Essential oil blends of Copaifera langsdorffii and Eucalyptus staigeriana Branch on fermentation parameters, microbial counts, and aerobic stability of whole-plant corn silage

ABSTRACT

The primary concern in corn silage is aerobic deterioration. This study aimed to evaluate the impact of essential oil (EO) blends extracted from copaiba (Copaifera langsdorffii) (Co) and Eucalyptus staigeriana Branch (ES) on the fermentation parameters and losses, nutritional value, microbial counts, and aerobic stability of corn silage. A completely randomized design was employed with four treatments and four replicates. The following treatments were employed: control (CON) – corn ensiled without EO; blend 50:50 (50 % ES plus 50 % Co); blend 75:25 (75 % ES plus 25 % Co); blend 25:75 (25 % ES plus 75 % Co). The dose was administered at a rate of 500 mg kg^–1 of ensiled mass (as-fed basis). The chemical composition, in vitro degradability, NH₃-N, pH, acetic, propionic, and butyric acids, aerobic stability, and microbial counts of silages were evaluated. The 75:25 blend reduced (p < 0.038) crude protein (CP) by 7.96 % compared to the 25:75 blend. However, the 50:50 blend reduced (p < 0.03) the hemicellulose (HEM) content of the silage in comparison to the other treatments. The blends were observed to increase (p = 0.046) the concentration of acetic acid. The propionic acid concentration was reduced by 88.13 % with the 25:75 blend compared to the 50:50 blend. The blends increased (p = 0.003) gas losses. The fungal population was drastically reduced (p = 0.048) by the 25:75 blend compared to the other treatments. It can be concluded that the 50:50 blend resulted in high concentrations of acetic and propionic acids, thereby improving the aerobic stability of corn silage.

Keywords
Zea mays ; antifungal; fermentative quality; secondary plant metabolites

Introduction

The inevitable degradation of silage upon exposure to air results in a significant loss of dry matter (DM) (Borreani et al., 2018). The aerobic deterioration of silage is intricately linked to the increase in temperature and pH that results from the metabolic activities of yeasts and bacteria acting on sugars and organic acids (Kung Jr et al., 2018). In particular, corn silage exhibits heightened susceptibility to aerobic deterioration because well-fermented silages provide a greater substrate availability for deteriorating microorganisms and produce lower levels of inhibitory substances against such microorganisms (Wilkinson and Davies, 2012).

The addition of antifungal additives can inhibit the growth of yeast and fungi, thereby reducing fermentation losses and deterioration (Muck et al., 2018). Over the past decade, research efforts have intensified to assess the efficiency of antifungals in silage. This is evidenced by studies conducted by Chaves et al. (2012), Foskolos et al. (2016), Turan and Soycan-Önenç (2018), Cantoia Jr et al. (2020). Nevertheless, there has been a paucity of research examining the combined use of essential oils (EOs) in silage, with only a few studies addressing this topic, including works by Kung Jr et al. (2008) and Soycan-Önenç et al. (2015).

The development of studies with EO blends is promising, as the possibility of obtaining additive and synergistic effects can enhance the efficacy and persistence of the practice (Calsamiglia et al., 2007). Therefore, a comprehensive understanding of these interactions is essential for optimizing the benefits of EOs in various applications, particularly in silage production (Nikkhah et al., 2017). Copaiba (Copaifera langsdorffii Desf.) (Co) is widely distributed in the Amazon, Central West regions of Brazil, and South America (Biavatti et al., 2006). The Co is a mixture of sesquiterpenes and diterpenes, among which copalic acid and sesquiterpenes (β-caryophyllene and α-copaene) have been identified as the primary components of the oil. These compounds have been demonstrated to possess anti-inflammatory, antibacterial, antifungal, and antiedemic properties (Veiga Jr and Pinto, 2002). In contrast, Eucalyptus staigeriana Branch (ES) is a species from the Cape York peninsula in the Queensland state, Australia. It is adapted to hot and sub-humid climatic zones. The main chemical compounds present are citral and limonene, which have been demonstrated to possess antibacterial and antifungal properties (Vitti and Brito, 2003).

Accordingly, this study hypothesized that the utilization of blends comprising EO from Co and ES could mitigate fermentation losses in corn silage, thereby increasing the duration of air exposure for the silage. Consequently, this study aimed to evaluate the influence of blends of EO from Co and ES on the fermentative parameters and losses, nutritional value, microbial count, and the aerobic stability of corn silage.

