What is he best known for?
The fields of study he is best known for:
- Biochemistry
- Food science
- Botany
His primary areas of investigation include Wine, Analytical chemistry, Chemometrics, Principal component analysis and Partial least squares regression.
His Wine research is classified as research in Food science.
The concepts of his Analytical chemistry study are interwoven with issues in Near infrared reflectance spectroscopy, Near-infrared spectroscopy, Near-Infrared Spectrometry, Multivariate analysis and Coefficient of determination.
Chemometrics is a subfield of Chromatography that Daniel Cozzolino explores.
His study looks at the intersection of Principal component analysis and topics like Linear discriminant analysis with Vintage.
His Partial least squares regression study combines topics from a wide range of disciplines, such as Soil carbon, Manganese, Crop rotation and Chemical composition.
His most cited work include:
- Prediction of phenolic compounds in red wine fermentations by visible and near infrared spectroscopy (241 citations)
- Identification of animal meat muscles by visible and near infrared reflectance spectroscopy (197 citations)
- FEASIBILITY STUDY ON THE USE OF VISIBLE AND NEAR INFRARED SPECTROSCOPY TOGETHER WITH CHEMOMETRICS TO DISCRIMINATE BETWEEN COMMERCIAL WHITE WINES OF DIFFERENT VARIETAL ORIGINS (190 citations)
What are the main themes of his work throughout his whole career to date?
His primary scientific interests are in Food science, Near-infrared spectroscopy, Analytical chemistry, Partial least squares regression and Wine.
His Food science research includes themes of Yeast and Botany.
Within one scientific family, he focuses on topics pertaining to Near infrared reflectance spectroscopy under Analytical chemistry, and may sometimes address concerns connected to Reflectance spectroscopy.
His biological study spans a wide range of topics, including Cross-validation, Sample preparation, Coefficient of determination, Attenuated total reflection and Principal component analysis.
His Wine research is multidisciplinary, incorporating elements of Mass spectrometry, Fermentation, Electronic nose and Chemometrics.
In his research, Multivariate analysis is intimately related to Linear discriminant analysis, which falls under the overarching field of Chemometrics.
He most often published in these fields:
- Food science (32.09%)
- Near-infrared spectroscopy (28.61%)
- Analytical chemistry (28.88%)
What were the highlights of his more recent work (between 2018-2021)?
- Food science (32.09%)
- Chemometrics (27.54%)
- Partial least squares regression (28.07%)
In recent papers he was focusing on the following fields of study:
His primary areas of study are Food science, Chemometrics, Partial least squares regression, KAKADU PLUM and Terminalia.
His Food science study combines topics from a wide range of disciplines, such as Composition and Sonication.
His Chemometrics research incorporates themes from Sample preparation, Wine, Near-infrared spectroscopy and High throughput analysis.
Daniel Cozzolino regularly ties together related areas like Ultraviolet visible spectroscopy in his Wine studies.
His Near-infrared spectroscopy study incorporates themes from Complex matrix and Analytical chemistry.
His Partial least squares regression research integrates issues from Cultivar, Chromatography, Linear discriminant analysis, Attenuated total reflection and Principal component analysis.
Between 2018 and 2021, his most popular works were:
- A review of methods for the detection of pathogenic microorganisms (87 citations)
- Contributions of Fourier-transform mid infrared (FT-MIR) spectroscopy to the study of fruit and vegetables: A review (68 citations)
- Bacterial-nanostructure interactions: The role of cell elasticity and adhesion forces. (39 citations)
In his most recent research, the most cited papers focused on:
- Biochemistry
- Food science
- Botany
Daniel Cozzolino focuses on Chemometrics, Food science, Risk analysis, Near-infrared spectroscopy and Infrared spectroscopy.
He has researched Chemometrics in several fields, including Partial least squares regression and Biochemical engineering.
The various areas that Daniel Cozzolino examines in his Partial least squares regression study include Regression analysis and Agricultural science.
His work deals with themes such as Lipidome, Lipid metabolism and Extraction, Lipid extraction, which intersect with Food science.
Daniel Cozzolino combines subjects such as Sampling, Electronic engineering and Calibration with his study of Near-infrared spectroscopy.
The Infrared spectroscopy study combines topics in areas such as Food quality, Wine and Pattern recognition.
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