Current Development of in Vitro and in Vivo Methods for Predicting Glycemic Indexes of Carbohydrate Foods

Glycemic index (GI) is a key indicator for evaluating the postprandial glycemic response to carbohydrate foods. A low GI diet can not only help to control appetite and delay hunger, but also benefit weight control and improve glucose and lipid levels in diabetic patients. The development of low GI foods has thus become a hotspot in current food research. At present, the international standard ISO 26642:2010, issued by the International Standards Organization (ISO), is the gold standard for measuring the GI values of foods using human subjects around the world. However, human testing has some disadvantages, such as individual differences may lead to significantly different results, even for the same foods, and it is costly and time consuming, and should be ethical, and it is unsuitable for high-throughput testing of food GI values. For this reason, researchers have successively developed various in vitro models to predict food GI values. This article focuses on reviewing the current in vitro and in vivo methods for predicting the GI values of foods, with a particular focus on their advantages and disadvantages, as well as their future developments. The current paper is aimed to provide new ideas for the development and promotion of low GI foods

Review of physicochemical properties and analytical characterization of lignocellulosic biomass

Lignocellulosic biomass is the most abundant and renewable material in the world for the production of biofuels. Using lignocellulosic biomass derived biofuels could reduce reliance on fossil fuels and contribute to climate change mitigation. A profound understanding of the physicochemical properties of lignocellulosic biomass and the analytical characterization methods for those properties is essential for the design and operation of associated biomass conversion processing facilities. The present article aims to present a comprehensive review of physicochemical properties of lignocellulosic biomass, including particle size, grindability, density, flowability, moisture sorption, thermal properties, proximate analysis properties, elemental composition, energy content and chemical composition. The corresponding characterization techniques for these properties and their recent development are also presented. This review is intended to provide the readers systematic knowledge in the physicochemical properties of lignocellulosic biomass and characterization techniques for the conversion of biomass and the application of biofuels

The distribution and characteristics of suspended particulate matter in the Chukchi Sea

Samples taken from the Chukchi Sea (CS) during the 4th Chinese National Arctic Research Expedition, 2010, were analyzed to determine the content and composition of suspended particulate matter (SPM) to improve our understanding of the distribution, sources and control factors of the SPM there. The results show that the SPM in the water column is highest in the middle and near the bottom in the south and central–north CS, followed by that off the Alaskan coast and in Barrow Canyon. The SPM content is lowest in the central CS. Scanning electron microscope (SEM) analysis shows that the SPM in the south and central–north CS is composed mainly of diatoms, but the dominant species in those two areas are different. The SPM off the Alaskan coast and in Barrow Canyon is composed mainly of terrigenous material with few bio-skeletal clasts. The distribution of temperature and salinity and the correlation between diatom species in SPM indicate that the diatom dominant SPM in the south CS is from the Pacific Ocean via the Bering Strait in summer. The diatom dominant SPM in the central–north CS is also from Pacific water, which reaches the CS in winter. The SPM in the middle and near the bottom of the water column off the Alaskan coast and in Barrow Canyon is from Alaskan coastal water and terrigenous material transported by rivers in Alaska

Sustainable and scalable in-situ synthesis of hydrochar-wrapped Ti3AlC2-derived nanofibers as adsorbents to remove heavy metals

To ensure a sustainable future, it is imperative to efficiently utilize abundant biomass to produce such as platform chemicals, transport fuels, and other raw materials; hydrochar is one of the promising candidates derived by hydrothermal carbonization of biomass in pressurized hot water. The synthesis of “hydrochar-wrapped Ti3AlC2-derived nanofibers” was successfully achieved by a facile one-pot hydrothermal reaction using glucose as the hydrochar precursor. Meanwhile, cellulose and pinewood sawdust as raw materials were also investigated. Products were characterized by XRD, N2 adsorption-desorption isotherms, SEM, TEM and FT-IR to investigate their crystal structures, textural properties, morphologies, and surface species. In the adsorption test to remove Cd(II) and Cu(II) in aqueous solution, hydrochar-wrapped nanofibers outperformed pure nanofibers derived from Ti3AlC2, hydrothermal carbon derived from glucose and commercial activated carbon. Finally, the regeneration, sorption kinetics, and possible adsorption mechanism were also explored

Theoretical Analysis of Double Logistic Distributed Activation Energy Model for Thermal Decomposition Kinetics of Solid Fuels

