Go to Top Go to Bottom
Anim Biosci > Volume 33(8); 2020 > Article
Cai, Du, Yamasaki, Nguluve, Tinga, Macome, and Oya: Community of natural lactic acid bacteria and silage fermentation of corn stover and sugarcane tops in Africa

Abstract

Objective

To effectively utilize crop by-product resources to address the shortage of animal feed during the dry season in Africa, the community of natural lactic acid bacteria (LAB) of corn stover and sugarcane tops and fermentation characteristics of silage were studied in Mozambique.

Methods

Corn stover and sugarcane tops were obtained from agricultural field in Mozambique. Silage was prepared with LAB inoculant and cellulase enzyme and their fermentation quality and microbial population were analyzed.

Results

Aerobic bacteria were the dominant population with 107 colony-forming unit/g of fresh matter in both crops prior to ensiling, while 104 to 107 LAB became the dominant bacteria during ensiling. Lactobacillus plantarum was more than 76.30% of total isolates which dominated silage fermentation in the LAB-treated sugarcane top silages or all corn stover silages. Fresh corn stover and sugarcane tops contain 65.05% to 76.10% neutral detergent fiber (NDF) and 6.52% to 6.77% crude protein (CP) on a dry matter basis, and these nutrients did not change greatly during ensiling. Corn stover exhibits higher LAB counts and water-soluble carbohydrates content than sugarcane top, which are naturally suited for ensiling. Meanwhile, sugarcane tops require LAB or cellulase additives for high quality of silage making.

Conclusion

This study confirms that both crop by-products contain certain nutrients of CP and NDF that could be well-preserved in silage, and that they are potential roughage resources that could cover livestock feed shortages during the dry season in Africa.

INTRODUCTION

The major constraint for cows in the tropics is shortage of feed in terms of quality and quantity, especially in the dry season [1]. The main roughage sources for cows in Africa are native grasses and agricultural by-products. When cows are not fed such quality roughage, decreased milk and meat production results [2]. In recent years, improved technologies for producing forage crops, grasses, and crop by-products have been investigated, and their adaptability to various conditions, nutritive value, and contribution to animal productivity explored [3]. Several factors can influence crops nutrition, such as plant genotype, sowing density, harvest season, irrigation and fertilization. Generally, tropical crops can only be grown during the rainy season and the bulk of by-product production occurs after harvest. Crop by-products should be preserved to ensure a continuous supply of feed for ruminants during the dry season. Improved silage preparation and storage are the most effective techniques for ensuring that the animal production system can cope with animal feed shortages in the tropics [1].
Corn (Zea mays L.) and sugarcane (Saccharum officinarum L.) are important crops for food and sugar production in Africa, and they were produced approximately 1.45 million tons and 2.76 million tons annually, respectively in Mozambique [4]. When corn is harvested for grain, more than 40% dry matter (DM) of the corn plant, including the leaves, stalks, husks, and cobs, are discarded in the field [5]. Sugarcane top as residue represent 15% to 25% of the aerial part of the plant [6]. Therefore, corn stover and sugarcane tops are among the main agricultural by-products produced in Africa, but they are generally discarded in the field, where they are often burned and used as fertilizer [7].
The by-products of both corn and sugarcane could be used for livestock feed, as they are cheap and abundant in the tropics, where other green fodder is unavailable. The preservation of forage crops, as silage, depends on the production of sufficient acid to inhibit the activity of contaminating microbes under anaerobic conditions [8]. Usually, it is difficult to make tropical forage crops and grasses of high fermentation quality due to their high moisture and low water-soluble carbohydrates (WSC) contents [2]. Better technologies aimed at creating good-quality animal feed, by providing long-term storage of silage from crop by-products, need to be developed. The improvement of ensiling techniques through use of biological additives, such as lactic acid bacteria (LAB) inoculants and cellulose, is widely anticipated. It is well-accepted that these silage additives could improve silage preservation efficiency and thereby enhance cattle performance [9]. In general, cellulase improves fibre degradation by increasing the WSC as a substrate for LAB, which then produce lactic acid. As a result, the pH decreases, preserving the forage crops.
Ensiling methods for creating good-quality silage and long-term storage are not available year-round in the tropics [1]. However, there is limited information available on epiphytic LAB characteristics and silage fermentation in Africa. In the present study, we identified and characterised LAB isolated from fresh corn stover and sugarcane tops in Mozambique, and then determined their ensiling characteristics. To improve fermentation quality, the silages were prepared with microbial additives, including LAB inoculants and cellulase enzymes, which are likely to play an important role in improving silage fermentation.

MATERIALS AND METHODS

Ensiling materials and silage preparation

Corn stover and sugarcane tops were obtained from agricultural field in a corn-production area and in an industrial sugar-production region in Maputo, Mozambique on September 2018, respectively. After harvest, fresh corn stover and sugarcane tops were immediately cut into 1 to 2 cm lengths by a chopper (92-2S, Sida Agri-Machine Co., Ltd, Luoyang, China), and approximately 8 kg were packed into 20 L polyethylene drum (Ka-Kosher Co., Ltd, Sinaloa, Mexico) silos. The silos were kept at an ambient temperature (25°C to 38°C) and opened after 60 d of ensiling for analysis of fermentation quality and microbial analysis [10]. The experiment was designed as a 2×4 factorial arrangement in a completely randomized design (crop by-products × additive treatments) with triple replicates per treatment. The commercial LAB inoculant FG (Lactobacillus plantarum, Snow Brand Seed Co., Ltd, Sapporo, Japan) and Acremonium cellulase (Acremonium cellulase, Meiji Seika Pharma Co., Ltd, Tokyo, Japan) were used as silage additives based on the guidelines of a commercial manufacturer. Inoculant strain originally isolated from forage crop that could produce more lactic acid in the silage environment. Cellulase is produced from Acremonium cellulolyticus, the main compositions are glucanase and pectinase, carboxymethyl cellulase activity is 7,350 U/g. The LAB were inoculated at 5 mg/kg as 1.0×105 colony-forming unit (cfu)/g on a fresh matter (FM) basis. Cellulase was added at 10 mg blended with 20 mL H2O per kg of FM. Silage treatments were designed as control, LAB, cellulase, and LAB+cellulase. The LAB and cellulase were diluted with deionized water, and the additive solution was sprayed using an electronic sprayer (SSP-5H, fujiwara Sangyo Co., Ltd, Miki, Japan) for addition of experiment treatments. The same amount of deionized water was sprayed on the control treatment.

