**Abstract**

Silage making is not a novel technique. However, the agricultural industry has made great strides in improving our understanding of—and efficiency in—producing high-quality silage for livestock. Silage microbiology research has been using the newest molecular techniques to study microbial diversity and metabolic changes. This chapter reviews important research that has laid the foundation for field-based utilization of silage inoculants. We also outline areas of current, and future, research that will improve global livestock production through the use of silage.

**Keywords:** silage, forage, inoculants, additives

## **1. Introduction**

Fermentation of forage is harder to control than other fermentation processes such as industrial fermentation of food. Whole plants cannot be manipulated to remove contaminating microorganisms, and this can lead to important variations in the quality of the forage. Harvesting machinery can also contribute to the inclusion of soil or manure particles as contaminants. Other factors have an impact on silage quality, which include harvesting management, packing rate, weather events during harvest, selection of the ensiling structure, and selection of a microbial or chemical additive to preserve the crops. **Figure 1** provides an overview of the interactions between the main parameters involved in the production of high-quality silage.

This chapter will evaluate the recent published literature and will expand on the current knowledge in the study of the microbiota, search for silage inoculants, issues with aerobic instability, and understanding nonusers of forage inoculants. We will also review important research areas of microbial inoculants: fiber digestibility, analyzing "big data" functional studies, co-ensiling with by-products or food-processing wastes, and how lactic acid bacteria (LAB) used as forage additives influence animal performance.

### **2. Microbiota diversity during ensiling**

Characterization of the different microbial species observed throughout the different phases of the ensiling process was traditionally performed using

**Figure 1.**

*Ensiling involves several biochemical and microbiological descriptors that are influencing silage quality and could be controlled by different management criteria (boxed elements), which are directly influencing the main fermentation parameters of forage as well as animal productivity.*

culture-dependent methods, following the isolation of strains and the determination of their taxonomic classification. The use of selective media has several shortcomings, including limited knowledge on how composition of the different defined culture media influences the growth of organisms within the targeted species range. Dormant or inactive cells (viable but nonculturable) may not have been accurately measured [1].

New techniques based on DNA profiling have helped understanding the microbial diversity of silage within specific families or genera [2]. These techniques were diverse and included denaturating gel electrophoresis [3] or metabolic fingerprinting by Fourier transform infrared spectroscopy [4].

Next generation sequencing (NGS) technologies provide more complete details on microbiota diversity. The first application of NGS in silage was performed on ensiled grass to help understand how inoculation would influence the microbial communities [5]. Three years passed before a second paper would be published using NGS studying spatial and temporal microbial variations in commercial bunkers [6]. Several more papers or communications were performed afterward (see **Table 1**).

One of the complexities facing ensiling of forage is that several factors will influence the size and diversity of the microbial community at harvest. Microbial diversity will change according to the plant species, weather conditions during growth and prior to harvesting, fertilization management, physiological state of the forage, and so on. As an example of the potential variation, important differences in the composition of the epiphytic bacterial population were observed from different organs of whole plant corn in the weeks prior to harvesting (**Figure 2**). Leaves, silk,

**155**

**Forage** *Time-related dynamic*

Alfalfa-grass

Alfalfa

Corn Corn Manyflower

Oat *Commercial silos*

Corn (bunker)

Corn (bunker)

Corn-Sorghum

320–510

Vary

n.a.

(bunker)

Corn (bag silo)

Corn (bunker)

*Experimental silos*

Alfalfa and

187–222

65 days

25 °C

No

91–96%

V3–V4

No

[85]

sweet corn

360

150

n.a.

383

150

n.a.

*L. buchneri* and *L. hilgardii*

(3 × 105 CFU g FM)

*L. hilgardii* (1.5 × 105 CFU g FM)

212–373

60 days

n.a.

n.a.

Vary

n.a.

n.a. n.a. n.a.

96% 8–90%

>90%

V4 V3–V4 V3–V4

ITS1-4

Unpublished

ITS1-4

Unpublished

No

[6]

V4

No

[84]

V1–V3

No

[83]

456

6 periods, up to

n.a.

*L. plantarum* (1 × 106 CFU g FM)

97%

V4–V5

No

[82]

90 days

410

6 periods, up to 30 days

Ambient

352

8 periods, up to 64 days

20°C

*L. buchneri* and *L. hilgardii*

(4 × 105 CFU g FM)

No

75%

V4–V5

No

[81]

95%

V3–V4

ITS1-4

[7]

381

9 periods, up to 90 days

n.a.

