Publications

Publications

Book chapters

  • Bheemanahalli, R., Krishnan, B. S., Wijewardane, N. K., Samiappan, S., & Reddy, K. R. (2023). Remote Sensing Algorithms and Their Applications in Plant Phenotyping. In M. Harohalli Masthigowda, K. Gopalareddy, R. Khobra, G. Singh, & G. Pratap Singh (Eds.), Translating Physiological Tools to Augment Crop Breeding (pp. 337–353). Springer Nature Singapore. https://doi.org/10.1007/978-981-19-7498-4_15

  • Ge, Y., Morgan, C. L. S., & Wijewardane, N. K. (2019). Visible and Near-Infrared Reflectance Spectroscopy Analysis of Soils. Methods of Soil Analysis, 4. https://doi.org/10.2136/msa2017.0040

Journal Articles

  • Gamagedara, Y., Wijewardane, N. K., Feng, G., Seybold, C., Williams, M., Tagert, M. L., & Martins, V. S. (2024). Can we use a mid-infrared fine-ground soil spectral library to predict non-fine-ground spectra?. Geoderma, 443, 116799.

  • Poudel, S., Vennam, R. R., V. Sankarapillai, L., Liu, J., Reddy, K. R., Wijewardane, N. K., ... & Bheemanahalli, R. (2024). Negative Synergistic Effects of Drought and Heat During Flowering and Seed Setting in Soybean. bioRxiv, 2024-01.

  • Nepal, D., Parajuli, P. B., Ouyang, Y., To, S. D. F., & Wijewardane, N. (2023). Assessing hydrological and water quality responses to dynamic landuse change at watershed scale in Mississippi. Journal of Hydrology, 625(PA), 129983. https://doi.org/10.1016/j.jhydrol.2023.129983

  • Silva, F. H. C. A., Wijewardane, N. K., Bheemanahalli, R., Raja Reddy, K., Zhang, X., & Vennam, R. R. (2023). Comparison of UV, visible and near-infrared, and mid-infrared spectrometers to estimate maize and sorghum leaf nutrients using dry-intact and ground leaves. Computers and Electronics in Agriculture, 211, 108001. https://doi.org/https://doi.org/10.1016/j.compag.2023.108001

  • Thayananthan, T., Zhang, X., Liu, W., Yao, T., Huang, Y., Wijewardane, N. K., & Lu, Y. (2023). Automating catfish cutting process using deep learning-based semantic segmentation. In M. S. Kim & B.-K. Cho (Eds.), Sensing for Agriculture and Food Quality and Safety XV (Vol. 12545, p. 18). SPIE. https://doi.org/10.1117/12.2663370

  • Wijewardane, N. K., Zhang, H., Yang, J., Schnable, J. C., Schachtman, D. P., & Ge, Y. (2023). A leaf-level spectral library to support high-throughput plant phenotyping: predictive accuracy and model transfer. Journal of Experimental Botany, 74(14), 4050–4062. https://doi.org/10.1093/jxb/erad129

  • Whatley, C. R., Wijewardane, N. K., Bheemanahalli, R., Reddy, K. R., & Lu, Y. (2023). Effects of fine grinding on mid-infrared spectroscopic analysis of plant leaf nutrient content. Scientific Reports, 13(1), 6314. https://doi.org/10.1038/s41598-023-33558-5

  • Li, J., Wijewardane, N. K., Ge, Y., & Shi, Y. (2023). Improved chlorophyll and water content estimations at leaf level with a hybrid radiative transfer and machine learning model. Computers and Electronics in Agriculture, 206, 107669. https://doi.org/https://doi.org/10.1016/j.compag.2023.107669

  • Poudel, S., Vennam, R. R., Shrestha, A., Reddy, K. R., Wijewardane, N. K., Reddy, K. N., & Bheemanahalli, R. (2023). Resilience of soybean cultivars to drought stress during flowering and early-seed setting stages. Scientific Reports, 13(1), 1277. https://doi.org/10.1038/s41598-023-28354-0

  • Murad, M. O. F., Jones, E. J., Minasny, B., McBratney, A. B., Wijewardane, N., & Ge, Y. (2022). Assessing a VisNIR penetrometer system for in-situ estimation of soil organic carbon under variable soil moisture conditions. Biosystems Engineering, 224, 197–212. https://doi.org/10.1016/j.biosystemseng.2022.10.011

  • Bheemanahalli, R., Ramamoorthy, P., Poudel, S., Samiappan, S., Wijewardane, N., & Reddy, K. R. (2022). Effects of drought and heat stresses during reproductive stage on pollen germination, yield, and leaf reflectance properties in maize (Zea mays L). Plant Direct, 6(8), e434. https://doi.org/10.1002/pld3.434

