Cereal Simulation
Ontology highlight
ABSTRACT:
PROVIDER: PRJEB53392 | ENA |
REPOSITORIES: ENA
Similar Datasets
Project description:Benefit of introgression depends on level of genetic trait variation in cereal breeding programs
| PRJEB53391 | ENA
Project description:Chinese traditional cereal vinegar Raw sequence reads
| PRJNA648475 | ENA
Project description:16S metabarcoding of the seed microbiome associated to eight cereal species
| PRJEB36663 | ENA
Project description:The domestication and transmission of cereals is one of the most fundamental components of early farming, but direct evidence of their use in early culinary practices and economies has remained frustratingly elusive. Using analysis of a well-preserved Early Bronze Age wooden container from Switzerland, we propose novel criterial for the identification of cereal residues. Using gas chromatography mass spectrometry (GC-MS), we identified compounds typically associated with plant products, including a series of phenolic lipids (alkylresorcinols) found only at appreciable concentration in wheat and rye bran. The value of these lipids as cereal grain biomarkers were independently corroborated by the presence of macrobotanical remains embedded in the deposit, and wheat and rye endosperm peptides extracted from residue. These findings demonstrate the utility of a lipid-based biomarker for wheat and rye bran and offer a methodological template for future investigations of wider range of archaeological contexts. Alkylresorcinols provide a new tool for residue analysis which can help explore spread and exploitation of cereal grains, a economically fundamental component the advent and spread of farming.
2017-08-04 | PXD005908 | Pride
Project description:The legacy effect of cover crops on soil fungal populations in a cereal rotation
| PRJEB12560 | ENA
Project description:Comprehensive Metabolomic Comparison of Five Cereal Vinegars Using Non-Targeted and Chemical Isotope Labeling LC-MS Analysis
2022-05-10 | MSV000089449 | MassIVE
Project description:Cereal aphids continue to be an important agricultural pest, with complex lifecycle and dispersal behaviours. Spatially-explicit models that are able to simulate flight initiation, movement direction, distance and timing of arrival of key aphid species can be highly valuable to area-wide pest management programmes. Here I present an overview of how knowledge about cereal aphid flight and migration can be utilized by mechanistic simulation models. This article identifies specific gaps in knowledge for researchers who may wish to further scientific understanding of aphid flight behaviour, whilst at the same time provides a synopsis of the knowledge requirements for a mechanistic approach applicable to the simulation of a wide range of insect species. Although they are one of the most comprehensively studied insect groups in entomology, it is only recently that our understanding of cereal aphid flight and migration has been translated effectively into spatially-explicit simulation models. There are now a multitude of examples available in the literature for modelling methods that address each of the four phases of the aerial transportation process (uplift, transport in the atmosphere, initial distribution, and subsequent movement). I believe it should now be possible to draw together this knowledgebase and the range of modelling methods available to simulate the entire process: integrating mechanistic simulations that estimate the initiation of migration events, with the large scale migration modelling of cereal aphids and their subsequent local movement.
| S-EPMC4337770 | biostudies-literature
Project description:In this study, the transcriptome of the introgression tomato breeding line BC5S2 and its parental line, Moneymaker (MM) were comparatively analyzed to identify candidate genes related to the differential induction effect of methyl-jasmonate (MeJA) on trichome-mediated resistance responses in these tomato lines.
2015-03-24 | E-MTAB-2898 | biostudies-arrayexpress
Project description:Salmonella enterica serovar Agona (S. Agona) is a foodborne pathogen that caused recurrent multistate outbreaks associated with cereal between 1998 and 2008, underscoring the endurance of Salmonella over time in low-moisture food (LMF) processing facilities. In this study, we aimed to determine the molecular mechanism of survival of S. Agona in LMF and confirm their impact on phenotype by the knockout study. S. Agona strain (CFSAN 000477), isolated from cereal, was selected for this study. A 100µl suspension with a concentration of ~10^11 cfu/ml was inoculated into 3g of rice cereals. Three replications of inoculated cereals were subjected to desiccation stress (aw ≤ 0.25) for 24h at room temperature (25⁰C). Inoculated cereal samples were collected at 6 timepoints post-inoculation. Cells were separated from the food matrix for RNA extraction. RNA sequencing was performed using the NextSeq 2000 platform. Read counts were generated with Salmon v1.9.0. Downstream analysis was conducted with R and KEGG mapper. There were 1120 differentially expressed genes (DEGs) in S. Agona in response to desiccation stress (Padj < 0.01, |log2FoldChange| >1), with 647 downregulated and 473 upregulated. Functional analysis of downregulated DEGs revealed that most of the genes were associated with metabolic pathways, followed by translation, suggesting slower growth in the surviving population. The top 3 upregulated genes/operons: kdp and ccm operon, and tisB were knocked out and checked for survival study. Approximately 1-2 log reduction (p>0.05) was noticed in the survival of the mutants compared with the wild type. This transcriptome data suggests that Salmonella Agona survives in low-moisture food by conserving energy, lowering metabolism, and reducing replication.
2025-06-01 | GSE297918 | GEO
Project description:cereal vinegar sediment (CVS) was concentrated from solid-state fermentation cereal vinegar from Zhangjiajie, Hebei Province, China.
CVS metabolites were extracted by 80% methanol method.
Vanquish was used as LC source of this study.
2021-05-06 | MSV000087375 | GNPS