镉胁迫下磷供应对芥菜生长和镉吸收的影响

采用土培和水培试验,研究了镉胁迫下磷供应对芥菜生长和镉吸收的影响。土培试验表明:施磷可以提高镉胁迫下小叶芥菜和雪里蕻种子的发芽率,提高小叶芥菜的生物量,而对雪里蕻生物量影响不大;施磷可以减少土壤中有效态镉含量,明显降低植株体内镉含量;植株体内的全磷含量随外加磷浓度的提高而显著增加。水培结果表明:镉胁迫下,磷供应对雪里蕻植株生物量影响不大;随着磷供应水平的增加,植株体内的全磷含量明显增加,但植株地上部镉、锌、钙、镁、锰等元素的含量明显降低。     

硅对盐胁迫下黄瓜幼苗生长和矿质元素吸收的影响

采用幼苗水培实验,研究外源硅对盐胁迫下黄瓜幼苗生长过程中吸收某些矿质元素的影响。对植株地上部和地下部各元素的分析表明,盐胁迫条件下,外源硅有效调节了黄瓜根系对Na 、Ca2 、K 的吸收以及向地上部的转运。适量的硅降低了黄瓜根系从介质中吸收Na 量,并减少其向地上部的运输,而增加了植株体对K 、Ca2 的吸收和转运量,有效缓解了Na 对黄瓜植株体造成的盐胁迫伤害,保证了黄瓜幼苗的正常生长。在相同的处理条件下,盐分敏感品种的Na 在根系和地上部累积量都要比耐盐品种高,而K 的积累量却正好相反,这可能是耐盐品种减轻盐害的主要方式。对其它营养元素的研究表明,施硅抑制了对N素的吸收,对P素的吸收则影响不大。     

山西省褐土施用钾肥对谷子 养分吸收及产量形成的影响

本文选用具有代表性两种母质发育的褐土进行盆栽试验。结果表明，红土母质褐土施钾在拔节期谷子对N、P、K、Ca、Mg、Fe、Mn、Cu和Zn的吸收均有促进作用，而在黄土母质褐土上谷子对Ca、Mg和Mn的吸收都随施钾量增加而下降。施钾对谷子苗期生长发育有明显的促进作用，有助于谷子穗分化，增加千粒重，加速光合产物的运输，提高谷子产量。     

设施栽培下仙客来的养分吸收规律研究

以设施栽培的仙客来‘NP3’为材料,探讨了仙客来的干物质积累和矿质养分吸收积累规律。结果表明,设施栽培条件下,成品时干物重为32.49g的仙客来单株矿质养分的需求总量为2.51g。越夏后10月份是仙客来干物质和养分积累的重要时期,N的吸收量最大,每日每株吸收11.36mg;K次之,9.56 mg;P为2.44 mg;Ca为3.83mg;Mg为2.36mg。不同生育期对矿质养分的吸收比例不同,但N/K基本平衡在1:1。     

Cd对油菜种子发芽与幼苗生长的生态毒性

通过水培实验研究了Cd胁迫下,油菜种子发芽及幼苗生长状况。结果表明:Cd胁迫下,发芽率、发芽势、发芽指数以5 mg L-1Cd浓度为阈值呈现低促高抑现象,发芽指数与Cd浓度曲线相关性好于发芽率和发芽势;活力指数、总长、芽长、根长、总重、芽重、根重表现为单抑现象。Cd对根生长抑制作用大于芽,逐步回归发现,Cd主要通过抑制根生长达到对幼苗生长抑制。种子电解质外渗率和根细胞有丝分裂指数分别与Cd浓度成极显著相关,相关系数分别为0.603**和-0.571**。因子分析发现,根长较其它指标对Cd敏感,可用于Cd污染的监测指标。     

