Next Article in Journal
Ground Frosts in Poland in the Growing Season
Next Article in Special Issue
Freshwater Cladophora glomerata Biomass as Promising Protein and Other Essential Nutrients Source for High Quality and More Sustainable Feed Production
Previous Article in Journal
IoFarm in Field Test: Does a Cost-Optimal Choice of Fertilization Influence Yield, Protein Content, and Market Performance in Crop Production?
Previous Article in Special Issue
Enhanced Ruminal Fermentation Parameters and Altered Rumen Bacterial Community Composition by Formulated Rumen Buffer Agents Fed to Dairy Cows with a High-Concentrate Diet
 
 
Search for Articles:
Title / Keyword
Author / Affiliation / Email
Journal
Article Type
 
 
Advanced Search
 
Section
Special Issue
Volume
Issue
Number
Page
 
Journals
Agriculture
Volume 11
Issue 7
10.3390/agriculture11070572
agriculture-logo
Submit to this Journal Review for this Journal Propose a Special Issue
► Article Menu

Article Menu

share Share announcement Help format_quote Cite question_answer Discuss in SciProfiles
first_page
settings
Order Article Reprints
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
Article

Effect of Red Orange and Lemon Extract-Enriched Diet in Suckling Lambs’ Fecal Microbiota

by
Massimo Ferrara
1,
Maria Federica Sgarro
2,
Aristide Maggiolino
2,*,
Sara Damiano
3,4,
Francesco Iannaccone
5,
Giuseppina Mulè
1 and
Pasquale De Palo
2
1
Institute of Sciences of Food Production (ISPA), National Research Council (CNR), Via G. Amendola 122/O, 70126 Bari, Italy
2
Department of Veterinary Medicine, University “Aldo Moro” of Bari, 70010 Valenzano, Italy
3
Department of Veterinary Medicine and Animal Productions, University of Naples “Federico II”, Via Federico Delpino n.1, 80137 Naples, Italy
4
Task Force of Microbiome Studies, University of Naples “Federico II”, 80137 Naples, Italy
5
Department of Agricultural and Environmental Science, University “Aldo Moro” of Bari, Via G. Amendola, 165/A, 70126 Bary, Italy
*
Author to whom correspondence should be addressed.
Agriculture 2021, 11(7), 572; https://doi.org/10.3390/agriculture11070572
Submission received: 4 May 2021 / Revised: 10 June 2021 / Accepted: 18 June 2021 / Published: 22 June 2021
(This article belongs to the Special Issue Improvement and Innovation in the Nutritional Quality and Technologies of Animal Feed)
Browse Figures
Versions Notes

Abstract

:
Red orange and lemon extract (RLE) is an anthocyanins-rich dietary supplement that may influence gastrointestinal bacterial community in ruminants. The aim of the present study was to investigate the RLE effects on gut microbiota composition in lambs. Twenty-eight lambs were randomly divided into a control group (CON; n = 14) and an anthocyanin group (ANT; n = 14) and fed the same diet; additionally, only the ANT received 90 mg/kg live weight of RLE at day. After lamb slaughter (40 ± 1 days), fecal samples were collected from the rectum and stored at −20 °C until analysis. Analysis of fecal microbiome was carried out by metabarcoding analysis of 16S rRNA. After reads denoising, sequences were aligned against SILVA rRNA sequence database using MALT, and taxonomic binning was performed with MEGAN. A significant increase in Firmicutes and Bacteroidetes and a decrease in Proteobacteria and Actinobacteria was observed in ANT compared to CON. Moreover, an interesting increase of Lactobacillus and Bifidobacterium genera and a decrease in Escherichia coli and Salmonella species were detected in ANT compared to CON. Results recommend that anthocyanin supplementation in lamb diet is able to modulate positively gut microbiota and may inhibit the growth of some potential pathogenic microorganisms.

1. Introduction

Mammals’ gut microbiota affects a wide range of host physiological functions, including digestion, stress adaption and immune response regulation [1,2]. Thus, gut microbial imbalance may cause health disorders in the host [3,4]. Investigation of ruminant gut microbiota represents a main aspect considering its responsibility for feed digestion but also its importance in physiological and immune functions [5]. In ruminants, the gastrointestinal tract harbors a high-density and -diversity microbiota composed of species and genera belonging to bacteria, archaea, fungi, ciliate protozoa and viruses (approximately 1011 microbial cells per gram of digesta) [6]. The ruminants’ gut microbiota is composed of trillions of microorganisms, and is the most complicated microecosystem [7]. Its composition is driven by various factors, like host genetic variations, weaning, diets, and stochastic events [8,9]. It plays a key role in pathogenic Gram-negative bacteria mucosal immunity, nutrient absorption and intestinal epithelium differentiation [7]. Among these, weaning plays a pivotal role in the establishment of a functional bacterial community in young animals. In the postnatal life, from birth to weaning, lambs are defined as functional monogastric, since they are born without a functional rumen, and the symbiotic ruminal microbial community is not established until the first months of life [10,11]. In pre-weaned lamb, milk is the main nourishment, which bypasses the rumen, due to the activation of the esophageal groove, and undergoes digestion in the abomasum and intestine [11]. The gut microbial community in 30-days lambs was previously shown to be heterogenous, with Lactobacillaceae (phylum Firmicutes) being predominant. Some other Firmicutes families exhibiting a remarkable abundance in the gut were Lachnospiraceae, Clostridiaceae, and Ruminococcaceae [12]. At weaning, lambs undergo a drastic change in nutrient intake from milk to a plant-based carbohydrates diet, and this transition phase may lead to sequential changes within microbial population of intestine [1,13]. It is known that dietary interventions in pre- and post-weaned lambs significantly affect the microbial community structure and functions, with likely consequences on physiological and practical implications for animal health [14,15]. These may include the use of plant matrices or plant-derived bioactive compounds as feed supplements, and several efforts have been addressed during the last decade to exploit agro-industrial by-products in animal diets. Researchers addressed their interest to phenolic compounds, for their ability to enhance the growth of specific beneficial bacteria and to exclude certain pathogenic microorganisms at gut level. Dietary anthocyanins may improve intestinal barrier functionality, enhance host/bacteria interaction, and promote the proliferation of beneficial bacteria such as Bifidobacterium spp. and Lactobacillus spp. [16]. These bacterial groups, actively involved in anthocyanin catabolism, exert antimicrobial effects towards pathogens microorganisms, and are usually associated to health benefit for the host [17,18]. According to Cheng et al. [19], phenolic compounds from blueberry pomace may contribute to reshaping the structure and diversity of fecal microbiota community. Moreover, phenolics-rich blueberries extracts had inhibitory effects on some Gram-positive (Listeria monocytogenes, Bacillus subtilis, and Enterococcus faecalis) and Gram-negative bacteria (Escherichia coli and Salmonella enterica ser. Typhimurium) [20]. In pigs supplemented with grape seeds extract, ecological changes in gut microbial population, with a dramatic increase in Lachnospiraceae, Clostridales, Lactobacillus and Ruminococcacceae, was recorded [21]. Cranberry and olive by-products were also shown to modulate the composition of gut microbiota and improve its integrity in broiler chicken [22,23].
Within this framework, our study proposed a metagenomic approach to investigate the effect of anthocyanin-rich red orange and lemon extracts (RLE) on lamb gut microbiota. Red orange (Citrus sinensis L.) and lemon (Citrus limon L.) peels are food industry by-products resulting from mechanical pulp removal and juice extraction [24]. Citrus by-products have a broad spectrum of application in pharmaceutical, nutraceutical, and food industries [25]. Their inherent chemical composition and the high content in phenolic compounds make citrus extracts suitable as a supplement in ruminant diets [26,27]. To the best of our knowledge, information about the effects of RLE on weaning lambs gut microbial ecology is lacking.

