Impact of dietary supplementation of black soldier fly larvae (Hermetia illucens L.) on nutrient digestibility, serum antioxidants, ruminal volatile fatty acids, and abundance of microbial dominant flora in goats

Abstract

This experiment aimed to investigate the potential impact of supplementing different levels of black soldier fly (BSF) on growth performance, serum antioxidants, and ruminal microbiota of goats. Twenty-four native Anglo-Thai male goats (18.43 ± 0.76 kg) were distributed across 4 dietary treatments with 6 repetitions in each group. The control treatment (BSF0) did not include BSF, the other treatments (BSF5, BSF10, and BSF15) contained 5%, 10%, and 15% of BSF, respectively. Black soldier fly supplementation did not affect (P > 0.05) growth performance. With increasing supplementation levels, the digestibility of dry matter (DM) decreased linearly and quadratically (P < 0.05), while organic matter (OM) decreased linearly and quadratically (P < 0.05). The apparent digestibility of crude protein (CP) decreased linearly (P < 0.001), and neutral detergent fiber (NDF) and acid detergent fiber (ADF) decreased linearly and quadratically (P < 0.05). Serum malondialdehyde concentration showed a linear (P < 0.05) response at 0 h, while superoxide dismutase activity and 2,2-diphenyl-1-trinitrophenylhydrazine (DPPH) concentration exhibited linear responses (P < 0.05) at 4 h. Black soldier fly supplementation did not affect (P > 0.05) ruminal pH. In the BSF15 group, ruminal ammonia nitrogen (NH₃–N) concentration decreased quadratically (P < 0.001) at 0 h, and linearly (P < 0.05) at 2 and 4 h. Acetic acid decreased linearly (P < 0.05) at 2 and 4 h, propionic acid decreased linearly (P = 0.029) at 4 h. However, the concentration of butyric acid significantly increased (P < 0.05). Total volatile fatty acids (VFAs) were highest (P < 0.05) in the BSF5 group, equal in BSF0 and BSF10, and lowest (P < 0.05) in the BSF15 group. The supplementation of BSF did not affect (P > 0.05) Chao 1, Shannon, and Simpson. The most abundant phylum were Bacillota, Bacteroidota, and Candidatus Saccharibacteria, the most abundant genera were Xylanibacter, Saccharibacteria, Butyrivibrio, and Ruminococcus, and there was no statistical difference (P > 0.05) among the 4 treatments. In summary, supplementing with BSF did not affect the growth performance and ruminal microbiota of goats. It was noteworthy that the supplementation of BSF at 5% and 10% were beneficial, as they increased antioxidant levels and the concentration of short-chain fatty acids. In contrast, the supplementation of 15% BSF results in decreased digestibility, antioxidant levels, and VFA parameters. Therefore, we recommend limiting the addition of BSF in goat diets to no more than 10%.

1. Introduction

The International Feed Industry Federation (IFIF) report states that by 2050, the world's population will surpass 10 billion (Statistics, 2021). At that time, the continuously growing population and the protein consumed by animals will be twice the current levels, with insufficient arable land to meet this demand (Abril et al., 2022). Additionally, protein, being the most expensive and constrained component in feed formulations, faces direct or indirect impacts on the global feed industry due to production factors, human-animal competition, and geopolitical events such as the Russia–Ukraine conflict, trade disputes between China and the United States and COVID-19, leading to a rise in prices of traditional protein feeds (Zhang, 2019; Goh and Chou, 2022). To fulfill the protein requirements of humans and animals, the production systems of the global livestock industry in the future will be compelled to explore new sources of high-quality and sustainable protein feeds as raw materials. Against this backdrop, humans are continually experimenting with animal protein feeds in livestock, and black soldier fly (BSF) larvae (Hermetia illucens L. Diptera: Stratiomyidae), mealworm larvae (Tenebrio molitor L.), and crickets (Orthoptera: Gryllidae) are the current hotspots of research.

Black soldier fly originates from the sparsely wooded grasslands of South America and is widely distributed in temperate, subtropical, and tropical regions. It thrives in a temperature range of 25 to 30 °C, lacking cold resistance and unable to survive in Northwestern Europe and climate zones with temperatures below 5 °C (Spranghers et al., 2017). Black soldier fly primarily feeds on organic waste, including plant residues, animal dung, waste, food scraps, agricultural by-products, or straws (Nana et al., 2018). Adult BSF only consumes water, does not approach humans, does not bite or sting, and does not transmit any specific diseases (Sheppard et al., 2002). Black soldier fly exhibits better feed conversion rates compared to crickets and mealworms, with its survival rate and nitrogen-phosphorus composition showing minimal changes with dietary variations (Shah et al., 2022a). Black soldier fly can convert organic waste into amino acids, peptides, proteins, oil, chitin, and vitamins (Ebeneezar et al., 2021). Its protein content ranges from 35% to 65%, comparable to soybean meal (46% to 49%) and slightly lower than fishmeal (approximately 68%). The fat content ranges from 29% to 63%, making it a valuable source of protein and energy for livestock (Lu et al., 2022). Moreover, BSF contains approximately 4% to 7% chitin and is rich in lauric acid (C12:0) (40% to 58%) (Ravi et al., 2021). The former plays a crucial role in immunity, antioxidation, and maintaining the ruminal environment's stability, while the latter contributes significantly to reducing methane emissions from ruminant animals (Patra, 2013; Ngo and Kim, 2014b).

Chitin is a homopolymer of N-acetyl-d-glucosamine (GlcNAc), (1-4)-linked 2-acetamido-2-deoxy-β-d-glucan, known for its resistance to easy degradation, digestion, and absorption (Ngo and Kim, 2014b). Chitin and its derivatives possess significant biological properties and exhibit a broad spectrum of potential applications, including enzyme inhibition, immunostimulation, anticoagulation, antibacterial, anti-hyperlipidemic, and wound healing activities (Synowiecki and Al-Khateeb, 2003; Elieh et al., 2018). The mode of action of chitosan in the rumen depends on pH. Chitosan polymers exhibit their main antibacterial effect by influencing cell permeability through polycationic chitosan (R–NH₃⁺). When the ruminal pH falls below 6.3, electronegative charges on the microbial surface come into play, fostering the hydrolysis of peptidoglycan in the microbial wall and leading to cell lysis (Shah et al., 2022b). Primarily, it reduces the abundance of Fibrobacteroidetes and Firmicutes while increasing the abundance of Proteobacteria and Bacteroidetes (Uyanga et al., 2023).

