherit characteristics from the specialized breeding line of Guizhou Black Goats and South African Kalahari Goats, exhibiting comparable environmental adaptability to the local Guizhou Black Goats. These goats were approximately one year old, and the experimental samples were carefully chosen from healthy animals. Ethical approval for the study was obtained from the Guizhou Breeding Livestock and Poultry Germplasm Determination Center and Guizhou University (EAE-GIU-2021-P009). Standard commercial procedures were followed during goat slaughter to ensure consistency in data collection pertaining to carcass and meat quality. The reproductive, production, and slaughter indices are presented in Tables 2 and 3.

Meat quality indices

Trade-offs between intramuscular fat (IMF) and other chemical components in the cross-breeding system are shown in Table 3 and Fig. 1B. Chemical analyses of IMF, pH₄₅-value, drip loss, moisture content, ash and protein of longissimus dorsi were made before meat quality evaluation. The IMF content in BKF4 increased by 44% compared to GB (3.05 g/100 g, p ≤ 0.001) and decreased by 30% compared to SK (6.08 g, p ≤ 0.001). However, the DL, MC and Ash significantly decreased (p ≤ 0.001) and pH₄₅-value increased in BKF4 (p ≤ 0.001). However, DL, MC, and ash content significantly decreased (p ≤ 0.001), while pH₄₅-value significantly increased in BKF4 (p ≤ 0.001). The high fat and low water characteristics of BKF4 may suggest improved quality.

Table 3.

Effect of cross-breeding on meat quality indices.

Parameter	Genotype (Gen)			P-value
	GB (N = 12)	SK (N = 12)	BKF4 (N = 12)
pH45-value	5.47 ± 0.16C	6.18 ± 0.37B	6.46 ± 0.17A	≤ 0.001***
Drip loss (DL, %)	4.47 ± 2.34A	3.60 ± 1.58A	1.49 ± 0.37B	≤ 0.001***
Moisture content (MC, %)	74.65 ± 0.94B	76.99 ± 2.84A	73.40 ± 1.09B	≤ 0.001***
Ash content (Ash, %)	5.01 ± 1.03A	4.29 ± 0.57B	3.65 ± 0.14B	≤ 0.001***
Crude protein content (CP, %)	20.33 ± 0.60B	19.21 ± 1.11C	21.5 ± 0.58A	≤ 0.001***
Intramuscular fat (IMF, %)	3.05 ± 0.59B	6.08 ± 2.46A	4.40 ± 1.23B	≤ 0.001***

Amino acid composition

Table 4 outlines the analysis of 16 amino acids in the samples, including 7 essential amino acids (EAAs), 4 conditionally essential amino acids (CEAAs), 5 non-essential amino acids (NEAAs), and 9 pharmacologically relevant amino acids (PAAs). Levels of CP, EAAs, CEAAs, PAAs, PAAs/TAAs, EAAs/NC, and EAAI, as well as SRC, NI, and BV, were significantly higher in GB and BKF4 compared to SK (p ≤ 0.001), with BCAAs and TAAs also showing a significant increase (p ≤ 0.05). Additionally, lysine, methionine, threonine, valine, phenylalanine, glycine, and proline levels in GB and BKF4 were significantly higher than those in SK (p ≤ 0.01), while arginine and alanine were also significantly elevated (p ≤ 0.05). Conversely, histidine was significantly lower in GB and BKF4 compared to SK (p ≤ 0.001), and serine was significantly lower (p ≤ 0.05). The amino acid profile of BKF4 closely resembled that of Guizhou Black Goat (GB). There were no significant differences in PER values among the three groups. In terms of taste intensity, GB and BKF4 exhibited significantly higher umami, (U + S + A)/B values and aromatic flavor compared to SK (p ≤ 0.01), higher sweetness (p ≤ 0.05), and lower bitterness (p ≤ 0.05). The B:U:S:A profile indicated that BKF4 was more similar to GB.

Table 4.

Effects of cross-breeding on amino acid composition in the longissimus Dorsi.

Parameter	Genotype (Gen)					P-value
	GB (N = 8)	SK (N = 6)			BKF4 (N = 10)
Crude protein content (CP; expressed as g/100 g fresh LD tissue)
CP	20.33 ± 0.60B	19.21 ± 1.11C			21.5 ± 0.58A	≤ 0.001***
Essential Amino Acids (EAAs; expressed as g/100 g fresh LD tissue)
#Isoleucine	3.78 ± 0.1	3.54 ± 0.29			3.68 ± 0.18	0.085
#Leucine	6.56 ± 0.19	6.16 ± 0.43			6.47 ± 0.29	0.056
#Lysine	6.82 ± 0.49A	2.56 ± 0.28B			7.06 ± 0.26A	≤ 0.001***
#Methionine	2.29 ± 0.08A	1.71 ± 0.18B			2.1 ± 0.21A	≤ 0.001***
Threonine	3.86 ± 0.12A	3.4 ± 0.24B			3.69 ± 0.17A	≤ 0.001***
Valine	4.19 ± 0.12A	3.6 ± 0.29B			3.96 ± 0.35A	0.003**
#Phenylalanine	3.54 ± 0.09A	3.07 ± 0.2B			3.42 ± 0.31A	0.004**
EAAs	31.05 ± 1.02A	24.03 ± 1.88B			30.37 ± 1.06A	≤ 0.001***
Conditionally essential amino acids (CEAAs; expressed as g/100 g fresh LD tissue)
#Arginine	5.14 ± 0.14a	4.69 ± 0.35b			5.12 ± 0.33a	0.014*
#Glycine	4.48 ± 0.18A	3.33 ± 0.27B			4.57 ± 0.1A	≤ 0.001***
Proline	3.23 ± 0.08A	2.81 ± 0.22B			3.28 ± 0.33A	0.004**
Tyrosine	2.73 ± 0.07	2.61 ± 0.21			2.67 ± 0.05	0.213
CEAAs	15.58 ± 0.44A	13.43 ± 1.05B			15.63 ± 0.44A	≤ 0.001***
Non-essential amino acids (NEAAs; expressed as g/100 g fresh LD tissue)
#Aspartic Acid	7.20 ± 0.38	6.67 ± 0.46			6.96 ± 0.37	0.069
#Glutamic acid	12.54 ± 0.74	11.67 ± 0.77			12.62 ± 0.75	0.055
Alanine	4.61 ± 0.31a	4.23 ± 0.33b			4.66 ± 0.34a	0.047*
Serine	2.46 ± 0.24b	2.94 ± 0.24a			2.6 ± 0.34b	0.017*
Histidine	3.14 ± 0.1B	6.4 ± 0.48A			2.34 ± 0.11C	≤ 0.001***
NEAAs	29.95 ± 1.69ab	31.92 ± 2.23a			29.18 ± 1.76b	0.031*
Partial sums (g/100 g of protein)
PAAs	52.36 ± 1.5A	43.39 ± 3.2B			51.99 ± 1.53A	≤ 0.001***
TAAs	76.58 ± 5.14a	69.38 ± 5.16b			75.19 ± 5.04a	0.041*
NC = NEAAs + CEAAs	45.53 ± 1.12	45.35 ± 3.28			44.81 ± 1.05	0.699
BCAAs	14.54 ± 0.61a	13.29 ± 1.00b			14.1 ± 0.64ab	0.038*
Ratios (%)
PAAs/TAAs	68.37 ± 0.16B	62.54 ± 0.09C			69.14 ± 0.21A	≤ 0.001***
EAAs/TAAs	40.54 ± 0.29A	34.63 ± 0.14B			40.39 ± 0.46A	≤ 0.001***
EAAs/NC	68.18 ± 0.83A	52.98 ± 0.33B			67.77 ± 1.27A	≤ 0.001***
Nutritional Indices (%)
EAAI	93.00 ± 0.03A	72.00 ± 0.06B			90.25 ± 0.03A	≤ 0.001***
SRC	80.96 ± 2.13A	73.54 ± 1.15C			77.23 ± 1.13B	≤ 0.001***
NI	18.93 ± 0.59A	13.87 ± 1.15B			19.38 ± 0.74A	≤ 0.001***
BV	89.8 ± 3.15A	67.02 ± 6.52B			86.54 ± 3.73A	≤ 0.001***
PER	2.22 ± 0.13	2.05 ± 0.17			2.19 ± 0.14	0.093
Taste intensity
Umami	4906.67 ± 113.36A	4558 ± 307.38B			4844.33 ± 135.62A	0.006**
Bitterness	556.94 ± 64.86b	666.46 ± 51.47a			551.13 ± 87.53b	0.013*
Sweetness	142.63 ± 9.87a	128.79 ± 9.97b			142.4 ± 9.78a	0.026*
Aromatic flavor	54.14 ± 1.43A	47.19 ± 3.17B			52.23 ± 2.51A	≤ 0.001***
Sweet and bitter	201.34 ± 10.84A	107.81 ± 9.37B			204.41 ± 8.48A	≤ 0.001***
(U + S + A)/B	9.16 ± 0.08A	7.11 ± 0.08B			9.3 ± 1.36A	≤ 0.001***
B: U: S: A	1:8.81:0.26:0.1	1:6.84:0.19:0.07			1:6.88:0.19:0.07

