Traceability Tools Change the Game for Agriculture

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By Peter Keen

Traceability is becoming as key to agriculture as shipping and payments are to online retailing. In each case, the product – foods, consumer goods, books, etc. – adds dimensions of value through how information is collected and accessed. Is it organized and categorized so that multiple providers can use it to streamline the steps from “farm to fork” for agriculture, producer to seller in goods and services, and bush to cup for teas? Can they add new services and extend relationships?

Traceability is best illustrated by questions that can be answered only if data is directly accessible at the needed level of detail:

How fresh is this tea? Here, the data needs to be gathered at the start and completion of each key process and stored in a form that cannot be altered for fraudulent purposes. It will include a batch identifier, using a standard format and encoding technique defined by a standard-setting authority like ISO.

Is this a genuine Taiwan oolong or a Vietnam counterfeit? The needed data here will increasingly be DNA fingerprinting, soil and weather data from sensors in the field, and other genetic and molecular information. This can then be accessed by the growing number of AI machine learning and neural models that are able to assess the sample via its software algorithms. The AI tools typically have a 95%+ success rate in accurately identifying source of origin, variety, terrain, and genotype.

Where did this shipment get contaminated? Food safety is increasingly a mandated traceability requirement, largely based on the principle of “one step back, one step forward.” This places accountability on an organization to record where it sends its ingredients or products (forward) and be able to where, when, and from whom it received them (back.) The new traceability infrastructures and data management tools extend this to any step back by any authorized participant in the business ecosystem (a bank examining historic quality data from growers or a broker assessing a container shipper or port cargo handler (forward.)

Accommodating other questions adds new players and types of record. For a bank: has the grower met its commitments so we can make payment immediately and electronically? (Add access to contract data and performance history.) For the consumer: can I find this tea in a nearby store and at a lower price? (Use a smartphone to scan the product identifier and link to internet search engines and shopping apps.) For the retailer: where is this missing package? (Access the audit trail of the goods that is updated at each step. Include growers, truck shippers, brokers. For regulators and procurement units: does this supplier meet standards of worker rights and ethical treatment? (many leading firms include publication of approved suppliers in their data stores, with links to relevant inspection reports, government reviews, etc.)

The collaborations that rest on shared traceability data form an ecosystem; an extended supply chain. Can we offer working capital credit lines to this grower, factory, or distributor? (Banks, insurers, public agencies.) Which 3PL (Third Party Logistics) transportation service that we use has the fewest delivery errors and customer returns? (Access to partner systems.)

All these questions are very different but the tools to answer them are increasingly converging. Implementing them is not always a simple matter. Small growers often lack the financial resources to invest in equipment. Lack of industry standardization of many data categories and codes blocks information-sharing. In some remote regions, needed wireless telecommunications services are absent, fragmented, or unreliable. That said, momentum is building as leading food companies whose business includes teas and technology providers together build experience and stretch beyond pilot projects.

Here’s a review of the general-purpose tool base that is becoming the norm. All the questions listed, plus many others, can be handled quickly, conveniently, and cheaply if the data is automatically collected (time, weather, process steps) and can be accessed by a mobile scanner. The major development in the past few years here has been that the best general-purpose scanner is now the smartphone.

Data acquisition and coding

The best representation and display of the data is the QR barcode. Consumers can easily point their phone at the code on the package and get traced answers: Is this fresh? Can I find it cheaper? Is it the published heritage, variety, and grade? Several Japanese firms are adding phone or internet access to the farmer from the supermarket.

This encodes data in optical form so that it can be accessed easily anywhere, anytime. And it can be any type of data. QR stands for quick response and was an initiative for tracking parts in auto manufacturing. The barcode has two dimensions; this permits cross-referencing of items. The barcode is a mini-database system that can store in non-alterable form up to 7,000 digits, typically. Changes and updates can be handled by uploading new data wirelessly to a remote processing system.

The barcode is limited in its functionality in two-way interaction and for most of the past decade, RFID chips seemed the prime opportunity. These can be updated at the point of event, while bar codes are fixed. RFID makes more effective use of NFC – near field communication. This is, in essence, a mini wi-fi with a shorter range. RFID tags don’t have to be in line of sight of scanners or sensors, unlike QR barcodes. Many can be programmed to, for instance, broadcast an alert when they detect a plant, weather, or soil problem. Add to this Bluetooth low energy beacons and the technology range is broad and flexible.

Much of the new data will come via wireless networked sensors using internet protocols. They are components in what is termed IoT: the internet of things – really of anything. Sensors include heat imaging and x-ray spectrography for pest detection, soil analysis, humidity, water conditions, pesticide levels, weather alerts, and many other components of precision agriculture.