Currently, numerous studies focus on BSF in fish, poultry, and pigs. Substituting 30% of fish meal with BSF, as reported by Hender et al. (2021), had no impact on growth performance, feed utilization, and total fatty acid composition of the meat; however, it increased the expression of immune-related genes. Agbohessou et al. (2021) discovered that a complete replacement of fish meal with BSF had no significant effect on growth parameters and innate immune status of Nile tilapia; however, it improved the systemic biochemical quality. Research on laying hens fed 5% or 10% whole-fat BSF revealed no significant differences between the treated hens and those fed diets based on corn kernels, soybean meal, and soybean oil (Kawasaki et al., 2019). Nevertheless, when feeding 15% BSF, the experimental results were controversial. Some studies indicated that supplementing 15% BSF negatively affects growth performance and digestibility of poultry (Dabbou et al., 2018b; Biasato et al., 2020b). However, other studies have found that it can still improve the growth performance of animals (Schiavone et al., 2019; Tahamtani et al., 2021), with similar results observed in pigs (Sogari et al., 2019; Biasato et al., 2020a). In conclusion, BSF can serve as a substitute for soybean meal as a protein source within 15% of the animal diet. However, currently, there is a lack of relevant studies on the application of BSF in goat diets. Therefore, the objective of this experiment was to investigate whether supplementation with varying levels of BSF would affect goat growth performance, antioxidant levels, and ruminal fermentation parameters and microorganisms.

2. Materials and methods

2.1. Animal ethics statement

This study was approved by the Animal Welfare Department of Suranaree University of Technology, number: SUT-IACUC-023/2021.

2.2. Experimental design, animal diets, and management

Twenty-four Anglo-Thai male goats (18.43 ± 0.76 kg) were distributed across 4 dietary treatments, with 6 replicates per treatment and 1 goat per replicate. The distribution was done using a completely randomized design. The control treatment (BSF0) did not include BSF, while the other treatments (BSF5, BSF10, and BSF15) contained 5%, 10%, and 15% of BSF, respectively. Throughout the 14-d adjustment period and the 75-d experimental period, the goats were fed a diet comprising 3% of their body weight in dry matter per day. The diet consisted of silage corn and concentrate feed with 14% crude protein, provided at a ratio of 40:60, and during the morning (08:00) and evening (16:00) each day. The goats were individually housed in rearing pens, with clean water freely provided to all animals. Black soldier fly at 12 d of age was killed in water at 90 °C for 30 s, and was dried at 65 °C in an oven for 48 h, ground, and sieved through a 1-mm screen. The experimental diet composition and chemical composition utilized in the treatment are shown in Table 1.

Table 1.

Ingredients and chemical composition of experimental diets (DM basis, %).

Item	BSF0	BSF5	BSF10	BSF15
Ingredients
Corn	20.00	18.00	15.00	12.00
Soybean meal	25.00	21.00	17.00	13.00
Rice bran	27.99	27.45	27.52	27.49
Cassava pulp	22.01	24.05	26.48	29.51
BSF	–	5.00	10.00	15.00
Soybean oil	2.00	1.50	1.00	–
Limestone	1.00	1.00	1.00	1.00
NaCl	1.00	1.00	1.00	1.00
Premix1	1.00	1.00	1.00	1.00
Total
Chemical composition2,% of DM
DM	87.80	88.70	88.80	89.00
OM	95.00	94.60	94.60	94.50
CP	14.30	14.20	14.10	14.00
EE	4.00	4.50	5.50	5.50
NDF	44.92	41.79	42.54	43.54
ADF	24.40	23.84	23.89	23.26
Fatty acid composition,%
C6:0	0.06	0.01	–	–
C8:0	0.04	0.02	–	–
C10:0	–	0.22	0.26	0.51
C12:0	0.09	5.87	6.99	13.79
C14:0	0.31	1.22	1.39	2.50
C14:1	0.04	0.06	0.07	0.09
C16:0	21.12	18.83	19.12	19.19
C16:1	0.18	0.58	0.64	1.20
C18:0	4.12	3.62	3.53	3.22
C18:1 n-9c	37.45	32.46	32.05	29.71
C18:2 n-6c	31.06	32.18	31.24	26.03
C18:3 n-3	2.46	2.83	2.67	2.12
C18:3 n-6	0.07	0.08	0.07	0.06
C20:0	0.80	0.56	0.56	0.43
C20:1 n-9	0.31	0.26	0.26	0.24
C20:2	0.27	0.14	0.13	0.08
C20:3 n-3	0.06	0.06	–	–
C20:4 n-6	–	0.06	0.08	0.17
C20:5 n-3	–	0.05	0.06	0.08
C21:0	0.05	0.03	0.03	0.01
C22:0	0.58	0.39	0.37	0.21
C22:1 n-9	0.02	0.05	0.02	0.03
C24:0	0.91	0.51	0.50	0.35
SFA	28.07	31.27	32.75	40.22
UFA	71.93	68.73	67.25	59.78
n-3 PUFA	2.53	2.89	2.73	2.21
n-6 PUFA	31.13	32.32	31.39	25.25
n-9 MUFA	37.78	32.76	32.33	29.98
n-3 PUFA/n-6 PUFA	0.08	0.09	0.09	1.8

BSF = black soldier fly; SFA = saturated fatty acid; UFA = unsaturated fatty acids; PUFA = polyunsaturated fatty acids; MUFA = monounsaturated fatty acids.

¹Contains per kilogram of premix: 10,000,000 IU, vitamin A; 70,000 IU, vitamin E; 1,600,000 IU, vitamin D; 50 g iron; 40 g zinc; 40 g manganese; 0.1 g cobalt; 10 g copper; 0.1 g selenium; 0.5 g iodine.

²Nutritional levels were analyzed values.

2.3. Growth performance

During the experiment, the remaining feed was collected and weighed before each feeding and used to calculate the daily dry matter intake (DMI). On day 1 and 75 of the experiment, the fasting morning weights of each goat were measured. According to Tian et al. (2020), growth performance was calculated using the following formulas:

Average daily gain (ADG, g/d) = Total weight gain (kg)/75 (d)/1000.

2.4. Diet chemical composition and apparent digestibility

Approximately 100 g of a basal diet was collected weekly and mixed at the end of the feeding trial. The duration of each digestibility trial was 12 d, including 7 d of adaption and 5 d of total feces collection. Before the morning feeding from day 70 to 75, the total feces of each goat were collected, weighed, and recorded. The manure samples were combined in equal proportions, at a ratio of 20% relative to the weight of fresh manure. The nitrogen was stabilized by adding 10% diluted sulfuric acid, and the samples were kept in a refrigerator at −20 °C. Feed and feces samples were dried at 65 °C in a vacuum oven for 72 h, ground, and sieved through a 1-mm screen. Subsequently, analyses were conducted for DM (method No. 934.01), ash (method No. 942.05), EE (method No. 920.39), and CP (method No. 976.06) (AOAC, 1995), as well as NDF and ADF (Van Soest et al., 1991), where each sample was run in triplicate. Apparent nutrient digestibility was analyzedusing the acid-insoluble ash (AIA) method (Bovera et al., 2012) with the following formula:

Apparent nutrient digestibility (%) = 1 – (AIA in diet/AIA in feces × Nutrient in feces/Nutrient in diet) × 100.

