Associate Professor Daniel Cozzolino
Associate Professor

Daniel Cozzolino

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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)

421 - 440 of 447 works

2005

Conference Publication

Identification of key aroma compounds in Australian Riesling and unwooded Chardonnay wines

Smyth, H. E., Cozzolino, D., Herderich, M., Sefton, M. A. and Francis, I. L. (2005). Identification of key aroma compounds in Australian Riesling and unwooded Chardonnay wines. 7th Wartburg Symposium on Flavor Chemistry and Biology, Eisenach, Germany, 21-23 April 2004. Eisenach, Germany: Deutsche Forschungsanstalt fur Lebensmittelchemie.

Identification of key aroma compounds in Australian Riesling and unwooded Chardonnay wines

2004

Journal Article

Non-destructive prediction of chemical composition in sunflower seeds by near infrared spectroscopy

Fassio, A. and Cozzolino, D. (2004). Non-destructive prediction of chemical composition in sunflower seeds by near infrared spectroscopy. Industrial Crops and Products, 20 (3), 321-329. doi: 10.1016/j.indcrop.2003.11.004

Non-destructive prediction of chemical composition in sunflower seeds by near infrared spectroscopy

2004

Conference Publication

Prediction of phenolic compounds in red wine fermentations by visible and near infrared spectroscopy

Cozzolino, D., Kwiatkowski, M. J., Parker, M., Cynkar, W. U., Dambergs, R. G., Gishen, M. and Herderich, M. J. (2004). Prediction of phenolic compounds in red wine fermentations by visible and near infrared spectroscopy. doi: 10.1016/j.aca.2003.08.066

Prediction of phenolic compounds in red wine fermentations by visible and near infrared spectroscopy

2004

Journal Article

Determination of potentially mineralizable nitrogen and nitrogen in particulate organic matter fractions in soil by visible and near-infrared reflectance spectroscopy

Moron, A. and Cozzolino, D. (2004). Determination of potentially mineralizable nitrogen and nitrogen in particulate organic matter fractions in soil by visible and near-infrared reflectance spectroscopy. Journal of Agricultural Science, 142 (3), 335-343. doi: 10.1017/S0021859604004290

Determination of potentially mineralizable nitrogen and nitrogen in particulate organic matter fractions in soil by visible and near-infrared reflectance spectroscopy

2004

Journal Article

Prediction of colour and pH in grapes using a diode array spectrophotometer (400–1100 nm)

Cozzolino, D., Esler, M.B., Dambergs, R.G., Cynkar, W.U., Boehm, D.R., Francis, I.L. and Gishen, M. (2004). Prediction of colour and pH in grapes using a diode array spectrophotometer (400–1100 nm). Journal of Near Infrared Spectroscopy, 12 (2), 105-111. doi: 10.1255/jnirs.414

Prediction of colour and pH in grapes using a diode array spectrophotometer (400–1100 nm)

2004

Journal Article

Exploring the use of near infrared reflectance spectroscopy (NIRS) to predict trace minerals in legumes

Cozzolino, D. and Moron, A. (2004). Exploring the use of near infrared reflectance spectroscopy (NIRS) to predict trace minerals in legumes. Animal Feed Science and Technology, 111 (1-4), 161-173. doi: 10.1016/j.anifeedsci.2003.08.001

Exploring the use of near infrared reflectance spectroscopy (NIRS) to predict trace minerals in legumes

2004

Conference Publication

Calibration transfer between different instruments for determination of colour in red grapes

Cozzolino, D., Gishen, M., Dambergs, R. G., Cynkar, W. U., Janik, L., Francis, I. L. and Høj, P. B. (2004). Calibration transfer between different instruments for determination of colour in red grapes. 11th International Conference on Near Infrared Spectroscopy, Cordoba, Spain, 2003. West Sussex, United Kingdom: NIR Publications.

Calibration transfer between different instruments for determination of colour in red grapes

2004

Journal Article

Identification of animal meat muscles by visible and near infrared reflectance spectroscopy

Cozzolino, D. and Murray, I. (2004). Identification of animal meat muscles by visible and near infrared reflectance spectroscopy. LWT - Food Science and Technology, 37 (4), 447-452. doi: 10.1016/j.lwt.2003.10.013

Identification of animal meat muscles by visible and near infrared reflectance spectroscopy

2004

Conference Publication

Prediction of colour and pH in grapes using a diode array spectrophotometer (400–1100 nm)

Cozzolino, D., Gishen, M., Dambergs, R. G., Cynkar, W. U., Boehm, D. R., Francis, I. L. and Høj, P. B. (2004). Prediction of colour and pH in grapes using a diode array spectrophotometer (400–1100 nm). 11th International Conference on Near Infrared Spectroscopy, Cordoba, Spain, 2003. West Sussex, United Kingdom: NIR Publications.

