The microbial diversity and structure in peatland forest in Indonesia

The microbial community structure and function under forest in tropical peatlands are poorly understood. In this study, we investigated the microbial community structure and diversity in natural peat swamp forest soil, disturbed peat soil and mineral soil in Central Kalimantan, Indonesia, using 454 pyrosequencing. The results showed that the natural peat soil had the greatest fungal species richness (Chao1), which was significantly (p < .05) larger than that in the other two soils. Community structure of both fungi and bacteria in natural peat soil differed significantly from that in the disturbed peat soil (p = .039 and p = .045, respectively). Ascomycota (40.5%) was the most abundant phylum across the three soils followed by Basidiomycota (18.8%), Zygomycota (<0.1%) and Glomeromycota (<0.1%). The linear discriminant analysis with effect size (LEfSe) showed that Ascomycota (p < .05) and genus Gliocephalotrichum (p < .05) dominated in natural peat soil. Functionally, pathotrophs were more abundant in disturbed peat soil (p < .05). Proteobacteria (43.8%) were the most abundant phylum followed by Acidobacteria (32.6%), Actinobacteria (9.8%), Planctomycetes (1.7%). Methylocystis, Telmatospirillum, Syntrophobacter, Sorangium and Opitutus were the more abundant genera in disturbed peat soil, whereas Nevskia and Schlesneria were more abundant in mineral soil and natural peat soil, respectively. The natural peat forest soil supported a more diverse microbiology; however, the land use of such a soil can change its microbial community structure. The results provide evidence that the disturbance of tropical peat land could lead to the introduction and spread of a large number of fungal diseases     

基于数字化植物表型平台（D3P）的田间小麦冠层光截获算法开发

冠层光截获能力是反映作物品种间差异的重要功能性状，高通量表型冠层光截获对提高作物改良效率具有重要意义。本研究以小麦为研究目标，利用数字化植物表型平台（D3P）模拟生成了100种冠层结构不同的小麦品种在5个生育期的三维冠层场景，记录了从原始冠层结构中提取的绿色叶面积指数（GAI）、平均倾角（AIA）和散射光截获率（FIPAR_dif）信息作为真实值,进一步利用上述三维小麦场景开展了虚拟的激光雷达（LiDAR）模拟实验，生成了对应的三维点云数据。基于模拟的点云数据提取了其高度分位数特征（H）和绿色分数特征（GF）。最后，利用人工神经网络（ANN）算法分别构建了从不同LiDAR点云特征（H、GF和H+GF）输入到FIPAR_dif、GAI和AIA的反演模型。结果表明，对于GAI、AIA和FIPAR_dif，预测精度从高到低对应的点云特征输入为GF+H > H > GF。由此可见，H特征对提高目标表型特性的估算精度起到了重要作用。输入GF + H特征，在中等测量噪音（10%）情况下，FIPAR_dif和GAI的估算均获得了满意精度，R²分别为0.95和0.98，而AIA的估算精度（R²=0.20）还有待进一步提升。本研究基于D3P模拟数据开展，算法的实际表现还有待通过田间数据进一步验证。尽管如此，本研究验证了D3P协助表型算法开发的能力，展示了高通量LiDAR数据在估算田间冠层光截获和冠层结构方面的较高潜力。     

Applying a kinetic method to an indirect ELISA measuring Ostertagia ostertagi antibodies in milk

Indirect enzyme-linked immunosorbent assays (ELISAs) are frequently run as endpoint ELISAs (e-ELISAs). However, kinetic ELISAs (k-ELISAs) have certain advantages over e-ELISAs. The objective of this study was to understand the relationship between e-ELISA and k-ELISA results. Specifically, to determine whether it was possible to run both k-ELISA and e-ELISA on the same plate and establish an appropriate time interval for k-ELISA measurements. A normalization method for k-ELISA slopes (slope ratio) is proposed. Using an indirect e-ELISA test measuring antibodies against Ostertagia ostertagi in milk from dairy cattle, we found that running a k-ELISA had no effect on optical density ratio results of an e-ELISA on the same plate, and that agreement was very strong at 10, 15, and 28 min, allowing for a reduction in the total processing time for ELISA tests.     

Pflanzliche Insektizide IV*. Die insektizide Wirkung des ätherischen Öls aus dem Balsamkraut,Chrysanthemum balsamita L

The essential oil ofChrysanthemum balsamita L. revealed insecticidal properties when tested againstM. dirhodum aphids. The insecticidal activity was attributed to the presence of pyrethrine I in the oil. By an appropriate testing procedure, the dependence of the activity upon the time of harvesting of the plants was determined. Furthermore, the insecticidal effect of the oil was compared with that of a commercially available pyrethrum preparation.     

