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Plant Science
Data Analysis for Plant Science
Plants provide us with food, clean air, water, fuel, clothes, medicines and much more. Humanity depends on plants; therefore, plant science is essential. Using a multidisciplinary approach, plant scientists analyse the biology of plants, their relationship to the environment and how this knowledge can be applied to any number of challenges, such as ensuring food security in the context of population growth and climate change.
From the domestication of the first agricultural plants around 11,000 years ago to the recent genome editing technique CRISPR-Cas9, plant scientists have been improving the quality of life for people around the world.
VSNi works with plant scientists to provide data analysis solutions that help improve decision making and outcomes.
How Plant Analysis Lead to Optimised Outcomes in Plant Science
For over 20 years VSNi has developed a range of data and analytics software to support scientists, researchers and breeders within the biosciences. Designed by statisticians with non-statisticians in mind, our products are ideal for users looking for exceptional decision-making tools that are able to accommodate increasingly large and complex datasets.
Our software is used for genetic analysis, mapping the genes that influence a particular trait (plant height, for instance) and helping researchers and plant breeders identify individual markers or sequences in crop genomes. Plant breeders, including some of the world’s largest seed companies, use these markers to breed varieties of crops with desirable traits. Our software can also be used to examine the effects of different treatments applied to crops, as well as a range of other statistical analysis.
Our Plant Science Software Solutions
VSNi creates easy-to-use statistical software to help your operation thrive. We also have fully documented user guides, knowledge bases and video tutorials, making VSNi’s products easy to learn- but should you need more assistance you can even get help directly from the team who developed the software (us!).
Genstat
Genstat has a long history dating back to 1968 and was born from the requirement for better plant science data analysis. The package provides an easy-to-use environment where only a few instructions or selections from the options menu are needed to undertake simple or more complex analyses, bringing reliable and accurate analytics to your plant breeding programmes.
Genstat includes comprehensive linear mixed model facilities for modelling field and multi-environment trial (MET) data, and decision support tools for automating the analysis of spatial data from a single trial or a series of trial data. Popular among plant breeders using Genstat is the suite of procedures for statistical genetics, including genomic prediction (or genomic selection) and selection indexes. You can explore the phenotypic performance of plant genotype in different environments using GGE biplots, AMMI models, Finlay & Wilkinson joint regression analysis and/or stability coefficients.
In addition to these main features used by plant scientists, Genstat also offers;
- QTL to identify the genetic factors underlying phenotypic variation in plants using QTL linkage analysis, or association linkage disequilibrium (LD) mapping from a genome-wide association study (GWAS).
- Tools to generate robust and efficient experimental designs, including randomised block, split-plot, row-column and cyclic designs for field trials and laboratory experiments
- Analysis of variance for comparing treatment or cultivar means
- Plus many, many more
AsReml
ASReml arose out of a collaboration between Arthur Gilmour and Brian Cullis (New South Wales Department of Primary Industries, Australia) with Robin Thompson and Sue Welham (Rothamsted Research, United Kingdom). The alliance of such world-leading expertise in the analysis of plant science data lead to the development of linear mixed model methods in ASReml that are both statistically and computationally efficient.
In plant breeding, typically there are several commercial traits of interest. ASReml can fit multi-trait models to obtain genetic correlations between traits to assist with product selection. ASReml is used to fit multi-environmental trial analyses with complex variance structures allowing for better use and understanding of genotype-by-environment interaction. Our software is designed to help you;
- Incorporate pedigree information in your linear mixed models anaysis to estimate breeding values to select your future parents
- Examine genotype-by-environment patterns to select your best genotypes
- Perform GWAS analyses for multiple traits and multiple environments
- Estimate heritability for multi-environment trials
- Detect QTLs for complex traits
- Deal with missing data
- Identify breeding values and determine which are the most important
- Plus many, many more
Genstat has a long history dating back to 1968 and was born from the requirement for better plant science data analysis. The package provides an easy-to-use environment where only a few instructions or selections from the options menu are needed to undertake simple or more complex analyses, bringing reliable and accurate analytics to your plant breeding programmes.
Genstat includes comprehensive linear mixed model facilities for modelling field and multi-environment trial (MET) data, and decision support tools for automating the analysis of spatial data from a single trial or a series of trial data. Popular among plant breeders using Genstat is the suite of procedures for statistical genetics, including genomic prediction (or genomic selection) and selection indexes. You can explore the phenotypic performance of plant genotype in different environments using GGE biplots, AMMI models, Finlay & Wilkinson joint regression analysis and/or stability coefficients.
In addition to these main features used by plant scientists, Genstat also offers;
- QTL to identify the genetic factors underlying phenotypic variation in plants using QTL linkage analysis, or association linkage disequilibrium (LD) mapping from a genome-wide association study (GWAS).
- Tools to generate robust and efficient experimental designs, including randomised block, split-plot, row-column and cyclic designs for field trials and laboratory experiments
- Analysis of variance for comparing treatment or cultivar means
- Plus many, many more
ASReml arose out of a collaboration between Arthur Gilmour and Brian Cullis (New South Wales Department of Primary Industries, Australia) with Robin Thompson and Sue Welham (Rothamsted Research, United Kingdom). The alliance of such world-leading expertise in the analysis of plant science data lead to the development of linear mixed model methods in ASReml that are both statistically and computationally efficient.
In plant breeding, typically there are several commercial traits of interest. ASReml can fit multi-trait models to obtain genetic correlations between traits to assist with product selection. ASReml is used to fit multi-environmental trial analyses with complex variance structures allowing for better use and understanding of genotype-by-environment interaction. Our software is designed to help you;
- Incorporate pedigree information in your linear mixed models anaysis to estimate breeding values to select your future parents
- Examine genotype-by-environment patterns to select your best genotypes
- Perform GWAS analyses for multiple traits and multiple environments
- Estimate heritability for multi-environment trials
- Detect QTLs for complex traits
- Deal with missing data
- Identify breeding values and determine which are the most important
- Plus many, many more
Case Studies
Our analytics software and consulting services are chosen by seed, plant, aqua and animal breeding companies worldwide to support and inform the development of new varieties, strains, stocks and breeds.
Accelerating sugar beet breeding insights for SESVanderHave
Explore SESVanderHave’s H3 Pipeline: Advancing sugar beet breeding through phenotypic…
Enhancing genetic evaluation and selection for a corn seed
Enhancing genetic evaluation and selection for a corn seed company
KWS: supplying seeds to the farming industry
KWS is one of the world’s leading suppliers of seeds to the farming industry and it is therefore no surprise that research into plant breeding and seeds is a crucial part…
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Plant Science , FAQs
What is Plant Analysis Software?
Plant analysis software is designed to help plant scientists and agronomists analyse various aspects of plant health, traits, genetics, and development. Researchers use such software to make their analysis work, quicker and more accurate. It can be used to make informed decisions, identify key traits and variations, generate experimental designs and analyse data to develop plant breeding programmes.
Which Plant Analysis Software Should You Use?
Our plant breeding software is a world leader in analysis solutions for plant breeding activities. It can accommodate increasingly large and complex datasets to drive exceptional decision making of your breeding programmes. Find out more about each of our tools including ASReml-R, ASReml-SA, Genstat and CycDesigN.
How Do You Use Plant Analysis Software?
If you are using plant analysis software for the first time, we have in depth guides available on how to use each. Check out our tutorial videos, knowledge base and E-Learning to become an expert and enhance your research.
How Do You Import Data into Plant Analysis Software?
You can follow our simple guide to importing and exporting data into plant analysis software here.