Empowering Cover Crop Decision Support with Visualization and Provenance Enhancement

Sujan Shrestha, Jianxin Sun, Katja Koehler-Cole, Andrea Basche, Hongfeng Yu

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Cover crops offer a range of agricultural and environmental benefits, such as reducing soil erosion, increasing carbon and enhancing water storage, increasing forage production, protecting soil nutrients, and so on. However, adoption of cover crop farming remains limited among Nebraska's farmers. To promote awareness of the value of cover crop farming, we harness modern tools and technology and develop a new web-based tool capable of quantifying potential forage production, forage quality, and environmental benefits when planting cover crops, taking into account factors like climate, soil types, and seeding periods. Our tool incorporates the concept of data provenance to capture simulation configurations and results. This implementation can enhance data integrity and facilitate knowledge sharing within the scientific community, supporting further research and broader public benefits. The tool also includes reporting functions with visualizations illustrating distributions of potential forage, transpiration, nitrogen uptake, and more. Based on factors such as cover crop types, planting and termination dates, locations, and soil types, our tool provides valuable insights, enabling farmers to experiment with different cover crops on their land, ultimately leading to improved environmental outcomes for the broader Nebraska community.

Original languageEnglish (US)
Title of host publicationProceedings - 2023 IEEE International Conference on Big Data, BigData 2023
EditorsJingrui He, Themis Palpanas, Xiaohua Hu, Alfredo Cuzzocrea, Dejing Dou, Dominik Slezak, Wei Wang, Aleksandra Gruca, Jerry Chun-Wei Lin, Rakesh Agrawal
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages4548-4556
Number of pages9
ISBN (Electronic)9798350324457
DOIs
StatePublished - 2023
Event2023 IEEE International Conference on Big Data, BigData 2023 - Sorrento, Italy
Duration: Dec 15 2023Dec 18 2023

Publication series

NameProceedings - 2023 IEEE International Conference on Big Data, BigData 2023

Conference

Conference2023 IEEE International Conference on Big Data, BigData 2023
Country/TerritoryItaly
CitySorrento
Period12/15/2312/18/23

Keywords

  • cover crops
  • environment
  • provenance
  • simulation
  • visualization

ASJC Scopus subject areas

  • Artificial Intelligence
  • Computer Networks and Communications
  • Computer Science Applications
  • Information Systems
  • Information Systems and Management
  • Safety, Risk, Reliability and Quality

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