Associate Professor Daniel Cozzolino
Associate Professor

Daniel Cozzolino

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+61 7 336 52144

Background

Cozzolino is a Principal Research Fellow with the Queensland Alliance for Agriculture and Food Innovation (QAAFI), University of Queensland. He has worked in several positions including Associate Professor in Food Chemistry (RMIT University, Melbourne), Head of Agriculture (CQUniversity, Rockhampton), Senior Research Fellow Barley Breeding Program (University of Adelaide, Adelaide), Team Leader Rapid Analytical Group (The Australian Wine Research Institute, Adelaide), Head of Animal Nutrition (INIA La Estanzuela, Uruguay).

His research focusses on the application of chemometric, machine learning and spectroscopic methods (e.g. NIR, MIR, hyperspectral) in a wide range of fields (eg. food, waste products, agricultural commodities). He has published more than 500 peer-review articles and book chapters (h index 68).

He was presented in 2013 with the Hirschfeld Award by the International Council of Near Infrared Spectroscopy for his outstanding contributions on the field of NIR spectroscopy. He ranked 94 in Australia and 3665 in the world as best-Chemistry-Scientist 2023 (Research.com).

Availability

Associate Professor Daniel Cozzolino is:
Available for supervision
Media expert

Fields of research

Agricultural, Veterinary and Food Sciences Chemical Sciences

Qualifications

  • Doctor of Philosophy, University of Aberdeen
  • Member, ANISG group, ANISG group
  • Member, American Chemical Society, American Chemical Society
  • Member, Australian Institute of Food Science and Technology, Australian Institute of Food Science and Technology
  • Member, Society for Applied Spectroscopy, Society for Applied Spectroscopy

Research interests

  • Objective measurement of foods and feeds

    Development of objective methods to analyse composition if foods based on the utilization of sensors and machine learning techniques.

  • Food Authenticity, fraud and provenance

    Development and implementation of rapid analytical methods to monitor food authenticity, fraud and provenance. Monitor all steps of the value chain using fingerprinting approaches.

  • Sensing technologies and machine learning applied to food and nutrition

    Application and development of sensing technologies in combination with machine learning techniques to analyse, monitor food composition and quality, monitor nutrition in animals and humans (e,g, hair, saliva and urine analysis).

Research impacts

He was presented in 2013 with the Hirschfeld Award by the International Council of Near Infrared Spectroscopy for his outstanding contributions on the field of NIR spectroscopy.

He ranked 94 in Australia and 3665 in the world as best-Chemistry-Scientist 2023 (Research.com).

Search Professor Daniel Cozzolino’s works on UQ eSpace

447 works between 1996 and 2025
All (447) Journal Article (381) Book Chapter (37) Conference Publication (28) Book (1)

401 - 420 of 447 works

2006

Journal Article

Classification of the floral origin of Uruguayan honeys by chemical and physical characteristics combined with chemometrics

Corbella, E. and Cozzolino, D. (2006). Classification of the floral origin of Uruguayan honeys by chemical and physical characteristics combined with chemometrics. LWT - Food Science and Technology, 39 (5), 534-539. doi: 10.1016/j.lwt.2005.03.011

Classification of the floral origin of Uruguayan honeys by chemical and physical characteristics combined with chemometrics

2006

Journal Article

Adaptive wavelet modelling of a nested 3 factor experimental design in NIR chemometrics

Donald, David, Coomans, Danny, Everingham, Yvette, Cozzolino, Daniel, Gishen, Mark and Hancock, Tim (2006). Adaptive wavelet modelling of a nested 3 factor experimental design in NIR chemometrics. Chemometrics and Intelligent Laboratory Systems, 82 (1-2 SPEC. ISS), 122-129. doi: 10.1016/j.chemolab.2005.05.013

Adaptive wavelet modelling of a nested 3 factor experimental design in NIR chemometrics

2006

Journal Article

The determination of red grape quality parameters using the LOCAL algorithm

Dambergs, R.G., Cozzolino, D., Cynkar, W.U., Janik, L. and Gishen, M. (2006). The determination of red grape quality parameters using the LOCAL algorithm. Journal of Near Infrared Spectroscopy, 14 (2), 71-79. doi: 10.1255/jnirs.593

The determination of red grape quality parameters using the LOCAL algorithm

2006

Journal Article

Predicting intramuscular fat, moisture and Warner-Bratzler shear force in pork muscle using near infrared reflectance spectroscopy

