Next Article in Journal
Influence of the Ratio of Sheep and Cow Milk on the Composition and Yield Efficiency of Lećevački Cheese
Next Article in Special Issue
Effects of Paper Mulberry Silage on the Growth Performance, Rumen Microbiota and Muscle Fatty Acid Composition in Hu Lambs
Previous Article in Journal
Aquafeed Production from Fermented Fish Waste and Lemon Peel
Previous Article in Special Issue
Succession of Microbial Communities of Corn Silage Inoculated with Heterofermentative Lactic Acid Bacteria from Ensiling to Aerobic Exposure
Order Article Reprints
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:

Silage Fermentation: A Potential Microbial Approach for the Forage Utilization of Cyperus esculentus L. By-Product

by 1,2,†, 1,†, 1, 1, 1,2, 1 and 1,2,*
State Key Laboratory of Microbial Resources, Institute of Microbiology, Chinese Academy of Sciences, Beijing 100101, China
School of Life Science, University of Chinese Academy of Sciences, Beijing 100039, China
Author to whom correspondence should be addressed.
Authors contributed equally to this work.
Fermentation 2021, 7(4), 273;
Received: 9 October 2021 / Revised: 18 November 2021 / Accepted: 21 November 2021 / Published: 23 November 2021
(This article belongs to the Special Issue Silage Fermentation)


Cyperus esculentus L. leaves (CLL) are agricultural by-products produced from Cyperus esculentus L. harvesting, and can be used as livestock feed despite their low economic value for human consumption. This study aims to develop a favorable approach to processing Cyperus esculentus L. by-product as coarse fodder. The chopped CLL was pretreated by (1) mixing with canola straw at a 4:1 ratio, or (2) wilting it for 8 h, then it ensiling with or without compounded lactic acid bacteria (LAB) additives for 60 days. Our results demonstrated that compounded LAB additives: improved CLL silage fermentation quality by increasing acetic acid and lactic acid contents and decreasing ethanol and ammonia-N contents; preserved nutrients by raising the level of crude protein and water soluble carbohydrates; modified the bacterial community by increasing the relative abundance of Lactobacillus while decreasing the relative abundance of undesirable Enterococcus; and also might improve animal health by increasing the relative concentrations of antioxidant substances (such as 7-galloylcatechin) and antibacterial compounds (such as ferulic acid). This study provides strong evidence that Cyperus esculentus L. by-product can be a potential livestock feed after being ensiled with compounded LAB additives.

1. Introduction

The perennial herb Cyperus esculentus L. comes from the family Cyperaceae, and is also known as tiger nuts [1,2,3]. After it was first introduced to China in 1952, it was widely planted due to its resistance to cold temperatures, drought, waterlogging, barrenness, salt, and alkaline conditions; the productivity of Cyperus esculentus L. tubers can reach 15–18 t/hm2 [4]. Cyperus esculentus L. is comprised of above-ground leaves, underground tubers and roots [5]. The nutritional value of these plant parts means that Cyperus esculentus L. can serve as a beneficial crop for both humans and animals [6]. Tubers with rich flavor and fats have historically been melted into “Horchata de Chufa,” a kind of drink with a nutty taste, and squeezed oil, leaving by-products such as leaves, which are typically burned or discarded [1,7].
However, Cyperus esculentus L. leaves (CLL) is a source of polysaccharides, fiber, and antioxidant compounds (such as vitamin E and polyphenols). CLL is comprised of 9.8% crude protein (CP) and 19.3% crude fiber, meaning its leaves can also be used as functional silage materials [4]. The CP content of CLL is similar to that of oats (Avena sativa), which are known for their high protein content and digestible fraction [8,9]. This suggests that CLL could be used as livestock feed, especially in the absence of high-quality forage. If mixed with forage and fed to cows, it can increase milk yield while decreasing cost [4]. Jing et al. have reported the neuroprotective capacity of Cyperus esculentus L. orientin obtained from CLL [5]. The antioxidant capability of silage can increase the accumulation of desirable fatty acids in the milk and meat of livestock, and improve the antioxidant capabilities of meat, as well as aid in fighting off rumen bloat [10]. Despite the potential benefits of CLL, it is still underutilized and there is little information about how it can be used as a coarse fodder.
Ensiling is typically the most effective and economical method to preserve fresh forage grass and it can improve palatability and prolong the maximum storage duration via anaerobic fermentation [11,12]. For silage fermentation, the low dry matter (DM) content (19.9%), the low water-soluble carbohydrates (WSC) content (2.52% DM), and the low level of epiphytic lactic acid bacteria (LAB, <105 colony-forming units (CFU)/g fresh matter (FM)) of fresh CLL make it difficult to ensile [12]. The DM content can be adjusted by adding absorbents (such as crops straw) and wilting. The common additives used to obtain high-quality silage are molasses and LAB. Molasses can be used as a soluble carbohydrate for LAB metabolism, and is subsequently converted into lactic acid to decrease silage pH value during the ensiling process [13,14]. LAB is divided into homofermentative and heterofermentative strains. Homofermentative LAB strains, such as Lactobacillus plantarum, quickly produce lactic acid, which helps to preserve nutrition by lowering the silage pH [15]; heterofermentative LAB strains, such as Lactobacillus buchneri, could improve aerobic stability by suppressing the growth of yeast and mold through producing acetic acid. Thus, compounded LAB additives (mainly consisting of L.plantarum CGMCC No.13318, L. buchneri CGMCC No.16534 and molasses) were applied to ensile the agricultural by-product CLL under proper DM content (36–37%).
This study aims to provide a suitable approach to forage utilization of Cyperus esculentus L. by-product. The effects of compounded LAB additives on CLL silage, pretreated with canola straw or wilted, were evaluated. In particular, the bacteria community and metabolomics were studied, which could provide vital information for further regulation of fermentation and the exploitation of bioactive ingredients.

2. Materials and Methods

2.1. CLL Harvest and Silage Making

The CLL was harvested from an experimental field of the Yellow River Delta Modern Agricultural Technology Innovation Center (37°67′ N; 118°90′ E) on 19 September 2020. Before ensiling, the harvested CLL were divided into two groups: the Sample 1 (S1) group was mixed with canola straw at a 4:1 ratio, while the Sample 2 (S2) group wilted for 8 h. Following these pretreatments, the DM contents of both groups adjusted to 36–37%.
The CLL were chopped into theoretically 2 cm-long pieces with a crop chopper. Then, they were randomly ensiled with the compound LAB additives, which were comprised of L. plantarum CGMCC No.13318, L. buchneri CGMCC No.16534, and molasses. The inoculants were added at a rate of 106 CFU/g FM, and the molasses were added at a level of 0.5% (w/w) FM in treatments (LM in the S1 group and WLM in the S2 group). An equal amount of distilled water was sprayed for the controls without additives (CK in the S1 group and WCK in the S2 group). They were then homogenously mixed with additives or distilled water, after which 300 g of fresh forage was packed into vacuum-sealing polyethylene plastic bags. A total of 24 silos (2 groups × 2 treatments × 6 replicates) were maintained at room temperature (21–30 °C). Samples were obtained after 60 days of ensiling.

2.2. Analysis of Culture-Based Microbial

To calculate the microbial counts, samples of 10 g CLL silage were mixed with 90 mL of a sterile saline solution, after which they were diluted from 10−1 to 10−7. One hundred μL were spread on the various agar plates. The amount of LAB was calculated on de Man, Rogosa, Sharpe agar (MRS), which was enumerated at 37 °C for 48 h under anaerobic conditions. The yeast and molds were counted on a potato dextrose agar (PDA) and were incubated at 30 °C for 24 h under aerobic conditions. Aerobes were calculated on Nutrient Agar (NA) at 37 °C for 24 h. All culture media were purchased from Beijing Solarbio Science & Technology Co., Ltd. Yeast and molds were distinguished from bacteria according to the appearance and cell morphology of the colony.