421

4 periods, up to 90 days

22–25°C

395

7 periods, up to 64 days

20°C

*L. buchneri* and *L. hilgardii*

(4 × 105 CFU g FM)

*L. plantarum* or *L. buchneri*

(1 × 106 CFU g FM)

*L. plantarum* MTD1 (106 CFU g FM)

93% 97%

V3–V4

ITS1-2

[9]

Full 16S—PacBio

No

[13]

61%

V3–V4

ITS1-4

[7]

**DM (g kg)**

**Time of fermentation**

**Temperature**

**Inoculation and rate**

**Abundance of** *Lactobacillus* **(max)**

**16S rDNA amplicons**

**ITS amplicons**

**Reference**

*Lactic Acid Bacteria as Microbial Silage Additives: Current Status and Future Outlook*

*DOI: http://dx.doi.org/10.5772/intechopen.89326*


#### *Lactic Acid Bacteria as Microbial Silage Additives: Current Status and Future Outlook DOI: http://dx.doi.org/10.5772/intechopen.89326*

*New Advances on Fermentation Processes*

culture-dependent methods, following the isolation of strains and the determination of their taxonomic classification. The use of selective media has several shortcomings, including limited knowledge on how composition of the different defined culture media influences the growth of organisms within the targeted species range. Dormant or inactive cells (viable but nonculturable) may not have been accurately

*Ensiling involves several biochemical and microbiological descriptors that are influencing silage quality and could be controlled by different management criteria (boxed elements), which are directly influencing the main* 

New techniques based on DNA profiling have helped understanding the microbial diversity of silage within specific families or genera [2]. These techniques were diverse and included denaturating gel electrophoresis [3] or metabolic fingerprint-

Next generation sequencing (NGS) technologies provide more complete details on microbiota diversity. The first application of NGS in silage was performed on ensiled grass to help understand how inoculation would influence the microbial communities [5]. Three years passed before a second paper would be published using NGS studying spatial and temporal microbial variations in commercial bunkers [6]. Several more papers or communications were performed afterward

One of the complexities facing ensiling of forage is that several factors will influence the size and diversity of the microbial community at harvest. Microbial diversity will change according to the plant species, weather conditions during growth and prior to harvesting, fertilization management, physiological state of the forage, and so on. As an example of the potential variation, important differences in the composition of the epiphytic bacterial population were observed from different organs of whole plant corn in the weeks prior to harvesting (**Figure 2**). Leaves, silk,

ing by Fourier transform infrared spectroscopy [4].

*fermentation parameters of forage as well as animal productivity.*

**154**

measured [1].

**Figure 1.**

(see **Table 1**).


*New Advances on Fermentation Processes*

**Table 1.**

**157**

**Figure 2.**

*Lactic Acid Bacteria as Microbial Silage Additives: Current Status and Future Outlook*

and tassels harbored different proportions of the main epiphytic bacterial families even though the variation in microbiota composition was small between the sam

pling periods. *Cytophagaceae* and *Methylobacteriaceae* were mainly observed on the leaves, while *Enterobacteriaceae* and *Pseudomonadaceae* were observed on silk, cob,

Published results of microbiome analysis were performed from varied forages from temperature and tropical regions, including pure strands of legumes or grasses and mixed forages. Several studies performed time-based samplings to describe changes in the microbial communities in relation to the fermentation periods [7–9] (**Table <sup>1</sup>**). Generally, the relationship between the time of fermentation and the microbial composition was similar to the general succession pattern previously reported by culture-dependent microbiological techniques. For example, with corn silage inoculated with either *Lactobacillus plantarum* or *Lactobacillus buchneri* and/ or *Lactobacillus hilgardii*, it was possible to observe that the succession to Firmicutes was rapid, in a matter of hours after sealing the experimental mini-silos. A second observation was that *Leuconostocaceae* (mainly *Weissella* sp.) was the dominant operational taxonomic unit (OTU) during early fermentation. In both studies, there were important changes in bacteria richness during the fermentation, with either values below 50 OTUs after incubation of 30 days [9] or decreasing throughout fermentation to a similar level of OTUs [8]. In both studies, fungal richness dropped

*Bacterial microbiome from different corn organs (leave, silk, and tassel) at four time points prior to harvesting.*


*DOI: http://dx.doi.org/10.5772/intechopen.89326*

and tassel [7].

throughout fermentation.

