Journal of Pest Science - Flower strips can play an important role in agro-ecosystems by supporting populations of pests’ natural enemies, thereby enhancing biological control. However, few... 相似文献
In this study, 1-year decomposition experiments were conducted to measure the litter carbon decomposition dynamics in saltmarsh and to determine the changes in the chemical structure of litter carbon during the litter decomposition process.
Methods
Litterbags containing a mixture of Spartina alterniflora litter and burned sediment were buried at four S. alterniflora saltmarshes and one S. alterniflora–Suaeda salsa co-existing saltmarsh. The contents of total organic carbon (TOC) and recalcitrant carbon (RC) were determined by a Sercon Integra CN isotope ratio mass spectrometer, while the content of labile carbon (LC) was estimated by calculation. 13C nuclear magnetic resonance (NMR) spectroscopy was conducted to characterise the chemical structures of the organic carbon compounds in the S. alterniflora litter during decomposition. Solid-state 13C–CPMAS-NMR spectra were obtained using an AVANCE III 400 MHz (Bruker) spectrometer.
Results
The results indicated that more RC than LC remained in the litterbag during decomposition. The organic carbon content of the S. alterniflora litter was largely composed of alcoxyl-C compounds (78.9%), the decomposition products of which dominated the litter organic carbon fractions, including the TOC, RC, and LC. In contrast, alkyl-C, aromatic-C, and carboxyl-C products contributed mostly to RC. Differences in the negative correlations between the litter carbon fractions and alkyl-C, aromatic-C, and carboxyl-C were found among the developing saltmarshes. Humus generated by the S. alterniflora litter was mainly composed of macromolecular organic compounds containing functional groups such as methyl, methylene, methine, methoxyl, aromatic rings, phenolic hydroxyl, and carboxyl.
Conclusions
During decomposition, the organic carbon in the S. alterniflora litter was found to be dominated by O-alkyl-C, followed by aromatic-C, alkyl-C, and carboxyl-C. O-alkyl-C plays a major role in the LC proportion of organic carbon, while aromatic-C, alkyl-C, and carboxyl-C contribute more to the RC proportion. Alkyl-C was found to be more easily decomposed than aromatic-C in the S. alterniflora litter. During litter decomposition, the molecular structure complexity, humification degree, and decomposition degree of organic carbon exhibited seasonal variations. In the 3-year saltmarsh, more decomposition of the organic carbon in the S. alterniflora litter was observed as compared to other sites.
With changes in food preferences and life styles,more and more attentions have been focused on healthier food.Nowadays,resistant starch(RS)which can resist digestion in the human intestine has been recognized and accepted.High RS diet shows great benefit for the human health,and breeding high RS rice variety is a great target for realizing dietary intervention.To provide guidance for RS improvement in rice,this review summarized the unique physiochemical properties of RS and the possible approaches,i.e.genetic regulation,for enhancing RS content in rice,and proposed the potential ways to obtain rice variety with high RS content. 相似文献
Despite the broad variety of available microRNA (miRNA) research tools and methods, their application to the identification, annotation, and target prediction of miRNAs in nonmodel organisms is still limited. In this study, we collected nearly all public sRNA-seq data to improve the annotation for known miRNAs and identify novel miRNAs that have not been annotated in pigs (Sus scrofa). We newly annotated 210 mature sequences in known miRNAs and found that 43 of the known miRNA precursors were problematic due to redundant/missing annotations or incorrect sequences. We also predicted 811 novel miRNAs with high confidence, which was twice the current number of known miRNAs for pigs in miRBase. In addition, we proposed a correlation-based strategy to predict target genes for miRNAs by using a large amount of sRNA-seq and RNA-seq data. We found that the correlation-based strategy provided additional evidence of expression compared with traditional target prediction methods. The correlation-based strategy also identified the regulatory pairs that were controlled by nonbinding sites with a particular pattern, which provided abundant complementarity for studying the mechanism of miRNAs that regulate gene expression. In summary, our study improved the annotation of known miRNAs, identified a large number of novel miRNAs, and predicted target genes for all pig miRNAs by using massive public data. This large data-based strategy is also applicable for other nonmodel organisms with incomplete annotation information. 相似文献