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1.
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.  相似文献   

2.
The development and ripening process of sweet cherry (Prunus avium L. cv. 4-70) on the tree was evaluated. For this purpose, 14 different stages were selected in accordance with homogeneous size and color. Some parameters related to fruit quality, such as color, texture, sugars, organic acids, total antioxidant activity, total phenolic compounds, anthocyanins, and ascorbic acid were analyzed. The results revealed that in sweet cherry, the changes in skin color, glucose and fructose accumulation, and softening process are initiated at early developmental stages, coinciding with the fast increase in fruit size. Also, the decrease in color parameter a was correlated with the greatest accumulation of total anthocyanins. Ascorbic acid, total antioxidant activity (TAA), and total phenolic compounds decreased during the early stages of sweet cherry development but exponentially increased from stage 8, which coincided with the anthocyanin accumulation and fruit darkening. TAA showed positive correlations (r(2) = 0.99) with both ascorbic acid and total phenolic compounds and also with the anthocyanin concentration from stage 8. Taking into account the reduced shelf life of sweet cherry and to ensure that these fruits reach consumers with the maximum organoleptic, nutritional, and functional properties, it is advisable to harvest sweet cherries at stage 12 of ripening.  相似文献   

3.
A combination of gas chromatography (GC) and chemometrics was evaluated for its ability to differentiate between apple juice samples on the basis of apple variety and applied heat treatment. The heat treatment involved exposure of 15 mL juice samples for 30 s in a 900 W domestic microwave oven. The chromatographic results were subjected to two chemometric procedures: (1) partial least squares (PLS) regression and (2) linear discriminant analysis (LDA) applied to principal component (PC) scores. The percent correct classification of samples were obtained from PLS and LDA in terms of separation on the basis of apple variety and applied heat treatment. PLS gave the highest level of correct classification of the apple juice samples according to both variety and heat treatment, 92.5% correct classification in each case. When LDA was performed on the PC scores obtained from GC analysis, 87.5% and 80% of samples were correctly classified according to apple variety used and applied heat treatment, respectively.  相似文献   

4.
Modification of an existing single kernel wheat characterization system allowed collection of visible and near-infrared (NIR) reflectance spectra (450–1,688 nm) at a rate of 1 kernel/4 sec. The spectral information was used to classify red and white wheats in an attempt to remove subjectivity from class determinations. Calibration, validation, and prediction results showed that calibrations using partial least squares regression and derived from the full wavelength profile correctly classed more kernels than either the visible region (450–700 nm) or the NIR region (700–1,688 nm). Most results showed >99% correct classification for single kernels when using the visible and NIR regions. Averaging of single kernel classifications resulted in 100% correct classification of bulk samples.  相似文献   

5.
A new device for evaluating the continuity of taste was developed with the use of surface plasmon resonance (SPR). The model of lingual cells was constructed with liposomes immobilized onto an L1 sensor chip for SPR. Using this device, we classified food components into three categories according to the sensorgram pattern and residual ratio on lipid bilayer. Samples in group A strongly interacted with lipid bilayer, those in group B poorly interacted, and those in group C belong to neither group A nor group B. Sweet proteins and gymnemic acids that prolonged sweet perception were categorized in group A. Almost all the carbohydrates investigated and aspartame, of which the taste perception does not continue, belonged to group B. This device made it possible to detect the interaction with lipid bilayer and dissected the mechanism of taste continuity.  相似文献   

6.
基于HJ-CCD数据和决策树法的干旱半干旱灌区土地利用分类   总被引：2，自引：5，他引：2  
为了实现干旱半干旱灌区地表信息低成本、高效率的动态监测,利用HJ-CCD数据的多时相和多光谱信息,探讨了平罗县土地利用遥感分类方法。首先建立研究区内典型地物的NDVI时间序列曲线,提取反映该区物候模式的时序特征参数;然后对土壤信息丰富的3月份多光谱影像进行主成分变换,选取第1主成分(PC1)作为光谱特征参数,最后基于分类回归树(classification and regression tree,CART)算法进行决策树监督分类。总体分类精度达到92.26%,Kappa系数为0.91,比最大似然法分类结果精度提高了2.58%。研究表明:构建的NDVI时间序列曲线对研究区内的地类具有较强的代表性,提取的时间维和光谱维的分类参数对各地类均有很好地区分性,CART决策树算法分类结果清晰准确且精度较高。该方法为HJ小卫星在干旱半干旱区等区域的深入应用提供科学依据和实证基础。  相似文献   

