Frontiers in Sustainability (Dec 2020)

Securing Data in Life Sciences—A Plant Food (Edamame) Systems Case Study

  • Susan E. Duncan,
  • Bo Zhang,
  • Wade Thomason,
  • Margaret Ellis,
  • Na Meng,
  • Michael Stamper,
  • Renata Carneiro,
  • Tiffany Drape

DOI
https://doi.org/10.3389/frsus.2020.600394
Journal volume & issue
Vol. 1

Abstract

Read online

Efforts to identify specialty crop genetics and agronomics, such as for edamame (vegetable soybean), that improve crop yields, resilience, and sustainability often fail to account for data on nutritional content, sensory profile, and/or consumer acceptability. Limited exchange of data across agricultural and food sectors challenges the design of specialty crops that meet consumer needs and expectations and the value chain, and can increase cyberbiosecurity risks. Communication and collaboration within the multi-sector system are essential to address cyberbiosecurity issues related to privacy of data producers, ownership of original data, risks of data sharing, security protection for data transfer and storage, and public perceptions of the food supply chain. This paper introduces a new exploration to design domestic (U.S.) edamame, which is based on both our domain knowledge of life science and our information-sharing mechanisms across the agriculture and food sectors. A case study, involving a multidisciplinary team of breeders and non-breeder researchers with expertise in crop/food production, processing, quality, and economics, serves as a model. We introduce the value chain attributed to combining and linking data from different sectors in the research and development phase, and explain why we believe such data-sharing mechanisms can facilitate better analyses that resonate throughout the full system, from seed to consumer. Our perspective illustrates that, by securely sharing and interpreting data across sectors and identifying cyberbiosecurity risks, we can design promising agricultural and food systems to better meet consumers' need and protection of life science data.

Keywords