*Characteristics of the silage and experimental design from publications using amplicon-based metagenomic to study the microbiome.*

*Lactic Acid Bacteria as Microbial Silage Additives: Current Status and Future Outlook DOI: http://dx.doi.org/10.5772/intechopen.89326*

and tassels harbored different proportions of the main epiphytic bacterial families even though the variation in microbiota composition was small between the sampling periods. *Cytophagaceae* and *Methylobacteriaceae* were mainly observed on the leaves, while *Enterobacteriaceae* and *Pseudomonadaceae* were observed on silk, cob, and tassel [7].

Published results of microbiome analysis were performed from varied forages from temperature and tropical regions, including pure strands of legumes or grasses and mixed forages. Several studies performed time-based samplings to describe changes in the microbial communities in relation to the fermentation periods [7–9] (**Table 1**). Generally, the relationship between the time of fermentation and the microbial composition was similar to the general succession pattern previously reported by culture-dependent microbiological techniques. For example, with corn silage inoculated with either *Lactobacillus plantarum* or *Lactobacillus buchneri* and/ or *Lactobacillus hilgardii*, it was possible to observe that the succession to Firmicutes was rapid, in a matter of hours after sealing the experimental mini-silos. A second observation was that *Leuconostocaceae* (mainly *Weissella* sp.) was the dominant operational taxonomic unit (OTU) during early fermentation. In both studies, there were important changes in bacteria richness during the fermentation, with either values below 50 OTUs after incubation of 30 days [9] or decreasing throughout fermentation to a similar level of OTUs [8]. In both studies, fungal richness dropped throughout fermentation.

**Figure 2.** *Bacterial microbiome from different corn organs (leave, silk, and tassel) at four time points prior to harvesting.*

*New Advances on Fermentation Processes*

**156**

**Forage**

**DM** 

**Time of** 

**Temperature**

**Inoculation and rate**

**Abundance of** 

**16S rDNA** 

**ITS** 

**Reference**

**amplicons**

**amplicons**

V4

ITS1

[86]

*Lactobacillus* **(max)**

34 (con)–99%

**fermentation**

**(g kg)**

Corn (whole)

Corn Grass (not

368

14 and 58 days

n.a.

further

defined)

High moisture

751

10, 30 and

20–22°C

*L. buchneri* and/or *L. hilgardii*

95%

V3–V4

ITS1–4

Unpublished

(4 × 105 CFU g FM)

4 species of LAB (individual)

61–97%

V3–V4

No

[11]

(105 CFU g FM)

No (vacuum bags)

No

86% 30%

V3–V4

V4-V5

[88]

V3–V4

No

[87]

90 days

corn

*Moringa oleifera*

*Moringa oleifera*

Purple prairie

300

76 days

22°C

clover

Small grain

385

90 days

22°C

No

82%

V3–V4

V4-V5

[89]

(mix)

Oat Soybean + corn

Sugar cane

**Table 1.**

n.a.

90 days

20–35°C *Characteristics of the silage and experimental design from publications using amplicon-based metagenomic to study the microbiome.*

340

60 days

15–30°C

450

217 days

23°C

*L. buchneri* 40788 (4 × 105 CFU g

57%

V4

ITS1

[10]

FM) and *P. pentosaceus*

(1 × 105 CFU g FM)

No No

60–80%

50%

V4

No

[91]

V3–V4

No

[90]

233

60 days

25–32°C

n.a.

60 days

15 and 30°C

234

90 days

22–25°C

380

100 days

23°C

*L. buchneri* 40788 (4 × 105 CFU g

FM) and *P. pentosaceus*

(1 × 105 CFU g FM)

*L. plantarum* or *L. buchneri*

>98%

Full

No

[32]

16S—PacBio

(1 × 106 CFU g FM)

*L. buchneri* CD034 (106 CFU g

35–67% (inoculated)

V3–V4

No

[5]

FM)

These changes in microbial population were also observed in samples collected on farms. Under commercial conditions, comparing silage made from the same forage between sites is difficult since differences in dry matter (DM), packing density, and other physical parameters will influence efficiency of the fermentation and the microflora. Associating those parameters to NGS studies could improve the understanding of this process. It will then be possible to comprehend how other physical variables may contribute, e.g., the impact of high or low temperature on microbial succession, the impact of length of storage, length of time at a high temperature, and the impact of DM variations within the same forage.

