Shaikh Jewan

Shaikh Jewan

Higher Degree by Research Candidate

School of Agriculture, Food and Wine

Faculty of Sciences, Engineering and Technology

I am Yassir, a researcher specializing in Agricultural Remote Sensing, currently part of a unique doctoral training partnership between the University of Nottingham and The University of Adelaide. This collaborative program allows me to split my research time between these two esteemed institutions, providing a broad and diverse academic experience.

My research expertise lies in the application of remote sensing technology and machine learning techniques to agriculture, with a particular focus on broadacre and horticultural crops. My work primarily revolves around monitoring crop growth and development, and predicting crop yield and quality. I have a special interest in groundnut and grapevine crops, and my research spans across various geographical locations including Malaysia, Australia, and the United Kingdom.

The foundation of my interest in remote sensing and geospatial analysis was laid during my undergraduate studies at the University of Mauritius. There, I conducted significant research on mangrove forest mapping using geospatial techniques. This early exploration into the intersection of environmental monitoring and sustainable management has profoundly shaped my approach to research and continues to inform my objectives.

As an emerging leader in agricultural remote sensing, my commitment extends beyond academic research. I am dedicated to bridging the gap between advanced technological research and its practical application in agriculture. My work not only contributes to the scientific community but also has a tangible impact on farming practices, aiding in the development of more efficient and sustainable agricultural systems globally.

Experienced in research with 120 hours of training from the University of Adelaide and 60 hours from the University of Nottingham. Proficient in Python, R, and MATLAB. Skilled in data analysis, machine learning, deep learning, geospatial analysis with ArcGIS and QGIS, and image processing using ERDAS, ENVI, Agisoft, Pix4D, and Photogrammetry. Licensed for UAV operation.

Remote and proximal sensing technology for crop yield prediction

  • Journals
    Year Citation
    2024 Jewan, S. Y. Y., Singh, A., Billa, L., Sparkes, D., Murchie, E., Gautam, D., . . . Pagay, V. (2024). Can Multi-Temporal Vegetation Indices and Machine Learning Algorithms Be Used for Estimation of Groundnut Canopy State Variables?. Horticulturae, 10(7), 748.
    DOI
    2022 Jewan, S. Y. Y., Pagay, V., Billa, L., Tyerman, S. D., Gautam, D., Sparkes, D., . . . Singh, A. (2022). The feasibility of using a low-cost near-infrared, sensitive, consumer-grade digital camera mounted on a commercial UAV to assess Bambara groundnut yield. International Journal of Remote Sensing, 43(2), 393-423.
    DOI Scopus14 WoS7
    2022 Cogato, A., Jewan, S. Y. Y., Wu, L., Marinello, F., Meggio, F., Sivilotti, P., . . . Pagay, V. (2022). Water Stress Impacts on Grapevines (Vitis vinifera L.) in Hot Environments: Physiological and Spectral Responses. AGRONOMY-BASEL, 12(8), 19 pages.
    DOI Scopus8 WoS3
    2021 Cogato, A., Wu, L., Jewan, S. Y. Y., Meggio, F., Marinello, F., Sozzi, M., & Pagay, V. (2021). Evaluating the Spectral and Physiological Responses of Grapevines (Vitis vinifera L.) to Heat and Water Stresses under Different Vineyard Cooling and Irrigation Strategies. Agronomy, 11(10), 1-20.
    DOI Scopus21 WoS18

  • Conference Papers
    Year Citation
    2024 Jewan, S. Y. Y., Billa, L., Sparkes, D., Murchie, E., Pagay, V., Gautam, D., . . . Singh, A. (2024). Monitoring Bambara Groundnut Canopy State Variables at Various Growth Stages Using Low-Cost Remote Sensing Technology and Machine Learning Techniques. In Advances in Science and Technology Vol. 144 (pp. 63-69). Trans Tech Publications Ltd.
    DOI
    2023 Jewan, S. Y. Y., Billa, L., Sparkes, D., Pagay, V., Gautam, D., Tyerman, S. D., & Singh, A. (2023). Monitoring Growth and Development of Bambara Groundnut Using a Low-Cost Unmanned Aerial Vehicle. In International Geoscience and Remote Sensing Symposium (IGARSS) Vol. 2023-July (pp. 3245-3248). Online: IEEE.
    DOI
    2022 Cogato, A., Sozzi, M., Meggio, F., Marinello, F., Jewan, S. Y. Y., & Pagay, V. (2022). Evaluation of the physiological and spectral responses of grapevines (Vitis vinifera L.) under different durations of drought stress under high temperature conditions. In 2022 IEEE Workshop on Metrology for Agriculture and Forestry, MetroAgriFor 2022 - Proceedings Vol. 56 (pp. 368-372). Perugia, Italy: IEEE.
    DOI

  • Datasets
    Year Citation
    2022 Jewan, S. (2022). dataset.

  • Memberships
    Date Role Membership Country
    2024 - ongoing Member Australian Society of Viticulture and Oenology Australia
    2022 - ongoing Member IEEE Geoscience and Remote Sensing Society United States

  • Review, Assessment, Editorial and Advice
    Date Title Type Institution Country
    2024 - ongoing Information Processing in Agriculture (Elsevier) Journal Review Information Processing in Agriculture (Elsevier) -
    2024 - ongoing Computers and Electronics in Agriculture (Elsevier) Journal Review Computers and Electronics in Agriculture (Elsevier) -
    2021 - ongoing Agriculture Water Management (Elsevier) Journal Review Agriculture Water Management (Elsevier) -
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