Prediction of colour and pH in grapes using a diode array spectrophotometer (400–1100 nm)

2003

Journal Article

Feasibility study on the use of visible and near-infrared Spectroscopy together with chemometrics to discriminate between commercial white wines of different varietal origins

Cozzolino, Daniel, Smyth, Heather Eunice and Gishen, Mark (2003). Feasibility study on the use of visible and near-infrared Spectroscopy together with chemometrics to discriminate between commercial white wines of different varietal origins. Journal of Agricultural and Food Chemistry, 51 (26), 7703-7708. doi: 10.1021/jf034959s

Feasibility study on the use of visible and near-infrared Spectroscopy together with chemometrics to discriminate between commercial white wines of different varietal origins

2003

Journal Article

Exploring the use of near infrared reflectance spectroscopy to study physical Prpoperties and microelements in soils

Moron, A. and Cozzolino, D. (2003). Exploring the use of near infrared reflectance spectroscopy to study physical Prpoperties and microelements in soils. Journal of Near Infrared Spectroscopy, 11 (2), 145-154. doi: 10.1255/jnirs.362

Exploring the use of near infrared reflectance spectroscopy to study physical Prpoperties and microelements in soils

2003

Journal Article

The use of visible and near-infrared reflectance spectroscopy to predict colour on both intact and homogenised pork muscle

Cozzolino, D., Barlocco, N., Vadell, A., Ballesteros, F. and Gallieta, G. (2003). The use of visible and near-infrared reflectance spectroscopy to predict colour on both intact and homogenised pork muscle. LWT - Food Science and Technology, 36 (2), 195-202. doi: 10.1016/S0023-6438(02)00199-8

The use of visible and near-infrared reflectance spectroscopy to predict colour on both intact and homogenised pork muscle

2003

Journal Article

The potential of near-infrared reflectance spectroscopy to analyse soil chemical and physical characteristics

Cozzolino, D. and Morón, A. (2003). The potential of near-infrared reflectance spectroscopy to analyse soil chemical and physical characteristics. Journal of Agricultural Science, 140 (1), 65-71. doi: 10.1017/S0021859602002836

The potential of near-infrared reflectance spectroscopy to analyse soil chemical and physical characteristics

2003

Journal Article

The use of near infrared spectroscopy for grape quality measurement

Dambergs, R. G., Cozzolino, D., Esler, M. B., Cynkar, W. U., Kambouris, A., Francis, I. L., Høj, P. B. and Gishen, M. (2003). The use of near infrared spectroscopy for grape quality measurement. Australian and New Zealand Grapegrower and Winemaker, 473a, 69-76.

The use of near infrared spectroscopy for grape quality measurement

2003

Journal Article

Determination of honey quality components by near infrared reflectance spectroscopy

Cozzolino, D and Corbella, E (2003). Determination of honey quality components by near infrared reflectance spectroscopy. Journal of Apicultural Research, 42 (1-2), 16-20. doi: 10.1080/00218839.2003.11101081

Determination of honey quality components by near infrared reflectance spectroscopy

2002

Journal Article

Determination of macro elements in alfalfa and white clover by near-infrared reflectance spectroscopy

Morón, A. and Cozzolino, D. (2002). Determination of macro elements in alfalfa and white clover by near-infrared reflectance spectroscopy. Journal of Agricultural Science, 139 (4), 413-423. doi: 10.1017/S0021859602002605

Determination of macro elements in alfalfa and white clover by near-infrared reflectance spectroscopy

2002

Journal Article

The assessment of the chemical composition of fishmeal by near infrared reflectance spectroscopy

Cozzolino, D., Chree, A., Murray, I. and Scaife, J. R. (2002). The assessment of the chemical composition of fishmeal by near infrared reflectance spectroscopy. Aquaculture Nutrition, 8 (2), 149-155. doi: 10.1046/j.1365-2095.2002.00206.x

The assessment of the chemical composition of fishmeal by near infrared reflectance spectroscopy

2002

Journal Article

Near infrared reflectance spectroscopy in the prediction of chemical characteristics of minced raw fish

Cozzolino, D., Murray, I. and Scaife, J. R. (2002). Near infrared reflectance spectroscopy in the prediction of chemical characteristics of minced raw fish. Aquaculture Nutrition, 8 (1), 1-6. doi: 10.1046/j.1365-2095.2002.00176.x

Near infrared reflectance spectroscopy in the prediction of chemical characteristics of minced raw fish

2002

Journal Article

Use of near infrared reflectance spectroscopy to analyse bovine faecal samples

Cozzolino, D., La Manna, A. and Martins, D. Vaz (2002). Use of near infrared reflectance spectroscopy to analyse bovine faecal samples. Journal of Near Infrared Spectroscopy, 10 (4), 309-314. doi: 10.1255/jnirs.347

Use of near infrared reflectance spectroscopy to analyse bovine faecal samples

2002

Journal Article

Visible and near infrared spectroscopy of beef Longissimus dorsi muscle as a means of dicriminating between pasture and corn silage feeding regimes

Cozzolino, D., Martins, Vaz and Murray, I. (2002). Visible and near infrared spectroscopy of beef Longissimus dorsi muscle as a means of dicriminating between pasture and corn silage feeding regimes. Journal of Near Infrared Spectroscopy, 10 (3), 187-193. doi: 10.1255/jnirs.334

Visible and near infrared spectroscopy of beef Longissimus dorsi muscle as a means of dicriminating between pasture and corn silage feeding regimes

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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