7.
于慧春  褚冰  殷勇 《农业工程学报》2012,28(23):258-264
电子鼻检测中常用的特征鉴别能力评价方法有2种,一是对判别结果的直观分析,二是对判别正确率的统计计算。但是,当判别正确率相同时,对于不同特征间鉴别能力的差异,2种方法都不能进行准确的定量评价。为实现特征鉴别能力的准确度量,以不同种类食醋为检测对象,对检测信号提取面积斜率比、方差、积分、平均微分值、相对稳态平均值、小波能量等6种特征参量,并将特征参量与类别间的相关系数作为特征鉴别能力的度量指标。计算结果可知：面积斜率比特征参量的相关系数绝对值最小,为0.1027,积分特征参量的相关系数绝对值最大,为0.6455。表明面积斜率比特征参量的鉴别能力最低,积分特征参量的鉴别能力最高。Fisher判别结果也证明了特征参量的鉴别能力越高,其分类效果越好。因此,用特征参量与类别间的相关系数作为特征鉴别能力的度量是合适的、也是有效的。  相似文献   

8.
食品工业一直在积极地发现新的甜味分子,传统发掘方法费时费力,效率较低。该研究基于分子的甜味和分子结构相关的假设,利用文献、专利及数据库中的数据,建立甜味、非甜味分子数据集和甜度分子数据集,采用随机森林和支持向量机算法建立定性构效关系模型定性预测甜味分子;采用主成分回归、k最邻近回归、随机森林回归和偏最小二乘回归四种算法建立定量构效关系模型定量预测甜味分子的甜度。研究发现,随机森林算法模型的分类效果最好,接受者操作特性曲线下的面积为0.987,准确度为0.966;随机森林回归模型的甜度预测效果最好,决定系数为0.82,误差均方根为0.60。联用这两个模型在食品成分数据库中,发现542个具有甜味剂潜力的食品分子。  相似文献   

9.
基于电子鼻传感器阵列优化的甜玉米种子活力检测   总被引：2，自引：5，他引：2  
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。  相似文献   

10.
食醋电子鼻检测中一种特征参量评价方法   总被引：4，自引：4，他引：0  
电子鼻检测中常用的特征鉴别能力评价方法有2种,一是对判别结果的直观分析,二是对判别正确率的统计计算。但是,当判别正确率相同时,对于不同特征间鉴别能力的差异,2种方法都不能进行准确的定量评价。为实现特征鉴别能力的准确度量,以不同种类食醋为检测对象,对检测信号提取面积斜率比、方差、积分、平均微分值、相对稳态平均值、小波能量等6种特征参量,并将特征参量与类别间的相关系数作为特征鉴别能力的度量指标。计算结果可知:面积斜率比特征参量的相关系数绝对值最小,为0.1027,积分特征参量的相关系数绝对值最大,为0.6455。表明面积斜率比特征参量的鉴别能力最低,积分特征参量的鉴别能力最高。Fisher判别结果也证明了特征参量的鉴别能力越高,其分类效果越好。因此,用特征参量与类别间的相关系数作为特征鉴别能力的度量是合适的、也是有效的。  相似文献   

