**Intensive Multiple Sequential Batch Simultaneous Saccharification and Cultivation of** *Kluyveromyces marxianus* **SS106 Thermotolerant Yeast Strain for Single-Step Ethanol Fermentation from Raw Cassava Starch**

#### **Kwanruthai Malairuang 1, Morakot Krajang 1, Rapeepong Rotsattarat <sup>2</sup> and Saethawat Chamsart 3,\***


Received: 29 June 2020; Accepted: 20 July 2020; Published: 27 July 2020

**Abstract:** We developed the intensive multiple sequential batch simultaneous saccharification and cultivation of the selected thermotolerant yeast strain for single-step ethanol production. The selection and high-cell-density inoculum production of thermotolerant yeast able to produce ethanol under the optimal conditions for single-step ethanol fermentation has become a necessity. In this study, the newly isolated *Kluyveromyces marxianus* SS106 could tolerate high temperatures (35–45 ◦C) and grow under a wide range of pH values (3.0–5.5), which are the optimum conditions of raw cassava starch hydrolyzing enzyme used in single-step ethanol fermentation. The high-cell-density concentration of *K. marxianus* SS106 was produced by a single batch and an intensive multiple sequential batch process in a 5-L stirred tank bioreactor using the simultaneous saccharification and cultivation (SSC) method. The single SSC process yielded the yeast cell biomass at a concentration of 39.30 g/L with a productivity of 3.28 g/L/h and a specific growth rate of 0.49 h<sup>−</sup>1. However, the yeast cell density concentration was higher in the intensive multiple sequential batch SSC than in the single batch process. This process yielded yeast cell biomass at concentrations of 36.09–45.82 g/L with productivities of 3.01–3.82 g/L/h and specific growth rates of 0.29–0.44 h−<sup>1</sup> in the first six batch cycle. The results suggested that the intensive multiple sequential batch simultaneous saccharification and cultivation of *K. marxianus* SS106 would be a promising process for high-cell-density yeast production for use as the inoculum in single-step ethanol fermentation. Furthermore, we also experimented with single-step ethanol production from raw cassava starch by *K. marxianus* SS106 in a 5-L stirred tank fermenter. This produced ethanol at a concentration of 61.72 g/L with a productivity of 0.86 g/L/h.

**Keywords:** simultaneous saccharification and cultivation (SSC); intensive multiple sequential batch cultivation; thermotolerant yeast; *Kluyveromyces marxianus*; ethanol production

#### **1. Introduction**

One of the problems associated with the conventional process for ethanol production based on cassava starch raw material is the different optimum temperatures for liquefaction, saccharification, and fermentation. This process requires high energy consumption because starch hydrolysis takes place at high temperatures that require enormous amounts of steam and an efficient water-based

cooling system to bring down the temperature to fermentation process [1,2]. To improve the ethanol production process from starchy materials, single-step ethanol production using a combination of raw starch hydrolysis and fermentation was developed here. This process used granular starch hydrolyzing enzyme and free cells of yeast at the same time for reducing the cost of energy input and fermentation time from multistage operation.

*Kluyveromyces marxianus*, a type of "non-conventional" yeast in the *Kluyveromyces* genus of the family Saccharomycetaceae, has recently been in the limelight for economic cellulosic ethanol production. Besides its ability of ethanol fermentation, *K. marxianus* possesses a number of advantages over *Saccharomyces cerevisiae*, which has been traditionally used in bioethanol production. *K. marxianus* is the fastest growing yeast, with a maximum growth rate of 0.80 h<sup>−</sup>1, and *S. cerevisiae* is only 0.37 h<sup>−</sup>1. *K. marxianus* can even grow at 52 ◦C due to its notable thermotolerance, while *S. cerevisiae* has optimum temperatures ranging from 30 to 37 ◦C. In addition, besides glucose, *K. marxianus* is able to utilize a variety of carbon sources, including inulin, xylose, and lactose, which cannot be used by *S. cerevisiae*. Furthermore, ethanol generation prefers an anaerobic environment; thus, the capability to grow under full anaerobiosis is also required for a yeast strain to be used in a fuel ethanol-producing process. *K. marxianus*, like *S. cerevisiae*, is a respiro-fermentative yeast, and the batch fermentation of *K. marxianus* in a strict anaerobic environment at 37 ◦C reached ethanol concentrations significantly higher than in aerobiosis. Based on the above, *K. marxianus* could be an ideal yeast for industrial bioethanol production. Currently, *K. marxianus* can only bear the maximum 6% (*v*/*v*) ethanol, which is measured by the growth ability in shake flask culture in YPD (yeast extract peptone dextrose) medium with 6% ethanol at 30 ◦C. The low ethanol tolerance leads to its low ethanol yield and is the major bottleneck to block its practical industry application so far [3].

In our previous studies, raw cassava starch hydrolysis was successfully done at a high temperature of 40 ◦C and low pH value of 3.0–4.0 [4]. Therefore, the selection and high cell inoculum production of yeast strain that could be tolerant to high temperatures, low pH values, and high ethanol concentrations are important and of interest in this study.

High temperature fermentation is a key requirement for effective ethanol production in tropical countries where average day-time temperatures are usually high throughout the year [5]. Therefore, several researchers studied the successful selections of thermotolerant yeast strains in ethanol fermentation. Most of the experiments have been focused on *S. cerevisiae* [6,7] and *K. marxianus* [8–10]. However, these strains were employed for ethanol production only by the simultaneous saccharification and fermentation process. Therefore, it is interesting to use the thermotolerant yeast strain for the single-step process in the ethanol production industry in Thailand.

Not only the selection of the thermotolerant yeast strain, but high-cell-density inoculum production is also very important for ethanol fermentation. The typical method employed for the increase in yeast cell number density is the fed-batch cultivation mode which has been proved to be one of the most successful processes for increasing cell concentration and volumetric productivity of standard batch cultivation [11]. Besides the fed-batch cultivation process, simultaneous saccharification and cultivation (SSC) could be focused in high-cell-density production. After starch liquefaction by alpha-amylase, nitrogen sources, mineral salts, and glucoamylase are added into liquefied slurry, concurrently with yeast inoculum, and SSC is conducted in a bioreactor. The presence of yeast with those enzymes reduces the sugar accumulation in a reactor. During cultivation, liquefied starch (oligomer called dextrin) is gradually hydrolyzed by glucoamylase to release glucose and is simultaneously utilized by yeast. This prevents the Crabtree effect that usually occurs in aerobic cultivation with high glucose concentration.

Here, the intensive multiple sequential batch cultivation method has been introduced to increase cell concentration, volumetric productivity and cost effectiveness. In intensive multiple sequential batch cultivation, a bioreactor is initially filled with a medium and yeast cells and then incubated under optimal conditions to achieve high-cell concentration. After the initial batch reaches the end of the exponential phase, a desired volume of culture is withdrawn as the product and then another equal volume of fresh medium is fed into the same bioreactor. The cultivation is again restarted under the same conditions as the first batch, using the remaining culture in the bioreactor as the starting inoculum. Therefore, it is interesting to improve the efficiency of the SSC process for high-cell-density yeast inoculum production by intensive multiple sequential batch cultivation. Moreover, it also reduces the operation time for cleaning, sterilization, and inoculation [2,12]. In this study, we also looked for an appropriate yeast strain for the single-step ethanol production using a combination of raw starch hydrolysis and fermentation. The objective of this study is not only to select a thermotolerant yeast strain for single-step ethanol fermentation, but also to establish a practical approach to produce high-cell-density yeast biomass by intensive multiple sequential batch simultaneous saccharification and cultivation.

#### **2. Materials and Methods**

#### *2.1. Materials*

According to our studies [13], liquefied starch with a dextrose equivalent (DE) of 10–13 was prepared in a 10-L hydrolysis bioreactor. A 10% (*w*/*v*) suspension of cassava starch was added with 0.1% (*w*/*w*) of α-amylase (Spezyme Alpha, thermostable α-amylase; Dupont Industrial Biosciences, Shanghai, China). Then, the mixture was agitated at 100 rpm for 3 h at 85 ◦C. Glucose at a DE of 95 was prepared by hydrolysis of liquefied starch. After liquefaction, the slurry was cooled to 60 ◦C and subsequently added with 0.2% (*w*/*w*) of glucoamylase and bacteria pullulanase (Distillase ASP, a blend of enzymes; Dupont Industrial Biosciences, Shanghai, China). The mixture was agitated at 100 rpm for 20 h at 60 ◦C.

Raw cassava starch, used as the carbon source for single-step ethanol fermentation, was pretreated in the 10-L hydrolysis bioreactor. A 20% (*w*/*v*) of cassava starch slurry was pretreated with 0.1% (*w*/*w*) of Distillase ASP. The mixture was agitated at 100 rpm for 1 h at 60 ◦C [4]. After pretreatment, the starch slurry was cooled to 40 ◦C for the single-step ethanol fermentation. (The composition of cassava starch was analyzed by [14]. The moisture, protein, ash, fat, crude fiber, carbohydrate, and amylose contents ranged from 7.10 to 7.61%, 0.32 to 31.02%, 0.45 to 2.67%, 0.17 to 1.19%, 0.07 to 1.69%, 8.13 to 90.77%, and 23.04 to 29.45%, respectively.)

#### *2.2. Media*

The yeast malt (YM) medium was composed of 3 g of yeast extract, 5 g of malt extract, 5 g of peptone, 10 g of glucose, per liter. The fermentation medium utilized in the selection of thermotolerant yeasts for ethanol production at high temperatures was composed of 200 g of glucose from cassava starch hydrolysis, 10 g of sugarcane molasses, 3.8 g of MgSO4.7H2O, per liter. The yeast peptone dextrose (YPD) medium (used in study of growth kinetics) was composed of 10 g of yeast extract, 20 g of peptone, 50 g of glucose, per liter. The yeast production medium was composed of 100 g of liquefied starch, 20 g of yeast extract, 1.5 g of KH2PO4, 1.8 g of Na2HPO4, 0.2 g of MgSO4.7H2O, 1 mL of trace element solution, per liter [15]. The ethanol production medium (utilized in single-step ethanol fermentation) was composed of 200 g of pretreated raw cassava starch, 100 g of sugarcane molasses, 0.2 g of (NH4)2HPO4, 1.5 g of KH2PO4, 1.8 g of Na2HPO4, 3.8 g of MgSO4.7H2O, per liter.

#### *2.3. Screening and Isolating of Thermotolerant Yeast Strains*

The yeast strains were isolated from dry cassava pulp and soil samples from a cassava starch factory, Chorchaiwat Industry Co., Ltd., Chonburi, Thailand. The first screening was done at 40 ◦C in YM medium at pH 5.5 with 1 *n* HCl. After inoculation, the cultures were incubated on a rotary incubator shaker (Lab Tech, Korea) at a shaking speed of 200 rpm for 48 h. The enriched cultures were spread on agar plates containing the same medium and incubated at the same temperature and time. The single colonies of the isolated strains were studied their morphology and picked. The purified strains were kept on a YM agar slant and incubated at the same temperature and time above, and after that were stored at 4 ◦C.

The thermotolerant strains were isolated based on their growth performances in YM medium by incubating them on a rotary incubator shaker at 35, 38, 40, 42, and 45 ◦C for 24 h at a shaking speed of 200 rpm. In addition, they were incubated at the designed temperature of 40 ◦C in the same medium with different initial pH of 3.0, 3.5, 4.0, 4.5, 5.0, and 5.5 for their growth study in acidic conditions. The successful cultured strains were selected and collected for further ethanol production at a high temperature.

#### *2.4. Selection of Thermotolerant Yeast for Single-Step Ethanol Fermentation*

Later, the selection of strains for ethanol production at the high temperature of 40 ◦C was conducted in 250 mL Erlenmeyer flasks each containing 50 mL of fermentation medium at pH 4.0. Inoculants were prepared by transferring one loop full of each isolate from the YM agar slant into the flask containing 50 mL of YM broth at the same temperature and then incubated on a rotary incubator shaker at 200 rpm for 24 h. After incubation, each culture was diluted with distilled water to adjust the optical density to 10.0 and transferred 10 mL of each isolate to the fermentation medium in the 250 mL flasks above, and then incubated at 40 ◦C on a rotary shaker at 100 rpm (anaerobic fermentation needs less air) for 48 h.

#### *2.5. Growth Kinetics of the Selected Thermotolerant Yeast*

Growth kinetics of the selected thermotolerant strain was studied by cultivation in a 250 mL Erlenmeyer flask containing YPD medium composed of 50 g/L of glucose, at 40 ◦C and pH 4.0. Five ml of inoculum (OD660 10.0) was inoculated into the above flask. The culture was then incubated on a rotary shaker at 200 rpm for 48 h.

#### *2.6. Optimization of StargenTM002 Concentration for Simultaneous Saccharification and Cultivation of the Selected Thermotolerant Yeast to Produce Cells at High-Density Concentration*

Normally, yeast cannot directly utilize starch or oligosaccharide so that the StargenTM002 (a granular starch hydrolyzing enzyme, Dupont Industrial Biosciences, Shanghai, China) was essentially optimized before adding into liquefied starch with the SSC method. The optimization of StargenTM002 concentration was conducted in the 10-L lysis reactor containing 100 g/L of liquefied starch. Different StargenTM002 dosages of 0.025, 0.050, 0.075, and 0.100% (*w*/*w*) were employed to study their effects on liquefied starch hydrolysis. The hydrolyzation was carried out at 40 ◦C and a stirrer speed of 300 rpm for 24 h, as we have experimented that for this reactor a stirrer speed at 300 rpm (equivalent to the power inputs of 0.25 W/kg) gave the best results [13].

#### *2.7. Single-Batch Simultaneous Saccharification and Cultivation of the Selected Thermotolerant Yeast to Produce Cells at High-Density Concentration*

High-cell-density productions of the selected thermotolerant yeast strain were conducted in a 5-L stirred tank bioreactor (BIOSTAT B, Braun Biotech International, Germany). To evaluate the cell biomass production strategy, 50 g/L or a 100 g/L of liquefied starch was used as the carbon source for cultivation by the SSC method. The production medium composed of 3 L of liquefied starch mixed with nitrogen source and mineral salt solution was directly sterilized at 121 ◦C for 30 min. The medium was then inoculated with 10% (*v*/*v*) of inoculum from the shake flask and added with 0.1% (*w*/*w*) of StargenTM002 at the initial stage. The cultivations were conducted at 40 ◦C for 24 h. The aeration rates and agitation rates were set at 2 vvm and 636 rpm (for 50 g/L batch), and at 4 vvm and 802 rpm (for 100 g/L batch).

