Data science at farm level: Explaining and predicting within-farm variability in potato growth and yield

摘要

The growth and yield of crops within a farm largely vary among fields. Farms are increasing in size by acquiring smaller land parcels from different farmers who have different management strategies. As a result, between-field variability increases and understanding such variability is a necessity for precision farming. New data analysis techniques are needed in this context, especially given the trend that more farms are collecting more data. Therefore, this study has the objective to provide a data analysis methodology to analyze within-year variability and identify year-independent factors that influence growth. As a second objective, we applied this novel methodology to a case study, where we analyzed potato growth data of four successive years of a farm in the south of the Netherlands.