Does organic farming reduce the content of Cd and certain other trace metals in plant foods? A pilot study

The effect of organic cultivation systems on the level of Cd in wheat was studied in two consecutive harvests. Additionally, the concentrations of Cd, Pb, Cr and Zn were analysed in single harvests of rye, carrots and potatoes from different farming systems. Wheat and rye were obtained from controlled field trials using several conventional and ecological systems at two separate locations in Sweden. Potatoes and carrots were collected at private farms with conventional or ecological production. These farms were juxtapositioned and had similar soil properties. The levels of Cd in the wheat did not correlate with the cultivation system or the Cd content in the soil. Conventionally grown wheat from one field trial showed a significantly higher Cd level compared with ecologically grown wheat, while in the other field trial significantly lower Cd levels were detected in the conventionally grown wheat. No statistically significant differences in the concentrations of Cd, Pb, Cr or Zn in rye, carrots and potatoes were detected between the cultivation systems. The results indicate that organic farming, at least in the short term, does not necessarily result in reduced levels of Cd and other potentially harmful metals in foods of vegetable origin. Factors other than cultivation system may be of greater importance for the final concentration of Cd and other metals in plant foods. © 2000 Society of Chemical Industry     

Cadmium in roadside grapes

The concentration of cadmium in unwashed wine grapes and leaves is considered as a function of the distance from the suspected source, an isolated straight road. Cadmium levels were determined by a.a.s. with electrothermal atomisation in a graphite furnace. The grape and leaf samples display an asymptotic decrease in cadmium concentration (c) according to the distance (d) from the edge of the road. The observed data can be fitted with the exponential function c=A+B exp (-Cd), the parameters being estimated by least-squares non-linear regression. The simple model allows the determination of the cadmium level at d→∞ (A) and at d=0 (A+B). The results obtained indicate that the effect of the presence of the road is not detectable beyond a distance of 50 m.     

A Meta‐Analysis of Enriched Pasta: What Are the Effects of Enrichment and Process Specifications on the Quality Attributes of Pasta?

Pasta products enriched with ingredients to improve their nutritional value or functionality have become increasingly popular, and substantial research efforts have been directed towards the development of new enriched pasta products. In this work, a meta‐analysis was conducted to quantify the impact of enrichment and process specifications on the quality attributes of pasta. A literature search revealed 66 studies on enriched pasta. Process specifications and quality attributes, namely proximate composition, dough, drying, cooking, and mechanical properties, color, and sensory attributes, were extracted from the studies and compiled in a data set. Analysis of the data set revealed significant differences between pasta enriched with high‐fiber ingredients and pasta enriched with pulse flour. High‐fiber ingredients generally preserved the quality attributes of pasta more effectively than pulse flour. Comparisons based on the drying temperature showed that high drying temperatures generally improve the cooking properties of enriched pasta. Sensory evaluations indicated that enrichment levels below 10% generally do not affect consumer acceptance, but higher enrichment levels significantly decrease it. Pearson correlation coefficients showed that the gelatinization temperature and Farinograph properties are useful indicators of the mechanical properties and sensory attributes of pasta. The meta‐analysis revealed the need to better understand the impact of the processing history of the enrichment ingredient on the quality attributes and the health benefits of enriched pasta.     

Assessment of homogeneity vs. heterogeneity of residual variance in random regression test-day models in a Bayesian analysis

Test-day first-lactation milk yields from Holstein cows were analyzed with a set of random regression models based on Legendre polynomials of varying order on additive genetic and permanent environmental effects. Homogeneity and heterogeneity of residual variance, assuming three and 30 arbitrary measurement error classes of different length were considered. Unknown parameters were estimated within a Bayesian framework. Bayes factors and a checking function for the cross-validation predictive densities of the data were the tools chosen for selecting among competing models. Residual variances obtained from 30 arbitrary intervals were nearly constant between d 70 and 300 and tended to increase towards the extremes of the lactation, especially at the onset. In early lactation, the temporary measurement errors were found to be larger and highly variable. A high order of the regression submodels employed for modeling the permanent environmental deviations tended to strongly correct the heterogeneity of the residual variance. Accordingly, the assumption of homogeneity of residual variance was the most plausible specification under both comparison criteria when the number of random regression coefficients was set to five. Otherwise, the heterogeneity assumption, using three or 30 error classes, was better supported, depending on the criterion and on the order of the submodel fitted for the permanent environmental effect.     

