Items where Author is "Tahmasbian, Iman"

Article

Uddin, S., Rohan, M., Weng, Z. H., Tahmasbian, I., Fang, Y., Hayden, H. L., Armstrong, R. and Tavakkoli, E. (2025) Enhancing Root Proliferation in an Alkaline Dispersive Subsoil: a Comparative Study of Organic and Inorganic Amendments with Different Amelioration Mechanisms. Journal of Soil Science and Plant Nutrition . https://doi.org/10.1007/s42729-025-02602-w

Tahmasbian, I., Navas, A. and Dunlop, M. W. (2025) Feature Wavelengths for Quantifying Methane Concentrations Using Shortwave Infrared Hyperspectral Imaging: A Controlled Condition Study. Analytical Chemistry, 97 (8). pp. 4416-4424. https://doi.org/10.1021/acs.analchem.4c05590

Omidvar, N., Xu, Z., Ogbourne, S. M., Ford, R., Sambasivam, P. T., Tran, T. D., Salehin, B., Michael, R. N., Wang, F., Tahmasbian, I., Wilson, R. S. and Bai, S. H. (2025) Long-term glyphosate application and its effects on soil total nitrogen and microbial composition two years after application stopped in biochar-amended soil. Applied Soil Ecology, 213 . p. 106266. https://doi.org/10.1016/j.apsoil.2025.106266

Ma, B., Tahmasbian, I., Guo, T., Zhou, M., Tang, W. and Zhang, M. (2024) Antagonistic Effect of Microplastic Polyvinyl Chloride and Nitrification Inhibitor on Soil Nitrous Oxide Emission: An Overlooked Risk of Microplastic to the Agrochemical Effectiveness. Journal of Agricultural and Food Chemistry, 72 (48). pp. 26654-26663. https://doi.org/10.1021/acs.jafc.4c06528

Guo, T., Wang, F., Tahmasbian, I., Wang, Y., Zhou, T., Pan, X., Zhang, Y., Li, T. and Zhang, M. (2024) Core Soil Microorganisms and Abiotic Properties as Key Mechanisms of Complementary Nanoscale Zerovalent Iron and Nitrification Inhibitors in Decreasing Paclobutrazol Residues and Nitrous Oxide Emissions. Journal of Agricultural and Food Chemistry, 72 (14). pp. 7672-7683. https://doi.org/10.1021/acs.jafc.3c06972

Seididamyeh, M., Tahmasbian, I., Phan, A. D. T. and Sultanbawa, Y. (2024) Geographical origin discrimination of lemon myrtle (Backhousia citriodora) leaf powder using near-infrared hyperspectral imaging. Food Bioscience, 59 . p. 103946. https://doi.org/10.1016/j.fbio.2024.103946

Gama, T., Farrar, M. B., Tootoonchy, M., Wallace, H. M., Trueman, S. J., Tahmasbian, I. and Hosseini Bai, S. (2024) Hyperspectral imaging predicts free fatty acid levels, peroxide values, and linoleic acid and oleic acid concentrations in tree nut kernels. LWT . p. 116068. https://doi.org/10.1016/j.lwt.2024.116068

Farrar, M. B., Omidvar, R., Nichols, J., Pelliccia, D., Lateef Al-Khafaji, S., Tahmasbian, I., Hapuarachchi, N. and Hosseini Bai, S. (2024) Hyperspectral imaging predicts macadamia nut-in-shell and kernel moisture using machine vision and learning tools. Computers and Electronics in Agriculture, 224 . p. 109209. https://doi.org/10.1016/j.compag.2024.109209

Bai, S. H., Tootoonchy, M., Kämper, W., Tahmasbian, I., Farrar, M. B., Boldingh, H., Pereira, T., Jonson, H., Nichols, J., Wallace, H. M. and Trueman, S. J. (2024) Predicting Carbohydrate Concentrations in Avocado and Macadamia Leaves Using Hyperspectral Imaging with Partial Least Squares Regressions and Artificial Neural Networks. Remote Sensing, 16 (18). p. 3389. https://doi.org/10.3390/rs16183389

Tahmasbian, I., McMillan, M. N., Kok, J. and Courtney, A. J. (2024) Underwater hyperspectral imaging technology has potential to differentiate and monitor scallop populations. Reviews in Fish Biology and Fisheries, 34 (1). pp. 371-383. https://doi.org/10.1007/s11160-023-09817-z

