Alkaloids in Processed Rhizoma Corydalis and Crude Rhizoma Corydalis Analyzed by GC/MS

The alkaloids in the processed Rhizoma Corydalis and the crude Rhizoma Corydalis were qualitatively and semiquantitatively analyzed using gas chromatography-mass spectrometry (GC/MS) method. The processing herb drug procedure was carried out according to the standard method of Chinese Pharmacopoeia. The samples were extracted using Soxhlet extractor with different solvents: methanol and acetone. The extraction effect on different solvents was investigated. The results showed that 11 kinds of alkaloids were identified from the crude Rhizoma Corydalis and only two were from the processed Rhizoma Corydalis. A total of 13 kinds of alkaloids were all based on two backbones. The alkaloids in the processed sample were less than those in the crude Rhizoma Corydalis significantly, while almost the corydaline has been changed in conformation after the sample had undergone processing, which provided support for the conclusion of reducing toxicity when the herbal medicine having been undergone a traditional drugs treatment process

In vitro and in vivo antiviral activity of monolaurin against Seneca Valley virus

IntroductionSurveillance of the Seneca Valley virus (SVV) shows a disproportionately higher incidence on Chinese pig farms. Currently, there are no vaccines or drugs to treat SVV infection effectively and effective treatment options are urgently needed.MethodsIn this study, we evaluated the antiviral activity of the following medium-chain fatty acids (MCFAs) or triglycerides (MCTs) against SVV: caprylic acid, caprylic monoglyceride, capric monoglyceride, and monolaurin.ResultsIn vitro experiments showed that monolaurin inhibited viral replication by up to 80%, while in vivo studies showed that monolaurin reduced clinical manifestations, viral load, and organ damage in SVV-infected piglets. Monolaurin significantly reduced the release of inflammatory cytokines and promoted the release of interferon-γ, which enhanced the viral clearance activity of this type of MCFA.DiscussionTherefore, monolaurin is a potentially effective candidate for the treatment of SVV infection in pigs

Imaging Spectroscopy and Machine Learning for Intelligent Determination of Potato and Sweet Potato Quality

Imaging spectroscopy has emerged as a reliable analytical method for effectively characterizing and quantifying quality attributes of agricultural products. By providing spectral information relevant to food quality properties, imaging spectroscopy has been demonstrated to be a potential method for rapid and non-destructive classification, authentication, and prediction of quality parameters of various categories of tubers, including potato and sweet potato. The imaging technique has demonstrated great capacities for gaining rapid information about tuber physical properties (such as texture, water binding capacity, and specific gravity), chemical components (such as protein, starch, and total anthocyanin), varietal authentication, and defect aspects. This paper emphasizes how recent developments in spectral imaging with machine learning have enhanced overall capabilities to evaluate tubers. The machine learning algorithms coupled with feature variable identification approaches have obtained acceptable results. This review briefly introduces imaging spectroscopy and machine learning, then provides examples and discussions of these techniques in tuber quality determinations, and presents the challenges and future prospects of the technology. This review will be of great significance to the study of tubers using spectral imaging technology

Imaging Spectroscopy and Machine Learning for Intelligent Determination of Potato and Sweet Potato Quality

Imaging spectroscopy has emerged as a reliable analytical method for effectively characterizing and quantifying quality attributes of agricultural products. By providing spectral information relevant to food quality properties, imaging spectroscopy has been demonstrated to be a potential method for rapid and non-destructive classification, authentication, and prediction of quality parameters of various categories of tubers, including potato and sweet potato. The imaging technique has demonstrated great capacities for gaining rapid information about tuber physical properties (such as texture, water binding capacity, and specific gravity), chemical components (such as protein, starch, and total anthocyanin), varietal authentication, and defect aspects. This paper emphasizes how recent developments in spectral imaging with machine learning have enhanced overall capabilities to evaluate tubers. The machine learning algorithms coupled with feature variable identification approaches have obtained acceptable results. This review briefly introduces imaging spectroscopy and machine learning, then provides examples and discussions of these techniques in tuber quality determinations, and presents the challenges and future prospects of the technology. This review will be of great significance to the study of tubers using spectral imaging technology.</jats:p

Optimization research on the site selection of fire safety for mega projects sites based on multi-objective particle swarm

