E22,t and longitudinal compressive strength Xc, which tend to follow a normal distribution. Among the four stiffness performance parameters, the correlation between v12 and the other three stiffness parameters was weak, whereas that between the other three stiffness parameters was strong.High-strength glass fibre-reinforced composites (H-GFRPs) are widely used in various engineering fields because of their excellent mechanical properties and designability. The mechanical properties of H-GFRPs are more sensitive to temperature and humidity. Under high temperature and humidity conditions, the properties decrease greatly and the dispersion increases. Tensile, compressive, and in-plane shear tests were carried out on five batches of H-GFRPs under five different conditions, and the strength and stiffness properties under different test conditions were obtained. In this paper, the strength and stiffness properties of H-GFRPs under room temperature and hygrothermal conditions are statistically analysed based on macroscopic test data and the meso-bridging model. The results showed that under hygrothermal conditions, the dispersion of performance tended to decrease. The distribution types of other parameters are consistent with those under room temperature conditions, except for the transverse tensile modulus  High-strength glass fibre-reinforced composites (H-GFRPs) are widely used in various engineering fields because of their excellent mechanical properties and designability. The complex manufacturing process of composite structures and the characteristics of integrated moulding of materials and structures result in the increased dispersion of the mechanical properties of composite structures ,2. SafetAt present, in engineering practice, the analysis and design of composite structures are generally performed based on the determined structural parameters, loads, and mechanical models. In deterministic design, the allowable load that the structure can bear is calculated according to the structural failure load obtained from strength analysis and a certain safety factor. However, several uncertainties exist in actual engineering structures that may cause large deviations in the structural response. Therefore, it is necessary to establish models that consider the uncertainties of the structural parameters and external loads. Currently, uncertainty models are mainly divided into probability, interval, and fuzzy models. After years of development, researchers have established a relatively perfect stochastic finite-element theory. Probability models based on stochastic theory mainly consider uncertainty based on the probability distribution characteristics of random parameters. By contrast, interval models examine uncertainty via interval analysis, for which only the upper and lower bounds of structural parameters need to be determined. Meanwhile, the fuzzy model primarily studies uncertainty based on the fuzzy statistical method. Among these three models, the probability model is the most widely used.When evaluating the dispersion of the mechanical properties of composite structures, it is necessary to first evaluate the randomness of the mechanical properties of the composites. The existing research can be divided into two categories. The first is research based on experimental methods at the macro-scale. The second type is theoretical or numerical research based on the meso-scale. Generally, tests are performed on basic mechanical properties to determine the statistical characteristics of mechanical properties according to a large amount of test data and probability distribution models commonly used in statistics  ,9,10,11.In the absence or scarcity of test data, the distribution parameters of the mechanical properties are determined according to the composite manual or empirical assumptions. For example, Nakayama et al. ,13 assumAccordingly, in this study, the dispersion of the mechanical properties of different batches of H-GFRPs was analysed based on the test data. A probability distribution analysis method for mechanical properties based on macro test data and a meso-mechanical model was proposed, and the probability distribution characteristics of the mechanical properties at room temperature (RT), in a dry state, and in a hygrothermal environment were determined. Subsequently, the reliability of the material mechanical properties based on the deterministic and probabilistic design methods was analysed.6C10-800). Five test environmental conditions were designed as shown in In this paper, the specimens were provided by China Composite Group Corporation Ltd. , which were manufactured from laminates made of H-GFRP  of the influence of different averages on the comparison of the variation degree of two or more data points. Therefore, we used the CV to measure the stability of the mechanical properties of the different batches of materials.E11 and transverse tensile–compression modulus E22, as shown in In addition, in the mechanical analysis of composite structures, the tensile and compression moduli are often not distinguished because they are usually very close. It can also be seen from the test results that the tensile and compression moduli of the H-GFRPs are similar. Therefore, we averaged the tensile and compression moduli of each batch of materials to obtain the longitudinal tensile–compression modulus In general, the strength performance dispersion of the five H-GFRP batches was greater than that of the stiffness performance. By comparing and analysing the CV of the test results of the five batches, it can be concluded that the stiffness performance stability of each batch of materials is good, and the strength performance stability is moderate.Existing literature also shows that the randomness of the mechanical properties of composites can be determined based on macro test data. The analytical process for this method was conducted as follows.® Software or other statistical analysis software was used to determine several test values of basic mechanical property parameters, wherein appropriate intervals were selected for frequency statistics to obtain the corresponding cumulative frequency for calculating the cumulative probability distribution.First, OriginSecond, three widely used continuous probability distribution functions, normal distribution, lognormal distribution, and Weibull distribution, were used for fitting, and their cumulative distribution functions (CDFs) are given by:Finally, a histogram of the mechanical property parameters was obtained using a statistical method, and the probability density function of the optimal distribution determined above is drawn in the figure for verification.(1)Probability distribution characteristics of the stiffness properties in the RTD stateUsing the above method, 30 test values based on stiffness performance for the RTD condition  were used to calculate the cumulative probability distribution, as depicted in E11,t, transverse tensile modulus E22,t, and transverse compression modulus E22,c tend to obey lognormal distribution, the in-plane Poisson’s ratio v12 tends to obey the normal distribution, while the longitudinal compression modulus E11,c and longitudinal and transverse shear modulus G12 tend to obey the Weibull distribution. It is worth noting that the goodness-of-fit values for the normal and lognormal distributions are very close, again demonstrating the equivalence of these two distributions in describing the randomness of material mechanical properties. In addition, the goodness-of-fit for the best distribution of E11,c and E22,t is 0.986, while those for the optimal distributions of other parameters are 0.995 or above.Furthermore, based on 30 test values, five histograms for the stiffness properties were obtained using a statistical method, and the probability density functions of the optimal distributions determined above are depicted in (2)Probability distribution characteristics of the strength properties in the RTD stateXc and transverse compressive strength Yc tend to obey the lognormal distribution, while the longitudinal tensile strength Xt, transverse tensile strength Yt, and longitudinal and transverse shear strength S12 tend to obey the Weibull distribution. In addition, regarding the optimal distribution, although the goodness-of-fit values for Yc and S12 are 0.987 and 0.955, respectively, those for the other three strength performance parameters are higher than 0.995.Moreover, Among the five environmental working conditions, except for RTD, condition V was the worst working condition, i.e., at 70 °C high temperature and equilibrium moisture absorption, as described in (1)Probability distribution characteristics of the stiffness performance in a humid and hot environmentE11,t and transverse compression modulus E22,c tend to obey the lognormal distribution, the transverse tensile modulus E22,t tends to obey the normal distribution, while the longitudinal compression modulus E11,c and longitudinal and transverse shear modulus G12 tend to obey the Weibull distribution. Although the goodness-of-fit values of the best distribution for E22,t and G12 are 0.976 and 0.988, respectively, those for the other parameters are higher than 0.99.E22,t, are consistent with the distribution trends.(2)Probability distribution characteristics of the strength properties in a humid and hot environmentXc tends to obey the normal distribution, the transverse compressive strength Yc tends to obey the lognormal distribution, and the longitudinal tensile strength Xt, transverse tensile strength Yt, and longitudinal and transverse shear strength S12 tend to obey the Weibull distribution. The goodness-of-fit values of the best distribution for transverse tensile strength Yt and longitudinal and transverse shear strength S12 are 0.987 and 0.989, respectively, whereas that for the other parameters is higher than 0.995.In addition, statistical histograms for the five strength performance parameters in a humid and hot environment were realized using a statistical method and are displayed in (1)Comparison of the probability distribution characteristics of stiffness performanceE22,t obeys the lognormal distribution in the RTD state and normal distribution in the humid and hot environment, the distribution types of the other parameters under the two working conditions are consistent. According to the previous analysis, we know that the lognormal and normal distributions are equivalent in describing the statistical characteristics of the material mechanical properties. It can be seen that humid and hot environments do not cause changes in the probability distribution type of the stiffness properties of the H-GFRPs.