Development and application of a strawberry yield-monitoring picking cart.

Highlights • An instrumented picking cart is developed for strawberry yield monitoring. • The yield-monitoring device is equipped with load cells, an RTK GPS, and an IMU. • A comprehensive calibration process is performed for the picking cart's load cells. • A yield map for a 300 m 2 plot of a strawberry field is generated. • The mean prediction accuracy of the load cells is 4.8 %. Abstract Strawberries in California have a $2 billion direct economic impact on the state; however, they are currently produced based only on uniform field management techniques. Creating yield maps of strawberries could allow for variable-rate and site-specific applications of inputs, which could improve productivity and reduce environmental pollution. This paper presents the development and application of an instrumented strawberry-picking cart for yield mapping. During manual harvest of strawberries planted on raised beds, pickers walk inside the furrows, pick fruit from the beds on both sides, and deposit them into a tray placed on a picking cart. A 'smart' picking cart, similar to the standard carts, has been designed and instrumented with several types of sensors including load cells, a real-time kinematic global positioning system (RTK GPS), a microcontroller, and an inertial measurement unit (IMU). This instrumented cart serves two purposes: to work in sync with tray-transporting robots during robot-aided strawberry harvesting, and to create yield maps of strawberry fields. A yield map for an approximately 300 m 2 plot of a strawberry field in Salinas, California, was generated after the cart was calibrated. During the yield-monitoring experiment, 13.5 trays, each with a capacity of about 4.2 k g of strawberries, were filled with fruit. The mean prediction accuracy of the mass of full trays measured by the load cells was calculated to be 4.8 %. [ABSTRACT FROM AUTHOR]