不同品种生姜的营养特性和养分吸收规律

连续三年多点研究不同品种生姜的营养特性和养分吸收规律。结果表明,柴姜全株养分平均含量的高低顺序为N>K>P>Mg>Ca>Zn,N、P、K、Ca、Mg、Zn比例为100:14.7:99.2:1.8:6.0:0.3,养分吸收量也较低,N∶P∶K约为7∶1∶7。狮头姜K含量最高,含P量较柴姜明显下降,K、N含量显著提高;养分吸收比例为100:11.9:128.9:1.4:5.1:0.2,吸P量占的份额较小,K、N比例增大,N∶P∶K约为8∶1∶11。狮头姜单位产量所需养分数量,P、Ca、Mg和Zn较柴姜增加不多,K和N大幅度提高。     

柠檬酸对高岭石的溶解作用

采用间歇法(batch method)研究柠檬酸对高岭石溶解的影响。结果表明:低浓度(0.02mmolL-1)柠檬酸可促进高岭石中Ca2 、Mg2 、Na 少量的释放。当柠檬酸浓度分别为1.0mmolL-1和8mmolL-1时,Ca2 ,Mg2 ,K ,Na ,Si,Al3 阳离子的释放量也相应地增加。释放的Ca2 、Mg2 主要来自高岭石表面的吸附,而Na 、K 则来自高岭石的溶解。     

纳米硫化铅离子敏感材料的研究

该文采用均相沉淀法研制了硫化铅纳米粒子,对影响纳米硫化铅晶体形成的各种因素作了详细和系统的探讨,确定了合成纳米硫化铅的最佳工艺路线.在反应温度为1～10℃,络合剂EDTA与铅离子的浓度比为l,pb2+的初始浓度为0.075 mol/L,pH为3.0～3.5,Na2S溶液的滴加速度为2 mL/min及乙醇/水比为1/1的条件下,可得到平均粒径为30纳米的硫化铅颗粒.另外,利用纳米硫化铅作为活性物质,研制了纳米硫化铅PVC膜电极,电极在铅离子浓度1.0×10-1～1.0×10-4mol/L范围内呈线性响应,电极的检测下限为6.0×10-5mol/L.K+、Na+、Ca2+、Mg2+、Co2+、Cu2+、Fe2+、Mn2+、Fe3+、Al3+对电极无干扰,而Ag+、Zn2+、Cd2+、Hg2+对电极有一定的干扰.     

小麦生长期土壤养分与根系活力变化及其相关性研究

研究了小麦生长期内土壤氮、钾与小麦根系活力变化及其相关性。结果表明,土壤速效氮、速效钾和非交换性钾含量随小麦生育进程呈现有规律的变化;小麦根系活力呈现先增加,孕穗期峰值出现后迅速下降,成熟时根系活力下降到最低值的变化规律,不同施肥处理小麦整个生育期内根系活力大小顺序为:MNPK、NPK>NK>N、NP>CK、M。土壤速效氮、速效钾、非交换性钾含量与小麦根系活力呈显著或极显著正相关,说明土壤N、K养分有效性的高低是影响小麦根系活力的重要因素。     

水分胁迫和氮素有限亏缺对小麦拔节期某些生理特性的影响

在营养液培养条件下,研究了水分轻度胁迫、氮素有限胁迫对冬小麦小偃22拔节期NR活性、根系活力等生理特性、养分累积及小麦产量的影响。结果表明,水分、氮素亏缺使叶绿素含量及叶片NR活性低于对照水平,根系活力,K3Fe(CN)6还原活性降低;水分胁迫影响大于氮素亏缺影响,水分和氮素亏缺之间有显著地交互作用。水分胁迫下,小麦植株地上部氮、磷、钾含量高于对照水平,但根系含量降低;氮素亏缺下,地上和根系的养分含量均低于对照水平;水分和氮素之间有极显著地交互作用。拔节时期水分、氮素亏缺使小麦成熟期的产量降低。     