#### *2.8. Intensive Multiple Sequential Batch Simultaneous Saccharification and Cultivation of the Selected Thermotolerant Yeast to Produce Cells at High-Density Concentration*

The conditions for intensive multiple sequential batch cultivation were the same as those of single-batch cultivation with 0.1% (*w*/*w*) of StargenTM002. The appropriate broth replacement time point was at 12 h (the end of exponential growth phase) which was obtained from the results of single-batch simultaneous saccharification and cultivation. At the end of each cycle (12 h), a 10% volume of culture remained in bioreactor to use as the starting inoculum for the next batch cycle, and another 90% volume was removed and collected for further analysis. Then, the equal volume of fresh production medium, with the addition of StargenTM002 as above, was added in order to initiate the next batch cycle. The SSC was intensively performed for multiple-batch cycles (8 cycles) until the yeast cell density concentration decreased.

#### *2.9. Single-Step Ethanol Production to Form Simultaneous Raw Cassava Starch Hydrolysis and Fermentation*

The single-step ethanol fermentation was conducted in a 5-L stirred tank fermenter containing 4 L of the ethanol production medium containing 200 g/L of pretreated raw cassava starch. Without sterilization, during medium mixing, 0.3% (*w*/*w*) of StargenTM002 and 2.0 g/L of thermotolerant yeast inoculum were added at the initial stage. The 0.3% (*w*/*w*) of StargenTM002 was used rather than the above dosages (Section 2.6) because: (i) The use of raw starch is more difficult to be hydrolyzed; (ii) the use of 2-time starch concentration at 200 g/L needs a higher amount of the enzyme; (iii) an overdose of enzymes helps complete hydrolysis. The ethanol fermentation condition was controlled at 40 ◦C, initial pH at 4, and an agitation rate at 300 rpm for 72 h without pH control throughout the fermentation. No medium sterilization and pH control were to mimic the industrial production operation.

The overall schematic scope of the studies can be summarized: (i) Screening and isolating of thermotolerant yeast strains; (ii) selection of thermotolerant yeasts for single-step ethanol fermentation; (iii) growth kinetics study of the selected strain; (ix) optimization of enzyme StargenTM002 concentration for simultaneous saccharification and cultivation (SSC) to produce cells at a high concentration; (x) study of single-batch SSC to produce cells at a high concentration; (xi) study of intensive multiple sequential batch SSC to produce cells at a high concentration; (xii) single-step ethanol production to form simultaneous raw cassava starch hydrolysis and fermentation.

#### *2.10. Analytical Methods*

The yeast cell growth was analyzed by measuring the optical density at 660 nm with a spectrophotometer and the dry cell weight concentration. A 1.5-mL sample was centrifuged at 10,000 rpm for 10 min. The cell was washed twice with distilled water, dried at 80 ◦C for 12 h, and weighed after cooling.

The concentrations of ethanol and glucose were determined using high-performance liquid chromatography (HPLC) (KNAUER Smartline, Berlin, Germany) with a refractive index (RI) detector (KNAUER Smartline 2300, Berlin, Germany) and a Eurokat H vertex column (KNAUER, Berlin, Germany). Eluent of 0.01 N sulfuric acid at a flow rate of 0.8 mL/min was used. The analyses were performed at 60 ◦C. The samples were 10-fold diluted, filtered through 0.45 μm filter, and injected into the column with an amount of 20 μl.

#### *2.11. Statistical Analysis*

The statistical analyses were done with a one-way analysis of variance (ANOVA) and the differences of the treatment mean values from 3 replications (each experiment was done in 3 replicates) were compared with the Tukey's range test method at a *p*-value of 0.05 using Minitab version 17.

#### *2.12. Kinetic Parameters' Calculations*

The six kinetic parameters were calculated using experimental data, i.e., cultivation time, t (h), cell biomass concentration, x (g/L), ethanol product concentration, *p* (g/L), and carbon (starch) substrate used, s (g/L). (i) The specific growth rate, μ (h−1) is calculated from μ = *dlnx dt* where the differential natural log of x is divided by the time change. (ii) The productivity or production rate of cell biomass, rx (g/l/h), is from rx= *dx dt* . (iii) The productivity of ethanol product, rp (g/L/h), is from rp<sup>=</sup> *dp dt* . (iv) The cell yield coefficient, Yx/<sup>s</sup> (g/g) is from Yx/<sup>s</sup> = <sup>Δ</sup>*<sup>x</sup>* <sup>Δ</sup>*<sup>s</sup>* , where Δs is starch substrate used (g/L) and Δx is cell

produced (g/L). (v) The ethanol product yield coefficient, Yp/<sup>s</sup> (g/g), is from Yp/<sup>s</sup> <sup>=</sup> <sup>Δ</sup>*<sup>p</sup>* <sup>Δ</sup>*<sup>s</sup>* , where Δs is the starch substrate used (g/L) and Δp is the ethanol produced (g/L). (xi) The production efficiency, Ef (%), is from Ef <sup>=</sup> *Yp*/*<sup>s</sup> Yp*/*<sup>s</sup> x*100, where Yp/<sup>s</sup> is from the experiment and Y'p/<sup>s</sup> is from the theoretical yield coefficient or stoichiometry.

#### **3. Results and Discussion**

#### *3.1. Screening and Isolating of the Thermotolerant Yeast Strains*

High temperature is a key physical parameter that limits the performance of the organism in terms of ethanol production [16]. The screening of thermotolerant yeast from industrial and natural resources in tropical regions is suitable for ethanol fermentation at high temperatures [17]. In this study thermotolerant yeasts were isolated from cassava pulp and soil samples from a cassava starch factory. Based on the colony characteristics, 15 potential isolates of yeast were obtained. The ability of the strains to grow at high temperature was tested at 35, 38, 40, 42, and 45 ◦C. The results showed that the 8 dominant isolates (strains) of CP202, CP203, SS101, SS103, SS106, SS108, SS111, and SS206 grew satisfactorily at 35–45 ◦C, but the remaining 7 isolates grew only at 35–40 ◦C.

In our study, the cultivation and fermentation were done at 35–40 ◦C, which were optimum temperatures of StargenTM002 for hydrolysis of raw cassava starch [4]. However, during ethanol fermentation, yeasts faced plenty of stresses simultaneously. The effects of combined stresses (high temperature, high ethanol concentration, and low pH value) on the fermentation performance of yeast strains has received attention [17]. In addition, a high temperature of 40 ◦C with low pH values of 3.0–4.0 gave high productivities of raw cassava starch hydrolysis in single-step ethanol fermentations. Therefore, we studied the combinations of a high temperature of 40 ◦C with different low pH values of 3.0, 3.5, 4.0, 4.5, 5.0, and 5.5 on the growth performance of all the natural isolates. The results showed that only 5 isolates grew at 40 ◦C under a wide range of pH values. At pH 4.5–5.5, the similar growth performance of all isolates was observed, whereas at pH 3.0–4.0, the satisfactory growth of only the strains SS101, SS106, SS108, SS111, and SS206 was achieved.

These results clearly indicate that the yeast strains SS101, SS106, SS108, SS111, and SS206 can be tolerant to high temperatures and grow under a wide range of pH values (Figure 1). Based on the results of their growth performances, these 5 dominant strains were selected as the candidates for ethanol production at a high temperature and used for further experiments.

#### *3.2. Selection of Thermotolerant Yeasts for Ethanol Production at a High Temperature and a Low pH*

There were no significant differences between the OD660 of 40 ◦C and 42 ◦C; thus, less temperature was chosen because of three reasons: (i) Energy saving for industry; (ii) milder biochemical reaction during cell growth and product formation; and (iii) in the industry, if the set point is 40 ◦C but the actual temperature is a bit higher due to the external environment and controlled system delay, yeast still grows. In addition, the values of pH 3 and 3.5 are normally too acidic for the systems: (i) A biological system uses more acid solution for control; (ii) strong acid condition operation is difficult and dangerous to both humans and all the processing equipment, e.g., corrosion. Therefore, the combination of a temperature of 40 ◦C and a pH value of 4.0 is the appropriate optimum condition. Thus, the five yeast strains from the previous screening were selected for their fermentative abilities at a high temperature in the fermentation medium containing 200 g/L of glucose. Fermentation was conducted at 40 ◦C with a low pH of 4.0.

**Figure 1.** Effects of temperature (**a**) and pH (**b**) on cell growth (OD660) of SS101 (filled diamonds), SS106 (filled squares), SS108 (crosses), SS111 (open diamonds), and SS206 (open squares) cultivated in yeast malt (YM) medium composed of 10 g/L of glucose, shaken at 200 rpm for 24 h.

Table 1 summarizes the kinetic parameters of ethanol fermentation by the selected yeast strains under high temperature. The maximum ethanol concentration of 25.33 g/L and the yield coefficient of 0.40 g/g were obtained from strain SS106, which represented the highest production efficiency of 79.22% with the productivity of 0.53 g/L/h, while the remaining stains gave slightly lower ethanol concentrations and productivities. Based on the results of its growth performance at high temperatures and under a wide range of pH values producing the highest ethanol concentration and efficiency among the tested strains, strain SS106 showed the effectiveness of thermotolerant yeast for ethanol production at a high temperature, which can be utilized for single-step ethanol production using a combination of raw cassava starch hydrolysis and fermentation.


**Table 1.** Comparison of the kinetic parameters of selected yeast stains after 48 h of fermentation in fermentation medium composed of 200 g/L of glucose at 40 ◦C.

Statistic comparisons of those mean values within their own columns (among strains) at *p*-values of 0.05 show different characters, a, b, c, and d, which mean statically significant differences.

The strain SS106 was identified using the method of "26 rDNA sequencing and phylogenetic tree analysis" by the Thailand Institute of Scientific and Technological Research (TISTR). It was exposed to be *Kluyveromyces marxianus*. The molecular taxonomic study on the DNA sequence of the D1/D2 region in 26S rDNA proved that the sequences of strain SS106 are most similar to *K. marxianus* at level of 100%. Therefore, the strain SS106 was identified as *K. marxianus*.

Previous literature has described the ability of *K. marxianus* to grow and ferment at 40 ◦C or above [9,18], which is in good agreement with the results of our study. *K. marxianus* SS106 grows well at temperatures as high as 35–45 ◦C and it can efficiently produce ethanol at a high temperature. Furthermore, it would be advantageous to use a thermotolerant yeast strain *K. marxianus* for ethanol production by reducing the cooling cost and decreasing the risk of bacterial contamination [6,17]. Based on the results of this study and with the above advantages, it is indicated that the thermotolerant yeast *K. marxianus* SS106 shows high potential to be a candidate for feasible single-step ethanol production using a combination of raw cassava starch hydrolysis and fermentation.

#### *3.3. Growth Kinetics of K. marxianus SS106 in Shake Flask Cultivation*

Growth kinetics of *K. marxianus* SS106 in shake flask cultivation in YPD medium composed of 50 g/L of glucose, at 40 ◦C for 48 h was conducted. It was observed that the maximum cell biomass concentration produced was 15.91 g/L at a productivity of 0.66 g/L/h. The yield coefficient was 0.38 g/g with a specific growth rate of 0.07 h−<sup>1</sup> (Table 2). However, this strain did not actually grow as well as expected in the shake flask cultivation due to insufficiently dissolved oxygen that resulted in the Crabtree effect. It produced ethanol rather than cell biomass at a high concentration of glucose at the first 12 h (data not shown). This phenomenon usually occurs in aerobic cultivation in most yeasts at high glucose concentration. For aerobic cultivation, it is necessary to control dissolved oxygen concentration in the further studies in order to maintain its enough saturation with air sparging during the cultivations. This is necessary to enhance the growth of *K. marxianus* SS106.



Statistic comparisons of those values within their own columns (among culture methods) at *p*-values of 0.05 show different characters, a, b, and c, which mean statically significant differences.

#### *3.4. E*ff*ect of Enzyme StargenTM002 Concentration on Liquefied Starch Hydrolysis for SSC of K. marxianus SS106*

The liquefied starch at a concentration of 100 g/L was further saccharified (hydrolyzed) by different StargenTM002 dosages in a 10-L lysis reactor. The hydrolyzation was carried out at a stirring speed of 300 rpm and 40 ◦C for 24 h. Glucose concentrations were increased with increasing enzyme concentrations. The maximum glucose concentration was achieved with 0.10% (*w*/*w*) dosage (Figure 2). After 18 h of hydrolysis, 99.25 g/L of glucose was released from 100 g/L of liquefied starch when the highest StargenTM002 dosage of 0.10% (*w*/*w*) was employed. As it showed a complete hydrolysis, it also gave the highest productivity of 5.51 g/L/h. Therefore, this enzyme at the concentration of 0.1% (*w*/*w*) was used for further studies on batch and intensive multiple sequential batch SSC of *K. marxianus* SS106.

**Figure 2.** The effect of StargenTM002 at concentrations of 0.025% (squares), 0.050% (diamonds), 0.075% (triangles), and 0.100% (cycles) on liquefied starch hydrolysis at 40 ◦C with a stirring speed at 300 rpm for 24 h.

#### *3.5. Batch Simultaneous Saccharification and Cultivation of K. marxianus SS106 in Stirred Tank Bioreactor to Produce Cells at High-Density Concentration*

Many cultivation methods have been employed for an increase in yeast cell biomass. High-cell-density concentrations of yeast typically also used high concentrations of substrate aerobically, however, which can also be toxic growth inhibitors. To prevent the growth inhibition, liquefied starch (a glucose oligomer of DE 10–13) was used as a substrate for biomass production by the SSC method. Normally, glucose is the main substrate for yeast cells. It cannot directly be utilized by liquefied starch; therefore, an enzyme, StargenTM002, was supplementary and added into the medium with cultivation. During cultivation and yeast cell growth, liquefied starch was gradually hydrolyzed to release glucose by that enzyme and was gradually utilized by yeast cells.

