流感病毒神经氨酸酶抑制剂的定量构效关系(QSAR)的研究

以31个分子结构与生物活性(-lgIC50)已知的流感病毒神经氨酸酶抑制剂为训练集,选用16个分子的理化描述子,包括分子的形状,静电作用能和范德华作用能以及疏水描述子,用二维定量构效关系(2D-QSAR)方法建立了预测模型。计算中使用偏最小二乘(PLS)和主成分分析(PCA)降低变量维数,减少噪音干扰。用交叉验证法(leave one out,LOO)检验了预测模型的可信性,并用一个由4个抑制剂组成的测试集进一步验证预测模型的预测能力,证实了QSAR预测模型有较好的预测能力。神经氨酸酶抑制剂的QSAR预测模型的建立为抗流感药物的设计和改进提供了有用的研究工具。     

基于机器学习算法的蒸发量模型评估

[目的]探讨合理的气候因子个数,建立蒸发量模型,提出基于特征选择算法筛选最优特征集。[方法]以陕西榆林、泾河和汉中3个气象站16年(2005-01至2021-03)的逐小时观测资料为研究对象,利用特征选择函数和遍历循环方法对模型参数、特征变量个数进行优化。基于最佳参数结合随机森林模型和多元线性回归模型两种机器学习算法建立榆林、汉中和泾河地区蒸发量模型,采用平均绝对误差、均方根误差和平方相关系数三项指标评估模型的预测精度。[结果]特征变量和随机森林模型中的决策树个数分别是8,61时,模型预测效果最佳。采用优化的随机森林模型、多元线性回归模型评估3个地区的平均绝对误差均为0,均方根误差除泾河地区相等外,榆林、汉中地区的均方根误差均小于优化的多元线性回归模型。优化的随机森林模型预测榆林、泾河和汉中地区蒸发量拟合效果分别为0.85,0.90,0.86,优化的多元线性回归模型的拟合效果分别为0.77,0.83,0.79。[结论]整体而言,优化的两种模型都具有良好的预测效果且随机森林模型的预测效果优于多元线性回归模型。     

体外模拟消化芝麻蛋白产生抗氧化肽的分离纯化与构效研究

为研究芝麻蛋白在胃肠道中产生抗氧化肽的结构与构效关系,本试验采用体外模拟消化水解芝麻蛋白,通过超滤水解液,制备液相分离,利用液质联用仪进行结构鉴定,合成相应多肽以验证活性,并对抗氧化活性最高的多肽开展构效关系研究和安全性预测.结果表明,芝麻蛋白经分离纯化与结构鉴定,共获得19条芝麻抗氧化肽,其中17条来自芝麻贮藏蛋白,...     

竖缝式鱼道内齐口裂腹鱼洄游行为模拟

鱼道是帮助洄游鱼类跨越河道内物理障碍的主要过鱼设施之一。针对鱼道结构优化试验耗时长、成本高的问题。该研究在物理试验基础上建立模拟鱼类运动的数值模型,基于竖缝式鱼道内齐口裂腹鱼的行为数据,结合机器学习和欧拉-拉格朗日智能体方法（Eulerian-Lagrangian-agent method,ELAM）建立了鱼类洄游路线预测模型。首先,将齐口裂腹鱼的游泳行为数据划分为3个数据集（顺流而下、侧向运动和逆流而上）;然后,根据不同机器学习算法（XGBoost、K-近邻、梯度提升决策树、随机森林）分别构建游泳行为分类模型和游泳速度回归模型,并通过试验结果对比,筛选出最优模型;最后,结合ELAM的框架,构建鱼类洄游数学模型,模拟了齐口裂腹鱼在3种体型的竖缝式鱼道中的洄游路线。结果表明：基于随机森林建立的游泳行为分类模型和游泳速度回归模型预测效果最佳,游泳行为分类精度为0.804,召回率为0.794,F1得分为0.798,3个数据集的游泳速度回归的R2均大于0.75。研究所建立的鱼类洄游数学模型能够较好的预测齐口裂腹鱼的洄游路线,可为相关鱼类保护措施的设计和优化提供参考。     

