Learn to analyse crop data without programming yourself

Learn to analyse crop data without programming yourself
Photo: WUR

By using sensors, companies in greenhouse horticulture increasingly have access to data, for example about diseases. But how can all that data be turned into useful information? Within the 'PPP Phenotyping 4 Profit (P4P)' project, the Greenhouse Horticulture and Flower Bulbs Business Unit of Wageningen University & Research recently organised a working session for breeders at the NPEC: participants learned how to easily interpret data - without being able to program themselves.

The Netherlands Plant Eco-phenotyping Center (NPEC) is a research center specialised in plant phenotyping. The aim is that large quantities of plants can be quickly and accurately assessed as to how plants respond to their environment. Researchers can map the properties of crops in six different modules - such as a greenhouse and climate cells. NPEC is an initiative of Wageningen University & Research (WUR) and Utrecht University (UU) and is funded by the Netherlands Organisation for Scientific Research (NWO).

In early November, WUR organised a working session within the 'PPP Phenotyping 4 Profit (P4P)' project. In this meeting participants, with the help of a Jupyter Notebook (a web-based platform), got to work with NPEC data on how different varieties of both cyclamen and peanut plants and tomatoes respond to plant diseases. The data came from both the companies involved and Wageningen researchers. A Jupyter Notebook takes the user step-by-step through the development of chunks of code, in the Python programming language, to interpret data: this allows the user to see both the code and the result directly on his or her screen.

Continue reading.

Source:

Share