Evaluation of Essential Oils and Their Blends on the Fermentative Profile, Microbial Count, and Aerobic Stability of Sorghum Silage

Abstract

This study aims to evaluate the effect of these essential oils and their blends on the fermentative profile, losses by gases and effluents, nutritional value, microbial count, and aerobic stability of sorghum silage. A completely randomized design was used with eight treatments and four repetitions. The evaluated treatments were the following: control (CON), without any essential oil; rosemary (Ros); tea tree (TT); citronella (Cit); Ros + TT (50% + 50%); Ros + Cit (50% + 50%); TT + Cit (50% + 50%); and Ros + TT + Cit (33% + 33% + 33%). A 1000 mg/kg dose of ensiled mass (as-fed basis) was used for each of the treatments. The addition of essential oils and their blends had a significant impact (p < 0.05) on the chemical composition of sorghum silage. Crude protein content increased (p < 0.001) with the use of essential oils and their blends. The Ros affected (p < 0.05) the fibrous fraction of sorghum silage. Neutral detergent fiber in vitro degradability was reduced (p = 0.003) when we used the blend TT + Cit compared to Ros and TT. We observed that only Ros did not reduce acetic acid concentration (p = 0.031) compared to the CON. The essential oils and their blends did not affect losses (p > 0.05). Lactic acid bacteria population increased (p = 0.039) when using the blend Ros + TT + Cit compared to the CON. However, the populations of entero-bacteria and fungi were not affected (p > 0.05) by the essential oils or their blends. For aerobic stability, we observed that Ros increased (p < 0.001) the air exposure time of the sorghum silage. Furthermore, the essential oils impacted the sorghum silage’s pH, which affected (p = 0.003) its aerobic stability. In conclusion, the essential oils did not reduce sorghum silage losses. However, the Ros improved the nutritional quality and aerobic stability of sorghum silage, while the blend Ros + TT + Cit increased the lactic acid bacteria count in the silage. More in-depth studies are needed to elucidate the action of essential oils as silage additives.

1. Introduction

Maintaining an anaerobic environment and low pH are the key factors for preserving stored forage [1]). Microorganisms that can cause silage to deteriorate are inhibited by a combination of acids produced during fermentation, high osmotic pressure, and the absence of oxygen [1,2]. However, when silage is exposed to air, the anaerobic environment is quickly replaced by an aerobic one. This change allows microorganisms, such as Aspergillus sp., Penicillium sp., Clostridium sp., and yeasts, to multiply and cause the silage to deteriorate [3].

Sorghum silage is susceptible to aerobic deterioration mainly due to the high moisture content, which can create a favorable environment for the proliferation of aerobic microorganisms when the silage is exposed to air after opening the silo [4], in addition to the greater availability of substrate for deteriorating microorganisms, producing small amounts of substances that inhibit such microorganisms [5]. With this, using additives and/or inoculants can increase silage safety, optimizing both fermentation and preservation of nutrients and the quality of the final product [6].

Antifungal additives play a crucial role in preserving silage quality, especially when it is exposed to air after the silo has been opened. These additives help prevent the growth of fungi and yeast, which can cause losses during fermentation. In this sense, essential oils (EOs) have been shown to be effective in antifungal control in silage [2,7]. Some studies have shown positive results against a range of microorganisms present in silage [8,9,10,11]. According to [12], essential oils, such as citronella, can disrupt vital metabolic processes in fungi, inhibiting fungal respiration, interfering with protein synthesis and DNA replication, and inducing oxidative stress through the antioxidant properties of essential oils. However, it is important to note that the effectiveness of essential oils may vary depending on the chemical components of each oil and the applied concentration [13]. The use of EO combinations can cause additive, synergistic, or antagonistic effects [14]. In a study conducted by [15], the authors used combinations of carvacrol and thymol, including thymol, eugenol, and a ternary compound of carvacrol; thymol and eugenol had a synergistic effect on in vitro inactivation of Listeria innocua.