Microbial analysis

The counts of microorganisms in the crop by-products or silages were measured by the plate count method [11]. Samples (10 g) were blended with 90 ml sterilized water and serially diluted 10−1 to 10−8 in sterilized water. The numbers of LAB were measured on Lactobacilli MRS (de Man, Rogosa and Sharpe) agar (Difco Laboratories, Detroit, MI, USA) incubated at 30°C for 48 h under anaerobic conditions (Anaerobic Pack Rectangular Jar; 2.5 liters, Mitsubushi Gas Chemical Company INC, Tokyo, Japan). For isolation of LAB, more than 20 strains on MRS agar medium were picked randomly from each sample, and a total of 97 isolates were collected, of which 75 isolates were considered to be LAB, as determined by the Gram-stain appearance, catalase test and lactic acid productivity [11]. Aerobic bacteria were counted on Nutrient agar (Nissui-Seiyaku Co., Ltd, Tokyo, Japan) incubated for 48 h at 30°C under aerobic conditions. Coliform bacteria were counted on Blue Light agar (Nissui-Seiyaku, Japan) incubated at 30°C for 48 h; mold and yeast were counted on Potato Dextrose agar (Nissui-Seiyaku, Japan) incubated for 48 to 72 h at 30°C. Yeasts were distinguished from mold and bacteria by colony appearance and observation of cell morphology. Colonies were counted as viable numbers of microorganisms in cfu/g of FM. For LAB identification, each colony of LAB was purified twice by streaking on a MRS agar plate. The pure cultures were grown on MRS agar at 30°C for 24 h, resuspended in a solution of nutrient broth (Difco, USA) and dimethyl sulfoxide at a ratio of 9:1, and stored as stock cultures in a deep freezer (MDF-U384, Sanyo Electric Co., Ltd, Osaka, Japan) at −80°C until further examination.
Gram stain and morphological characteristics of LAB were determined after 24 h of incubation on MRS agar, and their catalase activity and gas production from glucose were determined as described by Kozaki et al [11]. Growth at different temperatures was detected in MRS broth after incubation at 5°C and 10°C for 10 d, and at 40°C, 45°C, and 50°C for 7 d. Growth at pH 3.0 to 7.0 was observed in MRS broth after incubation at 30°C for 7 d. Carbohydrate assimilation and fermentation of 49 different compounds with one control were identified on AP 50 CH strips. These strains were divided into five groups (A to E) according to morphological and biochemical characters and 16S rRNA sequence analysis, and the representative strains of each group were selected by their different fermentation patterns of AP 50 CH.

16S rRNA gene sequence analysis

Cells of representative strains grown for 8 h in MRS broth at 30°C were used for DNA extraction and purification [12]. The 16S rDNA sequence coding region was amplified by polymerase chain reaction (PCR) and performed in a PCR ThermalCycler (GenAmp PCR System 9700; PE Applied Biosystems, Foster City, CA, USA) and reagents from a Takara Taq PCR Kit (Takara Shuzo Co., Ltd, Otsu, Japan). Sequencing was performed twice on both strands by the dideoxy method using a PRISM BigDye Terminator Cycle Sequence Ready Reaction Kit (Applied Biosystems, USA) in combination with an Applied Biosystems model 310 A automated sequencing system. Searching 16S rDNA sequence similarity was performed at GenBank data library by using the BLAST program. Then the sequence information was introduced into the CLUSTAL W software program (Hitachi Software Engineering Co., Ltd, Tokyo, Japan) for assembly and alignment [13]. The 16S rDNA sequences of isolates were compared with sequences from the strains of LAB held in the GenBank. Nucleotide substitution rates were calculated, and phylogenetic trees were constructed by the neighbor-joining method. Bacillus subtilis NCDO 1769 was used as an outgroup organism [11]. The topology of trees was evaluated by bootstrap analysis of the sequence data with CLUSTAL W software based on 100 random resamplings [13].

Chemical analysis

Pre-ensiled corn stover and sugarcane tops, and their silage samples were dried in a forced air oven at 70°C for 48 h, and ground to pass a 1 mm mesh screen (FW 100, Taisite Instrument Co., Ltd, Tianjin, China) for chemical composition analyses. The data of chemical composition on DM basis were corrected for residual moisture after 3 h at 105°C. The DM, ash, crude protein (CP) and ether extract (EE) were analyzed by the methods 934.01, 942.05, 976.05, and 920.39 of AOAC [14], respectively. The organic matter (OM) content was calculated as the weight loss upon ashing. The neutral detergent fiber (NDF) and acid detergent fiber (ADF) were obtained according to the method of Van Soest et al [15] with an ANKOM A200i fiber analyzer (ANKOM Technology, Macedon, NY, USA) and were expressed exclusive of residual ash. The acid detergent lignin (ADL) analysis was subsequently performed following the procedure of Van Soest et al [15]. The WSC was determined by Anthron method [16]. Lactate buffer capacity (LBC) was measured by titrating with 0.1 M HCl to reduce pH from initial pH to pH 3.0 and then titrated to pH 6.0 with 0.1 M NaOH as described by McDonald et al [17]. Degradable intake protein (DIP) was analyzed by the method of Roe et al [18]. Undegraded intake protein (UIP) was calculated as described by Licitra et al [19]. Soluble intake protein (SIP) was analyzed by the method of Licitra et al [19] in omitting sodium azide. Binding protein (BP) and neutral detergent insoluble protein (NDIP), the CP contents of sequential NDF residue were determined with the method of Licitra et al [19]. Pre-ensiled material and samples preparation for macro mineral analysis was carried out as described by Khan et al [20]. The concentration of calcium (Ca), phosphorous (P), magnesium (Mg), and potassium (K) was measured using an atomic absorption spectrophotometer (PerkinElmer, LAMBDA 1050, Shelton, CT, USA).

Fermentation analysis

The fermentation products of silage were analyzed by using cold-water extract, a 10 g wet silage sample was homogenized with 90 mL of deionized water and kept in a refrigerator at 4°C for 24 h as described by Cai [10]. Then, the material was filtered, and the filtrate was used to measure pH, ammonia-N, and organic acids. The pH was measured using a glass electrode pH meter (Starter 100/B, OHAUS, Shanghai, China), the ammonia-N content was analyzed by using steam distillation of the filtrates [10], the concentration of organic acid including lactic acid, acetic acid, propionic acid and butyric acid were measured by high-performance liquid chromatography (Sodex RS Pak KC-811column; Showa Denko K.K., Kawasaki, Japan; DAD detector: 210 nm, SPD-20A, Shimadzu Co. Ltd., Kyoto, Japan; eluent: 3 mm HClO4, 1.0 mL/min; temperature: 40°C) methods as described by Cai [10].