基于随机森林模型的耕地表层土壤有机质含量空间预测——以河南省辉县市为例

耕地表层土壤有机质含量与作物生长发育密切相关,掌握土壤有机质空间分布对土壤肥力定向培养和农业生产指导具有重要意义。本研究以河南省辉县市5 922个耕地资源管理单元图斑中心点为基础数据,并分别按8∶2、7∶3、6∶4的比例随机划分训练数据集和验证数据集,以土壤类型作为辅助定性变量,利用随机森林模型模拟预测土壤有机质含量与自然环境变量(坡向、曲率、坡度、高程、土壤质地、归一化植被指数NDVI)、社会经济因子(排水能力、灌溉状况)之间的复杂非线性关系。结果表明:①当训练集与检验集中样点数量的比例为8∶2时,对应的随机森林模型总体上预测精度较高;②选用80%基础数据作为训练集时,预测得到的地图与已有图件相比,相关性达到0.859;③当用303个实地数据验证时,预测值与实测值的皮尔逊相关系数为0.595。通过对影响因子的重要性排序,发现土壤质地是研究区农用地表层土壤有机质含量的最重要影响因子。因此,随机森林模型作为机器学习和数据挖掘的有效方法,能较好地模拟输入变量与有机质含量之间的关系,预测图件与实际情况相符,但对有机质含量精细的差异不能很好体现。     

ASD Field Spec3野外便携式高光谱仪诊断冬小麦氮营养

氮素营养诊断关键在于氮营养指数(nitrogen nutrient index,NNI)预测。对于冬小麦氮营养指数预测模型而言,如何选取预处理方法和建模方法不一而足,不同预处理和模型选取对预测结果精度的影响程度目前还不清楚。该研究以ASD Field Spec3野外便携式高光谱仪采集乐陵市冬小麦冠层高光谱数据,采用10种光谱预处理方法并结合3种模型(偏最小二乘回归、BP神经网络和随机森林算法)建立多种冬小麦氮营养指数高光谱预测模型。对比模型预测精度表明最佳的高光谱建模方法为随机森林算法结合SG卷积平滑预处理所建模型(预测集R2=0.795,RMSE=0.125,RE=11.7%)精度高、可靠性强,是筛选出最佳的冬小麦氮营养指数高光谱预测模型。该研究结果对冬小麦氮营养指数高光谱预测建模具有科学价值,为筛选最优高光谱预处理方法和预测模型提供技术参考。     

运用PLS算法由HJ-1A/1B遥感影像估测区域小麦实际单产

为进一步提高遥感估产精度,显示国产影像在农业估产中的应用效果。该研究以2010-2013年HJ-1A/1B影像为遥感数据,分析了卫星遥感变量与小麦实际单产的定量关系,运用偏最小二乘回归算法构建及验证了以实际单产为目标的多变量遥感估产模型,并制作了小麦实际单产空间等级分布图。研究表明:实际单产与所选用的大多数遥感变量间关系密切,且多数遥感变量两两间具有严重的多重相关关系;实际单产偏最小二乘回归模型的最佳主成分为5,且植被衰减指数、绿色归一化植被指数、调整土壤亮度的植被指数、比值植被指数和归一化植被指数为实际单产遥感估测的敏感变量;建模集和验证集实际单产估测模型的决定系数分别为0.74和0.70,均方根误差分别为754.05和748.20 kg/hm2,相对误差分别为11.5%和8.88%,且估测精度比线性回归算法分别提高20%以上和40%以上,比主成分分析算法分别提高18%以上和30%以上,说明偏最小二乘回归算法模型估测区域实际单产的效果要明显好于线性回归和主成分分析算法,该模型应用结果与小麦实际单产区域分布情况相符合,为提高区域小麦实际单产的遥感估测精度提供了一种途径。     

