Prediction of traditionally utilised wheat dough technological quality parameters from Mixolab values: development and evaluation of regression models

The research was conducted with the aim to investigate the possibility of Farinograph, Extensograph and Amylograph values prediction with linear and/or multiple Mixolab regression models. In total, 163 flour samples were divided based on Machalanobis distances into three sets: prediction, validation and external sample set. Determination coefficients ranged from 0.145 to 0.640 for linear regression models and from 0.279 to 0.739 for multiple regression models. Internal and external validation of developed regression models was conducted. Testing of developed models resulted in a high share of samples for which predicted values were out of the ranges of method official reproducibility and a high share of samples for which predicted values were out of the quality level range obtained by analytical measurement. It was concluded that it is impossible to develop applicable regression models for prediction of Farinograph, Extensograph and Amylograph parameters on the basis of Mixolab values from standard protocol.     

混合试验仪确定冷冻面团馒头复配添加剂最佳配方

利用混合试验仪研究硬酯酰乳酸钠（SSL）、黄原胶、抗坏血酸（VC）对冷冻面团特性的影响。通过单因素试验、正交试验确定了冷冻面团复配添加剂的最佳配方为SSL0.1%、VC0.010%和黄原胶0.3%。用不同复配添加剂配方制作冷冻面团馒头,利用感官品质评分、质构品质测定进行综合评价,最佳结果与Mixolab试验结果一致。     

冷冻面团原料小麦粉的筛选及各指标的相关性分析

本实验选取了六种不同商业高筋小麦粉,采用粉质仪、拉伸仪和糊化仪对其进行基础成分和流变学特性的测定,并对所得指标数据进行相关性分析,同时对应用各小麦粉制作的冷冻面团的质构特性进行测定分析,筛选出北大荒高筋小麦粉适于制作冷冻面团。各特性指标进行相关性分析结果显示,吸水率与水分含量、蛋白质含量、最大拉伸阻力呈显著正相关(p<0.05),相关系数为0.849、0.789、0.828;形成时间与湿面筋含量、最大拉伸比例呈显著正相关(p<0.05),相关系数为0.900、0.885;形成时间与拉伸阻力、最大拉伸阻力、拉伸比例呈极显著正相关(p<0.01),相关系数为0.986、0.958、0.933;水分含量与最大拉伸阴力呈显著正相关(p<0.05),相关系数达到0.828;蛋白质含量与拉伸阻力、最大拉伸阻力、拉伸比例呈显著正相关(p<0.01),相关系数为0.986、0.958、0.933。      

小麦品质指标与面团流变学特性指标的相关性及多元回归分析

选取安徽、河北、河南、江苏、山东5个省的小麦样品313份,测定了样品品质指标和粉质拉伸特性指标,进行了相关性分析,并分别以面团稳定时间、最大拉伸阻力、拉伸面积为因变量,以硬度指数、体积质量、千粒重、沉淀指数、降落数值、蛋白质含量、湿面筋含量、面筋指数为自变量,进行了多元回归分析.分析结果表明,硬度指数与面团吸水率、最大拉伸阻力、拉伸面积极显著正相关,与弱化度极显著负相关;体积质量与与形成时间和延伸度极显著负相关;千粒重与弱化度极显著正相关,与稳定时间、质量指数以及拉伸特性指标均极显著负相关;除降落数值与延伸度、湿面筋含量与弱化度相关性不显著外,降落数值、蛋白质含量、湿面筋含量、面筋指数与粉质拉伸特性的其他指标均呈显著或极显著相关性.     

照相测量中胸围拟合的回归分析

在二维照相非接触式人体测量系统中,如何获取人体胸围数据是关键性问题。基于照相测量的方法,分析了人体胸围尺寸拟合中的难点。对照相测量中获得的人体相关部位的数据进行分析,发现一些数据同胸围数据的相关性,通过相关分析、回归分析等统计分析方法推导出适合青年女性的胸围回归公式。通过新文化式原型样衣的实验,验证了公式的可靠性,取得了满意的效果,为实现非接触式人体自动测量奠定了基础。     

Development and evaluation of multiple regression models for prediction of sweet cherry liking