2. Materials and Methods

2.1. Animal Management and Feeding

The experiment was authorized by the Animal Welfare Organization of the University of Naples Federico II (PG/2019/0028161 of 03/19/2019).
The experimental procedures were carried out at the experimental farm of the Council for Agricultural Research and Economics, Research Centre of Animal Production and Aquaculture (CREA-ZA, Bella, PZ, Italy). Twenty-eight Merino male lambs were natural suckled and, from 25 days of life until slaughtering (40 ± 1 days), they were fed with ad libitum alfalfa hay (188 g/kg crude protein DM, 322 g/kg crude fiber DM) and starter (205 g/kg crude protein DM, 18 g/kg fat DM, 250 g/kg crude fiber DM). Feed chemical composition was determined according to the methods described by Maggiolino et al. [28]. At the start of the present trial, all animals were in good health; no disease was diagnosed during and at the end of the treatments.
After natural colostrum administration, within 2 h from birth, all lambs were randomly subdivided into two treatment groups: one group received the RLE (ANT; n = 14), and the control group (CON; n = 14) did not receive the additive. During their life, until slaughter (40 ± 1 days), the lambs were permanently housed indoors. The daily intake was calculated daily from the unconsumed feed before the next feeding. It was of 65 g/day and 68 g/day of starter and of 18 g/day and 20 g/day of hay, respectively, for the ANT and CON groups. Each lamb received 90 mg/kg of live weight of RLE once daily. The supplement was orally administered to each lamb of the ANT group. It was mixed with water to obtain a cream [28], which was then administered directly in the mouth using a large syringe. All animals were weighed every 2 days at the same time (7:00 a.m.) and the correct amount of RLE that had to be administered to each ANT lamb was quantified.

2.2. Composition of Red Orange and Lemon Extract

The additive (dry powder) was obtained by a patented extraction process (Italian Patent No. 102017000057761) from red orange and lemon processing wastes. It was created at CREA—Research Centre for Olive, Fruit and Citrus Crops (CREA-OFA, Acireale, Italy), for research purposes only. The separation of anthocyanins content was performed as described by Maggiolino et al. [29]. The RLE chemical composition is shown in Table 1.

2.3. Fecal Sampling and Microbiome Analysis

All lambs were slaughtered in a slaughterhouse approved by the European Community. Fecal samples were collected soon after stunning and jugulation, before evisceration procedures, directly from the rectal ampoule using digital rectal retrieval. All samples were stored immediately at −80 °C until analysis.
Fecal samples were subjected to DNA extraction and 16S rRNA sequencing. For 16S rRNA gene amplicon sequencing, the bacterial V4 regions were amplified from extracted DNA by using the universal primers 515F (5′-GTGCCAGCMGCCGCGGTAA-3′) and 806R (5′-GGACTACVSGGGTATCTAAT-3′). The PCR reactions were carried out in triplicates using Platinum SuperFi DNA Polymerase (Invitrogen, Carlsbad, CA, USA) with the following conditions: 98 °C for 30 min, 25 cycles of 98 °C for 10 s, 58 °C for 20 s and 72 °C for 30 s and a final extension of 72 °C for 5 min. Amplified libraries were verified on 2% agarose gel and PCR products were purified using Agencourt AMPure XP magnetic beads (Agencourt Bioscience, Beverly, MA, USA). Purified libraries were quantified with Qubit dsDNA HS Assay Kit (Invitrogen, Carlsbad, CA, USA) and pooled at a final concentration of 100 pM. Libraries were sequenced on an Ion S5 Sequencing System (Thermo-Fisher Scientific, Waltham, MA, USA). Quality filtered reads were aligned using MALT (v0.4.1) [30], against the SILVA rRNA sequence database (SSURef_NR99, release 128). Taxonomic binning was performed by using MEGAN software [31]. Core microbiome was calculated at genus level by MEGAN (sample threshold = 80%; class threshold = 1%).

2.4. Statistical Analysis

Statistical comparison of the relative abundance of taxonomic categories was performed using STAMP software [32] by two-sided G-test (w/Yates’ + Fisher’s) with asymptomatic confidence intervals (0.95) and the Benjamini–Hochberg False Discovery Rate (FDR) method (q-value < 0.05). Rank abundance and alpha and beta diversity indexes were estimated using Microbiome Analyst [33]. Moreover, principal coordinate analysis (PCoA) was calculated using the Bray–Curtis index. Hypothesis testing was conducted by the analysis of molecular variance (AMOVA) test (p < 0.05) [34].