Barlocco, N., Vadell, A., Ballesteros, F., Galietta, G. and Cozzolino, D. (2006). Predicting intramuscular fat, moisture and Warner-Bratzler shear force in pork muscle using near infrared reflectance spectroscopy. Animal Science, 82 (1), 111-116. doi: 10.1079/ASC20055

Predicting intramuscular fat, moisture and Warner-Bratzler shear force in pork muscle using near infrared reflectance spectroscopy

2006

Journal Article

Metabolic profiling as a tool for revealing Saccharomyces interactions during wine fermentation

Howell, Kate S., Cozzolino, Daniel, Bartowsky, Eveline J., Fleet, Graham H. and Henschke, Paul A. (2006). Metabolic profiling as a tool for revealing Saccharomyces interactions during wine fermentation. FEMS Yeast Research, 6 (1), 91-101. doi: 10.1111/j.1567-1364.2005.00010.x

Metabolic profiling as a tool for revealing Saccharomyces interactions during wine fermentation

2006

Journal Article

Combining near infrared spectroscopy and multivariate analysis as a tool to differentiate different strains of Saccharomyces cerevisiae: a metabolomic study

Cozzolino, D., Flood, L., Bellon, J., Gishen, M. and De Barros Lopes, M. (2006). Combining near infrared spectroscopy and multivariate analysis as a tool to differentiate different strains of Saccharomyces cerevisiae: a metabolomic study. Yeast, 23 (14-15), 1089-1096. doi: 10.1002/yea.1418

Combining near infrared spectroscopy and multivariate analysis as a tool to differentiate different strains of Saccharomyces cerevisiae: a metabolomic study

2006

Conference Publication

Combining mass spectrometry based electronic nose, visible-near infrared spectroscopy and chemometrics to assess the sensory properties of Australian Riesling wines

Cozzolino, Daniel, Smyth, Heather E., Lattey, Kate A., Cynkar, Wies, Janik, Les, Dambergs, Robert G., Francis, I. Leigh and Gishen, Mark (2006). Combining mass spectrometry based electronic nose, visible-near infrared spectroscopy and chemometrics to assess the sensory properties of Australian Riesling wines. 4th Symposium on In Vino Analytica Scientia, Montpellier, France, 7-9 July 2005. Amsterdam, Netherlands: Elsevier BV. doi: 10.1016/j.aca.2005.11.008

Combining mass spectrometry based electronic nose, visible-near infrared spectroscopy and chemometrics to assess the sensory properties of Australian Riesling wines

2006

Conference Publication

Potential of VIS-NIR spectroscopy to predict perceived ‘muddy’ taint in Australian farmed barramundi

Smyth, H. E., Drasch, P., Cozzolino, D., Fox, G. and Percival, S. (2006). Potential of VIS-NIR spectroscopy to predict perceived ‘muddy’ taint in Australian farmed barramundi. 12th Australian Near Infrared Spectroscopy Conference: NIR a Fruitful Science, Rockhampton, QLD, Australia, 9-10th May 2006.

Potential of VIS-NIR spectroscopy to predict perceived ‘muddy’ taint in Australian farmed barramundi

2006

Journal Article

Potential of near-infrared reflectance spectroscopy and chemometrics to predict soil organic carbon fractions

Cozzolino, D. and Morón, A. (2006). Potential of near-infrared reflectance spectroscopy and chemometrics to predict soil organic carbon fractions. Soil and Tillage Research, 85 (1-2), 78-85. doi: 10.1016/j.still.2004.12.006

Potential of near-infrared reflectance spectroscopy and chemometrics to predict soil organic carbon fractions

2006

Journal Article

Use of Near Infrared Reflectance (NIR) spectroscopy to predict chemical composition of forages in broad-based calibration models

Garcia, Jaime and Cozzolino, Daniel (2006). Use of Near Infrared Reflectance (NIR) spectroscopy to predict chemical composition of forages in broad-based calibration models. Agricultura Tecnica, 66 (1), 41-47. doi: 10.4067/S0365-28072006000100005

Use of Near Infrared Reflectance (NIR) spectroscopy to predict chemical composition of forages in broad-based calibration models

2006

Journal Article

Exploring the potential of visible-near infrared spectroscopy to predict sensory properties of food

