Proceedings 2018, 2, 980; doi:10.3390/proceedings2130980 www.mdpi.com/journal/proceedings Proceeding Electromagnetic Sensing for Non-Destructive Real- Time Fruit Ripeness Detection: Case-Study for Automated Strawberry Picking † Olga Korostynska 1 , Alex Mason 1,2, * and Pål Johan From 1 1 Faculty of Science and Technology, Norwegian University of Life Sciences, 1432 Ås, Norway; olga.korostynska@nmbu.no (O.K.); pal.johan.from@nmbu.no (P.J.F.) 2 Animalia AS, Norwegian Meat Research Institute, 0513 Oslo, Norway; alex.mason@animalia.no * Correspondence: alex.mason@animalia.no; Tel.: +47-917-49-792 † Presented at the Eurosensors 2018 Conference, Graz, Austria, 9–12 September 2018. Published: 10 December 2018 Abstract: Rapid non-destructive measurement or prediction of ripeness, quality and fungal infection in various fruits is a challenge currently affecting automation of fruit harvesting and gathering. This is especially true for delicate and difficult to store fruit such as strawberries, which are traditionally delivered directly to the customer from the farm. However, transportation of the product, often overseas, means that fruits’ condition at the time of gathering should be precisely planned. This paper reports on the initial trials of using non-invasive athermal microwave spectroscopy as a tool to assist in real-time fruit ripeness detection. The trials were conducted during June 2018 and have illustrated that the proposed method can distinguish between strawberries at different stages in ripening (R 2 = 0.788, p = 0.0283). The findings support further development of the technique, which aims for integration with the Thorvald II agricultural robotic system. Keywords: microwave spectroscopy; strawberry; ripeness prediction; agricultural robots; automated fruit picking 1. Introduction This work is focused on developing a real-time strawberry ripeness analysis tool for the use with the Thorvald II robotic system, which can be configured modularly depending on the specific agricultural product and need. This robot (Figure 1) has been successful in demonstrating its capabilities for applying UV light to strawberries with a goal to investigate the effect of UV light on mildew [1]. The robot used an inertial measurement unit, encoder odometry and LiDAR together with a map for localisation, and navigates to pre-recorded way-points in a predefined map. A cartesian-type harvesting robot for strawberry picking was reported in [2]. A point cloud was generated by a RGB-D camera and used to assist in strawberry harvesting, the overall efficiency of the robot was approx. 65.3%, but reached more than 95% for single strawberries without occlusion or in clusters. The approach of using real-time microwave spectroscopy aims to achieve much higher efficiency for sustainable agricultural applications. Microwave sensing is a versatile and attractive novel technology which has already been successfully used for various industrial applications including water level measurements, material moisture content, in construction industry for non-invasive evaluation of structures and even in the healthcare industry for real-time monitoring of patients’ health indicators [3,4]. Its application in food evaluation and analysis is also attracting attention especially due to non-destructive and hygienic means suitable for a variety of foods [5]. In this work the feasibility of using planar type