Optimization and sensory analysis of a beetroot, apple, and oat-based beverage using response surface methodology

Tuğba Gül Dikme

Makale detayları

Optimization and sensory analysis of a beetroot, apple, and oat-based beverage using response surface methodology

Yazarlar:

Tuğba Gül Dikme

Yayıncı:

Gültekin ÖZDEMİR

Ana Başlıklar:

Beverage Chemistry and Beverage Sensory Science

Dergi:

International Journal of Agriculture Environment and Food Sciences Vol.9 Issue 2, pp.374-383

Belge Tipi:

Makale

Yayın Tarihi:

6/2025

Belge Dili:

İngilizce

Document ID (Org No.):

2001348435

pISSN:

2618-5946

Anahtar kelimeler:

Özet:

 This study aimed to optimize a functional beverage formulation comprising beetroot juice, apple juice, and oats, with a focus on enhancing taste, consistency, and overall acceptability. Optimization was carried out using Response Surface Methodology RSM to identify the ideal proportions of ingredients that would maximize sensory quality. The developed regression models demonstrated high predictive accuracy, with R² values exceeding 0.94, indicating a strong correlation between the experimental data and model predictions. The optimized formulation 10.07 beetroot juice, 59.99 apple juice, and 8.86 oats yielded the highest sensory scores: 8.40 for taste, 7.19 for consistency, and 8.12 for overall acceptability. Lack-of-fit tests confirmed the adequacy and reliability of the models. Results revealed that apple juice effectively moderated the earthy flavor of beetroot juice, while oats improved texture when used at moderate levels but detracted from sensory appeal at higher concentrations. Overall, the study highlights the effectiveness of RSM in optimizing multi-ingredient beverage formulations based on sensory criteria.

 This study aimed to optimize a functional beverage formulation comprising beetroot juice, apple juice, and oats, with a focus on enhancing taste, consistency, and overall acceptability. Optimization was carried out using Response Surface Methodology RSM to identify the ideal proportions of ingredients that would maximize sensory quality. The developed regression models demonstrated high predictive accuracy, with R² values exceeding 0.94, indicating a strong correlation between the experimental data and model predictions. The optimized formulation 10.07 beetroot juice, 59.99 apple juice, and 8.86 oats yielded the highest sensory scores: 8.40 for taste, 7.19 for consistency, and 8.12 for overall acceptability. Lack-of-fit tests confirmed the adequacy and reliability of the models. Results revealed that apple juice effectively moderated the earthy flavor of beetroot juice, while oats improved texture when used at moderate levels but detracted from sensory appeal at higher concentrations. Overall, the study highlights the effectiveness of RSM in optimizing multi-ingredient beverage formulations based on sensory criteria.

 This study aimed to optimize a functional beverage formulation comprising beetroot juice, apple juice, and oats, with a focus on enhancing taste, consistency, and overall acceptability. Optimization was carried out using Response Surface Methodology RSM to identify the ideal proportions of ingredients that would maximize sensory quality. The developed regression models demonstrated high predictive accuracy, with R² values exceeding 0.94, indicating a strong correlation between the experimental data and model predictions. The optimized formulation 10.07 beetroot juice, 59.99 apple juice, and 8.86 oats yielded the highest sensory scores: 8.40 for taste, 7.19 for consistency, and 8.12 for overall acceptability. Lack-of-fit tests confirmed the adequacy and reliability of the models. Results revealed that apple juice effectively moderated the earthy flavor of beetroot juice, while oats improved texture when used at moderate levels but detracted from sensory appeal at higher concentrations. Overall, the study highlights the effectiveness of RSM in optimizing multi-ingredient beverage formulations based on sensory criteria.

 This study aimed to optimize a functional beverage formulation comprising beetroot juice, apple juice, and oats, with a focus on enhancing taste, consistency, and overall acceptability. Optimization was carried out using Response Surface Methodology RSM to identify the ideal proportions of ingredients that would maximize sensory quality. The developed regression models demonstrated high predictive accuracy, with R² values exceeding 0.94, indicating a strong correlation between the experimental data and model predictions. The optimized formulation 10.07 beetroot juice, 59.99 apple juice, and 8.86 oats yielded the highest sensory scores: 8.40 for taste, 7.19 for consistency, and 8.12 for overall acceptability. Lack-of-fit tests confirmed the adequacy and reliability of the models. Results revealed that apple juice effectively moderated the earthy flavor of beetroot juice, while oats improved texture when used at moderate levels but detracted from sensory appeal at higher concentrations. Overall, the study highlights the effectiveness of RSM in optimizing multi-ingredient beverage formulations based on sensory criteria.

Makale detayları

Optimization and sensory analysis of a beetroot, apple, and oat-based beverage using response surface methodology

Yazarlar:

Tuğba Gül Dikme

Yayıncı:

Gültekin ÖZDEMİR

Ana Başlıklar:

Beverage Chemistry and Beverage Sensory Science

Dergi:

International Journal of Agriculture Environment and Food Sciences Vol.9 Issue 2, pp.374-383

Belge Tipi:

Makale

Yayın Tarihi:

6/2025

Belge Dili:

İngilizce

Document ID (Org No.):

2001348435

pISSN:

2618-5946

Fruit-vegetable beverage

Beetroot juice

Apple juice

Oats

Response surface methodology (RSM)

Sensory analysis

Optimization

Sayı

Makale detayları

Yazarlar: Tuğba Gül Dikme

Yayıncı: Gültekin ÖZDEMİR

Ana Başlıklar: Beverage Chemistry and Beverage Sensory Science

Dergi: International Journal of Agriculture Environment and Food Sciences Vol.9 Issue 2, pp.374-383

Belge Tipi: Makale

Yayın Tarihi: 6/2025

Belge Dili: İngilizce

Document ID (Org No.): 2001348435

pISSN: 2618-5946

Sayı

Yazarlar:

Tuğba Gül Dikme

Yayıncı:

Gültekin ÖZDEMİR

Ana Başlıklar:

Beverage Chemistry and Beverage Sensory Science

Dergi:

International Journal of Agriculture Environment and Food Sciences Vol.9 Issue 2, pp.374-383

Belge Tipi:

Makale

Yayın Tarihi:

6/2025

Belge Dili:

İngilizce

Document ID (Org No.):

2001348435

pISSN:

2618-5946