(2)Probability distribution characteristics of the strength properties under the humid and hot environment conditionsXc, which obeys a lognormal distribution in the RTD state and a normal distribution in the humid and hot environment. According to the previous analysis, we know that the lognormal and normal distributions are similar, and the mechanical property parameters of the materials are basically equivalent in terms of statistical characteristics. It can be observed that the humid and hot environment conditions do not change the probability distribution type corresponding to the strength properties of the H-GFRPs.(1)Determine the statistical characteristics of the component material performance parameters.(2)Conduct a random number of simulations based on the statistical characteristics of the component materials to obtain the random input parameters.(3)Substitute the random input parameters into the meso-mechanical theoretical model to obtain randomly distributed composite stiffness properties.The literature shows that the method of analysing the statistical characteristics of the mechanical properties of materials based on the meso-scale is more efficient than that based on test data. The process of determining the probability distribution characteristics of the composite mechanical properties based on the meso-scale method is as follows:It can be seen that the key factors in this method include the statistical characteristics of component materials and the theoretical model of micromechanics.fE, fv, and fG denote the elastic modulus, Poisson’s ratio, and shear modulus of the glass fibre, respectively, meeting the requirements of mE, mv, and mG represent the elastic modulus, Poisson’s ratio, and shear modulus of the matrix, respectively, meeting the requirements of fV and mV denote the volume contents of the fibre and matrix, respectively. When the void content is ignored, they satisfy the requirement of fV + mV = 1.Although researchers have developed several micromechanical theoretical models, most of them can only predict the stiffness properties of composites. Research shows that among the existing theoretical micromechanical models, the bridging model  can predfE, fv, mE, mv, and fv. When using the model to determine the statistical characteristics of composite stiffness properties, it is necessary to first determine the statistical characteristics of the mutually independent random variables.It can be seen from the calculation formula of the above bridging model that the mutually independent variables in the model include T* was used to fit the functional relationship between the mechanical properties of the composites and the hygrothermal environment. The normalised temperature is defined as follows ; values close to 0 indicate that the two variables are uncorrelated or weakly correlated, whereas values close to −1.0 or 1.0 indicate stronger correlation. Correlation coefficient values in the range of  represent positive correlations, whereas those in the range of [−1, 0) represent negative correlations.x and y are random variables and N is the number of sample variables. The correlation between the parameters can be calculated from 10,000 sampling points of the material stiffness performance, as shown in E11 is positively correlated with E22 and G12, with a correlation coefficient of approximately 0.7, and weakly correlated with v12 (−0.196); E22 is positively correlated with G12 with a correlation coefficient of 0.97, and weakly correlated with v12, whereas v12 is negatively correlated with G12.Here, Among the four humid and hot working conditions tested, the worst working condition was the combination of a high temperature of 70 °C and balanced moisture absorption. Therefore, the probability distribution characteristics of the mechanical properties of the material in this case are analysed in ®, and 10,000 sample points for the stiffness properties of H-GFRPs under a humid and hot environment were calculated using the bridging model. In Origin®, frequency statistics were created based on the stiffness performance sample points to obtain the corresponding cumulative frequency and cumulative probability distribution relative to each performance parameter, as shown in According to the distribution parameters for the random variables listed in E11, transverse tensile–compression modulus E22, and longitudinal and transverse shear modulus G12 tend to obey a lognormal distribution, whereas Poisson’s ratio v12 tends to obey a normal distribution. The goodness-of-fit values for the best distributions of the four stiffness performance parameters were ≥0.99995.Moreover, according to the frequency statistics listed above, the corresponding frequency can be obtained to calculate the probability density distribution histogram for each stiffness performance parameter, as shown in v12 and the other three stiffness parameters is weak, whereas that between the other three stiffness parameters is strong. E11–E22 and E11–G12 completely covered the test results, indicating that the model can well predict the correlation of stiffness performance under ETW.Furthermore, the correlation between various stiffness performance parameters was obtained through a micromechanical analysis. To qualitatively analyse the correlation between the stiffness properties, 10,000 sampling points were drawn in the coordinate system to obtain the correlation diagram between various stiffness properties, as shown in E11 is positively correlated with E22 and G12, with a correlation coefficient of approximately 0.7, and weakly correlated with v12 (−0.196). E22 is positively correlated with G12, with a correlation coefficient of 0.97, and weakly correlated with v12, whereas v12 is negatively correlated with G12.Moreover, the Pearson linear correlation coefficient between the parameters could be calculated according to the 10,000 sampling points of the material stiffness performance; the results are displayed in To analyse the influence of humid and hot environments on the statistical characteristics of the stiffness properties of H-GFRPs, the probability distribution characteristics of the stiffness properties in the RTD state and humid and hot environment determined in E11 obeys the normal distribution in the RTD state and the lognormal distribution under the hot and humid environment, the distribution types of the other parameters under the two working conditions are similar; more precisely, the transverse tensile–compression modulus E22 and the shear modulus G12 obey the lognormal distribution under both working conditions. It should be noted that Poisson’s ratio v12 exhibits similar distributions under the two working conditions because the influence of the humid and hot environment on Poisson’s ratio and the volume fraction of the component materials was neglected. As mentioned above, the lognormal and normal distributions are equivalent in describing the statistical characteristics of the mechanical property parameters of materials. It can be observed that a humid and hot environment does not alter the probability distribution type of the stiffness properties of H-GFRPs.(1)The mechanical properties of different batches did not become unstable in hot and humid environments; however, with the deterioration of hot and humid conditions, the dispersion of performance tended to decrease.(2)E22,t and longitudinal compressive strength Xc, which tend to follow a normal distribution.The probability distribution characteristics of the stiffness and strength performances were obtained using the macroscopic test data. Under hot and humid conditions, the distribution types of other parameters are consistent with those under RT conditions, except for the transverse tensile modulus (3)v12 and the other three stiffness parameters was weak, whereas that between the other three stiffness parameters was strong.The probability distributions of the stiffness performances and their correlations were obtained using a method based on the meso-mechanical model. Among the four stiffness performance parameters, the correlation between In this study, the dispersion of the mechanical properties of different batches of H-GFRPs was analysed based on test data. A probability distribution analysis method for the mechanical properties based on the macroscopic test data and a meso-mechanical model was proposed. The following conclusions were drawn:


The results showed RSPN had the lowest glycemic index value if compared to BSP and SPN  and fell under food with medium GI, but the differences were not statistically significant. RSPN and SPN were classified as medium GI; however, the process of partial gelatinization followed by retrogradation during the preparation of flour used for raw material in making RSPN has successfully maintained the total phenol and anthocyanin and increased resistant starch content of the noodle Processing of purple sweet potato flour into noodle lowered the GI category, and when the flour was partially gelatinized and retrograded, the noodle had more potentiality as a functional food due to their high total phenolic and anthocyanin content.Purple sweet potato is a source of starch with high potential to be developed as a functional food. It can be boiled and consumed as a snack or processed into intermediate goods such as flour. The flour can then be modified through partial gelatinization and followed by a retrogradation process to produce resistant starch-rich purple sweet potato flour. The study was aimed at obtaining the glycemic response values of purple sweet potato products, namely, boiled purple sweet potatoes (BSP), purple sweet potato noodles (SPN), and resistant starch-rich purple sweet potato noodles (RSPN). SPN was prepared from conventional purple sweet potato flour, whereas RSPN was made from resistant starch-rich purple sweet potato flour. Moreover, water, ash, protein, fat, and carbohydrate; total phenolic, anthocyanin, and resistant starch contents; and the rate of hydrolysis of starch were evaluated. Ten subjects were involved in the estimation of glycemic response determined by the area under the curve (AUC) of the blood glucose after consuming products. Glucose syrup was used as a reference. The glycemic response data were processed using ANOVA and further tested using LSD at  Purple sweet potato is a food source rich in carbohydrates, primarily starch. As a starch source, purple sweet potatoes have a high potential to be developed as a functional food due to its bioactive components that are said to be good for health. One of the bioactive components with physiological functions is anthocyanins . Anthocyα-glucosidase enzyme [α-amylase enzyme activities [Processing purple sweet potatoes into flour has other benefits such as having more flexible utilization, saving storage space, and being available anytime without waiting for the harvest season. Another benefit is that it is easy to modify purple sweet potato flour to maintain its bioactive components and improve its physiological functions. Nurdjanah  reportede enzyme  and α-amtivities .α-amylase enzyme activity in the small intestines is inhibited, slowing down glucose digestion [Research by Sajilata et al.  states tigestion . Second,igestion .Research regarding the glycemic response of processed food made from high-carbohydrate tubers such as purple sweet potatoes is still limited. The same ingredient has different glycemic indexes when processed differently because the characteristics and physiochemical properties have changed . For exa2SO4, H2SO4, 95% alcohol, 0.02 N HCL, H3BO3, Na2CO3, gallic acid, 0.2% citric acid, KCl buffer solution, pH 4.75 sodium acetate buffer solution, pH 1.5 KCl-HCl buffer solution, phenol, KOH 4 M, pepsin, glucose, α-amylase enzyme from Aspergillus oryzae (powder), 3,5-dinitrosalicylic acid (DNS), and glucoamylase enzyme.The main material of this research was local purple sweet potatoes from a traditional market in Way Kandis, Bandar Lampung, Indonesia. Chemical substances for analysis included NaOH, HgO, KEquipment used in this study was a modified rotary drum dryer, refrigerator, peeler, and cabinet dryer. Equipment used for analysis included Kjeldahl flask, boiling flask, Soxhlet extractor, vortex, centrifuge spectrophotometer Genesys S10-UV-VIS, water bath, and blood glucose testing equipment Accu-Chek Performa.Fresh purple sweet potatoes (1 kg) were sorted, washed, drained, and boiled in boiling water (2 L) for about 30 minutes. Boiled purple sweet potatoes were then taken out, drained, peeled, and cut into 2 × 2 × 2 cm cubes to be served to respondents.Purple sweet potatoes were cleaned and grated to 1 mm thickness. Purple sweet potatoes were then dehydrated in a cabinet dryer at 60°C for about 16 hours until the water content was about 10%. Dehydrated purple sweet potatoes were processed into flour using a hammer mill and sieved through the 80-mesh sieve.Purple sweet potato flour noodles were prepared following the method of Yuliana et al.  with sliPurple sweet potatoes were cleaned, grated, and heated to 90°C for 30 minutes in a rotary drum dryer. For the cooling process, purple sweet potatoes were then cooled at 25°C for 1 hour and put into the refrigerator at 5°C for 48 hours. Cold purple sweet potatoes were dried in a cabinet dryer at 60°C for about 16 hours until the water content reached 10%, then processed into flour using a hammer mill and sieved through the 80-mesh sieve [The proximate analysis of water, ash, protein, fat, and carbohydrate by difference contents followed the AOAC (2005) method .2CO3) was added before mixing again in a vortex for 1 minute and left in a dark room for 30 minutes at room temperature. The absorbance of gallic acid reaction with the Folin-Ciocalteu reagent was then read at 760 nm wavelength. A blank form with the same procedure as the sample was prepared. The absorbance results were plotted on a standard curve for gallic acid using the linear regression equation with gallic acid concentration on the x axis and absorbance on the y axis. A standard curve for gallic acid was made by mixing 1 mg of gallic acid with distilled water , preparing a series of 0%, 20%, 40%, 60%, 80%, and 100% dilution from that gallic acid solution, and giving them the same treatment as the sample. The results were shown in the standard curve equation:Total phenolic content analysis used a modified version of the method of Nurdjanah et al. . The extThe total anthocyanin concentration was measured using the method by Giusti and Wrolstad . Two samA is absorbance, MW is molecular weight of cyanidin 3-glucoside (449), DF is dilution factor, ε is coefficient of cyanidin 3-glucoside molar extinction , and 1 is cuvette thickness.The total anthocyanin content was determined using the following equation:The resistant starch content was determined following the Goni et al.  method wα-amylase enzyme solution was added. The mixture was then incubated for 16 hours in a water bath at 37°C with constant stirring and centrifuged for 15 minutes at 3000 rpm. The resulting supernatant was thrown away, and 10 mL of distilled water was added to the residue to be centrifuged again . The supernatant was then separated. The residue was mixed together with an additional 3 mL of distilled water and added with KOH (4 M) before being incubated in a Memmert shaker water bath for 30 minutes at 25°C with constant stirring. Then, 5.5 mL HCl (2 M) and 3 mL sodium acetate (0.4 M) buffer solutions were added, and pH was adjusted to 4.75 by adding HCl (2 M).The mixture was put into a 40°C water bath for 60 minutes, then cooled at room temperature. pH was adjusted to pH 6.9 by adding NaOH (0.5 M), and 1 mL of μL of glucoamylase enzyme was added and mixed in and left in a Memmert water bath for 45 minutes at 60°C. The supernatant was separated using a centrifuge tube  and kept while 10 mL of distilled water was added to the residue and centrifuged again. The resulting residue was then thrown away. The supernatant was mixed with the previously obtained supernatant, and distilled water was added to reach 50 mL in volume. Glucose content was determined using the phenol-sulfuric acid method, and resistant starch content was determined by multiplying the glucose content by 0.9.After that, 80 α-amylase enzyme was determined following the modified method by Nurdjanah et al. [α-amylase enzyme and 3 mL of pH 7 phosphate (0.1 M) buffer solution; incubated at 37°C for 0, 60, and 120 minutes; and centrifuged at 3000 rpm for 15 minutes. The glucose content of the resulting sample was then determined using the phenol-sulfuric acid method.The hydrolysis rate of starch with h et al. . Powdere2) and in healthy conditions. The exclusion criteria included having no history of diabetes, no current digestive issues, not being in the middle of treatment, not using illegal drugs, not smoking, and not drinking alcohol. There were 10 candidates selected as respondents, and they were given a short explanation of this research before signing informed consent forms.The glycemic response was evaluated in several steps, which were (a) ethical clearance application, (b) subject candidate recruitment, (c) subject candidate selection, (d) research explanation and informed consent, and (e) glycemic response evaluation. This research was done after obtaining ethical clearance from the authorized committee of ethics. The recruitment and selection of subject candidates were done using the purposive sample method that fulfilled the inclusive and exclusive criteria. The inclusive criteria were subjects aged between 18 and 30 years of age of any gender with normal BMI  was then calculated with the following equation:After consuming each purple sweet potato products, 0.6 x axis (time) and y axis (glycemic response). The glycemic responses of ten respondents on each product were averaged to reveal the curve chart. The effect of consuming each product on the glycemic responses was analyzed for its normality, followed by the paired samples test using the software SPSS 16.0.This research was arranged in a completely randomized design with three replications. The data of proximate composition were reported for their means and standard deviation, whereas total phenol, total anthocyanin, and resistant starch content' data were then analyzed for their homogeneity and additivity using the Bartlett and Tukey tests, then processed using analysis of variance (ANOVA), and further tested using the least significant difference (LSD) test. All the cooked purple sweet potato products and pure glucose were then evaluated for their glycemic responses following the method of El  with tenIn this research, proximate analysis was completed to figure out the nutritional content of these products such as water, fat, ash, and carbohydrate by difference. One factor that affects blood glucose response is the composition of nutrition . Boiled The results of total phenolic, anthocyanin, and resistant starch contents are presented in This research revealed that the highest total phenolic content of 357.33 mg GAE/100 g was found in boiled purple sweet potatoes . This miIn this research, the total phenolic content of resistant starch-rich purple sweet potato noodles was lower than that of boiled purple sweet potatoes because in the noodle-making process, there was direct heat contact during dough steaming before making noodle sheets and dry noodle steaming. When boiling purple sweet potatoes, the skin stayed on thus avoiding direct heat contact between the water and the purple sweet potato flesh. According to Padda and Picha , the proBoiled purple sweet potatoes showed the highest amount of total anthocyanin content with 95.64 mg/100 g . MeanwhiThe higher amount of total anthocyanin content in boiled purple sweet potatoes than in other products was directly proportional to the amount of total phenolic content. Heat treatment on purple sweet potatoes is predicted to inactivate the enzymes that caused browning such as polyphenol oxidase and peroxidase , thus inBoth SPN and RSPN showed lower anthocyanin content when compared to boiled purple sweet potato anthocyanin content. This was probably because during the thermal process anthocyanins experience deglycosylation, nucleophilic attack of water, cleavage, and polymerization . These rThe result of this research revealed that boiled purple sweet potatoes had the lowest amount of resistant starch with only 2.99% . This miThe highest amount of resistant starch (14.29%) was found in resistant starch-rich sweet potato noodles. This relatively high amount was because of the partial gelatinization of purple sweet potato flour at 90°C for 30 minutes and the following retrogradation at 5°C for 48 hours. Nurdjanah and Yuliana  stated tα-amylase enzyme was inversely proportional to the resistant starch content of purple sweet potato products. High resistant starch content in food may decrease the enzyme hydrolysis rate [The highest hydrolysis rate in 120 minutes happened in boiled purple sweet potatoes with 78.56% ± 0.26%. Meanwhile, the hydrolysis rate of purple sweet potato noodles reached 66.28% ± 1.88% with the lowest number of 52.27% ± 1.40% belonging to resistant starch-rich sweet potato noodles. The rate of hydrolysis with sis rate . Resistasis rate . That ensis rate .  