基于气象因子的长三角地区农田站点土壤水分时间序列预测

以长三角3省1市为研究区,旨在构建长三角地区土壤水分长时间序列,为农业生产和遥感算法提供数据支撑。研究基于空间匹配的站点土壤水分数据和气象数据,利用主成分分析得到4个有效主成分作为线性回归和BP神经网络模型的输入因子,建立土壤水分与气象因子间的定量关系,并评估所构建模型的精度。结果表明,基于全部站点数据建立的单一BP神经网络模型优于单一线性回归模型。单一线性回归模型的R 2=0.34,RMSE=0.046 m³/m³,MAE=3.67%;而单一BP神经网络模型的训练、验证和测试3个数据集的R 2均在0.64以上,RMSE<0.043 m³/m³,MAE低于3.4%。根据逐个站点分别构建分站点的BP神经网络模型,其总体精度高于基于全部站点数据构建的单一BP神经网络模型。分站点构建的BP神经网络模型的总体精度方面,3个数据集的R 2均值在0.75以上,RMSE<0.039 m³/m³,MAE低于3%。通过对逐个站点分别构建BP神经网络模型,获得了精度较高、较稳定的土壤水分拟合结果。     

基于电子鼻传感器阵列优化的甜玉米种子活力检测

针对甜玉米种子活力传统检测方法操作繁琐、重复性差等不足,该研究利用电子鼻技术建立甜玉米种子活力快速检测方法。利用电子鼻获取不同活力甜玉米种子的气味信息,再结合主成分分析(PCA,principal component analysis)、线性判别分析(LDA,linear discriminant analysis)、载荷分析(loadings)和支持向量机(SVM,support vector machine)对气味信息进行提取分析,建立甜玉米种子活力的定性定量分析模型。结果显示:PCA和LDA分析均无法区分不同活力的甜玉米种子,而SVM的鉴别效果较好。全传感器阵列数据集SVM分类判别模型训练集和预测集正确率分别为97.10%和96.67%,建模时间为30.75 s,回归预测模型训练集和预测集决定系数R~2分别为0.993和0.913,均方差误差分别为2.23%和8.50%。经Loadings分析将10个传感器阵列优化为6个。优化后传感器阵列数据集SVM分类判别模型训练集和预测集正确率分别为98.55%和96.67%,建模时间为21.81 s,回归预测模型训练集和预测集决定系数R~2分别为0.982和0.984,均方差误差分别为3.80%和3.01%。结果表明:基于SVM的电子鼻技术可以实现对不同活力甜玉米种子的高效判别和预测,将传感器阵列优化为6个,判别和预测效果均有所提升。该研究为电子鼻技术应用于甜玉米种子活力检测提供理论依据。     

基于PCA-SVR的冬小麦土壤水分预测

土壤含水量状况是影响农作物生长的重要因素,对农作物生长关键期土壤水分的精准预测是田间管理的重要内容。研究选取宝鸡市2014年至2016年冬小麦种植区3—5月的气象、地形和土壤属性3个方面共15个预测因子,建立基于主成分分析(principal component analysis,PCA)的支持向量回归机(support vector regression,SVR)模型预测0~20 cm和20~40 cm土层的土壤水分,并同时采用随机森林(random forest,RF)回归模型对同质数据进行预测分析,以对比分析PCA-SVR模型的预测效果。结果表明:PCA-SVR模型对宝鸡市冬小麦土壤水分的预测在0~20 cm和20~40 cm土层的平均预测精度分别为92.899%和92.656%,RMSE分别为7.521和8.011;随机森林回归预测模型在0~20 cm和20~40 cm土层的平均预测精度为87.632%和87.842%,RMSE分别为10.759和11.042。因此,PCA-SVR模型对宝鸡市冬小麦土壤水分具有更好的预测能力,且模型在0~20 cm土层的预测效果略优于20~40 cm土层。     

