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

446 works between 1996 and 2025
All (446) Journal Article (380) Book Chapter (37) Conference Publication (28) Book (1)

441 - 446 of 446 works

2002

Journal Article

Visible/near infrared reflectance spectroscopy for predicting composition and tracing system of production of beef muscle

Cozzolino, D, De Mattos, D and Martins, DV (2002). Visible/near infrared reflectance spectroscopy for predicting composition and tracing system of production of beef muscle. Animal Science, 74, 477-484. doi: 10.1017/S1357729800052632

Visible/near infrared reflectance spectroscopy for predicting composition and tracing system of production of beef muscle

2002

Journal Article

Low frequency of melanocortin-4 receptor (MC4R) mutations in a Mediterranean population with early-onset obesity

del Giudice, EM, Cirillo, G, Nigro, , Santoro, N, D'Urso, L, Raimondo, P, Cozzolino, D, Scafato, D and Perrone, L (2002). Low frequency of melanocortin-4 receptor (MC4R) mutations in a Mediterranean population with early-onset obesity. International Journal of Obesity, 26 (5), 647-651. doi: 10.1038/sj/ijo/0801983

Low frequency of melanocortin-4 receptor (MC4R) mutations in a Mediterranean population with early-onset obesity

2002

Journal Article

Determination of dry matter and crude protein contents of undried forages by near-infrared reflectance spectroscopy

Cozzolino, Daniel and Labandera, Marcel (2002). Determination of dry matter and crude protein contents of undried forages by near-infrared reflectance spectroscopy. Journal of the Science of Food and Agriculture, 82 (4), 380-384. doi: 10.1002/jsfa.1050

Determination of dry matter and crude protein contents of undried forages by near-infrared reflectance spectroscopy

2002

Journal Article

Effect of sample presentation and animal muscle species on the analysis of meat by near infrared reflectance spectroscopy

Cozzolino, D. and Murray, I. (2002). Effect of sample presentation and animal muscle species on the analysis of meat by near infrared reflectance spectroscopy. Journal of Near Infrared Spectroscopy, 10 (1), 37-44. doi: 10.1255/jnirs.319

Effect of sample presentation and animal muscle species on the analysis of meat by near infrared reflectance spectroscopy

2000

Journal Article

The use of near-infrared reflectance spectroscopy (NIRS) to predict the composition of whole maize plants

Cozzolino, D., Fassio, A. and Gimenez, A. (2000). The use of near-infrared reflectance spectroscopy (NIRS) to predict the composition of whole maize plants. Journal of the Science of Food and Agriculture, 81 (1), 142-146. doi: 10.1002/1097-0010(20010101)81:13.0.co;2-i

The use of near-infrared reflectance spectroscopy (NIRS) to predict the composition of whole maize plants

1996

Journal Article

Visible and near infrared reflectance spectroscopy for the determination of moisture, fat and protein in chicken breast and thigh muscle

Cozzolino, D., Murray, I., Paterson, R. and Scaife, J. (1996). Visible and near infrared reflectance spectroscopy for the determination of moisture, fat and protein in chicken breast and thigh muscle. Journal of Near Infrared Spectroscopy, 4 (1), 213-223. doi: 10.1255/jnirs.92

Visible and near infrared reflectance spectroscopy for the determination of moisture, fat and protein in chicken breast and thigh muscle

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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