Materials and Methods

The research was conducted at the Laboratório de Zootecnia of the Universidade Estadual do Norte Fluminense Darcy Ribeiro (UENF) in Campos dos Goytacazes, situated in the Rio de Janeiro state, Brazil (21°45’45” S, 41°17’06” W, altitude 8 m). The climatic conditions in northern Rio de Janeiro are categorized as Aw, representing a humid tropical climate, as defined by the Köppen-Geiger. This classification is characterized by rainy summers and dry winters (Alvares et al., 2013).

Silage preparation

Corn plants (Zea mays L.) cv. UENF MSV2210 were manually harvested with an average DM content of 323.17 g kg^–1 on a fresh matter basis. Subsequently, the harvested material underwent chopping using a stationary forage harvester (JF Maxxium, JF Agricultural Machinery LTDA) to achieve an average particle size of 1.5 cm.

The study employed polyvinyl chloride (PVC) silos with dimensions of 150 mm in diameter and 50 cm in height, equipped with a Bunsen valve for gas release. At the base of the PVC silos, approximately 600 g of dry sand was isolated from the ensiled mass by a layer of cotton fabric, which served to quantify effluent losses. The density of each silo was 600 kg m³ (fresh matter), and then all silos were stored in a facility at a temperature of 25 ± 2.3 °C for 60 days.

This study employed a completely randomized design comprising four treatments and four repetitions. The following treatments were evaluated: control (CON) corn ensiled without EO; blend 50:50 (50 % ES plus 50 % Co); blend 75:25 (75 % ES plus 25 % Co); blend 25:75 (25 % ES plus 75 % Co). As in previous studies, the dose administered was 500 mg kg^–1 of ensiled mass (as-fed basis) (Kung Jr et al., 2008; Chaves et al., 2012).

The EOs of Co and ES were purchased from a commercial source and extracted through steam distillation. The specifications of the oil are as follows: Co density (20 °C) = 0.88-0.91 (g mL^–1), refractive index (20 °C) = 1.496-1.506 (g cm³), and the main component present is b-caryophyllene = 51 %. ES density (20 °C) = 0.87-0.89 (g mL^–1), refractive index (20 °C) = 1,470-1,490 (g cm³) and the main components present are: limonene = 28 %, citral = 24 %, α-terpinolene = 9 %.

Chemical composition

The plant and silage samples were dried in a forced air oven at 55 °C for 72 h. They were then processed further using a Wiley mill equipped with a 1 mm sieve. The chemical composition was determined by the methodology established by the AOAC (2019) for DM contents (method 967.03), crude fat (CF, method 2003.06), ash (AOAC method 942.05), and crude protein ([N × 6.25] CP, method 984.13). The fibrous fraction was determined following the recommendations presented by Detmann et al. (2012), precisely the procedures for neutral detergent fiber (NDF, INCT-CA method F-001/1), acid detergent fiber (ADF, INCT-CA F-003/1), and lignin (Lig, INCT-CA method F-005/1). Non-fibrous carbohydrate (NFC) was estimated according to the following formula: NFC (g kg^–1) = 1000 – CP – Fat – Ash – NDF. Hemicellulose (HEM) was calculated by subtracting NDF from ADF, whereas cellulose content was computed as the difference between ADF and Lig, all expressed in g kg^–1 DM.

The gross energy (GE) of the samples was analyzed using an adiabatic bomb calorimeter PARR (Model 2081).

In vitro degradability

The Animal Research Ethics Committee of the UENF approved all experimental procedures under protocol number 588/2023.

The study utilized three rumen-fistulated sheep with an average weight of 55 kg (standard deviation of 4.8 kg) as ruminal fluid donors. The animals were housed in collective stalls, equipped with feeders and waterers. Prior to the collection of ruminal fluid, the sheep underwent a 14-day adaptation period to a diet comprising corn silage and concentrate feed, sufficient to meet their maintenance requirements. Subsequently, ruminal fluid was collected before the morning meal in accordance with the protocol outlined by Yáñez-Ruiz et al. (2016). Subsequently, amber flasks containing 50 mL of the previously prepared inoculum (a 1:4 ratio of ruminal fluid to buffer solution, as recommended by McDougall, 1948) and 500 mg of DM (standard deviation of 10 mg) from the silage samples were utilized. Throughout the incubation period, the flasks were intermittently agitated to ensure homogeneity of the contents.