Statistical analysis

Data on the microorganism population, chemical composition and fermentation quality after 60 d of ensiling were analyzed with a completely randomized design with a 2×4 (crops [C] × additives [A]) factorial treatment structure. The two ways analysis of variance (ANOVA) procedure of SAS version 9.1 (SAS Institute, Cary, NC, USA) was used for the analysis and the statistical model is as follows:
Yijk=μ+αi+βj+αβij+ɛijk
where Yijk = observation; μ = overall mean, αi = crops effect (i = corn stover and sugarcane top), βj = additives effect (j = 1 to 4), αβij = crops×additives effect, and ɛijk = error. The mean values were compared by Tukey’s test [21].

Accession numbers

The nucleotide sequences for the 16S rDNA described in this report were deposited with GenBank under accession numbers LC434015, LC434016, LC434017, LC434018, and LC434019 for the strains MB1, MB14, MB6, MB52, and MB38, respectively.

RESULTS

The chemical, protein and macro mineral composition of corn stover and sugarcane tops are shown in Table 1. The DM content of the fresh corn stover was 16.97% higher (p<0.05) than that in fresh sugarcane tops. The CP and EE contents of both crop by-products did not show marked differences. The OM, NDF, ADF, ADL, and LBC contents of corn stover were lower (p<0.05) than those of respective values in sugarcane tops. The WSC content of corn stover was 2.53% of DM higher (p<0.05) than sugarcane tops. Regarding the protein composition, the DIP and SIP contents were higher (p<0.05), and the UIP and NDIP contents lower (p<0.05), in the corn stover than in sugarcane tops. The BP contents were similar in both crops. Regarding the macro minerals, the K contents were similar in both crops, while the Ca, P, and Mg contents were higher (p<0.05) in the corn stover.
The microbial population of the corn stover and sugarcane tops before ensiling are shown in Table 2. Aerobic bacteria dominated both crops with similar levels of 107 cfu/g in FM. The corn stover contained 107 coliform bacteria, 106 yeasts, and 104 molds cfu/g in FM. The microbial counts for all three microorganisms were lower in the sugarcane tops than corn stover. The natural LAB, including the genera Lactobacillus, Weissella, Lactococcus, and Pediococcus, were present at 103 to 106 cfu/g of FM in both crops.
The characteristics of LAB of corn stover and sugarcane tops and their silages are shown in Table 3. Representative strains MB1, MB6, MB14, MB38, and MB52 were isolated from both crops or their silages. A total of 97 strains were isolated from MRS agar plates. Of those, 22 strains did not exhibit characteristics of LAB, namely Gram-negative, catalase-positive, and unable to produce lactic acid in MRS broth. The other 75 strains were considered to be LAB, they were Gram-positive and catalase-negative rods or cocci. Those strains are able to form D(−) isomer, L(+) isomer, or approximately equal quantities of D(−) and L(+)-lactic acid, and did or did not produce gas from glucose.
The phylogenetic trees of 16S rRNA gene sequence for rod-shaped and cocci-shaped LAB strains obtained in this study are shown in Figure 1, 2, respectively. More than 1,500 bases of 16S rRNA of these strains were determined. Following phylogenetic analysis, the rod-shaped strains MB1, FG, and MB14 were placed in the cluster making up the genus Lactobacillus. Strains MB14 were clearly assigned to the Lactobacillus brevis. While strains MB1 and FG grouped on the phylogenetic tree together with L. plantarum, including species, L. pentosus, L. argentoratensis, and L. paraplantarum, and in a 100% bootstrap cluster. Furthermore, strains MB1 and FG appeared to be equally linked to L. plantarum, these strains were phylogenetically associated with L. plantarum. Cocci-shaped strains MB6, MB38, and MB52 were placed in the cluster making up the genus Weissella, Lactococcus, and Pediococcus, respectively. These type strains of Weissella cibaria, Lactococcus lactis, and Pediococcus acidilactici were the species most closely to the strains MB6, MB38, and MB52 in the phylogenetic tree, and they showed the sequence similarity value more than 99.80% with each strain. Based on the morphological and biochemical characteristics, and 16S rRNA gene sequence analysis, these isolates were identified as Lactobacillus plantarum, Lactobacillus brevis, Weissella cibaria, Lactococcus lactis, and Pediococcus acidilactici.
The LAB community of corn stover and sugarcane tops and their silages are shown in Figure 3. Microbial diversity of LAB was observed in corn stover, where Lactobacillus plantarum (58.40%; percentage of total isolates), Lactobacillus brevis (20.60%), Weissella cibaria (17.00%), and Pediococcus acidilactici (4.00%) were the predominant species. In the sugarcane tops, the LAB microbial communities included Lactobacillus brevis (32.20%), Weissella cibaria (55.60%), Lactococcus latcis (7.20%), and Pediococcus acidilactici (5.00%). Lactobacillus plantarum, the dominant bacterium in the corn stover, was not detected in the sugarcane tops. Weissela cibaria was the dominant LAB in sugarcane tops. Lactobacillus brevis and Pediococcus acidilactici were abundant in both crops. After 60 d of fermentation, L. plantarum was the dominant LAB species (76.30% to 83.60% of total isolates) in the LAB− and LAB+celllulase-treated sugarcane tops, and all corn stover silages, while Weissella cibaria (57.40% to 60.50%) was the dominant species in control and cellulase-treated sugarcane top silages.
The chemical composition of corn stover and sugarcane top silages are shown in Table 4. After 60 d of ensiling, the CP contents of the corn stover and sugarcane tops silages were similar, ranging from 5.99% to 6.57% and 6.00% to 6.28% of DM, respectively. The contents of OM and EE in by-product silages did not show marked differences from the control, LAB, cellulase or combined LAB and cellulase treatments. However, the NDF and ADF contents of the cellulase-treated silages were lower (p<0.05) than those of control and LAB-treated silages. Compared to corn stover silages, the OM, EE, NDF, ADF, and ADL contents of sugarcane tops silages were higher (p<0.05). Crops (C) influenced OM, EE, NDF, ADF, and ADL contents (p = 0.0073 to 0.0164 or p<0.0001), but the CP (p = 0.3059) did not. The additives (A) influenced (p≤ 0.0001) NDF and ADF contents, while the other chemical composition did not (p = 0.2580 to 0.6179). The interaction between C and A (C×A) influenced (p = 0.0344 to 0.0445) NDF and ADL contents, but not OM, CP, EE, or ADF (p = 0.2932 to 0.9777).
The fermentation quality of the corn stover and sugarcane top silages after 60 d of fermentation is shown in Table 5. All of the corn stover silages were well-preserved, with low pH values (<3.97) and ammonia-N content (<0.77% g/kg of DM), and high lactic acid content (>4.14% of DM). The fermentation quality of the control, LAB−, cellulase−, and LAB+ cellulase-treated corn stover silages did not display marked differences. In contrast, the fermentation quality of sugarcane top silages varied markedly. After 60 d of fermentation, the control silage was of poor quality, with low lactic acid content (0.61% of DM) and a relatively high pH value (4.71). However, the LAB−, cellulase−, and LAB+cellulase-treated silages had similar good fermentation patterns, with higher (p<0.05) lactic acid contents and lower (p<0.05) pH than those of the control silage. The DM and lactic acid content were higher (p<0.05), and the pH and butyric acid content lower (p<0.05), in corn stover silages compared with sugarcane top silages. The acetic acid, propionic acid, and ammonia-N contents were similar between the corn stover and sugarcane top silages. The C influenced (p = 0.0005 to 0.0088 or p<0.0001) silage DM, pH, lactic acid, butyric acid and ammonia-N contents, while the A and A×C influenced pH (p = 0.0012 to 0.0024), lactic acid (p = 0.0072 to 0.0073), acetic acid (p = 0.0008 to 0.0160), butyric acid (p = 0.0005 to 0.0008) and ammonia-N (p = 0.0071 to 0.0111). The A also influenced (p = 0.0434) the propionic acid content.
The microbial populations of corn stover and sugarcane top silages after 60 d of fermentation are shown in Table 6. For the corn stover silages, the microbial populations were similar among all treatments; LAB (106 cfu/g of FM) was the dominant species. Additionally, the aerobic bacteria count was 104 to 105 cfu/g, and that of yeasts was 105 cfu/g of FM. Meanwhile, coliform bacteria and molds were below detectable levels (<102 cfu/g of FM). For the sugarcane top silages, 104 to 107 LAB, 103 to 105 aerobic bacteria, and 103 to 105 yeasts counts were presented in the silages. In the LAB−, cellulase− and LAB+cellulase-treated silages, the LAB count was significantly (p<0.05) higher than that of the control, while that of aerobic bacteria was significantly (p<0.05) lower. Similar to the corn stover silages, the counts of coliform bacteria and molds in all sugarcane top silages were below detectable levels (<102 cfu/g of FM). The C, A, and C×A influenced (p = 0.0002 to 0.0213 or p<0.0001) the LAB, aerobic bacteria, and yeast counts.