3. Results

A total of 11,757,088 quality-filtered sequences with an average length of 291 bp were obtained from the 28 fecal samples. The abundance-based coverage estimators (ACE) and the alpha diversity index Chao1 indicated that the richness of the samples was increased by anthocyanins supplementation. A similar behavior was observed for Shannon and Simpson indexes, although less marked between the two groups (Figure S1). Taxonomic assignment identified a total of 11 different phyla among all fecal samples (Figure 1). Overall, the lamb fecal microbiota was dominated by the Proteobacteria and Firmicutes phyla, followed by Actinobacteria and Bacteroidetes.
Significant differences between groups at phylum level are reported in Figure 2.
The ANT group showed a reduced (q < 0.01) presence of Proteobacteria and Actinobacteria and increased (q < 0.01) presence of Firmicutes, Bacteroidetes, Verrucomicrobia, Candidatus Saccharibacteria and Euryarchaeota quantity. Differences at family level are reported in Figure 3.
Lambs fed with anthocyanin dietary supplementation showed higher (q < 0.01) quantity of Planococcaceae, Pseudomonadaceae, Moraxellaceae, Bacillaceae, Caulobacteraceae, Lactobacillaceae and Bifidobacteriaceae families and lower (q < 0.01) quantity of Enterobacteriaceae, Sptreptomycetaceae, Ruminococcaceae and Lachnospiraceae. Moreover, the anthocyanin addition slightly increased Micrococcaceae, Nocardiaceae, Xanthomonadaceae, Akkermansiaceae, Clostridiaceae, Promicromonosporaceae, Rhodobacteriaceae, Microbacteriaceae, Campylobacteriaceae, Carnobacteriaceae, Dermabacteraceae, Paenibacellaceae, Preptostreptococcaceae, Rhizobiaceae and Methanobacteriaceae families, reducing the Bacteroidaceae, Streptococcaceae, Staphylococcaceae, Peptococcaceae and Clostridiales families (q < 0.01). Figure 4 shows statistical differences between experimental groups at genus level.
Feces of lambs fed with anthocyanins were richer (q < 0.01) in microorganisms belonging to the Acinetobacter, Solibacillus, Paenisporosarcina, Pseudomonas, Brevundimonas, Lactobacillus and Bifidobacterium genera, and poorer (q < 0.01) of those belonging to Psychrobacter, Streptomyces, Sporosarcina, Enterobacter, Phocaeicola, Lelliottia, Blautia and Bacteroides genera. However, considering the common core microbiota of the control and anthocyanin groups was composed by Acinetobacter (50%), Psychrobacter (27%), Paenisporosarcina (10%), Enterobacter (8%) and Lelliottia (4%), as shown in Figure S2. Taking into account the unique genera identified in the two experimental groups, 14 and 23 unique taxa were detected in the control and anthocyanin groups, respectively (Table S1).
Principal coordinate analysis at species level showed that the microbial community profiles were almost similar, although some individuals had a distinct profile (Figure 5).
Differences at species level were reported in Figure 6.
Considering the total number of reads assigned at species level, AG recorded higher (q < 0.05) presence of Methanobrevibacter ruminantium and Bacteroides uniformis, but lower (q < 0.05) of Escherichia coli, Bacteroides caccae and Salmonella sp. 1681.

4. Discussion

Gut microbiota composition, especially in young ruminant, is very susceptible to modifications [14,35]. In the present study, a total of 11 different phyla were identified among all fecal samples. Regardless of the treatment, Proteobacteria and Firmicutes were the most abundant phyla (about 80% and 15% of the reads respectively), representing over 90% of the total reads, followed by Actinobacteria and Bacteroidetes. These phyla are predominant in mammal small intestine [36] and in chicken cecum intestine [37], but their proportion is influenced by multiple factors such as species, diet, age and genotype [38,39]. Similarly, Li et al. [7] reported that these phyla are the most abundant in goats gut microbiota, representing over 90% of the taxonomic groups identified; differently, some authors in lambs [40] and calves [41,42] reported that Firmicutes and Actinobacteria represented the most abundant phyla, covering about 90% of the groups identified. Particularly for ruminant, Firmicutes, and in particular Lactobacillus genus, play a pivotal role in fiber and cellulose degradation [43] and contribute to maintain microflora balance by counteracting pathogenic invasions [44]. On the contrary, Bacteroidetes degrade sugars and proteins, and are positively related to immune system effectiveness [45,46]. Differently, Proteobacteria mainly consists of Gram-negative bacteria and some of them are responsible for important pathologies, such as diarrhea and malabsorption, affecting the gastrointestinal system [47]; however, the amount of Proteobacteria in small ruminants, as in goat kids, decreased with increasing age [38]. The relative abundance of Proteobacteria and Firmicutes was 86.4% and 8.5% in the control group and 80.6% and 14.8% in anthocyanin group, respectively. Comparable results were obtained from a study conducted on male goats, fed adding condensed tannins to the diet, where the predominant phyla were Proteobacteria and Firmicutes, followed by Bacteroidetes [48]. Regardless of the age and feeding system, Proteobacteria and Firmicutes were detected as the dominant phyla also in goat kids [38]. Anthocyanin supplementation significantly decreased the percentage of Proteobacteria (−5.8%) and Actinobacteria (−1.4%), and increased, favourably, Firmicutes (+6.3%) and Bacteroidetes (+0.7%) compared to the control group, which could have positive effects on intestinal health and growth rates in lambs.
There was a significant reduction in the Enterobacteriaceae population (−9.5%) in the fecal microbiota of the lambs supplemented with anthocyanins compared to the control group. Although it is not fully elucidated the anthocyanins mechanism of action in the gut, it could be that these substances act by inhibiting some microorganism replication, favoring the replication of some other, probably inducing more availability of some substances that may act as prebiotics [49]. Enterobacteriaceae is a large family of Gram-negative bacteria that includes many commensal bacteria but also many spread pathogens such as Salmonella, E. coli, Shigella, Yersinia, Proteus [50], which could result in diarrhea, gastritis, vomiting, gastrointestinal ulcers and often death of the animal [47,51]. Although the Bifidobacteriaceae and Lactobacillaceae families are poorly represented in all samples, anthocyanin supplementation resulted in an increase in the presence of bacteria belonging to the Lactobacillaceae (+0.5%) and Bifidobacterium (+0.3%) family compared to the control group.
A total of 27 genera were identified in the fecal samples. Important differences in composition were observed for the genus level between the groups. The most represented genera were Psychrobacter (36.5% and 4.5% for the control and anthocyanin group, respectively) and Acinetobacter (21.8% and 50.5% for the control and anthocyanin group, respectively), representing together more than 50% for both experimental groups. Interestingly, the decrease in Enterobacter and the increase in Bifidobacterium and Lactobacillus were observed in the anthocyanin group. In fact, both Bifidobacterium and Lactobacillus are well-known beneficial microbiota [52], also representing spread probiotic matrices sold on the market [53]. Bifidobacterium has been reported to stimulate the early development of gut regulating its microbial homeostasis, inhibiting pathogens and modulating local and systemic immune responses, improving vitamins production and increasing the bioconversion of dietary components to active compounds [54]. Lactobacillus has been linked to immune system improvement in young calves [55]. Some studies reported that these bacteria in young ruminants are able to increase weight gain and to decrease feed conversion ratio [56,57], as reported for kids fed with anthocyanins administration by Salzano et al. [58]. Lactobacillus and Bifidobacterium have an antagonist activity on some potential pathogens like Salmonella, E. coli and Clostridium perfrigens [59]. Escherichia is a commensal bacterium in the intestinal microbiota, although some strains are harmless, while other ones can provoke intestinal diseases, diarrhea and inflammatory events, that represented the main cause of morbidity and mortality in new-born ruminants [56,60]. The Escherichia coli species and Salmonella spp. bacteria were significantly lower in the anthocyanin group, showing a positive effect of additive. This is an important result for the intestinal health of lambs, digestibility and for the growth rate of young animals, showing a positive effect of anthocyanins administration. Furthermore, a reduction in E. coli could significantly reduce the risk of transmission of food poisoning from animals to humans [61]. The low percentage of E. coli in the anthocyanin group could be explained by the antimicrobial activity of anthocyanins and phenolic compounds [62], but the inhibition mechanism is not yet fully known [49]. Some studies reported the Bifidobacterium and Lactobacillus effect in hindering the Escherichia attachment to the epithelial cell surface, reducing indices of intestinal disease [63,64].