东北农田黑土中Cd、Pb、As含量空间分异特征分析

采用点面结合方法,研究了东北区农田黑土中Cd、Pb、As含量的空间分异特征。结果表明,三种元素含量的变异系数为Cd>Pb>As。Cd、Pb的平均含量高于其背景值;其中Cd有45个样品超过了国家二级标准限值。Cd、Pb、As含量由南至北未表现出明显的分布规律。对煤矿区周围农田土壤的调查发现,煤矿是其周围农田土壤的主要污染源。采用最优内插法得到了长春市市郊农田黑土中Cd、Pb、As含量的空间分布图,结果表明人为活动显著改变了局部地区Cd、Pb、As的含量,污染源主要为汽车尾气和固体废弃物的堆积。对三种元素垂直分布进行了分析,剖面土层Cd、Pb、As主要来自于表面污染源,向下迁移作用还不很强烈。     

Se和Cd在土壤-植物系统中的迁移与食品安全

本文就Se和Cd在土壤-植物系统中的迁移及其与食品安全及人体健康之间的潜在关系进行了综合评述。Cd和Se在植物中积累并迁移到植物的可食或收获部分,取决于土壤条件、气候因子、农艺管理措施等。Cd是对食物链造成污染的重要元素,其在土壤中的富集通常是由工农业生产或城市人为污染造成的,减少Cd对土壤的污染及Cd污染土壤的生物修复已成为土壤学、环境科学及生态学研究的热点。Se是一种对动植物有益的元素,在土壤中含量过低会引发人体疾病,但Se含量过高也会导致污染并引发人体疾病;土壤中的高浓度Se通常来自于含Se量高的母岩以及燃煤的灰尘污染;基于食品安全的需要,中国在重视Se素营养补给的同时,要防止富Se地区及人为因素造成的Se污染。     

RGB图像颜色检测的Cd（II）浓度测量研究

在实验中,镉离子（Cd（II））与对硝基苯重氮氨基偶氮苯反应的溶液随着Cd（II）浓度从0.0660～0.6482μg/mL会有颜色深浅的变化。为了探求颜色变化与Cd（II）浓度之间的关系,本研究包含了红绿兰（ RGB）测量结构、实验图像采集、对实际采集的RGB图像数据处理,其中重点在于RGB图像处理中的图像定位、图像分割和RGB图转YUV图时V值计算。最终通过非线性拟合得到颜色变化（ V值）与Cd（ II）五种浓度之间的关系服从指数函数关系。     

不同栽培方式对镉污染水稻土籼、粳稻根表铁膜铁、镉含量及根镉含量的影响

通过对镉污染水稻土籼、粳稻分蘖、孕穗、灌浆和收获期根表铁膜的铁、镉和根系镉含量的测定,研究淹水、覆膜、覆草和湿润栽培对籼、粳稻吸镉量的影响。结果表明:1)分蘖期,淹水和覆草栽培籼稻根表铁膜铁含量高于粳稻;覆膜和湿润栽培的粳稻根镉含量高于籼稻。2)孕穗期,淹水和覆膜栽培的籼稻根表铁膜铁含量高于粳稻;湿润栽培的籼稻根表铁膜镉含量高于粳稻;覆膜、覆草和湿润栽培的籼稻根镉含量低于粳稻。3)灌浆期,淹水和湿润栽培籼稻根表铁膜铁含量高于粳稻;覆膜和湿润栽培的籼稻根表铁膜镉含量低于粳稻;根镉含量籼稻低于粳稻。4)收获期,根表铁膜铁含量籼稻低于粳稻;根表铁膜镉含量覆膜栽培的籼稻高于粳稻;根镉含量覆膜、覆草和湿润栽培的籼稻低于粳稻。     

Simultaneous measurement of Pb, Cd and Zn using differential pulse anodic stripping voltammetry at a bismuth/poly(p-aminobenzene sulfonic acid) film electrode

