Structural and quantitative changes of saponins in fresh alfalfa compared to alfalfa silage

Szumacher-Strabel, M.; Stochmal, Anna; Cieślak, Adam; Kozłowska, Martyna; Kuznicki, Dawid; Kowalczyk, Mariusz; Oleszek, Wiesław

doi:10.1002/jsfa.9419

Cited by 24 publications

(27 citation statements)

References 26 publications

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“…Betavulgaroside IV is a representative triterpene secoglycoside that constitutes a small family of plant saponins (Zhu et al, 2008). It was reported that alfalfa saponins are pentacyclic triterpenes, including medicagenic acid, soyasapogenol, and other glycosides of several aglycones (Szumacher-Strabel et al, 2019). The total saponin concentration increases when fresh alfalfa is processed into silage (Szumacher-Strabel et al, 2019).…”

Section: Discussionmentioning

confidence: 99%

“…It was reported that alfalfa saponins are pentacyclic triterpenes, including medicagenic acid, soyasapogenol, and other glycosides of several aglycones (Szumacher-Strabel et al, 2019). The total saponin concentration increases when fresh alfalfa is processed into silage (Szumacher-Strabel et al, 2019). An apparent negative linear relationship was observed between protein and saponin content in alfalfa silage (Szumacher-Strabel et al, 2019).…”

Section: Discussionmentioning

confidence: 99%

“…The total saponin concentration increases when fresh alfalfa is processed into silage (Szumacher-Strabel et al, 2019). An apparent negative linear relationship was observed between protein and saponin content in alfalfa silage (Szumacher-Strabel et al, 2019). Thus, the decreased level of triterpene aglycones in FRU and PEC compared to CON also indicated the improved fermentation quality of alfalfa silage after adding fructose or FIGURE 5 | Correlation matrix between the fermentation and nutritional characteristics and the top 20 enriched bacteria at the genus level from the comparisons between the CON group and FRU group (A) and between the CON group and PEC group (B).…”

Section: Discussionmentioning

confidence: 99%

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Functional Analysis of Sugars in Modulating Bacterial Communities and Metabolomics Profiles of Medicago sativa Silage

Wang

Gao

et al. 2020

Front. Microbiol.

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This study explored the effects of four sugar source treatments, including no sugar (CON), fructose (FRU), pectin (PEC), and starch (STA), on the microbiota and metabolome of alfalfa (Medicago sativa) silage. The bacterial community was determined via 16S rRNA gene sequencing. The metabolome was analyzed using ultra high-performance liquid chromatography tandem time-of-flight mass spectrometry (UHPLC/TOF-MS). After 60 days of fermentation, the pH values in FRU and PEC were lower than those in STA and CON. FRU had a greater lactic acid concentration compared to STA and CON. Weissella (47.44%) and Lactobacillus (42.13%) were the dominant species in all four groups. The abundance of Pediococcus was lower, and the abundance of Leuconostoc, Pantoea, and Microbacterium was higher, in FRU compared to CON. The abundance of norank_f__Bacteroidales_S24-7_group was higher, and the abundance of Turicibacter was lower, in both FRU and PEC than in CON. Leuconostoc was negatively correlated with the pH value, and Pediococcus was positively correlated with the pH value. No microbiomes were detected as discriminative features between STA and CON. The addition of FRU and PEC presented more peptides, such as Leu-Val-Thr, Leu-Phe, Ile-Pro-Ile, Val-Trp, and Ile-Leu-Leu but a lower abundance of metabolites for triterpene glycosides including sanchinoside B1, medicagenic acid, betavulgaroside IV, and prosapogenin compared to CON. The addition of PEC presented more phenyllactic acid compared to CON. Our study demonstrated that the addition of pectin and fructose improved the quality of alfalfa silage mainly by promoting Leuconostoc, Pantoea, and Microbacterium, and inhibiting Pediococcus in FRU, and promoting norank_f__Bacteroidales_S24-7_group and inhibiting Turicibacter in both FRU and PEC; this was due to altered metabolic profiles resulting from antifungal activity and decreased triterpene glycoside accumulation. This study improves our understanding of ensiling mechanisms related to the contributions of sugar.

