Trusted Data: What is It and Why is It Important to the Agriculture Supply Chain?
What is Trusted Data?
- Reliable and Accurate: Data should represent an actual event or situation without being misleading. For example, if a certain quantity of crops was sprayed with a particular pesticide, the recorded data should accurately reflect the same quantity and pesticide type.
- Authenticated: The sources of data should be verifiable. This is particularly significant in scenarios where data is used to validate the origin of agricultural products or verify claims about organic, non-GMO, or other specialty farming practices.
- Timely: Data should be captured and made available in real-time or near real-time, especially when decisions based on this data impact the freshness, quality, or safety of agricultural products.
- Consistent: Regardless of where or when the data is captured in the supply chain, there should be a standard method or format in which it’s recorded.
- Secure: Given the sensitivity of some agricultural data (like proprietary farming practices or trade secrets), it’s important to ensure that data is stored securely, with access limited to authorized personnel.
- Comprehensive: For a clear picture of the supply chain, the data captured should be holistic, covering all relevant facets from soil health, water usage, and inputs (like fertilizers and pesticides) to post-harvest handling, transportation, and even retail shelving.
Why is Trusted Data Important?
- Traceability: As consumers become more health-conscious and interested in the origin of their food, there’s a growing demand for complete traceability in the food supply chain. Trusted data helps map a product’s journey from the farm to the consumer’s plate.
- Safety and Quality Assurance: Reliable data can help quickly identify sources of contamination or quality issues, enabling faster responses in case of recalls.
- Sustainability and Environmental Practices: As there’s a global push towards sustainable farming practices, trusted data can help validate claims about water conservation, carbon footprints, or other eco-friendly practices.
- Operational Efficiency: With accurate and timely data, stakeholders can make informed decisions, optimize resource allocation, and reduce wastage.
- Market Access and Premium Pricing: Producers who can verify their claims about organic, non-GMO, or other premium farming practices can access niche markets and potentially command higher prices.
To ensure the trustworthiness of data, various technologies like artificial intelligence, blockchain, IoT, and advanced analytics are being used to capture, verify, and share data across the agriculture supply chain.
Real-Time Whole Chain Tracing
Risk is unmanageable without visibility. dFarm’s Precision Trace utilizes dFarm’s deep data collection technologies to provide tracing back to the specific sources at the farm and lot level, and tracing forward to all recipients.