Referencing Table 5, the analysis revealed that the essential amino acid (EAA) profile of BKF4 closely mirrors that of its purebred progenitors, aligning well with the FAO/WHO amino acid (AA) standards and demonstrating high nutritional value. Notably, the ratio coefficients (RC) for isoleucine, lysine, the combination of phenylalanine and tyrosine, threonine, and valine in both GB and SK were above 1, indicating an abundance of these AAs suitable for nutritional enhancement. Additionally, RC for leucine in both GB and BKF4 were also above 1. In contrast, the combined RC values of methionine and cysteine, as well as tryptophan across all groups, and lysine in SK specifically, were below 1, suggesting a relative deficiency. Tryptophan was notably absent, making it the primary limiting AA, with methionine plus cysteine identified as the secondary limiting AA.

Table 5.

The ideal protein ratio recommended by FAO/WHO³⁵, also known as protein digestibility-corrected amino acid score (PDCAAS).

Parameter	FAO/WHO scoring pattern (g/100 g of protein)				RAA			RC
	Standard Value	GB	SK	BKF4	GB	SK	BKF4	GB	SK	BKF4
#Isoleucine	4	3.8	3.5	3.7	0.95	0.88	0.91	1.14	1.35	1.13
#Leucine	7	6.6	6.2	6.5	0.94	0.88	0.92	1.13	1.35	1.15
#Lysine	5.5	6.8	2.6	7.1	1.24	0.47	1.29	1.50	0.71	1.60
#Methionine + Cysteine	3.5	2.3	1.7	2.1	0.65	0.49	0.60	0.79	0.74	0.75
#Phenylalanine + Tyrosine	6	6.3	5.7	6.1	1.05	0.95	1.02	1.26	1.45	1.26
Threonine	4	3.9	3.4	3.7	0.97	0.85	0.92	1.17	1.30	1.15
Tryptophan	1	0.0	0.0	0.0	0.00	0.00	0.00	0.00	0.00	0.00
Valine	5	4.2	3.6	4.0	0.84	0.72	0.79	1.01	1.10	0.98
E/T′ (Left); SRC’(Right)	40	44.11	38.41	43.95	–	–	–	54.86	50.86	53.00
E/N′ (Left); EAAI’(Right)	60	74.18	58.76	73.74	–	–	–	93.22	72.15	89.98

In this study, Essential Amino Acids (EAAs), Conditionally Essential Amino Acids (CEAAs), and Non-Essential Amino Acids (NEAAs) are delineated. Amino acids with pharmacological significance are marked as PAA with “#”. Branched-chain amino acids (BCAAs) consist of Ile, Leu, and Val, while Total Amino Acids (TAAs) encompass the complete amino acid profile. Parameters such as RAA, RC, SRC, EAAI, BV, NI, and PER are pivotal in evaluating amino acid quality. RAA (Amino Acid Ratios) indicates the essential amino acid ratio to its recommended amount, shedding light on their presence in protein composition. RC (Ratio Coefficients) compares individual amino acids to the overall essential amino acid profile by relating a specific essential amino acid's RAA to the mean RAA of all essential amino acids. SRC (Amino Acid Scores), calculated as 100 − RSD × 100 with RSD as the relative standard deviation of RC, reflects the amino acid quality. EAAI (Essential Amino Acid Index) mirrors protein quality based on essential amino acid content. BV (Biological Value) evaluates protein utilization by the body, with higher values pointing to enhanced protein synthesis. NI (Nutritional Index) offers insights into protein value by examining the essential amino acid-protein content relationship. PER (Protein Efficiency Ratio) assesses a protein source's efficacy in growth and maintenance, with higher values indicating better protein utilization for these purposes. These parameters collectively serve to evaluate amino acid composition and quality, furnishing crucial information on the nutritional worth and bioavailability of dietary protein sources. All these parameters, along with the taste attributes of amino acids such as “umami (U)”, “bitter (B)”, “sweet (S)”, and “Aromatic flavor (A)”, were detailed in Tables 4 and 5.

For a detailed assessment of BKF4's nutritional quality, the ratio of amino acids (RAA), ratio coefficient (RC), and score of ratio coefficient (SRC), as defined by the FAO/WHO, were utilized. SRC values close to 100 indicate a higher protein nutritional value. The SRC values for GB, SK, and BKF4, scored on a percentage scale, were 54.86, 50.86, and 53.00, respectively, establishing a nutritional hierarchy of GB > BKF4 > SK. Moreover, higher E/N’ or E/T’ ratios suggest greater nutritional merit. When compared to the FAO/WHO's ideal protein benchmark, the E/T’ ratio for SK was below this standard, while the E/N’ ratios for GB and BKF4 exceeded it, underscoring BKF4's superior nutritional profile to SK.

The Essential Amino Acid Index’ (EAAI’) denotes the similarity of the EAA composition to the standard reference protein, with a value approaching 1 indicative of superior nutritional value. The EAAI’ values recorded for the samples stood at 93.12, 72.22, and 87.51 for GB, SK, and BKF4, respectively, reflecting a comparatively superior amino acid profile in BKF4 to SK.