2.3. Fermentation Quality Analysis

Samples of 10 g CLL silage were blended with 90 mL sterilized water, after which they were incubated overnight at 4 °C. They were then filtered through a 0.22 μm filter [13]. The resulting extract was used to measure pH value (pH 213; HANNA; Italy), the contents of ammonia-N, and organic acid. Levels of ammonia-N were analyzed using the ninhydrin colorimetric and phenol-hypochlorite procedures outlined by Broderick and Kang [16]. The contents of organic acid were assessed by High-Performance Liquid Chromatography (HPLC, 1200, Agilent, California, America) equipped with a 210 nm UV detector and an ICSep COREGEL-87H column (temperature of column: 55 °C). The mobile phase was 0.004 mol/L H2SO4 with a flow rate of 0.6 mL/min and an injection volume of 10 µL. The buffering capacity (BC) was measured according to the methods used by Playne and McDonald [17].

2.4. Chemical Composition Analysis

Approximately 150 g samples (pre-ensiled material and silage sample) were collected. They were then placed in an oven at 65 °C for 48 h, and the temperature was increased to 105 °C until they reached a constant weight. The DM content was then calculated as a former record [18]. The dried sample was ground to a particle diameter of 1.0 mm to analyze the chemical composition. The WSC was determined according to the methods used by Murphy [19] and the CP was examined according to the procedures established by the AOAC [20]. The content of the neutral detergent fiber (NDF), the acid detergent fiber (ADF), and the acid detergent lignin (ADL) were all measured according to the procedures used by VanSoest et al. [21].

2.5. Bacterial Diversity Sequenced by High-Throughput Sequencing

Samples of 10 g CLL silage were randomly selected and vigorously blended with 40 mL sterilized water at 4 °C and shaken at 120 rpm for 30 min. The resulting mix was then filtered through a filter (0.22 mm, Cat. B-CYD400G1), after which it was obtained by centrifugation at 4 °C at 5000 rpm for 2 min, which removed the impurities and transported the supernatant to obtain microbial pellets. It was then centrifuged at 4 °C and 12,000 rpm for 10 min. The total DNA was extracted from the samples using a MolPure Soil DNA Kit (Yeasen, Beijing, China), according to the manufacturer’s instructions.
Universal primers 338F (ACTCCTACGGGAGGCAGCA) and 806R (GGACTACHVGGGTWTCTAAT) were used to amplify the V3–V4 variable regions of the bacterial 16S rDNA. The PCR reactions were conducted according to the methods used by Su et al. [14]. To minimize PCR deviation, a triple PCR reaction was performed for each sample. Three PCR products were mixed and sequenced using paired-end reads (2 × 300 bp) with an Illumina MiSeq platform (Shanghai Majorbio Bio-pharm Technology Co. Ltd.) according to standard protocols. The sequenced reads were processed according to the methods used by Ni et al. [22]. The raw tags were quality-filtered and merged using Trimmomatic (Version 3.29) and FLASH (Version 1.2.11). ACE, Simpson, Chao, Shannon, and Good’s coverage were all calculated to assess the alpha diversity.

2.6. Metabolomics Analysis Using LC-MS

A non-targeted metabolome method was used to evaluate the metabolomics of CLL ensiling with the LC-MS ABSciex Triple TOF 5600TM (ABSCIEX, USA) in Majorbio Bio-pharm Technology (Shanghai, China) according to the published procedures of a previous study [23]. A partial extract (75 μL) from each sample was used for the quality control (QC) samples. The raw data were imported to ProgenesisQI (WatersCorporation, Milford, CT, USA) to normalize the retention times, MZ, observations and peak intensities. According to the characteristic peaks and the MS mass spectra information, the metabolites were matched with the metabolic databases such as: (accessed on 23 March 2021) (accessed on 13 April 2021) and self-built databases on the on the Majorbio I-Sanger platform (, accessed on 15 April 2021). The MS mass error was set to less than 10 ppm. Relative quantifications of metabolites were carried out as a ratio of their peak areas to the peal area of internal standard substance (0.02 mg/mL 2-Chloro-L-Phenylalanine, CAS. 103616-89-3, Adamas-beta). The data were then filtered the missing value, missed value recoding, normalized and logarithmic transformed. Principal component analysis (PCA) and orthogonal partial least-squares-discriminant analysis (OPLS-DA) were carried out to show the metabolism changes among the S1 and S2 groups after mean centering and unit variance scaling. The differential metabolites were defined at the fold change ≥1 or ≤0.5 as well as variable importance in the projection (VIP) of the OPLS-DA model greater than 1.

2.7. Calculation of Relative Feed Value and Fermentation Coefficient

Relative feed value (RFV) is a forage evaluation index typically used for assessing intake and energy value and was published by the American Forage and Grassland Council [24]. RFV is calculated by ADF and NDF according to the following formula [24]:
D D M   % D M = 88.90 0.779 × A D F   % D M
D M I   % B o d y   w e i g h t = 120 / N D F   % D M
R F V = D D M × D M I / 1.29
DDM: digestible dry matter; DMI: dry matter intake.
To evaluate the ensilability of CLL, a fermentation coefficient (FC) was calculated from DM% content, WSC content, and BC of CLL according to the following formula [25]:
F C = D M %   + 8 × W S C   % D M / B C

2.8. Statistical Analysis

Unless otherwise stated, the statistical analyses were conducted using the SAS (version 9.0, 2002; SAS Institute, Cary, NC, USA). The independent sample t-tests of variance were applied to compare the data in S1 and S2 groups, respectively. The significance was declared if p < 0.05. The data presented are the means ± standard deviation (SD). Microbial counts were assessed via log 10 and analyzed based on their FM. Correlations between differentially presented metabolites and main bacteria species in the S1 and S2 groups were plotted as Spearman correlations, respectively. p values < 0.05 were considered statistically significant. *, p <  0.05; **, p <  0.01; ***, p <  0.001.

3. Results

3.1. Characteristics of Fresh CLL

Table 1 displays the chemical composition and the number of microorganisms in the raw materials prior to ensiling. In harvested CLL, the DM content was approximately 20%; the CP content was 11.56% DM; the NDF, ADF, and ADL concentrations were 56.08% DM, 28.92% DM and 9.54% DM, respectively; and the WSC content was approximately 2.52% DM. After it was mixed with canola straw at a 4:1 ratio in the S1 group, the DM content was 37.20%; the CP content was 5.17% DM; the NDF, ADF, and ADL concentrations were 61.40% DM, 40.55% DM, and 4.54% DM, respectively; and the WSC contents was 6.46% DM. After wilting for 8 h in the S2 group, the DM content was 36.40%; the CP content was 11.96% DM and the NDF, ADF, and ADL concentrations were 55.10% DM, 29.40% DM, and 8.40% DM, respectively; and the WSC content was 3.20% DM. Otherwise, the amount of epiphytic LAB, yeast, and aerobes in CLL was close to that of canola straws (which were obtained via plate culturing). The amount of LAB was lower than 105 CFU/g FM, while the number of yeast and aerobes was approximately 106 CFU/g FM.

