To optimize feeding systems, regarding the use of medium and low quality tropical pastures and forages, and due to the need to increase voluntary intake, productivity and health status of animals, microbial additives are currently used, mostly composed of bacteria of bacillus genus (Musa et al. 2009).
According to FAO (2016), the use of microbial additives (probiotics and ruminal fermentation activating microorganisms) in animal production, contributes to improve the use of food and increase productive performance. Galina et al. (2007) refer that the increase of voluntary intake of animals is the product of the increase of nutrient availability and the stabilization of ruminal environment, as basic elements capable of stimulating the activity of ruminal microorganisms (Ortíz et al. 2002).
It is suggested that rumen pH constitutes an essential physical parameter in digestion and nutrition of ruminants (de Veth and Kolver 2001). This indicator can vary between 5.2 and 7.2, depending on the type of diet and food management (Owen and Goetsch 1989). However, there is no consensus among researchers when assigning a single pH value or range, in which ruminal performance is optimized (Calsamiglia et al. 2002).
Therefore, the objective of this study was to evaluate the effect of a lactic probiotic on voluntary intake and performance of ruminal pH in sheep.
Materials and Methods
Location. The experiment was carried out in the Ruminant Department, belonging to the Institute of Animal Science (ICA, initials in Spanish) of the Republic of Cuba. This facility is located at 22º 53' N and 82º 02' W, at 92 meters above sea level, in San José de las Lajas municipality, Mayabeque province.
Preparation and use of the probiotic. It is a ferment reproduced in Cuba, from SORBIAL line. It was made from live Lactobacillus strains (L. farciminis 3699 and L. rhamnosus 3698), obtained from the rumen of goats, selected by in vitro tests (isolation and purification), associated to metabolic products resulting from lactic fermentation, which gives the product a high nutritional value and microbiological stability (table 1).
% | |
---|---|
Soy bean meal (without fat) | 85.00 |
Milk powder | 6.00 |
Sugar | 4.00 |
Water | 3.00 |
Urea | 1.00 |
Strain | 1.00 |
100 | |
Humidity, % | 12.00 |
Crude protein (CP), % | 30.00 |
Ether extract, % | 1.50 |
Ashes, % | 9.70 |
Cellulose, % | 4.00 |
pH | 3.80-4.20 |
109cfu g-1 | |
109cfu g -1 |
Treatment and design. Four healthy Pelibuey lambs were used, with an initial live weight of 20.75 ± 0.84 kg (15.56 ± 0.63 kg LW0.75) and twelve months old, housed in individual metabolism cages (60 x120 cm). For the analysis, a Latin square design (4x4) was used with periods of 15 days (10 for adaptation and 5 for data collection). The allocation of treatments to animals was carried out at random, according to the statistical design used.
The evaluated experimental treatments consisted of four increasing levels of the probiotic (0, 15, 25 and 35 g d-1) with the concentrate (5 g kg LW-1), which were offered on a single occasion (08:30 am), with access to water and mineral salts at will. The basal diet consisted of grass forages (Megathyrsus maximus and Cynodon nlemfuensis) at free will, so as it allowed a level of rejection higher than 10% of the total offered. Food intake was determined by the difference between the amount of offered and rejected food. Forage and concentrate chemical composition are shown in table 2.
Contribution | Value |
---|---|
Forage | |
DM, % | 90.82 |
OM, % | 91.61 |
CP, % | 7.79 |
ME, MJ kg MS-1 | 7.95 |
NDF, % | 80.08 |
DM, % | 92.30 |
OM, % | 93.80 |
CP, % | 16.00 |
ME, MJ kg MS-1 | 9.20 |
NDF, % | 40.60 |
Estimation of metabolizable energy (ME) for forage according to Maff (1984) and Díaz et al. (1995)
DM-dry matter, OM- organic matter, ME- metabolizable energy, NDF- neutral detergent fiber
Sanitary management. Before starting the experimental stage, animals were dewormed with ivermectin (0.2 mg kg LW-1).
Measurements. In each period, for five consecutive days, and by means of the difference between weighing of offered food and the rejected one, voluntary DM intake was registered. To determine DM percentage, samples of the different foods were dried in a forced air oven at 60 ºC for 48 h until reaching constant weight. After dried, they were ground (1mm) and preserved for chemical analysis.