The production of *K. marxianus* SS106 biomass was conducted in a 5-L stirred tank bioreactor containing the yeast production medium (composed of 50 g/L and 100 g/L of liquefied starch) and cultivated at 40 ◦C for 24 h. It can be observed that the quantities of biomass in the media using 50 g/L and 100 g/L of liquefied starch were changed in the same manner (Figure 3). The biomass concentrations were increased exponentially within the first 9 h. After that, the growths were limited and reached to the stationary phases. In contrast to the growths which were increasing from the start, glucose concentrations were slightly increased at the initial phases, after which they were rapidly decreased. These results indicated that the rates of glucose uptake by *K. marxianus* SS106 were related to the cell growths. During SSC, glucose was continuously released by StargenTM002 activities. At the lag phases, the rates of liquefied starch hydrolyzation by the enzyme were higher than those of glucose utilizations by *K. marxianus* SS106 because of low cell concentrations at these phases resulting in slightly increased concentrations of glucose in the first 3 h of cultivations. On the other hand, after 3 h, the cultivations changed to log phases. In these times, exponential growth rates were observed. The rates of liquefied starch hydrolysis were lower than those of glucose utilizations. Therefore, glucose concentrations were steadily decreased with times in these phases.

**Figure 3.** Changes in the optical density (diamonds), glucose (squares), and cell concentration (triangles) of *K. marxianus* SS106 in aerobic batch simultaneous saccharification and cultivation using (**a**) 50 g/L and (**b**) 100 g/L of liquefied starch as the substrate.

When compared with the previous experiments, it could be noticed that the growth rates of *K. marxianus* SS106 in the stirred tank bioreactor were much faster than that in the shake flask. Table 2 shows growth kinetic parameters of *K. marxianus* SS106 in the shake flask and in the bioreactors. It shows no significant difference between the cell biomass concentrations of the shake flask cultivation using glucose and the bioreactor using liquefied starch at the same concentration of 50 g/L as the carbon sources. However, the growth rates and the cell biomass production rates of *K. marxianus* SS106 in the bioreactors were greatly higher than those in shake flask cultivation. These results indicated that the use of liquefied starch as the carbon source for yeast cell cultivation in the bioreactor can achieve the effective growth.

The growth and productivity of *K. marxianus* SS106 increased due to the appropriate concentration of glucose in cultivation broth released from liquefied starch by StargenTM002 activities. This prevented the Crabtree effect that usually occurs in an aerobic cultivation at high glucose concentrations. Moreover, a sufficient oxygen concentration during cultivation also increased the growth. The bioreactor can control the dissolved oxygen concentration in cultivation broth, in order to keep enough saturation with the optimum aeration and agitation during the cultivation. Sufficient oxygen is important for cell growth. Oxygen is a primary electron acceptor in the electron transport chain and also effects yeast respiration. A high amount of dissolved oxygen from aeration results in an increase of cell biomass. In biomass production, the influence of oxygen supply on yeast growth at a steady state has been studied. Many research works have reported that the biomass concentration, yield coefficient, productivity, and substrate utilization rate were importantly increased by increasing the air supply [19,20].

Moreover, Table 2 also shows that there are increases of cell biomass and the production rate when increasing the liquefied starch at a concentration of 100 g/L. However, there is no significant difference between the specific growth rate of *K. marxianus* SS106 cultivated with 50 g/L of liquefied starch and that of 100 g/L. This result suggests that the increasing liquefied starch concentration improves the cell biomass, yield coefficient, and productivity of *K. marxianus* SS106. Therefore, the cell biomass of *K. marxianus* SS106 using 100 g/L of liquefied starch as the carbon source can be effectively produced by the SSC process.

#### *3.6. Intensive Multiple Sequential Batch Simultaneous Saccharification and Cultivation of K. marxianus SS106 in Stirred Tank Bioreactor to Produce Cells at High-Density Concentration*

High-cell-density cultivations are designed to achieve high product concentrations in broth by growing cells to high densities while maintaining high specific cell productivity. As a result, high-density cultivation has become an important tool in modern bioprocessing. It has been achieved with *Kluyveromyces marxianus*-improved ethanol accumulation using fed-batch technology [21].

Thus, to achieve high-cell density concentration, long-term stability and performance of simultaneous saccharification and cultivation of *K. marxianus* SS106 in the aerobic stirred tank bioreactor were carefully studied using the intensive multiple sequential batch technique. This method was performed by replacing the mature yeast culture broth with fresh medium. It can essentially promote cell biomass productivity and its growth rate as it reduces the time for growth of seed culture, inoculation, cleaning, sterilization, and other operations of the bioreactor, and avoids cessation of the process between each batch. The results obtained from eight continual cycles of intensive multiple sequential batches are presented in Figure 4 and Table 3. Each batch cycle employed in this experiment was completed after 12 h of cultivation, for a total of 96 h after eight batch cycles.

**Figure 4.** Changes in the optical density (**a**), glucose (**b**), and dry cell concentration (**c**) of *K. marxianus* SS106 in aerobically intensive multiple sequential batch simultaneous saccharification and cultivation using 100 g/L of liquefied starch as the substrate.

A similar trend of a decrease in the glucose concentration and subsequent increase in cell biomass production over the eight cycles of the intensive multiple sequential batch is shown in Figure 4. *K. marxianus* SS106 was, importantly, capable of continuously producing cell biomass for up to eight cycles through intensive multiple sequential batch cultivation. The adaptations of *K. marxianus* SS106 to their growth conditions were observed at the first cycle. It adapted to the new condition and medium. After that, the growth was able to stabilize, and the cell biomass kept producing until the finishing of every cycle.


**Table 3.** Kinetic parameters of *K. marxianus* SS106 cell biomass production undergoing intensive multiple sequential batch simultaneous saccharification and cultivation in an aerobic bioreactor.

Statistic comparisons of those values within their own columns (among batch cycles) at *p*-values of 0.05 show different characters, a, b, c, d, <sup>e</sup> and <sup>f</sup> , which mean statistically significant differences.

Table 3 shows the kinetic parameters of *K. marxianus* SS106 undergoing intensive multiple sequential batch SSC in an aerobic bioreactor. *K. marxianus* SS106 has shown its ability to undergo continual sequential batch run. The eight cycles could be operated by the intensive multiple sequential batch SSC method. During the intensive multiple sequential batch SSC, biomass production started to increase at the first cycle. Afterwards, growth was the highest at the end of third cycle and later the cell biomass slowly declined and subsequently remained nearly constant after the sixth cycle. The consistent cell biomass of 32.07–45.82 g/L with the specific growth rate of 0.19–0.44 h−<sup>1</sup> and productivity of 2.67–3.82 g/L/h was obtained at the end of each cycle. During intensive multiple sequential batch SSC, cell biomass and productivity were continuously increased in the first three cycles. The highest cell biomass of 45.82 g/L and productivity of 3.82 g/L/h were clearly achieved at the end of the third cycle. No significant differences were observed (*p* < 0.05) in the values between the first and the sixth cycle, whereas low values occurred after the sixth cycle. Cell biomass and productivity after the sixth cycle were less than in the first cycle. The first and the second cycles were the climbing phases, the third was the peak, after that, they were slightly declining with more cycles and longer times. This is because the age (phase) of cells affects cell strength, growth, and yield. However, the results indicated that *K. marxianus* SS106 could tolerate the repeated use. Six cycles could be cultivated in the bioreactor from a total of eight cycles. For the averages of six cycles, a biomass of 39.73 g/L with a specific growth rate at 0.36 h−<sup>1</sup> and a productivity of 3.31 g/L/h were achieved. This was essentially very high, and much higher when compared to those values of other research works, although some groups operated with fed-batch cultivation mode [22].

#### *3.7. Single-Step Ethanol Production From Simultaneous Raw Cassava Starch Hydrolysis and Fermentation*

Single-step ethanol production from especially simultaneous raw cassava starch hydrolysis and fermentation was demonstrated at 40 ◦C in a stirred tank fermenter containing ethanol production medium. After the additions of enzyme StargenTM002 and inoculum, the ethanol fermentation was performed at an agitation speed of 300 rpm for 72 h. It was observed that *K. marxianus* SS106 produced ethanol at a final concentration of 7.91% (*v*/*v*) with a productivity of 0.86 g/L/h (Figure 5). However, the fermentation completed by 48 h indicated that though it was using raw starch, the production time was still normal, as compared to general production in the industry using sugar as the raw material. The ethanol production result by this thermotolerant yeast strain was similar to that of Limtong et al. [5], who studied ethanol production at 37 ◦C in a 5-L jar fermenter at an agitation speed of 300 rpm and an aeration rate of 0.02 vvm. They found that *K. marxianus* DMKU 3–1042 yielded a final ethanol concentration of 8.15% (*v*/*v*) with a productivity of 1.3 g/L/h. In addition, here, it was interesting to

note that, except glycerol, the other by-products such as lactic acid and acetic acid were not produced when ethanol was produced at this high temperature by single-step fermentation of raw cassava starch with *K. marxianus* SS106 (data not shown). The SSF (simultaneous saccharification and fermentation) process using starch substrates is more promising, and commercial industrial production is also feasible in many countries. The advantages of the process are reduction in investment by having a single fermenter for both saccharification and fermentation. The feedback inhibition of sugars is greatly reduced. The fermentation time is very reduced in the SSF process [23].

**Figure 5.** The yield of ethanol production by *K. marxianus* SS106 at 40 ◦C in 5-L fermenter using single-step ethanol fermentation. (Comparison of those values among fermentation times at *p*-value 0.05 shows different characters, a, b and c, which are statically significant difference.).

#### **4. Conclusions**

It is clear that the new isolated strain *K. marxianus* SS106 is a suitable potential strain that could be employed for single-step ethanol production using a combination of simultaneous raw cassava starch hydrolysis and fermentation. This new thermotolerant yeast strain can significantly tolerate high temperatures up to 42 ◦C and grows well under a wide range of pH values. For high-cell-density biomass production of *K. marxianus* SS106 in the stirred tank bioreactor, the simultaneous saccharification and aerobic cultivation using 100 g/L of liquefied starch as the substrate is an effective method. The yeast cell biomass could be produced at a concentration of 39.30 g/L with a productivity of 3.28 g/L/h and a specific growth rate of 0.49 h−1. These values are very high and higher than those of other research works. Furthermore, intensive multiple sequential batch simultaneous saccharification and cultivation also shows excellent high-cell-density production. It produced the maximum yeast cell biomass at a concentration of 45.82 g/L with a productivity of 3.82 g/L/h and a specific growth rate of 0.44 h<sup>−</sup>1. This method gave a high concentration of cell biomass and growth.

Again, we concluded that the advantages of this research work are as follows. (i) *K. marxianus* SS106 is the new potential industrial yeast strain. (ii) It is thermotolerant to high temperatures and low pH values. (iii) It can grow very well in both types of carbon source, i.e., liquefied starch (dextrin) and raw starch. (iv) It grows both aerobically to produce cell biomass used as an inoculum or other purposes, and anaerobically to produce ethanol, moreover, in single-step operation without acid by-products. (v) It can grow in several continual batch runs. (vi) It grows at a high rate, with high-cell

concentration, high productivity, and high efficiency, and (vii) this minimizes process steps of operation, cost, and time. (viii) It can be scaled-up to the industry.

**Author Contributions:** Conceptualization, K.M. and M.K.; methodology, investigation, analysis and writing—original draft preparation, R.R.; resources and data curation, S.C.; visualization and supervision S.C. All authors have read and agreed to the published version of the manuscript.

**Funding:** A research grant was from The Office of the Higher Education Commission. This work was also supported by the Biochemical Engineering Pilot Plant, Biological Science Graduate Program, and Department of Biology, Faculty of Science, Burapha University, Chonburi, Thailand.

**Acknowledgments:** The authors would like to sincerely thank Chorchiwat Industry Co., Ltd. who supported raw materials, some experiments, and analytical instruments for this study.

**Conflicts of Interest:** The authors declare no conflicts of interest. The funder had no role in the design of this study, analyses, or interpretation of data; in the writing of the manuscript; or in the decision to publish the experimental results.

#### **References**


© 2020 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).

## *Article* **Microbial Communities, Metabolites, Fermentation Quality and Aerobic Stability of Whole-Plant Corn Silage Collected from Family Farms in Desert Steppe of North China**

**Chao Wang 1, Lin Sun 1, Haiwen Xu 2, Na Na 1, Guomei Yin 1, Sibo Liu 1, Yun Jiang 1,3 and Yanlin Xue 1,\***


**Abstract:** Whole-plant corn silages on family farms were sampled in Erdos (S1), Baotou (S2), Ulanqab (S3), and Hohhot (S4) in North China, after 300 d of ensiling. The microbial communities, metabolites, and aerobic stability were assessed. *Lactobacillus buchneri*, *Acinetobacter johnsonii*, and unclassified *Novosphingobium* were present at greater abundances than others in S2 with greater bacterial diversity and metabolites. *Lactobacillus buchneri*, *Lactobacillus parafarraginis*, *Lactobacillus kefiri*, and unclassified *Lactobacillus* accounted for 84.5%, and 88.2%, and 98.3% of bacteria in S1, S3, and S4, respectively. The aerobic stability and fungal diversity were greater in S1 and S4 with greater abundances of unclassified *Kazachstania*, *Kazachstania bulderi*, *Candida xylopsoci*, unclassified *Cladosporium*, *Rhizopus microspores*, and *Candida glabrata* than other fungi. The abundances of unclassified *Kazachstania* in S2 and *K. bulderi* in S3 were 96.2% and 93.6%, respectively. The main bacterial species in S2 were *L. buchneri*, *A. johnsonii*, and unclassified *Novosphingobium*; *Lactobacillus* sp. dominated bacterial communities in S1, S3, and S4. The main fungal species in S1 and S4 were unclassified *Kazachstania*, *K. bulderi*, *C. xylopsoci*, unclassified *Cladosporium*, *R. microspores*, and *C. glabrata*; *Kazachstania* sp. dominated fungal communities in S2 and S3. The high bacterial diversity aided the accumulation of metabolites, and the broad fungal diversity improved the aerobic stability.

**Keywords:** whole-plant corn silage; bacterial community; fungal community; metabolites; fermentation quality; aerobic stability

#### **1. Introduction**

Family farms, as new agricultural business entities, partake in more commercially oriented agricultural production and management than their forerunners ("farming households") in China, even though their main labour force still consists of family members, and the major source of their income remains agricultural work [1]. Family farms are the main mode of management in the Inner Mongolian pastoral area of North China [2]. Whole-plant corn silage, alfalfa hay, grass hay, crop straw, and natural grass are the major forages of family farms in the desert steppe of Inner Mongolia. In general, these farmers ensile whole-plant corn without any additives to save processing costs [3]. Moreover, the microbial communities present in this form of whole-plant corn silage are still unclear, and understanding them is critical to explaining the fermentation quality and aerobic stability of such silage.