2.5. Chitin analysis

The chitin content of BSF meal was analyzed following the method outlined by Liu et al. (2012) with minor modifications. In brief, an aliquot of the prepupae meal (90–100 mg) was enclosed in an ANKOM filter bag (ANKOM Technology, Macedon, NY, USA) shaped to fit a 15 mL screw cap centrifuge tube. This aliquot underwent demineralization for 30 min in 5 mL of 1 mol/L HCl at 100 °C. The demineralization process was followed by 5 washing steps in ultra pure water, ensuring neutrality. Subsequently, a deproteinization step was carried out in 5 mL of 1 mol/L NaOH at 80 °C for 24 h. Finally, the sample was washed 5 times in ultra pure water until neutrality was achieved. After drying at 105 °C in an air-forced oven for 2 h, the chitin content (CT, g/kg DM) was calculated using the following formula:

$$CT=1000\times \frac{Fw-\left(Bw\times C\right)}{Sw}\text{,}$$

where Fw is the weight after demineralization, deproteinization, and drying (g); Bw is the weight of the modified extraction bag (g), C is dimensionless factor taking into account the mean weight loss of extraction bags (0.999, n = 6) treated according to the same procedure used for the samples, and Sw is the exact amount of sample processed (g).

2.6. Minerals analysis

Mineral content was analyzed following the method outlined by Pieterse et al. (2019). In brief, 5 mL of 6 mol/L hydrochloric acid was added to 0.5 g of the sample. The mixture was placed in an oven at 50 °C for 30 min, removed, and then 35 mL of distilled water was added. The solution was filtered and adjusted to a final volume of 50 mL. Mineral concentrations were analyzed using an iCAP 6000 series inductively coupled plasma (ICP) spectrophotometer (Thermo Electron Corporation, Milan, Italy), which was equipped with a vertical quartz torch and an autosampler (Cetac ASX-520, Teledyne CETAC Technologies, Omaha, NE, USA). Mineral concentrations were calculated using TEVA Analyst software.

2.7. Fatty acids analysis

The analysis of fatty acids was conducted according to the method by Tian et al. (2020), fatty acids from both BSF and FFS were extracted using a chloroform-methanol solution. The procedure was as follows: approximately 50 mg of the sample was mixed with 3 mL of chloroform-methanol solution (2:1) and agitated in a tissue lyser at 60 Hz for 15 min. The extract was collected and 0.6 mL of physiological saline was added, then centrifuged at 4000 × g for 10 min to obtain a lipid extract. 1 mL of lipid extract was combined to 0.2 mL of 5.00 mg/mL glycerol undecanoic acid triglyceride (C₃₆H₆₈O₆, CAS: 13552-80-2) as an internal standard, and all of the samples were esterified with 0.2 mL methanol. All samples were esterified by 8 mL of 2% sodium hydroxide-methanol solution. Then 1 mL of n-heptane was added and centrifuged at 10,000 × g for 5 min. The supernatant was gathered and 100 mg of powdered anhydrous sodium sulfate was added. The extract was filtered through a 13-mm 0.45-μm nylon syringe filter and analyzed for individual fatty acids by gas chromatography (GC–MS; Thermo Fisher Scientific, Waltham, Massachusetts, USA). A capillary column Thermo TG-FAME (50 m × 0.25 mm × 0.20 μm, TG-FAME capillary column, Thermo Fisher Scientific, Waltham, Massachusetts, USA), 1 μL injection volume, 8:1 split ratio; inlet temperature 250 °C, ionization temperature 230 °C, transmission line temperature 250 °C, quadrupole temperature 150 °C. Helium served as the carrier gas with a flow rate of 0.63 mL/min, and the ionization energy was set at 70 eV. The results were shown as the proportion of each fatty acid to the total fatty acid.

2.8. Amino acid analysis

The preprocessing of BSF amino acid analysis followed the method outlined by Tian et al. (2022). The Ultra Performance Liquid Chromatography (UPLC) conditions were as follows: individual amino acids were separated on an ACQUITY UPLC BEH C18 column (2.1 mm × 100 mm × 1.7 μm, Waters, Milford, USA) with a column temperature of 40 °C; the injection volume was 5 μL. The mobile phase consisted of A = 10% methanol (containing 0.1% formic acid) and B = 50% methanol (containing 0.1% formic acid). The gradient elution conditions were as follows: 0 to 6.5 min, 10% to 30% B; 6.5 to 7 min, 30% to 100% B; 7 to 8 min, 100% B; 8 to 8.5 min, 10% to 100% B; 8.5 to 12.5 min, 10% B. The flow rate was as follows: 0 to 8.5 min, 0.3 mL/min; 8.5 to 12.5 min, 0.3 to 0.4 mL/min. The mass spectrometry (MS) conditions were as follows: electrospray ionization source, positive ion ionization mode; ion power temperature was 500 °C, ion source voltage was 5500 V; collision gas pressure of 6 psi, curtain gas pressure of 30 psi; nebulization gas pressure and aux gas pressure were both 50 psi; and multiple-reaction monitoring scan mode.

2.9. Antioxidant analysis

On the last day of the experiment, blood was collected on an empty stomach in the morning and again 2 and 4 h after feeding, allowed to stand for 30 min and then centrifuged at 3500 × g for 15 min at 4 °C. The supernatant was then extracted and stored at −80 °C for analysis of serum antioxidant parameters. Antioxidant kits (Sigma–Aldrich, Darmstadt, Germany) were utilized, and analytical procedures were conducted following the provided instructions. The kit numbers for the assays were as follows: glutathione peroxidase (GSH-Px) - MAK437, catalase (CAT) - MAK381, total antioxidant capacity (T-AOC) - MAK187. Malondialdehyde (MDA) was measured at 532 nm using kit number MAK085. 2,2-Diphenyl-1-trinitrophenylhydrazine (DPPH) was measured using kit number MAK085. Superoxide dismutase (SOD) was assessed using kit number CS0009. The BUN assay was conducted with kit number MAS008.

2.10. Ruminal fermentation parameters

At the same time as the blood collection, ruminal fluid was sampled using a gastric tube connected to a vacuum pump. Ruminal fluid samples were promptly measured for pH using a portable pH meter (Mettler Five Easy Plus Series, Columbus, OH, USA) and then filtered through 4 layers of cheesecloth. 5 mL of ruminal fluid with 1 mL of 15% metaphosphoric acid was mixed, stored at −20 °C, and analyzed volatile fatty acids (VFAs) following the method described by Suong et al. (2022). In brief, the concentration of VFAs in the filtrate was analyzed using gas chromatography (Agilent 6890 GC, Agilent Technologies, Santa Clara, CA, USA) with a silica capillary column (30 m × 250 μm × 0.25 μm). The initial temperature was 40 °C for 2 min, followed by an increase to 100 °C at a rate of 3.5 °C/min, and then to 249.8 °C at a rate of 10 °C/min. The total run time was 30 min. The boiling chamber temperature was 250 °C, and the carrier gas, helium (99.99%), had a pressure of 31.391 psi. The carrier gas flow rate was 3.0 mL/min, and the solvent delay time was 3 min. The technique of Nur et al. (2018) was used to detect ammonia nitrogen (NH₃–N).

