The effect of retrogradation time and ambient relative humidity on the quality of extruded oat noodles

Abstract Commercial process of oat noodles was mainly hindered by its lack of gluten and difficulty in forming dough. Extrusion could be an effective method to produce oat noodles by forming network of gelatinized starch, and noodle quality could be improved by regulating the retrogradation process. In this study, we produced oat noodles by two‐step extruding and investigated the effect of retrogradation treatment (retrogradation time and ambient relative humidity) on noodle properties. At each corresponding ambient relative humidity (RH), the starch crystallinity and enthalpy value increased, while setback value decreased, as well as noodle cooking loss was significantly improved as retrogradation time increased to 48 hr, and then decreased at 72 hr. At the same retrogradation time, the starch crystallinity, setback, and enthalpy value decreased to RH70% and then had a slight rise at RH80%, while noodle cooking loss with reversal trend. The retrogradation time of 48 hr and ambient RH of 60% could be an optimum treatment for effectively improving extruded oat noodle quality. Furthermore, multivariate data analysis indicated that samples at the same ambient RH tended to be clustered together. This study could provide basic knowledge for controlling processing condition of the extruded oat noodle.

starch is gelatinized during extrusion, thereby promoting the formation of network (Shiau, 2010). Oat noodles can be prepared by this technique, and it requires reboiling or soaking in hot water before eating (Reungmaneepaitoon, Sikkhamondhol, & Tiangpook, 2006). However, extruded oat noodles are faced with high cooking loss and poor eating quality after boiling. Furtherly, regular one-step extrusion could not produce oat noodles with satisfying cooking quality, so a second extrusion was introduced to press the intermediate product, which could give the noodle uniform and compact shape, which could meet with consumer's requirements.
With regard to the nongluten food, starch plays an important role in its processing and eating qualities (Witczak et al., 2016). Regulating or changing starch structure, that is, amylose and amylopectin, crystalline structure, and granular structure, can drastically affect noodle qualities (Li, Dhital, & Wei, 2017). Starch retrogradation is a process that gelatinized starch molecules rearrange and form a more ordered structure, which contribute to the increase of crystallinity and endow the products' apparent quality with firmness and rigidness Wang, Li, Copeland, Niu, & Wang, 2015). This process is influenced by several factors, such as storage temperature, storage time, moisture content, and additives (Aguirre, Osella, Carrara, Sánchez, & Buera, 2011;Bello-Pérez, Ottenhof, Agama-Acevedo, & Farhat, 2005;Patel & Seetharaman, 2010). Several studies have found drying temperature had no significant effects on the cooking loss of rice noodles, and some other researches have got similar results (Aktan & Khan, 1992;Lee, Woo, Lim, Kim, & Lim, 2005). In general, starch retrogradation possesses two processes, short-term and long-term retrogradation. Short-term retrogradation can be very quickly, usually completed within several hours after gelatinization; this process is dominated by amylose rearranging (Xiong, Li, Shi, & Ye, 2017). In contrast, long-term retrogradation usually takes several days and is mainly the rearrangement of amylopectin (Krystyjan, Adamczyk, Sikora, & Tomasik, 2013). Water also plays a crucial role in the retrogradation process. Within a certain range of water content, the increase of water can promote starch crystallization, because amylopectin can move more quickly under ample water content, while excess water leads to an inhibition of crystallization owing to its dilute effect making amylopectin with more mobility and rearranging more difficult (Ding, Zhang, Tan, Fu, & Huang, 2019).
Different retrogradation treatment condition resulted in different retrogradation phenomenon and affected the noodle texture significantly (Mariotti, Iametti, & Cappa, 2011). Regulating the environmental storage condition is an effective way to promote starch retrogradation for its easy handling, energy saving, and avoiding of external additives. In this study, we aimed to investigate the extruded oat noodle starch retrogradation and the noodle qualities under different ambient relative humidity and storage time, exploring the effect of regulating storage condition on starch structure and noodle qualities. This study can provide a theoretical basis for the development of commercial oat noodles.