Fatty acid composition

In beef and lamb, the intramuscular fat in muscle contains 45–48 g/100 g of saturated fatty acids (SFAs), 35–45 g/100 g of monounsaturated fatty acids (MUFAs), and up to 50 g/100 g of polyunsaturated fatty acids (PUFAs)³⁶. Table 6 presents the fatty acid profile identified in the intramuscular fat of the studied goat groups, revealing 18 different types of fatty acids. There are 6 types each of SFAs, MUFAs, and PUFAs, showing significant inter-group differences (p ≤ 0.01). Specifically, SFAs increased from 38.9 to 49.3%, MUFAs decreased from 48.2 to 42.9%, and PUFAs decreased from 12.8 to 7.9%, indicating an adverse shift in relative content. Furthermore, IMF, BCFAs, EFAs, UFAs, TFAs, n − 6, UI, DFA, OFA, and h/H all demonstrate the highest content in SK, followed by GB, and the lowest in BKF4 with significant differences (p ≤ 0.01). Both AI and TI values are markers for evaluating the risk of cardiovascular diseases. Higher values indicate a higher risk of cardiovascular diseases for individuals, yielding disappointingly negative outcomes. Despite this, n − 3 content in BKF4 significantly surpasses that in GB, particularly with a remarkable increase in three key bioactive fatty acids: ALA, EPA, and DHA, leading to a substantial reduction in the n − 6/n − 3 ratio from 28.9 in GB and 18.20 in SK to 6.56 in BKF4. In terms of individual fatty acids, most fatty acids exhibit a similar trend, except for eicosenoic acid.

Table 6.

Effects of cross-breeding on fatty acid compositiont of LD.

Parameter	Genotype (Gen)			P-value
	GB (N = 6)	SK (N = 6)	BKF4 (N = 6)
Intramuscular Fat (IMF; expressed as g/100 g fresh LD tissue)
IMF	3.05 ± 0.59B	6.08 ± 2.46A	4.40 ± 1.23B	≤ 0.001***
Saturated Fatty Acids (SFAs; expressed as mg/100 g fresh LD tissue)
Myristic acid (C14:0)	15.90 ± 1.92C	53.73 ± 2.84A	22.10 ± 1.61B	≤ 0.001***
Pentadecanoic acid (C15:0)	ND	15.50 ± 2.91A	7.76 ± 0.07B	≤ 0.001***
Palmitic acid (C16:0)	832.40 ± 104.0A	957.04 ± 47.51A	657.50 ± 45.05B	≤ 0.001***
Heptadecanoic acid(C17:0)	8.38 ± 0.29C	61.57 ± 1.40A	14.85 ± 3.60B	≤ 0.001***
Stearic acid (C18:0)	510.40 ± 75.61B	725.00 ± 46.13A	462.43 ± 42.43B	≤ 0.001***
Docosanoic acid(C22:0)	6.31 ± 1.95B	9.26 ± 0.07A	8.08 ± 0.07AB	0.002**
SFAs (g/100 g)	1.37 ± 0.16B	1.82 ± 0.01A	1.17 ± 0.08C	≤ 0.001***
Monounsaturated Fatty Acids (MUFA; expressed as mg/100 g fresh LD tissue)
Myristoleic acid (C14:1n5)	ND	5.45 ± 0.35	ND	–
Palmitoleic acid (C16:1n7)	44.58 ± 29.72b	98.97 ± 1.47a	49.90 ± 33.83b	0.004**
Eicosenoic acid(C20:1n7 + C20:1n9)	31.74 ± 2.47a	10.08 ± 0.29b	3.38 ± 0.46c	≤ 0.001***
Elaidic acid(C18:1n9t)	10.57 ± 2.01B	22.07 ± 1.53A	7.97 ± 0.14C	≤ 0.001***
Oleic acid (C18:1n9c)	1301.20 ± 172.81B	2120.00 ± 170.59A	956.75 ± 40.98C	≤ 0.001***
Erucic acid (C22:1n9)	ND	5.35 ± 0.33	ND	–
MUFAs (g/100 g)	1.39 ± 0.16B	2.26 ± 0.17A	1.02 ± 0.04B	≤ 0.001***
Polyunsaturated Fatty Acids (PUFA; expressed as mg/100 g fresh LD tissue)
Cis-11,14-eicosadienoic acid (C20:2n6)	10.76 ± 2.07	ND	ND	–
#Linoleic acid (LA, C18:2n6c)	259.01 ± 34.51B	442.0 ± 35.79A	117.25 ± 22.78C	≤ 0.001***
#Alpha-linolenic acid (ALA, C18:3n3)	10.59 ± 1.21C	18.17 ± 0.76A	14.21 ± 1.26B	≤ 0.001***
#Arachidonic acid (AA, C20:4n6)	46.59 ± 5.08B	130.33 ± 19.14A	44.88 ± 3.44B	≤ 0.001***
#EPA (C20:5n3)	ND	7.20 ± 0.28	7.17 ± 0.42	0.157
#DHA (C22:6n3)	ND	6.08 ± 0.07A	3.54 ± 0.41B	≤ 0.001***
PUFAs (g/100 g)	0.33 ± 0.04B	0.6 ± 0.03A	0.19 ± 0.02C	≤ 0.001***
Partial sums (g/100 g fresh LD tissue)
Branched-chain fatty acids (BCFAs)	0.84 ± 0.10B	1.03 ± 0.05A	0.68 ± 0.05C	≤ 0.001***
EFAs	0.32 ± 0.04B	0.60 ± 0.03A	0.19 ± 0.02C	≤ 0.001***
UFAs	1.72 ± 0.18B	2.87 ± 0.17A	1.21 ± 0.06C	≤ 0.001***
TFAs	3.09 ± 0.31B	4.69 ± 0.16A	2.38 ± 0.12C	≤ 0.001***
n − 6	0.31 ± 0.04B	0.57 ± 0.03A	0.16 ± 0.02C	≤ 0.001***
n − 3	0.01 ± 0.00C	0.03 ± 0.00A	0.02 ± 0.00B	≤ 0.001***
Ratios (%)
PUFAs/SFAs	24.10 ± 4.32B	33.14 ± 1.69A	15.95 ± 1.33C	≤ 0.001***
PUFAs/MUFAs	23.66 ± 2.92A	26.74 ± 2.38A	18.36 ± 1.56B	≤ 0.001***
UFAs/TFAs	55.56 ± 2.21B	61.12 ± 1.46A	50.70 ± 1.73C	≤ 0.001***
SFAs:MUFAs:PUFAs:EFAs	1:1.01:0.24:0.23	1:1.24:0.33:0.33	1:0.87:0.16:0.16
Evaluation Index
UI	1.74 ± 0.18B	3.13 ± 0.1A	1.36 ± 0.04C	≤ 0.001***
AI (%)	52.80 ± 6.27B	40.92 ± 2.22C	61.96 ± 3.86A	≤ 0.001***
DFA (g/100 g)	2.23 ± 0.25B	3.59 ± 0.15A	1.67 ± 0.09C	≤ 0.001***
OFA (g/100 g)	0.85 ± 0.1B	1.01 ± 0.04A	0.68 ± 0.05C	≤ 0.001***
TI	1.5 ± 0.14B	1.14 ± 0.06C	1.7 ± 0.10A	≤ 0.001***
h/H	1.93 ± 0.28B	2.71 ± 0.16A	1.68 ± 0.11B	≤ 0.001***
n − 6/ n − 3	28.90 ± 2.49A	18.20 ± 0.94B	6.56 ± 1.22C	≤ 0.001***

