响应面法优化玉米苞叶中木聚糖的提取工艺

为了给玉米苞叶工业化生产木聚糖提供基础研究资料,本研究以玉米苞叶为原料,采用响应面法(RSM)对玉米苞叶木聚糖碱法提取工艺进行优化研究,选择碱浓度、提取温度和提取时间作为考察因素,以玉米苞叶木聚糖提取率作为评价指标,考察3个不同因素及其交互作用对玉米苞叶木聚糖提取率的影响。研究结果表明:玉米苞叶木聚糖的最佳提取工艺条件为氢氧化钠浓度9.2%(M/V)、提取温度93.0℃、提取时间13.0 h;在此工艺参数条件下提取3批玉米苞叶,获得的木聚糖平均提取率为(15.8±1.2)%(n=3),与采用响应面法优化回归模型预测提取率(16.0%)基本一致。     

Psychometric Properties of Geometrical Texture Features for Tactile Roughness Sensation of Fabric Surfaces

The lack of understanding of the psychometric properties on the basic texture features forming tactile texture sense hinders the development of haptic rendering technology of textiles. The differential threshold and Weber fraction were investigated for a deep understanding of how surface texture features of fabrics affect the perceived roughness sensation by the constant stimulus method and the paired comparison method. The results showed that the differential threshold for the mean deviation of surface profile was0. 86 μm,and that the differential threshold of texture spatial period(TSP) was 2. 48 mm. And also,the difference thresholds and Weber fraction were affected by the reference stimulus intensity. As there is a significant interaction between four extracted texture feature indexes,any of the indexes alone cannot represent roughness sensation of fabrics.     

Anthropomorphic Classification of Tactile Qualities of Woven Fabrics Based on Skin/Textile Friction-Induced Vibrations

The common method classifying tactile qualities of fabrics is indirectly based on their difference of purely mechanical and physical properties. When human skin slides across fabric surfaces, the friction interaction between fabrics and skin will occur and trigger the cutaneouS tactile receptors, which are responsible for perceived tactile sensation. By the extracted features from friction- induced vibration signals, this paper presents an anthropomorphic classification method classifying tactile qualities of fabrics. The friction-induced vibration signals are recorded by a three-axis accelerator sensor, and the entice testing procedure is conducted in an anthropomorphic way to obtain vibration signals. The fast Fourier transform （FFT） is applied to analyzing the recoded signals, and then the classification features are extracted from the FFT data by the neurophysiological properties of tactile receptors. The extracted features are used to classify fabric samples by the softness sensation and the roughness sensation, respectively, and the classification performance is checked by a comparison with those in a sensory evaluation procedure. The results showed that the anthropomorphic objective classification method was precise and efficient to clarify tactile qualities of woven fabrics.