To date, most of the data collected from experimental silos was performed with incubation periods shorter than 100 days and at a temperature around 20–25°C. These conditions offer an initial set of parameters but must be expanded to simulate real-life conditions in silos, which could include variances of more than 20°C above ambient temperatures during fermentation and long fermentation periods [10].

Most of the published studies included a comparison between control and a microbial silage additive or between different strains of LAB. The general trend on microbial diversity is that inoculation with LAB reduces the microbial diversity, but the impact differs in relation to the forage and the species of LAB. As observed by Wang et al. [11], microbial diversity was influenced by the inoculation of *Moringa oleifera* differentially for each of the four LAB species inoculated as well as from the temperature of incubation.

Comparisons between studies tend toward similar changes in microbial composition. To facilitate comparisons, it will be necessary to standardize DNA isolation and preparation of the amplicons prior to sequencing. By summarizing the main methodology information from different trials (**Table 1**), it was observed that some studies did not include fungal diversity, and the amplified DNA region differed. Most bacterial studies were performed following the amplification of the V3–V4 region, but there was a trend toward using the V4 or V4–V5 region, which offers potential for longer DNA strand and improves comparison scores against the database. Using a good quality database is also a critical step that is often overlooked during analysis [12]. The drawback of the current methodology for amplicon-based metagenomic is that the amplified region is short and does not provide enough coverage of the complete 16S rRNA gene. Two published studies were able to gather near complete fragments by sequencing the 16S rRNA gene on a PacBio sequencer instead of the Illumina model [12, 13]. This expanded the analysis of diversity to the species, or even subspecies, level.

Currently, no study has tried to mix the potential offered by polymerase chain reaction (PCR)-based profiling technology—like PCR-DGGE—with NGS capacities. Instead of amplifying with universal primers, primers targeting regions of lower variations within ribosomal DNA, or in other genes, provide more precise results allowing higher similarity scores at the species level.

Microbial communities continuously evolve during the storage period, even during the anaerobic stable phase. By improving our knowledge on the succession between communities, genus, species, and even strains, it will be possible to refine how strains are selected as microbial silage additives. This could easily allow selection of strains for particular forage species or climatic conditions.

#### **3. Searching for new forage inoculants in temperate and tropical forages**

The fermentation capability—or the acidification potential—depends directly on the DM content, at the level of water-soluble carbohydrates (WSC), and,

**159**

14.15SE.

*Lactic Acid Bacteria as Microbial Silage Additives: Current Status and Future Outlook*

forages: tropical (C4), temperate (C3) grasses, and legumes.

additionally, its nutritive value sharply declines as maturity advances.

lactic acid. Yeast and molds also form a large group [18].

inhibit undesirable and detrimental microorganisms.

The microflora existing on the vegetative parts of plants consist mainly of microorganisms considered undesirable from the point of view of the fermentation process. These include anaerobic bacilli of the genus *Clostridium*; aerobic bacteria of the genus *Bacillus*; coliform bacilli, including *Escherichia coli*, *Enterobacter* spp., *Citrobacter* spp., and *Klebsiella* spp.; as well as bacteria of the genus *Listeria*, *Salmonella*, and *Enterococcus* (*E. faecium*, *E. faecalis*, *E. mundtii*, *E. casseliflavus*, *E. avium,* and *E. hirae*); and the occurrence of actinomycetes. Species of *Clostridium* are responsible for large losses because they produce CO2 and butyric acid instead of

Concerning the presence of LAB, Pahlow et al. [19] found in grasses that *L. plantarum*, *L. casei*, *E. faecium* and *Pediococcus acidilactici* were the most frequently observed species. However, with the development and the use of DNA sequencing profile techniques, it is possible to identify hundreds of species as mentioned earlier. Most of the studies done by scientific groups were based on the efforts to find any microorganisms, especially bacteria, able to drive a good fermentation and

Zielińska et al. [20] demonstrated that microbial inoculants altered many parameters of silages, but the strength of the effects on fermentation depends on specific characteristic of an individual strain. Several research teams have been searching for new strains able to perform better than the ones currently on the market. For example, Agarussi et al. [21] searched for new promising strains for alfalfa silage inoculants and isolated *Lactobacillus pentosus* 14.7SE, *L. plantarum* 3.7E, *Pediococcus pentosaceus* 14.15SE, and a mixture of *L. plantarum* 3.7E and *P. pentosaceus* 14.15SE. The authors concluded that all of the tested strains had a positive effect on at least one chemical feature of the silage during the fermentation process, although the most promising strain found in that trial was the *P. pentosaceus*