2.11. DNA extraction and PCR amplification

The instructions of the kit were followed, MagPure Soil DNA LQ Kit (Guangzhou Magan Biotechnology Co., Ltd., Guanghzou, China) was used to extract genomic DNA from the samples. The DNA concentration and purity were evaluated using NanoDrop 2000 (Thermo Fisher Scientific, Waltham, Massachusetts, USA) and agarose gel electrophoresis, and the extracted DNA was stored at −20 °C. The extracted genomic DNA was then used as a template for bacterial 16S rRNA gene PCR amplification. Universal primers 343F (5′-TACGRAGGCAGCAG-3′) and 798R (5′-AGGGTATCTAATCCT-3′) were used to target the V3 to V4 variable region of the bacterial 16S rRNA gene (Nossa et al., 2010), for diversity analysis. PCR products were analyzed by agarose gel electrophoresis, sequenced on the Illumina NovaSeq 6000 platform, generating paired-end reads of 250 bp. Library construction, sequencing, and data analysis were performed by Shenzhen Huada Gene Co., Ltd., Shenzhen, China. After data collection, Cutadapt software was used to trim primer sequences from the raw data sequences. The default parameters of QIIME 2 (2020.11) (Bolyen et al., 2019) were used, and Divisive Amplicon Denoising Algorithm 2 (DADA2) was employed to perform quality filtering, denoising, merging, and removal of chimeric sequences on qualified paired-end raw data, resulting in representative data sequences and an amplicon sequence variant (ASV) abundance table. After representative sequences were selected for each ASV using the QIIME 2 software package, all representative sequences were aligned and annotated against the Silva database (version 138). Alpha and Beta diversity analyses were performed using the QIIME 2 software. Alpha diversity of samples was assessed using metrics such as the Chao 1 and Shannon index. Unweighted UniFrac principal coordinates analysis (PCoA) was conducted using an unweighted UniFrac distance matrix computed by R to assess the beta diversity of samples. Differential analysis was performed using ANOVA statistical methods based on the R package.

2.12. Statistical analysis

Statistical analyses were performed using the SPSS software package (version 27.0; SPSS, Chicago, IL, USA). The data were presented as the mean and SEM. One-way ANOVA and post hoc multiple mean comparisons (Tukey's HSD test) were performed to analyze differences between the samples with a confidence interval of 95%. The statistical method model was as follows:

$$Y_{ij}=\mathrm{\mu }+{\tau }_i+{\epsilon }_{ij}\text{,}$$

where Y_ij is the observation j (j = 1–6) in treatment i, μ is the overall mean, τ_i is the effect of the treatment (denoted an unknown parameter), and ε_ij is the random error with a mean of 0 and variance σ². The polynomial comparison method was used to test the linear and quadratic responses to increasing BSF levels in the diets. The significance level was set at P < 0.05.

3. Results

3.1. The proximate composition of BSF

The proximate composition of BSF is shown in Table 2. The composition included a dry matter (DM) content of 97.35%, crude protein (CP) content of 40.81%, and ether extract (EE) content of 32.90%. The minerals with the highest content were ranked in the following order: Fe (150.00 mg/kg), Mg (1.80 g/kg), and Ca (26.00 g/kg). The chitin content was 77.83 g/kg.

Table 2.

The proximate composition of black soldier fly (BSF) (DM basis).

Item	Content
DM, %	97.35
CP, %	40.81
EE, %	32.9
OM, %	91.71
Ca, g/kg	26.00
Mg, g/kg	1.80
Fe, mg/kg	150.00
P, mg/kg	5.70
Cu, mg/kg	5.80
Se, mg/kg	0.26
Chitin, g/kg	77.83

3.2. Amino acid content of BSF

Amino acid content is presented in Table 3. Black soldier fly exhibited a high content of indispensable amino acids: phenylalanine (3.00%), leucine (1.81%), lysine (1.42%), and arginine (1.37%). Threonine and valine also exceeded 1% in content.

Table 3.

Amino acid content of black soldier fly (BSF) (%).

Item	Content
Indispensable amino acids
Arginine	1.37
Histidine	0.22
Isoleucine	0.71
Leucine	1.81
Lysine	1.42
Methionine	0.10
Phenylalanine	3.00
Threonine	1.00
Valine	1.10
Dispensable amino acids
Alanine	2.01
Aspartic acid	2.67
Glycine	1.53
Glutamic acid	3.91
Proline	1.52
Serine	1.33
Tyrosine	1.42

3.3. Fatty acids content of BSF

The contents of fatty acids are shown in Table 4. The saturated fatty acids with the highest content were C12:0 (20.02%), followed by C16:0 (18.25%), C14:0 (4.13%), and C18:0 (3.38%). The contents of C18:1, C18:2, and C18:3 were 26.36%, 20.76%, and 2.94%, respectively. The contents of SFA and UFA were 46.62% and 53.38%, respectively. Additionally, the contents of n-3 PUFA, n-6 PUFA, and n-9 MUFA were 3.25%, 21.31%, and 26.46%, respectively, with a n-3/n-6 ratio of 0.15.

Table 4.

Fatty acid content of black soldier fly (BSF) (%).

Item	Content
C10:0	0.70
C12:0	20.02
C14:0	4.13
C14:1	0.14
C16:0	18.25
C16:1	2.18
C18:0	3.38
C18:1n-9c	26.36
C18:2n-6c	20.76
C18:3n-3	2.94
C18:3n-6	0.11
C20:0	0.07
C20:1n-9	0.11
C20:2	0.04
C20:4n-6	0.43
C20:5n3	0.30
C21:0	0.06
SFA	46.62
UFA	53.38
n-3 PUFA	3.25
n-6 PUFA	21.31
n-9 MUFA	26.46
n-3 PUFA/n-6 PUFA	0.15

SFA = saturated fatty acid; UFA = unsaturated fatty acids; PUFA = polyunsaturated fatty acids; MUFA = monounsaturated fatty acids.

3.4. Effects of BSF on dry matter intake and growth performance and apparent digestibility in goats

The effects of BSF on feed intake, growth performance, and apparent digestibility of goats are shown in Table 5. Black soldier fly showed no significant effect (P > 0.05) on final weight, ADG, and DMI. However, BSF supplementation exhibited a tendency to increase (0.05 ≤ P < 0.10) both ADG and DMI. The apparent digestibility of DM and NDF decreased linearly and quadratically (P < 0.05) as BSF was supplemented. The apparent digestibility of OM decreased linearly and quadratically (P < 0.05). The apparent digestibility of CP decreased linearly (P < 0.001), and that of ADF decreased quadratically (P < 0.001).

Table 5.

Effects of BSF on growth performance and nutrient apparent digestibility in goats.