Analysis of cyclic vacuum drying curve

The objective of this research was to analyze the cyclic vacuum drying curve within one cycle. Red oak specimens of two different groups, square in cross-section, were used. Group one was comprised of four different thicknesses (2.54, 3.81, 5.08, and 6.35 cm) with a length of 25.4 cm and group two was comprised of three different lengths (12.7, 25.4, and 38.1 cm) with the thickness of 2.54 cm. The specimens were heated to 60°C in the heating oven and then dried in the vacuum oven at 18 mm Hg. The vacuum oven was at room temperature (20°C). The vacuum pump was kept running for 140 min. It was found that the cyclic vacuum drying curve consisted of two distinct parts. The fast drying period lasted about 10 to 15 min. The slow drying period occurred when the pressure inside wood approached the ambient pressure. Most of the moisture was removed during the fast drying period.     

Fusarium wilt of chickpea: physiological specialization, genetics of resistance and resistance gene tagging

Chickpea wilt caused by Fusarium oxysporum f. sp. ciceris is one of the major yield limiting factors in chickpea. The disease causes 10–90% yield losses annually in chickpea. Eight physiological races of the pathogen (0, 1A, 1B/C, 2, 3, 4, 5 and 6) are reported so far whereas additional races are suspected from India. The distribution pattern of these races in different parts of the world indicates regional specificity for their occurrence leading to the perception that F. oxysporum f. sp. ciceris evolved independently in different regions. Pathogen isolates also exhibit differences in disease symptoms. Races 0 and 1B/C cause yellowing syndrome whereas 1A, 2, 3, 4, 5 and 6 lead to wilting syndrome. Genetics of resistance to two races (1B/C and 6) is yet to be determined, however, for other races resistance is governed either by monogenes or oligogenes. The individual genes of oligogenic resistance mechanism delay onset of disease symptoms, a phenomenon called as late wilting. Slow wilting, i.e., slow development of disease after onset of disease symptoms also occurs in reaction to pathogen; however, its genetics are not known. Mapping of wilt resistance genes in chickpea is difficult because of minimal polymorphism; however, it has been facilitated to great extent by the development of sequence tagged microsatellite site (STMS) markers that have revealed significant interspecific and intraspecific polymorphism. Markers linked to six genes governing resistance to six races (0, 1A, 2, 3, 4 and 5) of the pathogen have been identified and their position on chickpea linkage maps elucidated. These genes lie in two separate clusters on two different chickpea linkage groups. While the gene for resistance to race 0 is situated on LG 5 of Winter et al. (Theoretical and Applied Genetics 101:1155–1163, 2000) those governing resistance to races 1A, 2, 3, 4 and 5 spanned a region of 8.2 cM on LG 2. The cluster of five resistance genes was further subdivided into two sub clusters of 2.8 cM and 2.0 cM, respectively. Map-based cloning can be used to isolate the six genes mapped so far; however, the region containing these genes needs additional markers to facilitate their isolation. Cloning of wilt resistance genes is desirable to study their evolution, mechanisms of resistance and their exploitation in wilt resistance breeding and wilt management.     

Potential transformations of chromium in natural waters

A study has been conducted on the transformation of Cr(III) and Cr(VI) in simulated natural water conditions. It has been found that these forms are readily interconvertible under natural water conditions. The results of this study indicate that Cr(VI) is reduced by Fe(II), dissolved sulfides, and certain organic compounds with sulfhydryl groups, while Cr(III) is oxidized by a large excess of MnO₂ and at a slow rate by Oz under conditions approximating those in natural waters. Based on the results of these studies, water quality standards for Cr should be based on total Cr rather than on Cr(VI), as has been frequently done in the past.     

Consequences of the spatial configuration of resources for the distribution and dynamics of the endangered Parnassius apollo butterfly

Based on several years of data from two populations of the endangered Apollo butterfly (Parnassius apollo, L. 1758), we study how the amount and spatial location of patches of larval (host-plant) and adult (nectar plant) resources affects the distribution of females and their larval offspring in the following year. In the coastal population (nectar-plant and host-plant patches spatially segregated), females moved frequently between patches to aggregate on larger host-plant patches close to nectar-plant patches. In the archipelago population (where nectar-plants and host-plants co-occur), the abundance of females increased with higher proximity to other host-plant patches and with more nectar-plants on the patch. Next year’s larval abundance correlated with the abundance of females in the previous season in both populations. A model of the population dynamics in the two populations in relation to the spatial configuration of nectar and host-plant patches showed that the spatial configuration of larval and adult resources had population-dynamical consequences. In many organisms, different life-history stages use different resources. Incorporation of information on the location and abundance of adult resources can provide additional insight for the suitability of a particular landscape in harbouring a population.     

Involvement of dehydroalanine and dehydrobutyrine in the addition of glutathione to nisin

Nisin variants and fragments were reacted with glutathione, and the products of the reactions were analyzed by matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS) and liquid chromatography/mass spectrometry (LC-MS). Reactions between glutathione and either [Ala5]nisin or [Ala33]nisin resulted in products with two glutathione molecules conjugated to one nisin variant molecule. Only one glutathione molecule was added to [Ala5,Ala33]nisin. Fragmentation of the nisin molecule resulted in nisin 1-12, nisin 1-20, and nisin 1-32 fragments. Each fragment retained two dehydro residues, which subsequently underwent reaction with glutathione. The data indicated that the dehydroalanine residues of nisin are sites of addition for glutathione. Such addition renders the nisin molecule inactive.