Simultaneous estimation of amylose,resistant, and digestible starch in pea flour by visible and near-infrared reflectance spectroscopy

Due to its health benefits, resistant starch (RS) has received increasing attention from the public, and there is a need to develop methods to measure the amylose and RS concentration in pea (Pisum sativum L.) flour. The aim of this study was to develop a visible and near-infrared reflectance (vis–NIR) model for the simultaneous determination of amylose, RS, and digestible starch (DS) in pea flour. A total of 123 dry pea samples consisting of different pea varieties grown in different environments were collected, and ground to flour, and then the vis–NIR spectra were scanned. The amylose, RS, and DS contents of the pea flours were also measured by an enzymatic colorimetric assay. The spectra data were calibrated with the enzymatic colorimetric-assayed values. Results showed that amylose, RS, and DS in the pea flours can be simultaneously estimated using the vis–NIR spectra. Instead of using the full spectrum (300–2300 nm), we found the most efficient wave bands lying in the visible region between 370 and 560 nm and the NIR spectra in the range of 1600–1800 nm. Using the stepwise regression with backward elimination method, the multiple linear regression (MLR) models were developed from the most efficient wavelengths. The MLR models had the determination coefficients R² of 0.95, 0.76, 0.80, and 0.88 for amylose, RS, DS, and total starch, respectively. The correlation coefficients between model estimated and the enzymatic colorimetric assayed values were 0.97, 0.80, 0.85, and 0.93 for amylose, RS, DS, and total starch, respectively.     

基于近红外光谱快速定量检测面粉中曲酸的方法建立

利用近红外光谱技术快速定量检测面粉中非法添加的褐变抑制剂曲酸。选取市场上常见3?种基本类型的面粉（高、中、低筋面粉）,分别制备曲酸质量分数为0.0%、0.5%、1.0%、3.0%、5.0%、10.0%的面粉样品,并采集其在1?000～2?400?nm波段下的光谱数据。对比不同预处理下高筋面粉样品数据所建偏最小二乘（partial least squares,PLS）回归模型效果,选取Savitzky-Golay一阶导数为最优预处理方法。采用区间偏最小二乘（interval partial least squares,iPLS）法选取1?088.8～1?153.5?nm为最佳光谱区间。结果表明,基于最佳光谱区间所建PLS回归模型预测效果优于基于全波段光谱数据所建模型。进一步,基于所选最优区间对中、低筋面粉和混合样品集分别建立PLS回归模型。高、中、低筋面粉及混合样品集基于最优区间的PLS模型的决定系数为0.949～0.972,标准误差为0.581%～0.830%,验证集标准偏差与预测标准偏差的比值为4.171～4.830。结果表明,基于最优区间的近红外光谱方法对不同类型面粉中曲酸质量分数为1.0%～10.0%的样品具有较好的预测结果,结合具有低检测限的化学检测方法,在对大批量样品的检测中可提高检测效率。     

Changes During Accelerated Storage in Millet–Wheat Composite Flours for Bread

Two millet–wheat composite flours, CF1 and CF2, were formulated based on the rheological and textural properties of dough using response surface methodology. The optimized contents of composite flour CF1 were 61.8% barnyard millet flour, 31.4% wheat flour, and 6.8% gluten, respectively. The optimized components of the composite flour CF2 were barnyard millet flour 9.1%, finger millet flour 10.1%, proso millet flour 10.2%, and wheat flour 70.6%. Millet–wheat composite flours were stored in three different packaging materials, namely, low-density polyethylene (LDPE), high-density polyethylene (HDPE), and metallized polyester (MP), at 90% RH and 40 °C temperature for 90 days. For the packaging of millet–wheat composite flour CF1, MP was found best among the tested packaging materials, where moisture gain in samples was minimum (55%) as compared with materials LDPE (124%) and HDPE (100%). Vitamin loss among the different packaging materials was not significantly different at the 5% level of significance. The shelf lives of the composite flours were estimated based on their critical moisture contents. After 90 days of storage of CF1, the highest retention of starch (91.85%) was recorded in MP packaging followed by HDPE (87.5%) and LDPE (84.8%). However, in CF2, the retention was not significant in all three packaging materials (P?相似文献   

Process Optimization by Response Surface Methodology and Characteristics Investigation of Corn Extrudate Fortified with Yam (Dioscorea alata L.)

Response surface methodology was used to investigate the optimum operation conditions of a single screw extruder and to analyze the effects of extrusion processing variables, including yam flour contents (10–30 %), moisture content (10–18 %), and screw speed (250–350 rpm) on characteristics of the corn–yam extrudates. Quadratic polynomial equations were also obtained by multiple regression analysis. The predicted models were adequate based on the lack-of-fit test and coefficient of determination obtained. By superimposing individual contour plots of the different responses, regions meeting the optimum conditions were also derived. The moisture content had critical effect on all responses variables. All the characteristic of the corn–yam extrudates evaluated were significantly affected by three process variables. Feed moisture content was the most significant variable with on most of characteristics. Increasing moisture content caused increase in bulk density, water absorption index and hardness, but decrease in radial expansion ratio. However, graphical optimization studies resulted in 21–23 %, 12–13 %, and 305–320 rpm of yam flour level, moisture content, and screw speed, respectively. The results suggested that corn extrudates fortified with yam produced by using the single-screw extruder are suitable for snack food development.     