Using an esophageal probe and during fermentation dynamics (0, 6, 12 and 20 h), after offering the probiotic plus the concentrate, ruminal liquor was extracted to determine pH, using a portable pH meter (Model pH-207 V). The result was recorded according to food incubation time, treatment, animal, period, day and time.
Samples of offered and rejected foods were subjected to proximal chemical analysis according to AOAC (2005) and fiber fractioning, according to the methodology of Goering and van Soest (1970). All the analyzes were carried out in the Central Laboratory Unit (UCELAB, initials in Spanish), belonging to the Institute of Animal Science. While the nutritional value and microbiological characterization of the probiotic was determined at the National Center for Sugar Cane Research (CNICA, initials in Spanish).
Statistical analysis. All data for absolute variables, like total dry matter intake (tDMI), crude protein intake (CPI), metabolizable energy intake (MEI) and neutral detergent fiber intake (NDFI), followed a normal distribution according to Shapiro-Wilks (1972) test. Analysis of variance (ANOVA) was performed to results, and, in the necessary cases, Duncan (1955) test was applied to determine differences among means. Similarly, linear regression analyzes were performed among the different variables (DMI: CPI, DMI: ME) and statistical adjustment criteria (R2, SE, SEP, CMEM, p) were proposed. All data was processed using INFOSTAT statistical package (Di Rienzo et al. 2012).
Results and Discussion
Table 3 shows that absolute DM intake (kg d-1), as relative to live weight (g kg LW0.75), was affected by the treatment, in which the minimum level (15 g d-1) of addition of the probiotic in the experimental groups reached the highest intake value (1.16 kg d-1), although with statistical similarity with respect to control.
Indicators | Probiotic level, g d-1 | ±SE | ||||
---|---|---|---|---|---|---|
0 | 15 | 25 | 35 | |||
DMI, kg d-1 | 1.14b | 1.16b | 0.92a | 0.93a | 0.05 | 0.0011 |
DMI, g kgLW0.75 | 118.40b | 120.37b | 94.73a | 98.09a | 5.25 | 0.0008 |
DMI, %LW | 5.57b | 5.60b | 4.44a | 4.60a | 0.24 | 0.0007 |
OMI, g kgLW0.75 | 108.50c | 110.05c | 86.88a | 89.91b | 3.85 | <0.0001 |
CPI, g d-1 | 93.84b | 94.61b | 74.32a | 76.72a | 3.89 | 0.0002 |
CPI, g kg LW-1 | 4.58b | 4.62b | 3.60a | 3.72a | 0.19 | 0.0002 |
MEI, MJd-1 | 9.24b | 9.33b | 7.41a | 7.65a | 0.09 | 0.0007 |
NDFI, % LW | 4.27b | 4.38b | 3.41a | 3.54a | 0.20 | 0.0012 |
NDFI: TN, g d-1 | 59.88 | 61.04 | 60.02 | 60.30 | 0.95 | 0.8306 |
CPI Req.CP-1, % | 117.10b | 100.34a | 86.43a | 97.38a | 5.21 | 0.0014 |
MEI Req. ME-1, % | 155.37b | 156.90b | 124.62a | 128.79a | 6.67 | 0.0007 |
abcdifferent letters differ for Duncan P<0.05; ± standard error of the mean
DMI: dry matter intake, OMI: organic matter intake, CPI: crude protein intake, MEI: metabolizable energy intake, NDFI: neutral detergent fiber intake, TN: total nitrogen
Gutiérrez et al. (2020) observed a similar increase in DMI, in correspondence with the participation of the microbial additive in the diet, when they used L. pentosus LB-31 strain, as an additive for feeding Pelibuey lambs. Similarly, Gutiérrez (2012) reported similar results in goats, when different levels of the microbial biological product VITAFERT (yeast, Lactobacillus sp.) were used in a basically fibrous diet, in which the level of 6 mL kg LW-1 also improved voluntary intake. Marrero (2005) also found an increase of total viable bacteria and, specifically, cellulolytic bacteria, which improves ration degradation and, consequently, DMI.