Item	BSF0	BSF5	BSF10	BSF15	SEM	P-value
						Treatment	L	Q
Growth performance
Initial weight, kg	18.55	18.64	18.02	18.45	0.162	0.607	0.547	0.621
Final weight, kg	27.61	28.27	27.39	27.50	0.384	0.858	0.739	0.740
ADG, g	120.80	128.33	124.93	120.67	4.683	0.934	0.933	0.564
DMI, g/d	748.95	778.98	775.45	764.24	8.238	0.617	0.585	0.241
Apparent digestibility,%
DM	65.74a	66.15a	64.50b	62.22c	0.241	<0.001	<0.001	<0.001
OM	68.06a	67.71b	66.19c	64.69d	0.232	<0.001	<0.001	<0.001
EE	92.20	92.67	93.34	92.49	0.238	0.377	0.517	0.183
CP	73.94ab	74.98a	71.61bc	69.97c	0.533	<0.001	<0.001	0.063
NDF	56.31ab	57.16a	56.10ab	53.55b	0.487	0.019	0.011	0.028
ADF	40.79b	47.72a	45.78a	41.92b	0.852	<0.001	0.516	<0.001

BSF = black soldier fly; ADG = average daily gain; DMI = dry matter intake; SEM = standard error of the mean; L = linear; Q = quadratic. BSF0: no BSF, BSF5: 5% of BSF, BSF10: 10% of BSF, BSF15: 15% of BSF.

Values with different small letter superscripts differ (P < 0.05).

3.5. The effect of supplementing BSF on blood urea nitrogen (BUN) and antioxidant capacity

The impacts of BSF on blood urea nitrogen (BUN) and antioxidant capacity are presented in Table 6. At 0 h, MDA showed a linear response (P = 0.038), with no impact (P > 0.05) on the antioxidant parameters among groups. At 2 h, BSF had no effect (P > 0.05) on the antioxidant parameters. At 4 h, both SOD and DPPH exhibited linear responses (P < 0.05), with no significant differences (P > 0.05) in other parameters.

Table 6.

The effect of supplementing BSF on BUN and serum antioxidant capacity.

Item	BSF0	BSF5	BSF10	BSF15	SEM	P-value
						Treatment	L	Q
0 h
BUN, mg/dL	12.14	13.97	15.60	14.40	0.853	0.577	0.290	0.383
SOD, U/mL	69.76b	75.89a	75.08a	72.99ab	0.881	0.048	0.633	0.208
CAT, U/mL	17.05	16.83	17.59	17.63	0.306	0.766	0.405	0.843
GSH-Px, U/mL	51.56	52.20	52.58	52.20	0.154	0.149	0.090	0.092
DPPH, %	89.05	90.87	90.27	90.46	0.409	0.483	0.345	0.343
MDA, nmol/mL	0.97	0.96	0.88	0.89	0.073	0.123	0.038	0.681
T-AOC, nmol/μL	8.52	9.76	10.88	8.70	0.637	0.568	0.774	0.197
2 h
BUN, mg/dL	12.52	14.35	15.95	14.77	0.774	0.521	0.258	0.349
SOD, U/mL	65.09	67.93	68.17	69.27	0.899	0.453	0.136	0.640
CAT, U/mL	16.17	16.23	14.78	14.14	0.417	0.186	0.048	0.663
GSH-Px, U/mL	52.28	51.35	52.32	50.82	0.354	0.380	0.295	0.695
DPPH, %	85.94	86.16	87.12	86.26	0.863	0.975	0.821	0.776
MDA, nmol/mL	1.05	1.23	1.18	1.18	0.082	0.904	0.677	0.619
T-AOC, nmol/μL	6.04	5.59	6.69	6.36	0.373	0.768	0.552	0.936
4 h
BUN, mg/dL	13.56	15.03	16.57	15.27	0.817	0.691	0.404	0.428
SOD, U/mL	68.80	72.13	74.36	73.53	0.838	0.108	0.029	0.197
CAT, U/mL	20.48	21.29	21.75	21.92	0.312	0.386	0.097	0.606
GSH-Px, U/mL	52.07	54.23	54.17	53.94	0.389	0.191	0.117	0.130
DPPH, %	86.47	89.22	88.91	89.38	0.463	0.092	0.039	0.195
MDA, nmol/mL	0.92	1.29	1.24	0.97	0.084	0.264	0.896	0.056
T-AOC, nmol/μL	8.63	9.38	10.61	9.96	0.338	0.246	0.095	0.306

BSF = black soldier fly; BUN = blood urea nitrogen; CAT = catalase; DPPH = 2,2-diphenyl-1-trinitrophenylhydrazine; GSH-Px = glutathione peroxidase; MDA = malondialdehyde; SOD = superoxide dismutase; T-AOC = total antioxidant capacity; SEM = standard error of the mean; L = linear; Q = quadratic. BSF0: no BSF, BSF5: 5% of BSF, BSF10: 10% of BSF, BSF15: 15% of BSF.

Values with different small letter superscripts differ (P < 0.05).

3.6. Effect of BSF supplementation on ruminal pH and NH₃-N

The effects of BSF on ruminal pH and NH₃–N are presented in Table 7. Supplementation of BSF had no significant effect (P > 0.05) on ruminal pH. With BSF supplementation, NH₃–N decreased quadratically (P < 0.001) at 0 h, and linearly (P < 0.05) at 2 and 4 h.

Table 7.

Effect of BSF supplementation on ruminal pH and NH₃–N.

Item	BSF0	BSF5	BSF10	BSF15	SEM	P-value
						Treatment	L	Q
pH
0 h	7.05	7.01	7.15	7.07	0.044	0.793	0.654	0.860
2 h	6.75	6.60	6.55	6.63	0.062	0.718	0.467	0.351
4 h	6.95	7.00	6.98	6.99	0.03	0.964	0.742	0.802
NH3–N, mg/dL
0 h	9.74b	12.61a	14.64a	9.71b	0.433	<0.001	0.424	<0.001
2 h	17.75a	15.63ab	15.60ab	14.21b	0.389	0.014	0.002	0.612
4 h	16.08a	13.84ab	12.80b	11.72b	0.447	0.003	<0.001	0.457

BSF = black soldier fly; NH₃–N = ammonia nitrogen; SEM = standard error of the mean; L = linear; Q = quadratic. BSF0: no BSF, BSF5: 5% of BSF, BSF10: 10% of BSF, BSF15: 15% of BSF.

Values with different small letter superscripts differ (P < 0.05).

3.7. Effect of BSF supplementation on ruminal VFAs

The effect of BSF supplementation on ruminal VFAs is depicted in Table 8. Acetic acid showed a quadratic decrease (P < 0.05) at 0 and 2 h, with no significant difference (P > 0.05) at 4 h. Propionic acid showed a quadratic increase (P = 0.029) at 2 h and a linear decrease (P = 0.006) at 4 h. Butyric acid increased linearly and quadratically (P < 0.05) at 0 and 2 h, and quadratically (P = 0.014) at 4 h. Total VFAs decreased quadratically (P = 0.001) at 0 h, linearly and quadratically (P < 0.05) at 2 and 4 h.

Table 8.

Effect of BSF supplementation on ruminal VFA concentration.