In the past decade, the development of next-generation sequencing technologies has helped to improve our understanding of the microbial communities present in silage [4]. *Lactobacillus* dominates the bacterial succession and determines the fermentation quality

**Citation:** Wang, C.; Sun, L.; Xu, H.; Na, N.; Yin, G.; Liu, S.; Jiang, Y.; Xue, Y. Microbial Communities, Metabolites, Fermentation Quality and Aerobic Stability of Whole-Plant Corn Silage Collected from Family Farms in Desert Steppe of North China. *Processes* **2021**, *9*, 784. https:// doi.org/10.3390/pr9050784

Academic Editor: Maria Tufariello

Received: 6 April 2021 Accepted: 27 April 2021 Published: 29 April 2021

**Publisher's Note:** MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations.

**Copyright:** © 2021 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https:// creativecommons.org/licenses/by/ 4.0/).

of whole-plant corn silage during fermentation process [5,6]. The main bacterial species present in the silage at the end of the process are *Lactobacillus acetotolerans*, *Lactobacillus silagei*, *Lactobacillus parafarraginis*, *Lactobacillus buchneri*, and *Lactobacillus odoratitofui* [7]. The geographical location where at the corn was grown influences the bacterial succession process taking place in whole-plant corn silage and the bacterial community in the final silage [8,9]. Drouin et al. [10] reported that ensiling whole-plant corn with lactic acid bacteria (LAB) increases the Shannon indexes of bacterial and fungal communities and modifies the aerobic stability, and *Saccharomyces*, *Issatchenkia*, and *Kazachstania* cause aerobic deterioration during aerobic exposure. Nevertheless, the effect of the geographical location on the fungal community and the aerobic stability of whole-plant corn silage has not yet been reported on.

Recently, the silage metabolome has attracted new interest [11]. Some studies have reported the effect of inoculating on the metabolite contents of whole-plant corn silage, alfalfa silage, and sainfoin silage with LAB [6,9,12]; the dynamics of metabolites in whole-plant corn silages during fermentation process [6]; and the correlation of the main metabolites with the main bacterial species and fermentation quality in whole-plant corn silages [6]. Additionally, Wu et al. [13] analysed the metabolic profiles of high-moisture sweetcorn kernel silages. Biogenic amines—a class of metabolites in silage—affect the palatability of silages, and the feed intake and performance of ruminants [14]. However, the concentration and composition of the metabolites—especially the biogenic amines in silages on the desert steppe—remain unclear.

In the present study, whole-plant corn silages on family farms in the desert steppe of Inner Mongolia in North China were assessed after about 300 d of ensiling. The hypothesis of the present study was the differences in microbial communities, metabolites, and aerobic stability between whole-plant corn silages from different areas. The objective was to analyse the bacterial and fungal communities, the metabolites, the fermentation quality and the aerobic stability of whole-plant corn silages.

#### **2. Materials and Methods**

#### *2.1. Sampling*

The corn (*Zea mays* L.) used for ensiling came from replicates grown on 3 family farms of each sampling area (silage 1 (S1), Angsu Town, Erdos City, 108◦4 29.093 E, 38◦14 24.212 N, 1378 m; S2, Bayinhua Town, Baotou City, 109◦54 15.260 E, 42◦16 34.133 N, 1251 m; S3, Jiang'an Town, Ulanqab City, 110◦51 14.249 E, 43◦10 06.845 N, 1077 m; S4, Chengguan Town, Hohhot City, 111◦39 31.784 E, 39◦55 19.160 N, 1137 m) in Inner Mongolia (desert steppe), North China (Figure 1). The variety of corn used was 23 Yu (No, 2008022, corn hybrid, Henan Dajingjiu Seed Industry Co., Ltd., Shangqiu, China). The corn plants were harvested at the 2/3, 1/3, 1/3, and 1/2 milk-line stages in Erdos (on 15 September 2018), Baotou (on 1 September 2018), Ulanqab (on 4 September 2018), and Hohhot (on 8 September 2018), respectively according to local tradition, and chopped into 1–2 cm pieces by combine-harvester (John Deere (China) Investment Co., Ltd., Beijing, China). The chopped forages on each family farm were ensiled in a silo (length, 100 m; width, 10 m; height, 2 m) without any additives at a density of more than 700 kg/m3. The samples of chopped forage were taken at filling to the 1/3, 1/2, and 2/3 of the length of the silo, respectively, and transported in ice boxes to the laboratory for analysis. After 30 d of ensiling, the silos were opened, and the silages were collected (around 30 cm thickness, from the front phase of the silo) for animal feeding on every morning. At about 300 d, the silages were sampled after the animals were fed. Subsamples were collected at 5 points along the face of a silo from each family farm: point 1, 1 m from the right wall, top film; point 2, 1 m from the left wall, top film; point 3, 1 m from the right wall, bottom; point 4, 1 m from the left wall, bottom; point 5, the centre of the silo's face. The subsamples (5 kg) were collected with a needle forage sampler about 30 cm long and uniformly mixed as a composite sample. The samples were transported in ice boxes to the laboratory for analysis.

**Figure 1.** Map of sampling locations.

#### *2.2. Analyses*

The silage from each silo was randomly divided into 4 batches (4 kg each). Every batch from each silo was placed into a separate plastic drum (diameter, 40 cm; height, 50 cm), and the tops of the drums were covered with 2 layers of cheesecloth. One batch from each silo was used for assessing the aerobic stability, which was measured with a temperature recorder (SMOWO Multi-Channel Data Logger, MDL-1048A; Shanghai Tianhe Automation Instrument Co., Ltd., Shanghai, China) via the method of Wang et al. [15]. The recorder's temperature sensor probe was placed into the centre of the silage in the drum. The temperatures of room and silage were recorded every hour. One of the three batches from each silo was randomly selected at 0, 2, and 5 d for assessment of microbial counts and fermentation quality; the silages were assessed at 0 d for microbial communities and metabolites.

Extracts of forage or silage were prepared by homogenizing 20 g of chopped forage or silage with 180 mL of sterile water for 100 s using a flap-sterile homogenizer (LW-09, Shanghai Jingxin Industrial Development Co., Ltd., Shanghai, China) and then filtering through 2 layers of cheesecloth according to the methods of Owens et al. [16]. The pH of the extracts was detected with a pH meter (PB-10, Sartorius, Gottingen, Germany). Counts of LAB, *Escherichia coli*, bacteria, and yeast/moulds were taken by culturing on De Man Rogosa Sharpe agar, violet-red bile agar, nutrient agar, and potato dextrose agar, respectively, at 37 ◦C for 48 h in an incubator (LRH-70, Shanghai Yiheng Science Instruments Co., Ltd., Shanghai, China) [17]. Water-soluble carbohydrates (WSC) were measured via anthrone–sulfuric acid colorimetry using a spectrophotometer (Genesys 10; Thermo Fisher Scientific, Waltham, MA, USA) at 620 nm.

The organic acids (lactic acid, acetic acid, propionic acid, and butyric acid) in the silages were assessed using high-performance liquid chromatography (DAD, 210 nm, SPD-20A, Shimadzu Co., Ltd., Kyoto, Japan) (detector, SPD-20A diode array detector (210 nm); column, Shodex RS Pak KC-811 (50 ◦C, Showa Denko K.K., Kawasaki, Japan); mobile phase, 3 mM HClO4 (1.0 mL/min)) [18]. The ammonia nitrogen content was determined via the Kjeldahl method using an autoanalyzer (Kjeltec 8400; FOSS Co., Ltd., Hillerød, Denmark).

The chopped forages or silages were dried using a forced-air oven (BPG-9240A, Shanghai Yiheng Scientific Instrument Co., Ltd., Shanghai, China) operated at 65 ◦C for

48 h, ground through a 1 mm screen with a mill (FS-6D; Fichi Machinery Equipment Co., Ltd., Jinan, Shandong, China), and then dried at 105 ◦C, until reaching a constant mass suitable for measuring dry matter (DM) content. The total nitrogen (TN) was assessed via the Kjeldahl method using an autoanalyzer with copper as the catalyst, and the crude protein (CP) concentration was calculated by multiplying the TN concentration by 6.25. The neutral detergent fibre (NDF) and acid detergent fibre (ADF) contents were determined via the method of Van Soest et al. [19] using an Ankom fiber analyzer (2000, Ankom, Macedon, NY, USA) without heat-stable amylase; acid detergent lignin (ADL) content was determined using a 72% H2SO4 solution [19].

The total bacterial DNA and fungal DNA were extracted using a DNA isolation kit (OMEGA-D4015-04) following the manufacturer's specifications. The DNA quality was evaluated via 1% (*w*/*v*) agarose gel electrophoresis. The full-length 16S rRNA gene was amplified via PCR using forward primer 5 -TAGRGTTYGATYMTGGCTCAG-3 and reverse primer 5 -RGYTACCTTGTTACGACTT-3 ; the full-length internal transcribed spacer (ITS) gene was amplified via PCR using forward primer 5 -TCCGTAGGTGAACCTGCGG-3 and reverse primer 5 -TCCTCCGCTTATTGATATGC-3 . The amplification conditions were as follows: 95 ◦C for 3 min; 25 cycles of 98 ◦C for 20 s, 57 ◦C for 30 s and 72 ◦C for 90 s; a final extension of 72 ◦C for 2 min. The 16S rRNA and ITS libraries were built with a Pacific Biosciences Template Prep Kit (Pacific Biosciences, Menlo Park, CA, USA). Amplicon sequencing was performed with a PacBio Sequel instrument (Pacific Biosciences). Raw circular consensus sequencing (CCS) reads were obtain using PacBio SMRT Link CCS software. The sequence data reported in this study have been submitted to the NCBI Sequence Read Archive database under the accession number PRJNA650284.

The silage extracts were prepared as follows: 5 g silage and 10 mL extraction liquid (70% methanol) were vortexed for 30 s, oscillated for 1 h at 4 ◦C, filtered through a 0.22 μm membrane, and then dried to 1 mL with a vacuum concentrator in a glass vial [20]. The metabolites in the silage were analysed via liquid chromatography–electrospray ionization– tandem mass spectrometry (HPLC, Shim-pack UFLC Shimadzu CBM30A system; MS, Applied Biosystems 4500 QTRAP system) using measured silage extracts. The conditions of analysis were as follows: HPLC column, Waters ACQUITY UPLC HSS T3 C18 (1.8 μm, 2.1 mm × 100 mm); mobile phase, water (0.04% acetic acid)/acetonitrile (0.04% acetic acid); gradient program, 100:0 (*v*:*v*) at 0 min, 5:95 at 11.0 min, 5:95 at 12.0 min, 95:5 at 12.1 min, and 95:5 at 15.0 min; flow rate, 0.40 mL/min; temperature, 40 ◦C; injection volume, 5 μL [7]. The effluent was then connected to an ESI triple-quadrupole linear ion trap (QqQ-LIT) mass spectrometer [7]. The qualitative and quantitative analyses, the pre-processing and the determination of the relative concentrations of metabolites were all undertaken according to Yan et al. [20] and Xu et al. [6]. Biogenic amines (tyramine, putrescine, phenylethylamine, spermidine, and noradrenaline) were selected from the metabolites, and their relative concentrations were recorded.

#### *2.3. Statistical Analyses*

The data of fermentation quality and microbial count were analysed via a 4 × 3 factorial design. The model included 4 sampling areas and 3 aerobic exposure times, and their interaction. Using one-factor analysis of variance via the general linear model (GLM) of SAS (SAS System for Windows, version 9.1.3; SAS Institute Inc., Cary, NC, USA), we analysed the differences in the pH, microbial counts, and nutritional composition of fresh forage from 4 sampling areas, in the fermentation quality and microbial counts of silage among 4 sampling areas and 3 aerobic exposure times, and in the sequencing data, alpha diversity, nutritional composition, total metabolites, and biogenic amines of silage from 4 sampling areas. The interaction between the sampling area and aerobic exposure time was analysed using the PDIFF procedure of SAS. The differences were compared via least significant differences, and significance was declared at *p* ≤ 0.05. The principal coordinates analysis (PCoA) of microbial beta diversity was performed using R 1.7.13 for Windows; the principal component analysis (PCA) of the metabolic profiles was performed using R 3.5.1.

#### **3. Results**

*3.1. Characteristics of Whole-Plant Corns before Ensiling*

The S1 and S4 had higher LAB counts than S2 and S3 (*p* < 0.05). The S2 and S3 displayed lower DM contents and greater WSC concentrations than S1 and S4 (*p* < 0.05), and S1 showed greater DM than S4 (*p* < 0.05). The S2 had the greatest level of CP, S4 contained the most NDF and ADF, and S3 had the lowest contents of ADF and ADL (*p* < 0.05) (Table 1).

**Table 1.** pH, microbial counts (log10 CFU/g fresh weight), dry matter content (DM, g/kg), and chemical component concentrations (g/kg DM) of whole-plant corn before ensiling (n = 3).


S1, fresh corn collected from Erdos; S2, fresh corn collected from Baotou; S3, fresh corn collected from Ulanqab; S4, fresh corn collected from Hohhot. SEM, standard error of the mean. Values with different lowercase letters (a, b, and c) indicate there was a significant difference among silages.

#### *3.2. Microbial Counts and Diversity*

At 0 d of aerobic exposure, S1 and S4 showed greater LAB and yeast counts than S2 and S3 (*p* < 0.05), and S1 had a greater bacterial count than other silages (*p* < 0.05); additionally, S3 contained more LAB and yeast than S2, and fewer bacteria than S2 and S4 (*p* < 0.05) (Table 2). During aerobic exposure, the LAB counts in S2 and S3 increased (*p* < 0.05), and the bacteria and yeast counts in S1 dropped (*p* < 0.05). The bacteria count decreased at 2 d and increased at 5 d in S2 (*p* < 0.05), while it increased at 2 d and decreased at 5 d in S3 and S4 (*p* < 0.05). The aerobic exposure time affected the LAB and bacteria counts (*p* < 0.05). The sampling area influenced the counts of LAB, bacteria, and yeast (*p* < 0.05), on which the aerobic exposure time and the sampling area had a compound effect (*p* < 0.05). *Escherichia coli* and moulds were not detected in all the silages.

Totals of 166,552 and 141,221 clean reads of the full-length 16S rRNA and ITS genes, respectively, were obtained from 12 samples of whole-plant corn silage according to SMRT sequencing. The S4 had a greater number of 16S rRNA gene reads than S1 (*p* < 0.05), and these silages contained more than 10,000 clean reads. There were no differences in the numbers of clean reads of the ITS gene among the silages (*p* > 0.05), more than 10,000 clean reads were derived for each, except for S1 (9250). In terms of bacteria, S2 showed the highest Shannon and Simpson indexes among the silages, and it also had a higher Chao1 index and number of observed species than S4 (*p* < 0.05). As regards fungi, the numbers of observed species and the indexes of Shannon, Simpson and Chao1 indexes in S1 and S4 were higher than those in S2 and S3 (*p* < 0.05) (Table 3). According to PCoA, the bacterial communities in all the silages were clearly distinct from one another; however, the fungal communities in S1 and S4 were distinct from those in S2 and S3 (Figure 2).


