Structure and Processing Properties of Nine Yam (Dioscorea opposita Thunb) Starches from South China: A Comparison Study

In order to explore the processing and application potential of Chinese yam starch, nine kinds of Chinese yam starch (GY11, GY5, GY2, GXPY, LCY, SFY, MPY, SYPY, ASY) from South China were collected and characterized. The chemical composition, rheological properties, thermal properties, and in vitro starch digestion were compared, and the correlation between the structure and processing properties of these yam starches was analyzed using Pearson correlation. The results show that GY2 had the highest amylose content of 28.70%. All the yam starches were similarly elliptical, and all the yam starch gels showed pseudoplastic behavior. Yam starches showed similar pasting temperatures and resistant starch content, but SYPY showed the largest particle size (28.4 μm), SFY showed the highest setback (2712.33 cp), and LCY showed the highest peak viscosity (6145.67 cp) and breakdown (2672.33 cp). In addition, these yam starches also showed different crystal types (A-type, B-type, C-type), relative crystallinity (26.54–31.48%), the ratios of 1045/1022 cm⁻¹ (0.836–1.213), pasting properties, and rheological properties, so the yam starches have different application potentials. The rheological and pasting properties were related to the structural properties of starch, such as DI, Mw, and particle size, and were also closely related to the thermodynamic properties. The appropriate processing methods and purposes of the processed products of these yam starches can be selected according to their characteristics.     

免疫分析技术在农药残留分析中的研究进展及在中药中的应用展望

中药材的农药残留问题一直是人们关注的重点,免疫分析技术作为一项特异性强、灵敏度高的快速分析检测技术,在实现中药材农药残留快速筛查方面发挥着重要作用.该文结合近年免疫分析相关研究进展,对不同的免疫分析技术在中药农药残留分析方面的应用、技术优势以及局限性进行总结分析,并对免疫分析技术的发展前景进行了展望,对免疫分析技术在农...     

《光学学报》四十周年:温故开新,不惑笃行

自1981年创刊以来,《光学学报》以发表国内优秀光学科研成果为己任,为我国光学科技人员提供了高水平、活跃的学术交流平台.《光学学报》经历了近40年的洗礼,见证了国内一代代优秀光学科研人员的成长.本文首先回顾了《光学学报》从创刊到转企、集群化发展,再到数字化出版的变革之路;其次,统计了《光学学报》历年来的出版数据、数据库...     

Light Intensity and Photoperiod Affect Growth and Nutritional Quality of Brassica Microgreens

We explored the effects of different light intensities and photoperiods on the growth, nutritional quality and antioxidant properties of two Brassicaceae microgreens (cabbage Brassica oleracea L. and Chinese kale Brassica alboglabra Bailey). There were two experiments: (1) four photosynthetic photon flux densities (PPFD) of 30, 50, 70 or 90 μmoL·m⁻²·s⁻¹ with red:blue:green = 1:1:1 light-emitting diodes (LEDs); (2) five photoperiods of 12, 14, 16, 18 or 20 h·d⁻¹. With the increase of light intensity, the hypocotyl length of cabbage and Chinese kale microgreens shortened. PPFD of 90 μmol·m⁻²·s⁻¹ was beneficial to improve the nutritional quality of cabbage microgreens, which had higher contents of chlorophyll, carotenoids, soluble sugar, soluble protein and vitamin C, as well as increased antioxidant capacity. The optimal PPFD for Chinese kale microgreens was 70 μmol·m⁻²·s⁻¹. Increasing light intensity could increase the antioxidant capacity of cabbage and Chinese kale microgreens, while not significantly affecting glucosinolate (GS) content. The dry and fresh weight of cabbage and Chinese kale microgreens were maximized with a 14-h·d⁻¹ photoperiod. The chlorophyll, carotenoid and soluble protein content in cabbage and Chinese kale microgreens were highest for a 16-h·d⁻¹ photoperiod. The lowest total GS content was found in cabbage microgreens under a 12-h·d⁻¹ photoperiod and in Chinese kale microgreens under 16-h·d⁻¹ photoperiod. In conclusion, the photoperiod of 14~16 h·d⁻¹, and 90 μmol·m⁻²·s⁻¹ and 70 μmol·m⁻²·s⁻¹ PPFD for cabbage and Chinese kale microgreens, respectively, were optimal for cultivation.     

An Uzawa-type algorithm for the coupled Stokes equations

An Uzawa-type algorithm is designed for the coupled Stokes equations discretized by the mixed finite element method. The velocity solved by the presented algorithm is weakly divergence-free, which is different from the one solved by the common Uzawa method. Besides, an optimal relaxation parameter of the presented algorithm is provided.     