In this study, BCFAs such as iso C15:0, iso C16:0, iso C17:0, anteiso C15:0, and anteiso C17:0, play crucial physiological roles, participating in various metabolic processes and physiological regulations. The Unsaturation Index (UI) quantifies the overall unsaturation level of fatty acids in a sample, with higher values indicating a greater proportion of unsaturated fatty acids. Furthermore, the Atherogenic Index (AI) predicts the potential atherogenicity of dietary fats, with higher values indicating a higher likelihood of promoting atherosclerosis and cardiovascular disease risk. In addition, the Thrombogenic Index (TI) evaluates the thrombogenic potential of dietary fats, where higher values suggest a greater propensity for blood clot formation, impacting cardiovascular health and thrombotic events. Moreover, DFA (Hypocholesterolemic Fatty Acids) can lower cholesterol levels, while OFA (Hypercholesterolemic Fatty Acids) may elevate cholesterol levels, with monitoring their balance offering insights into cholesterol levels and cardiovascular health. The Hypocholesterolemic/Hypercholesterolemic ratio (h/H) reflects the balance between cholesterol-lowering and cholesterol-raising effects of fatty acids, important for cardiovascular and cholesterol management. Notably, the n − 6 (Omega-6 fatty acids) include C18:2, C20:3, and C20:4, while n − 3 (Omega-3 fatty acids) comprise C18:3, C20:5, C22:5, and C22:6. Evaluating the n − 6/ n − 3 ratio to assess the balance between omega-6 and omega-3 polyunsaturated fatty acids is crucial for overall health and inflammation prevention. Moreover, fatty acids labeled with “#” are Essential Fatty Acids, with ND indicating non-detection. UFAs and TFAs stand for Unsaturated Fatty Acids and Total Fatty Acids, respectively. The specifics are outlined in Table 6.

Principal component analysis (PCA)

This study employed Principal Component Analysis (PCA) to thoroughly assess the value of BKF4³⁷. After Z-score standardization of the original data, the eigenvalues and contribution rates of the principal components were computed, as detailed in Table 7. The analysis indicated that the quality influence factors of the three goat groups were predominantly governed by two principal components, which contributed 83.49% and 16.51%, respectively, to the variance explained. The mathematical expressions for these principal components, derived using data from Tables 7 and 8, were as follows:

$$\begin{array}{cc}\hfill {\text{y}}_1& =-0.017X_{\text{pH45}}+0.061X_{\text{DL}}-0.162X_{\text{MC}}-0.018X_{\text{Ash}}+0.152X_{\text{CP}}-0.136X_{\text{IMF}}\hfill \\ \hfill & +0.161X_{\text{EAAs}}+0.164X_{\text{CEAAs}}-0.164X_{\text{NEAAs}}+0.162X_{\text{PAAs}}+0.156X_{\text{TAAs}}+0.145X_{\text{BCAAs}}\hfill \\ \hfill & +0.165X_{\text{PAAs}/\text{TAAs}}+0.163X_{\text{EAAs}/\text{TAAs}}+0.163X_{\text{EAAs}/\text{NC}}+0.159X_{\text{EAAI}}+0.129X_{\text{SRC}}\hfill \\ \hfill & -0.165X_{\text{NI}}+0.159X_{\text{BV}}-0.157X_{\text{PER}}+0.157X_{\text{Umami}}+0.164X_{\text{Bitterness}}+0.163X_{\text{Sweetness}}\hfill \\ \hfill & +0.151X_{\text{Aromatic flavor}}+0.164X_{\left(\text{U}+\text{S}+\text{A}\right)/\text{B}}+0.163X_{\text{SFAs}}-0.163X_{\text{MUFAs}}-0.162X_{\text{PUFAs}}\hfill \\ \hfill & -0.156X_{\text{BCFAs}}-0.163X_{\text{EFAs}}-0.163X_{\text{UFAs}}-0.163X_{\text{TFAs}}+0.161X_{\text{n}-6}-0.130X_{\text{n}-3}\hfill \\ \hfill & -0.155X_{\text{PUFAs}/\text{SFAs}}-0.142X_{\text{PUFAs}/\text{MUFAs}}-0.155X_{\text{UFAs}/\text{TFAs}}-0.165X_{\text{UI}}-0.157X_{\text{AI}}\hfill \\ \hfill & -0.163X_{\text{DFA}}+0.152X_{\text{OFA}}-0.161X_{\text{TI}}-0.164X_{\text{h}/\text{H}}+0.028X_{\text{n}-6/\text{n}-3}\hfill \\ \hfill \end{array}$$

$$\begin{array}{cc}\hfill {\text{y}}_2& =-0.369X_{\text{pH45}}-0.345X_{\text{DL}}+0.076X_{\text{MC}}+0.369X_{\text{Ash}}-0.142X_{\text{CP}}-0.211X_{\text{IMF}}\hfill \\ \hfill & +0.085X_{\text{EAAs}}+0.046X_{\text{CEAAs}}+0.049X_{\text{NEAAs}}+0.066X_{\text{PAAs}}+0.119X_{\text{TAAs}}+0.177X_{\text{BCAAs}}\hfill \\ \hfill & +0.014X_{\text{PAAs}/\text{TAAs}}+0.061X_{\text{EAAs}/\text{TAAs}}+0.062X_{\text{EAAs}/\text{NC}}+0.097X_{\text{EAAI}}+0.231X_{\text{SRC}}\hfill \\ \hfill & -0.026X_{\text{NI}}+0.101X_{\text{BV}}-0.113X_{\text{PER}}+0.{\text{114 X}}_{\text{Umami}}+0.037X_{\text{Bitterness}}+0.059X_{\text{Sweetness}}\hfill \\ \hfill & +0.149X_{\text{Aromatic flavor}}+0.032X_{\left(\text{U}+\text{S}+\text{A}\right)/\text{B}}-0.059X_{\text{SFAs}}+0.056X_{\text{MUFAs}}+0.073X_{\text{PUFAs}}\hfill \\ \hfill & +0.12X_{\text{BCFAs}}+0.063X_{\text{EFAs}}+0.059X_{\text{UFAs}}+0.059X_{\text{TFAs}}-0.083X_{\text{n}-6}-0.\text{23 X34}\hfill \\ \hfill & +0.127X_{\text{PUFAs}/\text{SFAs}}+0.188X_{\text{PUFAs}/\text{MUFAs}}+0.124X_{\text{UFAs}/\text{TFAs}}+0.023X_{\text{UI}}+0.111X_{\text{AI}}+0.053X_{\text{DFA}}\hfill \\ \hfill & -0.144X_{\text{OFA}}+0.079X_{\text{TI}}+0.034X_{\text{h}/\text{H}}-0.366X_{\text{n}-6/\text{n}-3}\hfill \\ \hfill \end{array}$$

Table 7.

Eigenvalues and contribution rate of the principal components.

Main components	Eigenvalues	Contribution rate, %	Cumulative contribution rate, %
P1	36.736	83.49	83.49
P2	7.264	16.51	100.00

Table 8.

Loading matrix of principal components.