Figure2) and in healthy conditions. The exclusive criteria included having no history of diabetes, no current digestive issues, not being in the middle of treatment, not using illegal drugs, not smoking, and not drinking alcohol. There was a total of 10 respondent subjects selected.This research was completed after obtaining ethical clearance from the Research Ethics Committee Faculty of Medicine University of Lampung Number 2985/UN26.8/DL/2017. Respondent subject recruitment was conducted through socialization with several students from the Agricultural Technology Department University of Lampung and interviewing them regarding their health history. The weight, height, and BMI of candidates were then observed. Candidates selected to be respondent subjects must fulfill the inclusive and exclusive criteria. The inclusive criteria were subjects aged between 18 and 30 of any gender with normal BMI  consensus, the normal BMI for Indonesians was between 18.5 and 22.9 kg/m2. The preprandial blood glucose level was obtained by averaging the four tests done at minute 0, indicating no diabetes history with the numbers all under 100 mg/dL.The average age of respondent subjects was 22 years with 53.5 kg weight, 1.6 m height, and 20.83 kg/mμL. The blood glucose level was measured using the Accu-Chek Performa digital glucometer. The blood samples obtained were touched onto the censor crack at the end of the test strip, and the results were read on the screen.Blood samples were obtained using lancet pens on respondent subjects' pointer, middle, and ring fingers. The respondent subjects' fingers were first cleaned and sterilized with an alcohol swab. For this research, the volume of the blood sample needed was minimum 0.6 Respondent subjects received food intervention of pure glucose syrup as a comparison in addition to the purple sweet potato products of boiled purple sweet potatoes, purple sweet potato noodles, and resistant starch-rich purple sweet potato noodles. Each food intervention was given 3–4-day intervals for recovery. Respondent subjects fasted for around 10 hours and were tested for their preprandial blood glucose levels. The testing was done in a comfortable room and relaxed condition with no influence from physical activities.The first food consumed was 50 g of pure glucose syrup dissolved in 200 mL of water for control. Pure glucose syrup was the recommended item to act as control when determining the glycemic index values of other foods due to its standardized and uniform composition, unlike white bread. Respondent subjects needed 3 minutes to consume the glucose syrup. Blood samples were taken for blood glucose level testing at minutes 30, 60, 90, and 120 afterwards. In order, food interventions given after pure glucose syrup were boiled purple sweet potatoes, purple sweet potato noodles, and resistant starch-rich purple sweet potato noodles. The serving size for each product was equivalent to 50 g of carbohydrate by difference, as shown in The biggest serving size was for boiled purple sweet potatoes, and the smallest was for resistant starch-rich purple sweet potato noodles. This research did not consider soluble and insoluble fiber; thus, the available carbohydrate content could not be measured. The serving size in this research was determined using the carbohydrate by the difference method without revealing the total available carbohydrate to be digested by the body. The serving size of resistant starch-rich purple sweet potato noodles should have been bigger because resistant starch was not easily digested, lowering the total available carbohydrate.Boiled purple sweet potatoes were served on the second testing (day 4) with 145 g serving size per person. Respondent subjects needed about 10 minutes to consume the sample. Purple sweet potato noodles were served on the third testing (day 8) with 112.87 g serving size per person and resistant starch-rich purple sweet potato noodles on the fourth testing (day 12) with 112.87 g per person. Respondent subjects needed about 15 minutes to consume these samples, which was quite a long time, due to the less desirable taste (distinctively sweet potato-like) and the portion size that was bigger than the regular noodle soup dishes. The amount of time it took to consume these products might affect the blood glucose level results because products consumed earlier would be digested earlier, too.x axis and blood glucose level on the y axis, and a curve was formed as seen in The glycemic response was determined from how respondent subjects' blood glucose levels responded to the samples of pure glucose syrup, boiled purple sweet potatoes, purple sweet potato noodles, and resistant starch-rich purple sweet potato noodles. The data from respondent subjects' blood glucose tests were entered with time on the The peak of blood glucose increment happens around 15-45 minutes after consuming food, depending on how fast the body digests and absorbs carbohydrates. The glycemic response of food products is shown by the fluctuation curve of glucose absorption in the blood after consuming them. Food components that are absorbed quickly by the body will cause high fluctuation in blood glucose levels in a short time. The curve with the lowest peak belongs to resistant starch-rich purple sweet potato noodles, indicating the slow digestion process that causes the slow release of blood glucose until 2 hours postprandial.After the curve was formed, the incremental area under the curve was calculated. The area under the horizontal basic line of the preprandial blood glucose level was not included  The areap < 0.05) due to the different treatments in the processing of purple sweet potato products. The change in structures might affect the postprandial response to starchy food [α = 0.05) between purple sweet potato noodles and resistant starch-rich purple sweet potato noodles  revealed there were differences in the area under the curve of each product  purple sweet potato flour that was made with partial gelatinization and retrogradation process. Partial gelatinization opened the amylose and amylopectin bond structures. Then, in the cooling process, compact starch molecules were restructured and stabilized with hydrogen bonds, creating starch that was difficult to hydrolyze by digestive enzymes . ResistaProcessing starch to produce resistant starch is one way to lower glycemic response values. Resistant starch type 3, due to its special properties as a result of the retrogradation process, is not digested in the small intestine. However, after 2 hours, this type of resistant starch will be fermented in the colon resulting in short-chain fatty acids. This type of resistant starch has beneficial effects on recuperating insulin resistance and lowering blood glucose in type 2 diabetes mellitus patients. Blood glucose levels of respondent subjects after consuming these food products were also quite stable even after two hours. A smaller area under the curve indicated slower digestion of carbohydrates that resulted in slower and less glucose release, so the curve had gentler response and lower peak level of glycemic response, and vice versa.Some respondent subjects only had a minimum difference in the area under the curve for different purple sweet potato products; some did not. Each respondent subject displayed different glycemic response curves with different peaks and glycemic index value indications. These varying results were assumed to be due to several factors of physiological responses such as metabolism, stress level, physiological condition, and fasting time.The area under the curve that showcases glycemic response becomes the reference in calculating the glycemic index value of a food product. As applied in this research, the glycemic index value indications of purple sweet potato products were determined by dividing the AUC of each purple sweet potato product by the AUC of pure glucose syrup, then multiplying by 100. This equation came from the glycemic index equation; however, this research called these results shown in α-amylase enzyme directly [directly .Based on general food glycemic index (GI) values, boiled purple sweet potatoes fell under food with high GI of over 70, while both noodles fell under the medium range with 55-70. Even though both noodles were in the medium range, resistant starch-rich purple sweet potato noodles still showed the lowest GI due to the main ingredient, RS3, that was made through partial gelatinization and retrogradation process and formed starch structures that were hard to digest. Different treatments and processes in making purple sweet potato products resulted in different glycemic index value indications.α-amylase enzyme, and it was inversely proportional with their resistant starch content. Partial gelatinization of sweet potato flour has failed to reduce GI of noodles as indicated that RSPN and SPN were classified as medium GI food, but the process has successfully maintained the total phenolic and anthocyanin and increased resistant starch content of the noodle. Processing of purple sweet potato into noodles lowered the GI category, and when the flour was partially gelatinized and retrograded, the noodles had more potentiality as a functional food due to their high total phenolic and anthocyanin content.The purple sweet potato products had different GI values depending on their processing method. The RSPN had the lowest glycemic index value if compared to BSP and SPN  and fell under food with medium GI, but the differences were not statistically significant. The pattern of the GI value of the products was concomitant with the pattern of the rate of starch hydrolysis with


