Evaluation of the optimal cooking time of rice by using FT-NIR spectroscopy and an electronic nose

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

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.

Volatile Organic Compounds, Evaluation Methods and Processing Properties for Cooked Rice Flavor

Rice (Oryza sativa L.), as the main refined grain in China, has attracted much attention in terms of quality. Rice is usually consumed after cooking, and it is a commonly staple food. Nowdays, people's requirements for cooked rice focus more on the taste characteristics and quality. Furthermore, aroma is one of the primary sensory reference points, which is the most intuitive way for people to judge cooked rice. By integrating and analyzing the researches of cooked rice aroma identification in recent five years, this paper expounds the extraction and identification methods (sensory evaluation method, GC-MS, SPME, MOS sensors, electronic nose, etc.) of the flavor substances in cooked rice, as the processing methods and properties of cooked rice, and the volatile organic compounds of cooked rice under different conditions are summarized as well.

US Consumers' Perceptions of Raw and Cooked Broken Rice

Rice supplies about 20% of the calories to the world’s consumers. Milling removes the outer husk and bran, breaking about 20% of the rice kernels during the milling process that equates to almost 100,000,000 tons of rice annually. Broken rice is discounted in price by almost half or relegated to non-human consumption. This study seeks to understand why this large percentage of rice production is discounted for human consumption. Consumers who routinely consume rice evaluated raw and cooked rice with 5%, 10%, 20%, 30% and 40% levels of brokens. Sensory analysis indicated the appearance of raw rice with high levels of brokens affected the price consumers were willing to pay. Panelists were not able to discern sensory differences amongst cooked rice samples with different brokens percentages despite an eight-fold difference in brokens (p < 0.01). From this, we concluded that the price discounts imposed on broken rice are not because of perceived differences in the eating quality of cooked rice. Overall impression and overall texture were the two most significant determinants in willingness to purchase rice. The five cooked-rice samples with different levels of broken rice inclusion did not differ in terms of willingness to purchase.

Chestnut Cultivar Identification through the Data Fusion of Sensory Quality and FT-NIR Spectral Data

The world production of chestnuts has significantly grown in recent decades. Consumer attitudes, increasingly turned towards healthy foods, show a greater interest in chestnuts due to their health benefits. Consequently, it is important to develop reliable methods for the selection of high-quality products, both from a qualitative and sensory point of view. In this study, Castanea spp. fruits from Italy, namely Sweet chestnut cultivar and the Marrone cultivar, were evaluated by an official panel, and the responses for sensory attributes were used to verify the correlation to the near-infrared spectra. Data fusion strategies have been applied to take advantage of the synergistic effect of the information obtained from NIR and sensory analysis. Large nuts, easy pellicle removal, chestnut aroma, and aromatic intensity render Marrone cv fruits suitable for both the fresh market and candying, i.e., marron glacé. Whereas, sweet chestnut samples, due to their characteristics, have the potential to be used for secondary food products, such as jam, mash chestnut, and flour. The research lays the foundations for a superior data fusion approach for chestnut identification in terms of classification sensitivity and specificity, in which sensory and spectral approaches compensate each other's drawbacks, synergistically contributing to an excellent result.

Functional Analysis of the Differences in the Dimensions of Two Types of Boiled and Steamed Rice Grains

The study tested how the cooking process can change the dimensions of rice grains. The impact of set times of cooking or steaming process on the characteristics such as length, width, and height of two varieties of rice, namely, long-grain white and parboiled, was investigated. The measurements of the dimension characteristics obtained at different times of the cooking process were converted to functional data. Different methods of multivariate functional data analysis, namely, functional multivariate analysis of variance, functional discriminant coordinates, and cluster analysis, were applied to discover the differences between the two varieties and the two heat treatment methods.

Effect of Supplementation of Flour with Fruit Fiber on the Volatile Compound Profile in Bread

This paper presents the analyses of the effect of fiber additives on volatile organic compounds in bread. The bread was baked from wheat flour with the addition of 3% of fruit fiber, following common procedures. After baking, volatile organic compounds contained in the control bread and breads supplemented with cranberry, apple, and chokeberry fiber were determined. The SPME/GC-MS technique was used for the identification of the odor profile, and the electronic nose Agrinose (e-nose) was used to assess the intensity of the aroma. The results of the analyses revealed the profile of volatile organic compounds in each experimental variant, which was correlated with responses of the electronic nose. The results indicate that the volatile compound profile depends on the bread additives used and influences the intensity of bread aroma. Moreover, the profile of volatile organic compounds in terms of their amount and type, as well as the intensity of their interaction with the active surface of the electrochemical sensors, was specific exclusively for the additive in each case.

Investigation of the conformational changes of a conducting polymer in gas sensor active layers by means of polarization-modulation infrared reflection absorption spectroscopy (PM-IRRAS)

Polarization-Modulation Infrared Reflection Absorption Spectroscopy (PM-IRRAS) was employed to observe the changes in the molecular conformation of poly(2-phenyl-1,4-xylylene) (PPPX) films that occurred after exposure to organic solvent vapors. The PPPX films were supported on solid matrixes by casting, spin-coating, and Langmuir-Blodgett (LB) techniques. The results show that the polymer is sensitive to the solvent vapors, which affect some of the vibration dipole moments, as detected by PM-IRRAS. The sensitivity depends on the method employed to immobilize the polymer, with more significant changes in films formed using techniques that result in a less systematically organized conformation. This feature enables the use of surface vibration spectroscopy to detect organic solvent vapors and may be applied in an artificial nose.