3.2. Effect of Additives on Silage Quality and Microbial Population of CLL Silages

As listed in Table 2, the additives significantly affected fermentation quality, chemical composition, and microbial population in both the S1 and S2 groups after 60 days of ensiling. In the S1 group, the pH value was significantly lower in the LM than in the CK (4.09 vs. 5.66, p < 0.01). A similar phenomenon was observed in the S2 group (3.91 vs. 5.84 of WLM vs. WCK, p < 0.01). Acetic acid and lactic acid were the predominant fermentation end products of CLL silage after 60 days of ensiling, followed by ethanol. The contents of lactic acid were 97.78 g/kg DM and 146.33 g/kg DM in the LM and WLM, respectively, and none was detected in CK and WCK. Neither butyric acid nor propanoic acid were detected. Additionally, the contents of ammonia-N significantly decreased by 42.28% and 71.2% in the S1 and S2 groups, respectively (p < 0.01). In the S1 group, LM had a higher FC value (36.83 vs. 36.01); in the S2 group, WLM also had a higher FC value (37.61 vs. 31.94). This indicated that the additives had promoted the fermentation quality of CLL silage.
The additives significantly improved the nutritive quality of CLL silage. The DM content after ensiling significantly increased in the WLM than that in the WCK (32.74% vs. 37.20%, p < 0.01), a similar trend was also found in the LM than that in the CK (36.88% vs. 37.89%, p = 0.31). Compared to the WCK, the NDF, ADF and ADL contents were obviously decreased in the WLM. Thus, the WLM had higher RFV than the WCK (p < 0.01). The similar results were found in S1 group although there is no significance. The CP contents increased by 16.93% and 9.70% in the S1 group and S2 group, respectively (p < 0.01), the WSC content also increased by 82.05% and 60.32% in the S1 and S2 groups, respectively (p < 0.01).
Table 2 also displays the culturable microorganism detected in the S1 and S2 groups. The LAB levels both significantly increased to over 105 CFU/g FM and the aerobe numbers decreased to below 103 CFU/g FM (p < 0.01) due to the additives. Mold and yeast were not detected in any samples.

3.3. Effects of the Additives on the Microbial Communities of CLL Silages

High-throughput sequencing of 16S rDNA gene amplicons demonstrates how bacterial communities are affected after systematic ensiling. The alpha diversity of all samples is exhibited in Table 3. The coverage values of all samples exceeded 0.99, suggesting that the sequencing depth was adequate to detect most bacteria. Compared with the controls in both groups, the treatment groups had both lower Chao and Shannon indexes, reflecting decreases in bacterial diversity due to dominant microorganisms that could have been replaced through cluster analysis. The variance in the microbial population in the S1 and S2 groups can be illustrated by principal component analysis (PCA). CK and LM can both be separated, while a similar discrepancy was also found in the S2 group (Figure S1). These results indicate that the additives significantly affected the bacterial community of CLL silage.
Figure 1 displays the bacterial communities at the genus and species level of the S1 and S2 groups after 60 days of ensiling. In the control groups (CK and WCK), Enterobacter was the most abundant genus, comprising approximately 77.51% and 50.16% of the entire communities, respectively. Kosakonia and Enterococcus were also present in the materials before ensiling. However, the relative abundance of Enterobacter significantly decreased or even disappeared in treatments (LM and WLM). Lactobacillus is a desirable genus that became the most prevalent genus; its abundance reached nearly 90% of the total population. Additionally, several spore-forming bacteria, such as Clostridium and Bacillus, were also detected in raw materials. These are always associated with aerobic deterioration. These results implied that the additives have obviously modified the fermented microbiota of CLL silage.

3.4. Metabolomics Profiles of CLL Silages Ensiling for 60 Days

Total 891 substances were detected by analyzing the retention time and mass:charge ratio of all ions found in the chromatograms of the CLL silage samples. Of these, 361 metabolites in the S1 group and 406 substances in the S2 group and their relative concentrations were identified and annotated based on the Human Metabolome Database (HMDB). PCA of positive and negative (Figure S2) demonstrated that there were clear differences between CK, LM, and QC (Quality Control) in the S1 group. Similarly, WCK, WLM, and QC were also clearly separated in the S2 group, indicating that there are differences between samples within treatments.
Table 4 displays the relative concentration of certain metabolites with biological functions in the S1 and S2 groups. In the S1 group, LM has more cinnamic acids and derivatives (such as sinapic acid, caffeic acid, and 2-hydroxycinnamic acid), flavonoids (such as the quercetin, theaflavic acid, and isorhamnetin), ferulic acid, and zeranol compared to CK. All of these have antioxidant properties and antibacterial activities. Toxic compounds such as hypoxanthine, 7a-hydroxy-5b-cholanic acid, and 7-epi-Jasmonic acid decreased in the LM compared to the CK. In the S2 group, higher contents of carboxylic acids and derivatives (such as valyl-isoleucine, threoninyl-isoleucine, glycyl-isoleucine, asparaginyl-isoleucine), flavonoids (such as kaempferol 3-(2″-rhamnosylrutinoside) and 7-galloylcatechin), organooxygen compounds (such as 1,3-dicaffeoylquinic acid, chlorogenic acid, and 3-O-feruloylquinic acid), ferulic acid, and D-(+)-3-phenyllactic acid were seen in WLM than in WCK, while the contents of compounds with a foul smell (such as grandisine III and piperidine) decreased.
In summary, the contents of metabolites with beneficial biofunctional activities (such as flavonoids, cinnamic acids and derivatives, steroids and steroid derivatives, and ferulic acid) increased in LM and WLM in the S1 and S2 groups, compared to the control groups (CK and WCK). The type of flavonoids in the S1 group increased more than in the S2 group, while more dipeptide and organooxygen compounds were observed in the S2 group.

3.5. Correlations between Main Microorganisms and Metabolites in CLL Silage

A Spearman correlation heat map was generated at the species level to display the association between differential metabolites and dominant bacteria in S1 and S2 groups respectively (Figure 2 and Figure 3). Metabolites positively correlated with LAB were negatively correlated with undesirable bacteria during the ensiling process. In the S1 group, ferulic acid, m-Coumaric acid, and p-Coumaric acid were positively correlated with L. plantarum and L. buchneri, and were negatively correlated with the unclassified Enterobacter, Pediococcus pentosaceus, unclassified Pantoea, Streptomyces albidoflavus, and unclassified Curtobacterium. In the S2 group, 7-galloylcatechin, chlorogenic acid, and 3-O-p-Coumaroylquinic acid were positively correlated with L. plantarum and L. buchneri, and were negatively correlated with the unclassified Lactobacillales, Enterococcus casseliflavus, Kosakonia cowanii and unclassified Enterobacter, Klebsiella aerogenes, and Agrobacterium larrymoorei.
In summary, metabolites with biological functions tended to positively correlated with LAB and negatively correlated with undesirable bacteria.