基于深度学习的甜味剂分类模型

针对开发甜味剂过程中筛选百万级别甚至千万级别的天然或合成分子需要大量时间和资金的问题,该研究提出了一种基于深度学习的甜味剂分类模型。首先对数据集进行了扩增和优化,生成分子指纹以及分子图片,然后将注意力机制加入到DenseNet结构中,对分子特征和提取的特征进行融合。在20 029个分子图像和分子指纹数据集上进行训练,并在独立测试集上进行模型检验。试验结果表明,分类准确率为0.934,准确率波动幅度小于0.005,4类物质（强甜味、弱甜味、无味、苦味）的分类精度均超过0.91,优于传统机器学习模型和常用的卷积神经网络模型,可以从大量分子中筛选并识别目标分子,能使相关研究人员更容易地筛选出潜在甜味剂,并为将来甜味剂的筛选提供了一种思路与方法。     

Constituents and their sweetness of food additive enzymatically modified licorice extract

Enzymatically modified licorice extract (EMLE) is a natural sweetener, which is prepared with cyclodextrin glucanotransferase. It is used because of its unique properties such as higher solubility and better taste than those of licorice extract. In the present paper, the structures of six major constituents isolated from EMLE were determined, and their sweetness was studied. The isolated compounds were glycyrrhizin (1), 3-O-[beta-D-glucuronopyranosyl-(1-->2)-beta-D-glucuronopyranosyl]liquiritic acid (2), and their derivatives glucosylated at the C-4 position of the terminal glucuronopyranose with additional one (3 and 4, respectively) and two (5 and 6, respectively) glucose moieties. Compounds 1 and 2 are the major and minor sweet constituents in licorice extract, respectively. Compounds 3-6 are new compounds isolated for the first time. Compound 2 was sweeter than compound 1. Interestingly, compound 3, which is a monoglucosylated derivative of compound 1, was sweeter than compound 4. The sweetness of both compounds was lower than that of the parent compounds, while the lingering sweet aftertaste was markedly improved. Compounds 5 and 6, which have two additional glucose moieties, showed only slight sweetness.     

Development of structure-taste relationships for monosubstituted phenylsulfamate sweeteners using classification and regression tree (CART) analysis

Twenty monosubstituted phenylsulfamates (cyclamates) have been synthesized and have had their taste portfolios determined. These have been combined with 63 compounds already in the literature to give a database of 83 ortho, meta, and para compounds. A training set of 75 compounds was randomly selected leaving eight compounds as a test set. A series of nine predictors determined with Corey-Pauling-Koltun models, calculated from the PC SPARTAN PRO program and Hammett sigma values taken mainly from the literature, have been used to establish structure-taste relationships for these types of sweeteners. The taste panel data for all compounds were categorized into three classes, namely, sweet (S), nonsweet (N), and sweet/nonsweet (N/S), and a novel "sweetness value" or weighting was also calculated for each compound. Linear and quadratic discriminant analysis were first used with the S, N, and N/S data, but the results were somewhat disappointing. Classification and regression tree analysis using the sweetness values for all 75 compounds was more successful, and only 14 were misclassified and six of the eight test set compounds were correctly classified. For the 29 meta compounds, one subset using just two parameters classified 83% of these compounds. Finally, using various methods, predictions were made on the likely tastes of a number of meta compounds and a striking agreement was found between the tree prediction and those given by earlier models. This appears to offer a strong vindication of the tree approach.     

Improved water solubility of neohesperidin dihydrochalcone in sweetener blends

Significant technological advantages in terms of sweetness synergy and hence cost-saving can be obtained if neohesperidin dihydrochalcone (NHDC) is used in sweetener blends with other intense or bulk sweeteners. The combination of NHDC with sodium saccharin or sodium cyclamate is an excellent method to improve the water solubility at room temperature of NHDC. In the case of NHDC-sodium saccharin, two different methods for blend preparation, a simple mixture and a cosolubilized mixture, can be used, with similar results obtained for solubility and solution stability properties. To improve temporally the water solubility of NHDC in combination with sodium cyclamate, it is absolutely necessary to prepare cosolubilized blends.     