In two experiments, multiple regression models were developed and evaluated to identify the relevant sensory attributes for cherry liking. In Experiment 1, 16 judges evaluated 18 cherry varieties for seven visual characteristics (colour intensity, uniformity-of-colour, speckles, size, stem length, external firmness and ‘visual’ liking) and seven flavour/texture characteristics (flesh firmness, flesh colour intensity, juiciness, sweetness, sourness, flavour intensity and ‘flavour/ texture’ liking). Stepwise multiple regression was used to develop the most appropriate statistical models for prediction of visual and flavour/texture liking based on visual and flavour/texture characteristics, respectively. Both models were simple and easily understandable with two sensory variables. The best model for visual liking required only size and uniformity-of-colour variables; whereas, the best model for flavour/texture liking required sweetness and flavour intensity variables. In Experiment 2, 18 judges evaluated 30 sweet cherry cultivars, using the same methodology, to create a validation data set. Correlation coefficients (R) and prediction standard errors (PSEs) between the observed (Experiment 2) and predicted (Experiment 1) liking scores were used to evaluate the prediction equations. The prediction equation for flavour/texture liking was most satisfactory (R = 0.85, PSE = 0.61). A new equation developed from the validation data confirmed the importance of sweetness and flavour intensity. In contrast, the prediction equation for visual liking was less satisfactory (R = 0.56) and a new equation developed from the validation data set confirmed only size as an important variable.     

Short communication: Genetic correlation and heritability of milk coagulation traits within and across lactations in Holstein cows using multiple-lactation random regression animal models

Genetic parameters of milk rennet coagulation time (RCT) and curd firmness (a₃₀) among the first 3 lactations in Holstein cows were estimated. The data set included 39,960 test-day records from 5,216 Estonian Holstein cows (the progeny of 306 sires), which were recorded from April 2005 to May 2010 in 98 herds across the country. A multiple-lactation random regression animal model was used. Individual milk samples from each cow were collected during routine milk recording. These samples were analyzed for milk composition and coagulation traits with intervals of 2 to 3 mo in each lactation (7 to 305 DIM) and from first to third lactation. Mean heritabilities were 0.36, 0.32, and 0.28 for log-transformed RCT [ln(RCT)] and 0.47, 0.40, and 0.62 for a₃₀ for parities 1, 2, and 3, respectively. Mean repeatabilities for ln(RCT) were 0.53, 0.55, and 0.56, but 0.59, 0.61, and 0.68 for a₃₀ for parities 1, 2 and 3, respectively. Mean genetic correlations between ln(RCT) and a₃₀ were −0.19, −0.14, and 0.02 for parities 1, 2, and 3, respectively. Mean genetic correlations were 0.91, 0.79, and 0.99 for ln(RCT), and 0.95, 0.94, and 0.94 for a₃₀ between parities 1 and 2, 1 and 3, and 2 and 3, respectively. Due to these high genetic correlations, we concluded that for a proper genetic evaluation of milk coagulation properties it is sufficient to record RCT and a₃₀ only in the first lactation.     

Comparison of random regression test-day models for Polish Black and White cattle

Test-day milk yields of first-lactation Black and White cows were used to select the model for routine genetic evaluation of dairy cattle in Poland. The population of Polish Black and White cows is characterized by small herd size, low level of production, and relatively early peak of lactation. Several random regression models for first-lactation milk yield were initially compared using the “percentage of squared bias” criterion and the correlations between true and predicted breeding values. Models with random herd-test-date effects, fixed age-season and herd-year curves, and random additive genetic and permanent environmental curves (Legendre polynomials of different orders were used for all regressions) were chosen for further studies. Additional comparisons included analyses of the residuals and shapes of variance curves in days in milk. The low production level and early peak of lactation of the breed required the use of Legendre polynomials of order 5 to describe age-season lactation curves. For the other curves, Legendre polynomials of order 3 satisfactorily described daily milk yield variation. Fitting third-order polynomials for the permanent environmental effect made it possible to adequately account for heterogeneous residual variance at different stages of lactation.     