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Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

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Functional Analysis of Sugars in Modulating Bacterial Communities and Metabolomics Profiles of Medicago sativa Silage

Wang

Gao

et al. 2020

Front. Microbiol.

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“…Alfalfa (Medicago sativa L.) is one of the most widely cultivated and used forages in the world [1]- [3]. It plays an important role in dairy farms in northwest China.…”

Section: Introductionmentioning

confidence: 99%

Precision Regulation Model of Water and Fertilizer for Alfalfa Based on Agriculture Cyber-Physical System

Liu

Zhang

et al. 2020

IEEE Access

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The regulation of water and fertilizer for alfalfa growth is not precise enough because the regulation strategy cannot track alfalfa growth dynamically. In this paper, we propose a precision regulation model of water and fertilizer for alfalfa based on agriculture cyber-physical system (ACPS) for irrigation and fertilizer management in alfalfa (PRMWFA-ACPS). The proposed PRMWFA-ACPS is a comprehensive model that includes the biophysical submodel, the computation submodel of water and fertilizer regulation, and the interaction of the submodels for both. The proposed model interacts with the alfalfa growth and its physical environment along with the irrigation strategy to improve the precise regulation of water and fertilizer. To verify the performance of the proposed model, we develop a simulation platform for PRMWFA-ACPS based on Ptolemy. Through physical experiments performed in the field at the Ningxia irrigation area of the Yellow River over three years (2016-2018), we verified and analyzed PRMWFA-ACPS by comparing the simulated and measured values, such as the growth period, leaf area index, soil water content and alfalfa yield. The experimental results show that the mean relative error of the growth period simulated by the model is between 1.9% and 6.8%, the mean relative error of the leaf area index simulated by the model is between 2.1% and 9.8%, the mean relative error of the soil water content simulated by the model is between 4.3% and 12.8%, and the mean relative error of the yield simulated by the model is between 1.2% and 14.3%. These findings indicate that PRMWFA-ACPS has promising applicability to the Ningxia irrigation area of the Yellow River and improves the accurate regulation of water and fertilizer application to alfalfa in a complex physical environment. INDEX TERMS Alfalfa, agriculture cyber-physical system, precise regulation, growth model, Ptolemy.

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“…Lactic acid bacteria with high growth rates, fibrolytic activities, and ferulic acid activities were suggested to be efficient in improving the quality of alfalfa silage [4]. Currently, changes in the content of functional composition during alfalfa ensiling have attracted much attention [6,7].…”

Section: Introductionmentioning

confidence: 99%

Effect of 3-Phenyllactic Acid and 3-Phenyllactic Acid-Producing Lactic Acid Bacteria on the Characteristics of Alfalfa Silage

Ying

et al. 2019

Agriculture

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In this study, an experiment was performed to evaluate the effect of lactic acid bacteria and 3-phenyllactic acid (PLA) on the fermentation quality and chemical composition of alfalfa silage. Several PLA-tolerant strains were screened from silages and identified. The selected strains (1 × 106 colony forming units/g fresh alfalfa) and PLA (1.0, 2.0, or 3.0 g/kg) were applied to alfalfa before ensiling. After 45 days of storage, the silages were unsealed and subjected to component analysis. Biochemical methods and 16S rDNA gene sequencing were used for the identification of the two strains as Lactobacillus plantarum. The characteristics of chemical and fermentation compounds indicated that PLA and the two strains efficiently improved the quality of the alfalfa silage. It can be concluded that the use of the strains and PLA can significantly improve the quality of silage.

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Structural and quantitative changes of saponins in fresh alfalfa compared to alfalfa silage

Cited by 24 publications

References 26 publications

Functional Analysis of Sugars in Modulating Bacterial Communities and Metabolomics Profiles of Medicago sativa Silage

Functional Analysis of Sugars in Modulating Bacterial Communities and Metabolomics Profiles of Medicago sativa Silage

Precision Regulation Model of Water and Fertilizer for Alfalfa Based on Agriculture Cyber-Physical System

Effect of 3-Phenyllactic Acid and 3-Phenyllactic Acid-Producing Lactic Acid Bacteria on the Characteristics of Alfalfa Silage

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