| Preparation of extruded naked oat flour noodle
The oat flour was obtained from Mengye Company in Inner Mongolia, which was milled from Chinese naked oat (moisture content 13%). The extruded oat flour noodles were produced using a factory-scale twinscrew extruder (YMP, Dayi, Jinan). The temperatures of barrel zones from I to β were 70°C, 80°C-100°C, and 140°C, respectively. Water content of the oat flour was adjusted to 38% prior to extrusion. The feed rate and screw speed of the first step extrusion was consistently kept at around 60 kg/hr and 300 rpm while the second step extrusion was a one screw extruder which ran at a speed around 200 rpm without heating process. Sample was extruded twice to produce final oat 1. Ambient RH and retrogradation time affect oat noodle quality and starch properties.
2. Retrogradation conditions improved noodle quality by regulating starch crystalline.
3. PCA and cluster analysis were used to optimize and verify noodle processing.
F I G U R E 1 Illustration of extruded oat noodle processing noodle product. The first extrusion was to pregelatinize the starch, and the second extrusion was to shape the noodles. Producing process can be illustrated in Figure 1.
After extrusion, the noodles were collected and retrograded by regulating the retrogradation time and ambient relative humidity (RH) in an incubator (HWS, Taisite). The retrogradation treatment was carried out for 12, 24, 48, and 72 hr at 25°C with the ambient RH of 60%, 70%, and 80%, respectively. All the samples were collected and transferred to a cryogenic refrigerator (DW-40L278, Haier, Qingdao) at −40°C once each retrogradation treatment was completed. The sample moisture content was determined by the method GB 5009.3-2016 (Chinese national standard for food safety: determination of moisture content in food). The samples were kept in the refrigerator until analysis. Samples were freeze-dried for pasting properties test, X-ray diffraction (XRD) measurement, and thermal properties test.

| Noodle cooking quality test
Noodle cooking loss was determined following the AACCI approved method 66-50 (AACC, 2000). Briefly, 20 g of noodles was accurately weighed and then boiled in 1,000 ml distilled water according to its optimum cooking time. After cooled to room temperature, the supernatant was collected and diluted to 1,000 ml with distilled water. 100 ml of the noodle soup was transferred into a beaker and then heated to evaporate. After most of the water was evaporated, another 100 ml of the supernatant was transferred to the beaker and was evaporated to near dry. Then, the beaker was placed in an air oven and heated to a constant weight at 105°C. The residue was weighted and reported as a percentage of the initial sample. The cooking loss was calculated according to the following equation.
where M is the dry matter weight of the supernatant, W is the moisture content of the noodles, and G is the fresh sample weight.

| Pasting properties
Pasting properties were determined using a Rapid Visco Analyzer

| X-ray diffraction (XRD) measurement
Starch crystalline structure was analyzed by an X-ray diffractometer coupled with a Cu-Kα radiation detector (D/Max2550VB+/ PC, Rigaku Corporation) at 40 kV and 40 mA. Freeze-dried noodle sample was milled and detected with a step size of 0.02 and a scanning rate of 4°min −1 from 5° to 45° (Zeng et al., 2015). The relative crystallinity was obtained by using Jade software 5.0 (Materials Data Inc.) to calculate the percentage of the peak area to the overall diffractogram area.

| Thermal properties
Thermal properties of samples were carried out on a differential scanning calorimeter (Q600 SDT, TA Instruments). Approximately 2 mg of sample was weighed and placed into aluminum pans, and 2 μl of distilled water was added. The suspension was equilibrated at room temperature overnight prior to test. Samples were heated from 20 to 95°C at a rate of 10°C min −1 (Qiu et al., 2017). Onset (T o ), peak (T p ), and final temperatures (T c ), as well as gelatinization enthalpies (ΔH), were obtained from the thermograms by the DSC data recording software.

| Statistical analysis
The data were presented as mean ± SD. All measurements were carried out with three replicates. Significance was carried out using SPSS software (version 16.0, SPSS Inc.) by one-way analysis of variance (ANOVA) with Duncan's method.

| Cooking quality
Cooking loss reflects the cooking resistance of noodles, and it is also an essential criterion for evaluating noodle cooking quality (Chillo, Ranawana, & Henry, 2011). Noodles without retrogradation treatment have a much higher cooking loss than those been treated. As demonstrated in Figure 2, varied retrogradation treatments caused Cooking loss = 5M∕ G × 1 − W × 100%, F I G U R E 2 Sample cooking loss under different retrogradation treatment predominant differences in cooking loss. When the RH was constant and retrogradation time was within 48 hr, the cooking loss decreased with time extension and was lowest at 48 hr, whereas a further increase occurred at a longer storage time of 72 hr. Under each ambient RH, the minimum cooking loss was observed at 48 hr, which was 5.04% (RH 60%), 8.17% (RH 70%), and 6.25% (RH 80%), respectively. Cooking loss varied at different ambient RH under varied retrogradation time.
Extrusion processing caused oat starch gelatinizing and formed a network to develop dough, which assisted the structural maintenance of noodles when cooking (Witczak et al., 2016). Time and ambient RH affected the starch crystallinity. The improved cooking quality could be ascribed to the increased crystallinity of starch after retrogradation, which enabled a more compact and rigid network and therefore prevented components leaking outside the network . However, the increase of cooking loss at further extending time was associated with the reversibility of starch crystallization, which conversely resulting in an incompact and week network (Ambigaipalan, Hoover, Donner, & Liu, 2013). In this study, the optimum cooking quality was observed at 48 hr with an ambient RH of 60%, which could be owing to the highest starch crystallinity.