A novel sensor was developed for simultaneous detection of Pb, Cd and Zn, based on the differential pulse anodic stripping response at a bismuth/poly(p-aminobenzene sulfonic acid) (Bi/poly(p-ABSA)) film electrode. This electrode was generated in situ by depositing simultaneously bismuth and the metals by reduction at −1.40 V on the poly(p-ABSA) modified electrode. Compared with the bismuth film electrode, the Bi/poly(p-ABSA) film electrode can yield a larger stripping signal for Pb, Cd and Zn. Under the optimum conditions, a linear response was observed for Cd and Zn in the range from 1.00 to 110.00 μg L⁻¹ and for Pb in the range from 1.00 to 130.00 μg L⁻¹. The detection limits of Pb(II), Cd(II) and Zn(II) were 0.80, 0.63 and 0.62 μg L⁻¹, respectively. Finally this sensor had been applied to the simultaneous determination of Pb(II), Cd(II) and Zn(II) in river water samples and the results were quite corresponding to the value obtained by atomic absorption spectrometry.     

Effects of cadmium and copper treatments and water stress on the thermal emission from peas (Pisum sativum L.): Controlled environment experiments

Pea plants (Pisum sativum L., cv. Feltham First) were grown in hydroponic solution and in vermiculite in controlled conditions and were treated with various concentrations of Cd and Cu in the two types of rooting medium. Relative canopy temperatures ($\text{Tini}$) were estimated from thermal images obtained with an AGA “Thermovision 680” infrared camera. Stomatal resistances ($\text{R}$), leaf temperatures measured with thermocouples ($\text{Tini}$) and plant water potentials (ψ) were also recorded. Metal-treated plants in hydroponic solution appeared to show a slight decrease in $\text{Tini}$ (in the order of 0.2 °C) relative to control plants, at concentrations up to 100 ppm Cd or Cu. At 200 ppm Cd or Cu, $\text{Tini}$ of treated plants was about 1 °C higher than control, associated with visual toxicity symptoms. $\text{R}$ in these plants was typically 5–10 sec cm^?1, compared with under 5 sec cm^?1 in control plants, and probably limited evaporative cooling. Plants in vermiculite gave results consistent with those above, and were also used for a water stress experiment. Prewilting water stress caused an increase in $\text{Tini}$ of up to 3.5 °C relative to fully watered control plants and caused an increase in $\text{R}$ up to about 20 sec cm^?1. These effects obscured thermal manifestations of metal toxicity. It is therefore suggested that thermal effects of geochemical metal anomalies may be most readily observed when vegetation is not under water stress, although it is also pointed out that metal-stressed and normal plants may show different responses to soil water deficits.     

Simultaneous determination of Zn(II), Cd(II) and Hg(II) in water

The use of artificial neural networks (ANNs) as a tool for simultaneous determination of Zn(II), Cd(II) and Hg(II) in water has been investigated, by employing an optode based on the 2-(5-bromo-2-pyridylazo)-5-(diethylamino)phenol (Br-PADAP) complex immobilised on Amberlite XAD-4 resin.

Studies were performed with binary and ternary mixtures of Zn(II), Cd(II) and Hg(II) ions in the 0–3.0 mg l⁻¹ range (prepared in pH 8.0 NH₄Cl solution), in order to avoid sensing phase saturation. A 0.1 mol l⁻¹ HCl solution was employed to regenerate the optode after each measurement. Reflectance measurements were recorded in the 400–800 nm region after pumping metal ion solution for 1, 1.5, 2.0, 2.5 and 3.0 min. Spectra were smoothed by employing a weighted sliding average of three reflectance intensities (weights of 1:3:1) and normalised to the reflectance intensities of the immobilised reagent in the NH₄Cl solution. A feed-forward ANN with error back-propagation training algorithm was employed for data treatment. The ANN was initially fed through seven inputs neurons, corresponding to reflectance intensities at 558, 568, 583, 590, 605, 615 and 623 nm, and optimised with respect to the number of hidden neurons, momentum and learning rate. Binary mixtures of Zn(II) and Cd(II), and Hg(II) and Cd(II) were employed to evaluate the capability of prediction by the ANN. Measurements were carried out in triplicate leading to standard deviations (expressed in mg l⁻¹) better than 0.29 for Cd(II), 0.38 for Hg(II) and 0.35 for Zn(II) and absolute errors better than 0.14 for Cd(II), 0.31 for Hg(II) and 0.36 for Zn(II). Similar results were obtained when solution mixtures containing all three metal ions were employed in the studies.