Short communication: Optimal random regression models for milk production in dairy cattle

Legendre polynomials of orders 3 to 8 in random regression models (RRM) for first-lactation milk production in Canadian Holsteins were compared statistically to determine the best model. Twenty-six RRM were compared using LP of order 5 for the phenotypic age-season groupings. Variance components of RRM were estimated using Bayesian estimation via Gibbs sampling. Several statistical criteria for model comparison were used including the total residual variance, the log likelihood function, Akaike's information criterion, the Bayesian information criterion, Bayes factors, an information-theoretic measure of model complexity, and the percentage relative reduction in complexity. The residual variance always picks the model with the most parameters. The log likelihood and information-theoretic measure picked the model with order 5 for additive genetic effects and order 7 for permanent environmental effects. The currently used model in Canada (order 5 for both additive and permanent environmental effects) was not the best for any single criterion, but was optimal when considering all criteria.     

Understanding cow evaluations in univariate and multivariate animal and random regression models

The relationship between cow evaluations from a 305-d lactation yield animal model [i.e., lactation model (LM)] and a random regression model (RRM) were studied using the first-lactation milk yield of 2,477,807 Holstein heifers. In the LM analysis, 2 values of heritability were used, 0.35 (LM1-H) or 0.57 (LM2-H), the latter being equal to that used in the random regression model for the analysis of the Holstein test-day records (RRM-H). The relative weights on parent average (PA) and yield deviations (YD) were computed and studied to understand factors contributing to reranking of cows’ predicted transmitting abilities (PTA) from the various models. The degree of relatedness and inbreeding were calculated for the top 2,000 cows from the various models. Analyses of Jersey milk yield in the first 3 parities was implemented using 305-d lactation yield multivariate animal (MLM-J) and random regression models (MRRM-J). The ability of both models using only first-parity yield records to predict evaluations in second and third parities when records for these later parities were excluded was studied in a sample of cows. The correlations of cow PTA between LM1-H or LM2-H and RRM-H were 0.91 and 0.92, respectively, in the Holstein data. The data sets used were identical in this case for all models in terms of number of cows and yield records. The correlations were slightly lower at 0.89, 0.87, and 0.88 for parities 1, 2, and 3 in the Jersey analyses, where the data sets were not identical. The relative weights on PA and YD were 0.28 (0.11) and 0.72 (0.89), respectively, from the LM2-H (RRM-H). The RRM-H placed more emphasis on YD and therefore on Mendelian sampling deviations. Thus, the top 2,000 cows from the RRM-H were less related and inbred. The average additive genetic relationship was 22% greater in the LM2-H and average inbreeding coefficients were 0.68 and 0.43% for the LM2-H and RRM-H, respectively. When records were initially available in the first parity, the MRRM-J predicted PTA in parities 2 and 3 with about 2 to 7% greater accuracy compared with the MLM-J.     

Chemical,Technological, and Sensory Properties of Wheat Grains (Triticum aestivum L) as Affected by Gaseous Ozonation

Gaseous ozonation, an emerging technology, is applied to microbiological decontamination and to the degradation of residues and contaminants in wheat grains. However, due to its high oxidizing capacity, ozone may cause undesirable effects on the quality of grains or in their derivatives. This study aimed to evaluate the influence of ozone gas on wheat grain quality when exposed to different levels of ozone concentration, exposure time, and grain mass, using a full 2³ factorial design. After the milling of ozonized grains, two fractions were evaluated: flour (A) and bran plus germ (B). In fraction A, the quality of the wheat flour was analyzed by both alveography and farinography. The flour extraction rate, falling number and gluten contents were also measured. The chemical and mineral profiles were determined in both fractions. A sensory evaluation, using the difference-from-control test, was applied to investigate the possible differences in aroma or in overall appearance of the flour obtained from the ozonized grains. The results showed that ozone concentration (60 mg/L) positively affected (p < 0.05) the toughness and the falling number of the flour. The other parameters of alveography, as well as farinography, gluten content, chemical composition, mineral, and sensory profiles were not affected (p > 0.05) by ozonation. This study demonstrated that gaseous ozonation, when applied under the conditions of 10 to 60 mg/L, from 2 to 5 h of exposure, grain mass from 2 to 5 kg, does not cause any negative impact on the wheat quality.     

