Webinar: half a million fruit scans reveal what traditional testing misses

Across global supply chains, fruit quality often appears inconsistent — even in operations that rely on established testing routines. A decade-long dataset compiled from more than 500,000 individual fruit scans now shows why. Using non-destructive NIR technology, researchers have uncovered the extent to which internal quality varies within crops such as avocado, mango, citrus, grapes and apples, highlighting patterns that traditional small samples regularly miss.

This body of data was presented in a recent webinar led by Director of Applied Science Galen George, who offered an in-depth look at how maturity, dry matter, and predicted shelf life behave within real commercial conditions. According to George, the scale of the dataset makes clear that many long-held assumptions about firmness, brix and dry matter do not always align with the true variability found in orchards, packing lines or retail supply.

Non-destructive tools redefine what “representative sampling” means

The session demonstrated how large-scale non-destructive testing allows teams to move beyond narrow samples and capture a wider, more accurate picture of internal quality. By scanning fruit at volume, NIR tools uncover trends and anomalies that would otherwise go unnoticed — especially in seasons with challenging climate or uneven orchard performance.

George noted that real operational decisions depend on understanding the full distribution of maturity and dry matter, not just a handful of test fruit. He underscored that data-driven approaches enable more precise harvest timing, improved lot segregation, and stronger alignment with retailer specifications.

Practical insights for operations facing quality pressure

For growers, packers and retailers working under tighter customer expectations and greater variability from climate or supply complexity, the webinar offered practical takeaways grounded in measurable data. Key themes included:

-why firmness and brix correlations may shift depending on cultivar, region and season

-how predicting shelf life from non-destructive measurements can reduce quality claims

-the value of actionable datasets when planning harvest, storage and shipment decisions

-how NIR tools support more consistent, retailer-ready fruit through accurate maturity assessment

By replacing assumptions with statistically meaningful data, operations can navigate variability more confidently and deliver more uniform fruit to the market.

Watch the webinar here.

Send an inquiry to explore how data-driven, non-destructive testing can transform your decisions from harvest to retail.