4. Discussion

Agricultural by-products are important sources of feed for livestock, especially when livestock cannot acces high-quality roughage. Ensiling is a method typically used to prolong the storage time of forage by using LAB fermentation under anaerobic conditions [13]. As such, a better understanding of the metabolomics and bacterial community during the fermentation process could provide powerful evidence for making high-quality silages [26]. Ensiling is a complex process that is affected by several factors, such as the DM content of materials, WSC content and epiphytic microbiota of materials. Low moisture content helps condense WSC content, promoting lactic acid fermentation and suppressing the production of ammonia-N [27]. In addition, abundant WSC content affects the quality of fermentation, while WSC contents exceeding 5% DM typically produce silage of sufficient quality [13]. Molasses is considered the most effective and economically fermentable substrate [13]. Concerning epiphytic microbiota, both Cai et al. [28] and Oliveira et al. [29] stressed that the forage would only be well-preserved if the level of LAB exceeded 105 CFU/g FM. During the ensiling process, LAB can produce lactic acid, hydrogen peroxide, and antimicrobial substances to inhibit undesirable microorganisms to reduce nutritional loss [14]. Otherwise, DM recovery decreases while ammonia-N concentration increases [28,29,30]. While aerobes are undesirable, they typically appear when the silo opens and are usually associated with high DM loss and decreased aerobic stability [30]. The high moisture content, low WSC content, low levels of epiphytic LAB, and presence of harmful microorganisms indicates that the ensiling process of fresh CLL must be controlled only if mixed with absorbent or wilted to increase DM content and inoculated with LAB and extra WSC.
Fermentation quality significantly improved after 60 days of ensiling with compound LAB additives. The pH values of additives treated CLL silage were below 4.2, which could be attributed to higher organic acid content produced by LAB. Increased levels of LAB resulted in significant increases in lactic acid and acetic acid contents. Lactic acid is the main product of LAB and has a pKa 3.86, which is the main organic acid affecting pH value and promotes the reductions in pH value observed in ensiled material [13]. However, acetic acid was the dominant fermentation product in both the S1 and S2 groups and likely resulted from the abundant heterofermentative pattern favored by L. buchneri, which aligns with the findings of Kung et al. [31], Zhang et al. [32] and Wang et al. [18] reported that acetic acid has significant antifungal properties, which are crucial for improving the aerobic stability of silage. Mold and yeast were not detected in all samples, which could be due to low pH values. As Li et al. [33] reported, anaerobic conditions and organic acid can inhibit yeast growth, especially after long storage periods. Additionally, ammonia-N contents decreased in both LM and WLM, which typically occurs during the ensiling process and is a result of the fermentation of Clostridium or the activity of plant protease [34]. In this study, Clostridium was found in CK/WCK instead of LM/WLM; as such, decreased ammonia-N could be attributed to the inhibited growth of Clostridium. Herrmann et al. [35] demonstrates that a raw material is suited for ensiling if it contains sufficient WSC as fermentable substrate, a low BC to allow rapid for acidification, and sufficient DM content. Therefore, the ensilability of silage raw material could be assessed by FC [35]. Weissbach et al. [25] proposed that if the FC value reaches 35, it means that high-quality silage is produced. In this study, the FC value in LM and WLM both exceed 35 and were higher than WCK and CK. The FC value in WLM was higher than in LM, suggesting that wilting may be a better way to promote fermentation than absorbents (canola straw).
The nutritional quality also improved in compound LAB additive-treated CLL silage. DM is a vital measure of the organic matter accumulation of silage, and increasing DM content maximizes the efficiency of the ensiling process [36]. The DM contents increased in both the S1 and S2 groups. The NDF, ADF, and ADL contents represent the digestibility of cellulose and hemicellulose by ruminant animals, which affects digestibility and feed intake [37]. Compared with CK and WCK, relatively low contents of NDF, ADF, and ADL were observed in LM and WLM. This indicates that LM and WLM had low lignocellulosic structures and became highly digestible. The contents of NDF and ADF were not significantly affected in the S1 group, which could be attributed to the addition of canola straw in the S1 group, making the fermentation effect inferior to that in the S2 group. RFV is widely acknowledged to predict forage quality [38]. The RFV of WCK and WLM exceeded that of CK and WCK, which could account for the lower content of ADF, NDF, and the higher content of WSC, which was used to calculate and parameterize the RFV. Alfalfa is a high-quality forage plant with a high protein content; it is cultivated and used for animal feed all over the world [14]. Ertekin et al. [37] reported that the RFV of alfalfa silage (harvested at 50% flowering period) could reach 107.09. The RFV of WCK and WLM exceeded that of alfalfa (108.5 and 119.87, respectively), suggesting that wilted CLL has great potential as a high-quality forage material. In addition, the WSC and CP contents were higher in the wilted group (S2 group), especially in WLM (compound LAB additives treated), indicating that the CLL silage were well-preserved and digestible for additives. Thus, accounting for chemical composition, the S2 group performed better than the S1 group.
High throughput analyses produce data sufficient for taxonomically classifying microbiota identified during ensiling [13]. However, no studies have assessed the bacterial community in CLL silage. The alpha diversity values obtained by this study demonstrate that the bacterial community saw decreases in richness and diversity compared to the control groups, which was similar to the results of Xu et al. [39]. The main genus in the control groups (CK and WCK) was Enterobacter, followed by Kosakonia, Enterococcus, Klebsiella, Sporolactobacillus, and Sphingomonas. These were defined as undesirable bacteria and were not expected found in silage, for they always competed with LAB and negatively affected silage [30]. After ensiling for 60 days, they were replaced by Lactobacillus, which occupied over 98% in the S1 group as well as 95.4% in the S2 group. Lactobacillus can inhibit undesirable microorganisms by producing organic acids and metabolites with antimicrobial activity [40]. Additionally, differences in the microbial community could significantly affect silage quality [22]. In this study, L. buchneri and L. plantarum were the main species found in the CLL silage after ensiling for 60 days. Furthermore, the proportion of L. buchneri exceeded that of L. plantarum, which is similar to what Xu et al. [40] reported in whole crop corn: that inoculation with L. plantarum can promote the growth of L. buchneri and result in more acetic acid production than lactic acid production. Heinl et al. [41] reported that the lactic acid produced by homofermentative LAB could be utilized as the substrate of heterofermentative LAB, which could account for this phenomenon.
The fermentation process entails many types of microorganisms, produces various metabolites, and is extremely complex. As such, a better understanding of the metabolomics and bacterial community during the fermentation process could provide powerful evidence for making high-quality roughage [26]. The Spearman correlation analyzed the main bacteria and the main differential metabolites in CLL silage. Our results demonstrate that the correlation between metabolites and Lactobacillus was opposite from that in the undesirable microorganisms, indicating that Lactobacillus and the undesirable microorganisms competed during CLL ensiling. Furthermore, metabolites with biological activities were always positively associated with Lactobacillus and negatively associated with undesirable microorganisms. In the S1 group, p-Coumaric acid, which is a precursor of various phenolic compounds and exerts antioxidant and antimicrobial activities, was positively associated with L. plantarum and L. buchneri [42]. As the major derivatives of p-Coumaric acid detected in natural plants with antifungal properties [43], ethyl−p−Coumarate was positively correlated with L. plantarum and L. buchneri. Solerol was negatively associated with L. plantarum and L. buchneri and is typically a marker for succinic semialdehyde dehydrogenase, which can cause neurological and cognitive disorders [44]. In the S2 group, betulin is positively associated with L. buchneri, which is an active natural triterpenoid alcohol with antioxidant potential [45]; 7-galloylcatechin is the key precursor that forms gallic acid during anaerobic fermentation [46] and is positively correlated with L. plantarum and L. buchneri. Carbofuran is extremely lethal to mammals due to its anticholinesterase activity [47], it has a significantly negative correlation with L. plantarum and L. buchneri. Additionally, the ferulic acid content increased in LM and WLM. This indicates that the fiber digestibility in the additives treatments is better than in the control since it is typically linked to polysaccharides by ferulic acid ester in plant cell walls, forming a solid protective layer [14]. The up-accumulation of nucleobase and dipeptide was detected, which was consistent with the findings of Guo et al. [26] and Xu et al. [40] that L. buchneri can produce certain amino acids during fermentation. Metabolites with biofunctions (such as corchorifatty acid, osmundain, and furelleran, et al.) were negatively correlated with LAB species, which could be due to sample concentrations that were too low to sufficiently detect, which was similar to the findings of Xu et al. [40]. In summary, samples treated with additives (LM/WLM) resulted in the accumulation of certain metabolites with antioxidant properties and antimicrobial activity, including m-Coumaric acid, theaflavic acid, quercetin, isorhamnetin, ferulic acid, and 7-galloylcatechin. This caused a reduction in toxic and hazardous substances, including carbofuran and solerol. Admittedly, the Spearman correlation is based on statistics and correlates parameters to obtain a result that represents nothing more than speculation. Even so, the correlations between LAB and the metabolites with biological activities in CLL silage provided clues on screening targeted functional LAB strains for modulating silage fermentation with the aim of obtaining high quality silage.

5. Conclusions

Cyperus esculentus L. by-product could be processed into silage with additives after being mixed with canola straw or wilted. The compound LAB additives produced positive fermentative properties, increased the nutritional value of CLL silage. Additives enhanced the fermentation quality, resulting in low pH values, high contents of lactic acid and acetic acid, and low ammonia-N concentrations. The improved nutritional values are reflected in the increased CP and WSC contents in additives treated groups. In the perspective of FC and RFV, the wilting approach is superior to mixing with canola straw. The compound LAB additives also altered the microbiota of CLL silage. The relative abundance of Lactobacillus was enhanced and the relative abundance of undesirable microorganisms, including Clostridium and Enterobacter, was reduced. In CLL silage, substances with antioxidant properties, bacteriostatic activity, and other flavoring agents were detected, all of which typically have a positive relationship with L. buchneri and L. plantarum. As the major species in CLL silage, L. buchneri and L. plantarum might regulate silage fermentation through modifying microbiota and metabolomics. In conclusion, Cyperus esculentus L. by-product could be used as a potential roughage after it is ensiled with compounded LAB additives.

