Cultivation pattern affects starch structure and physicochemical properties of yam (Dioscorea persimilis)

Resistant starch from yam: Preparation, nutrition, properties and applications in the food sector

Yam is a significant staple food and starch source, particularly in tropical and subtropical regions, holding the fourth position among the world's top ten tuber crops. Yam tubers are rich in essential nutrients and a diverse range of beneficial plant compounds, which contribute to their multifaceted beneficial functions. Furthermore, the abundant starch and resistant starch (RS) content in yam can fulfil the market demand for RS. The inherent and modified properties of yam starch and RS make them versatile ingredients for a wide range of food products, with the potential to become one of the most cost-effective raw materials in the food industry. In recent years, research on yam RS has experienced progressive expansion. This article provides a comprehensive summary of the latest research findings on yam starch and its RS, elucidating the feasibility of commercial RS production and the technology's impact on the physical and chemical properties of starch. Yam has emerged as a promising reservoir of tuber starch for sustainable RS production, with thermal, chemical, enzymatic and combination treatments proving to be effective manufacturing procedures for RS. The adaptability of yam RS allows for a wide range of food applications.

Quality and Process Optimization of Infrared Combined Hot Air Drying of Yam Slices Based on BP Neural Network and Gray Wolf Algorithm

In this paper, the effects on drying time (Y1), the color difference (Y2), unit energy consumption (Y3), polysaccharide content (Y4), rehydration ratio (Y5), and allantoin content (Y6) of yam slices were investigated under different drying temperatures (50-70 °C), slice thicknesses (2-10 mm), and radiation distances (80-160 mm). The optimal drying conditions were determined by applying the BP neural network wolf algorithm (GWO) model based on response surface methodology (RMS). All the above indices were significantly affected by drying conditions (p < 0.05). The drying rate and effective water diffusion coefficient of yam slices accelerated with increasing temperature and decreasing slice thickness and radiation distance. The selection of lower temperature and slice thickness helped reduce the energy consumption and color difference. The polysaccharide content increased and then decreased with drying temperature, slice thickness, and radiation distance, and it was highest at 60 °C, 6 mm, and 120 mm. At 60 °C, lower slice thickness and radiation distance favored the retention of allantoin content. Under the given constraints (minimization of drying time, unit energy consumption, color difference, and maximization of rehydration ratio, polysaccharide content, and allantoin content), BP-GWO was found to have higher coefficients of determination (R2 = 0.9919 to 0.9983) and lower RMSEs (reduced by 61.34% to 80.03%) than RMS. Multi-objective optimization of BP-GWO was carried out to obtain the optimal drying conditions, as follows: temperature 63.57 °C, slice thickness 4.27 mm, radiation distance 91.39 mm, corresponding to the optimal indices, as follows: Y1 = 133.71 min, Y2 = 7.26, Y3 = 8.54 kJ·h·kg-1, Y4 = 20.73 mg/g, Y5 = 2.84 kg/kg, and Y6 = 3.69 μg/g. In the experimental verification of the prediction results, the relative error between the actual and predicted values was less than 5%, proving the model's reliability for other materials in the drying technology process research to provide a reference.