基于稻谷X射线荧光光谱测定快速识别糙米和精米中的镉含量

目的 基于稻谷镉的X射线荧光光谱测定, 建立糙米、精米镉的快速定量识别模型, 简化入仓稻谷重金属检测的砻谷、碾米等预处理步骤。方法 采用X射线荧光光谱法一一对应分析26组稻谷-糙米-精米样品中镉含量。根据线性、对数、逆、二次、三次、幂、指数等函数关系分别拟合稻谷-糙米、稻谷-精米、糙米-精米镉含量之间的回归模型。采用另外4组样品对决定系数(r2)大于0.95的模型准确性进行验证, 根据决定系数、误差值等筛选最优拟合模型。结果 稻谷-糙米-精米镉含量之间存在较强的相关性, 在此基础上建立的3个可食用米镉含量快速识别模型分别为: 稻谷-糙米三次函数回归模型Y=0.0131+0.7178X+0.5722X2-0.3492X3 (R2=0.9859); 稻谷-精米三次函数回归模型Y=0.0284+0.3779X+1.5500X2-1.2046X3 (r2=0.9855); 糙米-精米幂函数回归模型Y=0.9412×X1.0233 (r2=0.9902), 三个模型预测结果的绝对误差分别为8.91%、8.57%和10.24%。结论 本研究建立的回归模型具有良好的稻米镉含量相互预测性能, 该法有望简化稻谷镉检测前的砻谷、碾米等预处理流程, 提高检测效率。     

镉对玉米的毒害机理及积累和转运机制

由于工矿业的不合理发展,玉米(Zea mays L.)农业生产受到了土壤镉(Cd)污染的威胁。由于在Cd胁迫下玉米产量与品质降低,故外源Cd对玉米的毒害作用及其机理受到广泛关注。同时,玉米对Cd的吸收与积累导致Cd可能通过玉米产品进入食物链,威胁人类健康,因此对玉米Cd转运和积累机制的研究已经成为分子生物学与植物生理学研究的热点之一。文章通过介绍Cd胁迫对玉米内源性植物激素系统、光合作用、水分及矿质元素吸收的影响,分析Cd毒害机理,探讨了Cd在玉米中短距离运输和长距离运输的途径及镉移动过程中的积累机制,并提出了降低玉米Cd积累的农艺防控措施,以期为后续的研究提供新的思路与方向。     

Prediction of Cadmium content in brown rice using near‐infrared spectroscopy and regression modelling techniques

The feasibility of prediction of cadmium (Cd) content in brown rice was investigated by near‐infrared spectroscopy (NIRS) and chemometrics techniques. Spectral pretreatment methods were discussed in detail. Synergy interval partial least squares (siPLS) algorithm was used to select the efficient combinations of spectral subintervals and wavenumbers during constructing the quantitative calibration model. The performance of the final model was evaluated by the use of root mean square error of cross‐validation (RMSECV), root mean square error of prediction (RMSEP) and correlation coefficients for calibration set and prediction set (R_c and R_p), respectively. The results showed that the optimum siPLS model was achieved when two spectral subinterval and fifty‐two variables were selected. The predicted result of the best model obtained was as follows: RMSECV = 0.232, R_c = 0.930, RMSEP = 0.250 and R_p = 0.915. Compared with PLS and interval PLS models, siPLS model was slightly better than those methods. These results indicate that it is feasible to predict and screen Cd content in brown rice using NIRS.