 Many of these capabilities won’t be used by most growers and other parties in the supply chain will select a few of them. The key point to make is that the smartphone and barcode, even the plain UPC product barcode that is on every item sold in a store, are inexpensive and people are comfortable with them. That includes smallholder tea growers, tea lovers, factory workers, tea store owners, etc. The bar code is familiar and simple to scan with no computer commands, elaborate displays or need for technical expertise.

Data quality and standardization

There’s a catch, of course. Most firms in most industries still have their own coding and data management systems so that their data can’t be directly linked to or accessed by other firms. The tea industry has been a laggard in implementing international data standards, of which there are hundreds.

Most companies have poor data in too many areas and poor processes. Given all the hype about Big Data and the massive investments large firms made through the early 2000s in integrated ERP systems (enterprise resource planning) this is a surprise. But a recent survey of Chief Executives reports the astonishing conclusion of 70% of them that their entire business is at risk in that their data quality and management is inadequate to meet the needs of the accelerating era of technology as a transformative force paced by AI.

For the thousands on thousands of tea smallholders – Assam has around 800 plantations and 100,000 small growers – there are issues of worker literacy, hand-written ledgers, and elementary book-keeping. Many of them adapt quickly to data of value to them in their farming: mapping from drones, weather alerts to smartphones, etc. But overall data management has never been a need or a skill.

The biggest problem is that one step back and one forward invariably means back to an outside supplier, grower, broker, shipper, blender, store, and many, many others. That makes the third component of a comprehensive traceability platform so complex: the collaborative ecosystem. This is the “soft” area. It is leveraged by the “hard” fourth and central technology innovation: blockchain. But first, the inter-organizational roles, processes, standards, and relationships must be smoothly coordinated.

Blockchain: traceability as an integrated platform

The combination of ecosystem partners – a community that is registered to share access to selected data – and the blockchain, a secure, comprehensive ledger of every transaction made that involves any of them is the next pivot driver of supply chain innovation and integration. STiR has covered blockchain regularly over the past two years. It is simple to summarize:

It is a secure electronic vault for storing records of transactions between parties. (It began as the technology base for cryptocurrency transactions: Bitcoin.)

Every transaction generates a new record: a block. These are time-stamped and cleverly tagged with the results of a simple math calculation that is dependent on previous blocks. Any effort to tamper with the block will show up in this chain’s string of records. The blockchain maintains copies of its up-to-date vault contents that are “distributed” to every computer in the network, which is like a mini-internet and can be private or public. There’s no central safe to crack.

Every transaction leaves a record. The records are linked through the hashtagging and tamperproof (There are, of course, many digital malefactors aiming to change that). The chain of transactions is a chain of events: “Then this update was made as an order… then the order was revised… then the shipment order was issued… then the bank checked the credit status...”

This, of course, adds up to automatic traceability, but with any number of steps back and any steps forward. The impact of blockchain here is illustrated by Walmart’s report that the average time to track and locate a missing package has been cut from a week to just a few seconds.

Blockchain Initiatives for Tea Traceability

Most commentators expected blockchain to move faster than it has; that reflects the soft issues of collaboration, standardization, governance of membership, and authorization to access other parties’ data and transactions, and coordination of the technology platform.

It is moving faster now with a strong base of technology providers and an expanding range of implementations. Initiatives in tea include:

The Unilever-led Trado pilot blockchain links any of Malawi’s 10,000 tea farmers, Sainsbury, the UK supermarket firm, three large financial institutions, and technology services. Paribas bank reported in late October 2019 that one major impact of the blockchain “trust machine” is earlier payments to small growers, reducing their reliance on expensive local loans; the bank has the traceability about the growing and harvesting, quality of leaf, shipments to factories or brokers, and so on.

The Tea Board of India’s call for technology vendors to develop a blockchain traceability system for higher quality orthodox teas and blends to help increase margins and reduce supply chain costs. Amazon’s cloud service unit and the giant Indian Infosys has publicly expressed an interest in the contract opportunity.

The Yunnan Pu’er Tea Traceability Platform as a collaboration between VEChain, the emerging dominant Chinese blockchain provider well positioned for global leadership, the Lincang City government leading pu’er producers, and the Yunnan Tea Traceability Association. The pu’er market is noted for high prices and frequent misrepresentation and counterfeiting. QR barcodes and NFC chips are highlighted as core to the use of the blockchain platform.

CCIC (China Certification and Inspection) winning the bid for a blockchain traceability service for a high-end China specialty tea, Liubao. The service includes aiding “standardization, marketization, industrialization, and branding.”

The basic formula for traceability is now clear: smartphone + QR + blockchain + collaborative network.