Impact Factor 4.106 | CiteScore 4.47
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in Plant Science

Bioinformatics and Computational Biology

Crop and Product Physiology

Functional Plant Ecology

Marine and Freshwater Plants

Plant Abiotic Stress

Plant Biophysics and Modeling

Plant Biotechnology

Plant Breeding

Plant Cell Biology

Plant Development and EvoDevo

Plant Metabolism and Chemodiversity

Plant Microbe Interactions

Plant Nutrition

Plant Physiology

Plant Proteomics

Plant Systematics and Evolution

Plant Systems and Synthetic Biology

Plant Traffic and Transport

Technical Advances in Plant Science

Virology

Scope

Technical Advances in Plant Science publishes new methods, techniques and protocols that advance our ability to study and understand the biology of plants of any type (unicellular or multicellular), at levels ranging from molecules to whole organisms.

World-class research. Ultimate impact.

Congratulations to our authors, reviewers and editors for accelerating new knowledge and solutions – and helping everyone to live great lives on a healthy planet.

Editorial Board

Scope

Technical Advances in Plant Science focuses on the development of new techniques and technologies that allow previously intractable questions to be addressed. The section aims to accelerate the pace of discovery through publication of new methods, techniques and protocols that advance our ability to study and understand the biology of plants of any type (unicellular or multicellular), at levels ranging from molecules to whole organisms. Topics covered by this section include, but are not limited to:

· Methods for system-level measurements, including genomics, proteomics, metabolomics

· High-throughput screening

· Methods for nucleic acid manipulation, amplification and sequencing

· Tools for the analysis and manipulation of gene expression, including epigenetics, gene targeting, transduction, RNA interference

· Chemical biology techniques, including chemical labeling, biosynthesis of probes, inducers, modulators and ligands and chemical screenings

· Microscopy and non-optical imaging techniques, including probe design and labeling methods, spectroscopy and in vivo imaging

· Methods for physiological and morphological analyses

· Protocols for plant transformation, if significant improvements over existing methods are clearly demonstrated

· Computational and bioinformatics approaches for analyzing and/or integrating large-scale datasets

· Methods for integrating mathematical, statistical, and/or computational models to decipher plant function and growth at any level

· Adaptation of existing methods to plant systems

· Improvements to existing methods that significantly increase their utility and/or robustness

· Instrumentation development

The main criteria for publication are proof-of-concept and demonstration of the application of the new research tool, and comparison with available approaches, along with the full experimental details to allow readers to employ it. Submissions lacking the aforementioned criteria or describing the optimization of an existing technique (e.g. for use with another tissue or plant species) do not fall within the scope of the section.

Please consider the requirements for experimental studies as listed below

Quantitative analysis need 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 mutant plants 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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in Plant Science

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Scope

World-class research. Ultimate impact.

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