Gaining a greater understanding of the plant microbiota and its interactions with its host plant heralds a new era of scientific discovery in agriculture. Different agricultural management practices influence soil microbial populations by changing a soil’s physical, chemical and biological properties. However, the impact of these practices on the microbiota associated with economically important crops such as oilseed rape, are still understudied. In this work we investigated the impact of two contrasting crop establishment practices, conventional (plow based) and conservation (strip–tillage) systems, on the microbiota inhabiting different plant microhabitats, namely rhizosphere, root and shoot, of winter oilseed rape under Irish agronomic conditions. Illumina 16S rRNA gene sequence profiling showed that the plant associated microhabitats (root and shoot), are dominated by members of the bacterial phyla Proteobacteria, Actinobacteria and Bacteroidetes. The root and shoot associated bacterial communities displayed markedly distinct profiles as a result of tillage practices. We observed a very limited ‘rhizosphere effect’ in the root zone of WOSR, i.e., there was little or no increase in bacterial community richness and abundance in the WOSR rhizosphere compared to the bulk soil. The two tillage systems investigated did not appear to lead to any major long term differences on the bulk soil or rhizosphere bacterial communities. Our data suggests that the WOSR root and shoot microbiota can be impacted by management practices and is an important mechanism that could allow us to understand how plants respond to different management practices and environments.

The development of next generation sequencing (NGS) techniques has enabled researchers to study and understand the world of microorganisms from broader and deeper perspectives. The contemporary advances in DNA sequencing technologies have not only enabled finer characterization of bacterial genomes but also provided deeper taxonomic identification of complex microbiomes which in its genomic essence is the combined genetic material of the microorganisms inhabiting an environment, whether the environment be a particular body econiche (e.g., human intestinal contents) or a food manufacturing facility econiche (e.g., floor drain). To date, 16S rDNA sequencing, metagenomics and metatranscriptomics are the three basic sequencing strategies used in the taxonomic identification and characterization of food-related microbiomes. These sequencing strategies have used different NGS platforms for DNA and RNA sequence identification. Traditionally, 16S rDNA sequencing has played a key role in understanding the taxonomic composition of a food-related microbiome. Recently, metagenomic approaches have resulted in improved understanding of a microbiome by providing a species-level/strain-level characterization. Further, metatranscriptomic approaches have contributed to the functional characterization of the complex interactions between different microbial communities within a single microbiome. Many studies have highlighted the use of NGS techniques in investigating the microbiome of fermented foods. However, the utilization of NGS techniques in studying the microbiome of non-fermented foods are limited. This review provides a brief overview of the advances in DNA sequencing chemistries as the technology progressed from first, next and third generations and highlights how NGS provided a deeper understanding of food-related microbiomes with special focus on non-fermented foods.

Fat rendering is a common process in the meat industry, whereby fatty or oily materials are melted away or cooked from the solid portion of the animal tissue. Once the fat, and more solid protein in the form of greaves, has been removed a co-product called glue water or stick water is produced which in generally considered a waste product. This study was established to investigate ways to revalorise this product and reduce the economic and environmental impact of this waste material. Proximate characterisation shows it contains 1.1–1.3% w/w of protein along with similar concentration of ashes (1.3% w/w). While low in protein this is a key pollutant if the product is disposed of, and could also represent an interesting protein source for downstream applications. In order to recover these proteins the salt has to be removed. Therefore, after the techno-functional properties of the raw material and of the recovered proteins were evaluated, especially those related to gelling formation, a new demineralizing method based on the excellent gelling properties of these proteins was developed and results compared with those obtained from three different ultrafiltration membranes (10, 3 and 1 kDa MWCO). Protein recovery was greater for the new method (79–90%) (50–77%); however, the amount of salt removed was higher when ultrafiltration was employed (90% compared to 81%).

Policy reform of the CAP and society’s expectations of agriculture have resulted in a growing need for improved information on the effectiveness of policy in achieving high-level objectives for more sustainable practice in agriculture. This is a high priority given its importance for consumers, public policy and private industry. Data collection programmes will need to adapt their scope if their information is to adequately address new information needs about high-level objectives. Assessment of sustainability at the farm level is hindered by the lack of data with which to derive appropriate, meaningful, and relevant indicators. This is particularly problematic for assessment of agricultural sustainability across the European Union (EU). Various databases exist at the EU scale regarding agricultural data sources and we identify one of these, the EU Farm Accountancy Data Network (FADN), as having considerable potential to assess farm-level sustainability at EU level. We critique several examples of published work that has attempted to assess agricultural sustainability using: FADN data alone; FADN data in combination with data from supplementary surveys, and; FADN data in combination with data from other EU databases. We conclude that the FADN would need to broaden its scope of data collection if it is to address the new information needs of policy, and we discuss the challenges in expanding FADN with a view towards wider farm-level assessment of sustainability. These include careful selection of indicators based on various criteria, the representativeness of the FADN, and the need to include new themes to address environmental, social, and animal welfare effects of policy.