In this context, essential oils have been studied because of their antimicrobial power in silage. The species Rosmarinus officinalis L., commonly known as rosemary, originates from the Mediterranean region and is cultivated almost everywhere on the planet. According to [16], the main components of rosemary essential oil are 1,8-cineole (40.55% to 45.10%), camphene (17.40% to 19.35%), and α-pinene (10.73 to [16] 15.06%). Rosemary essential oil has excellent antibacterial and antifungal characteristics. Citronella (Cymbopogon winterianus) is widely cultivated in the planet’s tropical regions. Citronella essential oil is rich in citronellal (40%), geraniol (27.44%), and citronellol (10.45%), which are responsible for antibacterial and antifungal activities [17]. Melaleuca, commonly called tea tree, is a plant native to southern Australia. The essential oil of tea tree is composed of terpinene–4–ol (42%), γ-terpinene (19%), and α-terpinene (10%). These compounds are responsible for antibacterial and antifungal activities [18].

Thus, we hypothesized that using essential oils of rosemary, citronella, and tea tree and their blends would reduce fermentative losses in sorghum silage, improving nutritional value and aerobic stability. We aimed to evaluate the effect of these essential oils and their blends on the fermentative profile, losses by gases and effluents, nutritional value, microbial community, and aerobic stability of sorghum silage.

2. Materials and Methods

2.1. Location

The experiment took place in the municipality of Campos dos Goytacazes, RJ, Brazil (21°45′45″ S, 41°17′06″ W, and 8 m a.s.l.) between May and September 2023. The location’s climate is classified as Aw, which means it is a humid tropical climate with rainy summers and dry winters, according to the Köppen–Geiger classification system [19], with an annual rainfall of 1020 mm in this area.

The Institutional Ethics Committee on the Use of Experimental Animals approved all experimental procedures under protocol 503/2021.

2.2. Harvesting, Ensiling, and Treatments

Sorghum plants (Sorghum bicolor (L.) Moench) were manually harvested (average dry matter content of 363.84 g/kg as-fed) and chopped in a stationary forage harvester (JF Maxxium, JF Agricultural Machinery LTDA, Itapira, Brazil) to an average particle size of 1.5 cm.

Cylindrical silos made of polyvinyl chloride (PVC), measuring 150 mm in diameter and 50 cm in height, were used in this study. These silos were equipped with a Bunsen valve for gas exhaust and contained approximately 600 g of dry sand, separated by cotton fabric to assess effluent losses. The silos were filled to a density of 600 kg/m³ (as-fed) and stored at 25 ± 3.2 °C for 60 days.

The study was conducted using a completely randomized design, which included eight treatments and four replicates. The evaluated treatments were the following: control (CON) without any essential oil; rosemary (Ros); tea tree (TT); citronella (Cit); Ros + TT (50% rosemary + 50% tea tree); Ros + Cit (50% rosemary + 50% citronella); TT + Cit (50% rosemary + 50% citronella); and Ros + TT + Cit (33% rosemary + 33% tea tree + 33% citronella). Blends were produced from essential oils after extraction. A 1000 mg/kg dose of ensiled mass (as-fed basis) was used for each treatment.

The essential oils were commercially (FERQUIMA Essential Oils Industry, Vargem Grande Paulista, Brazil) purchased and extracted through a steam distillation process. The specifications of the rosemary essential oil are as follows: density (20 °C) = 0.9–0.93 (g/mL) and refractive index (20 °C) = 1.460–1.475 (g/cm). The main components are 1,8-cineol (40%), camphor (15%), α-pinene (13%), and β-pinene (7%). The specifications of the tea tree essential oil are as follows: density (20 °C) = 0.885–0.906 (g/mL) and refractive index (20 °C) = 1.470–1.482 (g/cm). The main components are terpinene-4-ol (41%), γ-terpinene (21%), and α-terpinene (9%). The specifications of the citronella essential oil are as follows: density (20 °C) = 0.875–0.895 (g/mL) and refractive index (20 °C) = 1.463–1.473 (g/cm). The main components are β-citronella (32.7%), geraniol (28.9%), and citronellol (9.6%).