**Table 2.** Microbial counts (log10 CFU/g fresh weight) of whole-plant corn silages during aerobic exposure (n = 3).

S1, silage collected from Erdos; S2, silage collected from Baotou; S3, silage collected from Ulanqab; S4, silage collected from Hohhot. SEM, standard error of the mean. Values with different lowercase letters (a, b, c, and d) indicate there was a significant difference among silages on the same day. Values with different uppercase letters (A, B, and C) indicate there were significant differences between sampling times. A, sampling area; D, aerobic exposure time (d). \*\*\*, *p* < 0.001.

**Table 3.** Sequencing data and alpha diversity of bacteria and fungi in whole-plant corn silage (n = 3).


S1, silage collected from Erdos; S2, silage collected from Baotou; S3, silage collected from Ulanqab; S4, silage collected from Hohhot. SEM, standard error of the mean. Values with different lowercase letters (a, b, c, and d) indicate there was a significant difference among silages.

#### *3.3. Bacterial Community*

*Lactobacillus* dominated the bacterial communities in S1, S3, and S4 with abundances of 86.74%, 88.69%, and 98.49%, respectively. The main bacterial genera in S2 were *Lactobacillus* (28.70%), *Acinetobacter* (20.40%), *Novosphingobium* (7.80%), and *Afipia* (5.37%) (Figure 3a). The main bacterial species in S1, S3, and S4 were *L. buchneri* (52.74%, 65.79%, and 45.92%, respectively), *L. parafarraginis* (17.09%, 0.64%, and 40.06%, respectively), *Lactobacillus kefiri* (3.58%, 17.14%, and 0%, respectively) and unclassified *Lactobacillus* (11.05%, 4.68%, and 12.36%, respectively). The dominant bacterial species in S2 were *L. buchneri* (20.71%), *Acinetobacter johnsonii* (10.73%), unclassified *Novosphingobium* (7.64%), and *L. parafarraginis* (3.19%) (Figure 3b).

**Figure 2.** Non-metric multi-dimensional scaling based on Bray-Curtis assessment of bacterial (**a**) and fungal (**b**) diversities in whole-plant corn silages (n = 3). S1, silage collected from Erdos; S2, silage collected from Baotou; S3, silage collected from Ulanqab; S4, silage collected from Hohhot.

**Figure 3.** Relative abundances of bacterial genera (**a**) and species (**b**) in whole-plant corn silage (n = 3). S1, silage collected frm Erdos; S2, silage collected from Baotou; S3, silage collected from Ulanqab; S4, silage collected from Hohhot.

#### *3.4. Fungal Community*

The dominant fungal genus in S2 and S3 was *Kazachstania* with abundances of 97.32% and 98.24%, respectively; *Kazachstania* (54.86%) was also dominant in S4, followed by *Candida* (16.28%), *Rhizomucor* (10.56%), and *Cladosporium* (6.15%). The main fungal genera in S1 were *Candida* (42.73%), *Kazachstania* (19.34%), *Cladosporium* (13.90%), and *Rhizopus* (8.52%) (Figure 4a). The main fungal species in S1 and S4 were unclassified *Kazachstania* (15.84% and 18.72%, respectively), *Kazachstania bulderi* (3.13% and 35.53%, respectively), *Candida xylopsoci* (31.19% and 9.64%, respectively), unclassified *Cladosporium* (13.79% and 6.14%, respectively), *Rhizopus microsporus* (7.54% and 9.60%, respectively), and *Candida glabrata* (7.03% and 5.25%, respectively). The dominant fungal species in S2 was unclassified *Kazachstania* (96.21%), while *Kazachstania bulderi* (93.61%) dominated in S3 (Figure 4b).

**Figure 4.** Relative abundances of fungal genera (**a**) and species (**b**) in whole-plant corn silage (n = 3). S1, silage collected from Erdos; S2, silage collected from Baotou; S3, silage collected from Ulanqab; S4, silage collected from Hohhot.

#### *3.5. Metabolites*

The silages collected from different sites (Erdos, Baotou, Ulanqab, and Hohhot) were clearly separated by PC1 and PC2 with 31% and 17% variation, respectively according to principal component analysis (Figure 5). A total of 668 substances were detected in 12 samples of whole-plant corn silages, which 292 substances were identified (Supplementary Table S1). The S2 had greater relative concentrations of total metabolites than other silages (*p* < 0.05) (Table 4). Five biogenic amines were detected in the whole-plant corn silages. The S2 showed the greatest abundances of phenylethylamine and spermidine among the silages (*p* < 0.05) (Table 4).

**Figure 5.** Principal component analysis of the metabolites in whole-plant corn silages (n = 3). S1, silage collected from Erdos; S2, silage collected from Baotou; S3, silage collected from Ulanqab; S4, silage collected from Hohhot.

**Table 4.** Relative concentrations of total metabolites and biogenic amines in whole-plant corn silage (n = 3).


S1, silage collected from Erdos; S2, silage collected from Baotou; S3, silage collected from Ulanqab; S4, silage collected from Hohhot. SEM, standard error of the mean. The relative concentration of major metabolites was <0.001 and >0. Values with different lowercase letters (a and b) indicate there was a significant difference among silages.

#### *3.6. Fermentation Quality and Chemistry Composition*

At 0 d of aerobic exposure, S1 and S4 displayed higher pH and acetic acid, but lower lactic acid, than S2 and S3 (*p* < 0.05); S1 contained more lactic acid and less acetic acid than S4 (*p* < 0.05). The S3 contained less ammonia nitrogen than other silages (*p* < 0.05), and S1 and S2 contained less than S4 (*p* < 0.05). Propionic and butyric acids were not detected in the silages at 0 d of aerobic exposure (Table 5). The contents of lactic acid and ammonia nitrogen (except for in S4) decreased (*p* < 0.05) by aerobic exposure, but pH increased (*p* < 0.05) except for in S1. The acetic acid in S2 and S4 decreased (*p* < 0.05), while it decreased in S3 at 2 d and then increased at 5 d (*p* < 0.05). The aerobic exposure time and sampling area had single and interactive effects on the pH and the contents of lactic acid, acetic acid, propionic acid, and ammonia nitrogen in the silages (*p* < 0.05) (Table 5).

The DM content in S1 was higher than that in other silages (*p* < 0.05). S2 and S3 had greater CP than S1 and S4, with S1 showing higher than S4 (*p* < 0.05). The NDF concentration in S4 was greater than that in other silages (*p* < 0.05) (Table 6).


**Table 5.** pH, organic acid contents (g/kg dry matter) and ammonia nitrogen contents (g/kg total nitrogen) of whole-plant corn silages during aerobic exposure (n = 3).

S1, silage collected from Erdos; S2, silage collected from Baotou; S3, silage collected from Ulanqab; S4, silage collected from Hohhot. SEM, standard error of the mean. Values with different lowercase letters (a, b, c, and d) indicate there was a significant difference among silages on the same day. Values with different uppercase letters (A, B, and C) indicate there were significant differences among sampling times. A, sampling areas; D, aerobic exposure time (d). \*\*\*, *p* < 0.001. ND, no detected.



S1, silage collected from Erdos; S2, silage collected from Baotou; S3, silage collected from Ulanqab; S4, silage collected from Hohhot. SEM, standard error of the mean. Values with different lowercase letters (a, b, and c) indicate there was a significant difference among silages.

#### *3.7. Aerobic Stability*

The temperatures of S1 and S4 did not exceed 2 ◦C above ambient temperature for 5 days after opening. The temperatures of S2 and S3 exceeded 2 ◦C above ambient temperature at 53 h and 39 h, respectively (Figure 6).

**Figure 6.** Temperature dynamics of silage reaching above-ambient temperature during aerobic exposure (n = 3). S1, silage collected from Erdos; S2, silage collected from Baotou; S3, silage collected from Ulanqab; S4, silage collected from Hohhot.

#### **4. Discussion**

In the present study, the materials displayed sufficient LAB counts (>5 log10 CFU/g FW) and WSC concentrations (>97 g/kg DM) (Table 1), resulting in a satisfactory fermentation quality for the whole-plant corn silages (Table 5). Before ensiling, S2 and S3 contained greater LAB and WSC contents and a lower DM content than S1 and S4 preensiling (Table 1), indicating the conditions of the former two were more conducive to LAB fermentation during the ensiling process. This contributed to the lower pH and higher lactic acid contents in S2 and S3 (Table 5).

As the microbial community composition plays a crucial role in the fermentation quality and aerobic stability of silage, it is necessary to assess the bacterial and fungal communities in order to explain the different fermentation quality and aerobic stability among silages. In the present study, *Lactobacillus* was the most dominant bacterial genus in all silages, followed by *Acinetobacter* in S1 and S3, and by *Acinetobacter*, *Novosphingobium*, *Afipia*, *Clostridium*, and unclassified *Actinobacteria* in S2 (Figure 3a). This indicated that *Lactobacillus* is generally the dominant bacterial genus in whole-plant corn silages after ensiling for about 300 d. Moreover, previous studies also reported *Lactobacillus* at the greatest abundance in whole-plant corn silages collected from five regions in Southwest China [9] and three sites in Iran [8]. In silage with a good fermentation quality, the bacterial community is dominated by *Lactobacillus* [21], explaining the satisfactory fermentation quality of whole-plant corn silages in our study. *Acinetobacter* was found in sugarcane top silage [22], and *Novosphingobium* was detected in whole-plant corn silage [23] and red clover silage [24]. However, the effect of these genera to fermentation quality and aerobic stability are not clear and require further research.

In the present study, the main bacterial species in S2 were *L. buchneri*, *Acinetobacter johnsonii*, and unclassified *Novosphingobium* with abundances of 20.7%, 10.7% and 7.64%, respectively (Figure 3b). *Lactobacillus buchneri*, *L. parafarraginis*, *L. kefiri*, and unclassified *Lactobacillus* dominated the bacterial communities in S1, S3, and S4 with total abundances of 84.5%, 88.2%, and 98.3%, respectively (Figure 3b). The main LAB species in the silages after ensiling for about 300 d were *L. buchneri*, *L. parafarraginis*, *L. kefiri*, and *L. diolivorans* (Figure 3b), which belong to *L. buchneri* group as the sole heterofermentative LAB [25]. However, in previous studies, the main LAB species were *L. acetotolerans*, *L. silagei*, *L. buchneri*, *L. odoratitofui*, *L. farciminis*, and *L. parafarraginis* in whole-plant corn silages (90 d) with low pH (from 3.68 to 3.74) [7], *L. plantarum*, *L. buchneri*, and *L. brevisi* in alfalfa silage (90 d) with high pH (from 4.9 to 5.2) [26], *L. plantarum*, *L. hammesi*, *L. brevisi*, *L. coryniformis*, and *L. piscium* in Italian ryegrass silages (42 d) with pH ranging from 4.40 to 5.52 [10].

These studies suggested that homofermentative LAB co-existed with heterofermentative LAB in short silage (42–90 d). The differences in LAB population between our study and previous studies might result from the differences in silage age (300 d vs. 42–90 d), in the epiphytic population of bacteria on materials, and in the quality of the silages. The effects of short- and long-term storage on the microbial community and fermentation quality of silage requires further study. In the present study, the activities of heterofermentative LAB were weak in S2 and S3 under more acidic conditions (pH = 3.61 and 3.63, respectively) for a long period (about 300 d after ensiling), while they were stronger in S1 and S4 (pH 3.97). This is reflected in the higher acetic acid contents and LAB counts, and the lower lactic acid concentrations, in the latter at 0 and 2 d, along with greater aerobic stability (Table 5). The bacteria count decreased in S2 in the first 2 d, while it increased in S3 and S4 (Table 2). This might be because S2 still had a lower pH (3.69) and higher lactic acid content (121 g/kg DM) at 2 d than S1, S3, and S4 (Table 5). More acidic conditions might have reduced the bacterial activity in the silage, although the silage had been exposed to air for 2 d. *Acinetobacter johnsonii*, a known spoilage organism [27], was one of the more dominant bacterial species in S1 and S2, and it was present in S3 and S4 at low levels (Figure 3b). The effect of *A. johnsonii* on the fermentation quality and safety of silage requires further study.

The main fungal genera in S1 and S4 were *Kazachstania*, *Candida*, *Cladosporium*, *Rhizopus*, *Rhizomucor*, *Alternaria*, and *Epicoccum*, whereas *Kazachstania* dominated the fungal communities in S2 and S3 (Figure 4a). Other studies have reported dominant fungal genera of *Candida* and *Monascus* in whole-plant corn silage (90 d) [28], *Pichia*, *Sporisorium, Meyerozyma*, and *Hannaella* in sugarcane top silage (60 d) [22], *Issatchenki* in barley silage (60 d) [29], and *Candida*, *Kazachstania*, and *Pichia* in sugarcane top silage (90 d) [15]. These results suggest that, in contrast to the bacterial community, the dominant fungal community in the silage was different between the silages at the genera level. In the present study, *Kazachstania* dominated the fungal communities in S2 and S3 with poor aerobic stability (Figure 5). S2 and S3 had lower pH and acetic acid, and higher lactic acid than the other silages (Table 5). During aerobic exposure, the pH increased and the lactic acid decreased in S3, with acetic acid reducing at 2 d and increasing rapidly at 5 d. Between 2 and 5 d in S2, the pH increased quickly and the lactic acid decreased rapidly, with acetic acid disappearing at 5 d (Table 5). These results agree with the findings of Wang et al. for sugarcane top silage [15]. The results above indicate that *Kazachstania* might have a strong tolerance to lactic acid and be a yeast species that is crucially involved in initiating the aerobic deterioration of silage with a relatively low pH and acetic acid content. *Kazachstania* was also detected in barley silage [29] and sugarcane top silage [22] as minor taxa. *Candida* was the predominant fungal genus in S1 and S4 (Figure 4a), which had greater aerobic stability and higher acetic acid content (Table 5), and lower temperatures, than other silages (Figure 6) during aerobic exposure. However, Liu et al. [29] and Romero et al. [30] reported that a high abundance of *Candida* sp. was associated with a lower aerobic stability in silage, owing to *Candida* assimilating lactic acid after aerobic exposure [28]. The difference between our results and those of previous studies might be due to the higher acetic acid concentration in our study (42.8 g/kg) than in the studies of Romero et al. [4] and Liu et al. [29] (7.4 g/kg and 18.3 g/kg, respectively)—acetic acid inhibits fungus growth in silage and can enhance aerobic stability [4,28,30,31].

