Skip to content
Food Science
Data Analysis for Food Science
Food manufacturers face a continuous challenge to increase productivity and save on costs while still meeting quality control and safety standards. You need systems that will help meet the needs of customers and also satisfy government regulations.
From government bodies such as the UK Food Standards Agency and AgResearch NZ to independent food processors and manufacturers, VSNi provides quality management and analytics software to support your business.
How Can Data Analysis Improve Safety, Nutrition and Flavour in Food 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 can accommodate increasingly large and complex datasets.
With many analyses, procedures and directives the following is but a small sample of some of the possibilities:
- Design experiments and plan monitoring systems
- Analysis of variance to compare varieties and trends
- Perform cluster analysis for large datasets
- Generalized Procrustes analysis for studying sensory evaluations
- Non-linear generalized canonical analysis
- Advanced modelling using HGLMs
- Integration between agri and climatic communities
The availability of software such as Genstat has created the opportunity to use powerful statistical methods in the research of food science. Our role is to support you in achieving your goals, and as such we promise an unparalleled level of support to assist with your work in food science.
Our data analysis software provides all the tools you need to bring viable results from your food science data analyses. You can:
- Analyse large, complex datasets easily and efficiently
- Assist in defining factors that affect your research
- Discover patterns in vast sets of data
- Determine genetic risk factors
- Examine traits of agro-economic importance
- Interpret sensory analysis data
- Design optimal experiments for sensory trials such as taste tests
- Assist in increasing yield and produce
- Create interactive visual presentations and interpretations of data
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 can accommodate increasingly large and complex datasets. The science of food seems to become more complex by the day with new standards and regulations being introduced and the demands of the consumer continually on the rise.
It takes a strong breed of software to keep up with the needs of today’s food scientists and researchers. You need software with a comprehensive knowledge of the biological sciences partnered with an understanding of harvesting right through to sensory evaluation.
Our Food Science Software Solutions
At VSNI, we have easy to use statistical software to help your food science research thrive. We also have fully documented user guides, knowledge bases and video tutorials, making VSNi’s products easy to use – but should you need it you can even get help directly from the team who developed the software (us!).
Genstat
Genstat  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 processes.
You have access to statistical tests for a wide range of response variables and hypotheses such t-test, Wilcoxon signed rank test, Kruskal Wallis test, Spearman correlation test, Binomial test, Chi-square test, McNemar’s test and many more.
Genstat’s powerful ANOVA models for the analysis of variance when comparing treatment means are widely used by those in the food science sector as well as the six-sigma statistical tools, including control-charts, for identifying variations or defects in a process leading to quality improvements.
AsReml
ASReml has become a default software package for the analysis of linear mixed models. The Average Information Sparse Matrix algorithm of ASReml maximises processing speed, allowing ASReml to rapidly solve a large number of mixed model equations with complex data sets. Linear mixed-effects models provide a rich and flexible tool for the analysis of many data sets commonly arising in food science.Â
The food science sector includes food safety, food sustainability, microbiology, probiotics, carbon footprint, foodborne diseases, post-harvest, shelf life, nutritional value, food allergens, animal feed and food formulation. ASReml’s facilities for linear mixed models with random effects, repeated measures, correlated structures, and messy unbalanced data can handle all your data analysis requirements.
Genstat  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 processes.
You have access to statistical tests for a wide range of response variables and hypotheses such t-test, Wilcoxon signed rank test, Kruskal Wallis test, Spearman correlation test, Binomial test, Chi-square test, McNemar’s test and many more.
Genstat’s powerful ANOVA models for the analysis of variance when comparing treatment means are widely used by those in the food science sector as well as the six-sigma statistical tools, including control-charts, for identifying variations or defects in a process leading to quality improvements.
ASReml has become a default software package for the analysis of linear mixed models. The Average Information Sparse Matrix algorithm of ASReml maximises processing speed, allowing ASReml to rapidly solve a large number of mixed model equations with complex data sets. Linear mixed-effects models provide a rich and flexible tool for the analysis of many data sets commonly arising in food science.Â
The food science sector includes food safety, food sustainability, microbiology, probiotics, carbon footprint, foodborne diseases, post-harvest, shelf life, nutritional value, food allergens, animal feed and food formulation. ASReml’s facilities for linear mixed models with random effects, repeated measures, correlated structures, and messy unbalanced data can handle all your data analysis requirements.
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.
Enhancing agronomic research through precise statistical analysis with Genstat
Deben Agronomy is dedicated to giving potato and vegetable growers…
Accelerating sugar beet breeding insights for SESVanderHave
Explore SESVanderHave’s H3 Pipeline: Advancing sugar beet breeding through phenotypic…
Food Standards Agency: safer food for the nation
Everything we do reflects our vision of ‘Safer food for the nation’. We aim to ensure that food produced or sold in the UK is safe to eat, consumers have the…
Discover More Solutions
Need a statistics tool for food science?
If you are looking for data science to develop your food science research, submit your details below and we’ll be in touch.