Ethanol and lactic acid production using sap squeezed from old oil palm trunks felled for replanting

Old oil palm trunks that had been felled for replanting were found to contain large quantities of high glucose content sap. Notably, the sap in the inner part of the trunk accounted for more than 80% of the whole trunk weight. The glucose concentration of the sap from the inner part was 85.2 g/L and decreased towards the outer part. Other sugars found in relatively low concentrations were sucrose, fructose, galactose, xylose, and rhamnose. In addition, oil palm sap was found to be rich in various kinds of amino acids, organic acids, minerals and vitamins. Based on these findings, we fermented the sap to produce ethanol using the sake brewing yeast strain, Saccharomyces cerevisiae Kyokai no.7. Ethanol was produced from the sap without the addition of nutrients, at a comparable rate and yield to the reference fermentation on YPD medium with glucose as a carbon source. Likewise, we produced lactic acid, a promising material for bio-plastics, poly-lactate, from the sap using the homolactic acid bacterium Lactobacillus lactis ATCC19435. We confirmed that sugars contained in the sap were readily converted to lactic acid with almost the same efficiency as the reference fermentation on MSR medium with glucose as a substrate. These results indicate that oil palm trunks felled for replanting are a significant resource for the production of fuel ethanol and lactic acid in palm oil-producing countries such as Malaysia and Indonesia.     

Effectiveness of Zataria multiflora Boiss essential oil and grape seed extract impregnated chitosan film on ready-to-eat mortadella-type sausages during refrigerated storage

BACKGROUND: The effectiveness of chitosan films containing Zataria multiflora Boiss essential oil (ZEO) (5 and 10 g kg^?1) and grape seed extract (GSE) (10 g kg^?1) on lipid oxidation and microbial (lactic acid bacteria, aerobic mesophiles and inoculated Listeria monocytogenes) characteristics of mortadella sausage at 4 °C for 21 days was evaluated. The release of total phenolics (TPs) into sausage was also assessed. RESULTS: All films exhibited antibacterial activity against L. monocytogenes on agar culture media. Chitosan films containing ZEO were the most effective on the growth of bacteria. The growth of L. monocytogenes was significantly inhibited by ZEO‐GSE containing films especially during storage of the sausages for 6 days. Aerobic mesophiles and lactic acid bacteria were the most sensitive and resistant groups to films by 0.1–1.1 and 0.1–0.7 log cycles reduction, respectively. Sausages wrapped by 10 g kg^?1 GSE + 10 g kg^?1 ZEO films had the lowest degrees of lipid oxidation, which was 23% lower than the control. The TPs of ZEO films decreased to zero after 6 days, whereas TPs of GSE films followed a slight decrease during the storage. CONCLUSION: Antimicrobial/antioxidant chitosan film could be developed by incorporating GSE and ZEO for extending the shelf life of mortadella sausage. Copyright © 2011 Society of Chemical Industry     

Physicochemical stability of antilisterial proteins from P. polymyxa Kp10 as potential food biopreservative

Listeria monocytogenes has continuously become a significant threat to consumers worldwide. The use of chemical-derived preservatives that are commonly associated with safety and nutritional issues has prompted the use of natural-based preservatives as a better alternative. Many bacterial strains including Paenibacillus polymyxa Kp10 have been reported to produce various antimicrobial proteins and compounds that are considered more natural. However, their stability in various physicochemical conditions should be examined before being applied in various types of food. In this study, the stability of four previously identified antilisterial proteins in P. polymyxa Kp10 upon exposure to several physicochemical conditions was examined. More than 80% residual antilisterial activity is conserved upon heat and proteinase K treatment. But, sensitivity to 24 h trypsin digestion has been observed. P1 and P2 proteins (histone-like DNA binding proteins HU) were sensitive to alkaline pH (pH 10-12) as compared with other proteins. More than 70% and 97% residual antilisterial activity were recovered after incubation in raw beef homogenates and simulated meat gravy model, respectively. However, the antilisterial activity of most proteins was highly compromised in chicken and salmon meat homogenates, and UHT cow milk. Inoculation of these proteins into Listeria-contaminated simulated meat gravy showed that all proteins exerted a bactericidal action against L. monocytogenes. P1 and P2 shared almost similar antilisterial activity rates, while P4 was the most potent antilisterial protein. The findings in this study could provide important preliminary data for future applications of these proteins as preservative in food products especially beef-based meat products.     

Potent Antidiabetic Activity and Metabolite Profiling of Melicope Lunu‐ankenda Leaves

Diabetes mellitus is normally characterized by chronic hyperglycemia associated with disturbances in the fat, carbohydrate, and protein metabolism. There is an increasing trend of using natural products instead of synthetic agents as alternative therapy for disorders due to their fewer side effects. In this study, antidiabetic and antioxidant activities of different Melicope lunu‐ankenda (ML) ethanolic extracts were evaluated using inhibition of α‐glucosidase and 2,2‐diphenyl‐l‐picrylhydrazyl (DPPH) radicals scavenging activity, respectively; whereas, proton nuclear magnetic resonance (¹H NMR) and ultra‐high performance liquid chromatography‐tandem mass spectrometric (UHPLC‐MS/MS) techniques were used for metabolite profiling of ML leaf extracts at different concentrations of ethanol and water. Sixty percent of ethanolic ML extract showed highest inhibitory effect against α‐glucosidase enzyme (IC₅₀ of 37 μg/mL) and DPPH scavenging activity (IC₅₀ of 48 μg/mL). Antidiabetic effect of ML extracts was also evaluated in vivo and it was found that the high doses (400 mg/Kg BW) of ML extract exhibited high suppression in fasting blood glucose level by 62.75%. The metabolites responsible for variation among ML samples with variable ethanolic levels have been evaluated successfully using ¹H‐NMR–based metabolomics. The principal component analysis (PCA) and partial least squares(PLS) analysis scores depicted clear and distinct separations into 4 clusters representing the 4 ethanolic concentrations by PC1 and PC2, with an eigenvalue of 69.9%. Various ¹H‐NMR chemical shifts related to the metabolites responsible for sample difference were also ascribed. The main bioactive compounds identified attributing toward the separation included: isorhamnetin, skimmianine, scopoletin, and melicarpinone. Hence, ML may be used as promising medicinal plant for the development of new functional foods, new generation antidiabetic drugs, as a single entity phytomedicine or in combinational therapy.     

