Associate Professor Daniel Cozzolino
Associate Professor

Daniel Cozzolino

Email: 
Phone: 
+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)

361 - 380 of 447 works

2009

Book Chapter

Wine and Beer

Cozzolino, Daniel and Dambergs, Robert G (2009). Wine and Beer. Infrared Spectroscopy for Food Quality Analysis and Control. (pp. 377-397) Elsevier Inc.. doi: 10.1016/B978-0-12-374136-3.00014-6

Wine and Beer

2009

Journal Article

A brief introduction to multivariate methods in grape and wine analysis

Cozzolino, D., Cynkar, W. U., Shah, N., Dambergs, R. G. and Smith, P. A. (2009). A brief introduction to multivariate methods in grape and wine analysis. International Journal of Wine Research, 1 (1), 123-130. doi: 10.2147/IJWR.S4585

A brief introduction to multivariate methods in grape and wine analysis

2009

Journal Article

Mid infrared spectroscopy and multivariate analysis: A tool to discriminate between organic and non-organic wines grown in Australia

Cozzolino, Daniel, Holdstock, Matt, Dambergs, Robert G., Cynkar, Wies U. and Smith, Paul A. (2009). Mid infrared spectroscopy and multivariate analysis: A tool to discriminate between organic and non-organic wines grown in Australia. Food Chemistry, 116 (3), 761-765. doi: 10.1016/j.foodchem.2009.03.022

Mid infrared spectroscopy and multivariate analysis: A tool to discriminate between organic and non-organic wines grown in Australia

2009

Journal Article

Discovering a chemical basis for differentiating wines made by fermentation with 'wild' indigenous and inoculated yeasts: Role of yeast volatile compounds

Varela, C., Siebert, T., Cozzolino, D., Rose, L., McLean, H. and Henschke, P. A. (2009). Discovering a chemical basis for differentiating wines made by fermentation with 'wild' indigenous and inoculated yeasts: Role of yeast volatile compounds. Australian Journal of Grape and Wine Research, 15 (3), 238-248. doi: 10.1111/j.1755-0238.2009.00054.x

Discovering a chemical basis for differentiating wines made by fermentation with 'wild' indigenous and inoculated yeasts: Role of yeast volatile compounds

2009

Journal Article

Geographical origin of Sauvignon Blanc wines predicted by mass spectrometry and metal oxide based electronic nose

Berna, Amalia Z., Trowell, Stephen, Clifford, David, Cynkar, Wies and Cozzolino, Daniel (2009). Geographical origin of Sauvignon Blanc wines predicted by mass spectrometry and metal oxide based electronic nose. Analytica Chimica Acta, 648 (2), 146-152. doi: 10.1016/j.aca.2009.06.056

Geographical origin of Sauvignon Blanc wines predicted by mass spectrometry and metal oxide based electronic nose

2009

Journal Article

Usefulness of near infrared spectroscopy to monitor the extent of heat treatment in fish meal

Cozzolino, Daniel, Chree, Allison, Murray, Ian and Scaife, Jeff R. (2009). Usefulness of near infrared spectroscopy to monitor the extent of heat treatment in fish meal. International Journal of Food Science and Technology, 44 (8), 1579-1584. doi: 10.1111/j.1365-2621.2008.01845.x

Usefulness of near infrared spectroscopy to monitor the extent of heat treatment in fish meal

2009

Journal Article

Direct comparison between visible near- and mid-infrared spectroscopy for describing diuron sorption in soils

Forouzangohar, Mohsen, Cozzolino, Daniel, Kookana, Rai S., Smernik, Ronald J., Forrester, Sean T. and Chittleborough, David J. (2009). Direct comparison between visible near- and mid-infrared spectroscopy for describing diuron sorption in soils. Environmental Science and Technology, 43 (11), 4049-4055. doi: 10.1021/es8029945