The distributed activation energy model (DAEM) has been widely used to analyze the thermal decomposition of solid fuels such as lignocellulosic biomass and its components, coal, microalgae, oil shale, waste plastics, and polymer etc. The DAEM with a single distribution of activation energies cannot describe those reactions well since the thermal decomposition normally involves multiple sub-processes of various components. The double DAEM employs a double distribution to represent the activation energies. The Gaussian distribution is usually used to represent the activation energies. However, it is not sufficiently accurate for addressing the activation energies in the initial and final stages of the thermal decomposition reactions of solid fuels. Compared to the Gaussian distribution, the logistic distribution is slightly thicker at the curve tail and suits better to describe the activation energy distribution. In this work, a theoretical analysis of the double logistic DAEM for the thermal decomposition kinetics of solid fuels has been systematically investigated. After the derivation of the double logistic DAEM, its numerical calculation method and the physical meanings of the model parameters have been presented. Three typical types of simulated double logistic DAEM processes have been obtained according to the overlapped situation of two derivative conversion peaks, namely separated, overlapped and partially overlapped processes. It is found that, for the partially overlapped process, the form of the minor peak (overlapped peak or peak shoulder) depends on the values of the frequency factor and heating rate. Considering the simulated processes and related examples from literature, the double logistic DAEM has been remarked as a more reliable tool with abundant flexibility to explain the thermal decomposition of various solid fuels. More accurate results are expected if the double logistic DAEM is coupled with the computational fluid dynamics (CFD) simulation for those reactions mentioned above

Kinetic Analysis of Bio-Oil Aging by Using Pattern Search Method

Bio-oil derived from fast pyrolysis of lignocellulosic biomass is unstable, and aging would occur during its storage, handling, and transportation. The kinetic analysis of bio-oil aging is fundamental for the investigation of bio-oil aging mechanisms and the utilization of bio-oil as biofuels, biomaterials or biochemicals. The aging kinetic experiments of bio-oil from poplar wood pyrolysis were conducted at different aging temperatures of 303, 333, 353, and 363 K for different specified periods of time in capped glass vessels. The traditional method with two separate fittings was employed to fit experimental data, and the results indicated that the obtained kinetic parameters could not fit the experimental data well. An advanced approach for kinetic modeling of bio-oil aging has been developed by simultaneously processing experimental data at different aging temperatures and using the pattern search method. The aging kinetic model with the optimized parameters predicted the aging kinetic experimental data of the bio-oil sample very well for different aging temperatures

Composition and distribution of fish species collected during the fourth Chinese National Arctic Research Expedition in 2010

There are awareness and concerns caused by the decreasing sea ice coverage around the Arctic and Antarctic due to effects of climate change. Emphasis in this study was on rapid changes in Arctic sea ice coverage and its impacts on the marine ecology during the fourth Chinese National Arctic Research Expedition in 2010. Our purpose was to establish a baseline of Arctic fish compositions, and consequent effects of climate change on the fish community and biogeography. Fish specimens were collected using a multinet middle-water trawl, French-type beam trawl, otter trawl, and triangular bottom trawl. In total, 36 tows were carried out along the shelf of the Bering Sea, Bering Strait, and Chukchi Sea in the Arctic Ocean. In total, 41 fish species belonging to 14 families in 7 orders were collected during the expedition. Among them, the Scorpaeniformes, including 17 species, accounted for almost one third of the total number (34.8%), followed by 14 species of the Perciformes (27.0%), 5 species of the Pleuronectiformes(22.3%), and 2 species of the Gadiformes (15.4%). The top 6 most abundant species were Hippoglossoides robustus, Boregadus saida, Myoxocephalus scorpius, Lumpenus fabricii, Artediellus scaber, and Gymnocanthus tricuspis. Abundant species varied according to the different fishing methods; numbers of families and species recorded did not differ with the various fishing methods; species and abundances decreased with depth and latitude; and species extending over their known geographic ranges were observed during the expedition. Station information, species list, and color photographs of all fishes are provided

A Predictive PBM-DEAM Model for Lignocellulosic Biomass Pyrolysis

Pyrolysis is a promising and attractive way to convert lignocellulosic biomass into low carbon-emission energy products. To effectively use biomass feedstock with size distribution to produce biofuels, a comprehensive kinetic model of the process, occurring at particle level, is important. In this study, the population balance model (PBM)-distributed activation energy model (DAEM) coupled model is first time developed to predict biomass pyrolysis. The Population balance model is used to present the variable size distribution of solid, decomposed from virgin biomass to porous char. Two different kinetic models are embedded into the conservation equations of mass and energy. They are compared to demonstrate the prediction performance of heating-up time during the pyrolysis process of biomass with a normal size distribution. It is found that non-isothermal kinetics without and with DEAM capture the intra-particle temperature distribution. There is a noticeable difference of heating-up time between single and distributed particle size