Κ‐CN gene polymorphism in Nili‐ravi buffalo,Achai and Sahiwal cattle of Pakistan

Kappa‐casein (κ‐CN) is the subtype of casein protein, an important constituent of bovine milk protein. The current study was undertaken to investigate the genetic polymorphism in κ‐CN gene of Nili‐ravi buffalo, Achai and Sahiwal cattle of Pakistan using polymerase chain reaction–restriction fragment length polymorphism (PCR‐RFLP) technique. The Nili‐ravi buffalo was found to be monomorphic (genotype BB only) for κ‐CN gene. Achai cattle were polymorphic for κ‐CN (having three genotypes AA, AB and BB) with a frequency of 0.70, 0.18 and 0.12, respectively, while in Sahiwal cattle, both the genotypes AA and AB were found with genotypic frequencies of 0.92 and 0.08, respectively. The presence of genotype BB in Achai cattle is surprising as it is absent in most of the cattle breeds worldwide.     

Melt Production and Antimicrobial Efficiency of Low-Density Polyethylene (LDPE)-Silver Nanocomposite Film

Colloidal silver nanoparticles with a size of 5.5 ± 1.1 nm were prepared by chemical reduction using polyethylene glycol (PEG). Silver nanoparticles were incorporated into low-density polyethylene (LDPE) by melt blending and subsequent hot pressing at 140 °C to produce nanocomposite film with an average thickness of 0.7 mm. PEG was added at 5% weight of polymer as a compatibilizer agent in order to prevent agglomeration and provide uniform distribution of nanoparticles in polymer matrix. Antimicrobial activity of silver nanocomposites against Escherichia coli ATCC 13706, Staphylococcus aureus ATCC12600, and Candida albicans ATCC10231 was evaluated by semi-qualitative agar diffusion test and quantitative dynamic shake flask test. Mechanical properties of nanocomposites were not significantly different from silver-free LDPE-containing PEG films (p > 0.05), and silver nanoparticles did not form chemical bonding with the polymer. LDPE-silver nanocomposite samples by more than 6.69 ppm silver nanoparticles showed considerable antimicrobial clear zone. LDPE-silver nanocomposite affected growth kinetic parameters of the examined bacteria and is more efficient on S. aureus than E. coli. Polyethylene-silver nanocomposites containing 22.64 ppm silver nanoparticles could reduce 57.8% growth rate and 23.3% maximum bacterial concentration and increase 35.8% lag time of S. aureus. This study shows the potential use of LDPE-silver nanocomposite as antimicrobial active film. Antimicrobial efficiency of silver nanocomposite depends on silver nanoparticles concentration; however, high level of silver nanoparticles may lead to weakening of mechanical properties.     

Survivable millimeter-wave mesh networks

Millimeter-wave mesh networks have the potential to provide cost-effective high-bandwidth solutions to many current bandwidth-constrained networks including cellular backhaul. However, the availability of such networks is severely limited due to their susceptibility to weather, such as precipitation and humidity. In this paper, we present a rigorous approach to survivable millimeter-wave mesh networks based on experimentation, modeling, and simulation. Individual link performance is characterised using frame error-rate measurements from millimeter-wave transmissions on test links over a period of one year. A geometric model based on radar-reflectivity data is used to characterise rain storms and determine their impact on spatially correlated links of a mesh network. To mitigate the impact of link impairments on network services, we present two cross-layered routing protocols to route around the failures: P-WARP (predictive weather-assisted routing protocol) and XL-OSPF (cross-layered open shortest-path first). We conduct a performance analysis of the proposed mesh network under the presence of actual weather events as recorded by the US National Weather Service. Results show that the proposed approach yields the highest dependability when compared against existing routing methods.     

A correlation-based ant miner for classification rule discovery

In recent years, a few sequential covering algorithms for classification rule discovery based on the ant colony optimization meta-heuristic (ACO) have been proposed. This paper proposes a new ACO-based classification algorithm called AntMiner-C. Its main feature is a heuristic function based on the correlation among the attributes. Other highlights include the manner in which class labels are assigned to the rules prior to their discovery, a strategy for dynamically stopping the addition of terms in a rule’s antecedent part, and a strategy for pruning redundant rules from the rule set. We study the performance of our proposed approach for twelve commonly used data sets and compare it with the original AntMiner algorithm, decision tree builder C4.5, Ripper, logistic regression technique, and a SVM. Experimental results show that the accuracy rate obtained by AntMiner-C is better than that of the compared algorithms. However, the average number of rules and average terms per rule are higher.