Direct comparison between visible near- and mid-infrared spectroscopy for describing diuron sorption in soils

2009

Journal Article

Near infrared spectroscopy in natural products analysis

Cozzolino, Daniel (2009). Near infrared spectroscopy in natural products analysis. Planta Medica, 75 (7), 746-756. doi: 10.1055/s-0028-1112220

Near infrared spectroscopy in natural products analysis

2009

Journal Article

Predicting the nutritive value of high moisture grain corn by near infrared reflectance spectroscopy

Fassio, A., Fernández, E. G., Restaino, E. A., La Manna, A. and Cozzolino, D. (2009). Predicting the nutritive value of high moisture grain corn by near infrared reflectance spectroscopy. Computers and Electronics in Agriculture, 67 (1-2), 59-63. doi: 10.1016/j.compag.2009.03.001

Predicting the nutritive value of high moisture grain corn by near infrared reflectance spectroscopy

2009

Journal Article

The effect of sample storage and homogenisation techniques on the chemical composition and near infrared spectra of white grapes

Cynkar, Wieslawa, Cozzolino, Daniel and Dambergs, Robert G. (2009). The effect of sample storage and homogenisation techniques on the chemical composition and near infrared spectra of white grapes. Food Research International, 42 (5-6), 653-658. doi: 10.1016/j.foodres.2009.02.002

The effect of sample storage and homogenisation techniques on the chemical composition and near infrared spectra of white grapes

2009

Journal Article

APPLICATION OF ELECTRONIC NOSES IN THE WINE INDUSTRY

Cozzolino, Daniel, Cynkar, Wies and Dambergs, Robert (2009). APPLICATION OF ELECTRONIC NOSES IN THE WINE INDUSTRY. Handbook On Mass Spectrometry: Instrumentation, Data and Analysis, and Applications, 435-445.

APPLICATION OF ELECTRONIC NOSES IN THE WINE INDUSTRY

2009

Journal Article

Prediction of the nutritive value of pasture silage by near infrared spectroscopy (NIRS) Predicción del valor nutritivo de ensilaje de pasturas mediante espectrofotometría en el infrarrojo cercano (NIRS)

Restaino, Ernesto A., Fernández, Enrique G., la Manna, Alejandro and Cozzolino, Daniel (2009). Prediction of the nutritive value of pasture silage by near infrared spectroscopy (NIRS) Predicción del valor nutritivo de ensilaje de pasturas mediante espectrofotometría en el infrarrojo cercano (NIRS). Chilean Journal of Agricultural Research, 69 (4), 560-566. doi: 10.4067/S0718-58392009000400011

Prediction of the nutritive value of pasture silage by near infrared spectroscopy (NIRS) Predicción del valor nutritivo de ensilaje de pasturas mediante espectrofotometría en el infrarrojo cercano (NIRS)

2009

Journal Article

Usefulness of near infrared reflectance (NIR) spectroscopy and chemometrics to discriminate between fishmeal, meat meal and soya meal samples

Cozzolino, Daniel, Restaino, Ernesto, la Manna, Alejandro, Fernandez, Enrique and Fassio, Alberto (2009). Usefulness of near infrared reflectance (NIR) spectroscopy and chemometrics to discriminate between fishmeal, meat meal and soya meal samples. Ciencia e Investigacion Agraria, 36 (2), 209-214. doi: 10.4067/S0718-16202009000200005

Usefulness of near infrared reflectance (NIR) spectroscopy and chemometrics to discriminate between fishmeal, meat meal and soya meal samples

2008

Journal Article

Measurement of condensed tannins and dry matter in red grape homogenates using near infrared spectroscopy and partial least squares

Cozzolino, Daniel, Cynkar, Wies U., Dambergs, Robert G., Mercurio, Meagan D. and Smith, Paul A. (2008). Measurement of condensed tannins and dry matter in red grape homogenates using near infrared spectroscopy and partial least squares. Journal of Agricultural and Food Chemistry, 56 (17), 7631-7636. doi: 10.1021/jf801563z