DISCUSSION

In general, the chemical compositions of tropical grasses and forage crops were different, especially with regard to DM, CP, NDF, and WSC contents. Some tropical grasses are less amenable to producing good-quality silage due to their low DM, high LBC, and low WSC contents [22]. The density is also an important factor for silage fermentation. In this study, the weight of corn and sugar cane silage packed into silo is 7.85 to 8.38 kg. Although the moisture of the two kinds of silages is different, there is no large difference in density between the two silages. This may be because the top of the sugar cane is rich in leaf parts, while the corn stover is rich in stem parts. The CP and EE contents of the by-products of both crop types were at similar levels, but the corn stover exhibited more suitable ensiling characteristics, such as lower moisture content and LBC, and higher WSC content. In addition, the DIP, SIP, UIP, BP, NDIP, Ca, P, and Mg contents in the corn stover were much higher than those in sugarcane tops, suggesting that corn stover contains high amounts of digestible feed ingredients that could contribute to livestock feed.
To comprehensively understand the microbial populations in crop by-products and their silages, we investigated the abundance of four kinds of microbes: LAB, aerobic bacteria, molds, and yeasts. Generally, farm silage is based on natural lactic acid fermentation, and epiphytic LAB from forage transform the WSC into organic acids during the ensiling process. As a result, the pH is reduced and the forage preserved [23]. Therefore, the abundance, taxonomy, and characteristics of epiphytic LAB have become significant factors for predicting the adequacy of silage fermentation and determining whether to apply bacterial inoculants to silage materials [23]. When LAB are present in low numbers in forage crops or grasses, they will fail to produce sufficient lactic acid during fermentation to reduce the pH and inhibit the growth of clostridia; therefore, the resulting silage will be of poor quality. In this study, the microbial population between the two crops is different. The reason for this is unclear. Perhaps the cultivation environment and their chemical composition of both crops, especially moisture and WSC contents may influence the distribution of native microorganisms [24]. Relatively high numbers of LAB (>105 cfu/g of FM) were present in the corn stover in this study. In particular, Lactobacilli were dominant within the LAB populations. In this case, it would not be necessary to use bacterial inoculants to control contaminating microbes during silage fermentation (Table 1). However, very low numbers of LAB (<103 cfu/g of FM) were observed in sugarcane tops, and Weissella were the dominant species in those populations; this suggests that it is necessary to use LAB inoculant to improve silage fermentation.
The isolates from this study were Gram-positive and catalase-negative rods or cocci that produced lactic acid from glucose. These properties suggest that these strains belong to the LAB species. The representative strains exhibited differences in terms of gas production from glucose, yielding approximately equal quantities of L(+) and D(−)-lactic acid, but they could not be identified down to the species level on the basis of these phenotypic characteristics. The identification and genetic interrelationships of the LAB, including new species isolated from silage, have been studied extensively in 16S rRNA gene sequence and DNA-DNA hybridisation experiments [23]. Recent results indicate that the LAB genera Lactobacillus, Pediococcus, Leuconostoc, Weissella, and Lactococcus exhibit a high degree of sequence similarity to one another and form a phylogenetically coherent group that is separate from other bacteria [1]. In the present study, isolated strains were of the genera Lactobacillus (two strains), Weissella, Lactococcus, and Pediococcus based on the phylogenetic analysis, thus confirming that these strains belong to these LAB genera. The representative strains MB1, MB6, MB14, MB38, and MB52 are the species most closely related to type strains of Lactobacillus plantarum, Lactobacillus brevis, Weissella cibaria, Lactococcus lactis, and Pediococcus acidilactici, respectively. The 16S rDNA sequence similarity of these strains was more than 99.80% to each other, and less than 98.00% to other type strains. The AP 50 CH data also supported these results, and these strains and their type strains had similar fermentation patterns. To our knowledge, this is also the first report of natural LAB community on Africa silage.
Certain lactic acid-producing cocci create an aerobic environment suitable for the development of lactobacilli only during the early stages of the silage fermentation process. In contrast, Lactobacilli (rods) are important promoters of lactic acid fermentation for longer periods [23]. Many studies have reported that homofermentative lactobacilli, such as Lactobacillus casei and Lactobacillus plantarum, promote lactic acid fermentation and improve silage quality [1]. In the present study, all corn stover silages were well-preserved, with high lactic acid contents and low pH values. The factors used to assess fermentation quality included the chemical composition of the corn stover material and the physiological properties of epiphytic LAB. The corn stover had a relatively high WSC content and low LBC, and a high number of epiphytic LAB (>105 cfu/g of FM). Lactobacillus plantarum are the dominant species naturally distributed in corn stover [25]; this species is a homofermentative type of LAB which grows well under low pH conditions and produces more lactic acid than other strains [26]. During ensiling, lactobacilli can use sugars to increase the production of lactic acid, thereby reducing the pH and inhibiting the growth of harmful bacteria, in turn resulting in good-quality silage. On the other hand, the control silage of the sugarcane top was of poor quality, while the microbial additive-treated silages were of good quality. The parameters for assessing fermentation quality include the chemical composition of the crop materials and the physiological properties of the epiphytic LAB. The sugarcane tops had a relatively low WSC content (<7.85% of DM), and the LAB could not ferment sufficient sugar to produce lactic acid (Table 4). Furthermore, the pH value of this silage did not decrease below 4.0, such that clostridia was present via butyric acid fermentation and ammonia-N production. However, when the sugarcane top silage was treated with LAB or cellulose, fermentation quality was higher. The cellulase addition could improve fibre degradation to increase WSC as a substrate for LAB, to produce lactic acid and thereby improve fermentation quality. Acremonium cellulase used in this study contain a strong activity of glucanase and pectinase, it can play an important role in the silage fermentation process [27]. It is suggested that a decrease in fibre content, including NDF and ADF, in sugarcane top silages underlies this phenomenon. Thus, if crops such as corn have sufficient sugar content, even without the addition of LAB, it would be possible to make a good-quality silage. Therefore, LAB and cellulase might influence the fermentation quality of silage. When the crop by-product contains an insufficient amount of LAB and WSC, it is necessary to add them for silage fermentation.
The present study mainly focused on silage preparation and ensiling characteristics analysis. The future experiment will be required to study the digestibility of these crop by-product silages for sheep or cows. Now, the silage or total mixed ration prepared by using local available resources and their evaluation on the digestibility and milk production of dairy cattle is under process. In Africa, agricultural residues from crop production have increased rapidly in recent years [28], in turn increasing the need for efficient use of crop by-products for economic and environmental reasons. Silage prepared with local crop by-products could be a very effective fermentation technology.