Factor	XIMF	XNI	XP/MUFAs	Xn−6	XDL	XAromatic	XMUFAs	XUmami	XDFA	XMC	XpH45-value	XTI	XPAAs	Xh/H	XAsh
P1	− 0.823	− 0.998	− 0.863	0.975	0.371	0.916	− 0.989	0.952	− 0.99	− 0.979	− 0.102	− 0.977	0.984	− 0.996	− 0.11
P2	− 0.569	− 0.07	0.506	− 0.224	− 0.929	0.402	0.15	0.307	0.143	0.205	− 0.995	0.214	0.179	0.091	0.994
	1.00054	1.00045	1.00040	1.00040	1.00034	1.00033	1.00031	1.00028	1.00027	1.00023	1.00021	1.00016	1.00015	1.00015	1.00007
Factor	XAI	XEAAs/NC	Xn−6/n−3	XSRC	XBV	XBCFAs	XEAAI	XOFA	XTAAs	XBitterness	XSFAs	XUFAs	XTFAs	XUI	XCP
P1	− 0.954	0.986	0.167	0.783	0.962	− 0.946	0.965	0.922	0.947	0.995	0.987	− 0.987	− 0.987	− 0.998	0.924
P2	0.3	0.167	− 0.986	0.622	0.273	0.324	0.262	− 0.387	0.321	0.099	− 0.16	0.16	0.16	0.061	− 0.382
	1.00006	1.00004	1.00004	0.99999	0.99999	0.99995	0.99993	0.99993	0.99992	0.99991	0.99988	0.99988	0.99988	0.99986	0.99985
Factor	XEAAs	XU+S+A/B	XNEAAs	XEFAs	XCEAAs	XE/TAAs	Xn−3	XP/TAAs	XPU/SFAs	XBCAAs	XPER	XPUFAs	XSweetness	XU/TFAs
P1	0.973	0.996	− 0.991	− 0.985	0.992	0.986	− 0.785	0.999	− 0.939	0.878	− 0.952	− 0.98	0.987	− 0.942
P2	0.23	0.087	0.132	0.171	0.124	0.165	− 0.619	0.037	0.343	0.478	− 0.305	0.197	0.158	0.334
	0.99981	0.99979	0.99975	0.99973	0.99972	0.99971	0.99969	0.99968	0.99968	0.99968	0.99966	0.9996	0.99957	0.99946

As shown in Table 8, the order of impact on the quality of goats is listed. In the context of principal component analysis (PCA), variables that exhibit significant positive and negative influences on P1 and P2 respectively are listed.

Additionally, as shown in Table 8, the order of impact on the quality of goats is IMF, NI, PUFAs/MUFAs, n − 6, DL, Aromatic flavor, MUFAs, Umami, DFA, MC, pH₄₅-value, TI, PAAs, h/H, Ash, etc. In the context of principal component analysis (PCA), variables such as PAAs/TAAs, U + S + A/B, Bitterness, CEAAs, Sweetness, SFAs, EAAs/TAAs, EAAs/NC, PAAs, n − 6, EAAs, EAAI, BV, Umami, TAAs, CP, OFA, and Aromatic flavor exhibit significant positive influences on P1, all above 0.9, predominantly associating with protein and flavor attributes. Conversely, variables like UI, NI, h/H, NEAAs, DFA, MUFAs, UFAs, TFAs, EFAs, PUFAs, MC, TI, AI, PER, BCFAs, UFAs/TFAs, and PUFAs/SFAs demonstrate substantial negative influences on P1, also all above 0.9, primarily aligning with fatty acids and amino acids. This distinction underscores P1's role in differentiating variables related to protein and flavor (positive loadings) from those related to fatty acids and amino acids (negative loadings). For P2, variables such as Ash (0.994), SRC (0.622), PUFAs/MUFAs (0.506), BCAAs (0.478), Aromatic (0.402), PUFAs/SFAs (0.343), UFAs/TFAs (0.334), BCFAs (0.324), TAAs (0.321), Umami (0.307), and AI (0.3) show substantial positive influence, primarily associated with ash content, fatty acid ratios, amino acids, and flavor. In contrast, variables like pH₄₅-value (0.995), n − 6/n − 3 (0.986), DL (0.929), n − 3 (0.619), IMF (0.569), OFA (0.387), CP (0.382), PER (0.305), n − 6 (0.224), and SFAs (0.16) exhibit significant negative influence, correlating with pH₄₅-value, fatty acid ratios, and protein quality and quantity. This delineation indicates that P2 primarily separates variables related to pH₄₅-value, fatty acid ratios, and protein content and quality (negative loadings) from those related to ash content, fatty acid ratios, amino acids, and flavor (positive loadings).

Table 9 presents the partial correlations between physicochemical characteristics and meat quality indices. pH₄₅-value shows positive correlations with DL (0.886), n − 3 (0.696), and IMF (0.649), while displaying negative correlations with Ash ( − 0.978) and SRC ( − 0.698). DL is positively correlated with n − 6/n − 3 (0.978), pH₄₅-value (0.886), OFA (0.701), and CP (0.698), and negatively correlated with Ash ( − 0.964) and AI ( − 0.633). MC shows similarities with TI (1.000), DFA (0.998), AI (0.995), h/H (0.993), UI (0.99), NI (0.962), PER (0.87), IMF (0.689), and n − 3 (0.642), and also shows negative correlations with n − 6 (− 1.000), CP (− 0.983), OFA (− 0.982), bitterness (− 0.954), sweetness (− 0.934), EAAI (− 0.891), BV (− 0.886), umami (− 0.814), and aromatic flavor (− 0.64). Ash demonstrates significant positive correlations with SRC (0.532) and AI (0.403), and significant negative correlations with n − 6/n − 3 (− 0.998), n − 3 (− 0.529), OFA (− 0.486), CP (− 0.481), and IMF (− 0.475). CP shows similarities with OFA, n − 6 (0.986), bitterness (0.882), sweetness (0.852), EAAI (0.792), BV (0.785), umami (0.762), and aromatic flavor (0.693), and also exhibits negative correlations with AI (− 0.996), TI (− 0.985), DFA (− 0.969), h/H (− 0.955), UI (− 0.946), NI (− 0.895), and PER (− 0.763). IMF shares similarities with n − 3 (0.999), PER (0.957), NI (0.861), UI (0.786), h/H (0.768), DFA (0.733), TI (0.682), and AI (0.614), and also shows negative correlations with SRC (− 0.998), aromatic flavor (− 0.982), umami (− 0.958), BV (− 0.947), EAAI (− 0.943), sweetness (− 0.902), bitterness (− 0.875), and n − 6 (− 0.674). In the assessment of amino acid indicators, apart from pH₄₅, DL, MC, Ash, and n − 6/ n − 3, NI and PER are negatively correlated with EAAI, while BV, umami, bitterness, sweetness, aromatic flavor, and SRC show positive correlations with EAAI, exhibiting similarities in their correlations with EAAI. In the evaluation of fatty acid indicators, excluding pH₄₅, DL, MC, Ash, and n − 6/ n − 3, OFA is positively correlated with n − 6, whereas UI, AI, DFA, TI, and h/H are negatively correlated with n − 6, demonstrating similarities in their correlations. The distribution of various variables across the two principal components (Principal Component 1 and Principal Component 2) is illustrated in Fig. 2.

Table 9.