11.
Japan’s only native crayfish species Cambaroides japonicus has been declining dramatically in the past few decades. For the purpose of conservation planning, twenty-two coastal streams were surveyed to investigate summer distributions of crayfish in relation to stream and riparian environment. Classification and regression trees were used to predict the occurrence and abundance of crayfish. The classification tree model with stream variables as predictors showed that crayfish would occur in swift or high gradient streams (correct classification rate = 91%). Within those streams, however, crayfish only inhabited depositional microhabitats, in which the areas are limited in availability. Crayfish were not found in gentle, low gradient streams containing abundant depositional microhabitats. This paradoxical distribution pattern was attributed to availability of boulder substrates in swift or high gradient streams. The regression tree model indicated that crayfish abundance was determined primarily by the percentage of boulder substrates and the presence of fish (observed vs. predicted r = 0.64).The classification tree model using only riparian variables indicated that the total woody plant (mainly broadleaf species) density followed by the percentage of early successional species such as alder and willow determined the splits of the tree model (correct classification rate = 95%). A leaf processing experiment on 10 riparian plant species suggested that crayfish preferred high nitrogen (or low C/N) leaves.These results suggest that swift or high gradient fishless streams associated with abundant cover in dense broadleaf forest serve conservation areas for this endangered crayfish, and that consideration of riparian composition may facilitate conservation efforts.  相似文献   

12.
A genetically and environmentally diverse collection of maize (Zea maize L.) samples was evaluated for physical properties and grit yield to help develop a standard set of criteria to identify grain best suited for dry-milling. Application of principal component analysis (PCA) reduced a set of approximately 500 samples collected from six states to 154 maize hybrids. Selected maize hybrids were placed into seven groups according to their dry-milled grit yields. Regression analysis explained only 50% of the variability in dry-milling grit yield. Patterns of differences in the physical properties for the seven grit yield groups implied that the seven yield groups could be placed into two or three groups. Using two pattern recognition techniques for improving classification accuracy, quadratic discriminant analysis and the classification and regression tree (CART) model, dry-milled grit yield groups were predicted. The estimated correct classification rates were 69–80% when the samples were divided into three yield groups and 81–90% when samples were divided into two yield groups. The results indicated the comparable success of both techniques and the superiority of the decision tree algorithm to quadratic discriminant analysis by offering higher accuracy and clearer classification rules in differentiating among dry-milled grit yield groups.  相似文献   

13.
Germination and subsequent drying of oat produced significantly different sensory profiles depending on processing parameters such as drying speed and temperature profile. The most salient sensory attributes for processed oat were roasted odor and flavor, sweet taste, intense odor, intense aftertaste, and hard, crisp, brittle texture (P < 0.05). High temperatures (>85°C) were necessary to produce these sensory attributes, and quick drying after germination resulted in higher levels of intensity of favorable sensory attributes. The total amount of volatile compounds was higher in native (ungerminated) oat than in processed oat. During germination, and particularly during the drying treatment, the profile of volatile compounds changed. The most abundant volatile compounds responsible for odor were dimethyl sulfide, hexanal, pentanal, and iso butanal. The relative amount of dimethyl sulfide increased as a function of temperature in drying, whereas hexanal, pentanal, and isobutanal disappeared during heating, as did several other small ketones, alcohols, and esters. The germinated oat dried at high temperatures (65–93°C and 65–85°C) was perceived as being roasted, sweet, and nutty. Sensory and instrumental profile analyses of selected volatile compounds using partial least squares (PLS) regression techniques showed that these sensory attributes were clearly related to dimethyl sulfides and isobutanol. A moist and earthy odor was related to cymene, limonene, and isobutanal. Phenolic compounds significantly influenced oat flavor, whereas lipids had a negligible effect.  相似文献   

14.
Phenolic compounds in 46 Spanish cider apple varieties were determined by RP-HPLC with direct injection. Several pattern recognition procedures, including principal component analysis (PCA), linear discriminant analysis (LDA), and partial least squares (PLS-1), were applied to the data in an attempt to classify the samples into bitter and nonbitter categories. Reliable decision rules were obtained by both LDA and PLS-1. LDA achieved 91.3 and 85.7% correct classification respectively, for internal and external evaluation of the model.  相似文献   

15.
Fourier transform infrared (FTIR) spectroscopy and attenuated total reflection (ATR) sampling have been used to detect adulteration of honey samples. The sample set comprised 320 spectra of authentic (n = 99) and adulterated (n = 221) honeys. Adulterants used were solutions containing both d-fructose and d-glucose prepared in the following respective weight ratios: 0.7:1.0, 1.2:1.0 (typical of honey composition), and 2.3:1.0. Each adulterant solution was added to individual honeys at levels of 7, 14, and 21% w/w. Spectral data were compressed and analyzed using k-nearest neighbors (kNN) and partial least squares (PLS) regression techniques. A number of data pretreatments were explored. Best classification models were achieved with PLS regression on first derivative spectra giving an overall correct classification rate of 93%, with 99% of samples adulterated at levels of 14% w/w or greater correctly identified. This method shows promise as a rapid screening technique for detection of this type of honey adulteration.  相似文献   