5. Conclusions

The administration of a red orange and lemon extract in suckling lambs induced changes in their gut microbiota, with a favorable increase of bacteria belonging to the Firmicutes phylum and Bifidobacterium and Lactobacillus genera and a decrease in potentially pathogenic bacteria such as E. coli and Salmonella spp. This should be considered as a potential way for reducing the use of antimicrobial substances, as well as improving animals’ health and welfare status.

Supplementary Materials

The following are available online at https://www.mdpi.com/article/10.3390/agriculture11070572/s1, Figure S1: Alpha diversity indexes (ACE, Chao1, Shannon, Simpson) of bacterial species assigned for anthocyanins and control group, Figure S2: Relative abundance and taxonomic assignments at genus level of the core microbiota common to the control and anthocyanins group, Table S1: List of unique taxa detected in control and anthocyanins group.

Author Contributions

Conceptualization, M.F., A.M. and P.D.P.; methodology, M.F., M.F.S., S.D. and F.I.; software, M.F.; validation, P.D.P. and G.M.; formal analysis, M.F. and S.D.; investigation, A.M., M.F. and P.D.P.; resources, P.D.P.; data curation, M.F. and M.F.S.; writing—original draft preparation, A.M., M.F.S. and M.F.; writing—review and editing, P.D.P. and G.M.; visualization, P.D.P. and G.M.; supervision, S.D. project administration, P.D.P. and A.M.; funding acquisition, P.D.P. All authors have read and agreed to the published version of the manuscript.

Funding

This research was funded by grants of the PSR Basilicata Region (ACCASATA Project), grant number E66C18000440002.

Institutional Review Board Statement

The study was conducted according to the guidelines of the Declaration of Helsinki and approved by the Animal Welfare Organization of the University of Naples Federico II (PG/2019/0028161 of 03/19/2019).

Data Availability Statement

The sequence data are available at NCBI SRA under BioProject ID: PRJNA726662.

Acknowledgments

The authors want to thank Giovanna Calzaretti and Francesco Giannico of the Department of Veterinary Medicine of the University of Bari for their help.

Conflicts of Interest

The authors declare no conflict of interest.