  • Grzybowski, M. W., Zwiener, M., Jin, H., Wijewardane, N. K., Atefi, A., Naldrett, M. J., Alvarez, S., Ge, Y., & Schnable, J. C. (2022). Variation in morpho-physiological and metabolic responses to low nitrogen stress across the sorghum association panel. BioRxiv, 2022.06.08.495271. https://doi.org/10.1101/2022.06.08.495271

  • Zhang, H., Ge, Y., Xie, X., Atefi, A., Wijewardane, N. K., & Thapa, S. (2022). High throughput analysis of leaf chlorophyll content in sorghum using RGB, hyperspectral, and fluorescence imaging and sensor fusion. Plant Methods, 18(1), 60. https://doi.org/10.1186/s13007-022-00892-0

  • Lu, Y., Young, S., Wang, H., & Wijewardane, N. (2022). Robust plant segmentation of color images based on image contrast optimization. Computers and Electronics in Agriculture, 193, 106711. https://doi.org/10.1016/j.compag.2022.106711

  • Grzybowski, M., Wijewardane, N. K., Atefi, A., Ge, Y., & Schnable, J. C. (2021). Hyperspectral reflectance-based phenotyping for quantitative genetics in crops: Progress and challenges. Plant Communications, 2(4), 100209. https://doi.org/10.1016/j.xplc.2021.100209

  • Wijewardane, N. K., Ge, Y., Sanderman, J., & Ferguson, R. (2021). Fine grinding is needed to maintain the high accuracy of mid‐infrared diffuse reflectance spectroscopy for soil property estimation. Soil Science Society of America Journal, 85(2), 263–272. https://doi.org/10.1002/saj2.20194

  • Liu, Z., Rady, A., Wijewardane, N. K., Shan, Q., Chen, H., Yang, S., Li, J., & Li, M. (2021). Fourier-transform infrared spectroscopy and machine learning to predict fatty acid content of nine commercial insects. Journal of Food Measurement and Characterization, 15(1), 953–960. https://doi.org/10.1007/s11694-020-00694-9

  • Wijewardane, N. K., Ge, Y., Sihota, N., Hoelen, T., Miao, T., & Weindorf, D. C. (2020). Predicting total petroleum hydrocarbons in field soils with Vis–NIR models developed on laboratory‐constructed samples. Journal of Environmental Quality, 49(4), 847–857. https://doi.org/10.1002/jeq2.20102

  • Wijewardane, N. K., Hetrick, S., Ackerson, J., Morgan, C. L. S., & Ge, Y. (2020). VisNIR integrated multi-sensing penetrometer for in situ high-resolution vertical soil sensing. Soil and Tillage Research, 199, 104604. https://doi.org/10.1016/j.still.2020.104604

  • Li, M., Wijewardane, N. K., Ge, Y., Xu, Z., & Wilkins, M. R. (2020). Visible/near infrared spectroscopy and machine learning for predicting polyhydroxybutyrate production cultured on alkaline pretreated liquor from corn stover. Bioresource Technology Reports, 9, 100386. https://doi.org/10.1016/j.biteb.2020.100386

  • Yuan, W., Wijewardane, N. K., Jenkins, S., Bai, G., Ge, Y., & Graef, G. L. (2019). Early Prediction of Soybean Traits through Color and Texture Features of Canopy RGB Imagery. Scientific Reports, 9(1), 14089. https://doi.org/10.1038/s41598-019-50480-x

  • Wijewardane, N. K., Ge, Y., Wills, S., & Libohova, Z. (2018). Predicting Physical and Chemical Properties of US Soils with a Mid-Infrared Reflectance Spectral Library. Soil Science Society of America Journal, 82(3), 722–731. https://doi.org/10.2136/sssaj2017.10.0361

  • Wijewardane, N. K., Ge, Y., & Morgan, C. L. S. (2016). Moisture insensitive prediction of soil properties from VNIR reflectance spectra based on external parameter orthogonalization. Geoderma, 267, 92–101. https://doi.org/10.1016/j.geoderma.2015.12.014

  • Wijewardane, N. K., Ge, Y., Wills, S., & Loecke, T. (2016). Prediction of Soil Carbon in the Conterminous United States: Visible and Near Infrared Reflectance Spectroscopy Analysis of the Rapid Carbon Assessment Project. Soil Science Society of America Journal, 80(4), 973–982. https://doi.org/10.2136/sssaj2016.02.0052

  • Wijewardane, N. K., Ge, Y., & Morgan, C. L. S. (2016). Prediction of soil organic and inorganic carbon at different moisture contents with dry ground VNIR: a comparative study of different approaches. European Journal of Soil Science, 67(5), 605–615. https://doi.org/10.1111/ejss.12362