Starch paste is a very complex dispersion that cannot be clearly classified as a solution, colloid or suspension and many factors affects its properties. As these ambiguities constitute a barrier to technological development, the aim of this study was to investigate the interaction of starch macromolecules with water by analysing the results of rheological properties, low field nuclear magnetic resonance (LF NMR), dynamic light scattering (DLS) and ζ potential analyses. Starch pastes with a concentration of 1%, prepared with distilled water and buffered to pH values of 2.5, 7.0 and 9.5 were analysed. It was proved that the pH buffering substantially decreased the values of consistency index but the pH value itself was not significant. LF NMR studies indicated that the dissolution of starch in water resulted in a reduction in spin-lattice as well as spin-spin relaxation times. Moreover, changes in relaxation times followed the patterns observed in rheological studies. Electrokinetic and DLS analyses showed that potential values are primarily influenced by the properties of the starches themselves and, to a lesser extent, by the environmental conditions. The conducted research also showed complementarity and, to some extent, substitutability of the applied research methods as well as exclusion chromatography (a method not used in this work). Starch, poly-α-glucan, is a polymer whose importance for food technology and human nutrition cannot be overestimated. The main plant crops, including corn, rice, wheat, potato and cassava, are rich sources of starch which is cheap and has become the main source of energy in human diet ,2. The eRheological properties of starch are influenced by a number of factors. First of all, they are determined by the molecular mass of this polymer according to the Mark-Houwink equation. Other structural factors such as the number and length of branches are also of significant importance . Moreove1H LF NMR analysis is based of proton relaxation phenomena, so it is designed for studying systems rich in water or fats. Food products contain water as an integral component, thus NMR relaxometry opens new possibilities to study the properties of these enormously complex mixtures [Low field nuclear magnetic resonance is a technique that makes it possible to study the effect of solutes present in the starch pastes. The physical basis of nuclear magnetic resonance (NMR) was given in the first half of the 20th century and initially it was used for studies in the field of physics. Due to the development of this technique, it soon became the basic tool for studying the structure of organic compounds. Currently the most important techniques of nuclear magnetic resonance include high resolution NMR (both in liquid and solid states), low field NMR and magnetic resonance imaging (MRI) . The lasmixtures ,35,36,37mixtures ,42,43,44Dynamic light scattering and ζ potential measurements have gained enormous popularity in recent years due to the development of nanotechnology and the need for comprehensive characterisation of nanoparticles, especially those of therapeutic relevance. Currently, table-top instruments are available which allow people to perform both the analyses in ordinary laboratory environments ,46. HoweStudy on the ζ potential of potato and wheat starches proved that this parameter is pH dependent and is related to the surface properties of granules. Effective removal of ionic substances from the surface of granules of potato starch results in a stable value of ζ potential of about −11 mV . The chaStarch, both in its native and pasted form, is a very complex dispersion that cannot be clearly classified as a solution, colloid or suspension. Moreover, the properties of starch pastes are affected by many factors, primarily pH and the presence of different solutes. The selection of appropriate starch for a specific application is still a challenge for technologists. Therefore, the aim of this study was to provide new information in order to facilitate the understanding of interactions of starch macromolecules with water. To this end, results of rheological, LF NMR, DLS and ζ potential analyzes were studied.Native potato starch and food grade modified starches–oxidised starch (E 1404), distarch phosphate (E 1412), acetylated starch (E 1420), were kindly provided by WPPZ SA . Laboratory manufactured starch sodium octenyl succinate (E 1450) and cationic starch were also tested. Starch sodium octenylsuccinate (OSA starch) was synthesised in a water suspension with octenylsuccinic anhydride as the esterifying agent , according to the procedure described by Jeon et al. . CationiDegrees of substitution of food grade modified starches were determined according to JECFA recommendations . For catSamples for rheological, LF NMR, DLS, and ζ potential analyses were prepared in a two-step manner. Firstly, gelatinisation of 2% starch suspensions was performed, by continuous stirring, for 30 min, followed by sterilisation at a temperature of 121 °C for 15 min. Secondly, after cooling, phosphate buffer was introduced in order to obtain pastes with known pH values and the starch concentration in the pastes was adjusted to 1%.Rheological properties were determined with RheoStress1 rheometer  equipped with a DG43 sensor. Tests were performed in CS mode. Shear stress was ramped from 0 Pa at time 0 s to 1.5 Pa at 120 s. Samples were thermostated at 25 °C. RheoWin 3 software  was used to determine the parameters of the Ostwald-de Waele model.®. The relaxation times of spin-lattice T1 and spin-spin T2, were measured using a pulse spectrometer PS15T . The device operates at the frequency of 15 MHz and includes an integrated system of temperature control. In order to measure of spin-lattice relaxation times, inversion-recovery pulse sequence was used [T1) was changed from 100 to 1300 ms. Repetition time TR was 20 s, and a single sequence consisted of 32 repetitions. 119 measurement points from each of the 32 FID signals were collected in order to carry out calculation. Measurements of spin-spin relaxation times were carried out with CMPG impulses [cτ, corresponding to the time necessary for one radian rotation of molecule, is derived from directly measured spin-lattice T1 and spin-spin T2 relaxation times [A is a parameter characterizing the interacting spins, ω is a Larmor frequency.Samples for LF NMR analyses were put into NMR tube (1.5 mL). The vessels were sealed with Parafilmwas used . Distancimpulses . Distancon times :(1)1T1=2Particle size (hydrodynamic diameter) in starch samples was determined using dynamic light scattering method. ζ potential was measured by electrophoretic light scattering. Zetasizer Nano ZS-90  was used in both measurements. ζ potential values are arithmetic mean of 6 independent measurements. Particle size was presented as z-average and the polydispersity index (PdI) was calculated  of DS = 0.02, acetylated starch (E 1420) of DS = 0.02, starch sodium octenylsuccinate of DS = 0.02, distarch phosphate, and cationic starch of DS = 0.04. All investigated starches, with the exception of cationic starch, are popular thickeners and texture forming agents used in the food industry. Cationic starch is a wet end additive used in the paper industry to improve paper web strength and quality. The values of the degree of substitution of the studied starches differ from each other, nevertheless they are representative for the particular classes of modifications. The degree of substitution of distarch phosphate was not determined because the phosphorus content in modified potato starch samples does not reflect the degree of cross-linking (dissimilar to corn or wheat starch) . This is404 of DSThe choice of modified starches for the study was not accidental. Modifying groups incorporated into the structure of starch macromolecules cause multidirectional changes in the structure and physicochemical properties of this polysaccharide. Oxidised starch is manufactured by hypochlorite treatment. As a result, carboxyl groups are introduced into the structure of the hydrophilic; slightly anionic biopolymer giving it a stronger anionic character. Moreover, partial depolymerisation of amylose and amylopectin occurs, thus resulting in decreased viscosity of starch pastes . Cross-lAnalyses of the rheological properties were carried out for pastes with rather low starch concentration of 1%. Despite the low viscosity of analysed samples, it was possible to observe the effect of both–the type of chemical modification and the properties of solvent . In geneT1) and transverse (T2) relaxation times of protons, more often those of water. The separation of multiple types of water protons is based on the deconvolution of T1 and T2 measurements [T1) relaxation time describes the transfer of previously absorbed energy from spin to the surrounding environment, whereas spin-spin (T2) relocation time describes the transfer of previously absorbed energy from spin to neighbouring spins. The first one is related to the ratio of free to entrapped water and second to water molecules dynamics [LF NMR enables studies of the differences in molecular mobility between various food components. They are reflected in the longitudinal  and alkaline (9.5) pH of the environment.The presence of starch macromolecules dissolved in water also reduced the spin-spin relaxation time T2 . The lar−12 s, whereas for ice this value is 10−6 s [cτ was observed. The only exception was OSA starch, which was found to strongly immobilize water molecules under the conditions of low ionic strength. The water dynamics were most significantly reduced by native starch, regardless of the dispersion medium.The experimental data of spin-lattice and spin-spin correlation times were used for the calculation of mean correlation time–the parameter describing rotational motions of the water molecules . Pure was 10−6 s . In systs 10−6 s . When anζ potential values