Instrumental Texture Profile Analysis (TPA) of Shelled Sunflower Seed Caramel Snack Using Response Surface Methodology

2007 ◽  
Vol 13 (6) ◽  
pp. 455-460 ◽  
Author(s):  
R.K. Gupta ◽  
Alka Sharma ◽  
R. Sharma
Keyword(s):  
Response Surface Methodology ◽  
Product Quality ◽  
Response Surface ◽  
Sunflower Seed ◽  
Profile Analysis ◽  
Texture Profile Analysis ◽  
Texture Profile ◽  
Texture Analyzer ◽  
Instrumental Texture

Models capable of predicting product quality of shelled sunflower seed caramel snack have been developed using response surface methodology. The textural profile analysis was conducted on the snacks using a texture analyzer. The quality attributes measured were hardness, cohesiveness, springiness, chewiness, and resilience as a function of sugar and sunflower kernels content. The sugar and shelled seed proportions affect the textural characteristics of the product significantly (p<0.05). The values of hardness, cohesiveness, springiness, chewiness, and resilience varied from 2.048 to 42.030 N, 1.002 to 5.003, 1.138 to 1.69, 2.773 to 228.146N, and 0.301 to 0.779, respectively. The highest values of hardness and chewiness were attained for the product with 70:30 sugar and shelled sunflower seed proportion respectively. Similarly the highest values of cohesiveness, springiness and resilience were observed in 50 : 30, 50 : 40, and 50 : 50 proportions respectively. The lowest values of hardness and chewiness were observed in 50 : 50 (sugar: shelled sunflower seed) proportion respectively. Similarly the lowest values of cohesiveness were observed in 70: 50 whereas the lowest values of springiness and resilience were observed in 70 : 30 proportions respectively. Hardness, cohesiveness, and chewiness trended to increase whereas springiness and resilience decreased with increase in sugar proportion.

Measurement of Instrumental Texture Profile Analysis (TPA) of Foods

2021 ◽  
pp. 427-465
Author(s):  
Mohammad Shafiur Rahman ◽  
Zahir Humaid Al-Attabi ◽  
Nasser Al-Habsi ◽  
Mohammed Al-Khusaibi
Keyword(s):  
Profile Analysis ◽  
Texture Profile Analysis ◽  
Texture Profile ◽  
Instrumental Texture

Texture profile analysis of low fat milk nuggets prepared with 2% fat corrected milk and skim milk coagulum and extended with optimum levels of barnyard millet flour and finger millet flour

2017 ◽  
Vol 36 (04) ◽  
Author(s):  
Jyanendr Kumar Shahi ◽  
Ragini Kumari ◽  
Rakesh Kumar ◽  
Geeta Chauhan ◽  
Sanjeev Kumar Roy
Keyword(s):  
Finger Millet ◽  
Profile Analysis ◽  
Skim Milk ◽  
Food Product ◽  
Texture Profile Analysis ◽  
Consumer Acceptability ◽  
Low Fat ◽  
Barnyard Millet ◽  
Texture Profile ◽  
Instrumental Texture

Texture profile analysis of any food product shows correlation with sensory and overall consumer acceptability of the developed milk products. Instrumental texture profile analysis was conducted on low fat milk nuggets prepared with 2% fat milk coagulum and skim milk coagulum and extended with optimum levels of barnyard millet flour and finger millet flour. The texture profile analysis results showed higher values for hardness, springiness, cohesiveness, gumminess and chewiness for the milk nuggets prepared with 2% fat milk coagulum as compared to the nuggets prepared with skim milk coagulum.

Pengaruh Varietas dan Lama Fermentasi Terhadap Kualitas Kefir Susu Kacang Tanah (Arachis Hypogaea)

2019 ◽  
Vol 6 (01) ◽  
pp. 42-56
Author(s):  
Klaudia Maris Stella
Keyword(s):  
Protein Content ◽  
Profile Analysis ◽  
Fat Content ◽  
Texture Profile Analysis ◽  
Plate Count ◽  
Total Acid ◽  
Alcohol Content ◽  
Texture Profile ◽  
Total Plate Count

Kefir is one fermented product that has a taste, a yogurt-like consistency color and has a distinctive yeast aroma. Peanuts are economically ranked second after soybeans. As peanut food has important nutritional benefits in the human nutriency of high protein, minerals and essential fatty acids such as linoleic and oleic acids. Peanut milk contains a very high amino acid almost equivalent to the protein content of animal milk and the price is relatively cheap This study aims to determine the effect of varieties and length of fermentation on the quality of peanut milk kefir. The research design used was Completely Randomized Design (RAL) consisting of 2 factor V peanut varieties consisting of 2 levels (Hypoma 1 and Singa) and long L fermentation factor consisting of 3 levels (21, 24 and 27 hours), each of which was repeated 3 times. The observed observations were pH, total acid, alcohol content, protein content, fat content, Total Plate Count (TPC), Texture Profile Analysis (TPA). Treatment of varieties and duration of fermentation of peanut milk kefir have significant effect on pH value, total acid, fat content, Total Plate Count (TPC), significantly affect alcohol content and no significant effect on protein content, Texture Profile Analysis (TPA), organoleptic aroma, taste and texture. Quality of peanut milk kefir produced on lion varieties with 24 hours fermentation time of total acid 6.43%, alcohol content 2.84%, protein content 2.80%, Total Plate Count (TPC) 30.67 x 103 CFU and Adhesiveness 1.324 g/s.

Relationship between Sensory Textural Attributes and near Infrared Spectra of Cooked Rice

2007 ◽  
Vol 15 (5) ◽  
pp. 333-340 ◽  
Author(s):  
Weena Srisawas ◽  
Vinod K. Jindal ◽  
Warunee Thanapase
Keyword(s):  
Near Infrared ◽  
Profile Analysis ◽  
Indica Rice ◽  
Nir Spectroscopy ◽  
Texture Profile Analysis ◽  
Eating Quality ◽  
Least Squares Regression ◽  
Texture Profile ◽  
Cooked Rice ◽  
Instrumental Texture

Fourteen varieties of Thai indica rice, cooked with five water-to-rice ratios ranging from 1.3 to 2.5 on a weight basis, were characterised by sensory and instrumental texture profile analysis. The potential of near infrared (NIR) reflectance spectroscopy was investigated as an alternative tool for evaluating eating quality attributes of cooked rice by developing predictive models for sensory hardness, stickiness and glossiness. Partial least squares regression models were developed which predicted sensory hardness and stickiness slightly better than the glossiness with r2v values ranging from 0.88 to 0.91 and standard errors of prediction ( SEP) lower than 0.4 unit score on nine-point sensory intensity scales. Results indicated that NIR spectroscopy-based models could be used for estimating the sensory hardness, stickiness and glossiness scores of cooked rice with higher accuracy (lower SEP) compared to the instrumental texture profile analysis based-models.

Sign in / Sign up

Export Citation Format

Share Document