Responses of microbial biomass and respiration of soil to topography,burning, and nitrogen fertilization in a temperate steppe

Temporal dynamics of microbial biomass and respiration of soil and their responses to topography, burning, N fertilization, and their interactions were determined in a temperate steppe in northern China. Soil microbial indices showed strong temporal variability over the growing season. Soil microbial biomass C (MBC) and N (MBN) were 14.8 and 11.5% greater in the lower than upper slope, respectively. However, the percentage of organic C present as MBC and the percentage of total N present as MBN were 16.9 and 26.2% higher in the upper than lower slope, respectively. Neither microbial respiration (MR) nor metabolic quotient (qCO₂) was affected by topography. Both MBC and MBN were increased by burning, on average, by 29.8 and 14.2% over the growing season, and MR and qCO₂ tended to reduce depending on the sampling date, especially in August. Burning stimulated the percentage of organic C present as MBC and the percentage of total N present as MBN in the upper slope, but did not change these two parameters in the lower slope. No effects of N fertilization on soil microbial indices were observed in the first growing season after the treatment. Further research is needed to study the long-term relationships between changes in soil microbial diversity and activity and plant community in response to burning and N fertilization.     

Handling missingness when modeling the force of infection from clustered seroprevalence data

Modeling infectious diseases data is a relatively young research area in which clustering and stratification are key features. It is not unlikely for these data to have missing values. If values are missing completely at random, the analysis on the complete cases is valid. However, in practice this assumption is usually not fulfilled. This article shows the effect of ignoring missing data in modeling the force of infection of the bovine herpesvirus-1 in Belgian cattle and proposes the use of weighted generalized estimating equations with constrained fractional polynomials as a flexible modeling tool.     

Free amino acid composition of quince (Cydonia oblonga Miller) fruit (pulp and peel) and jam

Twenty-one free amino acids present in several samples of quince fruit (pulp and peel) and quince jam (homemade and industrially manufactured) were analyzed by GC/FID. The analyses showed some differences between quince pulps and peels. Generally, the highest content in total free amino acids and in glycine was found in peels. As a general rule, the three major free amino acids detected in pulps were aspartic acid, asparagine, and hydroxyproline. For quince peels, usually, the three most abundant amino acids were glycine, aspartic acid, and asparagine. Similarly, for quince jams the most important free amino acids were aspartic acid, asparagine, and glycine or hydroxyproline. This study suggests that the free amino acid analysis can be useful for the evaluation of quince jam authenticity. It seems that glycine percentage can be used for the detection of quince peel addition while high alanine content can be related to pear addition.     

Incorporating parameter uncertainty into prediction intervals for spatial data modeled via a parametric variogram

In spatial predictions, researchers usually treat the estimated theoretical variogram parameters as known without error and ignore the variability of the parameter estimators. Although the prediction is still unbiased, the prediction error is usually underestimated. Therefore, the coverage probability of the prediction interval usually is lower than the nominal probability. A simulation study is performed to show how the coverage probability for prediction relates to the true range and sill of an exponential variogram. This article proposes two parametric bootstrap methods to incorporate the variability of the corresponding parameter estimators. A simulation study is performed to evaluate the coverage probability of these proposed methods. Finally, we apply the parametric bootstrap methods to a real dataset and compare the results with those from naive (i.e., treating estimated parameters as known) and Bayesian methods.     

Nitrogen fixation in biological soil crusts from southeast Utah,USA

Biological soil crusts can be the dominant source of N for arid land ecosystems. We measured potential N fixation rates biweekly for 2 years, using three types of soil crusts: (1) crusts whose directly counted cells were >98% Microcoleus vaginatus (light crusts); (2) crusts dominated by M. vaginatus, but with 20% or more of the directly counted cells represented by Nostoc commune and Scytonema myochrous (dark crusts); and (3) the soil lichen Collema sp. At all observation times, Collema had higher nitrogenase activity (NA) than dark crusts, which had higher NA than light crusts, indicating that species composition is critical when estimating N inputs. In addition, all three types of crusts generally responded in a similar fashion to climate conditions. Without precipitation within a week of collection, no NA was recorded, regardless of other conditions being favorable. Low (<1°C) and high (>26°C) temperatures precluded NA, even if soils were moist. If rain or snow melt had occurred 3 or less days before collection, NA levels were highly correlated with daily average temperatures of the previous 3 days (r²=0.93 for Collema crusts; r²=0.86 for dark crusts and r²=0.83 for light crusts) for temperatures between 1°C and 26°C. If a precipitation event followed a long dry period, NA levels were lower than if collection followed a time when soils were wet for extended periods (e.g., winter). Using a combination of data from a recording weather datalogger, time-domain reflectometry, manual dry-down curves, and N fixation rates at different temperatures, annual N input from the different crust types was estimated. Annual N input from dark crusts found at relatively undisturbed sites was estimated at 9 kg ha^-1 year^-1. With 20% cover of the N-fixing soil lichen Collema, inputs are estimated at 13 kg ha^-1 year^-1. N input from light crusts, generally indicating soil surface disturbance, was estimated at 1.4 kg ha^-1 year^-1. The rates in light crusts are expected to be highly variable, as disturbance history will determine cyanobacterial biomass and therefore N fixation rates.     