Correlation coefficient between physicochemical traits and meat quality evaluation coefficients in three groups of goats.

	pH45-value	DL	MC	Ash	CP	IMF	EAAI	SRC	NI	BV	PER	U	B	S	A	n − 6	n − 3	UI	AI	DFA	OFA	TI	h/H	n − 6/ n − 3
pH45-value	1
DL	0.886	1
MC	− 0.104	− 0.553	1
Ash	− 0.978	− 0.964	0.311	1
CP	0.286	0.698	− 0.983	− 0.481	1
IMF	0.649	0.223	0.689	− 0.475	− 0.543	1
EAAI	− 0.358	0.115	− 0.891	0.154	0.792	− 0.943	1
SRC	− 0.698	− 0.287	− 0.64	0.532	0.486	− 0.998	0.919	1
NI	0.171	− 0.304	0.962	0.04	− 0.895	0.861	− 0.981	− 0.825	1
BV	− 0.369	0.103	− 0.886	0.166	0.785	− 0.947	1	0.923	− 0.979	1
PER	0.4	− 0.07	0.87	− 0.199	− 0.763	0.957	− 0.999	− 0.936	0.971	− 0.999	1
U	− 0.402	0.067	− 0.869	0.201	0.762	− 0.958	0.999	0.937	− 0.971	0.999	− 1	1
B	− 0.2	0.277	− 0.954	− 0.011	0.882	− 0.875	0.986	0.841	− 1	0.984	− 0.978	0.977	1
S	− 0.257	0.219	− 0.934	0.048	0.852	− 0.902	0.994	0.872	− 0.996	0.993	− 0.989	0.988	0.998	1
A	− 0.492	− 0.033	− 0.814	0.299	0.693	− 0.982	0.989	0.967	− 0.942	0.991	− 0.995	0.995	0.951	0.968	1
n − 6	0.124	0.569	− 1	− 0.33	0.986	− 0.674	0.882	0.624	− 0.956	0.876	− 0.86	0.859	0.948	0.927	0.803	1
n − 3	0.696	0.284	0.642	− 0.529	− 0.489	0.998	− 0.92	− 1	0.827	− 0.925	0.937	− 0.938	− 0.843	− 0.873	− 0.968	− 0.627	1
UI	0.04	− 0.427	0.99	0.171	− 0.946	0.786	− 0.947	− 0.744	0.991	− 0.943	0.932	− 0.931	− 0.987	− 0.976	− 0.889	− 0.986	0.746	1
AI	− 0.202	− 0.633	0.995	0.403	− 0.996	0.614	− 0.842	− 0.56	0.93	− 0.835	0.817	− 0.815	− 0.919	− 0.894	− 0.753	− 0.997	0.563	0.97	1
DFA	− 0.042	− 0.5	0.998	0.251	− 0.969	0.733	− 0.918	− 0.686	0.977	− 0.913	0.899	− 0.898	− 0.971	− 0.955	− 0.849	− 0.997	0.689	0.997	0.987	1
OFA	0.291	0.701	− 0.982	− 0.486	1	− 0.539	0.789	0.482	− 0.893	0.781	− 0.76	0.759	0.879	0.85	0.689	0.985	− 0.485	− 0.944	− 0.996	− 0.968	1
TI	− 0.114	− 0.561	1	0.32	− 0.985	0.682	− 0.887	− 0.632	0.959	− 0.881	0.865	− 0.864	− 0.951	− 0.931	− 0.808	− 1	0.634	0.988	0.996	0.997	− 0.984	1
h/H	0.011	− 0.453	0.993	0.2	− 0.955	0.768	− 0.937	− 0.724	0.987	− 0.933	0.921	− 0.92	− 0.982	− 0.969	− 0.876	− 0.991	0.726	1	0.977	0.999	− 0.953	0.992	1
n − 6/n − 3	0.964	0.978	− 0.366	− 0.998	0.532	0.423	− 0.096	− 0.482	− 0.098	− 0.108	0.141	− 0.144	0.069	0.01	− 0.242	0.384	0.479	− 0.228	− 0.456	− 0.307	0.536	− 0.375	− 0.256	1

Table presents the partial correlations between physicochemical characteristics and meat quality indices. There are complex positive and negative correlations between different indices.

Figure 2.

Principal component map of three groups of goats.

Furthermore, integrating the data from Tables 7 and 8, a comprehensive evaluation function for the principal components was developed, represented as: Y = 0.8349 y₁ + 0.1651 y₂. In this function, Y denotes the score factor, while y₁ and y₂ are the expressions for the two principal components. This formula allows for the calculation of comprehensive score values and rankings for meat quality among the three goat groups. According to the results presented in Table 10, the ranking in terms of meat quality is as follows: BKF4 > GB > SK.

Table 10.

Principal component scores and comprehensive scores of three goat varieties.

Principal component	y1	y2	Y	Rank
BKF4	4.33	− 2.44	3.21	1
GB	2.59	2.89	2.64	2
SK	− 6.93	− 0.45	− 5.86	3

This study employed Principal Component Analysis (PCA) to thoroughly assess the value of BKF4³⁷. After Z-score standardization of the original data, the eigenvalues and contribution rates of the principal components were computed, as detailed in Table 7. The analysis indicated that the quality influence factors of the three goat groups were predominantly governed by two principal components, which contributed 83.49% and 16.51%, respectively, to the variance explained. The mathematical expressions for these principal components, derived using data from Tables 7 and 8, were as follows:

y₁ = − 0.017 X_pH45 + 0.061 X_DL − 0.162 X_MC − 0.018 X_Ash + 0.152 X_CP − 0.136 X_IMF + 0.161 X_EAAs + 0.164 X_CEAAs − 0.164 X_NEAAs + 0.162 X_PAAs + 0.156 X_TAAs + 0.145 X_BCAAs + 0.165 X_PAAs/TAAs + 0.163 X_EAAs/TAAs + 0.163 X_EAAs/NC + 0.159 X_EAAI + 0.129 X_SRC − 0.165 X_NI + 0.159 X_BV − 0.157 X_PER + 0.157 X_Umami + 0.164 X_Bitterness + 0.163 X_Sweetness + 0.151 X_{Aromatic flavor} + 0.164 X_(U+S+A)/B + 0.163 X_SFAs − 0.163 X_MUFAs − 0.162 X_PUFAs − 0.156 X_BCFAs − 0.163 X_EFAs − 0.163 X_UFAs − 0.163 X_TFAs + 0.161 X_n−6 − 0.130 X_n−3 − 0.155 X_PUFAs/SFAs − 0.142 X_PUFAs/MUFAs − 0.155 X_UFAs/TFAs − 0.165 X_UI − 0.157 X_AI − 0.163 X_DFA + 0.152 X_OFA − 0.161 X_TI − 0.164 X_h/H + 0.028 X_n−6/n−3.

y₂ = − 0.369 X_pH45 − 0.345 X_DL + 0.076 X_MC + 0.369 X_Ash − 0.142 X_CP − 0.211 X_IMF + 0.085 X_EAAs + 0.046 X_CEAAs + 0.049 X_NEAAs + 0.066 X_PAAs + 0.119 X_TAAs + 0.177 X_BCAAs + 0.014 X_PAAs/TAAs + 0.061 X_EAAs/TAAs + 0.062 X_EAAs/NC + 0.097 X_EAAI + 0.231 X_SRC − 0.026 X_NI + 0.101 X_BV − 0.113 X_PER + 0.114 X_Umami + 0.037 X_Bitterness + 0.059 X_Sweetness + 0.149 X_{Aromatic flavor} + 0.032 X_(U+S+A)/B − 0.059 X_SFAs + 0.056 X_MUFAs + 0.073 X_PUFAs + 0.12 X_BCFAs + 0.063 X_EFAs + 0.059 X_UFAs + 0.059 X_TFAs − 0.083 X_n−6 − 0.23 X34 + 0.127 X_PUFAs/SFAs + 0.188 X_PUFAs/MUFAs + 0.124 X_UFAs/TFAs + 0.023 X_UI + 0.111 X_AI + 0.053 X_DFA − 0.144 X_OFA + 0.079 X_TI + 0.034 X_h/H − 0.366 X_n−6/n−3.