The in vitro degradability was determined following the methodology Goering and Van Soest (1970) recommended. For each sample, three replicates of approximately 200 mg of partially dried sample were weighed and placed in 100 mL amber flasks with 20 mL buffer solution and inoculum.

Following a 48-h incubation period, the flasks were removed from the water bath and immediately rinsed with hot distilled water (> 90 °C). The incubated material was filtered through quantitative filter paper (55 L s^–1 m² air permeability). After washing, the materials were dried (55 °C 24 h^–1 followed by 105 °C 16 h^–1) and weighed, resulting in the undigested DM residues. Subsequently, the material was analyzed for NDF content, resulting in the undigested residue of NDF. The methodology described by Detmann et al. (2012) was employed to evaluate the in vitro degradability of NDF.

The degradability (D) of DM and NDF was determined using the following equation:

$D=(M-[R-B\left]\right)/M)\times 1000$ (1)

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

Gas and effluent losses

Losses were calculated using the equations described by Jobim et al. (2007):

Gas losses were calculated as follows:

$GL=(SMB-SMA)/(EFM\times EDM)\times 100$ (2)

where: GL = gas losses (% DM); SMB = silo mass before ensiling (kg); SMA = silo mass after opening (kg); EFM = ensiled forage mass (kg); and EDM = ensiled DM (% DM).

Effluent losses were calculated according to the equation:

$EL=\left\{\right[(MESo-Ms)-(MESc-Ms)\left]/EFM\right\}$ (3)

where: EL = effluent losses (kg t^–1 fresh matter); MESo = mass of the empty silo + mass of the sand after opening (kg); Ms = mass of the empty silo (kg); MESc = mass of the empty silo + mass of the sand at closure (kg); and EFM = ensiled forage mass (kg).

DM recovery was calculated as follows:

$DMR=(FMO\times DMO)/(EFM\times EDM)\times 100$ (4)

where: DMR = DM recovery (% DM); FMO = forage mass at opening (kg); DMO = DM at opening (%); EFM = ensiled forage mass (kg); and EDM = ensiled DM (% DM).

Fermentation profile

Upon opening each silo, the contents were homogenized, and a 25 g sample of fresh silage was extracted. The sample was blended with 225 mL of saline solution (8.5 g NaCl L^–1 of distilled water) for 1 min. Subsequently, the mixture was filtered, resulting in the isolation of three distinct aliquots. Two aliquots were utilized to determine the fermentation parameters, while the third was designated for microbial counts. In the first aliquot, the pH was measured, and 0.036 N sulfuric acid was added to facilitate the determination of ammonia nitrogen content (NH₃-N) through distillation with magnesium oxide, as recommended by Fenner (1965). The second aliquot was employed for the quantification of short-chain fatty acids (SCFA). Subsequently, 0.5 mL of sulfuric acid solution (50 %) was added to this aliquot, in accordance with the protocol described by Ranjit and Kung Jr. (2001). The determination of SCFA was conducted using high-performance liquid chromatography (HPLC; YL9100 HPLC System Young Lin), equipped with a column REZEX RCM-Monosaccharide Ca + 2 (8 %), by the methodology described by Meirelles Jr et al. (2024).

Microorganism counts

The third aliquot of the aqueous silage extract was subjected to filtration, and 9 mL of the resulting filtrate was transferred to a sterile Falcon tube. There, it underwent serial dilutions ranging from 10-1 to 10-6. The microbial count was performed in triplicate for each dilution. The count of Enterobacteria was conducted using a Violet Red Bile (VRB) culture medium, with an incubation period of 24 h at 37 °C. The fungal count was conducted using potato dextrose agar (PDA) and an incubation period of four days at 25 °C. The count of lactic acid bacteria was performed using De Man, Rogosa, and Sharpe (MRS) agar, with an incubation period of 48 h at 37 °C. The microbial counts were expressed as colony-forming units per gram (CFU g^–1). Subsequently, the microbial count data were transformed logarithmically to achieve a lognormal distribution.