Prediction of wheat quality parameters using near-infrared spectroscopy and artificial neural networks

In wheat and flour processing, the quality control needs quick analytical tools for predicting physical, rheological, and chemical properties. In this study, near infrared reflectance (NIR) spectroscopy combined with artificial neural network (ANN) was used to predict the flour quality parameters that are protein content, moisture content, Zeleny sedimentation, water absorption, dough development time, dough stability time, degree of dough softening, tenacity (P), extensibility (L), P/G, strength, and baking test (loaf volume and loaf weight). A total of 79 flour samples of different wheat varieties grown in different regions of Turkey were chemically analyzed, and the results of both NIR spectrum (400–2,498 nm) and chemical analysis were used to train/test the network by applying various ANN architectures. Prediction of protein, P, P/G, moisture content, Zeleny sedimentation, and water absorption in particular gave a very good accuracy with coefficient of determination (R ²) of 0.952, 0.948, 0.933, 0.920, 0.917, and 0.832, respectively. The results indicate that NIR combined with the ANN can successfully be used to predict the quality parameters of wheat flour.     

Application of full-factorial design for optimization of the moisture determination in wheat flour using infrared scales

We studied the parameters that may affect the analysis of the moisture content in wheat flour using infrared scales. The parameters were studied by one-factor at a time methodology and then, by full-factorial design (2³). The best condition using infrared scales occurred at 120 °C, with a sample weight of 1.5 g and an exposure time to infrared radiation of 6 min. We observed the interaction effect between the three factors studied. The analysis time was 60 times lower than classical method. The optimized method for determination of the moisture content in wheat flour using infrared scales was validated to range between 9 and 17 %.     

Evaluation of the TLC quantification method and occurrence of deoxynivalenol in wheat flour of southern Brazil

ABSTRACT

The study evaluated a QuEChERS (Quick, Easy, Cheap, Effective, Rugged and Safe) extraction method for use with a TLC quantification procedure for deoxynivalenol (DON). It also surveyed DON occurrence in wheat flour from the southern region of Brazil. Forty-eight wheat flour samples were analysed, divided into 2 different harvest lots, each consisting of 24 different brands. The detection and quantification limits of the method were 30 and 100 ng of DON on the TLC plate. The various concentrations of DON presented high linearity (R² = 0.99). A negative matrix effect (?28%) of the wheat flour was verified, with suppression of the chromatographic signal of DON, and 80.2–105.4% recovery. The TLC method was reliable for DON evaluation, with a coefficient of variation of less than 10%. High-performance liquid chromatography of lot 2 samples confirmed the presence of DON in all samples identified DON-positive by the TLC technique. Of the 48 wheat flour samples in lots 1 and 2 analysed by TLC, 33.3 and 45.8% of the samples respectively were above the Brazilian legislation limit. Correlations were observed between the water activity and DON content, and between the fungal count and moisture content of the wheat flours.     

The conditioning of wheat. An investigation into the conditioning requirements of Canadian western red spring no. 1

Canadian Western Red Springs (CWRS) No. 1 wheat has been conditioned to 16 and 17% moisture content by 2 and 4% water additions in each case. Lying times in the range 4–48 h before milling have been investigated. The milling performance of the conditioned wheat has been assessed in terms of extraction rate, colour and flour moisture content. Lying times in excess of 12 h were found to have no influence on extraction rate, colour and flour moisture content. For lying times less than 12 h the extraction rate was affected by the level of added water. When CWRS No. 1 wheat was milled at moisture contents in the range 14–18% using a fixed lying time, extraction rate, flour colour and ash fell with increasing wheat moisture content while flour moisture content increased.     

Effects of pre-heating temperature and formulation on porosity,moisture content,and fat content of fried batters

The effect of pre-heating temperatures on moisture and fat contents, and porosity of fried batters was studied. Batter pre-heated at 60 °C showed higher moisture content, lower fat content and lower porosity than non-pre-heated batter and batters pre-heated at 70 and 80 °C. Moisture content, fat content, and porosity at 4 min frying for batters with different pre-heating treatments ranged from 35.08 to 39.37, 3.92 to 5.16, and 13.14 to 45.31 %, respectively. Because of significant reduction in fat content, 60 °C pre-heating temperature was chosen to study the effect of batter formulations on moisture and fat contents, and porosity. Different wheat to rice flour ratios were prepared, and then each batter was pre-heated at 60 °C. Batters with higher wheat flour content showed higher moisture content, and lower fat content and porosity than batters with higher rice flour.     

Dietary exposure to aluminium from wheat flour and puffed products of residents in Shanghai,China

A dietary survey of 3431 residents was conducted by a 24-h dietary recall method in Shanghai, China, quarterly from September 2013 to September 2014. A total of 400 food samples were tested for aluminium concentration, including wheat flour and puffed products from 2011 to 2013. Probabilistic analysis was used to estimate the dietary exposure to aluminium from wheat and puffed products. The means of dietary aluminium exposure for children (2–6 years old), juveniles (7–17 years old), adults (18–65 years old) and seniors (over 65 years old) were 1.88, 0.94, 0.44 and 0.42 mg kg^?1 body weight (bw) week^?1 respectively, with a population average of 0.51 mg kg^?1 bw week^?1. The proportions of those who had aluminium exposure from wheat and puffed products lower than the provisional tolerable weekly intake (PTWI) were 77%, 90%, 97%, and 97% respectively from children to seniors. We estimated that the proportions of people at risk would decrease by 13%, 6%, 2% and 2% respectively under the new China National Standards – GB 2760–2014 National Food Safety for Standards for using food additives. The results indicated that aluminium from wheat flour and puffed products is unlikely to cause adverse health effects in the general population in Shanghai; however, children were at a higher risk of excess aluminium exposure. Significant improvements in reducing the dietary exposure to aluminium are expected in the population, especially for children after the implementation of GB 2760–2014.