Evaluation of sensory and texture profile analysis properties of stored Khalal Barhi dates nondestructively using Vis/NIR spectroscopy

2019 ◽  
Vol 42 (6) ◽  
Author(s):  
Abdullah M. Alhamdan ◽  
Adil Fickak ◽  
Ahmed R. Atia
Keyword(s):  
Profile Analysis ◽  
Nir Spectroscopy ◽  
Texture Profile Analysis ◽  
Texture Profile

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.

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
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