References

  1. Wang, Y.; Zhang, H.; Zhu, L.; Xu, Y.; Liu, N.; Sun, X.; Hu, L.; Huang, H.; Wei, K.; Zhu, R. Dynamic Distribution of Gut Microbiota in Goats at Different Ages and Health States. Front. Microbiol. 2018, 9, 2509. [Google Scholar] [CrossRef]
  2. Flint, H.J.; Duncan, S.H.; Scott, K.P.; Louis, P. Interactions and competition within the microbial community of the human colon: Links between diet and health. Environ. Microbiol. 2007, 9, 1101–1111. [Google Scholar] [CrossRef]
  3. Kuhn, K.A.; Stappenbeck, T.S. Peripheral education of the immune system by the colonic microbiota. Semin. Immunol. 2013, 25, 364–369. [Google Scholar] [CrossRef] [Green Version]
  4. Russell, J.B.; Rychlik, J.L. Factors That Alter Rumen Microbial Ecology. Science 2001, 292, 1119–1122. [Google Scholar] [CrossRef] [PubMed]
  5. Sommer, F.; Bäckhed, F. The gut microbiota—masters of host development and physiology. Nat. Rev. Microbiol. 2013, 11, 227–238. [Google Scholar] [CrossRef]
  6. Henderson, G.; Cox, F.; Kittelmann, S.; Miri, V.; Zethof, M.; Noel, S.; Waghorn, G.; Janssen, P. Effect of DNA Extraction Methods and Sampling Techniques on the Apparent Structure of Cow and Sheep Rumen Microbial Communities. PLoS ONE 2013, 8, e74787. [Google Scholar] [CrossRef] [Green Version]
  7. Li, A.; Yang, Y.; Qin, S.; Lv, S.; Jin, T.; Li, K.; Han, Z.; Li, Y. Microbiome analysis reveals gut microbiota alteration of early-weaned Yimeng black goats with the effect of milk replacer and age. Microb. Cell Factories 2021, 20, 78. [Google Scholar] [CrossRef]
  8. Morgavi, D.P.; Rathahao-Paris, E.; Popova, M.; Boccard, J.; Nielsen, K.F.; Boudra, H. Rumen microbial communities influence metabolic phenotypes in lambs. Microb. Cell Factories 2015, 20, 1–14. [Google Scholar] [CrossRef] [Green Version]
  9. Benson, A.K.; Kelly, S.A.; Legge, R.; Ma, F.; Low, S.J.; Kim, J.; Zhang, M.; Oh, P.L.; Nehrenberg, D.; Hua, K.; et al. Individuality in gut microbiota composition is a complex polygenic trait shaped by multiple environmental and host genetic factors. Proc. Natl. Acad. Sci. USA 2010, 107, 18933–18938. [Google Scholar] [CrossRef] [Green Version]
  10. Lane, M.A.; Baldwin, R.L., IV; Jesse, B.W. Developmental changes in ketogenic enzyme gene expression during sheep rumen development1. J. Anim. Sci. 2002, 80, 1538–1544. [Google Scholar] [CrossRef]
  11. Huws, S.A.; Creevey, C.J.; Oyama, L.B.; Mizrahi, I.; Denman, S.E.; Popova, M.; Muñoz-Tamayo, R.; Forano, E.; Waters, S.M.; Hess, M.; et al. Addressing Global Ruminant Agricultural Challenges Through Understanding the Rumen Microbiome: Past, Present, and Future. J. Anim. Sci. 2018, 80, 1538–1544. [Google Scholar] [CrossRef]
  12. Palomba, A.; Tanca, A.; Fraumene, C.; Abbondio, M.; Fancello, F.; Atzori, A.S.; Uzzau, S. Multi-Omic Biogeography of the Gastrointestinal Microbiota of a Pre-Weaned Lamb. Front. Microbiol. 2017, 5, 36. [Google Scholar] [CrossRef] [Green Version]
  13. Meale, S.J.; Li, S.; Azevedo, P.; Derakhshani, H.; Plaizier, J.C.; Khafipour, E.; Steele, M.A. Development of Ruminal and Fecal Microbiomes Are Affected by Weaning But Not Weaning Strategy in Dairy Calves. Front. Microbiol. 2016, 7, 582. [Google Scholar] [CrossRef] [Green Version]
  14. Lyons, T.; Boland, T.; Storey, S.; Doyle, E. Linseed Oil Supplementation of Lambs’ Diet in Early Life Leads to Persistent Changes in Rumen Microbiome Structure. Front. Microbiol. 2017, 8, 1656. [Google Scholar] [CrossRef] [Green Version]
  15. Huang, Q.; Holman, D.B.; Alexander, T.; Hu, T.; Jin, L.; Xu, Z.; McAllister, T.A.; Acharya, S.; Zhao, G.; Wang, Y. Fecal microbiota of lambs fed purple prairie clover (Dalea purpurea Vent.) and alfalfa (Medicago sativa). Arch. Microbiol. 2018, 200, 137–145. [Google Scholar] [CrossRef]
  16. Boto-Ordóñez, M.; Urpi-Sarda, M.; Queipo-Ortuño, M.I.; Tulipani, S.; Tinahones, F.J.; Andres-Lacueva, C. High levels of Bifidobacteria are associated with increased levels of anthocyanin microbial metabolites: A randomized clinical trial. Food Funct. 2014, 5, 1932–1938. [Google Scholar] [CrossRef] [Green Version]
  17. Ma, Y.; Ding, S.; Fei, Y.; Liu, G.; Jang, H.; Fang, J. Antimicrobial activity of anthocyanins and catechins against foodborne pathogens Escherichia coli and Salmonella. Food Control. 2019, 106, 106712. [Google Scholar] [CrossRef]
  18. Anhê, F.F.; Roy, D.; Pilon, G.; Dudonné, S.; Matamoros, S.; Varin, T.V.; Garofalo, C.; Moine, Q.; Desjardins, Y.; Levy, E.; et al. A polyphenol-rich cranberry extract protects from diet-induced obesity, insulin resistance and intestinal inflammation in association with increased Akkermansia spp. population in the gut microbiota of mice. Gut 2015, 64, 872–883. [Google Scholar] [CrossRef] [Green Version]
  19. Cheng, Y.; Wu, T.; Chu, X.; Tang, S.; Cao, W.; Liang, F.; Fang, Y.; Pan, S.; Xu, X. Fermented blueberry pomace with antioxidant properties improves fecal microbiota community structure and short chain fatty acids production in an in vitro mode. LWT Food Sci. Tehnol. 2020, 125, 109260. [Google Scholar] [CrossRef]
  20. Puupponen-Pimiä, R.; Nohynek, L.; Hartmann-Schmidlin, S.; Kähkönen, M.; Heinonen, M.; Määttä-Riihinen, K.; Oksman-Caldentey, K.-M. Berry phenolics selectively inhibit the growth of intestinal pathogens. J. Appl. Microbiol. 2005, 98, 991–1000. [Google Scholar] [CrossRef]
  21. Choy, Y.Y.; Quifer-Rada, P.; Holstege, D.M.; Frese, S.A.; Calvert, C.C.; Mills, D.A.; Lamuela-Raventos, R.M.; Waterhouse, A.L. Phenolic metabolites and substantial microbiome changes in pig feces by ingesting grape seed proanthocyanidins. Food Funct. 2014, 5, 2298–2308. [Google Scholar] [CrossRef]
  22. Herrero-Encinas, J.; Blanch, M.; Pastor, J.J.; Mereu, A.; Ipharraguerre, I.R.; Menoyo, D. Effects of a bioactive olive pomace extract from Olea europaea on growth performance, gut function, and intestinal microbiota in broiler chickens. Poult. Sci. 2020, 99, 2–10. [Google Scholar] [CrossRef] [PubMed]
  23. Islam, M.R.; Hassan, Y.I.; Das, Q.; Lepp, D.; Hernandez, M.; Godfrey, D.V.; Orban, S.; Ross, K.; Delaquis, P.; Diarra, M.S. Dietary organic cranberry pomace influences multiple blood biochemical parameters and cecal microbiota in pasture-raised broiler chickens. J. Funct. Foods 2020, 72, 104053. [Google Scholar] [CrossRef]
  24. Ghasemi, K.; Ghasemi, Y.; Ebrahimzadeh, M.A. Antioxidant activity, phenol and flavonoid contents of 13 citrus species peels and tissues. Pak. J. Pharm. Sci. 2009, 22, 277–281. [Google Scholar] [PubMed]
  25. Mahato, N.; Sharma, K.; Sinha, M.; Cho, M.H. Citrus waste derived nutra-/pharmaceuticals for health benefits: Current trends and future perspectives. J. Funct. Foods 2018, 40, 307–316. [Google Scholar] [CrossRef]
  26. Yang, X.-Y.; Xie, J.-X.; Wang, F.-F.; Zhong, J.; Liu, Y.-Z.; Li, G.-H.; Peng, S.-A. Comparison of ascorbate metabolism in fruits of two citrus species with obvious difference in ascorbate content in pulp. J. Plant Physiol. 2011, 168, 2196–2205. [Google Scholar] [CrossRef] [PubMed]
  27. Bampidis, V.A.; Robinson, P.H. Citrus by-products as ruminant feeds: A review. Anim. Feed. Sci. Technol. 2006, 128, 175–217. [Google Scholar] [CrossRef]
  28. Maggiolino, A.; Lorenzo, J.M.; Quiñones, J.; Latorre, M.A.; Blando, F.; Centoducati, G.; Dahl, G.E.; De Palo, P. Effects of dietary supplementation with Pinus taeda hydrolyzed lignin on in vivo performances, in vitro nutrient apparent digestibility, and gas emission in beef steers. Anim. Feed. Sci. Technol. 2019, 255, 114217. [Google Scholar] [CrossRef]