CONCLUSION

This study suggests that corn stover contained effective LAB species for natural silage fermentation; meanwhile, sugarcane tops could yield good silage with LAB inoculant. Based on the silage fermentation and chemical composition analyses, corn stover and sugarcane tops contain an abundance of nutrients for livestock. Fresh corn stover exhibits good ensiling characteristics and high levels of LAB, which are naturally suited for ensiling and fermentation. Meanwhile, sugarcane tops require LAB or cellulase additives for silage production. This study suggests that by-products of both crops, as silage, are well-suited for preservation of forage crops and could serve as roughage sources to cover animal feed shortages during the dry season in Africa.

IMPLICATIONS

The present study reports the community of natural LAB and silage fermentation of corn stover and sugarcane tops, focus on addressing feed shortage during dry season in Africa. Corn stover and sugarcane tops contain an abundance of nutrients for animal. The LAB, especially Lactobacillus plantarum became the dominant bacteria affect silage fermentation after ensiling. Fresh corn stover exhibits good ensiling characteristics and high levels of LAB, which are naturally suited for ensiling and fermentation. Meanwhile, fresh sugarcane tops require LAB or cellulase additives for silage preparation. Based on the bacterial community and silage fermentation analyses, the crop by-products can be well-preserved as silage and have great potential as a feed source for livestock, to cover feed shortages during the dry season in Africa. Silage prepared with local available crop by-product resources could be a very effective fermentation technology for animal production.

Notes

CONFLICT OF INTEREST

We certify that there is no conflict of interest with any financial organization regarding the material discussed in the manuscript.

ACKNOWLEDGMENTS

This work was supported by the project “Development of sustainable technologies to increase agricultural productivity and improve food security in Africa (Food Security in Africa)”, Japan International Research Center for Agricultural Sciences (JIRCAS), Japan, and Instituto de Investigacao Agraria de Moçambique (IIAM), Mozambique.

Figure 1
Phylogenetic tree showing the relationship between the 16S rDNA sequences of rod-shaped LAB strains obtained in this study. Numbers at nodes are bootstrap values based on a neighbor-joining bootstrap analysis with 1,000 replications. Bacillus subtilis is used as the outgroup. The bar indicates 1% sequence divergence. Knuc, nucleotide substitution rates; LAB, lactic acid bacteria.
ajas-19-0348f1.jpg
Figure 2
Phylogenetic tree showing the relationship between the 16S rDNA sequences of cocci-shaped LAB strains obtained in this study. Numbers at nodes are bootstrap values based on a neighbor-joining bootstrap analysis with 1,000 replications. Baccillus subtilis is used as the outgroup. The bar indicates 1% sequence divergence. Knuc, nucleotide substitution rates; LAB, lactic acid bacteria.
ajas-19-0348f2.jpg
Figure 3
Community of lactic acid bacteria of corn stover, sugarcane top and silage. LAB, lactic acid bacteria inoculant FG; Cellulase, Acremonium cellulase.
ajas-19-0348f3.jpg
Table 1
Chemical, protein and macro mineral composition of corn stover and sugarcane tops
Items Corn stover Sugarcane top SEM p-value
Chemical composition
 DM (%) 42.65±1.67a 25.68±2.08b 1.09 0.0004
 OM (% of DM) 84.22±2.55b 94.65±0.87a 1.10 0.0026
 CP (% of DM) 6.52±0.20 6.77±0.78 0.33 0.6165
 EE (% of DM) 1.57±0.60 1.80±0.28 0.30 0.6319
 NDF (% of DM) 65.05±0.50b 76.10±2.01a 0.85 0.0008
 ADF (% of DM) 35.08±3.62b 42.46±1.04a 1.54 0.0274
 ADL (% of DM) 3.49±0.54b 5.11±0.36a 0.26 0.0119
 WSC (% of DM) 10.38±0.40a 7.85±0.39b 0.23 0.0014
 LBC (meq/ kg of DM) 539.75±21.23b 1,772.40±183.30a 75.33 0.0003
Protein composition (% of CP)
 DIP 69.34±1.51a 61.36±2.08b 1.05 0.0051
 UIP 30.66±1.75b 38.64±1.40a 0.92 0.0034
 SIP 39.31±1.34a 24.66±0.69b 0.61 <0.0001
 BP 25.90±4.03 24.08±4.07 2.34 0.6115
 NDIP 39.67±3.98b 50.59±1.22a 1.70 0.0105
Macro mineral (mg/kg)
 Ca 0.35±0.01a 0.27±0.04b 0.01 0.0177
 P 0.20±0.01a 0.14±0.01b 0.01 0.0031
 Mg 0.21±0.01a 0.18±0.01b 0.01 0.0161

SEM, standard error of the mean; DM, dry matter; OM, organic matter; CP, crude protein; EE, ether extract; NDF, neutral detergent fiber; ADF, acid detergent fiber; ADL, acid detergent lignin; WSC, water soluble carbohydrates; LBC, lactate buffer capacity; DIP, degradable intake protein; UIP, undegradable intake protein; SIP, soluble intake protein; BP, binding protein; NDIP, neutral detergent insoluble protein; Ca, calcium; P, phosphorous; Mg, magnesium; K, potassium.

a,b Means±standard deviation within rows with different superscript letters differ significantly from each other (p<0.05).

