Ultrasound freeze-thawing style pretreatment to improve the efficiency of the vacuum freeze-drying of okra (Abelmoschus esculentus (L.) Moench) and the quality characteristics of the dried product

Vacuum freeze-drying is a new and high technology on agricultural product dehydrating dry, but it faces the high cost problem caused by high energy consumption. This study investigated the effect of ultrasound (US), freeze-thawing (including the freeze-air thawing (AT), freeze-water thawing (WT), freeze-ultrasound thawing (UST), and freeze-air ultrasound thawing (AT + US)) pretreatments on the vacuum freeze-drying efficiency and the quality of dried okra. The results indicated that the application of ultrasound and different freeze-thawing pretreatments reduced the drying time by 25.0%–62.50% and the total energy consumption was 24.28%–62.35% less. The AT pretreatment reduced the time by of okra slices by 62.50% and the total energy consumption was 62.35% less. The significant decrease in drying time was due to a change in the microstructure caused by pretreatment. Besides, the okra pretreated with the US retained most of the quality characteristics (flavor, color, hardness, and frangibility) among all methods, while, AT + US had the most changeable characteristics in quality, which is deprecated in our study. The okra pretreated with the US and AT, separately, had the best dry matter content loss (9.008%, 5.602%), lower chlorophyll degradation (5.05%, 5.44% less), and higher contents of total phenolics, total flavonoids, and pectin, with strong antioxidant capacity, compared to other methods. The pretreatments did not have a large effect on the functional groups and the structure of pectin, but slightly affected the viscosity. It can be concluded that AT and US pretreatment methods are better than others.     

The effect of high power airborne ultrasound and microwaves on convective drying effectiveness and quality of green pepper

The effectiveness of hybrid drying based on convective drying with application of ultrasound and microwave enhancement is the main subject of the studies. The drying kinetics, energy consumption as well as the quality aspect of green pepper is analysed. It was shown that hybrid drying methods shorten significantly the drying time, reduce the energy consumption and affect positively the quality factors. Each of the analysed aspects depend on combination of the convective-ultrasound-microwave drying programs. Besides, based on the drying model elaborated earlier by one of the authors, the effects of ultrasound on convective drying assessed by such phenomena as “heating effect”, “vibration effect” and “synergistic effect” are presented.     

Effects of high-energy ultrasound on the functional properties of proteins

In recent years, high-energy ultrasound has been used as an alternative to improve the functional properties of various proteins, such as from milk, eggs, soy and poultry. The benefits of implementing this technology depend on the inherent characteristics of the protein source and the intensity and amplitude of the ultrasound, as well as on the pH, temperature, ionic strength, time, and all of the variables that have an effect on the physicochemical properties of proteins. Therefore, it is necessary to establish the optimal conditions for each type of food. The use of ultrasound is a promising technique in food technology with a low impact on the environment, and it has thus become known as a green technology. Therefore, this review focuses on the application of high-energy ultrasound to food; its effects on the functional properties of proteins; and how different conditions such as the frequency, time, amplitude, temperature, and protein concentration affect the functional properties.     

Effects of multi-frequency ultrasound on freezing rates and quality attributes of potatoes

The effects of multi-frequency ultrasound assisted freezing on the freezing rate, microstructure, quality properties (drip loss, firmness, total calcium content, l-ascorbic acid content and total phenol content) of potatoes were studied. The results indicated that the freezing effects of multi-frequency ultrasound was better than those of single-frequency ultrasound. Multi-frequency ultrasound could significantly increase the freezing rate and preserve the quality of frozen samples better. With increase in the number of ultrasonic frequencies, the freezing effect was more obvious. In addition, scan electron microscopy (SEM) images showed that the ice crystals formed by the multi-frequency ultrasonic treatment were fine and uniformly distributed, which caused less damage to the frozen potato samples. From the analysis of the quality attributes, the nutritional values of the samples after multi-frequency ultrasonic treatment was higher, but attention should be paid to the negative influence of the hydroxyl radical generated by the multi-frequency ultrasound.     

UV-Derivative Spectrophotometric Determination of Ritonavir Capsules and Comparison with LC Method

Abstract

An ultraviolet-derivative spectrophotometric method (UV-D) has been proposed as an alternative to a previously described liquid chromatographic (LC) method for the quantitative determination of ritonavir in soft gelatin capsules. The spectrophotometric method is based on recording the second-derivative spectra for ritonavir at 222.3 nm of its solutions in methanol. The linear dynamic range was 10.0–30.0 µg · mL^?1 with a correlation coefficient of 0.9995. Mean recoveries were between 99.2% and 100.2% for the tested capsules samples. Mean intra- and interassay relative standard deviations (RSDs) were less than 2.0%. The statistic analysis showed that LC and UV-D methods were equivalent to assay ritonavir capsules.     

价值引领融入“无机化学与化学分析”的课程思政建设

将课程思政应用到"无机化学和化学分析"教学中,更好发挥其价值引领作用。开展课程思政建设,应做到守正与创新。本文以价值引领为切入点,介绍如何将思想政治教育有机融入课程内容设置和课堂讲授等环节,力求培养学生的家国情怀、国际视野、法治意识、生态意识、工程伦理、人文关怀等科学素养,深入践行立德树人,提高本科教学质量。     

PLS分析与RBF神经网络耦合环境模型

鉴于城市大气环境质量受到诸多复杂因素影响,且各因素间存在多重相关性,本文将偏最小二乘(PLS)分析与人工神经网络径向基网络(RBF)耦合,建立偏最小二乘径向基神经网络模型(PLSRBF),应用于贵阳大气环境质量的检验和预测。实例表明:PLSRBF模型可对原多自变量模型进行降维简化,并可有效提取解释变量信息,防止信息丢失,且具有较强的拟合能力。