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Dr Mobashwer Alam

Research Fellow

Centre for Horticultural Science
Queensland Alliance for Agriculture and Food Innovation
m.alam@uq.edu.au
+61 7 5453 5971
0407925991

Overview

Dr Mobashwer Alam is a Plant Geneticist and Breeder with twenty years' research and teaching experience in public and private industries, and in the universities in Australia and Bangladesh. He has been working at the Centre for Horticultural Science, QAAFI, UQ and is based at Maroochy Research Station, Nambour, QLD 4560. Over the last twenty years, Dr Alam received experiences in multi-disciplinary research, including Plant Breeding, Quantitative Genetics, Genomics, Plant physiology, and Crop modelling. Before joining at QAAFI, UQ, Dr Alam had been working as a Senior Plant Breeder (Grain SOrghum) at Nuseed Pty Ltd. He achieved his PhD in Plant Molecular Genetics in 2013 through the School of Agriculture and Food Sciences of the University of Queensland. During his study at UQ, he worked with Crop Physiology and Modelling group at St. Lucia, and Sorghum Breeding group of Hermitage Research Station, Warwick. Before coming in Australia as a PhD student, Dr Alam had been working as a Lecturer and Assistant Professor of the Department of Genetics and Plant Breeding at Patuakhali Science and Technology University in Bangladesh. Throughout his academic and research career, he worked on multiple crops including Macadamia, Stone Fruits, Sorghum, Sugarcane, Lablab bean, Tomato, Okra, and Ash gourd. He is interested in developing rapid breeding tools and utilizing plant Genomics in tree crops improvement.

Research Interests

  • Developing quick breeding tools for rapid genetic gain in Macadamia
  • Crop Improvement through Plant Molecular Genetics and Genomics
  • Quantitative Genetic study of Complex traits
  • Developing rapid disease diagnostic tools
  • Rapid phenotyping using artificial intelligence

Qualifications

  • Doctor of Philosophy, The University of Queensland

Publications

View all Publications

Grants

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Supervision

View all Supervision

Available Projects

  • Inheritance of stomatal size and density in macadamia

    To cope with global climate change, one of the key focuses of the plant breeding program is to develop climate-smart varieties with efficient water use and photosynthesis. Finding out heritable and simple traits associated with less water loss and high photosynthesis can help breeders to select drought and high temperature tolerant elite cultivars. Stomatal pores on the leaf epidermis are the windows of water loss through transpiration and CO2 uptake for photosynthesis. By altering the stomatal size and density, it can be possible to optimize the amount of CO2 uptake and water loss. The focus of this project is to identify the variability in stomatal apparatus across a large number of breeding progeny, cultivars and wild germplasm of macadamia. The genetic and environmental effects on the variability of stomatal size and density will also be estimated. The inheritance pattern of the traits can be useful for future breeding decisions and planning.

    This project is open for undergraduate, honours, and masters by coursework students with a background in Genetics, Plant Science, Horticulture, Plant breeding, Plant Ecology, Botany, Plant Physiology.

    The scholar will develop skills in plant phenotyping, genetics, data analysis, and interpretation of results. They may have an opportunity to generate publications from their research and presenting in conferences.

    The project will be based at Queensland Government’s Maroochy Research Facility (MRF) at Nambour, which will create an opportunity to develop networks and relationships with researchers in horticulture, fruit and nut breeding, physiology, pathology, biotechnology and statistics. At MRF, the scholar will have access to modern laboratory, glasshouse and field facilities for conducting the research.

  • Rapid phenotyping: Developing image processing tools in macadamia

    In macadamia, plant growth characteristics are measured annually to calculate the yield efficiency of the breeding progeny. Nut traits are key components of yield per tree. However, the existing phenotypic evaluation for these traits is time consuming, laborious and expensive. Developing algorithm to utilize artificial intelligence for measuring different growth traits can assist in rapid phenotyping and improve breeding efficiency. This project will develop a proof of concept for field-based image processing tool for rapid characterisation of plant size and kernel recovery. An established rootstock trial (a common scion on to 24 different rootstocks) planted in 2017 will be used for plant size measurement, and a breeding progeny trial planted in multiple trials will be used for the estimation of kernel recovery. An artificial intelligence algorithm for image analysis will be developed and tested against actual field data.