  29. Maggiolino, A.; Bragaglio, A.; Salzano, A.; Rufrano, D.; Claps, S.; Sepe, L.; Damiano, S.; Ciarcia, R.; Dinardo, F.R.; Hopkins, D.L.; et al. Dietary supplementation of suckling lambs with anthocyanins: Effects on growth, carcass, oxidative and meat quality traits. Anim. Feed. Sci. Technol. 2021, 276, 114925. [Google Scholar] [CrossRef]
  30. Herbig, A.; Maixner, F.; Bos, K.I.; Zink, A.; Krause, J.; Huson, D.H. MALT: Fast alignment and analysis of metagenomic DNA sequence data applied to the Tyrolean iceman. bioRxiv 2016, 050559. [Google Scholar] [CrossRef] [Green Version]
  31. Huson, D.; Beier, S.; Flade, I.; Górska, A.; El-Hadidi, M.; Mitra, S.; Ruscheweyh, H.; Tappu, R. MEGAN Community Edition-Interactive Exploration and Analysis of Large-Scale Microbiome Sequencing Data. PLoS Comput. Biol. 2016, 12, e1004957. [Google Scholar] [CrossRef] [Green Version]
  32. Parks, D.H.; Beiko, R.G. Identifying biologically relevant differences between metagenomic communities. Bioinformatics 2010, 26, 715–721. [Google Scholar] [CrossRef] [Green Version]
  33. Dhariwal, A.; Chong, J.; Habib, S.; King, I.L.; Agellon, L.B.; Xia, J. MicrobiomeAnalyst: A web-based tool for comprehensive statistical, visual and meta-analysis of microbiome data. Nucleic Acids Res. 2017, 45, W180–W188. [Google Scholar] [CrossRef]
  34. Mengoni, A.; Bazzicalupo, M. The statistical treatment of data and the analysis of Molecular Variance (AMOVA) in molecular microbial ecology. Ann. Microbiol. 2002, 52, 95–101. [Google Scholar]
  35. Tanca, A.; Fraumene, C.; Manghina, V.; Palomba, A.; Abbondio, M.; Deligios, M.; Pagnozzi, D.; Addis, M.F.; Uzzau, S. Diversity and functions of the sheep faecal microbiota: A multi-omic characterization. Microb. Biotechnol. 2017, 10, 541–554. [Google Scholar] [CrossRef]
  36. Malmuthuge, N.; Griebel, P.J.; Guan, L.L. Taxonomic Identification of Commensal Bacteria Associated with the Mucosa and Digesta throughout the Gastrointestinal Tracts of Preweaned Calves. J. Appl. Environ. Microbiol. 2014, 80, 2021–2028. [Google Scholar] [CrossRef] [Green Version]
  37. Mancabelli, L.; Ferrario, C.; Milani, C.; Mangifesta, M.; Turroni, F.; Duranti, S.; Lugli, G.A.; Viappiani, A.; Ossiprandi, M.C.; van Sinderen, D.; et al. Insights into the biodiversity of the gut microbiota of broiler chickens. Environ. Microbiol. 2016, 18, 4727–4738. [Google Scholar] [CrossRef] [PubMed]
  38. Jiao, J.; Lu, Q.; Forster, R.J.; Zhou, C.; Wang, M.; Kang, J.; Tan, Z. Age and feeding system (supplemental feeding versus grazing) modulates colonic bacterial succession and host mucosal immune maturation in goats1. J. Anim. Sci. 2016, 94, 2506–2518. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  39. Li, K.; Mehmood, K.; Zhang, H.; Jiang, X.; Shahzad, M.; Dong, X.; Li, J. Characterization of fungus microbial diversity in healthy and diarrheal yaks in Gannan region of Tibet Autonomous Prefecture. Acta Trop. 2018, 182, 14–26. [Google Scholar] [CrossRef]
  40. Li, C.; Wang, W.; Liu, T.; Zhang, Q.; Wang, G.; Li, F.; Li, F.; Yue, X.; Li, T. Effect of Early Weaning on the Intestinal Microbiota and Expression of Genes Related to Barrier Function in Lambs. Front. Microbiol. 2018, 9, 1431. [Google Scholar] [CrossRef] [Green Version]
  41. Bi, Y.; Yang, C.; Diao, Q.; Tu, Y. Effects of dietary supplementation with two alternatives to antibiotics on intestinal microbiota of preweaned calves challenged with Escherichia coli K99. Sci. Rep. 2017, 7, 5439. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  42. Castro, J.J.; Gomez, A.; White, B.A.; Mangian, H.J.; Loften, J.R.; Drackley, J.K. Changes in the intestinal bacterial community, short-chain fatty acid profile, and intestinal development of preweaned Holstein calves. 1. Effects of prebiotic supplementation depend on site and age. J. Dairy Sci. 2016, 99, 9682–9702. [Google Scholar] [CrossRef] [PubMed]
  43. Thoetkiattikul, H.; Mhuantong, W.; Laothanachareon, T.; Tangphatsornruang, S.; Pattarajinda, V.; Eurwilaichitr, L.; Champreda, V. Comparative Analysis of Microbial Profiles in Cow Rumen Fed with Different Dietary Fiber by Tagged 16S rRNA Gene Pyrosequencing. Curr. Microbiol. 2013, 67, 130–137. [Google Scholar] [CrossRef]
  44. Garneau, J.E.; Tremblay, D.M.; Moineau, S. Characterization of 1706, a virulent phage from Lactococcus lactis with similarities to prophages from other Firmicutes. Virology 2008, 373, 298–309. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  45. Spence, C.; Wells, W.G.; Smith, C.J. Characterization of the Primary Starch Utilization Operon in the Obligate Anaerobe Bacteroides fragilis: Regulation by Carbon Source and Oxygen. J. Bacteriol. 2006, 188, 4663–4672. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  46. Nuriel-Ohayon, M.; Neuman, H.; Koren, O. Microbial Changes during Pregnancy, Birth, and Infancy. Front. Microbiol. 2016, 7, 1031. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  47. Yang, H.; Xiao, Y.; Gui, G.; Li, J.; Wang, J.; Li, D. Microbial community and short-chain fatty acid profile in gastrointestinal tract of goose. Poult. Sci. 2018, 97, 1420–1428. [Google Scholar] [CrossRef]
  48. Min, B.R.; Solaiman, S.; Shange, R.; Eun, J.-S. Gastrointestinal Bacterial and Methanogenic Archaea Diversity Dynamics Associated with Condensed Tannin-Containing Pine Bark Diet in Goats Using 16S rDNA Amplicon Pyrosequencing. Int. J. Microbiol. 2014, 2014, 141909. [Google Scholar] [CrossRef]
  49. Kafantaris, I.; Kotsampasi, B.; Christodoulou, V.; Kokka, E.; Kouka, P.; Terzopoulou, Z.; Gerasopoulos, K.; Stagos, D.; Mitsagga, C.; Giavasis, I.; et al. Grape pomace improves antioxidant capacity and faecal microflora of lambs. J. Anim. Physiol. Anim. Nutr. 2017, 101, e108–e121. [Google Scholar] [CrossRef]
  50. Blake, D.P.; Hillman, K.; Fenlon, D.R.; Low, J.C. Transfer of antibiotic resistance between commensal and pathogenic members of the Enterobacteriaceae under ileal conditions. J. Appl. Microbiol. 2003, 95, 428–436. [Google Scholar] [CrossRef]
  51. Huang, Z.; Kraus, V.B. Does lipopolysaccharide-mediated inflammation have a role in OA? Nat. Rev. Rheumatol. 2016, 12, 123–129. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  52. Quijada, N.M.; Bodas, R.; Lorenzo, J.M.; Schmitz-Esser, S.; Rodríguez-Lázaro, D.; Hernández, M. Dietary Supplementation with Sugar Beet Fructooligosaccharides and Garlic Residues Promotes Growth of Beneficial Bacteria and Increases Weight Gain in Neonatal Lambs. Biomolecules 2020, 10, 1179. [Google Scholar] [CrossRef] [PubMed]
  53. Douillard, F.P.; de Vos, W.M. Functional genomics of lactic acid bacteria: From food to health. Microb. Cell Factories 2014, 13, S8. [Google Scholar] [CrossRef] [Green Version]
  54. Malmuthuge, N.; Griebel, P.J.; Guan, L.L. The Gut Microbiome and Its Potential Role in the Development and Function of Newborn Calf Gastrointestinal Tract. Front. Veter. Sci. 2015, 2, 36. [Google Scholar] [CrossRef] [Green Version]
  55. Al-Saiady, M.Y. Effect of Probiotic Bacteria on Immunoglobulin G Concentration and Other Blood Components of Newborn Calves. J. Anim. Vet. Adv. 2010, 9, 604–609. [Google Scholar] [CrossRef] [Green Version]
  56. Rada, V.; Vlková, E.; Nevoral, J.; Trojanová, I. Comparison of bacterial flora and enzymatic activity in faeces of infants and calves. FEMS Microbiol. Lett. 2006, 258, 25–28. [Google Scholar] [CrossRef] [Green Version]