Genetic analysis of somatic cell score in Norwegian cattle using random regression test-day models

The dataset used in this analysis contained a total of 341,736 test-day observations of somatic cell scores from 77,110 primiparous daughters of 1965 Norwegian Cattle sires. Initial analyses, using simple random regression models without genetic effects, indicated that use of homogeneous residual variance was appropriate. Further analyses were carried out by use of a repeatability model and 12 random regression sire models. Legendre polynomials of varying order were used to model both permanent environmental and sire effects, as did the Wilmink function, the Lidauer-M?ntysaari function, and the Ali-Schaeffer function. For all these models, heritability estimates were lowest at the beginning (0.05 to 0.07) and higher at the end (0.09 to 0.12) of lactation. Genetic correlations between somatic cell scores early and late in lactation were moderate to high (0.38 to 0.71), whereas genetic correlations for adjacent DIM were near unity. Models were compared based on likelihood ratio tests, Bayesian information criterion, Akaike information criterion, residual variance, and predictive ability. Based on prediction of randomly excluded observations, models with 4 coefficients for permanent environmental effect were preferred over simpler models. More highly parameterized models did not substantially increase predictive ability. Evaluation of the different model selection criteria indicated that a reduced order of fit for sire effects was desireable. Models with zeroth- or first-order of fit for sire effects and higher order of fit for permanent environmental effects probably underestimated sire variance. The chosen model had Legendre polynomials with 3 coefficients for sire, and 4 coefficients for permanent environmental effects. For this model, trajectories of sire variance and heritability were similar assuming either homogeneous or heterogeneous residual variance structure.     

Random regression test-day models with residuals following a Student's-t distribution

First-lactation milk yield test-day records of Canadian Holsteins were analyzed by single-trait random regression test-day models that assumed normal or Student's-t distribution for residuals. Objectives were to test the performance of the robust statistical models that use heavy-tailed distributions for the residual effect. Models fitted were: Gaussian, Student's-t, and Student's-t with fixed number of degrees of freedom (equal to 5, 15, 30, 100 or 1000) for the t distribution. Bayesian methods with Gibbs sampling were used to make inferences about overall model plausibility through Bayes factors, posterior means for covariance components, estimated breeding values for regression coefficients, solutions for permanent environmental regressions, and residuals of the models. Bayes factors favored Student's-t model with the posterior mean of degrees of freedom equal to 2.4 over all other models, indicating very strong departure from normality. Number of outliers in Student's-t model was reduced by 35% in comparison with the Gaussian model. Differences in covariance components for regression coefficients between models were small, and rankings of animals based on additive genetic merit for the first two regression coefficients (total yield and persistency) were similar. Results from the Gaussian and Student's-t models with fixed degrees of freedom become more alike (smaller departures from normality for Student's-t models) with increasing number of degrees of freedom for the t-distributions. For any pair of Student's-t models, the one with the smaller number of degrees of freedom for the t-distribution was shown to be superior. Similarly, number of outliers increased with increasing degrees of freedom for the t distribution.     

基于回归分析方法的烟丝结构与卷烟物理指标关系研究

为探究烟丝结构及其均匀性对卷烟物理质量稳定性的影响,通过筛分将成品烟丝细化为8个不同的烟丝结构层S1~S8,进而对烟丝结构与物理指标(重量、圆周、吸阻、硬度、端部落丝量、含末率)做相关性分析及回归分析,探讨了影响物理指标及其稳定性的具体烟丝分布。结果表明:烟丝结构对各物理指标影响强弱依次为:圆周>烟支单重>硬度标偏>含末率>吸阻>硬度;与物理指标关系密切的烟丝结构分布层主要是S2、S4、S5、S6、S7。根据烟丝结构与物理指标间的回归方程可针对性的对波动较大的物理指标进行优化调整,从而提高卷烟质量及其稳定性。      

核桃乳理化稳定指标的回归相关性分析

对核桃乳各项基本指标及稳定系数之间的相关性进行回归分析,确定与稳定系数相关性高的因素;进而比较相关系数及回归方程中的相关性。结果表明,可以通过脂肪上浮率预测产品的稳定系数,通过脂肪上浮率预测产品的沉淀率,通过平均粒度预测产品的黏度,并且准确度均高达99%以上。     

Genetic parameters for functional traits in dairy cattle from daily random regression models