    This project is open to applications from students with a background in Computational Science, Plant Breeding.

    The scholar will develop skills in plant phenomics, image analysis, computational biology, data analysis, and interpretation of results. They may have an opportunity to generate publications from their research, and presenting in conferences.

  • Identification of genomic regions associated with target traits: Genome Wide Association Study (GWAS) in macadamia

    Identification of molecular markers is important for Marker Assisted Selection (MAS), where an elite progeny is selected based on a marker associated with the trait of interest, rather than on the trait itself. Genome Wide Association study (GWAS) provides opportunities for the identification of genomic region(s) associated with the target traits by combining genome information with phenotypic data. Over the last five years, ~1000 breeding progeny, elite selections, cultivars and wild germplasm were genotyped using high throughput marker systems. Using phenotypic and genotypic data, this project aimed to identify markers associated with the trait of interest. Multiple projects are available. Target trait can be discussed before submitting the application.

    This project is open to applications from students with a background in Genetics, Computational Science, Plant Breeding, Plant Biotechnology, Plant Physiology, and Quantitative Genetics.

    The scholar will develop skills in Plant phenotyping, statistical genetics, genomics, data analysis, and interpretation of results. They may have an opportunity to generate publications from their research, and to present in conferences.

View all Available Projects

Publications

Featured Publications

Book

Book Chapter

  • Molecular breeding for combating salinity stress in sorghum: progress and prospects

    Chakma, Nidhi, Chakraborty, Moutoshi, Bhyan, Salma and Alam, Mobashwer (2021). Molecular breeding for combating salinity stress in sorghum: progress and prospects. Molecular breeding in wheat, maize and sorghum: strategies for improving abiotic stress tolerance and yield. (pp. 421-432) Wallingford, United Kingdom: CABI. doi: 10.1079/9781789245431.0024

  • Macadamia (Macadamia spp.) breeding

    Topp, Bruce L., Nock, Catherine J., Hardner, Craig M., Alam, Mobashwer and O’Connor, Katie M. (2019). Macadamia (Macadamia spp.) breeding. Advances in Plant Breeding Strategies: Nut and Beverage Crops. (pp. 221-251) edited by Jameel M. Al-Khayri, Shri Mohan Jain and Dennis V. Johnson. Cham, Switzerland: Springer International Publishing. doi: 10.1007/978-3-030-23112-5_7

Journal Article

Conference Publication

Other Outputs

Grants (Administered at UQ)

PhD and MPhil Supervision

Current Supervision

Possible Research Projects

Note for students: The possible research projects listed on this page may not be comprehensive or up to date. Always feel free to contact the staff for more information, and also with your own research ideas.

  • Inheritance of stomatal size and density in macadamia

    To cope with global climate change, one of the key focuses of the plant breeding program is to develop climate-smart varieties with efficient water use and photosynthesis. Finding out heritable and simple traits associated with less water loss and high photosynthesis can help breeders to select drought and high temperature tolerant elite cultivars. Stomatal pores on the leaf epidermis are the windows of water loss through transpiration and CO2 uptake for photosynthesis. By altering the stomatal size and density, it can be possible to optimize the amount of CO2 uptake and water loss. The focus of this project is to identify the variability in stomatal apparatus across a large number of breeding progeny, cultivars and wild germplasm of macadamia. The genetic and environmental effects on the variability of stomatal size and density will also be estimated. The inheritance pattern of the traits can be useful for future breeding decisions and planning.

    This project is open for undergraduate, honours, and masters by coursework students with a background in Genetics, Plant Science, Horticulture, Plant breeding, Plant Ecology, Botany, Plant Physiology.

    The scholar will develop skills in plant phenotyping, genetics, data analysis, and interpretation of results. They may have an opportunity to generate publications from their research and presenting in conferences.

