A Sensitive Spectrophotometric Determination of Nitrite in Water and Soil

A highly sensitive spectrophotometric method for the determination of nitrite in water and soil has been developed. The reaction of nitrite with acidified potassium iodide to liberate iodine which oxidizes leuco‐crystal violet (LCV) to form crystal violet having absorption maxima at 590 nm forms the bases of this method. In aqueous medium the system obeys Beer's law in the range of 0.1 to 1.0 μg per 25 mL (0.004–0.04 ppm), while in an extractive system the range is 0.025–0.25 μg in 100 mL (0.00025–0.0025 ppm). The molar absorptivity and Sandell's sensitivity were found to be 1.54 × 10⁶ 1 mol^?1 cm^?1 and 44 pg cm^?2, respectively.     

Halogenation in Fungi: What Do We Know and What Remains to Be Discovered?

In nature, living organisms produce a wide variety of specialized metabolites to perform many biological functions. Among these specialized metabolites, some carry halogen atoms on their structure, which can modify their chemical characteristics. Research into this type of molecule has focused on how organisms incorporate these atoms into specialized metabolites. Several families of enzymes have been described gathering metalloenzymes, flavoproteins, or S-adenosyl-L-methionine (SAM) enzymes that can incorporate these atoms into different types of chemical structures. However, even though the first halogenation enzyme was discovered in a fungus, this clade is still lagging behind other clades such as bacteria, where many enzymes have been discovered. This review will therefore focus on all halogenation enzymes that have been described in fungi and their associated metabolites by searching for proteins available in databases, but also by using all the available fungal genomes. In the second part of the review, the chemical diversity of halogenated molecules found in fungi will be discussed. This will allow the highlighting of halogenation mechanisms that are still unknown today, therefore, highlighting potentially new unknown halogenation enzymes.     

Purification and Characterization of Gum-Derived Polysaccharides of Moringa oleifera and Azadirachta indica and Their Applications as Plant Stimulants and Bio-Pesticidal Agents

Plant gums are bio-organic substances that are derived from the barks of trees. They are biodegradable and non-adverse complex polysaccharides that have been gaining usage in recent years due to a number of advantages they contribute to various applications. In this study, gum was collected from Moringa oleifera and Azadirachta indica trees, then dried and powdered. Characterizations of gum polysaccharides were performed using TLC, GC-MS, NMR, etc., and sugar molecules such as glucose and xylose were found to be present. Effects of the gums on Abelmoschus esculentus growth were observed through root growth, shoot growth, and biomass content. The exposure of the seeds to the plant gums led to bio stimulation in the growth of the plants. Poor quality soil was exposed to the gum polysaccharide, where the polysaccharide was found to improve soil quality, which was observed through soil analysis and SEM analysis of soil porosity and structure. Furthermore, the plant gums were also found to have bio-pesticidal activity against mealybugs, which showed certain interstitial damage evident through histopathological analysis.     

Symbiotic N2 Fixation and N Uptake of Yellow and White Lupines Influenced by Spontaneous Rhizobia Infection and Substrate

Abstract

By using soil as substrate, white and yellow lupines (Lupinus albus L., Lupinus luteus L.) assimilated higher N amounts than under quartz sand conditions. This was caused by spontaneous infection of lupines with wild Rhizobia strains and also by an additional N uptake from the soil. In yellow lupines without inoculation in non-sterile soil, only the additional N uptake played a role. Differences in P and K supply as the cause of different N acquisition from soil and quartz sand could be excluded. As compared with white lupines, yellow lupines inoculated with Rhizobia had a high N₂ fixation that exceeded the effect of spontaneous infections. This result as well as the positive effect of spontaneous infections with soil-borne Rhizobia on white lupines indicates insufficient effectiveness of the strains used for inoculation on this plant species.     

生境片段化对千岛湖次生马尾松林土壤理化性质的影响

土壤是森林生态系统的重要组成部分,对森林生物多样性和生态功能的维持具有不可替代的作用.据此,本研究以千岛湖地区大陆35个样方和29个不同大小和隔离度的陆桥岛屿次生马尾松林土壤为研究对象,分析了生境片段化对土壤理化性质的影响.研究发现,大陆马尾松林土壤厚度显著高于岛屿,而其土壤最大持水量显著低于岛屿;大陆土壤的全磷（P）显著低于岛屿,而土壤有效磷（AP）和硝态氮（NO₃-N）显著高于岛屿.在片段化的岛屿生境中,土壤C、N、P、NO₃-N、AP随与边缘距离的增大而降低;隔离度和地形对部分土壤理化因子有影响,而岛屿面积对土壤理化性质无影响.土壤理化因子和植物群落多样性存在显著相关性.生境片段化改变了千岛湖地区马尾松林的土壤条件,而边缘效应是影响片段化生境中土壤性质空间分布的主要过程之一.通过分析片段化景观中土壤理化性质的空间分布格局及其影响因素,深化了生境片段化对土壤条件影响的认识,对于片段化森林管理措施的制定具有重要意义.     

酸性红黄壤土上大麦遗传改良研究

本文报道了酸性红黄壤土上大麦遗传改良研究结果:(1)采用酸铝营养液培养幼苗的方法鉴定了我国3871份大麦品种的耐酸铝性，得到一级耐性材料315份，占鉴定总数的8.13劣，(2)相关通径分析表明，酸性红黄壤土上大麦单株籽粒产量损失起主要作用的是有效分菜数下降(P = 0. 7324 )、每穗实粒数减少(P = 0 . 5923 )和千粒重降低(P = 0.5877),由此可见，这是在红黄壤土田间条件下选择耐酸铝性大麦的三个主要选择指标;(3)发现大麦耐酸铝性基因遗传方式除单基因遗传方式外，尚有多基因控制的表现数量性状遗传方式;'(4)从对酸铝性表现敏感的大麦品种“早熟3一号”的花药、幼胚等外植体诱导出的愈伤组织，通过离体细胞突变体筛选，得到了“耐性细胞系”.以上结果表明，通过耐酸铝性遗传改良培育出适应酸性红黄壤土种植的大麦新品种是可行的，亦为开发利用红黄壤土地资源补充了另一条有效途径.     