Omidvar, N., Ogbourne, S. M., Xu, Z., Burton, J., Ford, R., Salehin, B., Tahmasbian, I., Michael, R., Wilson, R. and Bai, S. H. (2023) Effects of herbicides and mulch on the soil carbon, nitrogen, and microbial composition of two revegetated riparian zones over 3 years. Journal of Soils and Sediments, 23 (7). pp. 2755-2782. https://doi.org/10.1007/s11368-023-03530-x

Dung, C. D., Trueman, S. J., Wallace, H. M., Farrar, M. B., Gama, T., Tahmasbian, I. and Bai, S. H. (2023) Hyperspectral imaging for estimating leaf, flower, and fruit macronutrient concentrations and predicting strawberry yields. Environmental Science and Pollution Research . https://doi.org/10.1007/s11356-023-30344-8

Zhou, T., Wang, F., Tahmasbian, I., Ma, B., Liu, M. and Zhang, M. (2023) Linking Carbendazim Accumulation with Soil and Endophytic Microbial Community Diversities, Compositions, Functions, and Assemblies: Effects of Urea-hydrogen Peroxide and Nitrification Inhibitors. Journal of Agricultural and Food Chemistry, 71 (46). pp. 17689-17699. https://doi.org/10.1021/acs.jafc.3c04777

Farrar, M. B., Wallace, H. M., Tahmasbian, I., Yule, C. M., Dunn, P. K. and Hosseini Bai, S. (2023) Rapid assessment of soil carbon and nutrients following application of organic amendments. CATENA, 223 . p. 106928. https://doi.org/10.1016/j.catena.2023.106928

Phillips, I. R., Paungfoo-Lonhienne, C., Tahmasbian, I., Hunter, B., Smith, B. C., Mayer, D. G. and Redding, M. R. (2022) Combination of Inorganic Nitrogen and Organic Soil Amendment Improves Nitrogen Use Efficiency While Reducing Nitrogen Runoff. Nitrogen, 3 (1). pp. 58-73. https://doi.org/10.3390/nitrogen3010004

Bai, S. H., Omidvar, N., Gallart, M., Kämper, W., Tahmasbian, I., Farrar, M., Singh, K., Zhou, G., Muqadass, B., Xu, C.-Y., Koech, R., Li, Y., Nguyen, T. T. N. and van Zwieten, L. (2022) Combined effects of biochar and fertilizer applications on yield: A review and meta-analysis. Science of The Total Environment, 808 . p. 152073. https://doi.org/10.1016/j.scitotenv.2021.152073

Farrar, M. B., Wallace, H. M., Brooks, P., Yule, C. M., Tahmasbian, I., Dunn, P. K. and Hosseini Bai, S. (2021) A Performance Evaluation of Vis/NIR Hyperspectral Imaging to Predict Curcumin Concentration in Fresh Turmeric Rhizomes. Remote Sensing, 13 (9). p. 1807. https://doi.org/10.3390/rs13091807

Tahmasbian, I., Wallace, H. M., Gama, T. and Bai, S. H. (2021) An automated non-destructive prediction of peroxide value and free fatty acid level in mixed nut samples. LWT, 143 , 110893. https://doi.org/10.1016/j.lwt.2021.110893

Tahmasbian, I., Morgan, N. K., Hosseini Bai, S., Dunlop, M. W. and Moss, A. F. (2021) Comparison of Hyperspectral Imaging and Near-Infrared Spectroscopy to Determine Nitrogen and Carbon Concentrations in Wheat. Remote Sensing, 13 (6). https://doi.org/10.3390/rs13061128

Hemmat-Jou, M. H., Safari-Sinegani, A. A., Che, R., Mirzaie-Asl, A., Tahmourespour, A. and Tahmasbian, I. (2021) Toxic trace element resistance genes and systems identified using the shotgun metagenomics approach in an Iranian mine soil. Environmental Science and Pollution Research, 28 (4). pp. 4845-4856. https://doi.org/10.1007/s11356-020-10824-x

Wang, D., Abdullah, K. M., Tahmasbian, I., Xu, Z. and Wang, W. (2020) Impacts of prescribed burnings on litter production, nitrogen concentration, δ13C and δ15N in a suburban eucalypt natural forest of subtropical Australia. Journal of Soils and Sediments, 20 . pp. 3148-3157. https://doi.org/10.1007/s11368-020-02664-6