2.3. Chemical Composition and In Vitro Assay

Plant and silage samples were dried in a forced-air oven at 55 °C for 72 h. After drying, the samples were ground in a Wiley mill (Tecnal, Piracicaba, São Paulo, Brazil) fitted with a 1 mm sieve. We analyzed dry matter (DM, method 967.03), crude fat (CF, method 2003.06), ash (method 942.05), and crude protein ([N × 6.25] CP) as described by [20]. Neutral detergent fiber (NDF) was analyzed with sodium sulfite and two additions of a standardized heat-stable amylase solution, excluding ash (aNDF, INCT-CA method F-001/1; [21], acid detergent fiber (ADF), according to INCT-CA F-003/1, as described by [21], and lignin (Lig) (INCT-CA method F-005/1; [21]). Non-fiber carbohydrate (NFC) content was estimated as follows: $NFC\left(\mathrm{g}/\mathrm{kg}\right)=1000-CP-\mathrm{CF}-Ash-NDF.$ Hemicellulose was calculated based on the difference between NDF and ADF, and cellulose was calculated based on the difference between ADF and lignin, all expressed in g/kg DM.

The in vitro degradation of DM and NDF was determined following the methodology recommended by [22]. Each sample was analyzed in triplicate by weighing approximately 200 mg of the sample and transferring it into 100 mL amber bottles. We added 20 mL of buffer solution and inoculum to the bottles and sealed them with rubber stoppers to prevent fermentation gas escape. The inoculum was made using [23] buffer and ruminal fluid from three sheep with rumen cannulas and 52 ± 5.2 kg body mass. The animals were fed a total mixed ration with 180 g of crude protein kg/DM and 520 g of neutral detergent fiber kg/DM and supplemented with a mineral premix. After 48 h of incubation, the bottles were withdrawn from the water bath and immediately rinsed with hot distilled water exceeding 90 °C. Following the rinsing, the resulting material was dried (55 °C for 24 h followed by 105 °C for 16 h), and the weight was recorded, yielding the undigested residue of DM. Subsequently, this material underwent analysis for NDF content, resulting in the undigested residue of NDF. The degradability (D) of DM and NDF was calculated according to the equation:

$$D=(M-\left[R-B\right]/M)\times 1000$$

where M = incubated mass (g) of DM or NDF; R = residue of DM or NDF from incubation (g); and B = residue of DM or NDF from blanks (g).

2.4. Gas and Effluent Losses and Dry Matter Recovery

Losses were calculated according to the equations proposed by [24].

Gas losses were calculated using Equation (1):

$$GL=\left(WSWE-WSWO\right)/EDM$$

(1)

where GL = gas loss (g/kg DM), WSWE is the whole silo weight at ensiling (g), WSWO is the whole silo weight at the opening (g), and EDM is the ensiled dry matter (kg).

Effluent losses were calculated according to Equation (2):

$$EL=\left(ESWO-ESWE\right)/EDM$$

(2)

where EL = effluent loss (g/kg DM), ESWO is the empty silo weight at the opening (g), and ESWE is the empty silo weight at ensiling (g).

Dry matter recovery was calculated using Equation (3):

$$DMR=ODM/EDM$$

(3)

where DMR = dry matter recovery (g/kg DM) and ODM is the DM at the opening (g).

Flieg’s score was calculated by assessing the DM and pH values of silages, following the equation by [25]:

$$Flie{g}^{\prime }sScore=200+\left(2\times \%DM-15\right)-40\times pH$$

(4)

2.5. Fermentative Profile and Microbial Count

Upon opening each silo, the contents were thoroughly mixed to ensure homogeneity. A 25 g sample of fresh silage was then collected and blended with 225 mL of saline solution (8.5 g of NaCl/L distilled water) for 1 min. The mixture was then filtered, and three separate aliquots were obtained. Two were used to determine the fermentative profile, while the third was used to determine the microbial community. The pH of the first aliquot was measured, and 0.036 N sulfuric acid was added. The mixture was then frozen to later assess the ammonia nitrogen content (NH₃-N) with magnesium oxide using the procedure described by [26]. The second aliquot was used to measure the concentration of short-chain fatty acids (SCFAs). A total of 0.5 mL of sulfuric acid solution (50%) was added to this aliquot, according to [27], and it was stored at −18 °C until analysis. The concentrations of SCFAs were determined using High-Performance Liquid Chromatography (HPLC; YL9100 HPLC System [Young Lin]) with a REZEX RCM-Monosaccharide Ca⁺² (8%) column. Ultra-pure water served as the mobile phase with a flow rate of 0.7 mL/min, maintaining the column at 60 °C, and a refractive index detector was employed.

