While many crops already are or are becoming mechanized, many valuable  crops still are hand-picked.    These crops sometimes need new ways to collect precise geospatial harvest data which can then be used to monitor, measure, and optimize what is happening in the field.   Inefficiencies and waste lead to loss of revenue, loss of the valuable resources which went into growing the crop, and environmental impact.

In February 2016, we visited Crisalida Farms in Oxnard, California.  Four harvesters carried smartphones with an app which gave us their GPS location every 5 seconds during the workday. Using this data, we tried to construct a yield map and estimate harvest speed.

Reference:  Srivastava N, Maneykowski P, Sowers RB. Algorithmic geolocation of harvest in hand-picked agriculture. Natural Resource Modeling. 2018;31:e12158. https://doi.org/10.1111/nrm.12158

Thanks to:

• Research Board of University of Illinois
• Maureen McGuire, Crisalida Farms

Code: https://gitlab.engr.illinois.edu/AlgorithmicGeolocation/Algorithm.git

Press releases:

• https://engineering.illinois.edu/news/article/24515
• https://math.illinois.edu/news/2018-03-22/smart-strawberry-field
• http://publish.illinois.edu/r-sowers/the-smart-strawberry-field/