Quality Evaluation of an Apple using Non- Invasive Microwave Technique
Keywords:
Dielectric constant, quality of fruit, rectangular patch antenna, non-invasive microwave techniqueAbstract
Fruit nutrition is the necessary part of human diet; hence determination of its quality has importance. The analysis of fruit quality is also a critical task in the commercial market. The non-invasive method is the most referred technique for quality evaluation. In this paper, the microwave technique is proposed and discussed. Both transmitter and receiver antennas are designed for a 2.45 GHz ISM band. In this paper, a microwave system is proposed to determine the different conditions of an apple, so that the rejection of the internally rotten apple is possible.
Downloads
References
Nelson, Stuart O. "Measuring dielectric properties of fresh fruits and vegetables." Antennas and Propagation Society International Symposium, IEEE, Vol. 4., 2003.
Nelson, Stuart O. "Dielectric spectroscopy studies on fresh fruits and vegetables." Antennas and Propagation Society International Symposium, IEEE. Vol. 4, 2005.
Nelson, Stuart O., Wenchuan Guo, and Samir Trabelsi. "Study of fruit permittivity measurements for quality detection." Instrumentation and Measurement Technology Conference Proceedings, IMTC 2008, IEEE, 2008.
Nelson, Stuart O. "Dielectric spectroscopy of fresh fruits and vegetables." Instrumentation and Measurement Technology Conference, IMTC 2005. Proceedings of the IEEE. Vol. 1. 2005.
Balanis, Constantine A. Antenna theory: analysis and design. John Wiley & Sons, 2016, pp 811-826.
Majumder, Alak. "Rectangular microstrip patch antenna using coaxial probe feeding technique to operate in S-band." International Journal of Engineering Trends and Technology (IJETT) 4.4 (2013).
Sreemathy, R., et al. "Design, Analysis and Fabrication of Dual Frequency Distinct Bandwidth Slot Loaded Wash Cotton Flexible Textile Antenna for ISM Band Applications." Prog. Electromagn. Res. M 109 (2022): 191-203.
Nelson, Stuart O. "RF and microwave energy for potential agricultural applications." Journal of Microwave Power, 20.2 (1985): 65-70.
Guo, Wenchuan, et al., “Maturity effects on dielectric properties of apples from 10 to 4500 MHz,” LWT-Food Science and Technology, vol. 44, No.1, pp. 224-230, 2011.
Gaikwad, Sandeep Vinayak, and Arun N. Gaikwad. "RF and Microwave Low Power Dielectric Heating Using Parallel Plate Applicator to Control Insect Pests on Tomato Plant." Progress In Electromagnetics Research M 49 (2016): 81-89.
Ghanem, T. H., “Dielectric properties of liquid foods affected by moisture contents and temperatures,” Misr Journal of Agricultural and Engineering, vol. 27(2), pp. 688-698, 2010.
Koledintseva, Marina, et al. "Engineering of ferrite-graphite composite media for microwave shields." (2006): 598.Mane, P. B. et al. (2017). Watermarking and cryptography based image authentication on reconfigurable platform. Bulletin of Electrical Engineering and Informatics, 6(2), 181-187.
Mandwale, A. J. et al. (2015, January). Different Approaches For Implementation of Viterbi decoder on reconfigurable platform. In 2015 International Conference on Pervasive Computing (ICPC) (pp. 1-4). IEEE.
Mane, P. B., & Mulani, A. O. (2018). High speed area efficient FPGA implementation of AES algorithm. International Journal of Reconfigurable and Embedded Systems, 7(3), 157-165.
Kashid, M. M et al. (2022, November). IoT-Based Environmental Parameter Monitoring Using Machine Learning Approach. In Proceedings of the International Conference on Cognitive and Intelligent Computing: ICCIC 2021, Volume 1 (pp. 43-51). Singapore: Springer Nature Singapore.
Mr.Rahul S Pol, Prof M. Murugan, 'A Review on Indoor Human Aware Autonomous Mobile Robot Navigation Through a Dynamic Environment', International Conference on Industrial Instrumentation and Control (ICIC 2015), held by Government college of engineeing Pune, ICIC2015, 28th-30th May 2015, pp-987
Dr. Rahul S Pol, Dr. B. Sheela Rani, Prof M. Murugan (2021). Optimal Path Planner for Indoor Mobile Robot Environment. Design Engineering, 8297-8309.
Desai, N. ., & Shukla, P. . (2023). Performance of Deep Learning in Land Use Land Cover Classification of Indian Remote Sensing (IRS) LISS – III Multispectral Data. International Journal on Recent and Innovation Trends in Computing and Communication, 11(3), 128–134. https://doi.org/10.17762/ijritcc.v11i3.6329
Ricci, A., Jankowski, M., Pedersen, A., Sánchez, F., & Oliveira, F. Predicting Engineering Student Success using Machine Learning Algorithms. Kuwait Journal of Machine Learning, 1(2). Retrieved from http://kuwaitjournals.com/index.php/kjml/article/view/118
Kothandaraman, D., Praveena, N., Varadarajkumar, K., Madhav Rao, B., Dhabliya, D., Satla, S., & Abera, W. (2022). Intelligent forecasting of air quality and pollution prediction using machine learning. Adsorption Science and Technology, 2022 doi:10.1155/2022/5086622
Downloads
Published
How to Cite
Issue
Section
License
This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.
All papers should be submitted electronically. All submitted manuscripts must be original work that is not under submission at another journal or under consideration for publication in another form, such as a monograph or chapter of a book. Authors of submitted papers are obligated not to submit their paper for publication elsewhere until an editorial decision is rendered on their submission. Further, authors of accepted papers are prohibited from publishing the results in other publications that appear before the paper is published in the Journal unless they receive approval for doing so from the Editor-In-Chief.
IJISAE open access articles are licensed under a Creative Commons Attribution-ShareAlike 4.0 International License. This license lets the audience to give appropriate credit, provide a link to the license, and indicate if changes were made and if they remix, transform, or build upon the material, they must distribute contributions under the same license as the original.