Aerobic stability

Following the opening of the silos, 2.0 kg of silage was transferred into plastic buckets with a capacity of 5.0 kg each. The silage was maintained in the buckets for a period of seven days to assess its aerobic stability. The samples were maintained at ambient temperature and monitored at 6-h intervals using data loggers (Log 110 EXF Incoterm) placed at a depth of 10 cm within the silage mass. The duration of time during which the temperature of the silage exceeded the ambient temperature by 2 °C after exposure to air was used to determine aerobic stability (Ranjit and Kung Jr., 2001). Subsequently, the pH of the silage following aerobic exposure was measured at 24-h intervals. Samples weighing 15 g were extracted, diluted in 250 g of distilled water, homogenized in a blender for 1 min, and the pH was measured using a potentiometer (model W3B, Tecnal).

Statistical Analysis

The data were subjected to comparison using Tukey’s test, with a significance level of 0.05, employing the mixed package in SAS (SAS University Edition, SAS Institute Inc.). A tendency was considered when 0.10 > p > 0.05.

The following statistical model was used:

$Y_{ij}=\mu +{\alpha }_i+e_{ij}$ (5)

where: Y_ij is the value observed for the variable under study referring to the j-th repetition of the i-th factor level α; m is the mean of all experimental units for the variable under study; α_i is the addition of blends in silages with i = 1, 2, 3, 4; e_ij is the error associated with the observation Y_ij.

The data on aerobic stability and pH were analyzed as repeated measures over time by regression analysis with a significance level of 0.05, using the MIXED package of SAS (SAS University Edition, SAS Institute Inc.).

The following statistical model was used:

$Y_{ijk}=\mu +{\alpha }_i+{\tau }_j+\alpha {\tau }_{ij}+e_{ijk}$ (6)

where: 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 h; m is the mean of all experimental units for the variable under study; α_i is the addition of blends in silages with i = 1, 2, 3, 4; τ_k is the random effect of the evaluation h with j = 0.24, ..., 144 for pH and 0, 8, 16, ..., 162 for temperature; ατ_ij is the interaction between blends and evaluation h; e_ijk is the error associated with the observation Y_ijk.

Results

The corn silage’s chemical composition was significantly influenced by the blends (p < 0.05). The blends demonstrated an increase (p = 0.003) in the DM content compared to the CON. Regarding the DM content, the 75:25 blend resulted in higher values (p = 0.047) than the CON (Table 1). The CP was also affected by the blends, with the 75:25 blend demonstrating a reduction (p < 0.038) by 7.96 % in the CP content compared to the 25:75 blend (Table 1). However, the 50:50 blend reduced (p < 0.03) the HEM content of the silage compared to the others (Table 1). The other variables were not influenced by the blends (p > 0.05) (Table 1). There was a tendency towards a reduction (p = 0.056) of NDF content when using the 50:50 blend compared to the others (Table 1). Regarding Lig, CON tended to reduce (p = 0.078) compared to blends (Table 1).

Table 1
– Effects of the blends of essential oils on the chemical composition of corn silage.

Variables	Corn	Blends				SEM	p-value
		CON	25:75	50:50	75:25
DM	323	293b	307a	313a	310a	1.92	0.003
OM	261	230b	240ab	245ab	251	1.97	0.047
CP	54.7	60.5ab	63.3a	60.8ab	58.2b	0.44	0.038
CF	23.4	32.6	32.4	36.8	31.9	0.67	0.137
Ashes	61.7	64.9	63.8	65.0	65.0	0.48	0.975
NDF	554	547	551	519	550	3.99	0.056
ADF	267	298	293	284	293	1.59	0.213
Lig	16.0	9.1	12.8	11.6	11.7	0.40	0.078
NFC	306	313	292	313	282	3.98	0.268
HEM	287	249ab	258a	235b	257a	2.76	0.030
Cell	251	289	280	272	281	1.60	0.106

• Corn = corn plant before ensiling; CON = control; 25:75 = 25 % Eucalyptus staigeriana Branch (ES) plus 75 % Copaifera langsdorffii (Co); 50:50 = 50 % ES plus 50 % Co; 75:25 = 75 % ES plus 25 % Co; SEM = standard error of the mean. DM = dry matter; OM = organic matter; CP = crude protein; CF = crude fat; NDF = neutral detergent fiber; ADF = acid detergent fiber; Lig = lignin; NFC = non-fibrous carbohydrate; HEM = hemicellulose; Cell = cellulose, all expressed as g kg^–1, except DM expressed as as-fed. Means followed by the different letters in a line differ significantly by the Tukey’s test (p < 0.05).

