Department of Agricultural and Food Sciences, University of Bologna, Italy
Statistics is essentially a branch of mathematics applied to analysis of data. The importance of proper application of statistics in agri-food research cannot be ignored. Use of the correct statistical tools is essential since the researcher needs to extract as much information as possible from sensors or experimental results. Statistical methods are important aids to detect trends, explore relationships and draw conclusions. Extracting information from the raw data generated by the sensors is a complicated task, especially when the amount of data is very large (big data).
With a specific focus on the agri-food sector, the aim of this special session is to capture contributions on the application of innovative statistical approaches to elaborate data generated by sensors.
- Machine learning in agri-food sector;
- Innovative multivariate statistical approaches;
- Analysis of data generated by in field sensors;
- Data analysis to monitor product shel-life, frauds, or quality parameters of agri-food products.
Chiara Cevoli is graduated in Food Science and Technologies and she earned the Ph.D in Agricultural Engineering. Actually she is Researcher in Agricultural Engineering at the Department of Agricultural and Food Sciences (University of Bologna). Her research is focused on the applications of the engineering methods to agricultural and food processes. Specific topics range from numerical simulation in food processing, physical characterization of agricultural and food materials, data analysis by using advanced statistical techniques. She is involved in several National, European and International research projects, and research collaboration with agri-food companies. She is a recognized statistical expert in the intergovernmental organization International Olive Council (IOC). She is author or co-author of more than 80 scientific publications.