Item	BSF0	BSF5	BSF10	BSF15	SEM	P-value
						Treatment	L	Q
Total VFAs, mmol/L
0 h	52.35ab	61.29a	61.42a	45.49b	1.948	0.006	0.188	0.001
2 h	97.72b	108.95a	92.57b	76.35c	2.363	<0.001	<0.001	<0.001
4 h	86.02ab	94.00a	88.79a	73.75b	2.016	0.002	0.008	0.002
Acetic acid,%
0 h	59.00ab	59.68a	61.96a	55.11b	0.671	0.004	0.076	0.003
2 h	66.10ab	68.27a	67.65a	64.67b	0.373	0.001	0.080	<0.001
4 h	66.02	67.65	68.62	67.39	0.447	0.236	0.209	0.120
Propionic acid,%
0 h	19.26ab	21.32a	18.94b	20.01ab	0.316	0.026	0.970	0.415
2 h	21.06	19.69	19.49	20.61	0.283	0.140	0.519	0.029
4 h	20.10	19.23	17.98	17.60	0.360	0.058	0.006	0.716
Butyric acid,%
0 h	21.74ab	19.00b	19.10ab	24.87a	0.576	<0.001	0.018	<0.001
2 h	12.84b	12.04b	12.86b	14.72a	0.244	<0.001	<0.001	0.001
4 h	13.88ab	13.12b	13.40ab	15.01a	0.253	0.033	0.077	0.014
A:P
0 h	3.09	2.83	3.23	2.84	0.084	0.050	0.423	0.366
2 h	3.15	3.49	3.51	3.16	0.618	0.147	0.950	0.019
4 h	3.31	3.59	3.89	3.87	0.092	0.079	0.016	0.416

BSF = black soldier fly; A:P = acetic acid to propionic acid ratio; VFAs = volatile fatty acids; SEM = standard error of the mean; L = linear; Q = quadratic. BSF0: no BSF, BSF5: 5% of BSF, BSF10: 10% of BSF, BSF15: 15% of BSF.

Values with different small letter superscripts differ (P < 0.05).

3.8. Effects of BSF on ruminal microbial community dynamics and species diversity

High-quality filtering and chimeric sequence removal resulted in 961,392 sequences, with an average coverage of 48,070 sequences per sample. Across all samples, a total of 8042 operational taxonomic units (OTUs) were calculated (Fig. 1A). The number of OTUs common to the 4 treatments was 503, and the number of OTUs unique to BSF0, BSF5, BSF10, and BSF15 treatments were 646, 654, 720, and 704, respectively. Principal coordinates analysis of dissimilarity matrices showed that ruminal bacterial communities in the 4 groups clustered together based on their ratio treatment and were separated (Fig. 1B). The results of the analysis of similarities support the tendency of differences in the community structure of the 4 groups (P = 0.180). From the coverage index, the coverage of each sample was very close to 1.0, reflecting that the sample quality of all samples was sufficient (Table 9). There was no statistically significant difference (P > 0.05) in species diversity among the 4 treatments.

Fig. 1.

Effects of BSF supplementation on ruminal microorganisms. (A) A Venn diagram of operational taxonomic units (OTUs). (B) Points of different colors or shapes represent sample groups. The scales of the horizontal and vertical axes were the projected coordinates of the sample points on the two-dimensional plane respectively. BSF = black soldier fly. BSF0: no BSF, BSF5: 5% of BSF, BSF10: 10% of BSF, BSF15: 15% of BSF.

Table 9.

Operational taxonomic unit count and diversity were estimated from sequencing analysis based on the 16S rRNA gene libraries.

Item	BSF0	BSF5	BSF10	BSF15	SEM	P-value
						Treatment	L	Q
Chao 1	648.10	621.41	626.00	619.00	16.124	0.930	0.601	0.780
Shannon	4.91	4.96	4.91	4.72	0.117	0.912	0.593	0.642
Simpson	0.04	0.03	0.03	0.06	0.011	0.554	0.435	0.236
Ace	648.25	621.5	626.09	619.06	16.114	0.929	0.600	0.780
Coverage	1	1	1	1	0.0	0.230	0.075	0.393

SEM = standard error of the mean; L = linear; Q = quadratic. BSF0: no BSF, BSF5: 5% of BSF, BSF10: 10% of BSF, BSF15: 15% of BSF.

3.9. Comparison of bacterial community composition among treatments

The bacterial abundance is depicted in Fig. 2A and B. At the phylum level; the most abundant species were Bacillota (BSF0: 56.51%, BSF5: 48.92%, BSF10: 53.03%, BSF15: 61.73%), Bacteroidota (BSF0: 28.48%, BSF5: 29.83%, BSF10: 30.47%, BSF15: 15.60%), and Candidatus Saccharibacteria (BSF0: 4.48%, BSF5: 9.16%, BSF10: 3.01%, BSF15: 3.86%), with Verrucomicrobiota and Pseudomonadota both exceeding 1%. The most abundant genera were Xylanibacter (BSF0: 7.24%, BSF5: 7.73%, BSF10: 6.09%, BSF15: 2.73%), Saccharibacteria (BSF0: 4.48%, BSF5: 9.16%, BSF10: 3.01%, BSF15: 3.81%), Butyrivibrio (BSF0: 2.27%, BSF5: 2.00%, BSF10: 2.47%, BSF15: 1.27%), and Ruminococcus (BSF0: 1.61%, BSF5: 1.04%, BSF10: 1.30%, BSF15: 0.73%). At the phylum and genus levels (Table 10, Table 11), among the top 10 species, only the genus Cyanobacteriota showed significant differences (P = 0.001), while other bacterial groups exhibited no statistically significant differences (P > 0.05). To provide clarity and visualization, a heatmap depicted the top 13 phyla and 52 genera (Fig. 2C and D). At the genus and phylum levels, there was no correlation between increased BSF and the relatedness of the bacterial flora. The LEfSe algorithm was used to identify ASV biomarkers (Fig. 3). Compared to the BSF0 group, the relative abundance of Mycobacteriales, Staphylococcus, Staphylococcaceae, Caryophanales, Corynebacterium, and Atopobiaceae increased in the BSF15 group. The relative abundance of Massiliimalia increased in the BSF10 group, and the relative abundance of Negativicutes increased in the BSF5 group.

Fig. 2.

Effects of BSF supplementation on ruminal microorganisms. (A and B) Ruminal microbial composition at phylum and genus levels, species that were not annotated at this taxonomic level and whose abundance was less than 0.5% in the sample were merged into others. (C and D) The heatmap showing the composition of the phylum and genus level microbiota combined with the results from the cluster analysis. BSF = black soldier fly. BSF0: no BSF, BSF5: 5% of BSF, BSF10: 10% of BSF, BSF15: 15% of BSF.

Table 10.

Effects of BSF supplementation on ruminal microorganisms (phylum level, %).