Comprehensive study on the chemical structure of dioxane lignin from plantation Eucalyptus globulus wood

Results of a comprehensive study on the chemical structure of lignin from plantation Eucalyptus globulus Labill are presented. Lignin has been isolated by a modified mild acidolysis method and thoroughly characterized by functional group analysis, by a series of degradation techniques (nitrobenzene oxidation, permanganate oxidation, thioacidolysis, and Py-GC-MS), and (1)H and (13)C NMR spectroscopy. Plantation Eucalyptus globulus lignin was found to be of the S/G type with an extremely high proportion of syringyl (S) units (82-86%) and a minor proportion of p-hydrophenyl propane (H) units (roughly 2-3 mol %). Unknown C-6 substituted and 4-O-5' type syringyl substructures represent about 65% of lignin "condensed" structures. Eucalypt lignin showed high abundance of beta-O-4 (0.56/C(6)) structures and units linked by alpha-O-4 bonds (0.23/C(6)). The proportion of phenylcoumaran structures was relatively low (0.03/C(6)). Different kinds of beta-beta substructures (pino-/syringaresinol and isotaxiresinol types) in a total amount of 0.13/C(6) were detected. ESI-MS analysis revealed a wide molecular weight distribution of lignin with the center of gravity of mass distribution around 2500 u.     

QTL mapping of sheath blight resistance in a deep-water rice cultivar

Sheath blight, caused by the pathogen Rhizoctonia solani Kühn, is one of the most serious diseases of rice and leads to severe yield loss worldwide. A recombinant inbred line (RIL) population consisting of 121 lines was constructed from a cross between HH1B and RSB03, the latter of which is a deep-water rice variety. Five traits were used to evaluate sheath blight resistance, namely disease rating (DR), lesion length (LL), lesion height (LH), relative lesion length [RLL, the ratio of LL to plant height (PH)], and relative LH (RLH, the ratio of LH to PH). Using the RIL population and 123 molecular markers, we identified 28 quantitative trait loci (QTLs) for the five traits in two environments. These QTLs are located on nine chromosomes and most of them are environment specific. A major QTL for DR (qSBR1) on chromosome 1 was identified with contributions of 12.7% at Shanghai and 42.6% at Hainan, and it collocated with a QTL for PH. The allele at this locus from RSB03 enhances sheath blight resistance and increases PH. Another QTL for DR on chromosome 7 was adjacent to QTLs for heading date (HD) and four other disease traits. RSB03 also carries the resistant allele at this locus and shortens HD. The susceptible parent, HH1B, provides the resistance allele at the locus qSBR8, where QTLs for four other disease traits were identified. QTL mapping results showed that most QTLs for LL, LH, RLL, and RLH are collocated with QTLs for DR. Three QTLs for DR are independent from HD, PH, and four other disease traits, while four QTLs are closely related to HD and PH. Four QTLs for LL, LH, RLL, and RLH are independent from DR, HD, and PH, while there is only one region harboring QTLs for these four traits and HD. Correlation analysis and QTL mapping results indicated that LL, LH, RLL, and RLH might be important indices, like DR, for evaluating the level of resistance to rice sheath blight.     

Allele mining and haplotype discovery in barley candidate genes for drought tolerance

In the present study, allele mining was conducted on a panel of drought related candidate genes in a set of 96 barley genotypes using EcoTILLING, which is a variant of the targeting induced local lesions in genomes (TILLING) technology. Analyzing approximately 1.5 million basepairs in barley a total number of 94 verified unique haplotypes were identified in 18 amplicons designed for 9 genes. Overall, 185 single nucleotide polymorphisms (SNPs) and 46 insertions/deletions (INDELs) were detected with a mean of 1SNP/92 bp and 1INDEL/372 bp genomic sequence. Based on overlapping haplotype sequences, markers were developed for four candidate genes (HvARH1, HvSRG6, HvDRF1, HVA1), which allows distinguishing between the main haplotypes showing either differences in amino acid sequence or which have larger INDELs in the promoter region. As “proof of concept”, the HvARH1 and HvSRG6 haplotypes were tested for the level of abscisic acid-induced gene expression in subsets of genotypes belonging to different haplotype categories. An integrated database was developed to contain information about the genes, genotypes, and haplotypes analyzed in this study. The database supplies profound information about the natural variation in the tested drought related candidate genes providing a significant asset for further mapping studies dealing with this highly polygenic trait.     

Impact of epistasis and QTL × environmental interaction on the oil filling rate of soybean seed at different developmental stages

The oil accumulation in the developing soybean seed has been shown to be a dynamic process with different rates and activities at different phases affected by both genotype and environment. The objective of the present study was to investigate additive, epistatic and quantitative trait loci (QTL) × environment interaction (QE) effects of the QTL controlling oil filling rate in soybean seed. A total of 143 recombinant inbred lines (RILs) derived from the cross of Charleston and Dongnong 594 were used in this study to obtain 2 years of field data (2004 and 2005). A total of 26 QTL with significantly unconditional and conditional additive (a) effect and/or additive × environment interaction (ae) effect at different filling stages were identified on 14 linkage groups. Among the QTL with significant a effects, 18 QTL showed positive effects and 6 QTL had negative effects on seed filling rate of oil content during seed development. A total of 29 epistatic pairwise QTL underlying seed filling rate were identified at different filling stages. About 28 pairs of the QTL showed additive × additive epistatic (aa) effects and 14 pairs of the QTL showed aa × environment interaction (aae) effects at different filling stages. QTL with aa and aae (additive × additive × environment) effects appeared to vary at different filling stages. Our results demonstrated that oil filling rate in soybean seed were under genetic, developmental and environmental control.