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Smart Framework for Quality Check and Determination of Adulterants in Saffron Using Sensors and AquaCrop

Author

Listed:
  • Kanwalpreet Kour

    (Chitkara University Institute of Engineering &Technology, Chitkara University, Rajpura 140401, India)

  • Deepali Gupta

    (Chitkara University Institute of Engineering &Technology, Chitkara University, Rajpura 140401, India)

  • Junaid Rashid

    (Department of Data Science, Sejong University, Seoul 05006, Republic of Korea)

  • Kamali Gupta

    (Chitkara University Institute of Engineering &Technology, Chitkara University, Rajpura 140401, India)

  • Jungeun Kim

    (Department of Software and CMPSI, Kongju National University, Cheonan 31080, Republic of Korea)

  • Keejun Han

    (School of Computer Engineering, Hansung University, Seoul 02876, Republic of Korea)

  • Khalid Mohiuddin

    (Department of Management Information Systems, College of Business, King Khalid University, Abha 61471, Saudi Arabia)

Abstract

Saffron is a rare and valuable crop that is only cultivated in specific regions with suitable topographical conditions. To improve saffron cultivation, it is crucial to monitor and precisely control the crop’s agronomic variables over at least one growth cycle to create a fully automated environment. To this end, agronomic variables in the Punjab region of India were analyzed and set points were calculated using third-order polynomial equations through the application of image processing techniques. The relationship between canopy cover, growth percentage, and agronomic variables was also investigated for optimal yield and quality. The addition of adulterants, such as turmeric and artificial colorants, to saffron is a major concern due to the potential for quality compromise and fraud by supply chain vendors. Hence, there is a need for devising an easy, reliable, and user-friendly mechanism to help in the detection of adulterants added to the saffron stigmas. This paper proposes an automated IoT-based saffron cultivation environment using sensors for determining set points of agronomical variables. In addition, a sensor-based chamber has been proposed to provide quality and adulteration checks of saffron and to eliminate product counterfeiting. The AquaCrop simulator was employed to evaluate the proposed framework’s performance. The results of the simulation show improved biomass, yield, and harvest index compared with the existing solutions in precision agriculture. Given the high value and demand for saffron, ensuring its purity and quality is essential to sustain its cultivation and the economic viability of the market.

Suggested Citation

  • Kanwalpreet Kour & Deepali Gupta & Junaid Rashid & Kamali Gupta & Jungeun Kim & Keejun Han & Khalid Mohiuddin, 2023. "Smart Framework for Quality Check and Determination of Adulterants in Saffron Using Sensors and AquaCrop," Agriculture, MDPI, vol. 13(4), pages 1-21, March.
    • Handle: RePEc:gam:jagris:v:13:y:2023:i:4:p:776-:d:1108830
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    References listed on IDEAS

    as
    1. Kanwalpreet Kour & Deepali Gupta & Kamali Gupta & Sapna Juneja & Manjit Kaur & Amal H. Alharbi & Heung-No Lee, 2022. "Controlling Agronomic Variables of Saffron Crop Using IoT for Sustainable Agriculture," Sustainability, MDPI, vol. 14(9), pages 1-16, May.
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    Cited by:

    1. Konstantinos Dolaptsis & Xanthoula Eirini Pantazi & Charalampos Paraskevas & Selçuk Arslan & Yücel Tekin & Bere Benjamin Bantchina & Yahya Ulusoy & Kemal Sulhi Gündoğdu & Muhammad Qaswar & Danyal Bust, 2024. "A Hybrid LSTM Approach for Irrigation Scheduling in Maize Crop," Agriculture, MDPI, vol. 14(2), pages 1-26, January.

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