| Pasting properties
RVA parameters are summarized in Table 1. SB value reflects retrogradation tendency of amylose. In general, higher SB values show a greater tendency for retrogradation (Ambigaipalan et al., 2013;Zhang et al., 2018). The highest SB values observed at each RH were 447 cP (60% RH-48 hr), 274 cP (70% RH-48 hr), and 388 cP (80% RH-24 hr). As time further prolonged, SB value declined, indicating that the retrogradation level of noodle starch reached a peak and then gradually fell down. This could also be well understood that the whole retrogradation treatment period is a combination of short-term and long-term retrogradation. During short-term retrogradation, amylose recrystallization dominated the retrogradation process, while amylopectin came to dominate the long-term retrogradation and some short chains were a reversible process (Chen, Ren, Zhang, Tong, & Rashed, 2015).  ascribed to reversible crystallization process of amylopectin. The short-term retrogradation of starch usually occurs with a few hours, which is mainly dominated by amylose recrystallization and is unreversible, whereas the long-term retrogradation is dominated by amylopectin recrystallization and is reversible (Miles, Morris, & Orford, 1985), which was because that the amylopectin recrystallization of shorter branch of (DP14 -18) has less stability than amylose crystal (Karim, Norziah, & Seow, 2000).

| Thermal properties of samples
Water content could also produce a great influence on starch melting enthalpies. As shown in Table 2, the enthalpies exhibited a decreasing tendency as ambient RH increased from 60% to 80% at each corresponding time. Higher environmental RH enabled oat starch to absorb more water, which could make amylopectin move more quickly and accordingly contribute to its retrogradation process ( (Johnson & Mauer, 2019). However, excess water had a dilute effect on the starch molecule and appeared as starch with more mobility, which made the crystallization more difficult, therefore inhibiting the retrogradation process, and produced a less ordered and stable starch molecule (Ding et al., 2019). The enthalpies were consequently decreased. This result indicated that the ambient RH of 60% and storage time of 48 hr could produce the most stable crystallites.

| Crystal structure
X-ray diffraction can well reflect the starch crystallinity ( Figure 3). As demonstrated in Figure 1, the noodles with all treatments showed diffraction peaks at 2θ of 13.8°, 17.5°, and 19.5°, respectively, indicating a typical B-type structure (Zobel, Young, & Rocca, 1988) and a V-type structure (Hoover, Smith, Zhou, & Ratnayake, 2003). This could be ascribed to the cooling process and retrogradation of gelatinization starch during storage. The retrogradation starch showed an obvious difference in the relative crystallinity as the storage time increased. After extrusion under high pressure and high temperature, V-type crystalline was formed because of the starch and lipid complex. The most intensive peak around 20° was observed in each sample, which indicated that V-type structure was intensified by complex of starch and lipid (Hoover et al., 2003). For the noodles at the same ambient relative humidity, the relative crystallinity gradually increased and reached peak at 48 hr (Table 3). For shortrange molecular order, the amylose retrogrades very quickly, while long-term retrogradation could take several days to complete amylopectin rearranging (Biliaderis, 2009). In this study, the retrogradation treatment process on samples in all ambient RH had completed within 48 hr.
Ambient relative humidity produced a profound effect on the relative crystallinity. At the same storage time, the relative crystallinity first fell and then rose as the RH increased, and it showed the highest value at RH of 60%. Ambient relative humidity enables starch absorbing more moisture and consequently affects the process of starch retrogradation (Johnson & Mauer, 2019). The ample moisture allowed amylose and amylopectin chains moving more flexible, therefore resulting in rearranging of amylose and amylopectin and forming more crystals. However, excess moisture produced a dilute effect, causing the realignment of amylose and amylopectin more difficult, and hence showing a decreased relative crystallinity (Wang, Li, Zhang, Copeland, & Wang, 2016). Data with different letters in the same column mean significant difference (p < .05).

| Principal component analysis
most significantly to the retrogradation quality. Therefore, a mathematical method to statistically analyze the data was obtained related to noodle quality (Nwabueze & Anoruoh, 2009). Principal component analysis (PCA) is an effective method to simplify data by dimensionality reduction. According to viewpoint of accumulative variance contribution, principal components with accumulative variance contribution reaching 85% were chosen (Hervé & Williams, 2010). Table 4 shows the selected first three principal components whose eigenvalues were greater than 1, and the sum of their infor-

| Cluster analysis
After the ten physical and chemical indicators, data were standardized and converted, the Chebyshev distance was used, and the system was clustered by the squared deviation method (Milligan & Cooper, 1986). The results shown in Figure 5   optimum retrogradation treatment should be around the ambient relative humidity of 60% and last about 48 hr. The results will provide theoretical guidance for the controlling condition of extruded oat noodle production.

CO N FLI C T O F I NTE R E S T
The authors declared that they have no conflicts of interest to this work.