单行甘薯秧蔓回收机设计与试验

针对目前国内甘薯秧蔓粉碎还田不能回收饲用或人工收割秧蔓劳动强度大的难题,该文设计了一种单行甘薯秧蔓回收作业机,可一次完成秧蔓喂入、切割粉碎、输送及集箱回收作业。应用Box-Behnken试验设计方法,以刀辊转速、机具前进速度、刀片离地间隙为试验因素,以秧蔓回收率、留茬长度、伤薯率为试验指标,对甘薯秧蔓回收机的工作参数进行试验研究,建立了试验指标与试验因素之间的回归模型,分析了各因素对试验指标的影响,并对试验因素进行了综合优化。最优工作参数组合为：刀辊转速2 000 r/min、机具前进速度2.5 km/h、离地间隙15 mm,秧蔓回收率为93.16%、留茬长度为33.8 mm、伤薯率为0.26%。研究结果可为甘薯秧蔓机械化回收饲用提供参考,对甘薯产业的轻简化生产、节本增效具有重要意义。     

Pentasaccharide glycosides from the tubers of sweet potato (Ipomoea batatas)

Sweet potato ( Ipomoea batatas) has been used as food and herb in many countries. In this research on the active constituents of sweet potato, nine compounds were isolated and identified, including seven new resin glycosides, batatosides A-G (1- 7), along with two known compounds, batatinoside I ( 8) and simonin IV ( 9). The structures of 1- 9 have been established by a combination of spectroscopic and chemical methods. The major characteristics of the new compounds are the presence of three different substituents. The absolute configuration of aglycones was established as S by Mosher's method. Batatoside E ( 5) showed weak cytotoxic activity against Hep-2 cells.     

Solution properties and sweetness response of selected bulk and intense sweeteners

Two bulk sweeteners (sucrose and maltitol) and four intense sweeteners (acesulfame K, aspartame, sodium cyclamate, and sodium saccharin) are used in this study. Densities and sound velocity values of the sweeteners in solution are measured at 20 degrees C, and their apparent molar and specific volumes, their isentropic apparent molar and specific compressibilities, as well as their compressibility hydration numbers are calculated and reported. The introduction of solute molecules in water results in a volume change of the solvent as a result of attractive forces exerted by the solute molecules; such forces are in the form of electrostrictive or hydrogen-bonding forces, or charge-dipole attraction. Changes of molar volumes with increasing concentration give an indication of the extent of solute-solute interaction, whereas isentropic compressibilities give a direct measurement of the state of hydration of the solute molecules. The compressibility hydration numbers reported give an indication of the number of water molecules disturbed by the presence of each solute molecule in solution. Isentropic compressibilities seem to be a more sensitive parameter for distinguishing the bulk sweeteners from the artificial sweeteners. The sweetness response of the sweeteners is then explained in terms of their solution behaviors.     

Simultaneous determination of saccharin and aspartame in commercial noncaloric sweeteners using the PLS-2 multivariate calibration method and validation by capillary electrophoresis

A new method to determine a mixture for sweetener sodium saccharin and aspartame in commercial noncaloric sweeteners is proposed. A classical full factorial design for standards was used in the calibration step to build the partial least-squares (PLS-2) model. Instrumental data were obtained by means of UV-visible spectrophotometry. Salicylic acid was used as an internal standard to evaluate the adjustment of the real samples to the PLS model. The concentration of analytes in the commercial samples was evaluated using the obtained model by UV spectral data. The PLS-2 method was validated by capillary zone electrophoresis (CZE), finding in all cases a relative error of less than 11% between the PLS-2 and the CZE methods. The proposed procedure was applied successfully to the determination of saccharin and aspartame in noncaloric commercial sweeteners.     

电渗析技术在大豆低聚糖溶液脱盐上的应用

从甜浆中提取的大豆低聚糖粗提液中含有很多的盐类,影响糖液的纯度。该试验通过离子交换膜辅助的电渗析法对大豆低聚糖模拟溶液进行脱盐处理,确定了较好的试验操作参数。试验结果表明:电渗析法对大豆低聚糖模拟液进行脱盐是可行的,且脱盐效果较好,脱盐率达到96.07%;该试验条件下较佳的工作电压为20 V,流量为60 L/h,样品稀释倍数为15倍。通过以上条件处理后,大豆低聚糖的保留率达到83.82%。