Screening a Lactobacillus plantarum strain for good adaption in alfalfa ensiling and demonstrating its improvement of alfalfa silage quality
Abstract
Aim To screen a lactic acid bacteria (LAB) strain for good adaption in alfalfa ensiling and to evaluate its effects on alfalfa ensiling. Methods and Results Lactobacillus plantarum (LP) strain ZZU203 was selected due to its superior ability to acidify structural carbohydrate metabolite and alfalfa powder. Alfalfa was ensiled with LP FG1 (from a commercial inoculant), LP ZZU203, or a no-additive control (CK) for 60 d. The two silages with LP additives significantly (P < 0·05) increased lactic acid (LA) and acetic acid (AA) concentrations compared to CK silage. The pH, ammonia nitrogen (NH3-N) and cellulose concentrations, and the numbers of bacilli, coliform, aerobic bacteria and Clostridium decreased significantly (P < 0·05). The dry matter, LA, AA and water-soluble carbohydrate concentrations of ZZU203 silage were significantly (P < 0·05) higher, whereas the NH3-N and the neutral detergent fibre concentrations, and the aerobic bacterial and Clostridium counts were significantly (P < 0·05) lower than in FG1 silage. Conclusion ZZU203 obtained by the screening method of this study can improve the quality of alfalfa silage. Significance and Impact of the Study The screening method designed for alfalfa silage conditions can effectively screen out LAB with potential application value in alfalfa silage.
Integrity signals
Registry
Cites
Statistics
Claims the paper makes
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
Lactiplantibacillus plantarum is extensively used as an inoculant for ensiling of lucerne, sorghum, maize, ryegrass, and other forages.
“Lactiplantibacillus plantarum is a species extensively used as inoculant for ensiling of lucerne (Filya et al., 2007; Zhao et al., 2020), sorghum (Thomas et al., 2013), maize (Dogi et al., 2013; Herrmann et al., 2015), ryegrass (Srigopalram et al., 2017; Muthusamy et al., 2020), and other forages (Ávila et al., 2010; Ni et al., 2015).”
From Potential of Lactic Acid Bacteria Isolated From Different Forages as Silage Inoculants for Improving Fermentation Quality and Aerobic Stability (2020) · cites this paper as Zhao et al., 2020
The citation lists haven’t been fetched yet
References 29 · Cited by 48
- Authors
- Zhao, S. S., Wang, Y. P., Yang, F. Y., Wang, Y., & Zhang, H.
- Affiliations
- Zhengzhou University (CN)
- Henan Key Laboratory of Ion Beam Bio‐engineering School of Agricultural Science Zhengzhou University Zhengzhou P. R. China
- Venue
- Journal of Applied Microbiology
- Publisher
- Oxford University Press (OUP)
- Published
- 2020-02-28
- Volume
- 129
- Issue
- 2
- Pages
- 233-242
- ISSN
- 1364-5072 (ISSN-L)
- 1365-2672
- OpenAlex
- W3005299681
- Cited by
- 48
- References
- 29
- Citations by year
- 2026: 1 · 2025: 7 · 2024: 8 · 2023: 7 · 2022: 12 · 2021: 8 · 2020: 5
- FWCI
- 10.00
- Type
- journal article
- Language
- en
- Open access
- closed
- Licence
- Locations
- Journal of Applied Microbiology (publishedVersion)
- PubMed (publishedVersion)
- Funders
- National Natural Science Foundation of China (No. 31772672)
- Topics
- Life Sciences › Agricultural and Biological Sciences › Agronomy and Crop Science › Ruminant Nutrition and Digestive Physiology
- Life Sciences › Agricultural and Biological Sciences › Food Science › Probiotics and Fermented Foods
- Life Sciences › Agricultural and Biological Sciences › Animal Science and Zoology › Animal Nutrition and Physiology
- Keywords
- Lactobacillus plantarum, alfalfa silage, silage inoculants, lactic acid bacteria, silage quality, lactic acid, acetic acid, ammonia nitrogen, Clostridium, aerobic bacteria, strain screening, silage acidification
- MeSH terms
- Adaptation, Physiological, Medicago sativa, Ammonia, Bacteria, Dietary Fiber, Fermentation, Hydrogen-Ion Concentration, Silage, Lactobacillus plantarum, Lactiplantibacillus plantarum
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
