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Abhilash Chandel

Assistant Professor
  • Research: Precision agriculture
Abhilash Chandel, Virginia Tech Biological Systems Engineering Faculty
Tidewater AREC
abhilashchandel@vt.edu

Education

Ph.D., Washington State University, Pullman, WA, Biological and Agricultural Engineering (2021)

M.Tech., Indian Institute of Technology, Karagpur, India, Farm Machinery and Power Engineering (2015)

B.Tech., Indian Institute of Technology, Karagpur, India, Agricultural and Food Engineering (2015)

Experience

Assistant Professor of Precision Agriculture Technologies and Data Management, Biological Systems Engineering (50% research, 50% extension), Virginia Tech (Dec 2021-present)

Post-doctoral Research Associate, Washington State University, WA, USA (May 2021-Dec 2021)

Graduate Research Assistant, Washington State University, WA, USA (August 2017-May 2021)

Junior Project Officer, Indian Institute of Technology, Kharagpur, India (July 2015–February 2017)

Awards

  • Finalist, WSU plant science and Corteva symposium, 2021
  • Graduate Student Leadership Award 2021, CAHNRS, WSU
  • Walter and Vinnie Hinz Outstanding Graduate Student Award 2020, BSE, WSU
  • ASABE-2021 Agricultural Equipment Technology Conference Sponsorship
  • Winner: Digital Ag-Athon 2020, jointly organized by Microsoft and WSU
  • Biological Systems Engineering Department Virtual Conference Award 2020
  • Water Smart Innovation Conference and Exposition Graduate Student Scholarship 2019
  • Alaska Airlines Travel Award 2019
  • Biological Systems Engineering Department Travel Award 2019
  • Merit-cum-Means (MCM) undergraduate scholarship 2010-2014
  • Rajwade, Y.A., Chandel, N.S., Chandel, A.K.C, Singh, S.K., Dubey, K., Subeesh, A., Chaudhary, V.P., Ramanna Rao, K.V. and Manjhi, M., 2024. Thermal–RGB Imagery and Computer Vision for Water Stress Identification of Okra (Abelmoschus esculentus L.). Applied Sciences, 14(13), p.5623. https://doi.org/10.3390/app14135623  
  • Jjagwe, P.G, Chandel, A.K.C and Langston, D.B., 2024. Impact Assessment of Nematode Infestation on Soybean Crop Production Using Aerial Multispectral Imagery and Machine Learning. Applied Sciences, 14(13), p.5482. https://doi.org/10.3390/app14135482  
  • Chandel, N.S., Chakraborty, S.K., Chandel, A.K.C, Dubey, K., Subeesh, A., Jat, D. and Rajwade, Y.A., 2024. State-of-the-art ai-enabled mobile device for real-time water stress detection of field crops. Engineering Applications of Artificial Intelligence, 131, p.107863. https://doi.org/10.1016/j.engappai.2024.107863  
  • Chapu, I., Chandel, A.K., Sie, E.K., Okello, D.K., Oteng-Frimpong, R., Okello, R.C.O., Hoisington, D. and Balota, M., 2024. Comparing Regression and Classification Models to Estimate Leaf Spot Disease in Peanut (Arachis hypogaea L.) for Implementation in Breeding Selection. Agronomy, 14(5), p.947. https://doi.org/10.3390/agronomy14050947  
  • Ranjan, R., Amogi, B.R., Chandel, A.K., Khot, L.R., Sallato, B.V. and Peters, R.T., 2024. Efficacy evaluation of apple sunburn mitigation techniques in WA 38 cultivar using crop physiology sensing system. Computers and Electronics in Agriculture, 216, p.108501. https://doi.org/10.1016/j.compag.2023.108501  
  • Jjagwe, P.G, Chandel, A.K.C and Langston, D., 2023. Pre-Harvest Corn Grain Moisture Estimation Using Aerial Multispectral Imagery and Machine Learning Techniques. Land, 12(12), p.2188. https://doi.org/10.3390/land12122188  
  • Kumar, S.P., Tewari, V.K., Chandel, A.K.C, Mehta, C.R., Pareek, C.M., Chethan, C.R. and Nare, B., 2023. Modelling specific energy requirement for a power-operated vertical axis rotor type intra-row weeding tool using Artificial Neural Network. Applied Sciences, 13(18), p.10084. https://doi.org/10.3390/app131810084  
  • Molaei, B., Peters, R.T., Chandel, A.K., Khot, L.R., Stockle, C.O. and Campbell, C.S., 2023. Measuring Evapotranspiration Suppression from the Wind Drift and Spray Water Losses for LESA and MESA Sprinklers in a Center Pivot Irrigation System. Water, 15(13), p.2444. https://doi.org/10.3390/w15132444  
  • Molaei, B., Chandel, A.K., Peters, R.T., Khot, L.R., Khan, A., Maureira, F. and Stockle, C., 2023. Investigating the application of artificial hot and cold reference surfaces for improved ETc estimation using the UAS-METRIC energy balance model. Agricultural Water Management, 284, p.108346. https://doi.org/10.1016/j.agwat.2023.108346  
  • Hota, S., Tewari, V.K., Dhruw, L.K. and Chandel, A.K., 2023. A sensor‐based assistive technology for lower‐limb‐disabled agricultural workers and abled female workers for tractor clutch and brake operation. Journal of Field Robotics. 1–18. https://doi.org/10.1002/rob.22214  
  • Modi, R.U., Chandel, A.K.C, Chandel, N.S., Dubey, K., Subeesh, A., Singh, A.K., Jat, D. and Kancheti, M., 2023. State-of-the-art computer vision techniques for automated sugarcane lodging classification. Field Crops Research, 291, p.108797. https://doi.org/10.1016/j.fcr.2022.108797  
  • Hota, S., Tewari, V.K. and Chandel, A.K.C, 2023. Workload assessment of agricultural tractor operations with ergonomic transducers and machine learning techniques. Sensors, 23(3), p.1408. https://doi.org/10.3390/s23031408
  • Becker, S., Bierman, D., Bucksch, A., Calvert, S., Caprez, A., Chandel, A.K., Craker, B., Dorius, S.F., Elsik, C., Clarke, J., Evans, J., 2023. The NAPDC: Stakeholder Input and Strategic Directions (No. tkg96). Center for Open Science. https://doi.org/10.31219/osf.io/tkg96 
  • Chandel, A.K.C, Moyer, M.M., Keller, M., Khot, L.R. and Hoheisel, G.A., 2022. Soil and Climate Geographic Information System Data-Derived Risk Mapping for Grape Phylloxera in Washington State. Frontiers in Plant Science, 13, pp.827393-827393. https://doi.org/10.3389/fpls.2022.827393  
  • Chandel, N.S., Rajwade, Y.A., Dubey, K., Chandel, A.K.C, Subeesh, A. and Tiwari, M.K., 2022. Water Stress Identification of Winter Wheat Crop with State-of-the-Art AI Techniques and High-Resolution Thermal-RGB Imagery. Plants, 11(23), p.3344. https://doi.org/10.3390/plants11233344