Scattering of Tollmien-Schlichting waves by localized roughness in transonic boundary layers

The laminar-turbulent transition in boundary-layer flows is often affected by wall imperfections, because the latter may interact with either the freestream perturbations or the oncoming boundary-layer instability modes, leading to a modification of the accumulation of the normal modes. The present paper particularly focuses on the latter mechanism in a transonic boundary layer, namely, the effect of a two-dimensional(2 D) roughness element on the oncoming Tollmien-Schlichting(T-S) modes when they propagate through the region of the rapid mean-flow distortion induced by the roughness. The wave scattering is analyzed by adapting the local scattering theory developed for subsonic boundary layers(WU, X. S. and DONG, M. A local scattering theory for the effects of isolated roughness on boundary-layer instability and transition: transmission coefficient as an eigenvalue. Journal of Fluid Mechanics, 794, 68–108(2006)) to the transonic regime, and a transmission coefficient is introduced to characterize the effect of the roughness. In the sub-transonic regime, in which the Mach number is close to, but less than, 1, the scattering system reduces to an eigenvalue problem with the transmission coefficient being the eigenvalue; while in the super-transonic regime, in which the Mach number is slightly greater than 1, the scattering system becomes a high-dimensional group of linear equations with the transmission coefficient being solved afterward. In the largeReynolds-number asymptotic theory, the K′arm′an-Guderley parameter is introduced to quantify the effect of the Mach number. A systematical parametric study is carried out,and the dependence of the transmission coefficient on the roughness shape, the frequency of the oncoming mode, and the K′arm′an-Guderley parameter is provided.     

粒子群算法优化中药化学成分的毛细管电泳分离条件

建立了一种基于粒子群优化算法的毛细管电泳条件辅助优化方法。以丹参为研究对象,将改良的色谱指数方程用于评价酚酸类成分的电泳分离性能,用粒子群优化算法对分离条件进行全局寻优,获得最佳的区带电泳分离条件(5.0 mmol/L硼砂,18.5 mmol/L磷酸二氢钠,6.1%乙腈,运行电压18.2 kV)。为进一步改善分离,在所获优化条件下添加50.0 mmol/L SDS,在胶束电动毛细管色谱分离模式下使酚酸类成分(原儿茶醛、丹参素、丹酚酸B等)得到更好分离。本方法准确可靠,可推广应用于其他复杂化学体系的毛细管电泳分离条件优化。     

Inhibition of Metalloproteinase Activity by Chinese Formulations Used to Treat Inflammatory Diseases

Introduction Matrixmetalloproteinases(MMPs)areaclassof zinc requiringextracellularendopeptidasesthatcanto getherdegradeallcomponentsoftheextracellularma trixandbasementmembranes[1—3].Theyplayimpor tantrolesinconnectivetissueremodeling,occurringin normalb…     

卷积神经网络用于近红外光谱古筝面板木材分级

目前,我国乐器制作行业在古筝面板用木材等级的筛选上主要依赖于技师主观评判,但此法缺少科学理论的依据,效率低,客观性及出材率的提高等方面受到限制,无法满足乐器市场的大量需求。实现古筝面板用木材快速、智能化的分级工作是一个急需解决的课题。近红外光谱非常适用于测量含氢的有机物质。古筝面板木材主要化学成分的化学键均由含氢基团组成,不同等级板材的化学成分存在差异,这些差异反映在近红外光谱中,为判断木材等级提供了可能。同时卷积神经网络对非线性数据具有较强的特征提取能力,所以提出一种应用卷积神经网络模型对光谱数据进行分析的方法,进而判别木材的等级。应用了Savitzky Golay一阶、二阶微分两种预处理方法和核主成分分析、连续投影算法两种数据压缩方法,通过所设计的卷积神经网络模型以样本识别准确率和模型构建过程中的损失值作为判定指标选出最佳预处理和数据压缩方法。为了提高模型提取分析光谱数据的能力和避免过拟合现象,应用了多通道卷积核、批量归一化和early stopping策略,将通过两层卷积层提取的特征信息送入全连接层,从而充分提取剩余信息,通过Softmax函数获得板材的最终预测等级,从而确定了最终模型。最终Savitzky Golay一阶微分和核主成分分析为最佳数据处理方法,同时得出用于区分不同等级的古筝面板用木材的主要关键谱带,分别为1 163~1 243, 1 346~1 375和1 525~1 584 nm。将该模型应用于测试集样本,古筝面板用木材的等级识别准确率为95.5%。实验结果表明所提出的方法可以高效地处理光谱数据,有效识别区分不同等级的古筝面板用木材的关键特征,从而为广阔的乐器市场提供一定的技术支持。     

中药微量元素含量区间尺最佳分级问题的探讨

在深入研究中药微量元素含量区间尺的基础上，从统计学角度对区间尺的最佳分级问题作了详细探讨，提出用5级区间尺来衡量中药中不同元素含量间相对高低水平，理论上更合理。