In the present study, the dominant fungal species in S1 and S4 were unclassified *Kazachstania*, *K. bulderi*, *C. xylopsoci*, unclassified *Cladosporium*, *Rhizopus microspores*, and *C. glabrata* with total abundances of 78.5% and 84.9% in fungal communities, respectively (Figure 4b). Unclassified *Kazachstania* and *K. bulderi* dominated the fungal communities in S2 and S3, respectively with abundances of 96.2% in S2 and 93.6% in S3 (Figure 4b). According to PCoA, the fungal species in S1 and S4 were connected, and were clearly separated from those of S2 and S3 (Figure 2). S1 and S4 thus had similar fungal species compositions, which were differentiated from those of S2 and S3. The differences in fungal species might be due to the differences in the fermentation processes of silage and in the epiphytic populations of fungi in the plant prior to ensiling [28]. Moreover, unclassified

*Kazachstania,* and *K. bulderi* belonging to *Kazachstania*, were the dominant fungi in S2 and S3, respectively (Figure 4b), and they had poor aerobic stability (Figure 6). This indicates that the aerobic deterioration taking place in the two silages might result from *Kazachstania* sp. growth after opening. Wang et al. [15] found *K. humilis* to be the key fungal yeast initiating aerobic deterioration in sugarcane top silage. *Kazachstania bulderi* was the predominant fungus in S3 and S4 in the present study. This strain was formerly named *Saccharomyces bulderi* [32] and was first isolated from maize silage as a novel species [33]. The present study first detected *C. xylopsoci*, *R. microspores*, and *Rhizomucor pusillus* in the silage in the form of fungal pathogens. *Candida xylopsoci* is usually isolated via fuel ethanol fermentation processes [34], *R. microsporus* has been detected in the traditional Chinese liquor *Daqu* using 18S rRNA gene sequencing [35], and *R. pusillus* has been identified in immunocompromised patients using real-time PCR [36]. The effects of these fungi on the fermentation quality and aerobic stability of silage should be investigated in future studies.

Moreover, Drouin et al. [10] revealed that ensiling whole-plant corn with LAB inoculant improved the aerobic stability of the silage, by maintaining a higher microbial diversity (Shannon index of bacteria and fungi), avoiding the dominance of a few bacteria, and preventing fungi from damaging silage quality. However, in the present study, the fungal communities in S1 and S4 had higher Shannon, Simpson, and Chao1 indexes, and greater aerobic stability, than S2 and S3, but the bacterial communities in S1, S3, and S4 had lower Shannon, Simpson, and Chao1 indexes than S2 (Table 3, Figure 6). This suggests that high fungal diversity, rather than bacterial diversity, contributes most significantly to aerobic stability in whole-plant corn silage.

S2 displayed the highest bacterial Shannon and Simpson indexes among the silages (Table 3), suggesting S2 had greater bacterial diversity in the present study. Additionally, the relative concentration of total metabolites in S2 was the highest among the silages (Table 4), and containing 93, 103, and 81 more metabolites identified than S1, S3, and S4, respectively (Supplementary Tables S2–S4). Previous studies showed that inoculating with LAB at ensiling increased the relative concentrations of some metabolites (e.g., organic acids, amino acids, and fatty acids) as well as the α-diversity (Shannon index) in wholeplant corn silages, sainfoin silages, and alfalfa silages [6,7,9,12]. This indicates that the high bacterial diversity might contribute to the accumulation of metabolites in whole-plant corn silages during fermentation process.

Biogenic amines in silages are produced by the decarboxylation of amino acids via the activities of plant enzymes and microbial enzymes, which accumulate during fermentation process and influence the palatability of silages, as well as the feed intake and performance of ruminants [14,37,38]. The intake of adequate amounts of biogenic amines can promote normal physiological activities in man and animals, but excessive amounts may result in food poisoning [38]. In the present study, tyramine, putrescine, phenylethylamine, spermidine, and noradrenaline were detected in whole-plant corn silages; the relative concentrations of tyramine and putrescine were considerable in S1, S2 and S3. Steidlová and Kalac also found that the concentrations of tyramine and putrescine were greater than those of histamine, cadaverine, tryptamine, spermidine and spermine in maize silages in 1999 (62 silages) and 2000 (51 silages) [14]. Nishino et al. [37] reported that inoculating with *Lactobacillus casei* reduced the concentrations of biogenic amines (histamine, tyramine, putrescine and cadaverine) in grass silage, maize silage, and total mixed ration silage, and that adding *L. buchneri* lowered the contents of biogenic amines in grass silages. Additionally, the activities of some undesirable bacterial genera (*Clostridia*, *Bacillus*, *Klebsiella*, *Escherichia*, *Pseudomonas*, *Citrobacter*, *Proteus*, *Salmonella*, *Shigella*, and *Photobacterium*) might result in the accumulation of biogenic amines in silages during ensiling [38,39]. In the present study, S2 contained higher *Bacillus*, *Pseudomonas*, and *Salmonella* contents than other silages, and greater *Escherichia* and *Klebsiella* than S3 and S4 (Supplementary Table S5), which might explain the higher relative concentrations of biogenic amines in S2 (Table 4).

#### **5. Conclusions**

Whole-plant corn silages showed a satisfactory fermentation quality after 300 d of ensiling. The main bacterial species in S2 were *L. buchneri*, *Acinetobacter johnsonii*, and unclassified *Novosphingobium*, while *L. buchneri*, *L. parafarraginis*, *L. kefiri*, and unclassified *Lactobacillus* dominated the bacterial communities in S1, S3, and S4. The main fungal species in S1 and S4 were unclassified *Kazachstania*, *K. bulderi*, *C. xylopsoci*, unclassified *Cladosporium*, *R. microspores*, and *C. glabrata*, while unclassified *Kazachstania* and *K. bulderi* dominated the fungal communities in S2 and S3, respectively, and were associated with these silages' poor aerobic stability. In whole-plant corn silage, high bacterial diversity helps the accumulation of metabolites, and high fungal diversity contributes to an improved aerobic stability.

**Supplementary Materials:** The following are available online at https://www.mdpi.com/article/ 10.3390/pr9050784/s1, Supplementary Table S1. Relative concentration of metabolites detected in whole-plant corn silages (n = 3). S1, silage collected from Erdos; S2, silage collected from Baotou; S3, silage collected from Ulanqab; S4, silage collected from Hohhot. (page: 1–16). Supplementary Table S2. Difference in metabolites identified between S1 and S2 (n = 3). S1, silage collected from Erdos; S2, silage collected from Baotou. (page: 17–19). Supplementary Table S3. Difference in metabolites identified between S2 and S3 (n = 3). S2, silage collected from Baotou; S3, silage collected from Ulanqab. (page: 20–22). Supplementary Table S4. Difference in metabolites identified between S2 and S4 (n = 3). S2, silage collected from Baotou; S4, silage collected from Hohhot. (page: 23–25). Supplementary Table S5. Relative abundance of *Bacillus*, *Pseudomonas*, *Escherichia*, *Klebsiella*, and *Salmonella* in whole-plant corn silages (n = 3). S1, silage collected from Erdos; S2, silage collected from Baotou; S3, silage collected from Ulanqab; S4, silage collected from Hohhot. (page: 26).

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

**Funding:** This study was funded by the National Key R&D Program of China (grant number, 2017YFE0104300) and the Science and Technology Project of Inner Mongolia (grant number, 2020GG0049).

**Institutional Review Board Statement:** Not applicable.

**Informed Consent Statement:** Informed consent was obtained from all subjects involved in the study.

**Data Availability Statement:** The data presented in this study are available on request from the corresponding author.

**Conflicts of Interest:** The authors declare no conflict of interest.

#### **References**


## *Article* **Bacterial Succession Pattern during the Fermentation Process in Whole-Plant Corn Silage Processed in Different Geographical Areas of Northern China**

**Chao Wang 1,†, Hongyan Han 2,†, Lin Sun 1, Na Na 1, Haiwen Xu 3, Shujuan Chang 4, Yun Jiang <sup>5</sup> and Yanlin Xue 1,\***


**Abstract:** Whole-plant corn silage is a predominant forage for livestock that is processed in Heilongjiang province (Daqing city and Longjiang county), Inner Mongolia Autonomous Region (Helin county and Tumet Left Banner) and Shanxi province (Taigu and Shanyin counties) of North China; it was sampled at 0, 5, 14, 45 and 90 days after ensiling. Bacterial community and fermentation quality were analysed. During fermentation, the pH was reduced to below 4.0, lactic acid increased to above 73 g/kg DM (*p* < 0.05) and *Lactobacillus* dominated the bacterial community and had a reducing abundance after 14 days. In the final silages, butyric acid was not detected, and the contents of acetic acid and ammonia nitrogen were below 35 g/kg DM and 100 g/kg total nitrogen, respectively. Compared with silages from Heilongjiang and Inner Mongolia, silages from Shanxi contained less *Lactobacillus* and more *Leuconostoc* (*p* < 0.05), and had a separating bacterial community from 14 to 90 days. *Lactobacillus* was negatively correlated with pH in all the silages (*p* < 0.05), and positively correlated with lactic and acetic acid in silages from Heilongjiang and Inner Mongolia (*p* < 0.05). The results show that the final silages had satisfactory fermentation quality. During the ensilage process, silages from Heilongjiang and Inner Mongolia had similar bacterial-succession patterns; the activity of *Lactobacillus* formed and maintained good fermentation quality in whole-plant corn silage.

**Keywords:** whole-plant corn silage; bacterial community; succession pattern; fermentation quality; fermentation process

#### **1. Introduction**

Ensiling fresh crops is an advanced technology for storing forage and supplying higher-quality forage to livestock throughout the year [1–4]. Compared with hay, silage exhibits greater dry-matter digestibility, metabolizable energy and crude-protein content, which contribute to improved liveweight gain [5].

In recent decades, whole-plant corn silage has become the predominant forage for the global dairy industry [6]. The characteristics of whole-plant corn silage are good fermentation quality and high energy, along with physically effective fibre, lower harvesting costs, minimised risks of production, elevated yield per area and flexibility to harvest corn for forage or grain [6–9]. In addition, more than 133 million dairy cattle globally consume

Na, N.; Xu, H.; Chang, S.; Jiang, Y.; Xue, Y. Bacterial Succession Pattern during the Fermentation Process in Whole-Plant Corn Silage Processed in Different Geographical Areas of Northern China. *Processes* **2021**, *9*, 900. https://doi.org/10.3390/pr9050900

**Citation:** Wang, C.; Han, H.; Sun, L.;

Academic Editors: Maria Tufariello and Francesco Grieco

Received: 28 April 2021 Accepted: 19 May 2021 Published: 20 May 2021

**Publisher's Note:** MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations.

**Copyright:** © 2021 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https:// creativecommons.org/licenses/by/ 4.0/).

about 665 million tons of silage each year, and whole-plant corn silage accounts for more than 40% of forage in dairy cattle farms [10,11].

Previous studies focused on the effects of the growing location and storing temperature on microbial communities and/or succession in whole-plant corn silage [2,12,13]. Gharechahi et al. [12] studied the dynamics of bacterial communities during the ensilage process in whole-plant corn silages obtained from Gorgan (temperate), Isfahan (warm and dry) and Qazvin (cold and dry) in Iran. Guan et al. [2] found different microbial communities in whole-plant corn that originated from five major ecological areas of the provinces of Sichuan, Chongqing and Guizhou in Southwest China. Additionally, high temperature affected the dynamics of the bacterial community in whole-plant corn silage, and resulted in a shift from a homofermentative to a heterofermentative lactic acid bacteria (LAB) population [13]. Moreover, most researchers are interested in the dynamics of microbial communities during the fermentation process in whole-plant corn silage with or without inoculants. Sun et al. [9] reported on bacterial succession in whole-plant corn silage during the initial aerobic, intense fermentation and stable phases. The study also found the LAB fermentation relay during the fermentation process, which was reflected by *Weissella*, *Lactococcus* and *Leuconostoc* in the first 5 h; *Weissella*, *Lactococcus*, *Leuconostoc*, *Lactobacillus* and *Pediococcus* between 5 and 24 h; *Lactobacillus* from 24 h to 60 days [9]. In addition, other studies revealed that adding LAB inoculants could promote bacterialcommunity succession, improve fermentation quality, and contribute to the accumulation of metabolites in whole-plant corn silage [11,14–17].

Heilongjiang, Inner Mongolia and Shanxi were among the top five provinces regarding whole-plant corn silage production in China in 2016 [18]. In addition, Heilongjiang has a temperate monsoon climate, and Inner Mongolia and Shanxi have a temperate continental climate. We hypothesised that there were differences in bacterial-succession patterns in whole-plant corn silage from different geographical locations. Thus, the objectives of this study were to determine changes in bacterial communities during the fermentation process in whole-plant corn silages processed in Heilongjiang, Inner Mongolia and Shanxi of North China.

#### **2. Materials and Methods**

#### *2.1. Materials and Silage Preparation*

The corn (*Zea mays* L.) plants used for ensiling were raised in experimental farms at 6 locations in 3 areas of North China: Heilongjiang province (Daqing city (H\_D; 124◦43 42.074 E, 46◦18 32.083 N) and Longjiang county (H\_L; 123◦7 32.120 E, 47◦21 23.396 N), cold and wet agricultural area), Inner Mongolia Autonomous Region (Helin county (I\_H; 111◦36 21.625 E, 40◦28 47.672 N) and Tumet Left Banner (I\_T; 111◦9 31.399 E, 40◦41 29.832 N), temperate and dry pastoral area) and Shanxi province (Taigu (S\_T; 112◦37 53.792 E, 37◦25 57.230 N) and Shanyin (S\_S; 112◦52 06.676 E, 39◦32 54.503 N) counties, temperate and dry agricultural area) (Figure 1). The variety of corn was 23 Yu for ensiling (no. 2008022, Henan Dajingjiu Seed Industry Co., Ltd., Shangqiu, China). Corn was harvested from 3 fields as replicates in each location; the harvesting stage according to local tradition was 1/3, 1/2 and 1/2 milk-line stage in Heilongjiang, Inner Mongolia and Shanxi, respectively. After harvesting, fresh forage from each field was chopped into 1 to 2 cm pieces using a chaff cutter (Hongguang Industry &Trade Co. Ltd., Ningbo Zhejiang, China), uniformly mixed and randomly divided into 5 batches (500 g per batch) that were ensiled in 5 plastic bags sealed with a vacuum sealer. Silage bags (500 g per bag) were stored at ambient temperature (22 ◦C to 25 ◦C) and sampled at 0, 5, 14, 45 and 90 days after ensiling.