In the original publication of this article [1], some errors in Table 4 need to be corrected as below:

Background Feed efficiency (FE) is an indicator of efficiency in converting energy and nutrients from feed into a tissue that is of major environmental and economic significance. The molecular mechanisms contributing to differences in FE are not fully elucidated, therefore the objective of this study was to profile the porcine Longissimus thoracis et lumborum (LTL) muscle transcriptome, examine the product quality from pigs divergent in FE and investigate the functional networks underpinning the potential relationship between product quality and FE. Results RNA-Seq (n = 16) and product quality (n = 40) analysis were carried out in the LTL of pigs differing in FE status. A total of 272 annotated genes were differentially expressed with a P < 0.01. Functional annotation revealed a number of biological events related to immune response, growth, carbohydrate & lipid metabolism and connective tissue indicating that these might be the key mechanisms governing differences in FE. Five most significant bio-functions altered in FE groups were ‘haematological system development & function’, ‘lymphoid tissue structure & development’, ‘tissue morphology’, ‘cellular movement’ and ‘immune cell trafficking’. Top significant canonical pathways represented among the differentially expressed genes included ‘IL-8 signalling’, ‘leukocyte extravasation signalling, ‘sphingosine-1-phosphate signalling’, ‘PKCθ signalling in T lymphocytes’ and ‘fMLP signalling in neutrophils’. A minor impairment in the quality of meat, in relation to texture and water-holding capacity, produced by high-FE pigs was observed. High-FE pigs also had reduced intramuscular fat content and improved nutritional profile in terms of fatty acid composition. Conclusions Ontology analysis revealed enhanced activity of adaptive immunity and phagocytes in high-FE pigs suggesting more efficient conserving of resources, which can be utilised for other important biological processes. Shifts in carbohydrate conversion into glucose in FE-divergent muscle may underpin the divergent evolution of pH profile in meat from the FE-groups. Moreover, altered amino acid metabolism and increased mobilisation & flux of calcium may influence growth in FE-divergent muscle. Furthermore, decreased degradation of fibroblasts in FE-divergent muscle could impact on collagen turnover and alter tenderness of meat, whilst enhanced lipid degradation in high-FE pigs may potentially underlie a more efficient fat metabolism in these animals.

Dairy and cereal are frequently combined to create composite foods with enhanced nutritional benefits. Dehydrated fermented milk–wheat composites (FMWC) were prepared by blending fermented milk (FM) and parboiled wheat (W), incubating at 35 °C for 24 h, drying at 46 °C for 48 h, and milling to 1 mm. Increasing the weight ratio of FM to W from 1.5 to 4.0 resulted in reductions in total solids (from 96 to 92%) and starch (from 52 to 39%), and increases in protein (15.2–18.9%), fat (3.7–5.9%), lactose (6.4–11.4%), and lactic acid (2.7–4.2%). FMWC need to be reconstituted prior to consumption. The water-holding capacity, pasting viscosity, and setback viscosity of the reconstituted FMWC (16.7% total solids) decreased with the ratio of FM to W. The reconstituted FMWC exhibited pseudoplastic flow behaviour on shearing from 18 to 120 s−1. Increasing the FM:W ratio coincided with a lower yield stress, consistency index, and viscosity at 120 s−1. The results demonstrate the critical impact of the FM:W ratio on the composition, pasting behavior, and consistency of the reconstituted FMWC. The difference in consistency associated with varying the FM:W ratio is likely to impact on satiety and nutrient value of the FMWCs.

