Development of hybrid stacking machine learning for evaluating parameters affecting refrigerated shrimp coated with chitosan-loaded Salvia officinalis nanoemulsions
This study investigated the effects of chitosan coatings containing Salvia officinalis L. essential oil nanoemulsion (NEO) at concentrations of 1 % and 3 % NEO (Ch-NEO-1 and Ch-NEO-3) on refrigerated shrimp quality for 12 days. A hybrid stacking ensemble method was proposed to assess treatment perfo...
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Elsevier
2025-06-01
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| Series: | Applied Food Research |
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| Online Access: | http://www.sciencedirect.com/science/article/pii/S2772502225002252 |
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| author | Mehran Sayadi Elahe Abedi Najmeh Oliyaei Maryam Mousavifard |
| author_facet | Mehran Sayadi Elahe Abedi Najmeh Oliyaei Maryam Mousavifard |
| author_sort | Mehran Sayadi |
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| description | This study investigated the effects of chitosan coatings containing Salvia officinalis L. essential oil nanoemulsion (NEO) at concentrations of 1 % and 3 % NEO (Ch-NEO-1 and Ch-NEO-3) on refrigerated shrimp quality for 12 days. A hybrid stacking ensemble method was proposed to assess treatment performance over time. It aggregates a support vector machine (SVM), extreme gradient boosting (XGBoost), and random forest (RF) as a meta-learner. The droplet size of the EO nanoemulsion was approximately 156 nm, and FTIR spectroscopy confirmed the encapsulation of the EO. The results showed that coating shrimp with Ch-NEO-3 positively inhibited lipid oxidation. The chemical results showed that the pH of all groups increased during storage, and the pH of the control group reached 11.14 ± 0.13, while it was 8.67±0.91 for the Ch-NEO-3 treated group. Moreover, PV and TBARS values of Ch-NEO-1 (14.51±0.02 meq O2 /kg lipid and 0.59± 0.01 mg MDA/kg) and Ch-NEO-3 (14.32±0.04 and 0.56± 0.01 mg MDA/kg) treated groups were significantly lower than those of control (1.41± 0.09 mg MDA/kg) after 12 days (p < 0.05). In addition, active Ch-NEO-3 coating showed antibacterial effects and lowered TVC, LAB and Enterobacteriaceae to 6.38± 0.11 log CFU/g, 2.06± 0.03 log CFU/g, and 2.47±0.12 log CFU/g, respectively, which was in line with the TVBN results. Shrimp coated with Ch and Ch-NEOs also have higher sensor scores than the control. The hybrid model consistently achieved high R² values, such as R2-train=0.986 and R2-test=0.986 for pH and R2-train=0.958 and R2-test=0.997 for overall acceptability, while maintaining low mean absolute error (MAE) values, notably 0.105 for pH and 0.138 for overall acceptability. In contrast, the individual models exhibited signs of overfitting; for example, for TABRS, XGBoost achieved an impressive R² of 0.998 in training but decreased to 0.695 in testing, and RF showed a significant gap between its training (R² = 0.926) and testing (R² = 0.595) performances. Similarly, SVR struggled with overfitting, yielding R² values of 0.924 for training and 0.830 for testing in the color assessment. The hybrid model's ability to maintain closely aligned R² values for training and testing across various properties underscores its robustness and reliability, highlighting its effectiveness over the standalone models. |
| format | Article |
| id | doaj-art-a932f3df047f4dd2a3e862fda9a3fc07 |
| institution | Kabale University |
| issn | 2772-5022 |
| language | English |
| publishDate | 2025-06-01 |
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| spelling | doaj-art-a932f3df047f4dd2a3e862fda9a3fc072025-08-20T03:31:20ZengElsevierApplied Food Research2772-50222025-06-015110091710.1016/j.afres.2025.100917Development of hybrid stacking machine learning for evaluating parameters affecting refrigerated shrimp coated with chitosan-loaded Salvia officinalis nanoemulsionsMehran Sayadi0Elahe Abedi1Najmeh Oliyaei2Maryam Mousavifard3Department of Food Safety and Hygiene, Faculty of Health, Fasa University of Medical Sciences, Fasa, IranDepartment of Food Science and Technology, Faculty of Agriculture, Fasa University, Fasa, Iran; Corresponding authors.Department of Food Science and Technology and Seafood Processing Research Center, School of Agriculture, Shiraz University, Shiraz, Iran; Corresponding