Table 2
Microbial population of corn stover and sugarcane tops before ensiling
Items Lactic acid bacteria Lactobacilli Weissella Lactococci Pediococci Aerobic bacteria Coliform bacteria Yeasts Molds

------------------------------------------------------------------ log 10 cfu/g of FM ----------------------------------------------------------------------
Corn stover 5.73 5.70 3.18 3.75 ND 7.89 7.72 6.41 4.12
Sugarcane top 6.56 3.08 6.54 ND 3.87 7.20 5.26 4.27 3.79

Data are means of three samples.

cfu, colony-forming unit; FM, fresh matter; ND, not detected.

Table 3
Characteristics of lactic acid bacteria isolated from corn stover, sugarcane tops and inoculant
Characteristic Lactobacillus plantarum Lactobacillus brevis Weissella cibaria Lactococcus lactlis Pediococcus acidilactici Lactobacillus plantarum
Representative strain MB1 MB14 MB6 MB52 MB38 FG
Isolated source Corn stover Sugarcane tops Corn stover Sugarcane tops Corn stover Inoculant
Shape Rod Rod Cocci Cocci Cocci Rod
Gram stain + + + + + +
Catalase
Gas from glucose + +
Lactate production in MRS broth (%) 1.96 1.31 0.67 0.45 0.92 0.92
Final pH in MRS broth 3.50 3.85 4.40 4.60 4.20 4.20
Fermentation type Homo Hetero Hetero Homo Homo Homo
Optical form of lactate DL DL D(−) L(+) DL DL
Growth at pH
 3.0
 3.5 +
 4.0 + + w
 4.5 + + + w + +
 5.0 + + + + + +
Carbohydrate fermentation patterns
 L-Arabinose + + w + +
 Ribose + + + + +
 D-Xylose + w + +
 Galactose + + + +
 D-Mannose + + + + +
 Mannitol + + +
 α Methyl-D-mannoside + +
 Amygdaline + + + + +
 16S rDNA similarity with each type strain (%) 100.00 99.80 99.90 99.80 99.90 99.90

+, positive; −, negative; w, weakly positive.

Carbohydrate fermentation pattern was tested by AP 50 CH; the sequence similarity of 16S rDNA of isolates were compared with sequences from each type strains of LAB held in the GenBank.

Table 4
Chemical composition of corn stover and sugarcane top silage after 60 d of fermentation
Items OM CP EE NDF ADF ADL

--------------------------------------------------------------------- % of DM ------------------------------------------------------------------------
Corn stover
 Control 91.98±5.38 6.44±0.59 1.28±0.27 64.69±0.62a 36.11±0.28a 2.95±0.35ab
 LAB 91.01±0.40 5.99±0.10 1.61±0.33 64.54±0.54a 36.09±0.16a 3.26±0.98a
 Cellulase 88.84±3.30 6.57±0.45 1.33±0.17 59.67±1.04b 33.53±0.59b 2.05±0.41b
 LAB+cellulase 88.14±4.52 6.53±0.94 1.42±0.34 60.49±0.79b 33.29±0.83b 2.27±0.25ab
Sugarcane top
 Control 92.76±2.05 6.21±0.83 1.63±0.56 77.89±1.58a 46.22±0.97a 4.05±0.53a
 LAB 94.70±1.22 6.00±0.09 1.95±0.15 76.16±0.82ab 44.80±1.67ab 4.29±0.24a
 Cellulase 93.25±0.66 6.28±0.52 1.83±0.62 74.97±0.34b 43.34±1.27b 4.61±0.32a
 LAB+cellulase 93.90±0.35 6.05±0.37 1.86±0.28 74.79±1.78b 44.05±0.21ab 4.22±0.12a
 SEM 1.69 0.33 0.22 0.58 0.52 0.27
Forage means
 Corn stover 89.99±3.74b 6.38±0.57 1.41±0.27b 62.35±2.48b 34.75±1.48b 2.63±0.71b
 Sugarcane top 93.65±1.31a 6.14±0.46 1.82±0.40a 75.95±1.68a 44.60±1.49a 4.29±0.36a
Additive means
 Control 92.37±3.66 6.32±0.65 1.45±0.44 71.29±7.31a 41.16±5.57a 3.50±0.72
 LAB 92.85±2.34 6.00±0.09 1.78±0.30 70.35±6.39a 40.44±4.88a 3.77±0.85
 Cellulase 91.04±3.22 6.42±0.46 1.58±0.49 67.32±8.41b 38.43±5.45b 3.33±1.44
 LAB+cellulase 91.02±4.27 6.29±0.69 1.64±0.37 67.64±7.93b 38.67±5.92b 3.24±1.08
Significance of main effects and interactions
 Crops (C) 0.0073 0.3059 0.0164 <0.0001 <0.0001 <0.0001
 Additives (A) 0.6179 0.6037 0.5185 <0.0001 0.0001 0.2580
 C×A 0.5234 0.8975 0.9777 0.0445 0.2932 0.0344

Data are means of three silage samples.

OM, organic matter; CP, crude protein; EE, ether extract; NDF, neutral detergent fiber; ADF, acid detergent fiber; ADL, acid detergent lignin; DM, dry matter; LAB, lactic acid bacteria inoculant FG; Cellulase, Acremonium cellulase; SEM, standard error of the mean.

a,b Means±standard deviation within columns with different superscript letters differ significantly from each other (p<0.05).