Furthermore, integrating the data from Tables 7 and 8, a comprehensive evaluation function for the principal components was developed, represented as: Y = 0.8349 y₁ + 0.1651 y₂. In this function, Y denotes the score factor, while y₁ and y₂ are the expressions for the two principal components. This formula allows for the calculation of comprehensive score values and rankings for meat quality among the three goat groups. According to the results presented in Table 10, the ranking in terms of meat quality is as follows: BKF4 > GB > SK.

Discussion

Reproductive and production performance

Cross breeding is an important way to improve livestock performance^9,19. Reproductive and production traits are economically significant in animal production. Enhancing these traits signifies enhanced productivity and profitability and is typically regarded as the top priority in breeding programs^38,39. Through three generations of progressive hybridization and molecular breeding, the lambing rate of BKF4 goats achieved 199% via the technology of cross-fixation. This rate notably surpasses that of the parent breeds. Additionally, BKF4 goats maintained a high survival rate of 95.1%, demonstrating commendable performance in environmental adaptability and animal well-being. In terms of growth performance, BKF4 goats benefit from the genetic characteristics of South African Kalahari goats, with an average daily weight gain of 276.5 ± 25.4 g at three months of age, twice the growth rate of Guizhou black goats. Slaughter performance stands as a pivotal metric for assessing livestock production capabilities. In this aspect, the adult body weight of BKF4 goats increased from 49 kg to 56.6 kg, and the dressing percentage escalated from 40.4 to 54.5%. This resulted in a profit surge of over 20%, notably boosting effectiveness.

Meat quality indicators

pH₄₅-value and drip loss (DL) are crucial parameters in assessing meat quality, influenced by factors including breed selection, nutrition levels, and feeding practices⁴⁰. Post-slaughter, heightened glycolytic activity in muscles accelerates ATP hydrolysis and muscle glycogen breakdown to lactate, causing a decline in muscle pH and subsequent meat degradation^41,42. The rate of pH decrease is directly linked to the pace of biochemical changes in meat, impacting important quality traits like water loss, color, tenderness, and flavor⁴³. A higher pH leads to slower anaerobic glycolysis of muscle glycogen, less water exudation loss, enhanced protein stability, and improved meat freshness⁴⁴. Additionally, pH₄₅-value is closely related to drip loss, as it can lower pH close to the protein's isoelectric point, reducing negative charges on fibers and lessening electrostatic repulsion. Lower pH levels also create larger gaps between myosin and actin filaments and decrease muscle fiber space⁴⁵. Drip loss is also influenced by intramuscular fat (IMF) content and distribution, with higher IMF values associated with decreased drip loss². This parameter serves as a key indicator of muscle water-holding capacity and significantly impacts the loss of marketable meat and its quality, affecting nutritional value, color, texture, flavor, and juiciness¹². Within the three groups studied, the pH₄₅-values were 5.47 for GB, 6.18 for SK, and 6.46 for BKF4, whereas DL values were recorded at 4.47% for GB, 3.6% for SK, and only 1.44% for BKF4. Furthermore, the ash contents of SK and BKF4 are statistically similar at 4.29% and 3.65%, respectively, with corresponding moisture levels of 74.65% in GB and 73.4% in BKF4. The decreased drip loss in BKF4 compared to the parental strain is in line with previous research findings^46,47, suggesting potentially enhanced juiciness in BKF4. The ash content, negatively correlated with the values of pH₄₅, DL and IMF, primarily consisting of minerals such as inorganic salts and metallic elements, serves as an indicator of the mineral content in food. Minerals are crucial for tissue formation and maintaining normal physiological functions, and they must be obtained from dietary sources as they cannot be synthesized by the human body. Thus, the content of mineral elements in food is of significant importance⁴⁸. Compared to GB, an increase in ABW is associated with decreased ash content and elevated protein content in BKF4, consistent with the findings of A. Zullo et al.⁴⁹, where the increase in protein content may also be attributed to a reduction in moisture content⁵⁰.

IMF plays a crucial role in palatability and consumer preferences of meat, showing a positive correlation with tenderness, flavor, juiciness, and overall acceptability^37,51–53, and it is linked to variables such as age, gender, and diet⁵⁴. Meat fat and moisture content typically demonstrate a negative correlation⁵⁵. Consumer preference for goat meat significantly increases at an IMF level of 3%, peaks at 4%, and continues to rise with higher IMF content³⁷. Optimal flavor richness is achieved when the IMF ranges between 3.4 and 4.5%⁴⁸. Sensory scores for juiciness, overall liking, flavor, and tenderness of loins increased across the IMF range of 2.5% to 7.0% by 10.7, 10.0, 9.1 and 5.9 units on a 0–100 scale⁵⁶. The IMF of the BKF4 group is 4.4%, which falls within consumers' preferred range. Previous research has shown that the expression levels of the H-FABP and ADSL genes can influence the content of IMF and IMP, indirectly contributing to the formation of muscle tenderness, juiciness, flavor, and freshness^40,57.

Protein and amino acids

In the context of dietary needs regarding nitrogen balance and growth, amino acids (AAs) are nutritionally defined as essential (indispensable), conditionally essential or nonessential (dispensable) for human protein synthesis and specific physiological structures and functions^26,58,59. High-quality proteins are characterized by a complete range of amino acids and a balanced proportion of essential amino acids (EAAs). BKF4 demonstrates higher levels of CP, EAAs, CEAAs, PAAs, BCAAs, TAAs, EAAI, SRC, NI, BV compared to SK, showing overall superiority in amino acid content and quality, with no significant difference between BKF4 and GB. BCAAs, including leucine, isoleucine, and valine, which cannot be synthesized by the human body, are often consumed by athletes or supplemented to healthy neonates, enhancing the activity of glutathione transferase (GST) and catalase⁵⁸. Lysine, as a therapeutic amino acid, plays a crucial role in promoting growth, enhancing mineral absorption, and boosting immune function⁶⁰. Arginine can promote the secretion of endogenous substances such as white blood cells and macrophages by the immune system, enhancing immunity⁴⁸. Following the FAO/WHO recommended model, BKF4's essential amino acid content has increased from 38.4% and 44.17% respectively to 51.53%. BKF4's EAAI value is 87.51, slightly lower than the GB group's 93.12 but significantly higher than the SK group's 72.22, indicating an overall enhancement in the meat quality of the hybrid goats. With the highest NI and BV values among the three groups, this suggests an improved amino acid profile and value of the meat from the hybrid goats. Furthermore, CP values exhibit positive correlations with EAAI and BV, as well as with bitterness, sweetness, umami, and aromatic flavor. Regarding flavor, amino acids, inosine, and peptides are crucial flavor precursors in meat, and their breakdown enhances the sensory attributes and taste of meat⁴⁶. The balance of bitterness (B), umami (U), sweetness (S), and aromatic flavors (A) (B:U:S:A ratio) in the three groups of goats suggests that the flavor profile of BKF4 is more similar to that of SK. Additionally, the increased levels of glutamate, lysine, serine, and alanine in the muscle significantly enhance the flavor (or aroma) of goat meat⁶¹.

