Developing data analysis tools to explain yield gaps and improve arable crop cultivation

Description

AgroVision supplies farmers and agribusiness organisations with specialised Farm Management Information Systems (FMIS). Through their distributors, they supply and support their software nationally and internationally. Thousands of farmers and companies in the agribusiness use their products every day. At any time of the day they have an excellent insight into their operational management. AgroVision is quick to respond to the requests and suggestions of customers.

For arable farmers, AgroVision is offering the FMIS CropVision. Farmers can document al their fields and keep track of the field operations like sowing, fertilization, crop protection and harvest. The farmer can also share his data with e.g. his advisor.  Besides documentation, farmers can also use weather based decision support systems (e.g. Gewis or ProPhy) for their operational management decisions during the growing season. 

The objective of this thesis is to investigate if the management decisions of the farmer (reflected in his field documentation) and additional information (e.g. weather conditions, field characteristics and crop rotation) can be used to estimate and explain yield variability within a farm and between farms. This information can be used to improve or develop new decision support tools for farmers and agribusiness organizations to crop production. In addition, it will provide more scientific insight in the explanation of yield gaps.

More information

www.agrovision.comwww.agrovision.nl/sectoren/teeltwww.cropvision.nl

Type of work

This project gives a great opportunity to combine data analysis techniques of big data, agronomic theory and practical knowledge of arable farming. Statistic techniques will be used, possibly in combination with crop simulation models.

Collaboration

AgroVision, Deventer.

Prerequisite

Completion of the course PPS-30306 Quantitative Analysis Land Use Systems. Familiarity with the software packages R/Stata and ArcGIS is desired, but can be improved during the thesis work. Practical knowledge of arable farming is useful. 

Time/ Location          

Agrovision, Deventer & Plant Production Systems Group, WUR

Supervisors

Pytrik Reidsma                                   0317-485578                           pytrik.reidsma@wur.nl

Leon Spätjens                                                                                     L.Spatjens@agrovision.nl