As for the in vitro degradability, blends 50:50 and 75:25 tended (p = 0.079) to reduce the in vitro dry matter degradability (IVDMD) compared to the 25:75 blend (Table 2). However, no effect was observed regarding in vitro neutral detergent fiber degradability (IVNDFD) (p = 0.225) and GE (p = 0.494) (Table 2).

Table 2
– Effects of the blends of essential oils on in vitro degradability and gross energy of corn silage.

Variables	Corn	Blends				SEM	p-value
		CON	25:75	50:50	75:25
IVDMD, g kg–1	502	525	555	448	449	14.79	0.079
IVNDFD, g kg–1	283	295	258	305	310	7.47	0.225
GE, MJ kg–1 DM	16.7	16.6	16.8	16.7	16.7	0.03	0.494

• Corn = corn plant before ensiling; CON = control; 25:75 = 25 % Eucalyptus staigeriana Branch (ES) plus 75 % Copaifera langsdorffii (Co); 50:50 = 50 % ES plus 50 % Co; 75:25 = 75 % ES plus 25 % Co; SEM = standard error of the mean. IVDMD = in vitro dry matter degradability; IVNDFD = in vitro neutral detergent fiber degradability; GE = gross energy; DM = dry matter.

The blends did not affect temperature (p = 0.999) and pH (p = 0.627) at the time of silo opening, as well as NH₃-N (p = 0.229) (Table 3). However, analyzing the short-chain acids, the use of blends increased (p = 0.046) acetic acid concentrations, with the 50:50 blend resulting in approximately 57.06 % more acetic acid than the CON (Table 3). Propionic acid was reduced with the 25:75 blend by 87.36 % compared to the 50:50 blend. Butyric acid was unaffected by the blends (Table 3).

Table 3
– Effects of the blends of essential oils on fermentative profile of corn silage.

Variables	Blends				SEM	p-value
	CON	25:75	50:50	75:25
T, °C at opening the silo	22.4	22.5	22.5	22.5	0.17	0.939
pH at opening the silo	3.6	3.5	3.5	3.4	0.03	0.627
NH3-N, g kg–1 CP	7.3	6.7	6.3	6.3	0.31	0.229
Acetic acid, g kg–1	28.0c	61.1a	65.3a	42.3b	4.37	0.046
Propionic acid, g kg–1	0.12ab	0.02b	0.18a	0.09ab	0.02	0.026
Butyric acid, g kg–1	0.30	0.17	0.24	0.30	0.03	0.831

• CON = control; 25:75 = 25 % Eucalyptus staigeriana Branch (ES) plus 75 % Copaifera langsdorffii (Co); 50:50 = 50 % ES plus 50 % Co; 75:25 = 75 % ES plus 25 % Co; SEM = standard error of the mean. T = temperature; CP = crude protein; NH₃-N = ammoniacal nitrogen. Means followed by tvhe different letters in a line differ significantly by the Tukey’s test (p < 0.05).

The blends did not influence effluent loss (p = 0.221) and DM recovery (p = 0.448); however, gas loss (p = 0.003) increased compared with the CON (Table 4). Moreover, no influence (p ≥ 0.05) was detected on the microbial population, although the lactic acid-producing bacteria (LAB) population was reduced by 43.06 % with the 25:75 blend compared to the 50:50 blend. However, the fungal population was drastically reduced (p = 0.048) by the 25:75 blend compared to the others. The blends reduced the amount (kg) of mold in the silage (Table 5).

Table 4
– Effects of the blends of essential oils on losses and dry matter recovery of corn silage.

Variables	Blends				SEM	p-value
	CON	25:75	50:50	75:25
Gas losses, g kg–1 DM	29.34b	31.30a	31.05a	30.73a	0.316	0.003
Effluent losses, g kg–1 DM	12.90	11.23	11.75	10.23	0.896	0.221
DM recovery, g kg–1 DM	956	957	957	959	0.699	0.448

• CON = control; 25:75 = 25 % Eucalyptus staigeriana Branch (ES) plus 75 % Copaifera langsdorffii (Co); 50:50 = 50 % ES plus 50 % Co; 75:25 = 75 % ES plus 25 % Co; SEM = standard error of the mean. DM = dry matter. Means followed by the different letters in a line differ significantly by the Tukey’s test (p < 0.05).

Table 5
– Effects of the blends of essential oils on microbial populations of corn silage.