16.
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.  相似文献   

17.
The potential of near-infrared (NIR) spectroscopy to determine the geographical origin of honey samples was evaluated. In total, 167 unfiltered honey samples (88 Irish, 54 Mexican, and 25 Spanish) and 125 filtered honey samples (25 Irish, 25 Argentinean, 50 Czech, and 25 Hungarian) were collected. Spectra were recorded in transflectance mode. Following preliminary examination by principal component analysis (PCA), modeling methods applied to the spectral data set were partial least-squares (PLS) regression and soft independent modeling of class analogy (SIMCA); various pretreatments were investigated. For unfiltered honey, best SIMCA models gave correct classification rates of 95.5, 94.4, and 96% for the Irish, Mexican, and Spanish samples, respectively; PLS2 discriminant analysis produced a 100% correct classification for each of these honey classes. In the case of filtered honey, best SIMCA models produced correct classification rates of 91.7, 100, 100, and 96% for the Argentinean, Czech, Hungarian, and Irish samples, respectively, using the standard normal variate (SNV) data pretreatment. PLS2 discriminant analysis produced 96, 100, 100, and 100% correct classifications for the Argentinean, Czech, Hungarian, and Irish honey samples, respectively, using a second-derivative data pretreatment. Overall, while both SIMCA and PLS gave encouraging results, better correct classification rates were found using PLS regression.  相似文献   

18.
基于深度学习的甜味剂分类模型   总被引：1，自引：1，他引：0  
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。  相似文献   

19.
无人机遥感在森林树种精细和高效分类制图中具有巨大的潜力。为了快速准确获取森林的优势树种分布信息,该研究探讨了半监督学习方法在树种分类方面的有效性。以福建省福州市、龙岩市和三明市的4个试验区为例,构建精简的ResNet18为主干的UNet树种分类模型（UNet-ResNet14*）,使用交叉熵和Dice系数的联合损失函数来优化模型参数,对比分析Self-training和Mean teacher两种不同的半监督学习方法在无人机影像森林树种分类模型的泛化能力。结果表明,以ResNet14*作为主干的分类模型与其他模型相比精度更高且预测速度更快,当联合损失函数权重值为0.5的情况下模型预测效果最好,总体精度达到了91.15%。经过Self-training的模型在木荷、马尾松、杉木3个样本充足的类别中精度均有所提升,总精度为91.08%,比原始模型略低,但在独立验证区的精度为88.50%,比原始模型高;Mean teacher方法的总精度为88.56%,在独立验证区的精度为73.56%。因此,研究认为可以采用Self-trainin半监督方法结合UNet-ResNet14*的方案快速得到试验区的树种组成信息。  相似文献   

20.
Examining the predictive capability of statistical models with data independent from that used to derive the model is a vital step in the iterative procedure of assessing model performance. I derived logistic regression models of the habitat use of the rufous treecreeper (Climacteris rufa) at two spatial scales: woodland (territory selection model) and territory (nest-site selection model). The performance of these models was assessed in relation to the original data collected and validated with new, independent data. When applied to the original data, the territory model had a high predictive capability correctly classifying 90% of sites (n=100) that were either occupied or unoccupied by treecreepers. Correct classification rate was reduced to 70% (n=50) when the model was applied to the validation data. Model performance was generally robust when probability of occurrence values for the species were varied. In contrast, the nest-site model had lower predictive capabilities correctly classifying between 66 and 68% of sites, and performed relatively poorly when probability values were varied. The performance of the models differed slightly between the original and validation data, and substantially between the spatial scales examined. Territory use by rufous treecreepers could be predicted with some confidence indicating that the territory model may be a useful tool for habitat management. Nest-site use could not be predicted with confidence probably as a result of the high abundance of suitable, but unused, nest sites in the study area.  相似文献   

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