Item	BSF0	BSF5	BSF10	BSF15	SEM	P-value
						Treatment	L	Q
Mycoplasmatota	0.06	0.04	0.05	0.08	0.011	0.841	0.686	0.430
Cyanobacteriota	0.03b	0.02b	0.01b	0.18a	0.010	0.001	0.002	0.006
Elusimicrobiota	0.11	0.05	0.24	0.03	0.012	0.129	0.903	0.239
Synergistota	0.41	0.17	0.83	0.07	0.044	0.351	0.800	0.427
Lentisphaerota	0.34	0.69	0.61	0.52	0.033	0.853	0.720	0.468
Spirochaetota	0.53	1.21	0.43	1.06	0.052	0.492	0.674	0.953
Actinomycetota	1.72	0.58	0.43	1.41	0.054	0.067	0.523	0.011
Verrucomicrobiota	1.16	1.48	2.53	3.37	0.093	0.189	0.037	0.734
Pseudomonadota	2.02	2.4	2.62	4.32	0.100	0.245	0.070	0.437
Candidatus Saccharibacteria	4.48	9.16	3.01	3.86	0.233	0.122	0.345	0.313
Bacteroidota	28.48	29.83	30.47	15.60	0.718	0.323	0.195	0.216
Bacillota	56.51	48.92	53.03	61.73	0.683	0.535	0.489	0.211
Others	4.13	5.41	5.51	7.64	0.189	0.592	0.205	0.818

BSF = black soldier fly; SEM = standard error of the mean; L = linearly; Q = quadratically. BSF0: no BSF, BSF5: 5% of BSF, BSF10: 10% of BSF, BSF15: 15% of BSF.

Species that were not annotated at this taxonomic level and whose abundance was less than 0.5% in the sample were merged into Others.

Values with different small letter superscripts differ (P < 0.05).

Table 11.

Effects of BSF supplementation on ruminal microorganisms (genus level, %).

Item	BSF0	BSF5	BSF10	BSF15	SEM	P-value
						Treatment	L	Q
Prevotella	0.12	1.00 00	0.34	0.56	0.193	0.476	0.725	0.418
Pararoseburia	0.92	0.51	0.55	0.38	0.114	0.325	0.108	0.567
Weissella	0.65	0.39	0.22	1.32	0.223	0.323	0.356	0.134
Treponema	0.46	1.11	0.31	0.98	0.201	0.450	0.673	0.986
Succiniclasticum	0.15	0.02	0.29	1.13	0.276	0.098	0.556	0.408
Saccharofermentans	1.32	1.29	0.64	0.54	0.268	0.213	0.054	0.907
Ruminococcus	1.61	1.04	1.30	0.73	0.283	0.745	0.375	0.996
Butyrivibrio	2.27	2.00	2.47	1.27	0.244	0.311	0.238	0.330
Saccharibacteria	4.48	9.16	3.01	3.86	1.013	0.122	0.345	0.313
Xylanibacter	7.24	7.73	6.09	2.37	1.565	0.654	0.282	0.528
Others	80.79ab	73.92b	84.78a	86.86a	1.622	0.011	0.020	0.095

BSF = black soldier fly; SEM = standard error of the mean; L = linear; Q = quadratic. BSF0: no BSF, BSF5: 5% of BSF, BSF10: 10% of BSF, BSF15: 15% of BSF.

Species that were not annotated at this taxonomic level and whose abundance was less than 0.5% in the sample were merged into Others.

Values with different small letter superscripts differ (P < 0.05).

Fig. 3.

LEfSe analysis. (A) The histogram of the distribution of LDA values was calculated with a score of LDA scores >2. (B) An example map of different species annotation branches in the figure. BSF = black soldier fly. BSF0: no BSF, BSF5: 5% of BSF, BSF10: 10% of BSF, BSF15: 15% of BSF.

4. Discussion

The intake of animals is influenced by the composition, availability, palatability, and feedback mechanisms of the diet (Nur et al., 2018). In this study, the inclusion of BSF did not alter the DMI and growth performance of goats. This is consistent with the findings of Bellezza et al. (2021), in which supplementing 5% whole BSF or Tenebrio molitor did not significantly affect the growth performance parameters of broilers overall. However, De Souza et al. (2021) obtained different results when supplementing 5%, 10%, 15%, and 20% whole BSF in broilers, where body weight increased linearly with the increase in BSF supplementation. The research from Ipema et al. (2021) on piglets also concluded that supplying whole BSF did not affect piglet growth, feed efficiency, energy efficiency, or fecal consistency. Biasato et al. (2019) reported that overall, defatted BSF did not affect the growth performance of pigs. The results above indicate that BSF at least maintained the growth performance of animals. Apparent digestibility reflects the degree of absorption and utilization of nutrients in the diet. In this study, BSF5 was beneficial in increasing the digestibility of nutrients, but as the supplementation of BSF increased, the digestibility decreased. An in vitro study indicated that BSF reduced the digestibility of DM and OM. However, another in vitro fermentation study, reported by Kahraman et al. (2023), found that supplementing with 20% and 40% defatted BSF increased the digestibility rates of DM and NDF at 24 and 48 h. This differs from the findings of our experiment. Furthermore, supplementing 20% defatted BSF in the diet of beagle dogs reduced the digestibility of CP and OM, while whole 8% BSF did not affect the apparent nutrient digestibility (Jian et al., 2022). In contrast, some studies have also found that feeding 5% or 20% whole BSF decreased the digestibility of CP in both beagle dogs and cats (Kröger et al., 2020; Do et al., 2022). Interestingly, in studies conducted on pigs, BSF showed no effect on apparent digestibility rates (Biasato et al., 2019). In poultry, apart from a reduction in the digestibility rate of EE, there were no significant differences in the apparent digestibility rates of DM, CP, starch, and energy (Cullere et al., 2016). The studies above indicated that the digestion of BSF in animals varies significantly, which may be related to factors such as the growth cycle of BSF, temperature, substrate, and environmental conditions (Seyedalmoosavi et al., 2022). In this study, the reduced digestibility rates observed with BSF10 and BSF15 may be associated with the content of chitin and C12:0. C12:0 inhibits ruminal fermentation, leading to a decrease in the digestion of nutrients (Hristov et al., 2009). Chitin is a linear polymer of β-(1-4) N-acetyl-D-glucosamine units with high molecular weight, poor water solubility, strong protein binding activity, minimal chitin-degrading enzyme activity in ruminal microorganisms, and exhibits anti-nutritional effects, negatively impacting protein digestibility rates (Longvah et al., 2011).

Oxidative stress can result in the activation of enzymes within the organism and oxidative damage to cellular systems. Free radicals attack large molecules such as DNA, proteins, and lipids, leading to disruptions in bodily functions (Ngo and Kim, 2014a). Due to the presence of chitin and C12:0, BSF exhibits antioxidant properties (Quintieri et al., 2023). In this study, there were no differences observed in the analyzed antioxidant parameters among treatment levels. However, MDA showed a linear response. By the 4 h mark, both SOD and DPPH showed a linear increase. This indicated that BSF did not impair the antioxidant system of goats. Caimi et al. (2020) reported that feeding 25% and 50% defatted BSF increased the activities of SOD, CAT, and GSH-Px in the fish liver while reduced the MDA concentration. There was a study by Dabbou et al. (2018a) and Gariglio et al. (2019), who indicated that 5%, 10%, and 15% defatted BSF supplementation enhanced the GSH-Px concentration and T-AOC in broiler chickens while also lowering the levels of MDA. In summary, BSF can exert antioxidant effects in goats similar to its effects in other animals.