The third aliquot of the aqueous silage extract was filtered, 9 mL was added in a sterile falcon tube, and it was subjected to serial dilutions (10⁻¹ to 10⁻⁶). We used the Violet Red Bile (VRB) culture medium to count enterobacteria and incubated it at 37 °C for 24 h (h). For the fungi count, the Potato Dextrose Agar (PDA) was incubated at 30 °C for four days. The De Man, Rogosa, Sharpe (MRS) was used for lactic acid bacteria count by incubating at 37 °C for 48 h. Microbial counts were expressed as colony-forming units per gram (cfu g⁻¹) and transformed to log₁₀ to obtain the lognormal distribution.

2.6. Aerobic Stability

After opening the silos, 2.0 kg of silage was placed in plastic buckets with a capacity of 5.0 kg. These buckets were then left for seven days at room temperature to evaluate their aerobic stability [28]. To monitor the temperature, data loggers not connected to the computer (Log 110 EXF Inconterm, Porto Alegre, Brazil) were inserted 10 cm deep in the center of the silage mass, and readings were taken every 6 h. Additionally, samples (200 g) were collected from silos of each treatment every 24 h to measure the pH after exposure to oxygen. The aerobic stability was calculated as the time in hours when the temperature of the silage exceeded the ambient temperature by 2 °C after air exposure [27].

2.7. Statistical Analysis

Data on chemical composition, gas and effluent losses, microbial count, fermentative profile, in vitro degradability, gross energy, and Flieg’s score were compared using Tukey’s test with a significance level of 0.05. The analysis was performed using the MIXED package of SAS (SAS OnDemand for Academics, SAS Institute Inc., Cary, NC, USA). A tendency was considered when the p-value was between 0.05 and 0.10. The Shapiro–Wilk test (PROC UNIVARIATE) was used to check for data normality.

The following statistical model was used:

$$Y_{ij}=\mu +{\alpha }_i+e_{ij}$$

In which $Y_{ij}$ is the value observed for the variable under study, referring to the j-th replicate of the i-th factor level, α; $\mu$ is the mean of all experimental units for the variable under study; ${\alpha }_i$ is the addition of essential oils and their blends in silages with i = 1, 2, 3, 4, 5, 6, 7, 8; and $e_{ij}$ is the error associated with the observation.

The aerobic stability and pH data were analyzed as repeated measures over time using regression analysis with a significance level of 0.05 using the MIXED package of SAS (SAS OnDemand for Academics, SAS Institute Inc., Cary, NC, USA, https://www.sas.com/en_us/software/on-demand-for-academics.html, accessed on 21 April 2024).

The following statistical model was used:

$$Y_{ijk}=\mu +{\alpha }_i+{\tau }_j+\alpha {\tau }_{ij}+e_{ijk}$$

In which $Y_{ijk}$ is the value observed for the variable under study, referring to the k-th replicate of the i-th factor level α in the j-th hour; $\mu$ is the mean of all experimental units for the variable under study; ${\alpha }_i$ is the addition of essential oils and their blends in silages with i = 1, 2, 3, 4, 5, 6, 7, 8; ${\tau }_k$ is the random effect of the evaluation hours with j = 0.24, …, 144 for pH and 0, 8, 16, …, 162 for temperature; $\alpha {\tau }_{ij}$ is the interaction between essential oils and their blends and evaluation hours; and $e_{ijk}$ is the error associated with observation $Y_{ijk}$.