    The project will be based at Queensland Government’s Maroochy Research Facility (MRF) at Nambour, which will create an opportunity to develop networks and relationships with researchers in horticulture, fruit and nut breeding, physiology, pathology, biotechnology and statistics. At MRF, the scholar will have access to modern laboratory, glasshouse and field facilities for conducting the research.

  • Rapid phenotyping: Developing image processing tools in macadamia

    In macadamia, plant growth characteristics are measured annually to calculate the yield efficiency of the breeding progeny. Nut traits are key components of yield per tree. However, the existing phenotypic evaluation for these traits is time consuming, laborious and expensive. Developing algorithm to utilize artificial intelligence for measuring different growth traits can assist in rapid phenotyping and improve breeding efficiency. This project will develop a proof of concept for field-based image processing tool for rapid characterisation of plant size and kernel recovery. An established rootstock trial (a common scion on to 24 different rootstocks) planted in 2017 will be used for plant size measurement, and a breeding progeny trial planted in multiple trials will be used for the estimation of kernel recovery. An artificial intelligence algorithm for image analysis will be developed and tested against actual field data.

    This project is open to applications from students with a background in Computational Science, Plant Breeding.

    The scholar will develop skills in plant phenomics, image analysis, computational biology, data analysis, and interpretation of results. They may have an opportunity to generate publications from their research, and presenting in conferences.

  • Identification of genomic regions associated with target traits: Genome Wide Association Study (GWAS) in macadamia

    Identification of molecular markers is important for Marker Assisted Selection (MAS), where an elite progeny is selected based on a marker associated with the trait of interest, rather than on the trait itself. Genome Wide Association study (GWAS) provides opportunities for the identification of genomic region(s) associated with the target traits by combining genome information with phenotypic data. Over the last five years, ~1000 breeding progeny, elite selections, cultivars and wild germplasm were genotyped using high throughput marker systems. Using phenotypic and genotypic data, this project aimed to identify markers associated with the trait of interest. Multiple projects are available. Target trait can be discussed before submitting the application.

    This project is open to applications from students with a background in Genetics, Computational Science, Plant Breeding, Plant Biotechnology, Plant Physiology, and Quantitative Genetics.

    The scholar will develop skills in Plant phenotyping, statistical genetics, genomics, data analysis, and interpretation of results. They may have an opportunity to generate publications from their research, and to present in conferences.

  • Exploring the variability and mechanism of self-compatibility in macadamia

    Macadamia is predominantly a self-incompatible nut crop with high industrial value worldwide. The commercial orchard production is largely dependent on the availability of insect-pollinators and cross-compatible pollen, which are prone to environmental risk factors. Presence of certain degree of self-compatibility was reported in some cultivars. Incorporation of self-compatibility in elite cultivars can reduce climatic risk and can ensure sustainable orchard production. However, the extent of variability and the mechanism of self-compatibility is unclear. This study aims to observe the variability in the degree of self-compatibility (or self-incompatibility) in breeding progeny, elite selections, cultivars and wild germplasm maintained by QAAFI’s National Macadamia Breeding and Evaluation Program. Inheritance pattern for the trait will also be evaluated. Experiments will be conducted to explore the mechanism of self-compatibility (or self-incompatibility) for further utilization in macadamia breeding program.

    This project is open to applications from students with a background in Genetics, Plant Breeding, Plant Physiology.

    The scholar will develop skills in Plant phenotyping, microscopy, genetics, data analysis, and interpretation of results. They may have an opportunity to generate publications from their research, and to present in conferences.

This staff member is a UQ Expert for media in the following fields:

Plant Genetics, Plant Breeding

They are happy to lend their expertise to your articles or broadcasts and share their research discoveries and insights with the community via media channels.

For additional assistance with story ideas, general advice and information or help with seeking further experts, please email the UQ Media Team or telephone (07) 3365 1120.

Links

ResearcherID: F-9833-2010

ORCID: 0000-0003-1502-5617

Scopus ID: 56076383300

Google Scholar ID: WYBe_18AAAAJ

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