Agriculture solutions - develop healthier, higher yielding crops

Agriculture

How Can Data Science Develop Healthier and Higher-Yielding Crops?

For over 20 years VSNi has developed a range of data and analytics software to support scientists, researchers and breeders within the Agriculture sector. 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.

Genstat

Genstat provides an easy-to-use environment where only a few instructions or selections from the menus are needed to undertake simple or more complex analyses, bringing reliable and accurate analytics to your processes. For those in Agriculture, REML analysis facilitates fitting complex linear mixed models to unbalanced, spatial or repeated measures data arising from on-farm trials. The strength in the ANOVA menu for analysis of variance when comparing treatment or cultivar means widley used in Genstat.

Genstat’s experimental design tools generate robust and efficient experimental designs, including randomised block, split-plot, row-column and cyclic designs for field trials. 

Genstat uses generalized linear mixed models (GLMMs) and hierarchical generalized linear models (HGLM) to analyse non-Normal data from complex experimental designs with several sources of random variation, such those in crop trials. Cited in thousands of research papers, GLMM analysis is a common model used by those in agriculture.

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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.

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