3. Results

The addition of essential oils and their blends had a significant impact (p < 0.05) on the chemical composition of sorghum silage. The CP content increased (p < 0.001) with the use of essential oils and their blends (

Table 1. Effects of the essential oils and their blends on the chemical composition and in vitro degradability of sorghum silage.

Variables	Sorghum	Essential Oils								SEM	p-Value
		CON	Ros	TT	Cit	Ros + TT	Ros + Cit	TT + Cit	Ros + TT + Cit
DM	363.84	345.01	365.28	387.18	404.21	367.76	378.95	331.55	352.8	6.747	0.465
CP	47.79	42.28 c	53.49 a	47.77 b	49.13 ab	50.10 ab	51.01 ab	46.43 bc	49.61 ab	0.462	<0.0001
NDF	685.26	726.19	670.3	687.99	701.34	738.72	709.37	733.64	723.32	5.227	0.091
Lig	15.46	14.76 b	17.96 a	15.26 ab	14.02 b	15.82 ab	14.97 ab	15.47 ab	16.94 ab	0.233	0.007
NFC	186.74	120.53	174.04	172.52	151.09	109.63	137.45	132.63	123.5	5.189	0.129
Hem	226.94	259.8	237.0	225.63	246.22	244.02	238.04	254.52	255.6	2.586	0.135
Cell	442.86	451.62 ab	415.34 b	447.09 ab	441.1 ab	478.89 a	456.36 ab	463.65 ab	450.78 ab	3.754	0.031
IVDMD	487.67	514.96	514.35	538.88	533.68	562.99	548.81	564.42	582.31	5.444	0.201
IVNDFD	570.48	586.83 b	584.73 b	573.74 b	610.54 ab	639.32 ab	616.93 ab	655.79 a	640.36 ab	5.617	0.003
GE	16.46	16.74	16.97	16.74	17.24	17.09	17.16	16.96	17.39	0.069	0.715

Sorghum = sorghum plant before ensiling; rosemary (Ros); tea tree (TT); citronella (Cit); Ros + TT (50% rosemary plus 50% tea tree); Ros + Cit (50% rosemary plus 50% citronella); TT + Cit (50% rosemary plus 50% citronella); and Ros + TT + Cit (33% rosemary plus 33% tea tree plus 33% citronella). SEM = standard error of the mean; DM = dry matter; CP = crude protein; NDF = neutral detergent fiber; Lig = lignin; NFC = non-fibrous carbohydrate; Hem = hemicellulose; Cell = cellulose; IVDMD = in vitro dry matter degradability; IVNDFD = in vitro neutral detergent fiber degradability; and GE = gross energy, all expressed as g/kg, except DM, expressed as as-fed, and GE, expressed as MJ/kg DM. Means followed by the different letters in a line differ significantly according to Tukey’s test (p < 0.05).

). The analysis of the fiber fraction revealed that the Ros increased the lignin content (p = 0.007) compared to the CON. The Cell content differed between essential oils and blends, e.g., Ros reduced it by 13.27% compared to the blend Ros + TT (Table 1). NDF degradability was reduced (p = 0.003) when we used the blend TT + Cit compared to Ros and TT. The other variables were not (p > 0.05) influenced by the oils (Table 1). The Ros and TT showed a tendency (p = 0.091) to reduce NDF content (Table 1). However, the variables NFC, Hem, IVDMD, and GE were not influenced (p > 0.05) by essential oils or their blends (Table 1).

When evaluating the fermentative profile, we observed that only Ros did not reduce the acetic acid concentration (p = 0.031) compared to the CON (

Table 2. Effects of the essential oils and their blends on fermentative profile of sorghum silage.