These results indicate that ANN can be employed for simultaneous determination of metal ions in water. However, attention must be given to the leaching and to the saturation of the sensing phase, which limit the lifetime and analytical range of the sensor, respectively.     

Enthalpy of formation of liquid Cd+Ga+In+Sn, Cd+Ga+ln+Zn, Ga+ln+Sn+Zn and Cd+Ga+In+Sn+Zn alloys

Using a high temperature Calvet microcalorimeter, the molar enthalpy of formation of liquid quaternary and quinary alloys have been carried out at 730 K along several sections belonging to their barycenter. The well-known models for extrapolation ( Kohler, Muggianu, Toop, Hoch-Arpshofen and Mathieu ) adapted to the n-component systems have been used to predict the enthalpy of formation of the liquid systems : Cd+Ga+ln+Sn, Cd+Ga+ln+Zn, Ga+ln+Sn+Zn and Cd+Ga+In+Sn+Zn. Experimental and calculated results have been compared.     

Detection of photosynthetic activity under cadmium stress by measurement of the red and far-red chlorophyll fluorescence

In this work it is shown that, with a new spectroscopic method based on ultraviolet light emitting diode-induced fluorescence spectroscopy (UV-LED IFS), the photosynthetic activity of an intact attached leaf can be measured in a non-destructive way within a few seconds. The effects of cadmium (Cd) toxicity on the photosynthetic activity of tomato plants (Solanum lycopersicum) were studied using various CdCl₂ (cadmium chloride) concentrations. The Cd treatment decreases the photosynthetic activity, measured via a decline of the variable chlorophyll (chl) fluorescence decrease ratio (R _Fd) values, calculated at 690 and 730?nm. The chl fluorescence ratios of intensity (FIR) and band area were also calculated. It was found that the R _Fd(690) and R _Fd(730) values decreased whereas the FIR increased from 1?μM Cd treatment and this behaviour is enhanced with the increasing of Cd concentrations. At 10 and 25?μM Cd, the decrease in R _Fd values was associated with a strong decline in the chlorophyll-a?+?chlorophyll-b (chl-a?+?b). The chl-a?+?b decline could also be followed via an increase of the chl fluorescence ratio F ₆₉₀/F ₇₃₀. Our study demonstrates that the UV-LED IFS is a promising technique for early detection of Cd stress (from 1?μM) in tomato plants, before visual symptoms appear.     

Integrating spectral indices with environmental parameters for estimating heavy metal concentrations in rice using a dynamic fuzzy neural-network model

A generalized dynamic fuzzy neural network (GDFNN) was created to estimate heavy metal concentrations in rice by integrating spectral indices and environmental parameters. Hyperspectral data, environmental parameters, and heavy metal content were collected from field experiments with different levels of heavy metal pollution (Cu and Cd). Input variables used in the GDFNN model were derived from 10 variables acquired by gray relational analysis. The assessment models for Cd and Cu concentration employed five and six input variables, respectively. The results showed that the GDFNN for estimating Cu and Cd concentrations in rice performed well at prediction with a compact network structure using the training, validation, and testing sets (for Cu, fuzzy rules=9, R² greater than 0.75, and RMSE less than 2.5; for Cd, fuzzy rules=9, R² greater than 0.75, and RMSE less than 1.0). The final GDFNN model was then compared with a back-propagation (BP) neural network model, adaptive-network-based fuzzy interference systems (ANFIS), and a regression model. The accuracies of GDFNN model prediction were usually slightly better than those of the other three models. This demonstrates that the GDFNN model is more suitable for predicting heavy metal concentrations in rice.