Profiles

Muhammad Shahinur Alam

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Muhammad Shahinur Alam

Digital Agriculture Scientist

Room NH.AO24.L02.267 , Building S

+61362262918 (phone)

MS.Alam@utas.edu.au

Muhammad Shahinur Alam (Shahin) is currently working in the position of Digital Agriculture Scientist at the Tasmanian Institute of Agriculture (TIA). His research focusses on improving farm productivity and resource use efficiency through the application of digital and precision agriculture tools and techniques.

Biography

Shahin completed his PhD in 2019 from the University of New England and had been working as a Casual Academic until he started in his position at UTAS. He also worked in the protected farming industry in Australia and has more than 12 years of experience working in the public and higher education sector in Australia and in Bangladesh. Before moving to Australia, Shahin was an Associate Professor in the Department of Agricultural Engineering at Sher-e-Bangla Agricultural University, Dhaka, Bangladesh. In his diverse career, he also worked with Bangladesh Rural Electrification Board, Bangladesh Agricultural Research Institute, University of New England and with Australian Natural Therapeutics Group.)

Career summary

Qualifications

PhD (Precision Agriculture), University of New England, Armidale, NSW 2350, Australia
MSc (Biosystems Engineering), Wageningen University and Research, Wageningen 6708 PB, The Netherlands
MSc (Farm Power and Machinery), Bangladesh Agricultural University, Mymensingh 2202, Bangladesh
BSc (Agricultural Engineering), Bangladesh Agricultural University, Mymensingh 2202, Bangladesh

Languages (other than English)

Bengali

View more on Mr Muhammad Shahinur Alam in WARP

Research Themes

He is an Agricultural Engineer, with experience and knowledge in the areas of both arable and protected farming systems, precision agriculture, agricultural mechanization and farming systems design. He worked on a project to expand mechanization and automation in the intercropping systems in Western Europe and therefore gained insight into the multi-species farming systems, their benefits, and existing constraints to introduce mechanization and automation in a new innovative farming system. He has a good understanding of how digitization and automation can influence productivity and profitability during his previous study and work in Bangladesh and the Netherlands. He completed his PhD in 2019 and for his PhD, worked with the Precision Agriculture Research Group at the University of New England, Armidale gaining research experience in the application of proximal sensing, using existing sensor networks to collect a large volume of data in the context of Australian agriculture.

Awards

Shahin was awarded the 'Chancellor's Doctoral Research Medal' for his outstanding PhD thesis at the University of New England, Armidale, NSW 2350, Australia.

Fields of Research

  • Agriculture, land and farm management (300299)
  • Agricultural systems analysis and modelling (300207)
  • Agricultural hydrology (300201)
  • Modelling and simulation (460207)
  • Applied geophysics (370601)
  • Electronic sensors (400906)
  • Agricultural land management (300202)
  • Sustainable agricultural development (300210)

Research Objectives

  • Expanding knowledge in the agricultural, food and veterinary sciences (280101)
  • Management of gaseous waste from animal production (excl. greenhouse gases) (100101)
  • Management of water consumption by plant production (260104)
  • Effects of climate change on Australia (excl. social impacts) (190504)
  • Soils (180605)
  • Water policy (incl. water allocation) (190211)

Publications

Shahin has published papers in the top ranked journals in his area of research including 'Computers and Electronics in Agriculture', 'Agricultural Water Management' and 'Water'.

Total publications

5

Journal Article

(3 outputs)
YearCitationAltmetrics
2021Alam MS, Lamb DW, Warwick NWM, 'A canopy transpiration model based on scaling up stomatal conductance and radiation interception as affected by leaf area index', Water, 13, (3) Article 252. ISSN 2073-4441 (2021) [Refereed Article]

DOI: 10.3390/w13030252 [eCite] [Details]

Citations: Scopus - 5Web of Science - 3

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2019Alam MS, Lamb DW, Rahman MM, 'In-situ partitioning of evaporation and transpiration components using a portable evapotranspiration dome : A case study in Tall Fescue (Festuca arundinacea)', Agricultural Water Management: An International Journal, 213 pp. 352-357. ISSN 0378-3774 (2019) [Refereed Article]

DOI: 10.1016/j.agwat.2018.10.042 [eCite] [Details]

Citations: Scopus - 5Web of Science - 4

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2018Alam MS, Lamb DW, Rahman MM, 'A refined method for rapidly determining the relationship between canopy NDVI and the pasture evapotranspiration coefficient', Computers and Electronics in Agriculture: An International Journal, 147 pp. 12-17. ISSN 0168-1699 (2018) [Refereed Article]

DOI: 10.1016/j.compag.2018.02.008 [eCite] [Details]

Citations: Scopus - 18Web of Science - 13

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Conference Publication

(2 outputs)
YearCitationAltmetrics
2018Alam MS, Lamb DW, Rahman MR, 'Rapid measurement of pasture evapotranspiration components using proximal sensors', SPAA, 10-11 September 2018, Adelaide Oval, Adelaide, South Australia, pp. 79-79. (2018) [Conference Extract]

[eCite] [Details]

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2017Alam MS, Lamb DW, Rahman M, Bradbury R, McCarthy C, 'Determining pasture evapotranspiration using active optical sensor derived normalized difference vegetation index', Preparing the digital future of livestock farming, 16-18 October 2017, Claudelands Conference and Exhibition Centre, Hami, pp. 1-7. (2017) [Refereed Conference Paper]

DOI: 10.5281/zenodo.897037 [eCite] [Details]

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