AbstractThere are large fire safety hidden dangers in the construction site of mega-projects. In order to improve the ability of fire safety emergency response on site, in this paper, the number of demand points on the construction site are firstly determined, and through using risk assessment of operating conditions method, the risk is evaluated and the risk level is determined. Secondly, according to the construction site layout criteria and fire safety technical criteria, and taking the economy, distance, time and coverage of fire safety site selection as the basic factors, a multi-objective site selection optimization model for fire safety points is established. Multi-objective particle swarm optimization is used to solve the multi-objective site selection model, and a series of fire safety point site selection schemes are obtained. Finally, the analytic hierarchy process is used to select the best scheme from a series of schemes. The research ideas and conclusions of this paper provide a scientific and reasonable analysis framework and ideas for site selection of fire safety points for mega projects, which has certain applicability and practicability.</jats:p

Extraction of <scp>dl</scp>-anabasine from Alangium platanifolium root using an emulsion liquid membrane

An experimental study on the extraction of dl-anabasine from Alangium platanifolium root (APR) using an emulsion liquid membranes system (ELMs) has been reported.</p

Governance and Actions for Resilient Urban Food Systems in the Era of COVID-19: Lessons and Challenges in China

The COVID-19 pandemic has drastically challenged urban food systems, has hurt the resilience and fundamental function of urban food systems and also accelerated the trends of digitization and changing preferences of consumers in cities. This research conducted a qualitative analysis of the discourses, actions and interactions of different actors in the urban food systems in China during COVID-19 using an actor-oriented approach and discourse analysis. This research finds that stricter regulations and policies have been implemented by governments to regulate the food supply chain and ensure human health. Local community service personnel, volunteers, stakeholders along the food supply chain and consumers formulated collective actions during the pandemic yet chaos and discourse distortions also emerged at different stages. The pandemic is a preamble to changes in consumers’ preferences and food supply chains in urban communities. There were significant structural changes and a dual structure of urban and rural food systems, where unbalanced supply and demand existed. Collective actions with community governance and an innovative food business model to digitize flows and easily adapt to shocks in food systems are required

Spatial Price Transmission and Price Dynamics of Global Butter Export Market under Economic Shocks

Recently, the world has experienced striking economic and policy changes, and subsequent uncertainties have impacts on dairy trade price fluctuations. The Global Vector Autoregressive (GVAR) methodology was established in this paper to better understand international butter export prices transmission, the feedback between the economic context changes and price fluctuations, and the link between the global butter market, energy market, and other commodity markets. We assessed which key factors are typically associated with butter export price movements with regards to shocks to crude oil price, palm oil price, farm-gate raw milk price, exchange rates, and consumer price index (CPI) for food of the EU, New Zealand, the U.S., and the rest of world (RoW), respectively. Using generalized impulse response functions, this study found that decreases in farm-gate raw milk price could be swiftly transmitted to butter export prices of not only a home country but other foreign countries. However, palm oil price and crude oil price merely affects global butter export prices. We also found that U.S. dollar depreciations against the Euro will cause a decline in U.S. butter export price. It is concluded that butter export markets are not well-integrated, yet butter export prices of New Zealand and the U.S. are highly linked

Spatial Price Transmission and Price Dynamics of Global Butter Export Market under Economic Shocks

Recently, the world has experienced striking economic and policy changes, and subsequent uncertainties have impacts on dairy trade price fluctuations. The Global Vector Autoregressive (GVAR) methodology was established in this paper to better understand international butter export prices transmission, the feedback between the economic context changes and price fluctuations, and the link between the global butter market, energy market, and other commodity markets. We assessed which key factors are typically associated with butter export price movements with regards to shocks to crude oil price, palm oil price, farm-gate raw milk price, exchange rates, and consumer price index (CPI) for food of the EU, New Zealand, the U.S., and the rest of world (RoW), respectively. Using generalized impulse response functions, this study found that decreases in farm-gate raw milk price could be swiftly transmitted to butter export prices of not only a home country but other foreign countries. However, palm oil price and crude oil price merely affects global butter export prices. We also found that U.S. dollar depreciations against the Euro will cause a decline in U.S. butter export price. It is concluded that butter export markets are not well-integrated, yet butter export prices of New Zealand and the U.S. are highly linked.</jats:p