Kefir is a putatively health-promoting dairy beverage that is produced when a kefir grain, consisting of a consortium of microorganisms, is added to milk to initiate a natural fermentation. Here, a detailed analysis was carried out to determine how the microbial population, gene content, and flavor of three kefirs from distinct geographic locations change over the course of 24-h fermentations. Metagenomic sequencing revealed that Lactobacillus kefiranofaciens was the dominant bacterial species in kefir during early stages of fermentations but that Leuconostoc mesenteroides became more prevalent in later stages. This pattern is consistent with an observation that genes involved in aromatic amino acid biosynthesis were absent from L. kefiranofaciens but were present in L. mesenteroides. Additionally, these shifts in the microbial community structure, and associated pathways, corresponded to changes in the levels of volatile compounds. Specifically, Acetobacter spp. correlated with acetic acid; Lactobacillus spp. correlated with carboxylic acids, esters and ketones; Leuconostoc spp. correlated with acetic acid and 2,3-butanedione; and Saccharomyces spp. correlated with esters. The correlation data suggest a causal relationship between microbial taxa and flavor that is supported by observations that addition of L. kefiranofaciens NCFB 2797 increased the levels of esters and ketones whereas addition of L. mesenteroides 213M0 increased the levels of acetic acid and 2,3-butanedione. Finally, we detected genes associated with probiotic functionalities in the kefir microbiome. Our results illustrate the dynamic nature of kefir fermentations and microbial succession patterns therein and can be applied to optimize the fermentation processes, flavors, and health-related attributes of this and other fermented foods. IMPORTANCE Traditional fermented foods represent relatively low-complexity microbial environments that can be used as model microbial communities to understand how microbes interact in natural environments. Our results illustrate the dynamic nature of kefir fermentations and microbial succession patterns therein. In the process, the link between individual species, and associated pathways, with flavor compounds is revealed and several genes that could be responsible for the purported gut health-associated benefits of consuming kefir are identified. Ultimately, in addition to providing an important fundamental insight into microbial interactions, this information can be applied to optimize the fermentation processes, flavors, and health-related attributes of this and other fermented foods.

Functional konjac glucomannan (KGM) was used to structure the water phase of O/W emulsions containing a lipophilic bioactive compound (β-carotene). KGM greatly increased the viscosity of the water phase and thus the viscosity of final emulsions. Results of Fourier-transform infrared spectroscopy (FT-IR) showed that there is no significant non-covalent interaction between KGM and whey proteins in the water phase. KGM significantly improved the creaming and pH stability of whey-protein-stabilized emulsions (p < 0.05), and significantly decreased the oiling-off of emulsions during freeze-thaw test. Emulsions with or without KGM all had good thermal stability at 80 °C. Microscopy observations indicated obvious aggregation of free proteins and oil droplets in gastric phase and an enzymatic-induced break-down of droplets, mainly in the intestinal phase of the simulated gastrointestinal tract (GIT) digestion. Emulsions with KGM-structured water phase showed a lower final release rate of encapsulated β-carotene than emulsion without KGM (p < 0.05), and the release rate decreased with the increasing KGM content. The findings of this study contribute to a better understanding of the influence of the water phase on the release of encapsulated compounds from emulsions, and make it possible to achieve controlled release of encapsulated compounds, and/or to deliver multiple health-beneficial nutrients at once by structuring emulsion-based carriers with functional natural biopolymers.

Metataxonomic 16S rDNA based studies are a commonplace and useful tool in the research of the microbiome, but they do not provide the full investigative power of metagenomics and metatranscriptomics for revealing the functional potential of microbial communities. However, the use of metagenomic and metatranscriptomic technologies is hindered by high costs and skills barrier necessary to generate and interpret the data. To address this, a tool for Phylogenetic Investigation of Communities by Reconstruction of Unobserved States (PICRUSt) was developed for inferring the functional potential of an observed microbiome profile, based on 16S data. This allows functional inferences to be made from metataxonomic 16S rDNA studies with little extra work or cost, but its accuracy relies on the availability of completely sequenced genomes of representative organisms from the community being investigated. The rumen microbiome is an example of a community traditionally underrepresented in genome and sequence databases, but recent efforts by projects such as the Global Rumen Census and Hungate 1000 have resulted in a wide sampling of 16S rDNA profiles and almost 500 fully sequenced microbial genomes from this environment. Using this information, we have developed “CowPI,” a focused version of the PICRUSt tool provided for use by the wider scientific community in the study of the rumen microbiome. We evaluated the accuracy of CowPI and PICRUSt using two 16S datasets from the rumen microbiome: one generated from rDNA and the other from rRNA where corresponding metagenomic and metatranscriptomic data was also available. We show that the functional profiles predicted by CowPI better match estimates for both the meta-genomic and transcriptomic datasets than PICRUSt, and capture the higher degree of genetic variation and larger pangenomes of rumen organisms. Nonetheless, whilst being closer in terms of predictive power for the rumen microbiome, there were differences when compared to both the metagenomic and metatranscriptome data and so we recommend, where possible, functional inferences from 16S data should not replace metagenomic and metatranscriptomic approaches. The tool can be accessed at http://www.cowpi.org and is provided to the wider scientific community for use in the study of the rumen microbiome.