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Distributed ledger technology applied to Big Data in agriculture presents challenges and opportunities. Opportunities exist to solve decades‐old farm data management problems. Real‐world examples of applying distributed ledger technology to current farm data problems in cotton include (1) yield monitor data quality assurance, (2) sustainability metrics and resource tracking of cotton lint quality data from ginner back to subfield locations, and (3) increasing supply chain coordination by providing more information to warehouse managers. The culmination of the discussion across three aspects of cotton production data is of interest to farmers, researchers, policy makers, and consumers.
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Griffin et al. (2021) studied this question.
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