  57. Vlková, E.; Trojanová, I.; Rada, V. Distribution of bifidobacteria in the gastrointestinal tract of calves. Folia Microbiol. 2006, 51, 325–328. [Google Scholar] [CrossRef] [PubMed]
  58. Salzano, A.; Damiano, S.; D’Angelo, L.; Ballistreri, G.; Claps, S.; Rufrano, D.; Maggiolino, A.; Neglia, G.; De Palo, P.; Ciarcia, R. Productive Performance and Meat Characteristics of Kids Fed a Red Orange and Lemon Extract. Animals 2021, 11, 809. [Google Scholar] [CrossRef]
  59. La Ragione, R.M.; Narbad, A.; Gasson, M.J.; Woodward, M.J. In vivo characterization of Lactobacillus johnsonii FI9785 for use as a defined competitive exclusion agent against bacterial pathogens in poultry. Lett. Appl. Microbiol. 2004, 38, 197–205. [Google Scholar] [CrossRef]
  60. Bi, Y.; Cox, M.S.; Zhang, F.; Suen, G.; Zhang, N.; Tu, Y.; Diao, Q. Feeding modes shape the acquisition and structure of the initial gut microbiota in newborn lambs. Environ. Microbiol. 2019, 21, 2333–2346. [Google Scholar] [CrossRef] [Green Version]
  61. Hammerum, A.M.; Heuer, O.E. Human Health Hazards from Antimicrobial-Resistant Escherichia coli of Animal Origin. J. Clin. Infect. Dis. 2009, 48, 916–921. [Google Scholar] [CrossRef] [Green Version]
  62. Lacombe, A.; Wu, V.C.H.; Tyler, S.; Edwards, K. Antimicrobial action of the American cranberry constituents; phenolics, anthocyanins, and organic acids, against Escherichia coli O157:H7. Int. J. Food Microbiol. 2010, 139, 102–107. [Google Scholar] [CrossRef]
  63. Benyacoub, J.; Rochat, F.; Saudan, K.-Y.; Rochat, I.; Antille, N.; Cherbut, C.; von der Weid, T.; Schiffrin, E.J.; Blum, S. Feeding a Diet Containing a Fructooligosaccharide Mix Can Enhance Salmonella Vaccine Efficacy in Mice. J. Nutr. 2008, 138, 123–129. [Google Scholar] [CrossRef] [PubMed]
  64. Milani, C.; Duranti, S.; Bottacini, F.; Casey, E.; Turroni, F.; Mahony, J.; Belzer, C.; Delgado Palacio, S.; Arboleya Montes, S.; Mancabelli, L.; et al. The First Microbial Colonizers of the Human Gut: Composition, Activities, and Health Implications of the Infant Gut Microbiota. J. Microbiol. Mol. Biol. Rev. 2017, 81, e00036-17. [Google Scholar] [CrossRef] [PubMed] [Green Version]
Agriculture 11 00572 g001 550
Figure 1. Relative abundance and taxonomic assignments at phylum level of the control group diet and the anthocyanin group diet supplemented with the red orange and lemon extract (RLE).
Figure 1. Relative abundance and taxonomic assignments at phylum level of the control group diet and the anthocyanin group diet supplemented with the red orange and lemon extract (RLE).
Agriculture 11 00572 g001
Agriculture 11 00572 g002 550
Figure 2. Differences in bacterial abundance at phylum level between the control and anthocyanin groups. The left side of the graph shows the abundance ratios of different taxa. The middle graph shows the difference in bacterial abundance with the 95% confidence interval with the respective q-values (q < 0.05). The right table shows the reads percentage assigned for each taxonomic group.
Figure 2. Differences in bacterial abundance at phylum level between the control and anthocyanin groups. The left side of the graph shows the abundance ratios of different taxa. The middle graph shows the difference in bacterial abundance with the 95% confidence interval with the respective q-values (q < 0.05). The right table shows the reads percentage assigned for each taxonomic group.
Agriculture 11 00572 g002
Agriculture 11 00572 g003 550
Figure 3. Differences in bacterial abundance at family level between the control and anthocyanin groups. The left side of the graph shows the abundance ratios of different taxa. The middle graph shows the difference in bacterial abundance with the 95% confidence interval with the relative q-values (q < 0.05). The right table shows the reads percentage assigned for each taxonomic group.
Figure 3. Differences in bacterial abundance at family level between the control and anthocyanin groups. The left side of the graph shows the abundance ratios of different taxa. The middle graph shows the difference in bacterial abundance with the 95% confidence interval with the relative q-values (q < 0.05). The right table shows the reads percentage assigned for each taxonomic group.
Agriculture 11 00572 g003
Agriculture 11 00572 g004 550
Figure 4. Differences in bacterial abundance at genus level between the control and anthocyanin groups. The left side of the graph shows the abundance ratios of different taxa. The middle graph shows the difference in bacterial abundance with the 95% confidence interval with the q-values (q < 0.05). The right table shows the reads percentage assigned for each taxonomic group.
Figure 4. Differences in bacterial abundance at genus level between the control and anthocyanin groups. The left side of the graph shows the abundance ratios of different taxa. The middle graph shows the difference in bacterial abundance with the 95% confidence interval with the q-values (q < 0.05). The right table shows the reads percentage assigned for each taxonomic group.
Agriculture 11 00572 g004
Agriculture 11 00572 g005 550
Figure 5. Principal coordinate analysis (PCoA) as 2D (left) and 3D (right) plots of bacterial species assigned for the anthocyanin and control groups. PCoA was calculated using the Bray-Curtis index to compute dissimilarities among different samples. Hypothesis testing was conducted by analysis of molecular variance (AMOVA) test (p < 0.05).
Figure 5. Principal coordinate analysis (PCoA) as 2D (left) and 3D (right) plots of bacterial species assigned for the anthocyanin and control groups. PCoA was calculated using the Bray-Curtis index to compute dissimilarities among different samples. Hypothesis testing was conducted by analysis of molecular variance (AMOVA) test (p < 0.05).
Agriculture 11 00572 g005
Agriculture 11 00572 g006 550
Figure 6. Top ten most abundant bacterial species and relative differences between proportions in bacterial abundance with the 95% confidence interval (q < 0.01).
Figure 6. Top ten most abundant bacterial species and relative differences between proportions in bacterial abundance with the 95% confidence interval (q < 0.01).
Agriculture 11 00572 g006
Table
Table 1. Red orange and lemon extract (RLE) chemical composition.
Table 1. Red orange and lemon extract (RLE) chemical composition.
Compound[M]+ (m/z)MSn (m/z)AnthocyaninRelative
Composition
(%) (a)
1611449/287cyanidin 3,5-diglucoside1.29
2465303delphinidin 3-glucoside2.67
3611287cyanidin 3-sophoroside0.41
4449287cyanidin 3-glucoside39.97
5595287cyanidin 3-rutinoside1.30
6479317petunidin 3-glucoside1.59
7551465/303delphinidin 3-(6”-malonyl)glucoside1.43
8463301peonidin 3-glucoside2.98
9565479/317petunidin 3-(6”-malonyl)glucoside1.45
10535449/287cyanidin 3-(6”-malonyl)glucoside21.76
11-271pelargonidin derivative1.44
12549463/301peonidin 3-(6”-malonyl)glucoside13.80
13-287cyanidin derivative2.39
14-301peonitin derivative1.82
Total anthocyanins (g CGE/100 g)2.66 ± 0.01
[M]+ (m/z): mass peak; MSn (m/z): MS fragmentation model; (a) Relative composition of anthocyanins calculated from peak areas recorded at 520 nm. The total anthocyanin content was expressed as mg of cyanidin 3-glucoside equivalents (CGE) 100 mL−1 and mg CGE 100 g−1 dry weight (DW) for the juice samples.
Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Share and Cite