Moreover, Saarisalo et al. [22] searched for LAB capable of lowering the pH of grass silages with low proteolytic activity. The researchers found a potential strain of *L. plantarum*, which was effective in reducing the deamination in silages. Besides aiming to enhance silage fermentation, aerobic stability has been an important topic in the last 20 years. During silage feedout, accelerated growth of spoilage organisms (yeasts) results in high temperatures and nutrients and DM losses, leading to increased silage deterioration [23]. According to McDonald et al. [24], even though yeasts can grow from 5 to 50°C, the optimum growth of most species occurs at 30°C. Other spoiling microorganisms, such as molds and *Clostridium* bacteria, grow between 25 and 37°C, respectively. Considering the specific temperature and humidity ranges of different microbes for growth, it is possible to see

that tropical climates are more prone to spoilage than temperate ones.

inversely, on the buffering capacity of a given forage [14]. Due to their compositions, the ensiling potential is completely different among the different families of

Studies conducted by Wilkinson [15] with C3 grasses have concluded that the minimal concentration of the WSC should be at least 2.5–3.0% of the fresh forage. Below 2% of WSC of fresh crop weight, forages are prone to undesirable fermentations. The average level of WSC found by Zopollatto et al. [16] in a review of microbial additives in Brazil for tropical grasses was only 1.6%, far from the minimum for

Tropical grasses provide large quantities of DM, which can reach up to 30 tons of DM per hectare. This great yield, however, comes at the optimal stage of maturity in terms of nutrients with other types of challenges: wilting is an issue, and the excess moisture can lead to important losses of nutrients through effluent production [17];

*DOI: http://dx.doi.org/10.5772/intechopen.89326*

a good fermentation.

#### *Lactic Acid Bacteria as Microbial Silage Additives: Current Status and Future Outlook DOI: http://dx.doi.org/10.5772/intechopen.89326*

inversely, on the buffering capacity of a given forage [14]. Due to their compositions, the ensiling potential is completely different among the different families of forages: tropical (C4), temperate (C3) grasses, and legumes.

Studies conducted by Wilkinson [15] with C3 grasses have concluded that the minimal concentration of the WSC should be at least 2.5–3.0% of the fresh forage. Below 2% of WSC of fresh crop weight, forages are prone to undesirable fermentations. The average level of WSC found by Zopollatto et al. [16] in a review of microbial additives in Brazil for tropical grasses was only 1.6%, far from the minimum for a good fermentation.

Tropical grasses provide large quantities of DM, which can reach up to 30 tons of DM per hectare. This great yield, however, comes at the optimal stage of maturity in terms of nutrients with other types of challenges: wilting is an issue, and the excess moisture can lead to important losses of nutrients through effluent production [17]; additionally, its nutritive value sharply declines as maturity advances.

The microflora existing on the vegetative parts of plants consist mainly of microorganisms considered undesirable from the point of view of the fermentation process. These include anaerobic bacilli of the genus *Clostridium*; aerobic bacteria of the genus *Bacillus*; coliform bacilli, including *Escherichia coli*, *Enterobacter* spp., *Citrobacter* spp., and *Klebsiella* spp.; as well as bacteria of the genus *Listeria*, *Salmonella*, and *Enterococcus* (*E. faecium*, *E. faecalis*, *E. mundtii*, *E. casseliflavus*, *E. avium,* and *E. hirae*); and the occurrence of actinomycetes. Species of *Clostridium* are responsible for large losses because they produce CO2 and butyric acid instead of lactic acid. Yeast and molds also form a large group [18].

Concerning the presence of LAB, Pahlow et al. [19] found in grasses that *L. plantarum*, *L. casei*, *E. faecium* and *Pediococcus acidilactici* were the most frequently observed species. However, with the development and the use of DNA sequencing profile techniques, it is possible to identify hundreds of species as mentioned earlier. Most of the studies done by scientific groups were based on the efforts to find any microorganisms, especially bacteria, able to drive a good fermentation and inhibit undesirable and detrimental microorganisms.