Variables	Essential Oils								SEM	p-Value
	CON	Ros	TT	Cit	Ros + TT	Ros + Cit	TT + Cit	Ros + TT + Cit
T, °C after opening the silo	23.63	24.18	24.00	24.43	24.13	23.98	24.23	23.73	0.200	0.997
pH after opening the silo	4.41	4.56	4.60	4.51	4.42	4.57	4.39	4.43	0.022	0.341
NH3-N, g/kg CP	0.65	0.89	0.68	0.58	0.80	0.59	0.67	0.74	0.028	0.251
Lactic acid, g/kg DM	35.12	65.44	40.72	21.33	61.78	37.36	31.43	42.05	4.191	0.533
Acetic acid, g/kg DM	57.97 a	55.08 a	13.24 d	28.68 c	36.27 b	37.93 b	11.88 d	37.98 b	3.446	0.031
Propionic acid, g/kg DM	0.04	0.09	0.14	0.29	0.35	0.33	0.13	0.16	0.026	0.242
Butyric acid, g/kg DM	0.04	0.09	0.07	0.19	0.15	0.08	0.12	0.08	0.014	0.610

Rosemary (Ros); tea tree (TT); citronella (Cit); Ros + TT (50% rosemary plus 50% tea tree); Ros + Cit (50% rosemary plus 50% citronella); TT + Cit (50% rosemary plus 50% citronella); and Ros + TT + Cit (33% rosemary plus 33% tea tree plus 33% citronella). SEM = standard error of the mean; T = temperature; NH₃-N = ammoniacal nitrogenMeans followed by the different letters in a line differ significantly according to Tukey’s test (p < 0.05).

). The other variables remained unchanged (p > 0.05) with the use of essential oils and their blends, among them lactic acid (p = 0.533), which is an important indicator of silage fermentation (Table 2).

The essential oils and their blends did not affect gas losses (p = 0.240), effluents (p = 0.891), or Flieg’s score (p = 0.932) (

Table 3. Effects of the essential oils and their blends on losses and dry matter recovery of sorghum silage.

Variables	Essential Oils								SEM	p-Value
	CON	Ros	TT	Cit	Ros + TT	Ros + Cit	TT + Cit	Ros + TT + Cit
Gas losses, g/kg DM	48.43	42.97	47.41	35.10	46.95	35.37	33.89	46.19	6.929	0.240
Effluent losses, g/kg DM	15.62	14.89	10.29	11.23	15.62	16.14	13.21	16.73	3.942	0.891
Dry matter recovery, g/kg	935.9 b	942.2 ab	942.3 ab	953.7 a	937.4 b	948.5 ab	952.9 a	952.1 b	0.764	0.012
Flieg’s score	77.60	75.56	78.23	85.44	81.65	77.79	75.81	78.36	1.519	0.932

Rosemary (Ros); tea tree (TT); citronella (Cit); Ros + TT (50% rosemary plus 50% tea tree); Ros + Cit (50% rosemary plus 50% citronella); TT + Cit (50% rosemary plus 50% citronella); and Ros + TT + Cit (33% rosemary plus 33% tea tree plus 33% citronella). SEM = standard error of the mean Means followed by the different letters in a line differ significantly according to Tukey’s test (p < 0.05).

). However, Cit and its blend TT + CIT increased dry matter recovery (p = 0.012) in sorghum silage (Table 3).

In terms of the microbial count, the LAB population increased (p = 0.039) when using the blend Ros + TT + Cit compared to the CON (Figure 1). However, the populations of enterobacteria and fungi were not affected (p > 0.05) by the essential oils or their blends (Figure 1).

Regarding the aerobic stability, we observed that Ros increased (p < 0.001) the air exposure time of sorghum silage in 138 h (Figure 2a). Furthermore, the essential oils impacted the sorghum silage’s pH, which affected (p = 0.003) its aerobic stability (Figure 2b).

4. Discussion

The increased CP levels in sorghum silage with the use of essential oils and their blends may be related to the antimicrobial action of the oils. Silages contain microorganisms, such as lactic acid bacteria (LAB), enterobacteria, and clostridia, with proteolytic activity [9]. According to [14], essential oils can inhibit proteolysis through antimicrobial activity. Another factor is the antioxidant action of essential oils, which can reduce protein breakdown. Antioxidants can intercept free radicals generated by cellular metabolism or exogenous sources, preventing the attack on amino acids and peptides [29]. Thus, the antioxidant properties of rosemary essential oil are attributed to 1,8-cineole, which acts as a free-radical-terminating agent and reactive oxygen species chelator [30]. According to the findings of our study, the NH₃-N remained unaffected (p = 0.251) despite it being an important indicator of protein degradation (Table 2). However, the antimicrobial properties of Ros and TT may likely have impacted the NDF degradability (Table 1). During the process of silage fermentation, various microorganisms, such as BAL, acetic acid bacteria, and fungi, play a crucial role in breaking down the main components of the plant cell wall, including cellulose, hemicellulose, and pectin [31]. Furthermore, the reduction may have occurred due to the antibacterial activity in the rumen fluid’s Archaea, protozoa, and cellulolytic bacteria (Fibrobacter succinogenes, Ruminococcus flavefaciens, and R. albus) [32].