recorded in the analysed starch samples are presented in The z-average value is the intensity weighted mean hydrodynamic diameter of the molecules measured with the DLS method. Z-average results are presented in the All of the methods applied in our study enable studies on starch-solvent interaction. This problem has been described most broadly in relation to rheological studies ,25,26,27n) formed bunches of lines located close to each other on the loadings plot. Their mutual localization confirmed a common knowledge that a decrease in consistency index is accompanied by increase in convergence with the Newtonian flow of starch pastes [T2) as well as of ζ potential (Z) also formed bunches of lines located close to each other on the loadings plot. This indicates that the values of these parameters are primarily influenced by the properties of the starches themselves and, to a lesser extent, by environmental conditions. In contrast, position of lines describing spin-lattice relaxation time (T1) as well as intensity weighted mean hydrodynamic diameter indicate a strong influence of the environment on these parameters. This suggests that these parameters are more sensitive to the environmental conditions in which starch macromolecules are dispersed.As can be seen at h pastes . MoreoveT2) and mean correlation time (t). This suggest that ζ potential of dispersed macromolecules determines dynamics of water molecules constituting the continuous phase. This relationship has not been reported in the literature so far.The position of the bunches of lines on the biplot  also shoThe relationship between rheological properties and LF NMR parameters ,75 has bAll investigated preparations were scattered throughout the whole area of the biplot . The mosg and hydrodynamic radius Rh, seem to be the same [Particular attention should be paid to understanding the data obtained as a result of electrokinetic and dynamic light scattering studies. With regard to starch, these studies have so far only been carried out for the dispersion of starch in granular form or its solid nanoparticles ,54,55,56the same ,45,46,47the same ,78. Relethe same  and was z and intensity weighted mean hydrodynamic diameter, but only in the case of the unbuffered paste. Data measured for pastes containing buffers revealed only minor correlation between Mw and Rg. The presence of low molecular mass solutes in these pastes significantly affects the conformation of starch macromolecules and, in consequence, their dimensions. Analysis of unbuffered paste most closely reproduces the conditions of SEC analysis which results in such a good correlation.The relationship between z-average molecular mass and intensity weighted mean hydrodynamic diameter seems to be very interesting, as both parameters were determined based on light scattering phenomena. As presented in All of the methods applied in our study enable investigation of both the properties of starches and their interaction with the dispersing environment.Rheological studies showed that the pH buffering substantially decreased values of consistency indexes. The pH value itself was found not significant. Moreover, the decrease in consistency index is accompanied by increase in convergence with the Newtonian flow of starch pastes, so that in buffered pastes almost all starches revealed Newtonian-like behaviour. Cross-linking is the only modification that resulted in the increase in the consistency index; slight changes were observed for OSA, more significant for cationic and acetylated starches. Oxidised starch, manifesting the most pronounced changes, stand out from the other starches tested;LF NMR studies indicated that dissolution of starch in water resulted in a reduction in spin-lattice as well as spin-spin relaxation times. Environmental conditions had a stronger effect on spin-lattice relaxation time, whereas spin-spin correlation time was primarily influenced by the properties of the starches themselves. Moreover, the changes in relaxation times followed the patterns observed in rheological studies;Electrokinetic and DLS studies showed that potential values are primarily influenced by the properties of the starches themselves and, to a lesser extent, by the environmental conditions. In contrast, intensity weighted mean hydrodynamic diameter values were more sensitive to the environmental conditions in which starch macromolecules are dispersed.z and intensity weighted mean hydrodynamic diameter but only if no other solutes are present in the paste.The conducted research also showed complementarity and, to some extent, substitutability of the applied research methods and size exclusion chromatography (a method not used in this work). ζ potential of the dispersed macromolecules is determined by dynamics of water molecules constituting the continuous phase. It is also reflected by the spin-spin relaxation time. Spin-lattice relaxation time, as well as intensity weighted mean hydrodynamic diameter, were more sensitive to the environmental conditions of the system within which starch macromolecules were dispersed. Moreover, there is a strong relationship between M


Endosperm transparency was positively correlated with water content and negatively correlated with the cumulative area of cavities within starch granules. The indica landrace 28Zhan had a translucent endosperm and exhibited good taste. Based on starch fine structure analysis, long-chain amylopectin and the B2 chain of amylopectin might be major contributors to the good taste and relatively slow digestion of this landrace. Rice grain quality is a complex trait that includes processing, appearance, eating, cooking, and nutrition components. The amylose content (AC) in the rice endosperm affects the eating and cooking quality along with the appearance of milled rice. In this study, four  Oryza sativa L.) is one of the most important food crops in the world. The improvement of living standards has led to demands for rice with better cooking, flavor, and appearance characteristics [Rice  generally exhibits a dull or milky grain appearance after the rice grains are stored under normal conditions [indica rice. Further study is needed to optimize the trade-off between grain appearance and eating quality. The appearance of rice is usually described based on the chalkiness, farina, and waxiness of rice ,6,7. Ric unclear ,10. Recendosperm . Other snditions ,13. Siminditions . HoweverRice eating quality is a composite index that includes the smell, color, shape, taste, viscosity, hardness, and other sensory indicators after cooking . The eatWx gene, and the allelic variation of the Wx locus  contributes greatly to the different amylose levels within rice varieties [indica rice landrace with a translucent endosperm and relatively low amylose content. Interestingly, we found that 28Z rice carries the bWx allele which controls medium amylose level (~15%). Thus, the 28Z rice is a novel low-amylose type that distinguishes it from other low-amylose rice carrying mpWx and opWx alleles [indica rice. Thus, one indica glutinous rice variety  and two normal indica rice varieties (carrying bWx) with intermediate AC were selected as control varieties for grain quality and starch structure analyses. The grain transparency, physical and chemical properties, eating quality, starch particle morphology, and fine structure of starch under low moisture content were investigated in detail. The findings improve our understanding of the factors affecting rice grain appearance and rice eating quality in indica rice. It is well known that the amylose content is mainly controlled by the arieties . In prev alleles . In the indica rice varieties (O. sativa L. subsp. indica) were used in the experiment: one glutinous rice variety, Yangfunuo 4 (YFN), and three non-glutinous varieties, 28Z, Huanghuazhan (HHZ), and Yangdao 6 . These varieties are typical indica varieties, and their heading date and plant height are similar. They were planted in the experimental field of Yangzhou University  from May to October of 2021. The above varieties were planted in triplicate and arranged randomly in each plot under the same management conditions. Mature seeds were harvested from each line at the end of October. Four After being stored in a cool and ventilated place, some of the harvested mature rice was roughened with a huller, refined, ground into a powder, and sieved through a 100-mesh sieve. The sieved rice flour was then placed into an oven at 40 °C for 2 d and the dampness at room temperature was balanced for 2 d to ensure the same water content in the experiment. Finally, the rice was sealed in a self-sealing bag for use. For rice starch extraction, 10 g of white rice was used for starch preparation using the alkaline protease method described by Li et al. . For graThe apparent amylose content (AAC) of rice flour was determined using the iodine colorimetry method according to the work of Tan et al. with some modifications . Brieflyw/w). Afterward, the rice samples were steamed for 45 min and cooled to room temperature. Then, the taste value of cooked rice grain was measured. The taste value of cooked milled rice was measured using a Japanese rice taste analyzer  as described by Li et al. . SpecifiThe protein content was measured by using a Kjeldahl nitrogen meter  according to the operating manual. In terms of total starch content, it was measured with a total starch assay kit  according to the operating manual supported by the kit. A rapid viscosity analyzer  was used to analyze the viscosity of the rice flour as previously described . Briefly−1. The DSC parameters were obtained from the curve: onset temperature (To), peak temperature (Tp), conclusion temperature (Tc), and enthalpy change in gelatinization (ΔH).A differential scanning calorimetry (DSC) apparatus  was used to measure starch thermal properties according to Zhang et al. [The digestive characteristics of the rice flour were determined according to the method of Lin et al.  with somhttp://rsbweb.nih.gov/ij/, accessed on 5 May 2020). Under the environmental conditions of natural light, performance photos of milled rice were taken. Gel Pro Analyzer software was then used to convert the transparency into black-and-white image values; the transparency was positively correlated with the black-and-white