Measurement of condensed tannins and dry matter in red grape homogenates using near infrared spectroscopy and partial least squares

2008

Journal Article

Varietal discrimination of Australian wines by means of mid-infrared spectroscopy and multivariate analysis

Bevin, Christopher J., Dambergs, Robert G., Fergusson, Allison J. and Cozzolino, Daniel (2008). Varietal discrimination of Australian wines by means of mid-infrared spectroscopy and multivariate analysis. Analytica Chimica Acta, 621 (1), 19-23. doi: 10.1016/j.aca.2007.10.042

Varietal discrimination of Australian wines by means of mid-infrared spectroscopy and multivariate analysis

2008

Journal Article

Relationship between wine scores and visible-near-infrared spectra of Australian red wines

Cozzolino, D., Cowey, G., Lattey, K. A., Godden, P., Cynkar, W. U., Dambergs, R. G., Janik, L. and Gishen, M. (2008). Relationship between wine scores and visible-near-infrared spectra of Australian red wines. Analytical and Bioanalytical Chemistry, 391 (3), 975-981. doi: 10.1007/s00216-008-2071-3

Relationship between wine scores and visible-near-infrared spectra of Australian red wines

2008

Journal Article

Comparison of metal oxide-based electronic nose and mass spectrometry-based electronic nose for the prediction of red wine spoilage

Berna, Amalia Z., Trowell, Stephen, Cynkar, Wies and Cozzolino, Daniel (2008). Comparison of metal oxide-based electronic nose and mass spectrometry-based electronic nose for the prediction of red wine spoilage. Journal of Agricultural and Food Chemistry, 56 (9), 3238-3244. doi: 10.1021/jf7037289

Comparison of metal oxide-based electronic nose and mass spectrometry-based electronic nose for the prediction of red wine spoilage

2008

Journal Article

Near infrared spectroscopy as a rapid tool to measure volatile aroma compounds in Riesling wine: possibilities and limits

Smyth, H. E., Cozzolino, D., Cynkar, W. U., Dambergs, R. G., Sefton, M. and Gishen, M. (2008). Near infrared spectroscopy as a rapid tool to measure volatile aroma compounds in Riesling wine: possibilities and limits. Analytical and Bioanalytical Chemistry, 390 (7), 1911-1916. doi: 10.1007/s00216-008-1940-0

Near infrared spectroscopy as a rapid tool to measure volatile aroma compounds in Riesling wine: possibilities and limits

2008

Journal Article

Preliminary study on the application of visible-near infrared spectroscopy and chemometrics to classify Riesling wines from different countries

Liu, L., Cozzolino, D., Cynkar, W. U., Dambergs, R. G., Janik, L., O'Neill, B. K., Colby, C. B. and Gishen, M. (2008). Preliminary study on the application of visible-near infrared spectroscopy and chemometrics to classify Riesling wines from different countries. Food Chemistry, 106 (2), 781-786. doi: 10.1016/j.foodchem.2007.06.015

Preliminary study on the application of visible-near infrared spectroscopy and chemometrics to classify Riesling wines from different countries

2008

Journal Article

Analysis of elements in wine using near infrared spectroscopy and partial least squares regression

Cozzolino, D., Kwiatkowski, M. J., Dambergs, R. G., Cynkar, W. U., Janik, L. J., Skouroumounis, G. and Gishen, M. (2008). Analysis of elements in wine using near infrared spectroscopy and partial least squares regression. Talanta, 74 (4), 711-716. doi: 10.1016/j.talanta.2007.06.045

Analysis of elements in wine using near infrared spectroscopy and partial least squares regression

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

Before you email them, read our advice on how to contact a supervisor.

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

Need help?

For help with finding experts, story ideas and media enquiries, contact our Media team:

communications@uq.edu.au