Supplementary Materials

The following are available online at, Figure S1: Principal component analysis (PCA) of metabolic profiles in S1 group (S1 A) and S2 group (S1 B) silage inoculated without (red circle) or with additives (blue triangle) (n = 6). S2: Principal component analysis (PCA) of metabolic profiles in S1 (pos: S2.A, neg: S2.B) and S2 (pos: S2 C, neg: S2 D) silage without or with additives. CK, mixed with canola straw without additives; LM ensiled with additives; WCK, wilted for 8 h without additives; WLM, wilted for 8 h and ensiled with additives.

Author Contributions

Conceptualization, J.Z. and T.W.; methodology, J.S. and W.S.; software, J.S. and C.M.; validation, J.S., T.W., W.S., C.M. and J.Z.; formal analysis, T.W.; investigation, J.S. and T.W.; resources, T.W.; data curation, J.S., T.W. and W.S.; writing—original draft preparation, J.S., F.H., Y.L.; writing—review and editing, J.S. and T.W.; visualization, T.W.; supervision, J.Z.; project administration, J.Z.; funding acquisition, J.Z. All authors have read and agreed to the published version of the manuscript.


This research was funded by Strategic Priority Research Program of the Chinese Academy of Sciences (XDA26040201), Key Deployment Project of Chinese Academy of Sciences (KFZD-SW-113).

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Not applicable.

Data Availability Statement

Data is contained within this article.


The authors are grateful to Guangmei Wang of the Yantai Institute of Coastal Zone Research, Chinese Academy of Sciences, for his donation of experimental materials.

Conflicts of Interest

The authors declare no conflict of interest.