Regarding the fermentative profile of sorghum silage, the increased acetic acid concentration is a highly determining factor in the inhibition of yeast metabolism during fermentation (anaerobiosis), resulting in significant improvements in the aerobic stability of silages [3,6]. This fact is due to the antifungal activity of acetic acid, which can suppress the growth of lactate-assimilating fungi and yeasts that start aerobic deterioration [6,33]. Therefore, adequate concentrations of acetic acid can reduce total losses in storage and post-opening silage [33].

The production of high-quality silage faces a great challenge in reducing DM losses. These losses, combined with quality changes, occur during every step of the ensiling process, thereby reducing silage quality [34]. Although some losses are unavoidable, good practical management can help reduce or compensate for these losses to ensure a good-quality forage [34]. Essential oils and their blends were not efficient in reducing clostridial activity, as indicated by the concentration of butyric acid (Table 2), a marker of clostridial fermentation [33]; consequently, they did not reduce losses due to gases and effluents (Table 3). However, the DMR showed values higher than 93%, as oils and their blends led to improvements. For instance, Cit increased by 1.86% and TT + Cit increased by 1.78% compared to the CON (Table 3).

During the ensiling process, lactic acid (3.86 pKa) produced by lactic acid bacteria (LAB) is generally the most abundant acid found in silage. This acid contributes the most to the pH drop during fermentation, which helps to preserve the forage mass [33,35]. In the present study, we observed that the Ros + TT + Cit blend resulted in higher BAL counts than the CON (Figure 1). This may be due to the interaction of antimicrobial properties, which inhibited the growth of undesirable microorganisms, such as spoilage bacteria and fungi [9]. It creates a more favorable environment for the growth of LAB, which is beneficial for the ensiling process [9].

Both sorghum and corn have desirable characteristics for fermentation, such as epiphytic microbiota, dry matter content, water-soluble carbohydrates, and buffer capacity (BC). These characteristics are essential for the ensiling process [34]. However, sorghum silage is vulnerable to losses from aerobic deterioration due to the greater availability of substrate for spoilage microorganisms in well-fermented silages, in addition to containing a lower content of substances that inhibit such microorganisms [5]. In this study, we found that using Ros in sorghum silage increased its exposure time to air (Figure 2a). This can be attributed to two factors. The first factor is the high concentration of acetic acid in the silage (Table 2). The second factor is the antifungal properties of Ros (specifically, α-pinene and β-pinene). As per [12], essential oils can inhibit fungal growth by disrupting vital metabolic processes, inhibiting respiration, interfering with protein synthesis and DNA replication, and inducing oxidative stress through their antioxidant properties. Regarding pH, essential oils showed values between 4.3 and 4.6 during the first 48 h of air exposure (Figure 2b). Thus, certain conditions, such as temperature, absence of oxygen, and pH, are favorable for preserving forage. A lower-pH environment inhibits the growth of spoilage organisms, such as molds and yeasts, which are less active in acidic conditions. This helps in maintaining silage quality upon air exposure [3,6].

5. Conclusions

The essential oils and their blends had different effects on sorghum silage. Among the essential oils, Ros and blends containing Ros showed greater efficiency. Ros helped improve the nutritional quality and aerobic stability of sorghum silage, while the blend Ros + TT + Cit increased the lactic acid bacteria count in the silage. However, the essential oils and their blends did not reduce sorghum silage losses. More in-depth studies are needed to elucidate the action of essential oils as silage additives.