Smyth, Heather, Mayze, John, Exley, Paul, Fox, Glen, Poole, Sue, Drabsch, Paul, Percival, Steve and Cozzolino, Daniel (2006). Exploring the potential of visible-near infrared spectroscopy to predict sensory properties of food. NIR News, 17 (8), 10-11. doi: 10.1255/nirn.935

Exploring the potential of visible-near infrared spectroscopy to predict sensory properties of food

2006

Journal Article

Use of near infrared reflectance spectroscopy to evaluate quality characteristics in whole-wheat grain

Cozzolino, Daniel, Delucchi, Inés, Kholi, Moham and Vázquez, Daniel (2006). Use of near infrared reflectance spectroscopy to evaluate quality characteristics in whole-wheat grain. Agricultura Tecnica, 66 (4), 370-375. doi: 10.4067/S0365-28072006000400005

Use of near infrared reflectance spectroscopy to evaluate quality characteristics in whole-wheat grain

2005

Journal Article

Multivariate determination of free fatty acids and moisture in fish oils by partial least-squares regression and near-infrared spectroscopy

Cozzolino, D., Murray, I., Chree, A. and Scaife, J. R. (2005). Multivariate determination of free fatty acids and moisture in fish oils by partial least-squares regression and near-infrared spectroscopy. LWT - Food Science and Technology, 38 (8), 821-828. doi: 10.1016/j.lwt.2004.10.007

Multivariate determination of free fatty acids and moisture in fish oils by partial least-squares regression and near-infrared spectroscopy

2005

Journal Article

Grape and wine analysis - enhancing the power of spectroscopy with chemometrics : A review of some applications in the Australian wine industry

GISHEN, M., DAMBERGS, R.G. and COZZOLINO, D. (2005). Grape and wine analysis - enhancing the power of spectroscopy with chemometrics : A review of some applications in the Australian wine industry. Australian Journal of Grape and Wine Research, 11 (3), 296-305. doi: 10.1111/j.1755-0238.2005.tb00029.x

Grape and wine analysis - enhancing the power of spectroscopy with chemometrics : A review of some applications in the Australian wine industry

2005

Journal Article

Effect of both homogenisation and storage on the spectra of red grapes and on the measurement of total anthocyanins, total soluble solids and pH by visual near infrared spectroscopy

Cozzolino, D., Cynkar, W.U., Dambergs, R.G., Janik, L. and Gishen, M. (2005). Effect of both homogenisation and storage on the spectra of red grapes and on the measurement of total anthocyanins, total soluble solids and pH by visual near infrared spectroscopy. Journal of Near Infrared Spectroscopy, 13 (4), 213-223. doi: 10.1255/jnirs.539

Effect of both homogenisation and storage on the spectra of red grapes and on the measurement of total anthocyanins, total soluble solids and pH by visual near infrared spectroscopy

2005

Journal Article

The use of visible (VIS) and near infrared (NIR) reflectance spectroscopy to predict fibre diameter in both clean and greasy wool samples

Cozzolino, D., Montossi, F. and San Julian, R. (2005). The use of visible (VIS) and near infrared (NIR) reflectance spectroscopy to predict fibre diameter in both clean and greasy wool samples. Animal Science, 80 (3), 333-337. doi: 10.1079/ASC41760333

The use of visible (VIS) and near infrared (NIR) reflectance spectroscopy to predict fibre diameter in both clean and greasy wool samples

2005

Journal Article

Usefulness of Near-infrared reflectance (NIR) spectroscopy and chemometrics to discriminate fishmeal batches made with different fish species

Cozzolino, Daniel, Chree, A., Scaife, J. R. and Murray, Ian (2005). Usefulness of Near-infrared reflectance (NIR) spectroscopy and chemometrics to discriminate fishmeal batches made with different fish species. Journal of Agricultural and Food Chemistry, 53 (11), 4459-4463. doi: 10.1021/jf050303i

Usefulness of Near-infrared reflectance (NIR) spectroscopy and chemometrics to discriminate fishmeal batches made with different fish species

2005

Journal Article

Relationship between sensory analysis and near infrared spectroscopy in Australian Riesling and Chardonnay wines

Cozzolino, Daniel, Smyth, Heather E., Lattey, Kate A., Cynkar, Wies, Janik, Les, Dambergs, Robert G., Francis, I. Leigh and Gishen, Mark (2005). Relationship between sensory analysis and near infrared spectroscopy in Australian Riesling and Chardonnay wines. Analytica Chimica Acta, 539 (1-2), 341-348. doi: 10.1016/j.aca.2005.03.019

