A Data Ecosystem for Orchard Research and Early Fruit Traceability

Author:

Williams Stephen Ross1,Agrahari Baniya Arbind1ORCID,Islam Muhammad Sirajul1ORCID,Murphy Kieran1ORCID

Affiliation:

1. AgriBio, Agriculture Victoria Research, Bundoora, VIC 3083, Australia

Abstract

Advances in measurement systems and technologies are being avidly taken up in perennial tree crop research and industry applications. However, there is a lack of a standard model to support streamlined management and integration of the data generated from advanced measurement systems used in tree crop research. Furthermore, the rapid expansion in the diversity and volumes of data is increasingly highlighting the requirement for a comprehensive data model and an ecosystem for efficient orchard management and decision-making. This research focuses on the design and implementation of a novel proof-of-concept data ecosystem that enables improved data storage, management, integration, processing, analysis, and usage. Contemporary technologies proliferating in other sectors but that have had limited adoption in agricultural research have been incorporated into the model. The core of the proposed solution is a service-oriented API-driven system coupled with a standard-based digital orchard model. Applying this solution in Agriculture Victoria’s Tatura tree crop research farm (the Tatura SmartFarm) has significantly reduced overheads in research data management, enhanced analysis, and improved data resolution. This is demonstrated by the preliminary results presented for in-orchard and postharvest data collection applications. The data ecosystem developed as part of this research also establishes a foundation for early fruit traceability across industry and research.

Funder

Department of Energy, Environment and Climate Action

Publisher

MDPI AG

Subject

Horticulture,Plant Science

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