Dataset for precision yield estimation and mapping in manual strawberry harvesting

This dataset contains harvest data collected during manual strawberry harvesting using instrumented picking carts (iCarritos) in two California fields over a harvest season. The data includes geo-tagged harvest mass and cart motion information recorded by load cells, a GPS receiver, and Inertial Measurement Units (IMU). The dataset enables data-driven yield estimation and mapping for manually harvested strawberries. Furthermore, the dataset could be used to optimize robotic strawberry harvest machines or harvest assist systems, such as crop transportation systems. This dataset is valuable for researchers and practitioners in precision agriculture, offering a foundation for developing scalable automation and precision agriculture technology in specialty crop harvesting. 
, Data was collected from iCarritos developed by modifying a conventional wireframe structure with a wheelbarrow system, integrated with sensors, mounting systems, and control hardware. Two load cells were installed at the front and back of each iCarrito, and the harvest mass was obtained by averaging the readings from these load cells. A significant design choice was to ensure that the iCarritos were low-cost and practical. To achieve this, the carts utilized an affordable Piksi Multi GNSS unit (Swift Navigation Inc., USA) with an integrated IMU. The GNSS unit operated based on SBAS localization and has a rated horizontal Circular Error Probable (CEP) accuracy of 0.75 meters. This unit was used to measure location (latitude and longitude) as well as acceleration data along the x, y, and z axes (ax, ay, az). 
A Raspberry Pi Zero W (Raspberry Pi Foundation, UK) microcomputer served as the central processing unit, with an SD card used to run the cart software and store data during harv..., # Dataset for precision yield estimation and mapping in manual strawberry harvesting with instrumented picking carts

Dataset DOI: [10.5061/dryad.v6wwpzh7h](10.5061/dryad.v6wwpzh7h)

## Description of the data and file structure

## Background

The main goal of the study was to develop a practical, low-cost yield monitoring system for manually harvested strawberries to encourage widespread adoption. A key design decision was to use an affordable GPS relying on the freely available Satellite Based Augmentation System (SBAS) corrections. Pickers were not trained prior to using the iCarritos, and the system was deployed in a commercial field with minimal disruption to established harvesting practices. Data were collected as part of the USDA Agricultural Research Service (USDA-ARS) Areawide Pest Management Grant Program project, “Site-Specific Soil Pest Management in Strawberry and Vegetable Cropping Systems Using Crop Rotation and a Needs-Based Variable Rate Fumigation Strategy,” through N..., While this dataset was derived from field operations involving human workers, it does not contain any personally identifiable information (PII). The dataset consists solely of sensor data collected from instrumented strawberry-picking carts (iCarritos), including GPS coordinates, timestamps, IMU measurements, and load-cell readings. No personal attributes, names, worker identifiers, or demographic information were collected. Carts were used interchangeably by multiple pickers during commercial harvesting operations, and no individual was permanently or uniquely associated with any specific cart. As a result, there is no linkage between the recorded data and any identifiable person.