水稻籽粒不同部位P与Al、Cd、Pb含量的关系

利用环境扫描电镜结合X射线电子探针显微分析技术,研究了水稻籽粒不同部位P与Al、Cd、Pb含量的关系.结果表明:金属元素Al、Cd、Pb和其他矿质元素一样,也在糊粉层中积累最多;水稻籽粒中P的积累与Al、Cd、Pb的富集有密切关系;其中,籽粒不同部位P与Al的含量存在极显著的正相关关系,而Pb和Cd的含量并不随着P含量的增加而增加,其变化幅度较小.说明P对Al的富集具有促进作用.     

提高小麦幼胚组织培养效果的初步研究

研究结果表明，幼胚接种前低温(-4℃)处理2d可显著提高分化频率。幼胚组培的最佳培养基是MS培养基。不同材料的幼胚外植体对软X射线有不同的辐射敏感性，较适宜的照射剂量为1kRad。     

不同氧化度六方水钠锰矿的结构研究

通过反复试验法(trial-and-error)粉末X射线衍射(XRD)结构模拟和X射线吸收光谱(XAS)研究了不同锰平均氧化度(manganese average oxidation state,Mn AOS)六方水钠锰矿的结构变化特点.合成的系列六方水钠锰矿中(样品HB1到HB6),Mn AOS由3.92减小为3.67,晶胞参数b由2.838 (A)增加至2.848 (A).在a-b平面上的紧密堆叠尺寸(CSD)由12.0 nm减小至7.0 nm,沿c轴堆叠的锰氧八面体层数约为10.6～13.4层.随着Mn AOS逐渐降低,样品中八面体空位含量由18％减小至8％.Mn AOS与空位含量呈极显著正相关,它们与晶胞参数b呈负相关.X射线吸收近边结构光谱(XANES)线性拟合表明,样品中Mn主要以+4价存在,随着空位含量的减少,低价锰(Mn2+/3+)含量逐渐增多.扩展X射线吸收精细结构光谱(EXAFS)全多重散射模型拟合分析表明,不同氧化度六方水钠锰矿样品的晶体结构和Mn局域配位环境基本相同.由于空位含量和颗粒尺寸减小,从HB1到HB6的表观锰位点占有率(focc)由0.74减小至0.66.随着Mn AOS逐渐降低,Mn-Mn(O)配位壳平均键长增加.     

MINERAL ELEMENT DISTRIBUTION AND ACCUMULATION PATTERNS WITHIN TWO BARLEY CULTIVARS

Growth stage effects on distribution of mineral nutrients or beneficial elements phosphorus (P), potassium (K), calcium (Ca), magnesium (Mg), sulfur (S), chloride (Cl), iron (Fe), zinc (Zn), manganese (Mn), copper (Cu), molybdenum (Mo), sodium (Na), silicon (Si) and nickel (Ni), and the elements bromine (Br), rubidium (Rb), strontium (Sr), barium (Ba), lanthanum (La), cerium (Ce), and uranium (U) in two barley (Hordeum vulgare L.) cultivars and how the distribution of these elements changed were determined during the 2006–2007 growing season in a field experiment. Barley plants were sampled from the field at shooting, heading, soft dough, hard dough and harvest stages, and mineral nutrients and other elements concentrations of spike, flag leaf, old leaf, and stem samples were determined by polarized energy dispersive X-ray fluorescence (PEDXRF). Distribution patterns varied considerably from element to element. At the end of the season much of the Ca, Mg, S, Si, Fe, Mn, Cu, Ni, Sr, Ba, La, Ce, and U were located in the spikes. However, much of the P, K, Zn, Cl, Na, Br, and Rb remained in the old leaves or stem.     

ELEMENTAL COMPOSITION OF PEPPER PLANTS FERTILIZED WITH PELLETIZED POULTRY MANURE

Poultry manure (PM) has been traditionally applied to crops for decades as an organic fertilizer, because it is a good and balanced source of plant nutrients. Its effect on plant growth and yield has been widely investigated and is well known. However, there has been little effort to relate elemental compositions of the manure applied to their concentrations in the plants. The objective of this study was to examine the effects of PM on the growth, and essential and non-essential element composition of pepper (Capsicum annuum) leaves and also fruits. Pepper plants were grown in soil with 0, 10, 20, and 40 g kg^?1 PM under greenhouse conditions. Concentrations of nitrogen (N), phosphorus (P), potassium (K), calcium (Ca), magnesium (Mg), sulfur (S), silicon (Si), aluminum (Al), iron (Fe), zinc (Zn), copper (Cu), manganese (Mn), molybdenum (Mo), chloride (Cl), nickel (Ni), bromine (Br), rubidium (Rb), strontium (Sr), barium (Ba), lanthanum (La), and cerium (Ce) in leaves at the flowering stage and in fruits were determined by polarized energy dispersive X-ray fluorescence (PEDXRF). Poultry manure fertilization significantly improved pepper shoot growth and also fruit yield, and increased leaf and fruit P concentrations but not N, K, Mg, Si, Al, Ni, and Fe. Leaf Ca was significantly reduced by increased rate of PM application. Applied PM increased the concentrations of leaf and fruit Zn and Cl. Poultry manure applications had a positive effect on the concentrations of leaf Cu, and fruit Mn. The concentrations of Rb and Ce in fruits and Br in fruit and leaves were increased by PM treatments. Applied PM levels had no clear effect on the concentrations of Ba and La in pepper leaves. The leaf Ba was the highest with 10 g kg^?1 PM, and leaf La was higher in 20 and 40 g kg^?1 PM treatments than in the control.     

Proximal sensor-enhanced soil mapping in complex soil-landscape areas of Brazil

Portable X-ray fluorescence (pXRF) spectrometry and magnetic susceptibility (MS) via magnetometer have been increasingly used with terrain variables for digital soil mapping. However, this methodology is still emerging in many countries with tropical soils. The objective of this study was to use proximal soil sensor data associated with terrain variables at varying spatial resolutions to predict soil classes using the Random Forest (RF) algorithm. The study was conducted on a 316-ha area featuring highly variable soil classes and complex soil-landscape relationships in Minas Gerais State, Brazil. The overall accuracy and Kappa index were evaluated using soils that were classified at 118 sites, with 90 being used for modeling and 28 for validation. Digital elevation models (DEMs) were created at 5-, 10-, 20-, and 30-m resolutions using contour lines from two sources. The resulting DEMs were processed to generate 12 terrain variables. Total Fe, Ti, and SiO₂ contents were obtained using pXRF, with MS determined via a magnetometer. Soil class prediction was performed using the RF algorithm. The quality of the soil maps improved when using only the five most important covariates and combining proximal sensor data with terrain variables at different spatial resolutions. The finest spatial resolution did not always provide the most accurate maps. The high soil complexity in the area prevented highly accurate predictions. The most important variables influencing the soil mapping were MS, Fe, and Ti. Proximal sensor data associated with terrain information were successfully used to map Brazilian soils at variable spatial resolutions.