Search Results
Methane prediction based on individual or groups of milk fatty acids for dairy cows fed rations with or without linseed
Milk fatty acids (MFA) are a proxy for the prediction of CH4 emission from cows, and prediction differs with diet. Our objectives were (1) to compare the effect of diets on the relation between MFA profile and measured CH4 production, (2) to predict CH4 production based on 6 data sets differing in the number and type of MFA, and (3) to test whether additional inclusion of energy-corrected milk (ECM) yield or dry matter intake (DMI) as explanatory variables improves predictions. Twenty dairy cows were used. Four diets were used based on corn silage (CS) or grass silage (GS) without (L0) or with linseed (LS) supplementation. Ten cows were fed CS-L0 and CS-LS and the other 10 cows were fed GS-L0 and GS-LS in random order. In feeding wk 5 of each diet, CH4 production (L/d) was measured in respiration chambers for 48 h and milk was analyzed for MFA concentrations by gas chromatography. Specific CH4 prediction equations were obtained for L0-, LS-, GS-, and CS-based diets and for all 4 diets collectively and validated by an internal cross-validation. Models were developed containing either 43 identified MFA or a reduced set of 7 groups of biochemically related MFA plus C16:0 and C18:0. The CS and LS diets reduced CH4 production compared with GS and L0 diets, respectively. Methane yield (L/kg of DMI) reduction by LS was higher with CS than GS diets. The concentrations of C18:1 trans and n-3 MFA differed among GS and CS diets. The LS diets resulted in a higher proportion of unsaturated MFA at the expense of saturated MFA. When using the data set of 43 individual MFA to predict CH4 production (L/d), the cross-validation coefficient of determination (R2 CV) ranged from 0.47 to 0.92. When using groups of MFA variables, the R2 CV ranged from 0.31 to 0.84. The fit parameters of the latter models were improved by inclusion of ECM or DMI, but not when added to the data set of 43 MFA for all diets pooled. Models based on GS diets always had a lower prediction potential (R2 CV = 0.31 to 0.71) compared with data from CS diets (R2 CV = 0.56 to 0.92). Models based on LS diets produced lower prediction with data sets with reduced MFA variables (R2 CV = 0.62 to 0.68) compared with L0 diets (R2 CV = 0.67 to 0.80). The MFA C18:1 cis-9 and C24:0 and the monounsaturated FA occurred most often in models. In conclusion, models with a reduced number of MFA variables and ECM or DMI are suitable for CH4 prediction, and CH4 prediction equations based on diets containing linseed resulted in lower prediction accuracy. © 2019 American Dairy Science Association
Genomics and prevalence of bacterial and archaeal isolates from biogas-producing microbiomes
Background: To elucidate biogas microbial communities and processes, the application of high-throughput DNA analysis approaches is becoming increasingly important. Unfortunately, generated data can only partialy be interpreted rudimentary since databases lack reference sequences. Results: Novel cellulolytic, hydrolytic, and acidogenic/acetogenic Bacteria as well as methanogenic Archaea originating from different anaerobic digestion communities were analyzed on the genomic level to assess their role in biomass decomposition and biogas production. Some of the analyzed bacterial strains were recently described as new species and even genera, namely Herbinix hemicellulosilytica T3/55T, Herbinix luporum SD1DT, Clostridium bornimense M2/40T, Proteiniphilum saccharofermentans M3/6T, Fermentimonas caenicola ING2-E5BT, and Petrimonas mucosa ING2-E5AT. High-throughput genome sequencing of 22 anaerobic digestion isolates enabled functional genome interpretation, metabolic reconstruction, and prediction of microbial traits regarding their abilities to utilize complex bio-polymers and to perform specific fermentation pathways. To determine the prevalence of the isolates included in this study in different biogas systems, corresponding metagenome fragment mappings were done. Methanoculleus bourgensis was found to be abundant in three mesophilic biogas plants studied and slightly less abundant in a thermophilic biogas plant, whereas Defluviitoga tunisiensis was only prominent in the thermophilic system. Moreover, several of the analyzed species were clearly detectable in the mesophilic biogas plants, but appeared to be only moderately abundant. Among the species for which genome sequence information was publicly available prior to this study, only the species Amphibacillus xylanus, Clostridium clariflavum, and Lactobacillus acidophilus are of importance for the biogas microbiomes analyzed, but did not reach the level of abundance as determined for M. bourgensis and D. tunisiensis. Conclusions: Isolation of key anaerobic digestion microorganisms and their functional interpretation was achieved by application of elaborated cultivation techniques and subsequent genome analyses. New isolates and their genome information extend the repository covering anaerobic digestion community members. © 2017 The Author(s).
Recent advances in d-lactic acid production from renewable resources: Case studies on agro-industrial waste streams
The production of biodegradable polymers as alternatives to petroleum-based plastics has gained significant attention in the past years. To this end, polylactic acid (PLA) constitutes a promising alternative, finding various applications from food packaging to pharmaceuticals. Recent studies have shown that d-lactic acid plays a vital role in the production of heat-resistant PLA. At the same time, the utilization of renewable resources is imperative in order to decrease the production cost. This review aims to provide a synopsis of the current state of the art regarding d-lactic acid production via fermentation, focusing on the exploitation of waste and byproduct streams. An overview of potential downstream separation schemes is also given. Additionally, three case studies are presented and discussed, reporting the obtained results utilizing acid whey, coffee mucilage and hydrolysate from rice husks as alternative feedstocks for d-lactic acid production. © 2019, University of Zagreb.
Extraction of phenolic compounds from palm oil processing residues and their application as antioxidants
The side streams derived from the palm oil production process, namely palm kernel cake, palm pressed fibre, palm kernel shells and empty fruit bunches, were evaluated as sources of phenolic compounds. Among these streams, kernel cake had the highest total phenolic content (in mg of gallic acid equivalents (GAE) per g of dry sample) with a value of 5.19, whereas the empty fruit bunches had the lowest value (1.79). The extraction time and liquid-to-solid ratio were investigated to optimize the phenolic extraction. Kernel cake exhibited the highest total phenolic content (5.35 mg/g) with a liquid-to-solid ratio of 40:1 during 20 min of extraction. The main phenolic compounds of the extracts deriving from all byproduct streams were also identified and quantified with HPLC-DAD. Pyrogallol, 4-hydroxybenzoic acid, gallic acid and ferulic acid were the main compounds found in kernel cake extracts. Empty fruit bunch and pressed fibre extracts were also rich in 4-hydroxybenzoic acid, while pyrogallol was the predominant compound in kernel shell extracts. All extracts showed antioxidant activity as it was indicated from the results of DPPH analysis and subsequently tested in sunflower oil aiming to prolong its shelf life. The addition of 0.8 % kernel cake extract increased the induction time of sunflower oil more than 50 %. According to the results obtained in this study, kernel cake extracts could be considered as a value-added co-product with a potential application as antioxidants in the food industry. © 2018 University of Zagreb.