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A Cloud-Based Digital Farm Management System for Vegetable Production Process Management and Quality Traceability

Author

Listed:
  • Feng Yang

    (College of Economics and Management, China Agricultural University, Beijing 100083, China
    Beijing Research Center for Information Technology in Agriculture, Beijing 100097, China)

  • Kaiyi Wang

    (Beijing Research Center for Information Technology in Agriculture, Beijing 100097, China)

  • Yanyun Han

    (Beijing Research Center for Information Technology in Agriculture, Beijing 100097, China)

  • Zhong Qiao

    (College of Economics and Management, China Agricultural University, Beijing 100083, China)

Abstract

Farm Management Information Systems (FMISs) are being expanded to improve operation efficiency, reduce inputs, and ensure compliance with standards and regulations. However, this goal is difficult to attain in the vegetable sector, where data acquisition is time-consuming and data at different stages is fragmented by the potential diversity of crops and multiple batches cultivated at any given farm. This applies, in particular, to farms in China, which have small areas and low degrees of mechanization. This study presents an integrated approach to track and trace production efficiently through our Digital Farm Management System (DFMS), which adopts the cloud framework and utilizes Quick Response (QR) codes and Radio Frequency Identification (RFID) technology. Specifically, a data acquisition system is proposed that runs on a smartphone for the efficient gathering of planting information in the field. Moreover, DFMS generates statistics and analyses of planting areas, costs, and yields. DFMS meets the FMIS requirements and provides the accurate tracking and tracing of the production for each batch in an efficient manner. The system has been applied in a large-scale vegetable production enterprise, consisting of 12 farms distributed throughout China. This application shows that DFMS is a highly efficient solution for precise vegetable farm management.

Suggested Citation

  • Feng Yang & Kaiyi Wang & Yanyun Han & Zhong Qiao, 2018. "A Cloud-Based Digital Farm Management System for Vegetable Production Process Management and Quality Traceability," Sustainability, MDPI, vol. 10(11), pages 1-19, November.
    • Handle: RePEc:gam:jsusta:v:10:y:2018:i:11:p:4007-:d:179980
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    References listed on IDEAS

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    1. Young-woo Kim & Tai-Woo Chang & Jinwoo Park, 2017. "Gen2 RFID-Based System Framework for Resource Circulation in Closed-Loop Supply Chains," Sustainability, MDPI, vol. 9(11), pages 1-17, October.
    2. Danny Pigini & Massimo Conti, 2017. "NFC-Based Traceability in the Food Chain," Sustainability, MDPI, vol. 9(10), pages 1-20, October.
    3. Sarac, Aysegul & Absi, Nabil & Dauzère-Pérès, Stéphane, 2010. "A literature review on the impact of RFID technologies on supply chain management," International Journal of Production Economics, Elsevier, vol. 128(1), pages 77-95, November.
    4. Husemann, Christoph & Novković, Nebojša, 2014. "Farm Management Information Systems: A Case Study On A German Multifunctional Farm," Economics of Agriculture, Institute of Agricultural Economics, vol. 61(2), pages 1-13, June.
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    Cited by:

    1. Pilaiwan Phupattanasilp & Sheau-Ru Tong, 2019. "Augmented Reality in the Integrative Internet of Things (AR-IoT): Application for Precision Farming," Sustainability, MDPI, vol. 11(9), pages 1-17, May.
    2. Yan-yun Han & Kai-yi Wang & Zhong-qiang Liu & Shou-hui Pan & Xiang-yu Zhao & Qi Zhang & Shu-feng Wang, 2020. "Research on Hybrid Crop Breeding Information Management System Based on Combining Ability Analysis," Sustainability, MDPI, vol. 12(12), pages 1-16, June.
    3. Rabhi, Loubna & Jabir, Brahim & Falih, Noureddine & Afraites, Lekbir & Bouikhalene, Belaid, 2023. "A Connected farm Metamodeling Using Advanced Information Technologies for an Agriculture 4.0," AGRIS on-line Papers in Economics and Informatics, Czech University of Life Sciences Prague, Faculty of Economics and Management, vol. 15(2), June.

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