Extension Publications

  • Chandel, A.K., Jjagwe, P., Langston, D., 2024. Drone imaging to evaluate impact of Nematodes on Soybean Yield. VCE Publications, BSE-362. 
  • Raman, R., Balota M., Chandel, A.K., Jjagwe, P., 2024. Faba Bean: A Multipurpose Specialty Crop for the Mid-Atlantic USA. VCE Publications, SPES-590NP.
  • Balota M., Chandel, A.K., 2024. Prohexadione Calcium or seed aging? VCE Publications, SPES-581NP. 
  • Aljawasim, B., Richardson, P., Samtani, J., Chandel, A.K., 2024. Researchers see promise in multi-spectral imaging for latent detection of anthracnose disease on strawberry crop. Virginia Strawberry Association news, 9(1), pp.12-13. 
  • Aljawasim, B., Richardson, P., Samtani, J., Chandel, A.K., 2024. Detection of anthracnose disease in strawberries. Southern Region Small Fruit Consortium. https://smallfruits.org/2024/01/detection-of-anthracnose-disease-in-strawberries/  
  • Chandel, A.K., Balota M., Jjagwe, P., Chappell, M., 2024. Pod maturity assessments for Virginia type peanuts: 2023 season results. Virginia-Carolinas peanut news. 72(1), p.14. https://www.aboutpeanuts.com/peanut-newsletter/166-2024-winter-peanut-news-vol-72-no-1
  • Becker, S., Bierman, D., Bucksch, A., Calvert, S., Caprez, A., Chandel, A.K., Craker, B., Dorius, S.F., Elsik, C., Clarke, J., Evans, J., 2023. The NAPDC: Stakeholder Input and Strategic Directions (No. tkg96). Center for Open Science. https://doi.org/10.31219/osf.io/tkg96  
  • Chandel, A.K., Langston, D., 2023. Aerial multispectral imagery for high-throughput mapping of spatial corn yield potentials. VCE Publications, SPES-526NP.
  • Chandel, A.K., Langston, D., 2023. Aerial multispectral imagery for high-throughput mapping of spatial soybean yield potentials. VCE Publications, SPES-527NP. 
  • Chandel A.K., 2023. Aerial imagery to improve disease diagnosis and management in field crops. VCE Publications, SPES-515NP.
  • Chandel, A.K., Amogi, B., Khot, L.R, Stöckle, C.O., Peters, R.T., 2022. Digitizing Crop Water Use with Data-Driven Approaches. ASABE Resource, July/Aug 2022, 269, 14–16. 
  • Chandel, A.K., Khot, L.R., Kilham, N., Kalcsits, L., Mantle, S., Peters, R.T., Stöckle, C.O., 2022. Multi-scale remote sensing data driven apple crop water use mapping. Washington State University – Fruit Matters, June 2022.