Prediction of traditionally utilised wheat dough technological quality parameters from Mixolab values: development and evaluation of regression models
Само за регистроване кориснике
2014
Аутори
Mastilović, JasnaKevrešan, Žarko S.
Torbica, Aleksandra
Janić-Hajnal, Elizabet
Živančev, Dragan
Чланак у часопису (Објављена верзија)
Метаподаци
Приказ свих података о документуАпстракт
The research was conducted with the aim to investigate the possibility of Farinograph, Extensograph and Amylograph values prediction with linear and/or multiple Mixolab regression models. In total, 163 flour samples were divided based on Machalanobis distances into three sets: prediction, validation and external sample set. Determination coefficients ranged from 0.145 to 0.640 for linear regression models and from 0.279 to 0.739 for multiple regression models. Internal and external validation of developed regression models was conducted. Testing of developed models resulted in a high share of samples for which predicted values were out of the ranges of method official reproducibility and a high share of samples for which predicted values were out of the quality level range obtained by analytical measurement. It was concluded that it is impossible to develop applicable regression models for prediction of Farinograph, Extensograph and Amylograph parameters on the basis of Mixolab values ...from standard protocol.
Кључне речи:
Amylograph / Extensograph / Farinograph / Mixolab / wheat qualityИзвор:
International Journal of Food Science & Technology, 2014, 49, 12, 2685-2691Издавач:
- Wiley, Hoboken
Финансирање / пројекти:
- Развој и примена нових и традиционалних технологија у производњи конкурентних прехрамбених производа са додатом вредношћу за европско и светско тржиште - Створимо богатство из богатства Србије (RS-MESTD-Integrated and Interdisciplinary Research (IIR or III)-46001)
- Вредновање квалитета и оптимизација прераде пшенице у светлу климатских промена (RS-MESTD-Technological Development (TD or TR)-31007)
DOI: 10.1111/ijfs.12601
ISSN: 0950-5423
WoS: 000344528200020
Scopus: 2-s2.0-84939255118
Колекције
Институција/група
FiVeRTY - JOUR AU - Mastilović, Jasna AU - Kevrešan, Žarko S. AU - Torbica, Aleksandra AU - Janić-Hajnal, Elizabet AU - Živančev, Dragan PY - 2014 UR - http://fiver.ifvcns.rs/handle/123456789/1314 AB - The research was conducted with the aim to investigate the possibility of Farinograph, Extensograph and Amylograph values prediction with linear and/or multiple Mixolab regression models. In total, 163 flour samples were divided based on Machalanobis distances into three sets: prediction, validation and external sample set. Determination coefficients ranged from 0.145 to 0.640 for linear regression models and from 0.279 to 0.739 for multiple regression models. Internal and external validation of developed regression models was conducted. Testing of developed models resulted in a high share of samples for which predicted values were out of the ranges of method official reproducibility and a high share of samples for which predicted values were out of the quality level range obtained by analytical measurement. It was concluded that it is impossible to develop applicable regression models for prediction of Farinograph, Extensograph and Amylograph parameters on the basis of Mixolab values from standard protocol. PB - Wiley, Hoboken T2 - International Journal of Food Science & Technology T1 - Prediction of traditionally utilised wheat dough technological quality parameters from Mixolab values: development and evaluation of regression models EP - 2691 IS - 12 SP - 2685 VL - 49 DO - 10.1111/ijfs.12601 ER -
@article{ author = "Mastilović, Jasna and Kevrešan, Žarko S. and Torbica, Aleksandra and Janić-Hajnal, Elizabet and Živančev, Dragan", year = "2014", abstract = "The research was conducted with the aim to investigate the possibility of Farinograph, Extensograph and Amylograph values prediction with linear and/or multiple Mixolab regression models. In total, 163 flour samples were divided based on Machalanobis distances into three sets: prediction, validation and external sample set. Determination coefficients ranged from 0.145 to 0.640 for linear regression models and from 0.279 to 0.739 for multiple regression models. Internal and external validation of developed regression models was conducted. Testing of developed models resulted in a high share of samples for which predicted values were out of the ranges of method official reproducibility and a high share of samples for which predicted values were out of the quality level range obtained by analytical measurement. It was concluded that it is impossible to develop applicable regression models for prediction of Farinograph, Extensograph and Amylograph parameters on the basis of Mixolab values from standard protocol.", publisher = "Wiley, Hoboken", journal = "International Journal of Food Science & Technology", title = "Prediction of traditionally utilised wheat dough technological quality parameters from Mixolab values: development and evaluation of regression models", pages = "2691-2685", number = "12", volume = "49", doi = "10.1111/ijfs.12601" }
Mastilović, J., Kevrešan, Ž. S., Torbica, A., Janić-Hajnal, E.,& Živančev, D.. (2014). Prediction of traditionally utilised wheat dough technological quality parameters from Mixolab values: development and evaluation of regression models. in International Journal of Food Science & Technology Wiley, Hoboken., 49(12), 2685-2691. https://doi.org/10.1111/ijfs.12601
Mastilović J, Kevrešan ŽS, Torbica A, Janić-Hajnal E, Živančev D. Prediction of traditionally utilised wheat dough technological quality parameters from Mixolab values: development and evaluation of regression models. in International Journal of Food Science & Technology. 2014;49(12):2685-2691. doi:10.1111/ijfs.12601 .
Mastilović, Jasna, Kevrešan, Žarko S., Torbica, Aleksandra, Janić-Hajnal, Elizabet, Živančev, Dragan, "Prediction of traditionally utilised wheat dough technological quality parameters from Mixolab values: development and evaluation of regression models" in International Journal of Food Science & Technology, 49, no. 12 (2014):2685-2691, https://doi.org/10.1111/ijfs.12601 . .