Table 5
Fermentation quality of corn stover and sugarcane top silage after 60 d of fermentation
Items DM % pH Lactic acid Acetic acid Propionic acid Butyric acid Ammonia-N (g/kg of DM)

-------------------------------------- % of DM -------------------------------------
Corn stover
 Control 31.69±3.05 3.93±0.13a 5.00±0.91a 1.19±0.21a 0.04±0.03a 0.01±0.01b 0.68±0.14
 LAB 31.07±1.78 3.95±0.22a 5.14±1.56a 1.06±0.16a 0.06±0.03a 0.03±0.04b 0.59±0.09
 Cellulase 31.02±1.29 3.95±0.07a 4.87±0.74a 1.17±0.12a 0.09±0.05a 0.12±0.05a 0.77±0.15
 LAB+cellulase 33.19±2.00 3.97±0.12a 4.14±0.62a 1.10±0.11a 0.02±0.01a 0.11±0.03a 0.76±0.14
Sugarcane top
 Control 27.33±2.67 4.71±0.08a 0.61±0.30b 1.58±0.14a 0.10±0.02a 2.49±0.79a 1.11±0.11
 LAB 27.71±0.04 3.86±0.08b 4.82±0.41a 0.77±0.17c 0.05±0.01b 0.46±0.23b 0.67±0.07
 Cellulase 25.51±0.41 4.09±0.32b 3.72±1.57a 1.43±0.15ab 0.09±0.04ab 0.81±0.50b 0.83±0.10
 LAB+cellulase 27.73±1.20 4.06±0.05b 3.30±0.42a 1.17±0.22b 0.06±0.01ab 0.96±0.23b 0.73±0.07
 SEM 1.06 0.09 0.54 0.10 0.02 0.20 0.06
Crop means
 Corn stover 31.74±2.03a 3.95±0.12b 4.79±0.96a 1.13±0.14 0.05±0.04 0.07±0.06b 0.70±0.13
 Sugarcane top 27.07±1.58b 4.18±0.37a 3.11±1.77b 1.24±0.35 0.08±0.03 1.18±0.92a 0.84±0.19
Additive means
 Control 29.51±3.50 4.32±0.44a 2.80±0.48c 1.39±0.26a 0.07±0.04ab 1.25±0.45a 0.90±0.26
 LAB 29.39±2.16 3.91±0.16b 4.98±1.03a 0.92±0.21c 0.05±0.02ab 0.24±0.28b 0.63±0.08
 Cellulase 28.27±3.14 4.02±0.22b 4.30±1.26ab 1.30±0.19ab 0.09±0.04a 0.46±0.12b 0.80±0.12
 LAB+cellulase 30.46±3.33 4.01±0.10b 3.72±0.66bc 1.14±0.16b 0.04±0.03b 0.54±0.49b 0.75±0.10
Significance of main effects and interactions
 Crops (C) <0.0001 0.0027 0.0005 0.1258 0.0664 <0.0001 0.0088
 Additives (A) 0.2679 0.0024 0.0073 0.0008 0.0434 0.0008 0.0071
 C×A 0.7099 0.0012 0.0072 0.0160 0.2706 0.0005 0.0111

Data are means of three silage samples.

DM, dry matter; LAB, lactic acid bacteria inoculant FG; Cellulase, Acremonium cellulase; SEM, standard error of the mean.

a–c Means±standard deviation within columns with different superscript letters differ significantly from each other (p<0.05).

Table 6
Microbial population of corn stover and sugarcane top silage after 60 d of fermentation
Item Lactic acid bacteria Aerobic bacteria Coliform bacteria Yeasts Molds

------------------------------------------------------------- Log10 cfu /g of FM -----------------------------------------------------------------
Corn stover
 Control 6.31±0.72a 5.02±0.74a ND 5.44±0.58a ND
 LAB 6.41±0.40a 4.33±0.47a ND 5.57±0.20a ND
 Cellulase 6.43±0.43a 5.31±0.87a ND 5.30±0.42a ND
 LAB+cellulase 6.52±0.20a 4.90±0.52a ND 5.54±0.24a ND
Sugarcane top
 Control 4.33±0.39d 5.48±0.33a ND 4.23±0.56a ND
 LAB 7.22±0.26a 3.08±0.06c ND 3.61±0.21b ND
 Cellulase 5.48±0.35c 4.73±0.08b ND 4.60±0.23a ND
 LAB+cellulase 6.38±0.46b 3.43±0.25c ND 3.00±0.13b ND
 SEM 0.25 0.29 - 0.21 -
Crop means
 Corn stover 6.42±0.41a 5.32±1.06a - 5.46±0.35a -
 Sugarcane top 5.85±1.17b 4.18±1.03b - 4.14±0.54b -
Additive means - -
 Control 5.32±0.39c 6.12±0.33a - 4.83±0.56a -
 LAB 6.81±0.26a 3.70±0.06c - 4.59±0.21ab -
 Cellulase 5.96±0.35b 5.02±0.08b - 4.95±0.23a -
 LAB+cellulase 6.45±0.46c 4.17±0.25c - 4.27±0.13b -
Significance of main effects and interactions
 Crops (C) 0.0052 0.0030 - <0.0001 -
 Additives (A) <0.0001 0.0002 - 0.0213 -
 C×A 0.0003 0.0174 - 0.0021 -

Data are means of three silage samples.

cfu, colony-forming unit; FM, fresh matter; ND, not detected; LAB, lactic acid bacteria inoculant FG; Cellulase, Acremonium cellulase; SEM, standard error of the mean; - means the value is zero.

a–d Means±standard deviation within columns with different superscript letters differ significantly from each other (p<0.05).

REFERENCES

1. Khota W, Pholsen S, Higgs D, Cai Y. Natural lactic acid bacteria population of tropical grasses and their fermentation factor analysis of silage prepared with cellulase and inoculant. J Dairy Sci 2016; 99:9768–81. https://doi.org/10.3168/jds.2016-11180
crossref pmid
2. Wiedmeier RD, Provenza FD, Burritt EA. Exposure to ammoniated wheat straw as suckling calves improves performance of mature beef cows wintered on ammoniated wheat straw. J Anim Sci 2002; 80:2340–8. https://doi.org/10.1093/ansci/80.9.2340
crossref pmid
3. Martin NP, Russelle MP, Powell JM, et al. Invited review: Sustainable forage and grain crop production for the US dairy industry. J Dairy Sci 2017; 100:9479–94. https://doi.org/10.3168/jds.2017-13080
crossref pmid
4. FAO Statistical databases (FAOSTAT). Statistical materials of agriculture, fishery and forestry [Internet]. Teikoku-Shyoin Co., Ltd.; c2016. [cited 2016 Dec 21]. Available from: http://www.fao.org/faostat/en/#home