Variables	Blends				SEM	p-value
	CON	25:75	50:50	75:25
LAB, log10 g–1 fresh silage	2.77	1.97	3.46	2.70	0.762	0.894
Fungi, log10 g–1 fresh silage	3.03b	0.33c	4.35a	3.86a	0.099	0.048
Mold, g of ensiled mass	93.25a	3.68b	6.25b	5.25b	8.500	0.025

• CON = control; 25:75 = 25 % Eucalyptus staigeriana Branch (ES) plus 75 % Copaifera langsdorffii (Co); 50:50 = 50 % ES plus 50 % Co; 75:25 = 75 % ES plus 25 % Co; SEM = standard error of the mean. LAB = lactic acid-producing bacteria. Means followed by the different letters in a line differ significantly by the Tukey’s test (p < 0.05). Did not observe any presence of enterobacteria on bacterial counts.

About aerobic stability, there was no interaction between blends and hours on temperature (p = 0.991) and pH (p = 0.972) in silages (Figure 1A). The blends did not affect temperature (p = 0.551) over the days (Figure 1A). However, the blends tended to reduce the pH (p = 0.084) compared to the CON (Figure 1B).

Figure 1
– Temperature and pH values of corn silage with different blends of essential oils for seven days. CON = control; 50:50 = 50 % Eucalyptus staigeriana Branch (ES) plus 50 % Copaifera langsdorffii (Co); 75:25 = 75 % ES plus 25 % Co; 25:75 = 25 % ES plus 75 % Co. On the panel A) Temperature, and B) pH. Temperature above the room temperature (2 °C): CON (2.4 °C in 36 h); 50:50 (2.5 °C in 66 h); 75:25 (4.8 °C in 60 h); 25:75 (3.6 °C in 60 h).

Discussion

The addition of EO blends to corn silage resulted in an increase in the DM content (Table 1) due to a greater DM recovery and a reduction in mold growth compared to the CON (Tables 4 and 5). The addition of EOs has been demonstrated to restrict microbial growth, thereby reducing DM losses (Li et al., 2022). The CP values exhibited variability according to the blends (Table 1), a finding consistent with the results reported by Soycan-Önenç et al. (2015). According to these authors, the discrepancy in CP content can be attributed to the influence of several active compounds present within EOs or their combinations, which exert an inhibitory effect on proteolysis. Although the blends did not affect NH₃-N in the silage, they reduced losses by proteolysis by an average of 12 % compared to the CON (Table 3). EO probably inhibits protein degradation by interacting with proteolytic bacteria through hydrogen bonds and ionic or hydrophobic interactions, ultimately leading to their inactivation (Foskolos et al., 2016). However, the highest NH₃-N value in the CON (7.32 g kg^–1 CP, Table 3) can be correlated with the DM content (293.43 g kg^–1, Table 1). Moisture can increase proteolysis by favoring the growth of proteolytic bacteria, triggering a more significant enzymatic activity (Vierstra, 1996; Kieliszek et al., 2021). There was a tendency to reduce the NDF content. Consequently, the reduced HEM content with the blend 50:50 is linked to increased lactic acid bacteria (Table 5) and acetic acid (Table 3). This reduction is due to the increased acid hydrolysis caused by HEM (Bolsen et al., 1996).

The 50:50 and 75:25 blends demonstrated a tendency (p = 0.079) to reduce the DM in vitro degradability, probably because of the inhibition of the more intense antibacterial activity on the bacteria that degrade fiber fractions (Patra and Yu, 2012). However, the addition of blends did not influence the in vitro NDF degradability (Table 2). The effect of EOs on the in vitro degradability of DM and NDF remains inconclusive, as it can be affected by factors such as composition, functional groups, and synergistic interactions between compounds. For instance, the position of the hydroxyl group within phenolic compounds is a critical determinant in their antimicrobial effectiveness (Di Pasqua et al., 2007). This phenomenon may explain the higher antimicrobial activity of EO blends of 50:50 and 75:25 in comparison to the other blends (Table 2).

