Items where Subject is "Inventions"

A

Akbarian, S., Xu, C.-Y., Wang, W., Ginns, S. P. and Lim, S. (2022) Sugarcane yields prediction at the row level using a novel cross-validation approach to multi-year multispectral images. Computers and Electronics in Agriculture, 190 , 107024.

Anderson, N. T., Walsh, K. B., Koirala, A., Wang, Z., Amaral, M. H., Dickinson, G. R., Sinha, P. and Robson, A. J. (2021) Estimation of Fruit Load in Australian Mango Orchards Using Machine Vision. Agronomy, 11 (9). p. 1711. ISSN 2073-4395

Atzeni, M. and Hill, J. (2018) Non-effluent water storage modelling using MEDLI. Project Report. State of Queensland.

B

Blair, A. and Robertson, J. (2014) Dual herbicide spray application technology in sugar cane. Proceedings of the Australian Society of Sugar Cane Technology, 36 . p. 108. ISSN 0726-0822

C

Clewett, J.F. (2005) Australian RAINMAN: Further development and application to improve management of climate variability. Project Report. Rural Industries Research and Development Corporation.

Cornwall, N.A. and Black, R.F. (1967) Glasshouse temperature measurement and screen design. Queensland Journal of Agricultural and Animal Sciences, 24 (1). pp. 95-100.

D

Department of Agriculture and Fisheries, Queensland, (2023) Queensland AgTech Roadmap 2023–2028. Technical Report. State of Queensland.

G

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. ISSN 9462612161

H

Han, L., Cao, J., Ibell, P. and Diczbalis, Y. (2022) DigiHort: Digital Twins for Innovation of Future Orchard Systems. In: TropAg 2022 International Agriculture Conference, 31 October - 2 November 2022, Brisbane, Australia.

I

Ibell, P., Wright, C. L., Ridgeway, K., Bally, I. S.E., O'Farrell, P. and Xu, Z. (2018) Preliminary investigation of water use efficiency of Avocado varieties, irrigation and intra-canopy variation. Project Report. State of Queensland.

L

Lowe, K.F. and Simpson, G.B. (2009) Pasture analyser - A database of the growth rates of irrigated temperate species in southern Queensland. Tropical Grasslands, 43 . pp. 255-258. ISSN 0049-4763

M

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. ISSN 0016-7061

P

Potgieter, A., Camino, C., Poblete, T., George-Jaeggli, B. and et, a. (2023) Advances in the Study of Biochemical, Morphological and Physiological Traits of Wheat and Sorghum Crops in Australia Using Hyperspectral Data and Machine Learning. In: IGARSS 2023 - 2023 IEEE International Geoscience and Remote Sensing Symposium, 16-21 July 2023, Pasadena, Calif. USA.

R

Robertson, J. and Blair, A. (2015) The dual herbicide sprayer. Proceedings of the Australian Society of Sugar Cane Technology, 37 . p. 22. ISSN 0726-0822

S

Sudholz, A., Denman, S., Pople, A. R., Brennan, M., Amos, M. and Hamilton, G. (2021) A comparison of manual and automated detection of rusa deer (Rusa timorensis) from RPAS-derived thermal imagery. Wildlife Research, 49 (1). pp. 46-53.

T

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.

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. ISSN 0016-7061