Che, R., Liu, D., Qin, J., Wang, F., Wang, W., Xu, Z., Li, L., Hu, J., Tahmasbian, I. and Cui, X. (2020) Increased litter input significantly changed the total and active microbial communities in degraded grassland soils. Journal of Soils and Sediments, 20 . pp. 2804-2816. https://doi.org/10.1007/s11368-020-02619-x

Malmir, M., Tahmasbian, I., Xu, Z., Farrar, M. B. and Bai, S. H. (2020) Prediction of macronutrients in plant leaves using chemometric analysis and wavelength selection. Journal of Soils and Sediments, 20 (1). pp. 249-259. https://doi.org/10.1007/s11368-019-02418-z

Kämper, W., Trueman, S. J., Tahmasbian, I. and Bai, S. H. (2020) Rapid Determination of Nutrient Concentrations in Hass Avocado Fruit by Vis/NIR Hyperspectral Imaging of Flesh or Skin. Remote Sensing, 12 (20). https://doi.org/10.3390/rs12203409

Phan, T. D., Smart, J. C. R., Stewart-Koster, B., Sahin, O., Hadwen, W. L., Dinh, L. T., Tahmasbian, I. and Capon, S. J. (2019) Applications of Bayesian Networks as Decision Support Tools for Water Resource Management under Climate Change and Socio-Economic Stressors: A Critical Appraisal. Water, 11 (12). p. 2642. https://doi.org/10.3390/w11122642

Malmir, M., Tahmasbian, I., Xu, Z., Farrar, M. B. and Bai, S. H. (2019) Prediction of soil macro- and micro-elements in sieved and ground air-dried soils using laboratory-based hyperspectral imaging technique. Geoderma, 340 . pp. 70-80. https://doi.org/10.1016/j.geoderma.2018.12.049

Tahmasbian, I., Xu, Z., Nguyen, T. T. N., Che, R., Omidvar, N., Lambert, G. and Bai, S. H. (2019) Short-term carbon and nitrogen dynamics in soil, litterfall and canopy of a suburban native forest subjected to prescribed burning in subtropical Australia. Journal of Soils and Sediments, 19 (12). pp. 3969-3981. https://doi.org/10.1007/s11368-019-02430-3

Tahmasbian, I., Xu, Z., Boyd, S., Zhou, J., Esmaeilani, R., Che, R. and Hosseini Bai, S. (2018) Laboratory-based hyperspectral image analysis for predicting soil carbon, nitrogen and their isotopic compositions. Geoderma, 330 . pp. 254-263. https://doi.org/10.1016/j.geoderma.2018.06.008

Gama, T., Wallace, H. M., Trueman, S. J., Tahmasbian, I. and Bai, S. H. (2017) Hyperspectral imaging for non-destructive prediction of total nitrogen concentration in almond kernels. Acta Horticulturae, 1219 . pp. 259-264. https://doi.org/10.17660/ActaHortic.2018.1219.40

Monograph

Tahmasbian, I., Dunlop, M. W. and Brown, G. (2020) Piggery Odour Emission Rate Validation Study. Project Report. Pork CRC.

Conference or Workshop Item

Tahmasbian, I., Moss, A. F., Morgan, N. K., Pepper, C.-M. and Dunlop, M. W. (2023) Hyperspectral imaging is a promising technology for real-time monitoring of feed and litter quality, and mycotoxin detection. In: 34th Australian Poultry Science Symposium,, 5th - 8th February 2023, Sydney, Australia.

Dataset

Tahmasbian, I., Wang, J., Hosseini Bai, S. and Simpfendorfer, S. (2024) Hyperspectral images captured from wheat grain samples with different levels of DON contamination. [Dataset] https://doi.org/10.60699/nrmy-9a65

Tahmasbian, I. and Wang, J. (2024) Python and MATLAB script used for analysing (regression and classification) the data extracted from hyperspectral images of wheat grain samples infected by Fusarium graminearum. [Dataset] https://doi.org/10.60699/qvsp-0w71

Tahmasbian, I., Wang, J., Simpfendorfer, S., Reid, R., Sultanbawa, Y., Seididamyeh, M. and Hosseini Bai, S. (2024) Reflectance values extracted from hyperspectral images captured from wheat grain samples along with reference DON concentrations. [Dataset] https://doi.org/10.60699/5z9b-ze09