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Frontiers in Plant Science

出版年份:暂无数据 年文章数:20544 投稿命中率: 开通期刊会员,数据随心看

出版周期:Irregular 自引率:17.6% 审稿周期: 开通期刊会员,数据随心看

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投稿信息

投稿信息
审稿费用
暂无数据
版面费用
2950.0元/篇 (网友贡献,非官方数据)
中国人发表比例
2023年中国人文章占该期刊总数量暂无数据 (2022年为100.00%)
自引率
17.6 %
年文章数
20544
期刊官网
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期刊简介
稿件收录要求

Frontiers in Plant Science is a leading journal in its field, publishing rigorously peer-reviewed research that seeks to advance our understanding of fundamental processes in plant biology. Field Chief Editor Prof. Yunde Zhao at the University of California is supported by an outstanding Editorial Board of international researchers. This multidisciplinary open-access journal is at the forefront of disseminating and communicating scientific knowledge and impactful discoveries to researchers, academics, policy makers and the public worldwide.

In an ever-changing world, plant science is of the utmost importance for securing humankind's future well-being. Plants provide oxygen, food, feed, fibers, and building materials, and are a diverse source of industrial and pharmaceutical chemicals. In addition, they are centrally important to the health of ecosystems, and the management and maintenance of a sustainable biosphere necessitates their thorough understanding. A basic knowledge of plant biology processes underpins our ability to both utilize and improve plants for sustainable production of food, biofuel, and renewable biomaterials, as well as better understand their role in the environment.

Plant science is extremely interdisciplinary, reaching from crop molecular genetics, cell biology, and physiology to ecology, evolution and plant pathogens. It uses the latest developments in computer science, optics, molecular biology, biochemistry, and genomics to address challenges at the cellular level, within whole plants, and into ecosystems; it explores the form, function, metabolism, growth, development, diversity, reproduction, evolution, and their interactions with the environment and other organisms throughout the biosphere.

Frontiers in Plant Science welcomes original and significant contributions from across the field — from single-plant to populations and whole-ecosystem analyses; from molecular, to biophysical, to computational approaches; from molecular to the organism-scale studies.

Please consider the quality and content requirements for experimental studies as listed below

Quantitative analysis needs to be performed on a minimum number of 3 biological replicates in order to enable an assessment of significance. This includes quantitative omics studies (transcriptomics, proteomics, metabolomics) as well as phenotypic measurements, quantitative assays, and qPCR expression analysis. Studies that do not comply with these replication requirements will not be considered for review.

Studies falling into the categories below will not be considered for review, unless they are expanded and provide insight into the biological system or process being studied:

i) Descriptive collection of transcripts, proteins or metabolites, including comparative sets as a result of different conditions or treatments;
ii) Descriptive studies that define gene families using basic phylogenetics and the assignment of cursory functional attributions (e.g. expression profiles, hormone or metabolites levels, promoter analysis, informatic parameters).

Studies using transgenic or mutants lines (plants and algae) should be based on data from multiple independent alleles (at least 2) displaying a common and stable phenotype. Examples include T-DNA, transposon, RNAi, CRISPR/Cas9, chemically induced, overexpressors, reporter fusions (GUS, FPs, LUC) etc. Qualitative data can be presented from a single allele but should be indicative of observations from multiple alleles which should be explicitly stated in the text. Quantitative data should be derived from multiple alleles (at least 2) and should be displayed separately for each allele (with at least 3 independent replications for each allele). Studies reporting single alleles may be considered acceptable when:

i) Complementation via transformation is used for confirmation;
ii) The allele has been previously characterized and published and is representative of multiple independent lines;
iii) Systems where genetic transformation is difficult or not yet possible, alternative evidence should be presented supporting the reported allele.
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