In this way, it can be considered that the stimulatory activity of the probiotic must have been associated, from the beginning, to the presence of active living cells in the ruminal liquor, as well as the contribution of peptides, amino acids and carbon chains from the probiotic, which could be used by ruminal microorganisms as an energy source for growth (Chen et al. 2007).
It is evident that this study could show a great variability of responses of the probiotic with respect to DMI. However, an analysis of statistical inferences among variables shows that DMI was related to protein intake (YDMI, kg=0.20658 (±0.04) + 0.00987 (±0.05) XCPI g d-1, R2=84.80%, ±SEE=0.11, CMEM=4.88, p <0.0001) and energy (YDMI, kg = -0.01553 (±0.02) + 0.12623 (±0.002) XMEI, MJ, R2=97.61%, ±SEE = 0.05, CMEM = 5.62, p <0.0001). According to the results of the equation, the effect of metabolizable energy intake was greater than protein intake.
Regression response indicates the degree of need for both nutrients (protein and energy), to guarantee basal development and enzymatic activity of the ruminal microorganisms and with it, the better use of ration (Malafaia et al. 2003 and Salgado 2006). These effects corroborate the statements of Di Marcos (2006), when they refer that protein and energy metabolism are closely related in ruminants, and the deficiency of one lead to affectations in the other.
Mean dry matter intake per unit of metabolic weight in control (107.91 ± 32.78 g kg LW0.75) and in the other treatments (104.40 ± 30.40 g kg LW0.75) was superior to the maximum potential value reported by García-Trujillo and Cáceres (1984) for adult sheep, fed grasses and forages (71g kg LW 0.75). Likewise, it was higher than that recorded by Ruiz (2004) (80 g kg LW0.75), who included 65% of Saccharina in substitution of corn or wheat.
Similarly, it exceeded the achievements (78 g kgLW0.75) of Reyes-Sánchez et al. (2006), with a basal diet of P. maximum forage and 0.750 kg DM of moringa (Moringa oleifera) forage. This registered intake was also better than that achieved by Gutiérrez et al. (2014) (70.25 g kgLW0.75) during the fattening of Pelibuey sheep, fed an integral mixture of sugar cane: Cenchrus purpureus cv. Cuba CT-169 and poultry manure (5 g kgLW-1). Likewise, it was above that obtained by Rodríguez (2018) (91.19 g kg LW0.75), in studies in which 16 and 33.5% of moringa were included in integral diets for Pelibuey sheep, under conditions similar to those of the current study.
The results derived from the present study, with 15 g of probiotic in the diet, are similar (120 g kg LW0.75) to those obtained by Galina et al. (2008) in lambs fed a probiotic prepared with lactic bacteria (Lactobacillus sp.) and corn silage, as basic ration. Results should have been determined by the functional fibrolytic effect of probiotic bacteria, a product of the improvement of the ruminal environment, in terms of nutrient production (amino acids, peptides and vitamins) and growth factors, which stimulated the promotion of ruminal microorganisms (Chaucheyras-Durand et al. 2008 and Gutiérrez 2012).
Variability of DMI could be attributed to OMI per unit of metabolic weight (g kg PV0.75), in which once again the lowest level (15g) of probiotic in the diet, together with control treatment, presented higher values and differed from the rest (P <0.0001). In this regard, Ketelaars and Tolkamp (1992) stated that OM availability of per unit of metabolic weight is directly related to OM digestibility, a variable that was not determined in this study, but that could influence on intake results.
CPI, in function of live weight (g kg LW-1), did not show differences between the treatment with 15 g of probiotic in diet and control, and was superior to the remaining treatments (P<0.0002). Similarly, despite the differences found in DMI and CPI, treatments with inclusion of probiotic did not practically cover the protein requirements. This effect must have been determined by the compensation between both variables, as a result of the increase of ration digestibility and of conversion efficiency with the inclusion of the probiotic (Ferreyra et al. 2019). On the contrary, MEI was higher than the demand.
In correspondence with the above, Fraga et al. (2014) report that probiotics increase microbial protein synthesis and energy production, factors that favorably influence on ruminal environment. Ushakova et al. (2015) stated that these microbial additives take advantage of available nitrogenous fractions.
