Understanding the influence of curdlan on the quality of frozen cooked noodles during the cooking process

Machine learning-enabled hyperspectral approaches for structural characterization of precooked noodles during refrigerated storage

The structural features of precooked noodles during refrigerated storage were non-destructively characterized using hyperspectral imaging (HSI) technology along with conventional analytical methods. The precooked noodles displayed a more rigid texture and restricted water mobility over the storage period, derived from the recrystallization of starch. Dimensionality reduction techniques revealed robust correlations between the storage duration and HSI absorbance of the noodles, and from their loading plots, the specific peaks of the noodles related to their structural changes were identified at wavelengths of around 1160 and 1400 nm. The strong relationships between the HSI results of the noodles and their storage period/texture were confirmed by training four machine learning models on the HSI data. In particular, the support vector algorithm displayed the best prediction performance for classifying precooked noodles by storage period (98.3% accuracy) and for predicting the noodle texture (R2 = 0.914).

Effect of oxidized starch on the storage stability of frozen raw noodles: Water distribution, protein structure, and quality attributes

Freezing is a popular method of food preservation with multiple advantages. However, it may change the internal composition and quality of food. This study aimed to investigate the effect of modified starch on the storage stability of frozen raw noodles (FRNs) under refrigerated storage conditions. Oxidized starch (OS), a modified starch, is widely used in the food industry. In the present study, texture and cooking loss rate analyses showed that the hardness and chewiness of FRNs with added OS increased and the cooking loss rate decreased during the frozen storage process. Low-field nuclear magnetic resonance characterization confirmed that the water-holding capacity of FRNs with OS was enhanced. When 6% OS was added, the maximum freezable water content of FRNs was lower than the minimum freezable water content (51%) of FRNs without OS during freezing. Fourier-transform infrared spectroscopy showed that after the addition of OS, the secondary structures beneficial for structural maintenance were increased, forming a denser protein network and improving the microstructure of FRNs. In summary, the water state, protein structure, and quality characteristics of FRNs were improved by the addition of OS within an appropriate range.

Effects of Freeze-Thaw Cycles on the Quality of a Novel Mixed Grain Composite Dough and Its Product (Potato-Oat Yu): Hybridization of Potatoes and Oats

To provide a theoretical basis for the frozen storage of potato-oat composite dough and its products, this investigation examines changes in the quality of potato-oat composite dough and its resulting product during freeze-thaw cycles. The study measured key aspects such as moisture content, dynamic rheological properties, water state, protein secondary structure, color, and sensory assessment. The influence of these factors on the product's quality is analyzed. The findings revealed that the freeze-thaw treatment caused a reduction in water content, freezable water, and deeply bound water, as well as an increase in weakly bound water, β-sheet, random coil, and α-helix, and a decreased β-turn of the potato-oat composite dough. Additionally, the dough treated by freeze-thaw cycles resulted in darker color, and the sensory properties of the product were affected significantly after exceeding three freeze-thaw cycles. Moreover, an increase in the number of freeze-thaw cycles resulted in an upward trend of moisture content for the composite dough, whereas G' initially increased and then decreased. The G″ of the composite dough peaked after the third freeze-thaw cycle. Overall, the composite dough quality significantly deteriorated at the fourth freeze-thaw cycle. There was a significant increase in the freezable water content, the largest modulus of elasticity, and the smallest tan δ. Therefore, the usage of the potato-oat composite dough should not exceed three cycles.

Precooking treatments affect the sensory and tensile properties of autoclaved recooked noodles via moisture distribution and protein structure

To improve the quality of autoclaved recooked noodles (ARNs), this study explored the effects of precooking on the sensory and tensile properties of ARNs from the perspectives of changes in protein structure and water distribution. The results showed that the ARNs of two kinds of pretreatments (Boiling 2 min, Boiling 1 min + Steaming 2 min) presented the best sensory quality (average score ≥ 7.50) and high tensile properties (tensile distance ≥ 45.24 mm). After autoclaving and recooking, the proportion of tightly bound water increased by 11.30%-12.52%, resulting in stronger water-solid interaction. The results of laser confocal microscopy (CLSM) proved that a strengthened gluten network (protein percentage area ≥ 40.28%; junction density ≥ 10.96 × 10^-4) appeared. Therefore, appropriate precooking treatment could effectively improve the sensory quality and tensile properties of ARNs by enhancing the tightly bound water ratio and strengthening the gluten network.

Effect of sanxan gel on the quality of salt-free noodles during cooking

The effect and mechanism of sanxan on the quality of salt-free noodles (SFNs) were investigated from different cooking stages (initial stage, 1 min; optimum cooking time, OCT; overcooked time, OT). The results showed significant changes in the cooking process with the addition of 1.2% sanxan. The OCT for noodles with 1.2% sanxan (experimental group, EG) was extended from 5 to 7 min compared to the non-added noodles (blank group, BG) and 1.5% salt-containing noodles (control group, CG). The hardness and adhesiveness of BG, EG, and CG all decreased significantly during cooking. In contrast, the springiness, maximum tensile strength, and tensile fracture distance trended first to increase and then to decrease. At OCT, EG had the highest hardness (3971.69 ± 94.49 g), adhesiveness (372.26 ± 33.56 g s), and maximum tensile strength (41.51 ± 2.76 g), which remained large even after overcooking. However, those in BG and CG showed a significant reduction (p < 0.05). The proportion of free water increased progressively as cooking progressed, with CG showing the largest increase, from 82.29% to 91.19%, whereas EG showed the smallest increase, from 78.34% to 86.02%. During the cooking process, the addition of sanxan delayed the water migration, whereas salt promoted it. Sensory evaluation showed that EG was smoother in appearance than BG and tasted malty with a slight stickiness. Moreover, EG had the smallest k₁ and C_∞ values. Thus, sanxan is an effective additive to enhance the quality of SFNs and can replace the role of salt in noodles in some properties, which is beneficial for the development of SFNs.