**Figure 1.** Sampling locations of whole-plant corn. Heilongjiang province (Daqing city (124◦43 42.074 E, 46◦18 32.083 N) and Longjiang county (123◦7 32.120 E, 47◦21 23.396 N), cold and wet agricultural area), Inner Mongolia Autonomous Region (Helin county (111◦36 21.625 E, 40◦28 47.672 N) and Tumet Left Banner (111◦9 31.399 E, 40◦41 29.832 N), temperate and dry pastoral area) and Shanxi province (Taigu (112◦37 53.792 E, 37◦25 57.230 N) and Shanyin (112◦52 06.676 E, 39◦32 54.503 N) counties, temperate and dry agricultural area).

#### *2.2. Analyses*

#### 2.2.1. Physicochemical Analysis

The dry-matter content was measured as follows: drying in a forced-air oven (BPG-9240A, Shanghai Yiheng Scientific Instrument Co., Ltd., Shanghai, China) at 65 ◦C for 48 h, grinding through a 1 mm screen using a mill (FS-6D; Fichi Machinery Equipment Co., Ltd., Jinan Shandong, China) and drying at 105 ◦C until a constant mass was reached. The silage extract was prepared as follows: a mixture of 20 g fresh silage and 180 mL sterile water was homogenised for 100 s in a flap-type sterile homogeniser (JX-05, Shanghai Jingxin Industrial Development Co., Ltd., Shanghai, China) and filtered through 4 layers of cheesecloth. The pH of silage was established using a pH meter (PB-10, Sartorius, Gottingen, Germany) to measure the silage extract. Concentrations of lactic acid (LA), acetic acid (AA), propionic acid (PA) and butyric acid in the silages were determined by high-performance liquid chromatography (HPLC; 20A; Shimadzu Co., Ltd., Kyoto, Japan; (detector, SPD-20A diode array detector (210 nm); column, Shodex RS Pak KC-811 (50 ◦C, Showa Denko K.K., Kawasaki, Japan); mobile phase, 3 mM HClO4 (1.0 mL/min)) [19]. Ammonia nitrogen

(AN) and total nitrogen (TN) contents were measured with a Kjeltec autoanalyser (8400; Foss Co., Ltd., Hillerød, Denmark) according to the Kjeldahl method [20].

#### 2.2.2. Microbial Analysis

The counts of LAB, enterobacteria, total aerobic bacteria and yeast in silage were determined by culturing on MRS agar, violet red bile agar, nutrient agar and potato dextrose agar, respectively, at 37 ◦C for 48 h in an incubator (LRH-70, Shanghai Yiheng Science Instruments Co., Ltd., Shanghai, China) [21].

Then, 20 g of silage from each bag was placed into a self-styled bag at each sampling time and stored at −80 ◦C to analyse the bacterial communities. Bacterial DNA in silage was extracted by the E.Z.N.A. ®®Stool DNA Kit (D4015, Omega Bio-Tek, Inc., Doraville, GA, USA) according to the manufacturer's instructions. Amplification of the V3–V4 region of the bacterial rRNA gene was operated by polymerase chain reaction (PCR) with primers 341F (5 -CCTACGGGNGGCWGCAG-3 ) and 805R (5 -GACTACHVGGGTATCTAATCC-3 ) as follows: 98 ◦C for 30 s, followed by 32 cycles of denaturation at 98 ◦C for 10 s, annealing at 54 ◦C for 30 s, an extension at 72 ◦C for 45 s, and a final extension at 72 ◦C for 10 min [22]. PCR products were purified by AMPure XT beads (Beckman Coulter Genomics, Danvers, MA, USA), quantified by Qubit (Invitrogen, Carlsbad, CA, USA) and sequenced on an Illumina NovaSeq PE250 platform. High-quality clean tags were obtained from raw reads under specific filtering conditions according to fqtrim (version 0.94). Alpha diversity and beta diversity were calculated by QIIME2, the sequence alignment of species annotation was performed by BLAST, and the alignment databases were SILVA and NT-16S. The stacked bars of bacterial genera were made by Excel (Microsoft 365, Microsoft Corporation, Seattle, DC, USA) according to the relative abundance of the bacterial community. Differences in bacterial communities among sampling areas at each sampling time were analysed using the Mann–Whitney U and Kruskal–Wallis tests by R version 3.6.1. Principal-component analysis (PCA) of the bacterial communities among sampling areas at each sampling time was performed with R version 3.5.0 using OmicStudio tools at https://www.omicstudio.cn/tool (accessed on 10 February 2021).

#### *2.3. Statistical Analyses*

Data on the dry matter, fermentation quality, microbial counts, bacterial sequencing, and alpha diversity of whole-plant corn silage were analysed as a 3 × 5 factorial design. The model included the effects of the sampling area, sampling time, and their interaction. Differences among sampling locations and sampling times were analysed by one-factor analysis of variance using the general linear model (GLM) procedure of SAS (version 9.1.3; SAS Inst. Inc., Cary, NC, USA). The interaction of sampling area and sampling time was analysed using the PDIFF procedure of SAS. Differences were compared with the least significant difference, and significance was declared at *p* ≤ 0.05. Correlation between bacterial community (top 10 genera) and fermentation quality (pH, LA, AA and PA) was established with R 3.6.1.

#### **3. Results**

#### *3.1. Fermentation Quality and Microbial Counts*

Sampling area influenced pH and contents of AA, PA and AN (*p* < 0.05); sampling time affected pH, LA, AA, PA and AN (*p* < 0.05). Moreover, pH, AA and AN were interactively influenced by sampling area and sampling time (*p* < 0.05; Table 1). The counts of LAB, enterobacteria and total aerobic bacteria were affected by the sampling area (*p* < 0.05), and the sampling time influenced LAB, enterobacteria, total aerobic bacteria and yeast (*p* < 0.05), which were also interactively impacted by the sampling area and sampling time (*p* < 0.05; Table 2). No butyric acid or mould were detected in the silages.


*Processes* **2021** , *9*, 900

 corn silages during

fermentation

**Table 1.** Dry matter (g/kg), pH, organic acid contents (g/kg dry matter) and ammonia nitrogen (g/kg total nitrogen) of whole-plant


**Table 1.** *Cont.*



**Table 2.** *Cont.*

sampling time. Values with different uppercase (A–E) and lowercase (a–e) letters indicate significant differences among sampling times of each lactation and sampling locations at the same

time, respectively.

 ND, not detected.

#### *3.2. Bacterial Communities*

A total of 5,669,279 clean reads were obtained from 90 samples of whole-plant corn silage according to 16S rRNA. Sampling area and sampling time affected the observed species diversity, Shannon, Simpson and CHAO1 indices (*p* < 0.05), and had an interactive effect on observed species and CHAO1 (*p* < 0.05) (Table 3). According to PCA, bacterial communities in I5\_H\_1, I5\_H\_2, I5\_H\_3 and S5\_S\_1 were separated from other silages at 5 days after ensiling (Figure 2A). Silages from Shanxi (S14\_S and S14\_T) and I14\_H had separation from other silages at 14 days (Figure 2B); additionally, silages from Shanxi (S\_S and S\_T) were clearly separated from other silages at 45 and 90 days (Figure 2C,D).

**Figure 2.** Principal-component analysis of bacterial communities at (**A**) 5, (**B**) 14, (**C**) 45 and (**D**) 90 days after ensiling (*n* = 3). Whole-plant corn silages were processed at 6 locations in 3 areas of North China: Heilongjiang province (Daqing city (H\_D; 124◦43 42.074 E, 46◦18 32.083 N) and Longjiang county (H\_L; 123◦7 32.120 E, 47◦21 23.396 N), cold and wet agricultural area), Inner Mongolia Autonomous Region (Helin county (I\_H; 111◦36 21.625 E, 40◦28 47.672 N) and Tumet Left Banner (I\_T; 111◦9 31.399 E, 40◦41 29.832 N), temperate and dry pastoral area) and Shanxi province (Taigu (S\_T; 112◦37 53.792 E, 37◦25 57.230 N) and Shanyin (S\_S; 112◦52 06.676 E, 39◦32 54.503 N) counties, temperate and dry agricultural area). 156

In silages from Heilongjiang, *Sphingobacterium*, *Stenotrophomonas*, *Sphingomonas* and *Allorhizobium–Neorhizobium–Pararhizobium–Rhizobium* in H\_D were the dominant bacterial genera at 0 days (17.4%, 14.8% and 7.61%, respectively), decreased rapidly in the first 5 days, and then stayed at a low level. *Leuconostoc*, *Weissella* and *Sphingobacterium* in H0\_L dominated the bacterial community. *Leuconostoc* and *Weissella* in H\_L quickly reduced in the first 5 days and then stayed at a low level. The abundance of *Sphingobacterium* in H\_L was reduced to 0.319% at 5 days, and then increased to 7.98% at 90 days. Moreover, the abundance of *Lactobacillus* in H\_D and H\_L was 1.72% and 0.32% at 0 days, increased rapidly to 84.1% and 92.3% at 5 days and was then reduced to 71.23% and 70.4% at 90 days, respectively (Figure 3A).

(**A**)

<sup>(</sup>**B**)

**Figure 3.** Relative abundance of bacterial communities (genus level) in whole-plant corn silage from (**A**) Heilongjiang, (**B**) Inner Mongolia and (**C**) Shanxi at 0, 5, 14, 45 and 90 days after ensiling (*n* = 3). Whole-plant corn silages were processed at 6 locations in 3 areas of North China: Heilongjiang province (Daqing city (H\_D; 124◦43 42.074 E, 46◦18 32.083 N) and Longjiang county (H\_L; 123◦7 32.120 E, 47◦21 23.396 N), cold and wet agricultural area), Inner Mongolia Autonomous Region (Helin county (I\_H; 111◦36 21.625 E, 40◦28 47.672 N) and Tumet Left Banner (I\_T; 111◦9 31.399 E, 40◦41 29.832 N), temperate and dry pastoral area) and Shanxi province (Taigu (S\_T; 112◦37 53.792 E, 37◦25 57.230 N) and Shanyin (S\_S; 112◦52 06.676 E, 39◦32 54.503 N) counties, temperate and dry agricultural area).

> In silages from Inner Mongolia, *Lactobacillus* in I\_H and I\_T had a rapidly rising abundance in the first 5 days (80.2% and 95.8%, respectively), and it decreased to 71.6% and 69.0% at 90 days, respectively. Abundances of *Leuconostoc* and *Lactococcus* rapidly decreased in the first 5 days, and then maintained low levels in silages. *Weissella* in I\_H was quickly reduced from 15.9% at 0 days to 0.20% at 5 days, and then stayed at a low level. *Pediococcus* in I\_H increased from 0.32% at 0 days to 12.5% at 5 days, and then reduced to 0.76% at 90 days. No *Weissella* and *Pediococcus* were detected in I\_T (Figure 3B).

> In silages from Shanxi, the main bacterial genera at 0 days were *Leuconostoc*, *Lactococcus*, *Weissella* and *Pantoea* in S\_T, and *Leuconostoc*, *Lactococcus* and *Sphingobacterium* in S\_S. The abundance of *Lactobacillus* in S\_T and S\_S rapidly increased in the first 5 days (86.6% and 77.0%, respectively), and then reduced to 30.8% and 35.6% at 90 days, respectively. *Leuconostoc* in S\_T and S\_S reduced to 4.90% and 6.32 % at 5 days, increased to 23.68% and 17.85% at 45 days and then decreased to 16.53% and 8.73% at 90 days, respectively. *Lactococcus* in S\_T was reduced to 3.95% at 5 days, and then increased to 5.37% at 90 days; in S\_S, it was decreased in the first 5 days and then stayed at a low level. *Weissella* was a minor taxon after 5 days in the silages (Figure 3C). H5 and S5 contained more *Leuconostoc* and less *Pediococcus* than those in I5 (*p* < 0.05); additionally, I5 and S5 had higher levels of *Lactococcus* than those in H5 (*p* < 0.05) (Figure 4A). At 14, 45 and 90 days, silages from Heilongjiang and Inner Mongolia contained greater amounts of *Lactobacillus* and less *Leuconostoc* than

those from Shanxi (*p* < 0.05). Moreover, silages from Heilongjiang had lower *Lactococcus* than that of other silages from 14 to 90 days (*p* < 0.05) (Figure 4B–D).

**Figure 4.** Difference in bacterial communities (genus level) among silages from Heilongjiang (H; cold and wet agricultural area), Inner Mongolia (I; temperate and dry pastoral area), and Shanxi (S; temperate and dry agricultural area) at (**A**) 5 and (**B**) 14 days after ensiling (*n* = 6), and (**C**) 45 and (**D**) 90 days after ensiling (*n* = 6).

(**D**)


*Processes* **2021** , *9*, 900

**Table 3.**

Sequencing

 data and alpha diversity of bacteria and fungi in whole-plant

 corn silage during

fermentation

 (*<sup>n</sup>* = 3).


39◦3254.503 N) counties, temperate and dry agricultural area). Sampling times were at 0, 5, 14, 45 and 90 days after ensiling. Note: SEM, standard error of the mean; A, sampling area;sampling time. Values with different uppercase (A–C) and lowercase (a–c) letters indicate significant differences among 6 sampling locations at the same time.

162

 T,

#### *Processes* **2021**, *9*, 900

**Table 3.** *Cont.*

#### *3.3. Correlation between Fermentation Quality and Bacterial Genera*

pH had a negative correlation with *Lactobacillus* in all silages (*p* < 0.05). It correlated positively with *Weissella* in silages from Heilongjiang (*p* < 0.05), and with *Lactococcus*, *Leuconostoc* and *Weissella* in silages from Inner Mongolia and Shanxi (*p* < 0.05). *Lactobacillus* had a positive correlation with LA and AA contents in silages from Heilongjiang and Inner Mongolia (*p* < 0.05). LA concentration was negatively correlated with *Weissella* in silages from Heilongjiang (*p* < 0.05), with *Lactococcus* and *Leuconostoc* in silages from Inner Mongolia (*p* < 0.05), and with *Lactococcus*, *Leuconostoc* and *Weissella* in silages from Shanxi (*p* < 0.05). The AA content had a negative correlation with *Lactococcus* and *Leuconostoc* in silages from Inner Mongolia (*p* < 0.05), and with *Lactococcus* and *Weissella* in silages from Shanxi (*p* < 0.05) (Figure 5).