The objective of the research was to estimate genetic parameters, such as heritabilities and genetic correlations, using daily test day data for milk yield (MY), milking speed (MS), dry matter intake (DMI), and body weight (BW) using random regression methodology. Data were from first lactation dairy cows (n = 320) from the Chamau research farm of the Swiss Federal Institute of Technology, Switzerland over the period from April 1994 to 2004. All traits were recorded daily using automated machines. Estimated heritabilities (h²) varied from 0.18 to 0.30 (mean h² = 0.24) for MY, 0.003 to 0.098 (mean h² = 0.03) for MS, 0.22 to 0.53 (mean h² = 0.43) for BW, and 0.12 to 0.34 (mean h² = 0.23) for DMI. A permanent environmental effect was included in both the univariate and bivariate models, but was assumed constant in estimating some genetic correlations because of convergence problems. Estimated genetic correlations varied from 0.31 to 0.41 between MY and MS, from −0.47 to 0.29 between MY and DMI, from −0.60 to 0.54 between MY and BW, from 0.17 to 0.26 between MS and DMI, from −0.18 to 0.25 between MS and BW, and from −0.89 to 0.29 between DMI and BW. Genetic correlations for MY, MS, DMI, and BW from calving to midlactation decreased similarly to 0.40, 0.36, 0.14, and 0.36 and, at the end of the lactation, decreased to −0.06, 0.23, −0.07, and 0.09, respectively. Daily genetic variance-covariance of many functional traits are reported for the first time and will be useful when constructing selection indexes for more than one trait based on longitudinal genetic parameters.     

Evolution of anthocyanins during maturation of tempranillo grape variety (Vitis vinifera) using polynomial regression models

In general, the anthocyanin content of grapes increases during ripening but presents a concentration minimum a few days before physiological maturity. This minimum is sharper for the acyl derivatives. Significant behavioural differences were found between monoglucosides and their acyl derivatives. A polynomial model was used to describe the evolution of anthocyanins in the maturation of Tempranillo grapes (Vitis vinifera L).     

Genetic parameters for test-day electrical conductivity of milk for first-lactation cows from random regression models

Electrical conductivity (EC) of milk has been introduced as an indicator trait for mastitis during the last few decades. The correlation of EC to mastitis, easy access to EC data, and the low cost of recording are properties that make EC a good indicator trait for mastitis. In this study, EC was measured daily during the lactation and available from 2101 first-lactation Holstein cows in 8 herds in the United States. Data were analyzed with an animal model that included herd-test-day, age at calving and days in milk (DIM) as fixed effects, and random additive genetic and permanent environmental effects. A repeatability model and 5 random regression (RR) models with increasing order of Legendre polynomials were used. The goodness of fit for the different models was evaluated based on several tests. Our results indicate that the best model was a RR model with a fourth-order Legendre polynomial for both additive genetic and permanent environmental effects. Heritability estimates obtained with this model were from 0.26 to 0.36. Due to the relatively high heritability obtained for EC of milk, EC might be a potential indicator trait to use in a breeding program designed to reduce the incidence of mastitis.     

新疆春小麦粉品质特性与饺子品质关系的研究?

为了测定新疆小麦粉品质与饺子加工品质关系,选择不同筋力的30个2000年后新疆生产种植的春小麦品种,分别测定其小麦粉理化指标和粉质参数,并对其进行饺子制作试验.通过分析小麦粉理化指标和粉质参数与饺子品质的关系可知,小麦粉灰分含量、吸水率、面团形成时间、稳定时间、弱化度、评价值、峰值黏度和稀懈值是影响饺子得分的主要因素.形成时间、稳定时间、评价值、峰值黏度和稀懈值与饺子总分呈正相关关系,其中,稳定时间和评价值与饺子总分的相关系数较大,对饺子品质的影响也较大.小麦粉灰分含量、吸水率和弱化度与饺子总分呈显著或极显著负相关,对饺子品质有负影响作用.通径分析和回归分析表明,面团稳定时间对饺子总分影响最大.     

青年女子体型的特征指标及岭回归预测研究

 利用三维人体测量仪,选择430名年龄在18~23岁之间的江浙籍青年女子测量其体型指标;对影响人体体型的46个部位尺寸数据进行了聚类分析,得到了决定并区分女子体型的典型指标:身高、前长、胸高、胸围、臀围和总肩宽。建立了能广泛应用人体细部规格与基本部位之间的岭回归模型关系,从而可以通过典型指标预测细部规格,其预测模型值的准确度高,相关性检验显著,可使制作的服装样板更加准确、合体。