5. Chen J, Stokes MR, Wallace CR. Effects of enzyme-inoculant systems on preservation and nutritive value of hay crop and corn silages. J Dairy Sci 1994; 77:501–12. https://doi.org/10.3168/jds.S0022-0302(94)76978-2
crossref pmid
6. Goncales M, Nunhes TV, Barbosa LCFM, de Campos FC, de Oliveira OJ. Opportunities and challenges for the use of cleaner production to reduce water consumption in brazilian sugar-energy plants. J Clean Prod 2018; 186:353–63. https://doi.org/10.1016/j.jclepro.2018.03.114
crossref
7. Hauser S, Nolte C, Carsky RJ. What role can planted fallows play in the humid and sub-humid zone of west and central Africa? Nutr Cycl Agroecosyst 2006; 76:297–318. https://doi.org/10.1007/s10705-005-5630-4
crossref
8. Zhao XL, Liu JH, Liu JJ, et al. Effect of ensiling and silage additives on biogas production and microbial community dynamics during anaerobic digestion of switchgrass. Bioresour Technol 2017; 241:349–59. https://doi.org/10.1016/j.biortech.2017.03.183
crossref pmid
9. Li J, Liu R, Chang G, et al. A strategy for the highly efficient production of docosahexaenoic acid by Aurantiochytrium limacinum SR21 using glucose and glycerol as the mixed carbon sources. Bioresour Technol 2015; 177:51–7. https://doi.org/10.1016/j.biortech.2014.11.046
crossref pmid
10. Cai Y. Analysis method for silage. Japanese Society of Grassland Science. Field and laboratory methods for grassland science. Tokyo, Japan: Tosho Printing Co., Ltd.; 2004. p. 279–82.

11. Kozaki M, Uchimura T, Okada S. Experimental manual for lactic acid bacteria. Tokyo, Japan: Tosho Printing Co., Ltd.; 1992. p. 29–72.

12. Tamaoka J, Komagata K. Determination of DNA-base composition by reversed-phase high-performance liquid-chromatography. FEMS Microbiol Lett 1984; 25:125–8. https://doi.org/10.1111/j.1574-6968.1984.tb01388.x
crossref pdf
13. Thompson JD, Higgins DG, Gibson TJ. Clustal-W: Improving the sensitivity of progressive multiple sequence alignment through sequence weighting, position-specific gap penalties and weight matrix choice. Nucleic Acids Res 1994; 22:4673–80. https://doi.org/10.1093/nar/22.22.4673
crossref pmid pmc pdf
14. Association of Official Agricultural Chemists (AOAC). Official methods of analysis of the AOAC International. 16th ed.Washington, MD, USA: AOAC International; 1995.

15. Van Soest PJ, Robertson JB, Lewis BA. Methods for dietary fiber, neutral detergent fiber, and nonstarch polysaccharides in relation to animal nutrition. J Dairy Sci 1991; 74:3583–97. https://doi.org/10.3168/jds.s0022-0302(91)78551-2
crossref pmid
16. Thomas T. An automated procedure for the determination of soluble carbohydrates in herbage. J Sci Food Agric 1977; 28:639–42. https://doi.org/10.1002/jsfa.2740280711
crossref
17. McDonald P, Henderson AR, Heron SJE. The biochemistry of silage. Marlow, UK: Chalcombe Publications; 1981.

18. Roe MB, Sniffen CJ, Chase LE. Techniques for measuring protein fractions in feedstuffs. Proceeing Cornell Nutrition. In : Conference for Feed Manufacturers Department of Animal and Poultry and Avian Sciences; NY, USA: Cornell University; 1990. p. 81–8.

19. Licitra G, Hernandez TM, Van Soest PJ. Standardization of procedures for nitrogen fractionation of ruminant feeds. Anim Feed Sci Technol 1996; 57:347–58. https://doi.org/10.1016/0377-8401(95)00837-3
crossref
20. Khan RU, Rahman ZU, Javed I, Muhammad F. Effect of vitamins, probiotics and protein level on semen traits and seminal plasma biochemical parameters of post-moult male broiler breeders. Br Poult Sci 2013; 54:120–9. https://doi.org/10.1080/00071668.2012.753511
crossref pmid
21. Steel RG, Torrie JH. Principles and procedures of statistics: a biometrical approach. New York, USA: Mc Graw Hill Company; 1980.

22. Shao T, Ohba N, Shimojo M, Masuda Y. Effects of adding glucose, sorbic acid and pre-fermented juices on the fermentation quality of guineagrass (Panicum maximum jacq.) silages. Asian-Australas J Anim 2004; 17:808–13. https://doi.org/10.5713/ajas.2004.808
crossref pdf
23. Cai Y, Benno Y, Ogawa M, Kumai S. Effect of applying lactic acid bacteria isolated from forage crops on fermentation characteristics and aerobic deterioration of silage. J Dairy Sci 1999; 82:520–6. https://doi.org/10.3168/jds.S0022-0302(99)75263-X
crossref pmid
24. Wang Z, Dien BS, Rausch KD, Tumbleson ME, Singh V. Improving ethanol yields with deacetylated and two-stage pretreated corn stover and sugarcane bagasse by blending commercial xylose-fermenting and wild type Saccharomyces yeast. Bioresour Technol 2019; 282:103–9. https://doi.org/10.1016/j.biortech.2019.02.123
crossref pmid
25. Haag NL, Nagele HJ, Fritz T, Oechsner H. Effects of ensiling treatments on lactic acid production and supplementary methane formation of maize and amaranth–An advanced green biorefining approach. Bioresour Technol 2015; 178:217–25. https://doi.org/10.1016/j.biortech.2014.08.048
crossref pmid
26. Weiss K, Kroschewski B, Auerbach H. Effects of air exposure, temperature and additives on fermentation characteristics, yeast count, aerobic stability and volatile organic compounds in corn silage. J Dairy Sci 2016; 99:8053–69. https://doi.org/10.3168/jds.2015-10323
crossref pmid
27. Khota W, Pholsen S, Higgs D, Cai Y. Comparative analysis of silage fermentation and in vitro digestibility of tropical grass prepared with Acremonium and Tricoderma species producing cellulases. Asian-Australas J Anim Sci 2018; 31:1913–22.
crossref pmid pmc pdf
28. Valbuena D, Tui SHK, Erenstein O, et al. Identifying determinants, pressures and trade-offs of crop residue use in mixed smallholder farms in sub-saharan africa and south asia. Agric Syst 2015; 134:107–18. https://doi.org/10.1016/j.agsy.2014.05.013
crossref


Editorial Office
Asian-Australasian Association of Animal Production Societies(AAAP)
Room 708 Sammo Sporex, 23, Sillim-ro 59-gil, Gwanak-gu, Seoul 08776, Korea   
TEL : +82-2-888-6558    FAX : +82-2-888-6559   
E-mail : editor@animbiosci.org               

Copyright © 2024 by Asian-Australasian Association of Animal Production Societies.

Developed in M2PI

Close layer
prev next