Reference spectra of important adsorbed organic and inorganic phosphate binding forms for soil P speciation using synchrotron‐based K‐edge XANES spectroscopy

Direct speciation of soil phosphorus (P) by linear combination fitting (LCF) of P K‐edge XANES spectra requires a standard set of spectra representing all major P species supposed to be present in the investigated soil. Here, available spectra of free‐ and cation‐bound inositol hexakisphosphate (IHP), representing organic P, and of Fe, Al and Ca phosphate minerals are supplemented with spectra of adsorbed P binding forms. First, various soil constituents assumed to be potentially relevant for P sorption were compared with respect to their retention efficiency for orthophosphate and IHP at P levels typical for soils. Then, P K‐edge XANES spectra for orthophosphate and IHP retained by the most relevant constituents were acquired. The spectra were compared with each other as well as with spectra of Ca, Al or Fe orthophosphate and IHP precipitates. Orthophosphate and IHP were retained particularly efficiently by ferrihydrite, boehmite, Al‐saturated montmorillonite and Al‐saturated soil organic matter (SOM), but far less efficiently by hematite, Ca‐saturated montmorillonite and Ca‐saturated SOM. P retention by dolomite was negligible. Calcite retained a large portion of the applied IHP, but no orthophosphate. The respective P K‐edge XANES spectra of orthophosphate and IHP adsorbed to ferrihydrite, boehmite, Al‐saturated montmorillonite and Al‐saturated SOM differ from each other. They also are different from the spectra of amorphous FePO₄, amorphous or crystalline AlPO₄, Ca phosphates and free IHP. Inclusion of reference spectra of orthophosphate as well as IHP adsorbed to P‐retaining soil minerals in addition to spectra of free or cation‐bound IHP, AlPO₄, FePO₄ and Ca phosphate minerals in linear combination fitting exercises results in improved fit quality and a more realistic soil P speciation. A standard set of P K‐edge XANES spectra of the most relevant adsorbed P binding forms in soils is presented.     

Using Short Wave Visible–Near Infrared Reflectance Spectroscopy to Predict Soil Properties and Content

In this study, short wave visible–near infrared reflectance spectroscopy was evaluated for prediction of diverse soil properties related to four different soil series of several regions in Jiangxi, China. A total of 240 soil samples were collected for the calibration (n = 168) and prediction (n = 72) sets. The used wavelength range of short wave visible–near infrared reflectance spectroscopy is 325–1075 nm. Partial least squares regression and back propagation neural network were used to develop models for soil properties such as organic matter and extractable forms of calcium, magnesium, and potassium. Performance of these models was also compared and analyzed. The input of back propagation neural network was the first six principal components resulted from the principal component analysis and the optimal number of latent variables obtained from partial least squares regression. The overall results showed that the performance of partial least squares regression model was inferior to all back propagation neural network models. The best prediction was obtained with latent variables as input of back propagation neural network model for organic matter (determination coefficient = 0.84 and relative predictive determinant = 2.38), which was classified as very good model predictions. The prediction of calcium, magnesium, and potassium was classified as fair (determination coefficient = 0.56–0.68 and relative predictive determinant = 1.51–1.61), where quantitative predictions were considered possible. It is recommended to adopt latent variables as input for back propagation neural network model predicting soil properties with short wave visible–near infrared reflectance spectroscopy. In conclusion, short wave visible–near infrared reflectance spectroscopy was variably successful in estimating soil properties and showed potential for substituting laboratory analyses.     

Identification and spectra–structure determination of soil minerals: Raman study supported by IR spectroscopy and X‐ray powder diffraction

Raman and IR spectroscopy were used for the characterization of several minerals in morphologically similar vertisol sequences from Kiževak (Serbia). It helped us to establish the surface layer transition going from calcic vertisols (containing gypsum and calcite) to calcimagnesic vertisols (containing aragonite, magnesium‐calcite and dolomite) derived from peridotite and serpentinite. The observed band positions are found to be solely characteristic for each carbonate mineral and are used to discuss the main structural features of carbonates and sulfates present in the studied soil. It was found that the dolomite, calcite and aragonite concretions are present in the deepest layer of the soil, whereas the gypsum is found in the topsoil. The identification was confirmed of the carbonates having calcite and aragonite structure, and the representative from the sulfate group (gypsum) was confirmed by X‐ray powder diffraction. Copyright © 2009 John Wiley & Sons, Ltd.     

氢化物发生—原子荧光法测定不同产地绞股蓝及其根际土壤中As,Hg,Se

通过优化了的氢化物发生—原子荧光法测定了7个省产绞股蓝及其根际土壤中As,Hg,Se三种元素的含量,研究结果表明:7个省产绞股蓝中As,Hg,Se的含量存在较大差异,但As和Hg两种重金属元素含量均低于《药用植物及制剂进出口绿色行业标准》中As和Hg的限量标准。Se元素含量同根际土壤中Se元素含量显示极显著相关性,故湖北恩施富硒区产绞股蓝中Se含量明显高于其他6省产绞股蓝。研究结果可以初步判定,绞股蓝中Se元素主要来源于土壤,而As和Hg元素的积累则不同于Se元素,还可能受到大气气溶胶的干、湿沉降等因素的影响。