Relationship between sensory analysis and near infrared spectroscopy in Australian Riesling and Chardonnay wines

2005

Journal Article

The use of visible and near infrared spectroscopy to classify the floral origin of honey samples produced in Uruguay

Corbella, E. and Cozzolino, D. (2005). The use of visible and near infrared spectroscopy to classify the floral origin of honey samples produced in Uruguay. Journal of Near Infrared Spectroscopy, 13 (2), 63-68. doi: 10.1255/jnirs.458

The use of visible and near infrared spectroscopy to classify the floral origin of honey samples produced in Uruguay

2005

Conference Publication

Usefulness of chemometrics and mass spectrometry-based electronic nose to classify Australian white wines by their varietal origin

Cozzolino, Daniel, Smyth, Heather E., Cynkar, Wies, Dambergs, Robert G. and Gishen, Mark (2005). Usefulness of chemometrics and mass spectrometry-based electronic nose to classify Australian white wines by their varietal origin. 13th International Conference on Flow Injection Analysis (ICFIA 2005), Las Vegas, NV, United States, 24-29 April 2005. Amsterdam, Netherlands: Elsevier BV. doi: 10.1016/j.talanta.2005.08.057

Usefulness of chemometrics and mass spectrometry-based electronic nose to classify Australian white wines by their varietal origin

Current funding

  • 2024 - 2026
    MyINDAH Diet - Inclusive Digital Solutions for Healthy and Sustainable Diets and Food Security in Java's Urban and Peri-Urban Food Systems
    Department of Foreign Affairs and Trade (DFAT) - KONEKSI / Knowledge Partnership Platform (KPP)
    Open grant
  • 2024 - 2025
    Natural compounds and essential oils to enhance the productivity of poultry and promote food safety
    Acacia Natural Science Pty Ltd
    Open grant
  • 2023 - 2025
    Ecological Traceability as a Public Commons - New Models of Indigenous Supply Chain Data Governance
    National Agriculture Traceability Grants - Australian Department of Agriculture, Fisheries and Forestry
    Open grant
  • 2023 - 2026
    Goat Industry - Sustainability Credentials Project
    Meat & Livestock Australia
    Open grant
  • 2023 - 2026
    North Queensland cotton-grains-cattle farming systems
    CRC for Developing Northern Australia
    Open grant
  • 2022 - 2025
    APL Industry Placement Program
    Australasian Pork Research Institute Ltd
    Open grant
  • 2022 - 2027
    Sustainable Precision Feeding in Broiler Chickens in Australia
    AgriFutures Chicken Meat Program Nutrition, Gut Health and Environment Research Program
    Open grant
  • 2021 - 2026
    Genetics of Fruit Sensory Preferences
    Horticulture Innovation Australia Limited
    Open grant

Past funding

  • 2022
    Objective Assessment of Seaweed Composition and Quality using rapid methods (Australia-Indonesia Centre PAIR Tactical Work Packages Project administered by Monash University)
    Monash University
    Open grant
  • 2021 - 2022
    Survey of Australian goat producers' use of KIDPLAN
    Meat & Livestock Australia
    Open grant
  • 2021 - 2024
    Optimising and industrialising black soldier fly (BSF) production: redirecting food waste to livestock feed production using insects
    Fight Food Waste CRC
    Open grant
  • 2020 - 2022
    Measurement of pH in high intramuscular fat samples and existing technology validation
    Meat & Livestock Australia
    Open grant
  • 2020 - 2021
    Authentication of Australian stingless bee honey - proof of concept study
    Queensland Health
    Open grant
  • 2019 - 2022
    Improving the efficiency of Kakadu Plum value chains to grow a robust and sustainable industry
    CRC for Developing Northern Australia
    Open grant

Availability

Associate Professor Daniel Cozzolino is:
Available for supervision

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Supervision history

Current supervision

Completed supervision

Enquiries

Contact Associate Professor Daniel Cozzolino directly for media enquiries about:

  • Cereal Quality
  • Chemometrics
  • Feed Composition
  • Food Composition
  • Food Fraud
  • Food Quality
  • Food Science
  • Foodomics
  • Grain Quality
  • Infrared
  • NIR
  • Nutrition
  • Provenance
  • RVA
  • Sensors
  • Spectroscopy
  • Traceability

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