Mid-Infrared Spectroscopy for Predicting Goat Milk Coagulation Properties
The assessment of milk coagulation properties (MCPs) is crucial for enhancing goat cheese production and quality. In this study, 501 bulk goat milk samples were collected from various farms to evaluate the MCPs. Traditionally, cheesemaking aptitude is evaluated using lactodynamographic analysis, a r...
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MDPI AG
2025-07-01
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| author | Arianna Goi Silvia Magro Luigi Lanni Carlo Boselli Massimo De Marchi |
| author_facet | Arianna Goi Silvia Magro Luigi Lanni Carlo Boselli Massimo De Marchi |
| author_sort | Arianna Goi |
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| description | The assessment of milk coagulation properties (MCPs) is crucial for enhancing goat cheese production and quality. In this study, 501 bulk goat milk samples were collected from various farms to evaluate the MCPs. Traditionally, cheesemaking aptitude is evaluated using lactodynamographic analysis, a reliable but time-consuming laboratory method. Mid-infrared spectroscopy (MIRS) offers a promising alternative for the large-scale prediction of goat milk’s technological traits. Reference MCP measurements were paired with mid-infrared spectra, and prediction models were developed using partial least squares regression, with accuracy evaluated through cross- and external validation. The ability of MIRS to classify milk samples by coagulation aptitude was evaluated using partial least squares discriminant analysis. Only the model for rennet coagulation time obtained sufficient accuracy to be applied for screening (R<sup>2</sup><sub>CrV</sub> = 0.68; R<sup>2</sup><sub>Ext</sub> = 0.66; RPD = 2.05). Lower performance was observed for curd-firming time (R<sup>2</sup><sub>CrV</sub> = 0.33; R<sup>2</sup><sub>Ext</sub> = 0.27; RPD = 1.42) and curd firmness (R<sup>2</sup><sub>CrV</sub> = 0.55; R<sup>2</sup><sub>Ext</sub> = 0.43; RPD = 1.35). Classification of high coagulation aptitude achieved balanced accuracy values of 0.81 (calibration) and 0.74 (validation). With further model refinement and larger calibration datasets, MIRS may become a resource for the dairy-goat sector to monitor and improve milk suitability for cheesemaking. |
| format | Article |
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| publishDate | 2025-07-01 |
| publisher | MDPI AG |
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| series | Foods |
| spelling | doaj-art-d623d0f8e6a4466e8e8094a65e9cc7d32025-07-11T14:40:19ZengMDPI AGFoods2304-81582025-07-011413240310.3390/foods14132403Mid-Infrared Spectroscopy for Predicting Goat Milk Coagulation PropertiesArianna Goi0Silvia Magro1Luigi Lanni2Carlo Boselli3Massimo De Marchi4Department of Agronomy, Food, Natural Resources, Animals and Environment, University of Padova, Viale dell’Università 16, 35020 Legnaro, ItalyDepartment of Agronomy, Food, Natural Resources, Animals and Environment, University of Padova, Viale dell’Università 16, 35020 Legnaro, ItalyIstituto Zooprofilattico Sperimentale del Lazio E Della Toscana “M. Aleandri”—National Reference Centre for Ovine and Caprine Milk and Dairy Products Quality, Via Appia Nuova 1411, 00178 Rome, ItalyIstituto Zooprofilattico Sperimentale del Lazio E Della Toscana “M. Aleandri”—National Reference Centre for Ovine and Caprine Milk and Dairy Products Quality, Via Appia Nuova 1411, 00178 Rome, ItalyDepartment of Agronomy, Food, Natural Resources, Animals and Environment, University of Padova, Viale dell’Università 16, 35020 Legnaro, ItalyThe assessment of milk coagulation properties (MCPs) is crucial for enhancing goat cheese production and quality. In this study, 501 bulk goat milk samples were collected from various farms to evaluate the MCPs. Traditionally, cheesemaking aptitude is evaluated using lactodynamographic analysis, a reliable but time-consuming laboratory method. Mid-infrared spectroscopy (MIRS) offers a promising alternative for the large-scale prediction of goat milk’s technological traits. Reference MCP measurements were paired with mid-infrared spectra, and prediction models were developed using partial least squares regression, with accuracy evaluated through cross- and external validation. The ability of MIRS to classify milk samples by coagulation aptitude was evaluated using partial least squares discriminant analysis. Only the model for rennet coagulation time obtained sufficient accuracy to be applied for screening (R<sup>2</sup><sub>CrV</sub> = 0.68; R<sup>2</sup><sub>Ext</sub> = 0.66; RPD = 2.05). Lower performance was observed for curd-firming time (R<sup>2</sup><sub>CrV</sub> = 0.33; R<sup>2</sup><sub>Ext</sub> = 0.27; RPD = 1.42) and curd firmness (R<sup>2</sup><sub>CrV</sub> = 0.55; R<sup>2</sup><sub>Ext</sub> = 0.43; RPD = 1.35). Classification of high coagulation aptitude achieved balanced accuracy values of 0.81 (calibration) and 0.74 (validation). With further model refinement and larger calibration datasets, MIRS may become a resource for the dairy-goat sector to monitor and improve milk suitability for cheesemaking.https://www.mdpi.com/2304-8158/14/13/2403mid-infrared spectroscopymilkgoattechnological properties |
| spellingShingle | Arianna Goi Silvia Magro Luigi Lanni Carlo Boselli Massimo De Marchi Mid-Infrared Spectroscopy for Predicting Goat Milk Coagulation Properties Foods mid-infrared spectroscopy milk goat technological properties |
| title | Mid-Infrared Spectroscopy for Predicting Goat Milk Coagulation Properties |
| title_full | Mid-Infrared Spectroscopy for Predicting Goat Milk Coagulation Properties |
| title_fullStr | Mid-Infrared Spectroscopy for Predicting Goat Milk Coagulation Properties |
| title_full_unstemmed | Mid-Infrared Spectroscopy for Predicting Goat Milk Coagulation Properties |
| title_short | Mid-Infrared Spectroscopy for Predicting Goat Milk Coagulation Properties |
| title_sort | mid infrared spectroscopy for predicting goat milk coagulation properties |
| topic | mid-infrared spectroscopy milk goat technological properties |
| url | https://www.mdpi.com/2304-8158/14/13/2403 |
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