Zielińska et al. [20] demonstrated that microbial inoculants altered many parameters of silages, but the strength of the effects on fermentation depends on specific characteristic of an individual strain. Several research teams have been searching for new strains able to perform better than the ones currently on the market. For example, Agarussi et al. [21] searched for new promising strains for alfalfa silage inoculants and isolated *Lactobacillus pentosus* 14.7SE, *L. plantarum* 3.7E, *Pediococcus pentosaceus* 14.15SE, and a mixture of *L. plantarum* 3.7E and *P. pentosaceus* 14.15SE. The authors concluded that all of the tested strains had a positive effect on at least one chemical feature of the silage during the fermentation process, although the most promising strain found in that trial was the *P. pentosaceus* 14.15SE.

Moreover, Saarisalo et al. [22] searched for LAB capable of lowering the pH of grass silages with low proteolytic activity. The researchers found a potential strain of *L. plantarum*, which was effective in reducing the deamination in silages.

Besides aiming to enhance silage fermentation, aerobic stability has been an important topic in the last 20 years. During silage feedout, accelerated growth of spoilage organisms (yeasts) results in high temperatures and nutrients and DM losses, leading to increased silage deterioration [23]. According to McDonald et al. [24], even though yeasts can grow from 5 to 50°C, the optimum growth of most species occurs at 30°C. Other spoiling microorganisms, such as molds and *Clostridium* bacteria, grow between 25 and 37°C, respectively. Considering the specific temperature and humidity ranges of different microbes for growth, it is possible to see that tropical climates are more prone to spoilage than temperate ones.

*New Advances on Fermentation Processes*

periods [10].

temperature of incubation.

species, or even subspecies, level.

and the impact of DM variations within the same forage.

These changes in microbial population were also observed in samples collected on farms. Under commercial conditions, comparing silage made from the same forage between sites is difficult since differences in dry matter (DM), packing density, and other physical parameters will influence efficiency of the fermentation and the microflora. Associating those parameters to NGS studies could improve the understanding of this process. It will then be possible to comprehend how other physical variables may contribute, e.g., the impact of high or low temperature on microbial succession, the impact of length of storage, length of time at a high temperature,

To date, most of the data collected from experimental silos was performed with incubation periods shorter than 100 days and at a temperature around 20–25°C. These conditions offer an initial set of parameters but must be expanded to simulate real-life conditions in silos, which could include variances of more than 20°C above ambient temperatures during fermentation and long fermentation

Most of the published studies included a comparison between control and a microbial silage additive or between different strains of LAB. The general trend on microbial diversity is that inoculation with LAB reduces the microbial diversity, but the impact differs in relation to the forage and the species of LAB. As observed by Wang et al. [11], microbial diversity was influenced by the inoculation of *Moringa oleifera* differentially for each of the four LAB species inoculated as well as from the

Comparisons between studies tend toward similar changes in microbial composition. To facilitate comparisons, it will be necessary to standardize DNA isolation and preparation of the amplicons prior to sequencing. By summarizing the main methodology information from different trials (**Table 1**), it was observed that some studies did not include fungal diversity, and the amplified DNA region differed. Most bacterial studies were performed following the amplification of the V3–V4 region, but there was a trend toward using the V4 or V4–V5 region, which offers potential for longer DNA strand and improves comparison scores against the database. Using a good quality database is also a critical step that is often overlooked during analysis [12]. The drawback of the current methodology for amplicon-based metagenomic is that the amplified region is short and does not provide enough coverage of the complete 16S rRNA gene. Two published studies were able to gather near complete fragments by sequencing the 16S rRNA gene on a PacBio sequencer instead of the Illumina model [12, 13]. This expanded the analysis of diversity to the

Currently, no study has tried to mix the potential offered by polymerase chain reaction (PCR)-based profiling technology—like PCR-DGGE—with NGS capacities. Instead of amplifying with universal primers, primers targeting regions of lower variations within ribosomal DNA, or in other genes, provide more precise

Microbial communities continuously evolve during the storage period, even during the anaerobic stable phase. By improving our knowledge on the succession between communities, genus, species, and even strains, it will be possible to refine how strains are selected as microbial silage additives. This could easily allow selec-

**3. Searching for new forage inoculants in temperate and tropical forages**

The fermentation capability—or the acidification potential—depends directly

on the DM content, at the level of water-soluble carbohydrates (WSC), and,

results allowing higher similarity scores at the species level.

tion of strains for particular forage species or climatic conditions.

**158**