authors.Department of Civil Engineering, Faculty of Engineering, Fasa University, Fasa, IranThis study investigated the effects of chitosan coatings containing Salvia officinalis L. essential oil nanoemulsion (NEO) at concentrations of 1 % and 3 % NEO (Ch-NEO-1 and Ch-NEO-3) on refrigerated shrimp quality for 12 days. A hybrid stacking ensemble method was proposed to assess treatment performance over time. It aggregates a support vector machine (SVM), extreme gradient boosting (XGBoost), and random forest (RF) as a meta-learner. The droplet size of the EO nanoemulsion was approximately 156 nm, and FTIR spectroscopy confirmed the encapsulation of the EO. The results showed that coating shrimp with Ch-NEO-3 positively inhibited lipid oxidation. The chemical results showed that the pH of all groups increased during storage, and the pH of the control group reached 11.14 ± 0.13, while it was 8.67±0.91 for the Ch-NEO-3 treated group. Moreover, PV and TBARS values of Ch-NEO-1 (14.51±0.02 meq O2 /kg lipid and 0.59± 0.01 mg MDA/kg) and Ch-NEO-3 (14.32±0.04 and 0.56± 0.01 mg MDA/kg) treated groups were significantly lower than those of control (1.41± 0.09 mg MDA/kg) after 12 days (p < 0.05). In addition, active Ch-NEO-3 coating showed antibacterial effects and lowered TVC, LAB and Enterobacteriaceae to 6.38± 0.11 log CFU/g, 2.06± 0.03 log CFU/g, and 2.47±0.12 log CFU/g, respectively, which was in line with the TVBN results. Shrimp coated with Ch and Ch-NEOs also have higher sensor scores than the control. The hybrid model consistently achieved high R² values, such as R2-train=0.986 and R2-test=0.986 for pH and R2-train=0.958 and R2-test=0.997 for overall acceptability, while maintaining low mean absolute error (MAE) values, notably 0.105 for pH and 0.138 for overall acceptability. In contrast, the individual models exhibited signs of overfitting; for example, for TABRS, XGBoost achieved an impressive R² of 0.998 in training but decreased to 0.695 in testing, and RF showed a significant gap between its training (R² = 0.926) and testing (R² = 0.595) performances. Similarly, SVR struggled with overfitting, yielding R² values of 0.924 for training and 0.830 for testing in the color assessment. The hybrid model's ability to maintain closely aligned R² values for training and testing across various properties underscores its robustness and reliability, highlighting its effectiveness over the standalone models.http://www.sciencedirect.com/science/article/pii/S2772502225002252ChitosanEdible coatingSalvia officinalis essential oil nanoemulsionHybrid stacking machine learning modelRefrigerated shrimpShelf life |
| spellingShingle | Mehran Sayadi Elahe Abedi Najmeh Oliyaei Maryam Mousavifard Development of hybrid stacking machine learning for evaluating parameters affecting refrigerated shrimp coated with chitosan-loaded Salvia officinalis nanoemulsions Applied Food Research Chitosan Edible coating Salvia officinalis essential oil nanoemulsion Hybrid stacking machine learning model Refrigerated shrimp Shelf life |
| title | Development of hybrid stacking machine learning for evaluating parameters affecting refrigerated shrimp coated with chitosan-loaded Salvia officinalis nanoemulsions |
| title_full | Development of hybrid stacking machine learning for evaluating parameters affecting refrigerated shrimp coated with chitosan-loaded Salvia officinalis nanoemulsions |
| title_fullStr | Development of hybrid stacking machine learning for evaluating parameters affecting refrigerated shrimp coated with chitosan-loaded Salvia officinalis nanoemulsions |
| title_full_unstemmed | Development of hybrid stacking machine learning for evaluating parameters affecting refrigerated shrimp coated with chitosan-loaded Salvia officinalis nanoemulsions |
| title_short | Development of hybrid stacking machine learning for evaluating parameters affecting refrigerated shrimp coated with chitosan-loaded Salvia officinalis nanoemulsions |
| title_sort | development of hybrid stacking machine learning for evaluating parameters affecting refrigerated shrimp coated with chitosan loaded salvia officinalis nanoemulsions |
| topic | Chitosan Edible coating Salvia officinalis essential oil nanoemulsion Hybrid stacking machine learning model Refrigerated shrimp Shelf life |
| url | http://www.sciencedirect.com/science/article/pii/S2772502225002252 |
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