Rapid prediction of essential oils major components by Vis/NIRS models using compositional methods
Essential oils (EOs) have often a major compound, which content is important for the industry. Thus, rapid techniques suitable to analyze the EOs composition are of great interest. Near infrared spectroscopy (NIRS) has proven suitable solutions for many similar targets. NIRS depends on multivariate...
| Main Authors: | , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Elsevier
2022-01-01
|
| Series: | Results in Chemistry |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S2211715622002818 |
| _version_ | 1811198993845190656 |
|---|---|
| author | Anass El Ouaddari Abdelaziz El Amrani Jamal Jamal Eddine José Antonio Cayuela-Sánchez |
| author_facet | Anass El Ouaddari Abdelaziz El Amrani Jamal Jamal Eddine José Antonio Cayuela-Sánchez |
| author_sort | Anass El Ouaddari |
| collection | DOAJ |
| description | Essential oils (EOs) have often a major compound, which content is important for the industry. Thus, rapid techniques suitable to analyze the EOs composition are of great interest. Near infrared spectroscopy (NIRS) has proven suitable solutions for many similar targets. NIRS depends on multivariate correlation methods, which were designed for the real space, with values comprised between - ∞ and + ∞. However, essential oils compounds are compositional data (CoDa), restricted to a simplex space. These are co-dependent data, therefore their multivariate correlation with the spectral variables needs specific methods. This study evaluates predictive models of the contents of cinnamaldehyde, eugenol methyl-ether and thymol, respectively in EOs of cinnamon, clove and thyme, built by using CoDa method. This last was the isometric log-ratio transformation (ILR). Besides, the calibrations set without CoDa methods, were assessed. The results showed clearly the best prediction in external validation exercises was by using ILR. This predictive exercise pointed out the compositional method provided better model robustness than the calibration without this. |
| first_indexed | 2024-04-12T01:40:29Z |
| format | Article |
| id | doaj.art-3dff55b865b3465a8fe4719902073d35 |
| institution | Directory Open Access Journal |
| issn | 2211-7156 |
| language | English |
| last_indexed | 2024-04-12T01:40:29Z |
| publishDate | 2022-01-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Results in Chemistry |
| spelling | doaj.art-3dff55b865b3465a8fe4719902073d352022-12-22T03:53:12ZengElsevierResults in Chemistry2211-71562022-01-014100562Rapid prediction of essential oils major components by Vis/NIRS models using compositional methodsAnass El Ouaddari0Abdelaziz El Amrani1Jamal Jamal Eddine2José Antonio Cayuela-Sánchez3Laboratory of Organic Synthesis, Extraction, and Valorization, Faculty of Sciences Aïn Chock, Hassan II University of Casablanca, B.P 5366 Maarif, Casablanca, MoroccoLaboratory of Organic Synthesis, Extraction, and Valorization, Faculty of Sciences Aïn Chock, Hassan II University of Casablanca, B.P 5366 Maarif, Casablanca, MoroccoLaboratory of Organic Synthesis, Extraction, and Valorization, Faculty of Sciences Aïn Chock, Hassan II University of Casablanca, B.P 5366 Maarif, Casablanca, MoroccoInstituto de la Grasa (CSIC), Campus Universidad Pablo de Olavide, Ed. 46., Ctra. Utrera Km 1, 41013 Sevilla, Spain; Corresponding author.Essential oils (EOs) have often a major compound, which content is important for the industry. Thus, rapid techniques suitable to analyze the EOs composition are of great interest. Near infrared spectroscopy (NIRS) has proven suitable solutions for many similar targets. NIRS depends on multivariate correlation methods, which were designed for the real space, with values comprised between - ∞ and + ∞. However, essential oils compounds are compositional data (CoDa), restricted to a simplex space. These are co-dependent data, therefore their multivariate correlation with the spectral variables needs specific methods. This study evaluates predictive models of the contents of cinnamaldehyde, eugenol methyl-ether and thymol, respectively in EOs of cinnamon, clove and thyme, built by using CoDa method. This last was the isometric log-ratio transformation (ILR). Besides, the calibrations set without CoDa methods, were assessed. The results showed clearly the best prediction in external validation exercises was by using ILR. This predictive exercise pointed out the compositional method provided better model robustness than the calibration without this.http://www.sciencedirect.com/science/article/pii/S2211715622002818CoDaCompositional dataEssential oilNIRS |
| spellingShingle | Anass El Ouaddari Abdelaziz El Amrani Jamal Jamal Eddine José Antonio Cayuela-Sánchez Rapid prediction of essential oils major components by Vis/NIRS models using compositional methods Results in Chemistry CoDa Compositional data Essential oil NIRS |
| title | Rapid prediction of essential oils major components by Vis/NIRS models using compositional methods |
| title_full | Rapid prediction of essential oils major components by Vis/NIRS models using compositional methods |
| title_fullStr | Rapid prediction of essential oils major components by Vis/NIRS models using compositional methods |
| title_full_unstemmed | Rapid prediction of essential oils major components by Vis/NIRS models using compositional methods |
| title_short | Rapid prediction of essential oils major components by Vis/NIRS models using compositional methods |
| title_sort | rapid prediction of essential oils major components by vis nirs models using compositional methods |
| topic | CoDa Compositional data Essential oil NIRS |
| url | http://www.sciencedirect.com/science/article/pii/S2211715622002818 |
| work_keys_str_mv | AT anasselouaddari rapidpredictionofessentialoilsmajorcomponentsbyvisnirsmodelsusingcompositionalmethods AT abdelazizelamrani rapidpredictionofessentialoilsmajorcomponentsbyvisnirsmodelsusingcompositionalmethods AT jamaljamaleddine rapidpredictionofessentialoilsmajorcomponentsbyvisnirsmodelsusingcompositionalmethods AT joseantoniocayuelasanchez rapidpredictionofessentialoilsmajorcomponentsbyvisnirsmodelsusingcompositionalmethods |