Ruminal pH is an important indicator of ruminal nutrient metabolism and digestive environment homeostasis, usually varying between 5.0 and 7.5 (Dijkstra et al., 2020). In this study, the pH values at all periods were within the normal range without significant differences, indicating that BSF supplementation may not affect the ruminal environment. NH₃–N was an intermediate product of ruminal microorganisms decomposing nitrogenous substances. It comes from the degradation of feed protein and was used to synthesize microbial protein. Its optimal concentration range NH₃–N is 2.37 to 27.3 mg/dL, which is the most important nitrogen source for ruminants (Hervás et al., 2022). Our results showed that at 0 h, BSF5 and BSF10 were significantly higher than BSF0 and BSF15; but at 2 and 4 h, BSF treatment was significantly lower than BSF0. It is known that soybean meal contains a high level of rapidly degradable protein fractions, leading to an increase in NH₃–N production in the rumen at 2 and 4 h of feeding in this study (Maxin et al., 2013). An in vitro study showed that the concentration of NH₃–N decreased with the decrease in soybean meal levels in the substrate (Jeong et al., 2015). In contrast, the reduction in NH3–N concentration in the BSF15 group at 0 h may be due to the increase in C12:0 and C14:0 in BSF, which inhibits the activity of protein microbes. A previous in vitro study found that BSF at 20% and 40% in the TMR diet reduced NH3–N concentration (Kahraman et al., 2023), andJayanegara et al. (2017) also observed a decrease in NH₃–N by adding 50% whole BSF. In summary, low levels of BSF favor NH₃–N production, while high levels inhibit ruminal NH₃–N concentration.

Volatile fatty acids are the major product of ruminal fermentation and were positively correlated with the digestibility of the substrate, accounting for approximately 40% to 70% of digestible energy intake (Cabezas-Garcia et al., 2017). In this study, acetic acid, propionic acid, and total VFAs were generally highest in the BSF5 and BSF10 groups, while lowest in the BSF15 group. The A/P ratio did not show significant differences. This may be related to the levels of saturated fatty acids and chitin because a small amount of chitin can change the ruminal fermentation pattern and increase propionic acid concentration (de Paiva et al., 2016; Vendramini et al., 2016; Dias et al., 2017; Goiri et al., 2010). As the proportion of BSF increases, the concentration of chitin also increases, but the level of chitinase in the rumen is very low, resulting in a decrease in the concentration of VFAs (Tabata et al., 2018). This has been confirmed by Renna et al. (2022). In addition, the role of fatty acids in reducing VFAs has been confirmed (Hristov et al., 2011; Vargas et al., 2020), it could be due to the partial exchange of easily fermentable carbohydrates by lipids in the diet. The decrease in VFA concentration is consistent with the reduced digestibility of OM and NDF. However, an unexpected increase in the concentration of butyrate in the BSF15 group was observed. This explanation can be attributed to the decrease in acetic acid and propionic acid concentrations, as the increase in butyric acid concentration inhibits the production of acetic acid and propionic acid (Górka et al., 2018). In summary, 5% and 10% of BSF promote the production of VFAs, while 15% of BSF inhibit VFA production.

Intestinal microbiota plays a key role in intestinal ecology. The dominant microbial community in the rumen of ruminants was not static and changes with variations in feed type (McCann et al., 2016; Yadav and Jha, 2019). In this study, the supplementation of BSF did not significantly differ in ruminal bacterial diversity indices. This indicated that adding BSF to the daily diet did not affect the diversity of the goat ruminal bacterial community, consistent with research findings on BSF in other animals (Dabbou et al., 2021; Jian et al., 2022). The predominant bacterial phyla in this experiment were Pseudomonadota, Candidatus Saccharibacteria, Bacteroidota, and Bacillota. Although their differences were not significant, there was a decreasing trend in Bacteroidota associated with protein hydrolysis (Wu et al., 2011), which also explains the observed decrease in protein apparent digestibility in this study. Xylanibacter, Saccharibacteria, Butyrivibrio, and Ruminococcus were the dominant bacterial genera among the 4 groups. Although the differences among groups were not statistically significant, with the supplementation of BSF, there was a decreasing trend in its abundance, attributable to the antibacterial properties of BSF fatty acid (C12:0) (Spranghers et al., 2018). Butyrivibrio is mainly responsible for the production of butyric acid, and Ruminococcus is mainly involved in the degradation of cellulose to produce acetic acid and propionic acid (Liang et al., 2021), this also explains the reason for the decrease in VFA concentration observed in this study. The results of other studies are completely different from this experiment. A study found that whole BSF reduced the abundance of beneficial bacteria and increased the abundance of harmful bacteria (Jian et al., 2022). Biasato et al. (2020b) conducted a study on the use of defatted BSF in broiler chickens, revealing that 15% BSF reduced α-diversity, increased β-diversity, and different BSF levels had distinct effects on the characteristics of the intestinal microbial community. Meanwhile, Dabbou et al. (2020) discovered that BSF oil has a positive impact the cecal microbiota of rabbits. The reason for this difference may be that the ruminal microbiota of ruminant animals is far more complex than that of monogastric animals. In summary, in this experiment, the supplementation of BSF did not result in statistically significant differences in ruminal microbial diversity and community composition. However, there was a trend of decreasing abundance in dominant bacterial groups.

5. Conclusion

Black soldier fly supplementation did not affect growth performance, feed intake, and ruminal pH. With the supplementation of BSF, the digestibility of nutrients decreased. BSF5 and BSF10 increased the production of ruminal acetic acid, propionic acid, and total VFAs, while BSF15 increased the concentration of butyric acid. On the other hand, BSF supplementation increased resistance to oxidation levels. The most abundant genera observed were Xylanibacter, Saccharibacteria, Butyrivibrio, and Ruminococcus, while the most abundant phyla were Bacillota, Bacteroidota, and Candidatus Saccharibacteria. However, there was no statistical difference observed among the 4 treatments. Therefore, we recommend supplementing 10% BSF in goat diets.

CRediT authorship contribution statement

Shengyong Lu: Data curation, Conceptualization. Siwaporn Paengkoum: Formal analysis, Data curation. Shengchang Chen: Funding acquisition, Formal analysis, Data curation. Yong Long: Project administration, Methodology. Xinran Niu: Investigation, Data curation. Sorasak Thongpea: Methodology, Investigation, Formal analysis. Nittaya Taethaisong: Methodology, Investigation, Funding acquisition, Conceptualization. Weerada Meethip: Resources, Project administration, Investigation, Funding acquisition. Pramote Paengkoum: Investigation, Funding acquisition, Formal analysis, Data curation.

Data availability

Datasets used or analyzed in this study were available by reasonable request from the corresponding author.

Declaration of competing interest

We declare that we have no financial and personal relationships with other people or organizations that can inappropriately influence our work, and there is no professional or other personal interest of any nature or kind in any product, service and/or company that could be construed as influencing the content of this paper.