Intramuscular fat and fatty acids

Intramuscular fat is predominantly composed of fatty acids, which are influenced by various factors such as species, cultivar, climate, and management, posited to render goat meat relatively healthier compared to other red meats^5,51. In the present study, the intramuscular fat (IMF) content of BKF4 (ranging from 3.17 to 5.63 g/100 g) falls between those of GB (2.46 to 3.64 g/100 g) and SK (3.24 to 8.92 g/100 g). It is positively correlated with n − 3, UI, h/H, DFA, TI, and AI, while displaying a negative correlation with n − 6. Overall, the levels of SFAs, MUFAs, PUFAs, BCFAs, and TFAs decreased, altering the ratios of SFAs:MUFAs:PUFAs:EFAs (GB vs SK vs BKF4, 1:1.01:0.24:0.23 vs 1:1.24:0.33:0.33 vs 1:0.87:0.16:0.16). This demonstrates a reduction in the proportions of MUFAs, PUFAs, and EFAs, leading to a lowered PUFA/SFA ratio (GB: 19.78% to 28.42%; SK: 31.45% to 34.83%; BKF4: 14.62% to 17.28%), significantly deviating from the recommended ratio of ≥ 0.45^62–65. Specific fatty acid contents varied, with some at intermediary levels and others significantly lower than those of the parental breeds. These discrepancies resulted in lower UI, DFA, h/H values, and higher AI, TI, leading to deteriorated meat quality, consistent with previous research findings^38,61. Encouragingly, n − 3 FAs increased in the hybrid offspring, with detectable levels of EPA and DHA that were absent in GB. Meanwhile, n − 6 FAs such as C_18:2n6 and C_20:4n6 decreased, reducing the n − 6/ n − 3 ratio from 26.41 to 31.39 in GB and 17.26 to 19.14 in SK, to 5.34 to 7.78 in BKF4. The recommended n − 6/ n − 3 ratio is usually ≤ 4^63,64,66. Studies have shown that a change in the n − 6/ n − 3 ratio from 1:1 to 15–20:1 may lead to metabolic disorders, causing symptoms such as insulin resistance, hyperinsulinemia, obesity, while n − 3 FAs and monounsaturated fatty acids have a protective effect against heart disease⁶⁷. C18:3n3 plays a key role in reducing blood lipids and blood sugar, antioxidation, antibacterial and antiinflammatory, and the development of brain and retinal^43,68. Additionally, extensive research indicates that saturated fatty acids (SFA) and trans fatty acids heighten cardiovascular risk⁶⁹, with excessive SFA intake potentially raising levels of both high-density lipoprotein (HDL) and low-density lipoprotein (LDL), thereby increasing the risk of atherosclerosis and coronary heart disease⁷⁰. Elevated levels of PUFAs/SFAs and oleic acid (comprising approximately 95% of MUFA) are beneficial in reducing serum cholesterol, lowering the risk of atherosclerosis, and preventing heart diseases^71,72. Replacing 1% of dietary SFAs with polyunsaturated fatty acids (PUFAs) is believed to reduce low-density lipoprotein (LDL) cholesterol by 2% or 3%⁷³. Furthermore, unsaturated fatty acids (USFAs) are known for their beneficial impact on the flavor, texture, and nutritional value of goat meat, with a significant correlation between the n − 6/ n − 3 ratio and meat flavor. Additionally, the oxidation of stearic acid (C_18:0) and other saturated fatty acids can generate volatile compounds, influencing consumer acceptability^6,74.

Research indicates that the FA composition of ruminant edible fats is mostly determined by complex interactions between dietary factors and rumen metabolism⁷⁵. Meat produced from forage-fed animals is considered superior to grain-fed counterparts, being rich in medium-chain fatty acids and antioxidants, with certain plant species potentially enhancing this further^36,51.Furthermore, supplementation of fats or specific mixed feeds can enhance meat nutritional quality, increasing levels of oleic acid, linoleic acid, linolenic acid, and long-chain PUFAs (such as DHA and EPA), elevating n − 3 FA levels and anticancer properties^64,76. Hence, adjusting dietary practices, feeding schedules, and other critical factors such as stress conditions can modulate and alter the fatty acid composition, thereby enhancing the quality of hybrid goat meat⁷⁷. Integrating edible quality traits into goat genetic improvement programs and employing novel methods such as molecular breeding and non-destructive detection techniques (such as near-infrared spectroscopy, ultrasound, CT imaging) hold promise for screening goats with specific fatty acid phenotypes^23,78,79.

Conclusions

The hybrid goat BKF4, bred through four generations of crossbreeding and six years of advanced molecular techniques, demonstrates high adaptability, strong reproduction and production performance, and notable economic benefits. In terms of meat quality, BKF4 outperforms the South African Kalahari Goat but slightly trails the Guizhou Black goat. It shows high protein content, increased intramuscular fat, enhanced water retention, and reduced ash content. Despite the negative effects on fatty acid composition and functionality, BKF4's amino acid profile resembles that of the Guizhou Black goat, and its taste is akin to the South African Kalahari Goat (SK). This prompts the need for improvements through molecular selection, non-destructive testing, and dietary adjustments in future phases.

Author contributions

M.Y.: Writing—original draft; L.C.: Writing—review and editing; S.X.: Methodology; J.Z.: Writing—review and editing; P.L.: Data curation; B.T.: Formal analysis; L.L.: Data curation; D.Y.: Resources; Q.L.: Funding acquisition; X.Z.: Conceptualization. All authors reviewed the manuscript.

Funding

This study was funded by the Guizhou Provincial Science and Technology Planning Project (Qiankehe Support [2019] No. 2279) and the 2023 Modern Breeding Industry Development Project (Collection and Preservation of Local Livestock and Poultry Genetic Materials in Guizhou).

Data availability

All data generated or analysed during this study are included in this published article [and its supplementary information files].

Competing interests

Patent applicant：Guizhou Testing Center for Livestock and Poultry Germplasm； inventor names：Qingmeng Long; Ping Li; Min Yao; Junsong Zhang; Fei Gong; Xiaoshan Tan; Jinrong Shen; Fu Wang; Li Xiong; Bing Yu; Chen Li; Lingling Xie; Chaoli Xiong; Danpin Yang; Xiaoyi Gao; Runxia He; Xia Tang; Mingzong Tang; Jin Zeng; Yunsong Zhang; Jingjing Yang; Junwei Zhang; Mingyan Tang; Yin Shen; Yu Wu; Li Shen; Enjun Yang; Futao Cai; Yuanheng Wang；application number: CN202310185414.5. Status of application: Patent has been authorized. Specific aspect of the manuscript covered in the patent application. Specific Hybrid Breeding Methods addressed in the manuscript. All the remaining authors declare no conflict of interest.

Supplementary Information

The online version contains supplementary material available at 10.1038/s41598-024-69174-0.