Tarras Cherry Corp is using New Zealand-developed orchard management technologies to ensure workers are paid for the exact kilograms of cherries they harvest.

The technology, which uses radio-frequency identification, was developed by Auckland based software company, Dataphyll.

Orchard and project manager Ross Kirk said at a time when pickers were in short supply, investing in smart technologies was a way to attract and retain quality workers.

“We want to lead the charge as an innovative and progressive operation throughout the supply chain.”

He said the software provides an absolute volume of harvested fruit through scanning and weighing.

The volume is then linked to the picker.

“Pickers know in real-time how much they have picked and how much they will earn,” he said.

Mr Kirk said as workers were paid per kilogram, there was an incentive to fill buckets.

“A smart picker can earn well because the more they pick, the more they get paid and it pinpoints top performers who pick above the minimum and may be eligible for bonuses.”

He said workers can keep track of their earnings via an app on their phone.

The technology also meant there was no risk of pickers being paid for fruit someone else harvested.

Mr Kirk said traceability would be the immediate benefit this season.

“Over time, long-term data collection will allow orchard mapping to determine harvest volumes and ease control of fruit flow to the packhouse.”

Dataphyll chief executive officer and co-founder Christoph Kistler said the technology was developed to pay pickers for performance, not attendance.

“It tracks workers and buckets via ID tags, which interface with mobile devices and weigh stations in the orchard.”

Mr Kistler said the software, developed initially for the berry industry in 2015, had been extended to meet Tarras Cherry Corp’s needs.

The concept means the weight of harvested cherries is captured via a unique identifier on the bucket. 

There were also other benefits, he said.

“Orchardists can review performance and production in real-time, highlight best performing workers, row-level yields and understand reject rates,” Mr Kistler said.