**Figure 5.** Correlation between the main bacterial genera (top 10) and fermentation quality (pH, lactic acid (LA), acetic acid (AA) and propionic acid (PA)) in silages from Heilongjiang (**A**; cold and wet agricultural area), Inner Mongolia (**B**; temperate and dry pastoral area), and Shanxi (**C**; temperate and dry agricultural area) during fermentation (*n* = 30).

#### **4. Discussion**

In the present study, whole-plant corn from Heilongjiang contained lower DM content (254 and 245 g/kg; Table 1), which might have been due to earlier harvesting (1/3 milk-line stage), and the cooler and wetter environment. This is similar to previous studies [2,12] that reported that the growing environment and harvesting stage influence the DM content of whole-plant corn. Earlier-harvesting corn contained lower DM content and greater amounts of water-soluble sugars, and its final silage had lower pH and greater lactic acid [23]. However, in the present study, silages from Inner Mongolia, with 285 and 288 g/kg of DM content, had a lower pH than that of other silages at 14 and 90 days, and less AN than that of silages from Heilongjiang at 45 and 90 days. In addition, the sampling area did not affect LA concentration in the final silages (Table 1). This indicated that silages from Inner Mongolia had better satisfactory fermentation quality than that of other silages. Moreover, silages from Heilongjiang had higher AN than that of other silages (except for I\_T) at 45 and 90 days, and contained the lowest DM content (Table 1). This indicated that the high moisture content in whole-plant corn before ensiling was not conducive to reducing AN content during fermentation. Whole-plant corn silage after 5 days of ensiling is in a stable fermentation phase according to Sun et al. [9]. The pH was less than 4.0 at 5 days and reached the lowest point at 60 days in all the silages except for H\_D, which agreed with a previous study [9]; moreover, lactic acid reached a high level (>76 g/kg DM) at 5 days and increased to its peak point at 14 or 45 days; AN content increased to its highest point at 45 days (Table 1). Ferrero et al. [24] also reported reduced pH and increased contents of lactic acid and AN in whole-plant corn silage after 15 days of ensiling. Those mentioned-above indicated that, during the stable fermentation phase, fermentation did not stop, and fermentation parameters changed to some extent in whole-plant corn silage.

The main bacterial genera were *Leuconostoc*, *Weissella*, *Sphingobacterium* and *Stenotrophomonas* in H0, and *Leuconostoc*, *Lactococcus*, *Weissella* and *Pantoea* in I0 and S0 (Figure 3 and Supplementary Figure S1). H0 contained less *Lactococcus* and more *Sphingobacterium*, *Stenotrophomonas* and *Sphingomonas* than I0 and S0 (Supplementary Figure S2). Additionally, the bacterial community in I0 and S0 flocked together (except for S0\_S\_1) and separated from H0\_D, H0\_L\_2 and H0\_L\_3 according to PCA (Supplementary Figure S3). This suggested that whole-plant corn from Inner Mongolia and Shanxi had a similar epiphytic bacterial community and differed from those from Heilongjiang. The different epiphytic bacterial community in raw materials might have resulted from the different geographical location [2,12,25]. Sampling locations in Inner Mongolia and Shanxi belong to a temperate continental climate and are close to each other; sampling locations in Heilongjiang, on the other hand, locate in temperate monsoon climates and are far from the other sampling locations (Figure 1). Guan et al. [2] and Gharechahi et al. [12] also reported the unique bacterial community in whole-plant corn from different sampling sites. The abundance of *Lactobacillus* was 1.02%, 1.08% and 1.51% in H0, I0 and S0, respectively (Figure 3 and Supplementary Figure S1); the same results were reported by previous studies [2,11–15,24,26]. This generally indicated that *Lactobacillus* is a minor taxon in whole-plant corn before ensiling. Additionally, the main LAB genera in fresh forages were *Leuconostoc*, *Weissella* and/or *Lactococcus* in the present study (Figure 3 and Supplementary Figure S1). This indicated that *Leuconostoc*, *Weissella* and *Lactococcus* might play a major role during the early stage (the first 24 h) of fermentation [9]. LAB counts in the raw materials were more than 10<sup>6</sup> colony-forming units/g fresh weight in the present study, and similar results were reported by a previous study [9,24]. This suggests that LAB count in whole-plant corn before ensiling is sufficient for satisfactory fermentation quality in the final silage.

According to Sun et al. [9], after 3 days of ensiling, whole-plant corn silage is in a stable fermentation phase, during which *Lactobacillus* plays a key role among bacterial genera in silage. In the present study, *Lactobacillus* had greater abundance than that of other bacterial genera in silages with low pH (<4.0) from 5 to 90 days (Figure 3 and Supplementary Figure S1). Results were consistent with those of previous studies [9,11,12,14,27]. Moreover, Xu et al. [26], Drouin et al. [28] and Wang et al. [29] revealed that *Lactobacillus* was the dominant bacterial genus in the final whole-plant corn silage. This showed that *Lactobacillus* usually dominates bacterial community succession in whole-plant corn silage during fermentation. However, after 5 days of ensiling, the abundance of *Lactobacillus* was reduced (Figure 3 and Supplementary Figure S1), and LAB count began to decrease in all silages (Table 2). Sun et al. [9] also observed the reduced abundance of *Lactobacillus* and decreased LAB count during the stable phase in whole-plant corn silage without any inoculant. This suggested that the epiphytic *Lactobacillus* on whole-plant corn might have weak acid resistance. *Weissella* is the most important LAB genus in whole-plant corn silage from 5 to 24 h after ensiling [9,14]. It is an obligatory heterofermentative LAB species that converts water-soluble sugars into LA and AA during the early stage of fermentation

in silage [30]. In the present study, no *Weissella* was detected in I\_T during the ensiling process (Figure 3), which might have resulted in the lower AA concentration in I\_T than that in other silages at 5, 45 and 90 days (Table 1). *Sphingobacterium*, *Stenotrophomonas*, *Sphingomonas*, *Enterobacter*, *Pantoea*, *Raoultella*, *Klebsiella*, *Serratia* and *Rahnella* are enterobacteria as facultatively anaerobic Gram-negative bacteria [31], some of which are undesirable in silage [23]. In the present study, the total abundances of those genera rapidly decreased in the first 5 days, and then increased to 12.9%, 9.33% and 24.9% in H90, I90 and S90, respectively (Supplementary Figure S1). Those above-mentioned suggested that it is necessary to add inoculants with greater capacity for acid production and resistance during the ensiling of whole-plant corn, especially *Lactobacillus* inhibiting enterobacteria.

In the present study, *Pediococcus* had considerable abundance in I5\_H (12.5%), while it was a minor taxon in other silages (<0.5%), which might have been the cause of the bacterial community in I5\_H being separated from other silages at 5 days (Figure 2A). According to PCA, the bacterial community in silages from Shanxi began to separate at 14 days, and separated clearly from other silages at 45 and 90 days (Figure 2). Moreover, the bacterial community in silages from Heilongjiang and Inner Mongolia clustered together as the ensiling process (Figure 2). The above-mentioned results indicated that silages from Heilongjiang and Inner Mongolia had a similar bacterial succession pattern during the fermentation process and differed from the silages from Shanxi. Additionally, compared with silages from Heilongjiang and Inner Mongolia, silages from Shanxi had a higher reducing rate of *Lactobacillus* from 14 to 90 days (Figure 3 and Supplementary Figure S1), and contained less *Lactobacillus* as the dominant bacterial genus (Figure 4). This suggested that *Lactobacillus* in silages from Shanxi had weaker acid resistance than that in other silages, which might have contributed to the different bacterial succession pattern in whole-plant corn silages among sampling areas. Silva et al. [32] also reported a tendency of bacterial communities to cluster together in whole-plant corn silage during the ensiling process. However, Xu et al. [11] and Keshri et al. [14] reported that the bacterial community in final silages clearly separated from silages at other sampling times.

Sun et al. [9] reported that *Lactobacillus* in whole-plant corn silage dominates the bacterial community during the stable phase and correlates negatively with pH from 1 to 60 days after ensiling. In the present study, *Lactobacillus* dominated the bacterial community during fermentation and had a negative correlation with pH in all silages and a positive correlation with LA and AA concentrations in the silages from Heilongjiang and Inner Mongolia (Figure 5). In addition, *Lactobacillus* also correlated positively with LA and AA without reaching the significance level in the silages from Shanxi (Figure 5C). The final silages had lower pH (from 3.52 to 3.80) and AN content (from 36.6 to 91.4 g/kg TN), and higher LA content (from 73.0 to 139 g/kg DM) (Table 1). Guan et al. [2] also found a positive correlation between LA content and *Lactobacillus* in whole-plant corn silages collected from five sampling sites in Southwest China. Previous studies reported that *Lactobacillus* dominated the bacterial community during fermentation in silages with good fermentation quality [11–14,17,33]. This indicated that the activity of *Lactobacillus* in silage mainly contributes to forming and maintaining satisfactory fermentation quality in silage during the ensilage process. In the present study, *Leuconostoc*, *Lactococcus* and *Weissella* had a positive correlation with pH, and were negatively correlated with LA and AA in silages (except for *Lactococcus* as a minor taxon in silages from Heilongjiang). Sun et al. [9] reported that *Leuconostoc*, *Lactococcus* and *Weissella* in whole-plant corn silage had an important effect on bacterial succession and the reduced pH in the first 24 h of ensiling, but positively correlated with pH from 1 to 60 days as minor taxa. This suggested that *Leuconostoc*, *Lactococcus* and *Weissella* might be inhibited under anaerobic and acidic environments, and played a limited role in whole-plant corn silage after 5 days of fermentation. Correlations of *Stenotrophomonas*, *Sphingomonas*, *Enterobacter* and *Pantoea* with fermentation quality were similar in silages from Inner Mongolia and Shanxi, which differed from the silages from Heilongjiang (Figure 5). The reason for the different correlations might be that the final silages from Inner Mongolia and Shanxi contained a lower abundance of LAB genera

than that of their materials and had similar changes in abundance of those genera during fermentation (Supplementary Figure S1). Ogunade et al. [34] found a negative correlation of *Pantoea*, *Pseudomonas*, *Sphingomonas* and *Stenotrophomonas* with pH in alfalfa silage. The effect of those bacterial genera on fermentation quality of silage needs to be further studied.

#### **5. Conclusions**

The geographic growth location mainly impacted the epiphytic bacterial community on whole-plant corn. Whole-plant corn silages had satisfactory fermentation quality. *Lactobacillus* was a minor taxon in fresh forage and dominated the bacterial community in whole-plant corn silages during the fermentation process. The acid resistance of *Lactobacillus* in whole-plant corn silage determined the bacterial succession pattern during fermentation, and silages from Heilongjiang and Inner Mongolia had similar bacterial succession pattern. The activity of *Lactobacillus* during the ensilage process contributed to forming and maintaining a satisfactory fermentation quality in whole-plant corn silage.

**Supplementary Materials:** The following are available online at https://www.mdpi.com/article/10 .3390/pr9050900/s1, Figure S1: Relative abundance of bacterial communities (genus level) in wholeplant corn silage from Heilongjiang (H; cold and wet agricultural area), Inner Mongolia (I; temperate and dry pastoral area) and Shanxi (S; temperate and dry agricultural area) at 0, 5, 14, 45 and 90 days after ensiling, Figure S2: Difference in bacterial communities (genus level) among whole-plant corn from Heilongjiang (H; cold and wet agricultural area), Inner Mongolia (I; temperate and dry pastoral area) and Shanxi (S; temperate and dry agricultural area), Figure S3: Principal component analysis of a bacterial community in whole-plant corn. Corn grown at six locations in three areas of Northern China: Heilongjiang province (Daqing city (H\_D; 124◦43 42.074 E, 46◦18 32.083 N) and Longjiang county (H\_L; 123◦7 32.120 E, 47◦21 23.396 N), cold and wet agricultural area), Inner Mongolia Autonomous Region (Helin county (I\_H; 111◦36 21.625 E, 40◦28 47.672 N) and Tumet Left Banner (I\_T; 111◦9 31.399 E, 40◦41 29.832 N), temperate and dry pastoral area) and Shanxi province (Taigu (S\_T; 112◦37 53.792 E, 37◦25 57.230 N) and Shanyin (S\_S; 112◦52 06.676 E, 39◦32 54.503 N) counties, temperate and dry agricultural area), Figure S4: Principal component analysis of a bacterial community in whole-plant corn silages from Heilongjiang province (Daqing city (H\_D; 124◦43 42.074 E, 46◦18 32.083 N) and Longjiang county (H\_L; 123◦7 32.120 E, 47◦21 23.396 N), cold and wet agricultural area), Inner Mongolia Autonomous Region (Helin county (I\_H; 111◦36 21.625 E, 40◦28 47.672 N) and Tumet Left Banner (I\_T; 111◦9 31.399 E, 40◦41 29.832 N), temperate and dry pastoral area) and Shanxi province (Taigu (S\_T; 112◦37 53.792 E, 37◦25 57.230 N) and Shanyin (S\_S; 112◦52 06.676 E, 39◦32 54.503 N) counties, temperate and dry agricultural area) at 0, 5, 14, 45 and 90 days after ensiling.

**Author Contributions:** Conceptualisation, C.W., H.H. and Y.X.; methodology, C.W., H.H. and L.S.; software, L.S., N.N. and S.C.; validation, C.W., H.H. and Y.X.; visualisation, S.C.; formal analysis, L.S. and N.N.; investigation, C.W., H.H., L.S. and N.N.; resources, C.W. and H.H.; data curation, C.W., H.H. and H.X.; writing—original draft, C.W. and H.H.; writing—review and editing, C.W., H.H., H.X., Y.J. and Y.X.; supervision, Y.X.; project administration, Y.X.; funding acquisition, Y.X. All authors have read and agreed to the published version of the manuscript.

**Funding:** This study was funded by the National Key R&D Program of China (grant number 2017YFE0104300) and the Science and Technology Project of Inner Mongolia (grant number 2020GG0049).

**Institutional Review Board Statement:** Not applicable.

**Informed Consent Statement:** Informed consent was obtained from all subjects involved in the study.

**Data Availability Statement:** The data presented in this study are available on request from the corresponding author.

**Conflicts of Interest:** The authors declare no conflict of interest.

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