  1. De Castro, O.; Gargiulo, R.; Del Guacchio, E.; Caputo, P.; De Luca, P. A molecular survey concerning the origin of Cyperus esculentus (Cyperaceae, Poales): Two sides of the same coin (weed vs. crop). Ann. Bot. 2015, 115, 733–745. [Google Scholar] [CrossRef][Green Version]
  2. Ayeh-Kumi, P.F.; Tetteh-Quarcoo, P.B.; Duedu, K.O.; Obeng, A.S.; Addo-Osafo, K.; Mortu, S.; Asmah, R.H. A survey of pathogens associated with Cyperus esculentus L. (tiger nuts) tubers sold in a Ghanaian city. BMC Res. Notes 2014, 7, 343. [Google Scholar] [CrossRef][Green Version]
  3. Cortes, C.E.M.; Frigola, A. Quality characteristics of horchata (a Spanish vegetable beverage) treated with pulsed electric field during shelf life. Food Chem. 2005, 91, 319–325. [Google Scholar] [CrossRef]
  4. Qu, P.; Cheng, Z.; Long, C.; Su, M.; Yang, D. Comprehensive development of chufa (Cyperuseslent L. varsatius) s. China Oils Fats 2007, 61–63. (In Chinese) [Google Scholar]
  5. Jing, S.; Wang, S.; Zhong, R.; Zhang, J.; Wu, J.; Tu, Y.; Pu, Y.; Yan, L. Neuroprotection of Cyperus esculentus L. orientin against cerebral ischemia/reperfusion induced brain injury. Neural Regen. Res. 2020, 15, 548–556. [Google Scholar] [CrossRef]
  6. Coskuner, Y.; Ercan, R.; Karababa, E.; Nazlican, A.N. Physical and chemical properties of chufa (Cyperus esculentus L.) tubers grown in the climate region of Turkey. J. Sci. Food Agric. 2002, 82, 625–631. [Google Scholar] [CrossRef]
  7. Roselló-Soto, E.; Martí-Quijal, F.J.; Cilla, A.; Munekata, P.E.S.; Lorenzo, J.M.; Remize, F.; Barba, F.J. Influence of temperature, solvent and pH on the selective extraction of phenolic compounds from tiger nuts by-products: Triple-TOF-LC-MS-MS characterization. Molecules 2019, 24, 797. [Google Scholar] [CrossRef] [PubMed][Green Version]
  8. Zhao, G.; Ju, Z.; Chai, J.; Jiao, T.; Jia, Z.; Casper, D.; Zeng, L.; Wu, J. Effects of silage additives and varieties on fermentation quality, aerobic stability, and nutritive value of oat silage. J. Anim. Sci. 2018, 96, 3151–3160. [Google Scholar] [CrossRef] [PubMed]
  9. Zhang, Y.; Wang, X.; Dai, J.; Meng, X.; Zhao, Y.; Li, Z.; Hu, Y.; Cui, Z. Construction and effect of lactic acid bacteria in oat silage and mechanism at low temperature. Trans. CSAE 2019, 35, 308–314. (In Chinese) [Google Scholar]
  10. Wang, Y.; McAllister, T.A.; Acharya, S. Condensed tannins in sainfoin: Composition, concentration, and effects on nutritive and feeding value of sainfoin forage. Crop Sci. 2015, 55, 13–22. [Google Scholar] [CrossRef]
  11. Tao, Y.; Sun, Q.; Li, F.; Xu, C.; Cai, Y. Comparative analysis of ensiling characteristics and protein degradation of alfalfa silage prepared with corn or sweet sorghum in semiarid region of Inner Mongolia. Anim. Sci. J. 2020, 91, 13321. [Google Scholar] [CrossRef]
  12. Wang, Y.; Wang, C.; Zhou, W.; Yang, F.; Chen, X.; Zhang, Q. Effects of wilting and Lactobacillus plantarum addition on the fermentation quality and microbial community of Moringa oleifera leaf silage. Front. Microbiol. 2018, 9, 1817. [Google Scholar] [CrossRef] [PubMed][Green Version]
  13. Ni, K.; Wang, F.; Zhu, B.; Yang, J.; Zhou, G.; Pan, Y.; Tao, Y.; Zhong, J. Effects of lactic acid bacteria and molasses additives on the microbial community and fermentation quality of soybean silage. Bioresour. Technol. 2017, 238, 706–715. [Google Scholar] [CrossRef]
  14. Su, R.; Ni, K.; Wang, T.; Yang, X.; Zhang, J.; Liu, Y.; Shi, W.; Yan, L.; Jie, C.; Zhong, J. Effects of ferulic acid esterase-producing Lactobacillus fermentum and cellulase additives on the fermentation quality and microbial community of alfalfa silage. PeerJ 2019, 7, 7712. [Google Scholar] [CrossRef] [PubMed][Green Version]
  15. Ren, H.; Feng, Y.; Pei, J.; Li, J.; Wang, Z.; Fu, S.; Zheng, Y.; Li, Z.; Peng, Z. Effects of Lactobacillus plantarum additive and temperature on the ensiling quality and microbial community dynamics of cauliflower leaf silages. Bioresour. Technol. 2020, 307, 123238. [Google Scholar] [CrossRef] [PubMed]
  16. Broderick, G.A.; Kang, J.H. Automated simultaneous determination of ammonia and total amino acids in ruminal fluid and In vitro media. J. Dairy Sci. 1980, 63, 64–75. [Google Scholar] [CrossRef]
  17. Playne, M.; McDonald, P. The buffering constituents of herbage and of silage. J. Sci. Food Agric. 1966, 17, 264–268. [Google Scholar] [CrossRef]
  18. Wang, T.; Teng, K.; Cao, Y.; Shi, W.; Xuan, Z.; Zhou, J.; Zhang, J.; Zhong, J. Effects of Lactobacillus hilgardii 60TS-2, with or without homofermentative Lactobacillus plantarum B90, on the aerobic stability, fermentation quality and microbial community dynamics in sugarcane top silage. Bioresour. Technol. 2020, 312, 123600. [Google Scholar] [CrossRef] [PubMed]
  19. Murphy, R.P. A method for the extraction of plant samples and the determination of total soluble carbohydrates. J. Sci. Food Agric. 1958, 9, 714–717. [Google Scholar] [CrossRef]
  20. Association of Official Analytical Chemists. Official Methods of Analysis; Association of Official Analytical Chemists: Arlington, VA, USA, 1990. [Google Scholar]
  21. VanSoest, P.H.; Robertson, J.B.; Lewis, B.A. Methods for dietary fiber, neutral detergent fiber, and nonstarch polysaccharides in relation to animal nutrition. J. Dairy Sci. 1991, 74, 3583–3597. [Google Scholar] [CrossRef]
  22. Ni, K.; Zhao, J.; Zhu, B.; Su, R.; Pan, Y.; Ma, J.; Zhou, G.; Tao, Y.; Liu, X.; Zhong, J. Assessing the fermentation quality and microbial community of the mixed silage of forage soybean with crop corn or sorghum. Bioresour. Technol. 2018, 265, 563–567. [Google Scholar] [CrossRef]
  23. Wang, X.; Sun, G.; Feng, T.; Zhang, J.; Huang, X.; Wang, T.; Xie, Z.; Chu, X.; Yang, J.; Wang, H. Sodium oligomannate therapeutically remodels gut microbiota and suppresses gut bacterial amino acids-shaped neuroinflammation to inhibit Alzheimer’s disease progression. Cell Res. 2019, 29, 787–803. [Google Scholar] [CrossRef]
  24. Xie, Z.; Zhang, T.; Chen, X.; Li, G.; Zhang, J. Effects of maturity stages on the nutritive composition and silage quality of whole crop wheat. Asian-Australas. J. Anim. Sci. 2012, 25, 1374–1380. [Google Scholar] [CrossRef] [PubMed]
  25. Weissbach, F.; Honig, H. On the anticipation and control of the run of fermentation silage making from extensively grown forages. Landbauforchung Völkenrode 1996, 46, 10–17, (In German, English Summary). [Google Scholar]
  26. Guo, X.; Ke, W.; Ding, W.; Ding, L.; Xu, D.; Wang, W.; Zhang, P.; Yang, F. Profiling of metabolome and bacterial community dynamics in ensiled Medicago sativa inoculated without or with Lactobacillus plantarum or Lactobacillus buchneri. Sci. Rep. 2018, 8, 357. [Google Scholar] [CrossRef] [PubMed][Green Version]
  27. Broderick, G.A.; Walgenbach, R.P.; Sterrenburg, E. Performance of lactating dairy cows fed alfalfa or red clover silage as the sole forage. J. Dairy Sci. 2000, 83, 1543–1551. [Google Scholar] [CrossRef]
  28. Cai, Y.; Benno, Y.; Ogawa, M.; Ohmomo, S.; Kumai, S.; Nakase, T. Influence of Lactobacillus spp. from an inoculant and of Weissella and Leuconostoc spp. from forage crops on silage fermentation. Appl. Environ. Microbiol. 1998, 64, 2982–2987. [Google Scholar] [CrossRef][Green Version]
  29. Oliveira, A.S.; Weinberg, Z.G.; Ogunade, I.M.; Cervantes, A.A.P.; Arriola, K.G.; Jiang, Y.; Kim, D.; Li, X.; Gonçalves, M.C.M.; Vyas, D.; et al. Meta-analysis of effects of inoculation with homofermentative and facultative heterofermentative lactic acid bacteria on silage fermentation, aerobic stability, and the performance of dairy cows. J. Dairy Sci. 2017, 100, 4587–4603. [Google Scholar] [CrossRef][Green Version]
