Academic Publications

July 13, 2021


Academic Publications

World-leading research from Food Agility's project teams and scholarship holders.

July 13, 2021

Non-project publications

Shahinur Alam, David Lamb, Nigel Warwick; A Canopy Transpiration Model Based on Scaling Up Stomatal Conductance and Radiation Interception as Affected by Leaf Area IndexWater2021,13(3), 252;

Sonam Peden, Ronald C. Bradbury, David William Lamb, Mark Hedley, A Model for RF Loss through Vegetation with Varying Water ContentJ.Electromagn. Anal. Appl.Vol.13 No.3, March 31, 2021 DOI:10.4236/jemaa.2021.133003

Salgadoe, A.S.A., Robson, A.J., Lamb, D.W., and Schneider, D., (2019), ‘A non-reference temperature histogram method for determining Tc from ground-based thermal imagery of orchard tree canopies’, Remote Sensing, 1(6), 714

Crabbe, R.A., Lamb, D.W., Edwards, C., Andersson, K. and Schneider, D., (2019), ‘A preliminary investigation of the potential of sentinel-1 radar to estimate pasture biomass in a grazed pasture landscape’, Remote Sensing 11(7), 872

Verma, N.K., Lamb, D.W., Reid, N., Wilson, B. and Sinha, P., (2019), ‘Airborne LiDAR and high-resolution multispectral data integration in Eucalyptus Tree species mapping in an Australian farmscape’, Geocarto International,

Stéphanie Camaréna Artificial Intelligence in the design of transitions to Sustainable Food Systems Journal of Cleaner Production, volume271, 20 October 2020, 122574 (doi: 10.1016/j.jclepro.2020.122574)

Salgadoe, A.S.A, Robson, A.J., Lamb, D.W. and Dann, E.K., (2019), ‘Assessment of Canopy Porosity in Avocado Trees as a Surrogate for Restricted Transpiration Emanating from Phytophthora Root Rot’, Remote Sensing, 11, 2972

Richard Crabbe, David Lamb, Clare Edwards  Discriminating between C3, C4, and mixedC3/C4 pasture grasses of a grazed landscape using multi-temporal Sentinel-1a data Remote Sensing. 11, 253 (doi:10.3390/rs11030253) 2019

Crabbe, R.A., Lamb, D.W. and Edwards, C., (2019), ‘Discrimination of Species Composition Types of a Grazed Pasture Landscape Using Sentinel-1 and Sentinel-2 Data’, International Journal of Applied Earth Observations and Geoinformation. 84, 101978

Zhou, I., Lipman, J., Abolhasan, M., Shariati, N. and Lamb, D.W., 2020. Frost monitoring cyber-physical system: a survey on prediction and active protection methods. IEEE Internet of Things Journal, doi: 10.1109/JIOT.2020.2972936

Barwick, J., Lamb, D.W., Dobos, R., Welch, M., Schneider, D. and Trotter, M., 2020. Identifying Sheep Activity from Tri-Axial Acceleration Signals Using a Moving Window Classification Model. Remote Sensing, 12(4), p.646,

Ian Zhou, Imran Makhdoom, Negin Shariati, Muhammad Ahmad Raza, Rasool Keshavarz, Justin Lipman,  Mehran Abolhasan, and Abbas Jamalipour. Internet of Things 2.0: Concepts, Applications and Future Directions  IEEE Access 2021, 9, 70961-71012 (DOI 10.1109/ACCESS.2021.3078549)

Richard Crabbe,David Lamb, Clare Edwards Investigating the potential of Sentinel-1 to detect varying surface heterogeneity in pasture cover in grasslands InternationalJournal of Remote Sensing, 42 (1), 254-265 (doi: 10.1080/01431161.2020)


Moshiur Rahman,David Lamb, Stanislaw Samborski Reducing the influence of solar illumination angle when using active optical sensor derived NDVIAOS to infer fAPAR for spring wheat (Triticum aestivum L.) Computers and Electronics in Agriculture. 156:1-9 (DOI: 10.1016/j.compag.2018.11.007)2019

Imran Makhdoom Farzad Tofigh, Ian Zhou, Mehran Abolhasan, and Justin Lipman PLEDGE: A Proof-of-Honesty based Consensus Protocol for Blockchain-based IoT Systems 2020 IEEE International Conference on Blockchain and Cryptocurrency(ICBC), Toronto, ON, Canada, 2020, pp. 1-3, doi:10.1109/ICBC48266.2020.9169406.