The presence of moderate levels of acetic acid in silage can offer advantages by restraining the growth of molds and yeast, thereby enhancing stability when the silage is exposed to air (Kung Jr et al., 2018). The results of this study demonstrated that silage treated with the 50:50 blend exhibited elevated acetic acid concentrations (Table 3), which resulted in improved aerobic stability of the silage (Figure 1A and B). The application of blends did not result in a change in temperature (Figure 1A). However, the 50:50 blend demonstrated the ability to maintain temperature stability for up to 66 h. In addition, during the 168-h aerobic stability evaluation, the temperature remained below 34 °C (maximum 33.8 °C and minimum 19.9 °C). For optimal silage fermentation, the temperature should be maintained between 20 and 30 °C, as higher temperatures (≥ 37 °C) have been shown to accelerate silage deterioration (Weinberg et al., 2001). In our study, the utilization of the 50:50 blend demonstrated a tendency (p = 0.08) to influence the pH levels, maintaining them between 3 and 4 for up to 96 h (Figure 1B). These levels fall within the recommended range (3.2 to 4.2) for efficient preservation of ensiled material, as McDonald et al. (1991) outlined. Accordingly, the optimal conditions for forage preservation are temperature, absence of oxygen, and pH. These factors prevent the growth of deteriorating microorganisms, including clostridia, yeasts, and molds (McDonald et al., 1991; Muck, 2010). The elevated acetic acid levels improve aerobic stability due to its robust antifungal attributes (Danner et al., 2003; Ferrero et al., 2021). Regarding propionic acid, the observed behavior was like that of acetic acid. The 50:50 blend resulted in an increased concentration of this acid in the silage (Table 3). Similarly, propionic acid contributes to good aerobic stability by inhibiting the growth of molds and yeasts, thereby preventing silage heating (Muck et al., 2018). Conversely, blends did not affect the concentration of butyric acid (Table 3), with values ranging between 0.02 and 0.03 % DM (e.g., 0.005 × 4.008). A concentration of butyric acid exceeding 0.5 % DM indicates clostridial silage fermentation the (Kung Jr et al., 2018). This acid signals clostridial activity, resulting in significant DM loss and energy recovery (Pahlow et al., 2003).

The generation of carbon dioxide (CO₂) and effluents caused the losses attributed to silo fermentation. The percentage of gas losses is typically within the 2-4 % range. The values obtained in the present study fell within the aforementioned range, approximately 3 %. It was observed that the blends resulted in increased gas losses, which may be linked to the oxidation of EOs, which can contribute to the formation of gases such as CO₂ and other volatiles. The oxidation of monoterpenes has been demonstrated to result in the photochemical formation of CO₂, as proposed by Griffin et al. (2007). Conversely, effluent loss is primarily caused by organic compounds such as proteins, sugars, and organic acids, representing a nutritional loss during silage preservation (McDonald et al., 1991).

LAB are primarily responsible for enhancing fermentation. These microorganisms produce lactic acid (pK_a of 3.86), which reduces the pH of the silage and contributes to the preservation of the forage mass (Kung Jr et al., 2018; Silva and Kung Jr, 2022). The blends did not stimulate the overall increase in the LAB population. However, the 50:50 blend demonstrated a 43.06 % increase in LAB compared to the 25:75 blend (Table 5). This may be related to the greater antimicrobial action of the blend, which is in accordance with the findings of Foskolos et al. (2016). Moreover, the 25:75 blend significantly reduced the fungal population (e.g., by 91.45 % compared to blend 75:25) (Table 5), exemplifying enhanced antifungal efficacy. The antimicrobial activity of the blends was effective for mold CON. It is known that EOs can induce cell wall degradation, leading to membrane weakening and changes in permeability, which consequently result in the loss of intracellular components (Nazzaro et al., 2013). However, the effects of interactions between EOs can be additive, synergistic, or antagonistic (Foskolos et al., 2016), a phenomenon observed in this study across the analyzed variables.

The overall result of the 50:50 blend was the production of high concentrations of acetic and propionic acids, which improved the aerobic stability of corn silage.

Acknowledgments

This research was supported by Fundação Carlos Chagas Filho de Amparo à Pesquisa do Estado do Rio de Janeiro (FAPERJ), process number E-26/200.191/2023 and Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq).

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• Data availability statement
  The entire dataset supporting the results of this is available upon request to the corresponding author.
• Declaration of use of AI Technologies
  The authors declare that there was no use of AI technologies in the production of this paper.

Edited by

• Edited by:
  Antonio Faciola

Data availability

The entire dataset supporting the results of this is available upon request to the corresponding author.

Publication Dates

• Publication in this collection
  17 Mar 2025
• Date of issue
  2025

History

• Received
  14 Mar 2024
• Accepted
  28 June 2024