  30. Ávila, C.L.S.; Carvalho, B.F. Silage fermentation-updates focusing on the performance of microorganisms. J. Appl. Microbiol. 2020, 128, 966–984. [Google Scholar] [CrossRef][Green Version]
  31. Kung, L., Jr.; Ranjit, N.K. The effect of Lactobacillus buchneri and other additives on the fermentation and aerobic stability of barley silage. J. Dairy Sci. 2001, 84, 1149–1155. [Google Scholar] [CrossRef]
  32. Zhang, Q.; Wu, B.; Nishino, N.; Wang, X.; Yu, Z. Fermentation and microbial population dynamics during the ensiling of native grass and subsequent exposure to air. Anim. Sci. J. 2016, 87, 389–397. [Google Scholar] [CrossRef]
  33. Li, X.; Chen, F.; Wang, X.; Sun, L.; Guo, L.; Xiong, Y.; Wang, Y.; Zhou, H.; Jia, S.; Yang, F. Impacts of low temperature and ensiling period on the bacterial bommunity of oat silage by SMRT. Microorganisms 2021, 9, 274. [Google Scholar] [CrossRef] [PubMed]
  34. Yan, Y.; Li, X.; Guan, H.; Huang, L.; Ma, X.; Peng, Y.; Li, Z.; Nie, G.; Zhou, J.; Yang, W.; et al. Microbial community and fermentation characteristic of Italian ryegrass silage prepared with corn stover and lactic acid bacteria. Bioresour. Technol. 2019, 279, 166–173. [Google Scholar] [CrossRef] [PubMed]
  35. Herrmann, C.; FitzGerald, J.; O’Shea, R.; Xia, A.; O’Kiely, P.; Murphy, J.D. Ensiling of seaweed for a seaweed biofuel industry. Bioresour. Technol. 2015, 196, 301–313. [Google Scholar] [CrossRef]
  36. Borreani, G.; Tabacco, E.; Schmidt, R.J.; Holmes, B.J.; Muck, R.E. Silage review: Factors affecting dry matter and quality losses in silages. J. Dairy Sci. 2018, 101, 3952–3979. [Google Scholar] [CrossRef] [PubMed][Green Version]
  37. Ertekin, İ.; Kızılşimşek, M. Effects of lactic acid bacteria inoculation in pre-harvesting period on fermentation and feed quality properties of alfalfa silage. Asian-Australas. J. Anim. Sci. 2019, 33, 245–253. [Google Scholar] [CrossRef][Green Version]
  38. Hackmann, T.J.; Sampson, J.D.; Spain, J.N. Comparing relative feed value with degradation parameters of grass and legume forages. J. Anim. Sci. 2008, 86, 2344–2356. [Google Scholar] [CrossRef][Green Version]
  39. Xu, D.; Ding, Z.; Wang, M.; Bai, J.; Ke, W.; Zhang, Y.; Guo, X. Characterization of the microbial community, metabolome and biotransformation of phenolic compounds of sainfoin (Onobrychis viciifolia) silage ensiled with or without inoculation of Lactobacillus plantarum. Bioresour. Technol. 2020, 316, 123910. [Google Scholar] [CrossRef]
  40. Xu, D.; Ding, W.; Ke, W.; Li, F.; Zhang, P.; Guo, X. Modulation of metabolome and bacterial community in whole crop Corn silage by inoculating homofermentative Lactobacillus plantarum and heterofermentative Lactobacillus buchneri. Front. Microbiol. 2018, 9, 3299. [Google Scholar] [CrossRef][Green Version]
  41. Heinl, S.; Wibberg, D.; Eikmeyer, F.; Szczepanowski, R.; Blom, J.; Linke, B.; Goesmann, A.; Grabherr, R.; Schwab, H.; Pühler, A.; et al. Insights into the completely annotated genome of Lactobacillus buchneri CD034, a strain isolated from stable grass silage. J. Biotechnol. 2012, 161, 153–166. [Google Scholar] [CrossRef]
  42. Pei, K.; Ou, J.; Huang, J.; Ou, S. p-Coumaric acid and its conjugates: Dietary sources, pharmacokinetic properties and biological activities. J. Sci. Food Agric. 2016, 96, 2952–2962. [Google Scholar] [CrossRef]
  43. Li, W.; Yuan, S.; Sun, J.; Li, Q.; Jiang, W.; Cao, J. Ethyl p-Coumarate exerts antifungal activity in vitro and in vivo against fruit Alternaria alternata via membrane-targeted mechanism. Int. J. Food Microbiol. 2018, 278, 26–35. [Google Scholar] [CrossRef]
  44. Brown, G.K.; Cromby, C.H.; Manning, N.J.; Pollitt, R.J. Urinary organic acids in succinic semialdehyde dehydrogenase deficiency: Evidence of alpha-oxidation of 4-hydroxybutyric acid, interaction of succinic semialdehyde with pyruvate dehydrogenase and possible secondary inhibition of mitochondrial beta-oxidation. J. Inherit. Metab. Dis. 1987, 10, 367–375. [Google Scholar] [CrossRef] [PubMed]
  45. Zhang, W.; Jiang, H.; Yang, J.; Jin, M.; Du, Y.; Sun, Q.; Cao, L.; Xu, H. Safety assessment and antioxidant evaluation of betulin by LC-MS combined with free radical assays. Anal. Biochem. 2019, 587, 113460. [Google Scholar] [CrossRef]
  46. Zhang, H.; Liu, Y.Z.; Xu, W.C.; Chen, W.J.; Wu, S.; Huang, Y.Y. Metabolite and microbiome profilings of Pickled Tea elucidate the role of anaerobic fermentation in promoting high levels of gallic acid accumulation. J. Agric. Food Chem. 2020, 68, 13751–13759. [Google Scholar] [CrossRef] [PubMed]
  47. Mishra, S.; Zhang, W.; Lin, Z.; Pang, S.; Huang, Y.; Bhatt, P.; Chen, S. Carbofuran toxicity and its microbial degradation in contaminated environments. Chemosphere 2020, 259, 127419. [Google Scholar] [CrossRef] [PubMed]
Figure 1. Relative abundances of bacteria communities in CLL silage. (A): the genus level of the S1 group; (B): the species level of the S1 group; (C): the genus level of the S2 group; (D): the species level of the S2 group. S1, Sample 1 (mixed with canola straw at a ratio of 4:1); S2, Sample 2 (wilted for 8 h). CK, mixed with rapeseed straw without additives; LM, ensiled with additives; WCK, wilted for 8 h without additives; WLM, wilted for 8 h and ensiled with additives.
Figure 1. Relative abundances of bacteria communities in CLL silage. (A): the genus level of the S1 group; (B): the species level of the S1 group; (C): the genus level of the S2 group; (D): the species level of the S2 group. S1, Sample 1 (mixed with canola straw at a ratio of 4:1); S2, Sample 2 (wilted for 8 h). CK, mixed with rapeseed straw without additives; LM, ensiled with additives; WCK, wilted for 8 h without additives; WLM, wilted for 8 h and ensiled with additives.
Fermentation 07 00273 g001
Figure 2. Spearman correlations between main bacteria species and differentially presented metabolites in S1 group. The differentially presented metabolites during fermentation were screened by OPLS-DA; p-values are shown as * p ≤ 0.05; ** p ≤ 0.01; *** p ≤0.001.
Figure 2. Spearman correlations between main bacteria species and differentially presented metabolites in S1 group. The differentially presented metabolites during fermentation were screened by OPLS-DA; p-values are shown as * p ≤ 0.05; ** p ≤ 0.01; *** p ≤0.001.
Fermentation 07 00273 g002
Figure 3. The differentially presented metabolites during fermentation were screened by OPLS-DA; p-values are shown as * p ≤ 0.05; ** p ≤ 0.01; *** p ≤ 0.001.
Figure 3. The differentially presented metabolites during fermentation were screened by OPLS-DA; p-values are shown as * p ≤ 0.05; ** p ≤ 0.01; *** p ≤ 0.001.
Fermentation 07 00273 g003
Table 1. Chemical composition and cultivable microbial population of raw materials before ensiling.
Table 1. Chemical composition and cultivable microbial population of raw materials before ensiling.
ItemCLLCanola StrawS1S2
Chemical composition
CP (%DM)11.565.215.1711.96
NDF (%DM)56.0862.4061.4055.10
ADF (%DM)28.9250.5140.5529.40
ADL (%DM)9.543.534.548.40
WSC (%DM)2.528.456.463.20
Cultivable microbial population (log10 CFU/g FM)
DM, dry matter; FM, fresh matter; CP, crude protein; NDF, neutral detergent fiber; ADF, acid detergent fiber; ADL, acid detergent lignin; WSC, water soluble carbohydrates; LAB, lactic acid bacteria; CFU, colony forming units; “/”, the detection was not performed; CLL, Cyperus esculentus L. leaves; S1, Sample 1 (mixed with canola straw at a ratio of 4:1); S2, Sample 2 (wilted for 8 h).
