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

Kanwalpreet Kour, Deepali Gupta, Junaid Rashid (), Kamali Gupta, Jungeun Kim (), Keejun Han and Khalid Mohiuddin
Additional contact information
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

Agriculture, 2023, vol. 13, issue 4, 1-21

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.

Keywords: IoT; saffron; artificial cultivation; hydroponics; saffron adulteration; saffron quality; AquaCrop (search for similar items in EconPapers)
JEL-codes: Q1 Q10 Q11 Q12 Q13 Q14 Q15 Q16 Q17 Q18 (search for similar items in EconPapers)
Date: 2023
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

Downloads: (external link)
https://www.mdpi.com/2077-0472/13/4/776/pdf (application/pdf)
https://www.mdpi.com/2077-0472/13/4/776/ (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:gam:jagris:v:13:y:2023:i:4:p:776-:d:1108830

Access Statistics for this article

Agriculture is currently edited by Ms. Leda Xuan

More articles in Agriculture from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().