MDPI and ACS Style

Ferrara, M.; Sgarro, M.F.; Maggiolino, A.; Damiano, S.; Iannaccone, F.; Mulè, G.; De Palo, P. Effect of Red Orange and Lemon Extract-Enriched Diet in Suckling Lambs’ Fecal Microbiota. Agriculture 2021, 11, 572. https://doi.org/10.3390/agriculture11070572

AMA Style

Ferrara M, Sgarro MF, Maggiolino A, Damiano S, Iannaccone F, Mulè G, De Palo P. Effect of Red Orange and Lemon Extract-Enriched Diet in Suckling Lambs’ Fecal Microbiota. Agriculture. 2021; 11(7):572. https://doi.org/10.3390/agriculture11070572

Chicago/Turabian Style

Ferrara, Massimo, Maria Federica Sgarro, Aristide Maggiolino, Sara Damiano, Francesco Iannaccone, Giuseppina Mulè, and Pasquale De Palo. 2021. "Effect of Red Orange and Lemon Extract-Enriched Diet in Suckling Lambs’ Fecal Microbiota" Agriculture 11, no. 7: 572. https://doi.org/10.3390/agriculture11070572

APA Style

Ferrara, M., Sgarro, M. F., Maggiolino, A., Damiano, S., Iannaccone, F., Mulè, G., & De Palo, P. (2021). Effect of Red Orange and Lemon Extract-Enriched Diet in Suckling Lambs’ Fecal Microbiota. Agriculture, 11(7), 572. https://doi.org/10.3390/agriculture11070572

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

Article Metrics

Back to TopTop