Non-linear viscoelastic behavior of cooked white, brown, and germinated brown Thai jasmine rice by large deformation relaxation test

Sirisomboon, Panmanas; Kaewsorn, Kannapot; Thanimkarn, Satthawat; Phetpan, Kittisak

doi:10.1080/10942912.2016.1213741

Cited by 5 publications

(4 citation statements)

References 27 publications

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“…The rice cooking method followed that described by Sirisomboon et al [ 26 ]. Home electronic rice cookers (RC-10 MM, Toshiba, Thailand) were used to cook 200 g GBR samples using the water-to-rice ratio of 1.6:1 recommended for GBR by rice producers.…”

Section: Methodsmentioning

confidence: 99%

Evaluation of Precision and Sensitivity of Back Extrusion Test for Measuring Textural Qualities of Cooked Germinated Brown Rice in Production Process

Kaewsorn,

Maichoon,

Pornchaloempong

et al. 2023

Foods

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The textural qualities of cooked rice may be understood as a dominant property and indicator of eating quality. In this study, we evaluated the precision and sensitivity of a back extrusion (BE) test for the texture of cooked germinated brown rice (GBR) in a production process. BE testing of the textural properties of cooked GBR rice showed a high precision of measurement in hardness, toughness and stickiness tests which indicated by the repeatability and reproductivity test but the sensitivity indicated by coefficient of variation of the texture properties. The findings of our study of the effects on cooked GBR texture of different soaking and incubation durations in the production of Khao Dawk Mali 105 (KDML 105) GBR, as measured by BE testing, confirmed that our original protocol for evaluation of the precision and sensitivity of this texture measurement method. The coefficients of determination (R2) of hardness, toughness and stickiness tests and the incubation time at after 48 hours of soaking were 0.82, 0.81 and 0.64, respectively. The repeatability and reproducibility of reliable measurements, which have a low standard deviation of the greatest difference between replicates, are considered to indicate high precision. A high coefficient of variation where relatively wide variations in the absolute value of the property can be detected indicates high sensitivity when small resolutions can be detected, and vice versa. The sensitivity of the BE tests for stickiness, toughness and hardness all ranked higher, in that order, than the sensitivity of the method for adhesiveness, which ranked lowest. The coefficients of variation of these texture parameters were 31.26, 20.59, 19.41 and 18.72, respectively. However, the correlation coefficients among the texture properties obtained by BE testing were not related to the precision or sensitivity of the test. By obtaining these results, we verified that our original protocol for the determination of the precision and sensitivity of food texture measurements which was successfully used for GBR texture measurement.

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Section: Methodsmentioning

confidence: 99%

Evaluation of Precision and Sensitivity of Back Extrusion Test for Measuring Textural Qualities of Cooked Germinated Brown Rice in Production Process

Kaewsorn,

Maichoon,

Pornchaloempong

et al. 2023

Foods

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“…The rice-cooking technique utilized by Sirisomboon et al [32] involved the use of personal rice cookers (RC−10 MM, Toshiba, Bangkok, Thailand) to prepare 200 g of GBR samples using water-to-rice ratios of 1.6:1. To produce cooked rice with the customary texture that customers want, the required water-to-rice ratio was employed.…”

Section: Methods Of Cooking Ricementioning

confidence: 99%

Modeling Textural Properties of Cooked Germinated Brown Rice Using the near-Infrared Spectra of Whole Grain

