The Nutritional and Antioxidant Potential of Artisanal and Industrial Apple Vinegars and Their Ability to Inhibit Key Enzymes Related to Type 2 Diabetes In Vitro

The main objective of the current study was to determine the physicochemical properties, antioxidant activities, and α-glucosidase and α-amylase inhibition of apple vinegar produced by artisanal and industrial methods. Apple vinegar samples were analyzed to identify their electrical conductivity, pH, titratable acidity, total dry matter, Brix, density, mineral elements, polyphenols, flavonoids, and vitamin C. The antioxidant activity of apple vinegar samples was evaluated using two tests, total antioxidant capacity (TAC) and DPPH radical scavenging activity. Finally, we determined α-glucosidase and α-amylase inhibitory activities of artisanal and industrial apple vinegar. The results showed the following values: pH (3.69–3.19); electrical conductivity (2.81–2.79 mS/cm); titratable acidity (3.6–5.4); ash (4.61–2.90); °Brix (6.37–5.2); density (1.02476–1.02012), respectively, for artisanal apple vinegar and industrial apple vinegar. Concerning mineral elements, potassium was the most predominant element followed by sodium, magnesium, and calcium. Concerning bioactive compounds (polyphenols, flavonoids, and vitamin C), the apple vinegar produced by the artisanal method was the richest sample in terms of bioactive compounds and had the highest α-glucosidase and α-amylase inhibition. The findings of this study showed that the quality and biological activities of artisanal apple vinegar were more important than industrial apple vinegar.     

植物组织基膜生物传感器的研制

应用微生物及动、植物组织的生物催化材料作传感器已越益引起人们的注意,已有用植物的叶、果、花等研制植物组织电极的报道。 香蕉皮中含有草酸盐氧化酶,苹果中含有L-天冬酸脱羧酶。我们选择了香蕉皮和苹果作为生物催化材料,以二氧化碳气敏电极为基础电极,研制了两种植物组织电极。     

苹果品质检测的可见-近红外激光漫反射光谱图像法的方法研究

利用可见-近红外激光漫反射光谱图像法及化学计量学方法检测了苹果的可溶性固形物含量和硬度。为了消除苹果形状对品质检测的影响,分析了5个不同波长的激光(680,780,880,940和980 nm)照射在富士苹果果面形成的光斑图像,并通过一系列图像处理方法得出了的苹果形状修正算法。分别利用修正前后的光谱图像参数建立苹果可溶性固形物含量和硬度的偏最小二乘回归(PLSR)模型,模型预测值和真实值之间的相关系数从0.78和0.80分别提高到0.87和0.89。为了消除果面镜面反射对苹果内部品质检测的影响,文章提出了象素强度频率检测法,并比较了利用果面光斑图像中光强均值和不同强度对应的象素强度频率建立的苹果硬度和可溶性固形物含量的PLSR模型效果,得出象素强度频率的模型效果更好。苹果可溶性固形物含量和硬度PLSR模型中预测均方根误差(RMSEP)分别从1.28°Brix和8.23 N.cm-2降低到0.84°Brix和6.17 N.cm-2。     

Study and modelling of two apple quality attributes: the soluble solids content and the firmness

Recently, the basic dynamics of fruit characteristics have been modelled using a stochastic approach. The time evolution of apple quality attributes was represented by means of a system of differential equations in which the initial conditions and model parameters are both random. In this work, a complete study of two apple quality attributes, the soluble solids content and the firmness, is carried out. For each of these characteristics, the system of differential equations is linear and the state variables and the parameters are represented as random variables with their statistical properties (mean values, variances, covariances, joint probability density function) known at the initial time. The dynamic behaviour of these statistical properties is analysed. The variance propagation algorithm is used to obtain an analytical expression of the dynamic behaviour of the mean value, the variance, the covariance and the probability density function. A Monte Carlo method and the Latin hypercube method were developed to obtain a numerical expression of the dynamic behaviour of these statistical quantities and particularly to follow the time evolution of joint probability density function which represents one but the best mean to characterize random phenomena linked with fruit quality attributes.     

Determination of major phenolic compounds in apples: Part I—Optimization of high‐performance liquid chromatography separation with diode array detection

The separation of seven phenolic compounds including gallic acid, chlorogenic acid, epicatechin, quercitrin, rutin, phloridzin, and phloretin present in apple peel and pulp and differing in elution properties has been optimized using high‐performance liquid chromatography with diode array detection. Several stationary phases were tested to achieve the efficient separation of phenolic compounds in fruit extracts and C18 was found to be the most efficient. Core–shell and fully porous C18 packings were assessed with respect to the complex composition of the fruit extracts. The developed high‐performance liquid chromatography method comprised gradient elution in which mobile phase A was water at pH 2.8 adjusted with acetic acid and B was acetonitrile. The gradient shape was the following: 0 min 95% A/5% B, 2.5 min 85% A/15% B, 12 min 50% A/50% B, 15 min 95% A/5% B. The flow rate was 1 mL/min, injection volume 10 μL, and UV detection at 255, 280, 320, and 365 nm was applied. Our method was validated for both C18 core–shell and fully porous packings. The resolution 6.2–14.8, symmetry 0.99–1.34, peak capacity 18–60, peak area repeatability 0.45–1.00% relative standard deviation, calibration range 0.125–5 mg/mL (0.25–10 mg/mL for chlorogenic acid and rutin), correlation coefficients of calibration curve 0.9976–0.9997, and accuracy evaluated as recovery 95.56–107.54% were determined for the core–shell column.     

SFC-UV determination of diflubenzuron residues,teflubenzuron and triflumuron in apple and pear pulps for baby food

Summary A method to determine residues of diflubenzuron (DFB), teflubenzuron (TFB), triflumuron (TFM) at 0.01 ppm with recoveries above 60% in apple and pear pulps for baby food is described. DFB, TFB and TFM are extracted with methanol, and cleaned up by SPE using C18 stationary phase and methanol mobile phase. Analysis of the three pesticides is by SFC-UV at 254 nm using a Diol column, and CO₂ at 30 MPa and 40°C modified with acetonitrile (10%) mobile phase.