Table 2. Effects of additives on CLL silage quality and microbial population after 60 days of storage.
Table 2. Effects of additives on CLL silage quality and microbial population after 60 days of storage.
ItemS1 GroupS2 Group
CKLMp ValueWCKWLMp Value
The fermentation quality
pH value5.66 ± 0.18 a4.09 ± 0.06 b<0.015.84 ± 0.02 a3.91 ± 0.01 b<0.01
Lactic acid (g/kg DM)ND97.78 ± 24.05<0.01ND146.33 ± 8.98<0.01
Acetic acid (g/kg DM)14.00 ± 2.10 b146.34 ± 13.74 a<0.0118.67 ± 1.97 b215.00 ± 2.83 a<0.01
Ethanol (g/kg DM)17.00 ± 1.63 a 10.17 ± 1.94 b <0.0119.67 ± 5.35ND <0.01
Ammonia-N (g/kg DM)2.26 ± 0.12 a1.30 ± 0.20 b<0.015.66 ± 0.49 a1.63 ± 0.32 b<0.01
BC (meq/100 g DM)19.79 ± 1.2922.83 ± 1.840.1921.55 ± 0.0618.45 ± 0.560.02
FC36.01 ± 1.3036.83 ± 0.270.4831.94 ± 2.7437.61 ± 2.610.17
Chemical composition
DM%36.88 ± 0.0237.89 ± 0.020.3132.74 ± 0.01 b37.20 ± 0.03 a<0.01
CP (%DM)8.21 ± 0.38 b9.60 ± 0.10 a<0.0112.17 ± 0.57 b13.35 ± 0.17 a<0.01
NDF (%DM)63.68 ± 1.8961.78 ± 1.930.2155.75 ± 1.06 a51.70 ± 1.88 b0.01
ADF (%DM)43.95 ± 1.0641.82 ± 2.510.1730.68 ± 0.48 a28.69 ± 0.32 b<0.01
ADL (%DM)8.95 ± 0.758.62 ± 0.840.573.89 ± 0.373.63 ± 0.280.30
WSC (%DM)0.39 ± 0.05 b0.71 ± 0.04 a<0.010.63 ± 0.20 b1.01 ± 0.08 a0.01
RFV79.93 ± 3.6184.92 ± 5.390.17108.5 ± 2.51 b119.87 ± 4.94 a<0.01
Cultivable microbial population (log10 CFU/g FM)
LAB3.95 ± 2.21 b5.54 ± 0.15 a<0.012.04 ± 2.36 b5.38 ± 0.14 a<0.01
Aerobes4.39 ± 0.12 a2.37 ± 1.84 b<0.014.22 ± 0.03 a1.17 ± 1.61 b<0.01
CK, mixed with canola straw without additives; LM, ensiled with additives; WCK, wilted for 8 h without additives; WLM, wilted for 8 h and ensiled with additives; DM, dry matter; CP, crude protein; NDF, neutral detergent fiber; ADF, acid detergent fiber; ADL, acid detergent lignin; WSC, water soluble carbohydrates; RFV, relative feed value; BC, buffering capacity; FC, fermentation coefficient; LAB, lactic acid bacteria; CFU, colony forming units; ND, not detected. S1, Sample 1 (mixed with canola straw at a ratio of 4:1); S2, Sample 2 (wilted for 8 h). Means ± SD within the same row with different letters is significantly different (p < 0.05).
Table 3. Alpha diversity of the bacterial community in the S1 and S2 groups after 60 days of ensiling.
Table 3. Alpha diversity of the bacterial community in the S1 and S2 groups after 60 days of ensiling.
ItemS1 GroupS2 Group
CKLMp ValueWCKWLMp Value
Shannon1.99 ± 0.08 a0.58 ± 0.03 b<0.012.00 ± 0.24 a0.83 ± 0.08 b<0.01
Simpson0.25 ± 0.02 b0.69 ± 0.02 a<0.010.29 ± 0.06 b0.55 ± 0.05 a0.02
ACE240.46 ± 11.46209.68 ± 16.930.13207.95 ± 21.69159.66 ± 10.510.13
Chao 1234.94 ± 11.42177.19 ± 18.940.03190.38 ± 17.50136.69 ± 10.240.07
CK, mixed with canola straw without additives; LM, ensiled with additives; WCK, wilted for 8 h without additives; WLM, wilted for 8 h and ensiled with additives. S1, Sample 1 (mixed with canola straw at a ratio of 4:1); S2, Sample 2 (wilted for 8 h). Means ± SD within the same row with different letters is significantly different (p < 0.05).
Table 4. Relative concentration and fold-changes in differential metabolites in S1 and S2 groups after 60 days of ensiling.
Table 4. Relative concentration and fold-changes in differential metabolites in S1 and S2 groups after 60 days of ensiling.
Metabolite NameS1 GroupS2 Group
CKLMFold ChangeWCKWLMFold Change
Benzene and substituted derivativesSyringic acid12.42 ± 0.18 b14.29 ± 0.55 a1.87 ± 0.5313.28 ± 0.30 b15.3 ± 0.13 a2.02 ± 0.31
Carboxylic acids and derivativesL-Tyrosine6.52 ± 0.83 b9.89 ± 0.14 a3.37 ± 0.88ND ND ND
Valyl-IsoleucineND ND ND 2.92 ± 0.65 b9.87 ± 0.15 a3.50 ± 0.61
Threoninyl-IsoleucineND ND ND 1.55 ± 2.33 b9.63 ± 0.15 a8.08 ± 2.34
Glycyl-IsoleucineND ND ND 5.18 ± 2.18 b10.85 ± 0.11 a5.66 ± 2.14
Asparaginyl-IsoleucineND ND ND 6.29 ± 0.65 b10.50 ± 0.12 a4.20 ± 0.74
Cinnamic acids and derivativesSinapic acid9.53 ± 1.2911.09 ± 0.701.56 ± 1.862.92 ± 0.65 b9.87 ± 0.15 a6.96 ± 0.77
Caffeic acid10.04 ± 0.1111.81 ± 0.791.78 ± 0.8210.60 ± 0.49 b13.53 ± 0.12 a2.93 ± 0.48
2-hydroxycinnamic acid12.25 ± 0.90 b14.76 ± 0.12 a2.51 ± 0.90ND ND ND
M-Coumaric acid8.18 ± 0.80 b11.61 ± 0.29 a3.42 ± 0.949.27 ± 0.76 b12.64 ± 0.08 a3.38 ± 0.73
Punicic acidPunicic acid14.93 ± 0.2815.25 ± 0.110.32 ± 0.27ND ND ND
FlavonoidsQuercetin12.21 ± 1.4014.14 ± 0.631.94 ± 1.68ND ND ND
Theaflavic acid14.73 ± 0.2915.27 ± 0.200.54 ± 0.38ND ND ND
Isorhamnetin14.21 ± 1.1315.52 ± 0.311.31 ± 1.21ND ND ND
Isovitexin14.27 ± 0.3314.76 ± 0.130.49 ± 0.40ND ND ND
7-galloylcatechinND ND ND 2.96 ± 1.54 b10.24 ± 0.41 a7.27 ± 1.76
Kaempferol 3-(2″-rhamnosylrutinoside)ND ND ND 9.31 ± 0.79 b13.64 ± 0.29 a4.32 ± 0.67
ImidazopyrimidinesHypoxanthine12.34 ± 0.2810.95 ± 0.15−1.39 ± 0.3712.50 ± 0.39 a10.09 ± 0.20 b−2.40 ± 0.49
Macrolides and analoguesZeranol8.84 ± 0.53 b10.48 ± 0.78 a1.64 ± 0.84ND ND ND
Organooxygen compounds1,3-dicaffeoylquinic acidNDNDND 11.39 ± 0.9412.35 ± 0.360.96 ± 0.92
3-O-p-Coumaroylquinic acidNDNDND 10.07 ± 0.24 b12.43 ± 0.54 a2.36 ± 0.43
Chlorogenic acidNDNDND 11.73 ± 0.54 b14.67 ± 0.57 a2.95 ± 0.72
N-di-Demethyl roxithromycinNDNDND 9.52 ± 1.47 b11.59 ± 0.58 a2.07 ± 1.87
3-O-feruloylquinic acidNDNDND 7.17 ± 1.38 b10.71 ± 0.75 a3.54 ± 1.51
Phenylpropanoic acidsHydroxyphenyllactic acidNDNDND 10.34 ± 0.42 b12.18 ± 0.14 a1.84 ± 0.45
Prenol lipidsAnnoglabasin E8.02 ± 0.949.96 ± 0.331.94 ± 1.126.36 ± 0.38 b10.56 ± 0.55 a4.20 ± 0.40
BetulinNDNDND7.08 ± 1.61 b11.02 ± 0.92 a4.02 ± 1.82
PiperidinePiperidineNDNDND14.64 ± 0.2114.39 ± 0.10−0.25 ± 0.18
Steroids and steroid derivatives7a-hydroxy-5b-cholanic acid13.19 ± 0.6611.87 ± 0.97−1.32 ± 1.413.97 ± 0.203.57 ± 0.30−0.40 ± 0.10
Quinolines and derivativesGrandisine IIIND ND ND 11.94 ± 0.7410.05 ± 0.54−1.88 ± 0.91
OthersFerulic acid11.47 ± 0.6913.31 ± 0.201.84 ± 0.6312.26 ± 0.6313.09 ± 0.140.83 ± 0.71
D-(+)-3-phenyllactic acid13.66 ± 0.2114.71 ± 0.061.05 ± 0.2612.67 ± 0.52 b14.86 ± 0.06 a2.19 ± 0.53
7-epi-Jasmonic acid12.15 ± 1.06 a8.46 ± 0.48 b−3.69 ± 1.4212.77 ± 3.24 a2.42 ± 1.23 b−10.36 ± 3.24
The relative concentration of each metabolite is an average of the data from six biological replicates. FC, fold-changes, positive value means upregulation; negative value means downregulation. CK, mixed with canola straw without additives; LM, ensiled with additives; WCK, wilted for 8 h without additives; WLM, wilted for 8 h and ensiled with additives; “ND”, not detected. “Others“ means there is no corresponding classification in the Human Metabolome Database (HMDB). Means ± SD within the same row with different letters is significantly different (p < 0.05).
Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Share and Cite

MDPI and ACS Style

Sun, J.; Wang, T.; Huang, F.; Liu, Y.; Shi, W.; Ma, C.; Zhong, J. Silage Fermentation: A Potential Microbial Approach for the Forage Utilization of Cyperus esculentus L. By-Product. Fermentation 2021, 7, 273.

AMA Style

Sun J, Wang T, Huang F, Liu Y, Shi W, Ma C, Zhong J. Silage Fermentation: A Potential Microbial Approach for the Forage Utilization of Cyperus esculentus L. By-Product. Fermentation. 2021; 7(4):273.

Chicago/Turabian Style

Sun, Jiahao, Tianwei Wang, Fuqing Huang, Yayong Liu, Weixiong Shi, Cui Ma, and Jin Zhong. 2021. "Silage Fermentation: A Potential Microbial Approach for the Forage Utilization of Cyperus esculentus L. By-Product" Fermentation 7, no. 4: 273.

Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here.

Article Metrics

Back to TopTop