Kaewsorn,

Phanomsophon,

Maichoon

et al. 2023

Foods

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If a non-destructive and rapid technique to determine the textural properties of cooked germinated brown rice (GBR) was developed, it would hold immense potential for the enhancement of the quality control process in large-scale commercial rice production. We combined the Fourier transform near-infrared (NIR) spectral data of uncooked whole grain GBR with partial least squares (PLS) regression and an artificial neural network (ANN) for an evaluation of the textural properties of cooked germinated brown rice (GBR); in addition, data separation and spectral pretreatment methods were investigated. The ANN was outperformed in the evaluation of hardness by a back extrusion test of cooked GBR using the smoothing combined with the standard normal variate pretreated NIR spectra of 188 whole grain samples in the range of 4000–12,500 cm−1. The calibration sample set was separated from the prediction set by the Kennard–Stone method. The best ANN model for hardness, toughness, and adhesiveness provided R2, r2, RMSEC, RMSEP, Bias, and RPD values of 1.00, 0.94, 0.10 N, 0.77 N, 0.02 N, and 4.3; 1.00, 0.92, 1.40 Nmm, 9.98 Nmm, 1.6 Nmm, and 3.5; and 0.97, 0.91, 1.35 Nmm, 2.63 Nmm, −0.08 Nmm, and 3.4, respectively. The PLS regression of the 64-sample KDML GBR group and the 64-sample GBR group of various varieties provided the optimized models for the hardness of the former and the toughness of the latter. The hardness model was developed by using 5446.3–7506 and 4242.9–4605.4 cm−1, which included the amylose vibration band at 6834.0 cm−1, while the toughness model was from 6094.3 to 9403.8 cm−1 and included the 6834.0 and 8316.0 cm−1 vibration bands of amylose, which influenced the texture of the cooked rice. The PLS regression models for hardness and toughness had the r2 values of 0.85 and 0.82 and the RPDs of 2.9 and 2.4, respectively. The ANN model for the hardness, toughness, and adhesiveness of cooked GBR could be implemented for practical use in GBR production factories for product formulation and quality assurance and for further updating using more samples and several brands to obtain the robust models.

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“…White, brown, and germinated brown rice samples of Oryza sativa L., Jasmine rice, were purchased from a commercial outlet in Bangkok, Thailand. The samples were prepared based on the previously reported cooking methods by Sirisomboon et al. (2017) .…”

Section: Methodsmentioning

confidence: 99%

“…The creep test was performed using a hold until time test by using a texture analyzer (HD Plus, Texture Analyzer, Stable Micro Systems, UK) with a 50-kg load cell. A 5 g sample of cooked rice was compressed up to 20 N maximum force using a deformation speed of 0.5 mm/s using the previously reported KMITL test rig ( Sirisomboon et al., 2017 ). The force was kept constant, hence the stress was constant as the compression area was approximately constant.…”

Section: Methodsmentioning

confidence: 99%

A new creep model for studying the non-linear viscoelastic behavior of cooked white, brown and germinated brown Thai jasmine rice by large deformation testing

Sirisomboon

Posom

2018

Heliyon

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A new creep model with three parameters for non-linear viscoelastic behavior is proposed as εt=ε0(1+tnk1+k2tn), where the applied stress is constant, εt is the strain at retardation time (t), ε0 is the initial strain and k1, k2 and n are constants. The relationship has been proved using data derived from cooked Thai Jasmine rice including white, brown and germinated brown rice samples. The creep test at high strain was conducted on scoops of cooked rice using a compression test rig. The model developed showed very accurate prediction performance with coefficients of determination (R2) between 0.9991–0.9992 and residual standard errors (RSE) between 0.00030–0.0004.

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Non-linear viscoelastic behavior of cooked white, brown, and germinated brown Thai jasmine rice by large deformation relaxation test

Cited by 5 publications

References 27 publications

Evaluation of Precision and Sensitivity of Back Extrusion Test for Measuring Textural Qualities of Cooked Germinated Brown Rice in Production Process

Evaluation of Precision and Sensitivity of Back Extrusion Test for Measuring Textural Qualities of Cooked Germinated Brown Rice in Production Process

Modeling Textural Properties of Cooked Germinated Brown Rice Using the near-Infrared Spectra of Whole Grain

A new creep model for studying the non-linear viscoelastic behavior of cooked white, brown and germinated brown Thai jasmine rice by large deformation testing

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