Food Safety & Traceability > DataBar's move into the Produce Industry

25 January 2018

DataBar's move into the Produce Industry

Owen Dance, Manager Quality Services GS1 New Zealand and Dr Hans Maurer, Chair Technical Advisory Group United Fresh New Zealand Inc.

Consumers, retailers, wholesalers, packhouses and growers alike are all familiar with fruit label- the tiny stickers commonly found on oranges, apples, kiwifruit, avocadoes and a myriad of other produce. The purpose of these stickers is pretty straight forward – identification.  But as nothing in life is simple, identification means different things to different people!  This is why not every fruit label looks the same and not every fruit label carries the same information. Commonly found information ‘bytes’ on fruit labels include brand, grower name, PLU numbers, country of origin, and of late, DataBar.  Not that all this information fits on a single fruit label, we have yet to see a produce grower or marketer succeed in that attempt! It follows therefore that some fruit labels are more useful at retail than others.  A fruit label only containing brand name and country of origin for example and no PLU number, will do nothing for price accuracy at the checkout, whilst a label with a global PLU number will allow for accurate price and product capture. And then there is DataBar.

DataBar is an idea that has been around for a while and whose time has now come for fresh produce, for a variety of reasons.  These include marketing, food safety and logistics opportunities, but understanding just what it offers is important to avoid unrealistic expectations or excessive impositions on the industry. 

There are plenty of reasons why suppliers and retailers should welcome this clever little barcode that can fit on a fruit label where workable barcodes couldn’t previously go.   They enable totally accurate identification at the checkout and eliminate the old problems of mistaken identification by operators, human error in keying PLUs and incorrect sales data leading to ordering errors with all the problems they create. 

DataBar works like any other barcode in retail.  It contains a GS1 identification number (Global Trade Item Number – GTIN) that is scanned and converted into data about what the product is.   The checkout system then searches the store’s database for the price of the product and it all comes together at the till.     The GTIN offers additional granularity compared to the PLU as an identifier as it enables more specific identification.   PLU 4133 is small Gala apple which is fine but whose small Gala apple is it?   GTINs can separately identify small Gala apples according to their source the way they can separate cans of Oak baked beans from cans of Heinz Wattie’s baked beans.

This is where the potential for misunderstanding arises.   Growers who learn about DataBar can end up having nightmares over the thought that their customers will expect them to stick DataBar labels on fruit before it goes out of the gate.  Packhouse operators have the vapours about the complexity of managing labels so that grower Smith’s small Gala apples have Mr Smith’s GTIN on them and grower Brown’s Gala apples have her GTIN on them.

Could it really get that complicated?  Theoretically yes, but logically nobody is going to want to impose that sort of difficulty and cost on the industry – as long as they understand the implications and how to use all barcodes properly for traceability and optimal identification.  In theory each grower could have a GTIN for each row in the orchard or field and retailers could know the origin of each piece of produce with that degree of detail.  Some zealous souls have been heard talking of such a possibility, but let’s run a reality check on the idea.

The complexity and cost of such practices would be prohibitive and retailers would not want databases cluttered with hundreds or thousands of GTINs for each variety they sell.   Supermarkets already have that problem with greeting cards and have given up trying to keep track of birthday cards for five-year-old boys versus anniversary cards for silver weddings versus retirement cards with humorous themes versus birthday cards for nine-year-old girls – you get the picture.  Now they just have a small range of GTINs that identify cards by price band and they leave it to the card suppliers to worry about restocking the displays.

Applied to produce that would be less use than PLUs but a happy medium can be found when produce is identified by brand and unbranded produce is identified by a GTIN agreed between the supplier and customer.   So, brands such as Zespri, Enza and others can carry on as they do now, and suppliers of unbranded produce can continue to send it out of the gate and leave it to the packhouse to apply the label with the DataBar appropriate to each consignment.   (Sorry packhouse operators.  Someone has to do it and you are the only logical contenders but at least it is not going to be as complicated as you may have feared).

In this way the GTIN in the DataBar tells the retailer what the produce is but does not contain specific traceability data.   That much data cannot fit into the type of DataBar that fits on a fruit label.  It can fit into DataBar Expanded barcodes but they are too big for fruit labels.  Larger items such as bagged salads can accommodate them however and they are very suitable for products like these.

But if traceability data can’t fit on fruit labels how can traceability back to the grower be achieved?   The way it is achieved already on meat and other date-sensitive products.   The GS1 System provides plenty of solutions to achieve that through the larger barcodes on cartons and trays.   Of course, that does not maintain the link from the back door of the supermarket to the checkout at single item level in the case of fresh produce.  Solving that part of the supply chain remains an issue for now in Australia and New Zealand.

In Europe and Asia the use of DataBar and DataBar Expanded is well advanced and across the Tasman DataBar is being rolled out now initially on stone fruits and apples.  A growing number of Australian retailers are already scanning DataBar on imported fruit and some of their New Zealand suppliers have been asked to use it.  This is the beginning of a process that will see both DataBar and DataBar Expanded in use across Australia within two or three years.  New Zealand retailers are watching with interest and can be expected to follow suit.

The chain is not perfect over the last few metres but work to further narrow the gap is going on all the time. In the meantime, DataBar offers a significant improvement in enabling accurate identification and improved category management.  Further out DataBar Expanded will add to the benefits for everyone involved.