image value from Gel Pro Analyzer. The scanning method used for starch grains was similar to that used for rice. However, in the scanning observation experiment of the milled rice section, it was necessary to form a natural section laterally. For the observation of starch granules in the grain cross section, rice grains were broken down naturally, fixed on the sample stage, coated with gold, and observed by scanning electron microscopy . The isolated starch was also analyzed by SEM. The average size and size distribution of the starch grains were determined from the SEM images using Image J software  was used to evaluate the degree of starch long range order structure according to the method of Wei et al. . Briefly−1 were extracted from the ATR-FTIR spectra after correction. The experiments were performed in duplicate. The external structure of the starch granules was examined via ATR-FTIR spectroscopy on a Varian 7000 FTIR spectrometer with an ATR single-reflectance cell containing a germanium crystal according to the method of Cai et al. . In detaplus NanoFit software. The Bragg spacing d was calculated from the position of the peak (qo) according to d = 2π/oq. The experiments were performed in duplicate.SAXS analysis of starch lamellar structures was performed using a Bruker NanoStar SAXS instrument equipped with a Vantec 2000 detector and pin-hole collimation for point focus geometry as previously described by Wei et al. . The staThe isolated starch was debranched with isoamylase  before starch fine structure analysis. For the starch relative molecular weight distribution measurement, a PL-GPC 220 high-temperature gel permeation chromatograph system  was used according to our previous report [The degree of polymerization (DP) of amylopectin was determined using a high-performance anion-exchange chromatography (HPAEC) system  equipped with a pulsed amperometric detector, a guard column, a CarboPacTM PA200 analytical column, and an AS-DV autosampler as described previously [The measurement data were collected in Microsoft Excel and analyzed using SPSS 16.0 statistical analysis software. All data were reported as mean ± standard deviation. indica rice varieties were compared. As shown in The grain morphologies of the white rice from the four To quantify the grain transparency, the endosperm transparency was converted into a relative translucence level by using the gray analysis function in Gel Pro Analyzer. Among the studied varieties, the glutinous rice YFN had the largest relative translucence and highest opacity, while 28Z had a higher relative translucence than HHZ and 9311 . The rel2) was significantly lower than that in YFN grains  B. The DSS), the peak position (maxS), and the Bragg spacing (D) of starch. Meanwhile, the diffraction peak intensity (maxI) of YFN (336.51 counts) was higher than that of the other three indica rice varieties. The maxI value of 28Z was smaller than that of HHZ (maxI 165.85 counts) but higher than that of 9311 (maxI 149.606 counts). The short-range ordered structures of starch granules were analyzed by ATR-FTIR. The degree of short-range order was analyzed by calculating the ratio of starch absorption at 1045 cm−1 to that at 1022 cm−1 ((1045/1022) cm−1). The infrared absorption curves of the four indica rice varieties were relatively consistent. Based on the calculated eigenvalues, there was no significant difference in (1045/1022) cm−1 among the three non-waxy varieties . As shown in arieties . Howeverindica rice varieties. The branching degree of 28Z is different from that of HHZ (SAP/LAP) 2.89, but there is a significant difference, YFN and 9311 (SAP/LAP) compared. To further clarify the distributions of amylopectin chain length in the four indica rice varieties, the structural features of amylopectin were analyzed by high-performance anion-exchange chromatography : fully transparent glassy, transparent, translucent, dark, partial white, light milky white, and pure milky white . Rice ACindica rice varieties revealed closely arranged and regular starch grains with no holes between starch granules but remarkable cavities within single starch granules. These cavities appeared even in the transparent grains of HHZ and 9311 under dry conditions. The cumulative cavity area of 28Z was lower than that of YFN but greater than that of HHZ and 9311. Through correlation analysis, we found that grain transparency was significantly negatively correlated with the cavity area within starch granules. These results are consistent with our previous findings that the cavity size in the starch granule core adversely affected the opaque appearance [In addition to grain moisture content and AC, starch morphology is an important factor in endosperm transparency. Liu et al. found that the small cavities between starch granules and the holes within starch granules contribute to the opaque endosperm of soft rice . Some lopearance ,24. Studpearance . Considepearance ,30. ThusThe AC within the rice endosperm is the most critical determinant of rice eating quality along with the physicochemical properties of starch . Generalindica rice varieties, while the diffraction peak intensity of 28Z was smaller than that of HHZ and 9311. Yuryev et al. reported that maxI was negatively correlated with AC [−1 can be used to reflect the ratio of amorphous to ordered components in starch [−1 values, and 28Z had a smaller amorphous component than HHZ. This is consistent with the crystal structure analysis of starch by XRD and SAXS.The physicochemical properties of starch are often closely related to the fine structure of starch. In the four rice varieties, the relative crystallinity of starch decreased with the AC values. In the XRD pattern, the peak at the 2θ angle of 23° corresponds to the amylose–lipid complex . The dif with AC . Therefon starch . In the Generally, rice starch consists of two components, amylose and amylopectin, and the fine structures of both components contribute to physicochemical properties. The relative molecular weight distributions determined by GPC showed that the B-chain content of secondary branch starch in 28Z was significantly lower than that of 9311 but higher than that of HHZ. Rice varieties with better eating quality generally have a higher proportion of short-chain amylopectin (AP1) ,38. The indica rice varieties. Notably, 28Z is a novel type of low AC rice with a higher AC than normal soft rice varieties, resulting in a translucent endosperm rather than a dull appearance. Our results indicate that grain transparency is positively correlated with water content and negatively correlated with the cavity size within starch granules. In addition, among the four indica rice varieties, we found that the eating quality of 28Z rice was better than that of non-glutinous rice. Considering the moderate AC and good taste value of 28Z, we believe that 28Z is a promising germplasm to improve rice grain quality through breeding. In particular, this variety achieves a trade-off between rice eating quality and appearance. In summary, we compared the appearance, physicochemical properties, and starch fine structures of rice grains from four


To explore the quality differences between dried wheat noodles (DWNs), stone-milled dried whole wheat noodles (SDWWNs), and commercially dried whole wheat noodles (CDWWNs), the cooking quality, texture properties, microstructure, protein secondary structure, short-range order of starch, antioxidant activity, in vitro digestive properties, and estimated glycemic index (eGI) of the noodles were investigated. The results showed that the cooking loss of SDWWNs was significantly lower than that of CDWWNs. The springiness, cohesiveness, gumminess, chewiness, and resilience of SDWWNs reached the maximum, and the tensile strength was significantly increased. The continuity of the gluten network of SDWWNs was reduced, and more holes appeared. The protein secondary structure of the SDWWNs and CDWWNs was mainly dominated by the β-sheet and β-turn, and the differences in the starch short-range order were not significant. Prior to and after the in vitro simulated digestion, the DPPH radical scavenging activity, the hydroxyl radical scavenging activity, and the total reducing power of the SDWWNs were the highest. Although the digested starch content of SDWWNs did not differ significantly from that of CDWWNs, the eGI was significantly lower than that of the CDWWNs and DWNs. Overall, the SDWWNs had certain advantages, in terms of quality characteristics. Triticum aestivum L.) is the earliest food crop grown by humans and is grown all over the world. Whole wheat flour contains more beneficial components than refined flours, derived solely from the endosperm, such as dietary fiber, minerals, vitamins, phenolic compounds, feruloylated oligosaccharides, glutathione, octacosanol, and phytosterols [Wheat . To obtain whole wheat flour, the wheat was ground in a stone mill with a diameter of 600 mm and a grinding speed of 28–30 rpm, then passed through a 125 µm sieve. The contents of moisture, ash, fat, and protein in the flour were determined by AACC 44-01.01, 08-12.01, 30-25.01, and 46-12.01 , respect200 g of flour, 75 g of purified water, and 1.70 g of salt were mixed for 5 min. The prepared dough was placed in a sealed plastic bag and matured for 15 min at room temperature. Then, the dough sheet was pressed using a noodle-making machine  until it was smooth. Then, the sheet was cut into fresh noodles of 1 mm thickness and 3 mm width. Following the drying at room temperature for 24 h, the dried noodles were cut into 22 cm length.1) and cooked in 500 mL boiling water for the optimum cooking time. Then, the cooked noodles were taken out and measured weight (m2) after absorbing the water, with two pieces of filter paper for 5 min. Then, the cooked noodles were collected and dried in an air oven at 135 °C until they reached a constant weight (m3). The water uptake ratio and cooking loss were calculated with the following Formulas (1) and (2), respectively. The noodle soup was cooled to room temperature, fixed to 500 mL with deionized water, and shaken well, and the turbidity of the noodle soup was measured at 720 nm.The water uptake ratio and cooking loss were determined by referring to the methods of Liu et al.  and WangThe texture properties were tested using a TA.XT plus texture analyzer , according to Liu et al. , with soThe raw noodles were broken into small squares of 1~2 mm, fixed on the sample table with the broken side facing upward for spraying gold, and observed using a scanning electron microscope . The morphologies of the noodles were imaged with an accelerating voltage of 25 kV.