La Manna et al. (2011) and Tieri et al. (2010) referred that, from the maintenance stage, protein level in the diet is necessary to guarantee animal development, especially considering that protein catabolism is an essential part of energy metabolism, mainly when diet energy concentration is low. It is also known that, in the amino acid structures, present carbohydrates provide the carbon (Ørskov 1997).
NDF intake, relative to live weight (% LW), as an indicator used to express diet quality and intake (Freitas et al. 2000), was different (p=0.0012), with higher values in the treatments with 15g of probiotic in the diet and control. These figures exceeded the range (0.80-1.20% LW), stated by van Soest (1994) for the ovine species. NDF intake represented 83.19 ± 7.63% (range 69.86-93.43%) of total ingested OM, in which 16.81 ± 7.63% were soluble cellular constituents. This demonstrates the importance of considering the concentration of cell solubles in fibrous diets, as available energy source during digestion process (Barahona and Sánchez 2005).
The high relationship between NDF intake and TN in all treatments, demonstrates that DMI was determined, above all, by forage ingestion and the capacity for fiber degradation by cellulolytic microorganisms (Hillal et al. 2011).
Table 4 shows that ruminal pH values did not differ during the ruminal fermentation time, and reached the mean value of 6.49 ± 0.18, with marked fluctuation between 6 and 20 hours after the initial food ingestion, which must have been associated with variations of intake during the day. This suggests that substrate concentration in the rumen, such as the active growth of ruminal microbiota and fermentability, varied during the day. As observed by Cajarville et al. (2006), the time of access to food has an important influence on values and dynamics of ruminal pH. In this way, it is confirmed that food intake raises ruminal pH value (Khalid et al. 2011 and Rodríguez et al. 2014).
Time, h | Probiotic level, g d-1 | ±SE | ||||
---|---|---|---|---|---|---|
0 | 15 | 25 | 35 | |||
0 | 6.32 | 6.22 | 6.21 | 6.22 | 0.31 | 0.6256 |
6 | 6.41 | 6.45 | 6.50 | 653 | 0.11 | 0.8989 |
12 | 6.62 | 6.49 | 6.44 | 6.59 | 0.14 | 0.8068 |
20 | 6.65 | 6.65 | 6.78 | 6.74 | 0.06 | 0.3872 |
p < 0.05 (Duncan 1955); ± Standard Error
In the present study, the found pH range (6.21-6.78) is the one indicated by Krause and Oestzel (2006) (5.5 -7.0) as values that do not affect growth of cellulolytic and hemicellulolytic microorganisms, their enzymatic activity and with this, the increase of metabolism products (Marrero 2005 and Gutiérrez 2012). Although according to López et al. (2017), when probiotics were used in the diet, the ruminal environment tended to reduce oxygen traces, lactate presence and the use of lactic acid, maintaining a slightly acid pH (6.5). This promotes the growth of cellulolytic microorganisms and improves degradability of structural carbohydrates, as referred above.
Other authors refer that intake of probiotics maintains the stability of ruminal pH, as a result of bacterial increase and the production of volatile fatty acid, as well as the lower permanence of food in the rumen and the increase of use efficiency and food intake (Ortiz-Rubio et al. 2009 and Solaiman and Owen 2010). In addition, the basically fibrous rations, as the one used in this study, were able to increase rumination, chewing, saliva segregation and buffer capacity (carbonates and phosphates).
In control treatment, from the first incubation stage (6h), pH values indicated low availability of simple carbon chains to be used by cellulolytic bacteria, an element that should have influenced on fermentation capacity of structural carbohydrates during the rest of the fermentation stages. In this regard, NRC (2000) points out that, in basic forage diets, as the one used in this treatment, available protein rapidly degrades, while energy (NDF components) is slow. These factors affect digestion, pH values and food permanence in the rumen.
Hillal et al. (2011) stated that ruminal pH variations are determined by the frequency of food provision, ration fermentability and buffer addition during the fermentation time. These effects should have occurred in this study, as well as the possible interaction with bacteria that use lactic acid.