Makhdoom, I., Zhou, I., Abolhasan, M., Lipman, J. and Ni, W., 2020. PrivySharing: A blockchain-based framework for privacy-preserving and secure data sharing in smart cities. Computers & Security, 88, p.101653,

Rahman, M.M., Lamb, D.W. and Samborski, S.M., (2019) ‘Reducing the influence of solar illumination angle when using active optical sensor derived NDVIAOS to infer fAPAR for spring wheat (Triticum aestivum L.)’, Computers and Electronics in Agriculture 156, p1-9

Yu, G., Wang, X., Yu, K., Ni, W., Zhang, J.A. and Liu, R.P., 2020. Survey: Sharding in blockchains. IEEE Access, 8, pp.14155-14181, DOI: 10.1109/ACCESS.2020.2965147

Amit Kumar, Nazanin Emaili and Massimo Piccardi. Topic-document inference with the Gumbel-Softmax distribution, IEEE Access 2021, 9, 1313-1320 (DOI 10.1109/ACCESS.2020.3046607)

Majid Amiri, Mehran Abolhasan, Negin Shariati, and Justin Lipman. “Soil moisture remote sensing using SIW cavity based metamaterial perfect absorber”, Nature Journals – Scientific Reports 11: 7153 (2021)

Project : Blockchain in Beef Export

Shoufeng Cao,  Warwick Powell, Marcus Foth, Valeri Natanelov, Thomas Miller and Uwe Dulleck, Strengthening consumer trust in beef supply chain traceability with a blockchain-enabled human-machine reconcile mechanism. Computers and Electronics in Agriculture180, Article number: 105886. 10.1016/j.compag.2020.105886

Lachlan Robb, Felicity Deane, Warwick Powell. “Panoptic blockchain ecosystems: An exploratory case study of the beef supply chain”. Monash Uni Law Review (2020) 46 (2), 57-84

Constellation CA002: Natural capital for climate resilient farm systems

Mitchell, M.C., Pritchard, J., Okada, S., Zhang, J., Venables, I., Vanhercke, T. and Ral, J.P., 2020. Increasing growth and yield by altering carbon metabolism in a transgenic leaf oil crop. Plant Biotechnology Journal,

Project FA004: Seafood tracking and traceability

Yu, G., Zha, X., Wang, X., Ni, W., Yu, K., Yu, P., Zhang, J.A., Liu, R.P. and Guo, Y.J., 2020. Enabling Attribute Revocation for Fine-Grained Access Control in Blockchain-IoT Systems. IEEE Transactions on Engineering Management, DOI 10.1109/TEM.2020.2966643

Yu, G., Zha, X., Wang, X., Ni, W., Yu, K., Zhang, J.A. and Liu, R.P., 2020. A Unified Analytical Model for Proof-of-X Schemes. Computers & Security, p.101934,

Yu, G., Wang, X., Yu, K., Ni, W., Zhang, J.A. and Liu, R.P., 2020. Survey: Sharding in blockchains. IEEE Access, 8, pp.14155-14181, DOI: 10.1109/ACCESS.2020.2965147

Project : Sensors for Summerfruit

Alessio Scalisi, Daniele Pelliccia and Mark Glenn O’Connell, Maturity prediction in yellow peach (Prunus persica L.) cultivars using a fluorescence spectrometer Sensors2020, 20, 6555; doi:10.3390/s20226555

Thomas Fahey, Hai Pham, Alessandro Gardi, Roberto Sabatini, Dario Stefanelli, Ian Goodwin, David William Lamb, Active and Passive Electro-optical Sensors for Health Assessment in Food CropsSensors 202121(1),171;

Project FA016: Yarrabilba Circular Food Economy

Messner, R., Richards, C. and Johnson, H., 2020. The “Prevention Paradox”: food waste prevention and the quandary of systemic surplus production. Agriculture and Human Values, pp.1-13,

CarolRichards, Bree Hurst, Rudolf Messner, Grace O'Connor, The paradoxes of food waste reduction in the horticultural supply chain. Industrial MarketingManagement Volume 93, February 2021, Pages 482-491.

Project FA003: On-Farm Experimentation

Fiona H. Evans, Angela Recalde Salas, Suman Rakshit, Craig Scanlan and Simon Cook, Assessment of the use of Geographically Weighted Regression (GWR) for analysis of large on-farm experiments and implications for practical application. Agronomy  10  (11). (DOI  10.3390/agronomy10111720)

Simon Cook, Elizabeth L. Jackson, Myles J. Fisher (In Memoriam), Derek Baker, Dean Diepeveen. Embedding digital agriculture into sustainable Australian food systems: pathways and pitfalls to value creation, International Journal of Agricultural Sustainability. (DOI: 10.1080/14735903.2021.1937881).


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