−1 with a resolution of 4 cm−1 [−1). The spectra were analyzed using Omnic 8.2 and Peakfit 4.12 software for measuring the relative area of the corresponding amide I region [−1 with a peak width of 40 cm−1, and an enhancement factor of 1.9. The ratio of the peak intensity at 1047/1022 cm−1 reflected the ratio of the short-range ordered structure in starch [The raw and cooked noodles were freeze-dried, then 1 mg of the tested sample and 100 mg KBr were put into an agate mortar, ground well, and pressed. The FTIR spectra were obtained by scanning from 400 to 4000 cmf 4 cm−1 . The secI region . The spen starch .g for 10 min. The obtained supernatant was collected and fixed to 10 mL with 80% ethanol. The DPPH radical scavenging capacity and hydroxyl radical scavenging capacity were measured, as described previously [The method for extracting the phenolic substances from the raw and cooked noodles was obtained from a published study, with slight modifications . The 2 geviously . +• working solution, the mixture reacted in the dark for 6 min, and the absorbance was measured at 734 nm. Deionized water was used instead of the sample solution as the blank group, and deionized water instead of the ABTS+• working solution as the control group. The ABTS+• scavenging activity was determined using the formula (3):The ABTS radical scavenging activity was determined using the method followed by Sridhar et al. , with suThe total reducing power was measured using the method suggested by Zhang et al. , with a 2PO4 in 500 mL of deionized water. The pH was adjusted to 6.8 with the addition of 0.1 mol/L NaOH. Finally, 0.20 g of trypsin was added to each 100 mL of buffer.The simulated saliva and gastric fluid were prepared, according to the method reported by Gawlik-Dziki et al. . The simg for 2 min at 37 °C. In the gastric digestion step, the mixture of the remaining noodles from the last step and 30 mL of simulated gastric fluid was adjusted to pH 3.0, with the addition of 0.1 mol/L NaHCO3 and then shaken at 120× g for 2 h at 37 °C. In the intestinal digestion step, the mixture of the remaining noodles from the last step and 30 mL of the simulated intestinal fluid was adjusted to pH 7.0, with the addition of 0.1 mol/L NaOH and then shaken at 120× g for 3 h at 37 °C. The samples digested by mouth, stomach, and intestine were inactivated and then centrifuged at 3200× g for 10 min, respectively, and the supernatant was used to determine the antioxidant activity.The in vitro digestion model was carried out with subtle adjustments . In the g in a constant temperature shaker  at 37 °C, and 2 mL of the digest was taken at 0, 20, 30, 60, 90, 120, 150, and 180 min, respectively, and then centrifuged at 3200× g for 5 min, following 5 min of enzyme inactivation in a boiling water bath. Glucose in the supernatant was measured using the 3,5-dinitrosalicylic acid (DNS) method [The in vitro digestibility of the noodles was measured, according to the previous report, with a slight revision . First, ) method . The con) method . The sta) method .The starch digestion curves were plotted using the starch hydrolysis rate as the vertical coordinate, and time as the horizontal coordinate. The curve followed the non-linear model established by Goni et al. . The stat is the percentage of digested starch at time t (min), C∞ is the equilibrium concentration of starch hydrolyzed after 180 min, k is the kinetic constant, t∞ is the final time point (180 min), and t0 is the initial time point (0 min). CThe hydrolysis index (HI) was obtained by dividing the area under the hydrolysis curve of the noodles by the corresponding area of the reference sample (white bread). The eGI was calculated, according to the HI value by Formula (6).The mean values with standard deviations of the replicate measurements are presented. The statistical analysis was performed using SPSS 21.0 . The images were drawn using Origin 2021 .p < 0.05). Wheat gluten protein had a good water absorption, whereas bran weakened the three-dimensional structure formed by the gluten protein, to a certain extent, reduced the water holding capacity of the gluten protein, and reduced the water uptake ratio of the whole wheat noodles [p < 0.05), which could be ascribed to the precipitation of amylose, due to the disruption of the gluten matrix continuity [As shown in  noodles . The noontinuity . In addintinuity  found thp < 0.05), and the breaking force of the wheat noodles was much less than that of the two whole wheat noodles, which was only 0.73 N. The breaking force of the raw noodles is related to the protein content of the flour, while whole wheat flour contains all of the proteins of wheat seeds, resulting in a highly stable starch-protein-fat complex [The greater the breaking force and breaking distance of the raw dried noodles, the more flexible they are and less likely to break during packaging, transportation, and sales. As can be seen from  complex . The bet complex . The for complex .p < 0.05), probably because the bran supported the internal structure of the noodles and formed a stable structural system, resulting in an increased hardness [In hardness . The sprhardness . The sprhardness . As shown in −1), random coil structure (1640–1650 cm−1), α-helix structure (1650–1660 cm−1), and β-turn structure (1660–1700 cm−1) [1047/1022 of the noodles are shown in 1047/1022 were significantly decreased (p < 0.05), probably because the starch was hydrolyzed after absorbing water and swelling during cooking, and the hydrogen bonds between the molecular chains were broken and the helical structure was unraveled [00 cm−1) . The pronraveled .+• scavenging activity, and the total reducing power of the three cooked dried noodles were significant (p < 0.05). The DPPH radical scavenging activity, hydroxyl radical scavenging activity, and total reducing power of the cooked-SDWWNs were the highest, which were 25.76%, 17%, and 0.444, respectively. The antioxidant activity of the cooked noodles was reduced, compared to the raw noodles, probably because the phenolic substances in the noodles were destroyed during high-temperature cooking and lost to the noodle soup.The antioxidant activity of the whole wheat noodles was higher than that of the wheat noodles, due to the presence of carotenoids, polyphenols, alkylresorcinols, phytic acid, and other antioxidant components in the bran and germ . In Figu+• scavenging activity and hydroxyl radical scavenging activity of the noodles were elevated after the intestinal digestion, probably on account of the increase in pH leading to the improvement of the stability of the phenolic compounds [In the oral digestion stage, the DPPH radical scavenging activity, the hydroxyl radical scavenging activity, and the total reducing power were in the order of SDWWNs > CDWWNs > DWNs . Compareompounds .p < 0.05), probably because white bread was loose and porous, which increased the contact area with glycosylase and α-amylase and promoted the starch digestion and absorption [p < 0.05) than that of the whole wheat noodles, mainly because the whole wheat noodles are rich in dietary fiber and resistant starch. The differences between the RDS, SDS, and RS contents of the SDWWNs and CDWWNs, were not significant (p > 0.05), probably because part of the whole wheat flour had been gelatinized after the stone milling and the starch structure had been destroyed, which promoted the decomposition of the starch by the digestive enzymes. Furthermore, the rich protein in the stone-milled whole wheat flour was tightly bound to the starch to prevent the digestive enzymes from entering the starch granules [As shown in sorption . Comparegranules .It can be seen from ∞, AUC, HI, and eGI of the DWNs, were significantly higher than those of the SDWWNs and CDWWNs (p < 0.05). The higher the RS content, the lower the C∞ and eGI. Different samples were different in k. The difference between k for the noodles and white bread was significant (p < 0.05), with smaller values indicating a slower in vitro digestion of starch to C∞. The eGI value was in the order of white bread (94.4) > DWNs (79.23) > CDWWNs (71.51) > SDWWNs (69.37). The eGI of different dried noodles was significantly lower than that of white bread (p < 0.05), which indicates that dried noodles are a good carrier for processing low eGI foods. The eGI value of SDWWNs was significantly lower than that of CDWWNs (p < 0.05), which was probably caused by the higher dietary fiber content and proportion of amylase to amylopectin of SDWWNs, resulting in the differences in the in vitro digestion properties of starch [In f starch . Moreove CDWWNs 7.51 > SDW DWNs 79.3 > CDWWNf starch .The SDWWNs performed best, in terms of the water uptake ratio (154.68%), cooking loss (6.31%), turbidity of the noodle soup (0.085), and tensile strength (0.24 N). The gluten network continuity of the SDWWNs and CDWWNs was reduced, compared to the DWNs, and more holes appeared, as a result of the presence of bran. The number and area of holes in the SDWWNs were also significantly increased. The protein secondary structure of the SDWWNs and CDWWNs was mainly composed of the β-sheet and β-turn. The high temperature changed the curled to stretched structure of the protein molecules, and the protein aggregation was promoted by the interaction between the protein molecules, so the β-sheet content of the cooked noodles increased. Prior to and after the in vitro simulated digestion, the DPPH radical scavenging activity, the hydroxyl radical scavenging activity, and the total reducing power of the SDWWNs were the highest. The RDS, SDS, and RS contents of the three kinds of noodles were different, and the starch hydrolysis rate was in the order of DWNs (73.36%) > CDWWNs (66.41%) > SDWWNs (64.25%). At the same time, the eGI value of the SDWWNs was the lowest. Overall, the SDWWNs had obvious advantages, in terms of cooking quality, textural properties, antioxidant activity, and controlling the glycemic response.