The objective of this study is to isolate and characterize lactic acid bacteria and their effect as a microbial inoculants in silage digestibility of Lolium perenne –Trifolium pratense (Rye grass - Red clover) (RG-RC), Avena sativa – Vicia sativa (Oat-Vetch) (O-V) and Corn Stover Zea mays (Corn) (C). The lactic acid bacteria (LAB) isolated from three mixtures were identified at 40 day of evolution of micro silages. Morphological, physiological, biochemical and molecular techniques were used to characterize the isolates lactic acid bacteria. The following species were identified from the mixture namely Lactobacillus buchneri, Lactobacillus plantarum, Lactobacillus brevis and Pediococcus acidilactici. 54 micro silages with each feed material were produced, 27 micro silos were inoculated with bacteria’s and the rest was used as a control. The nutritional value of protein, ether extract (EE), ash, energy, neutral detergent fiber (NDF), acid detergent fiber (ADF) at 20, 30 and 40 days of ensilage was compared. The percentage of each in vitro digestibility of treatments performed on day 40 was obtained that corresponded best A-V and RG-TR inoculated with bacteria as they were 35% and 41% more digestible than the control treatments appropriate, concluding that the inoculation of lactic acid bacteria facilitated improved digestibility of silage obtaining good nutritional quality, with optimal values. These results will enable future research on the relationship between LAB species and silage fermentation quality. Use of lactic acid bacteria is recommended as an additive to improve the nutritional quality of food animals as alternative in times of scarcity of fodder or as a supplement to improve the nutritional status of livestock herd.
Key words: Microsilage, Lactobacillus, Pediococcus, Nutritional parameters, In vitro digestibility.
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Neural regeneration research. 2022; 17(4): 911-919
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Talanta. 2022; 236(): 122682
Comprehensive Laboratory Data Analysis to Predict the Clinical Severity of Coronavirus Disease 2019 in 1,952 Patients in Daegu, Korea.
Yoo EH, Chang SH, Song DY, Lee CH, Cheong GY, Park S, Lee JH, Lee S, Kwak SG, Jeon CH, Song KE
Annals of laboratory medicine. 2022; 42(1): 24-35
An In Vitro Model System to Test Mechano-Microbiological Interactions Between Bacteria and Host Cells.
Santos LC, Munteanu EL, Biais N
Methods in molecular biology (Clifton, N.J.). 2022; 2364(): 217-235
Determination of Bioenergetic Parameters in Mycobacterium ulcerans.
Thomas SS, Pethe K
Methods in molecular biology (Clifton, N.J.). 2022; 2387(): 219-230