Different multi-scale structural features of oat resistant starch prepared by ultrasound combined enzymatic hydrolysis affect its digestive properties

In this research, oat resistant starch (ORS) was prepared by autoclaving-retrogradation cycle (ORS-A), enzymatic hydrolysis (ORS-B), and ultrasound combined enzymatic hydrolysis (ORS-C). Differences in their structural features, physicochemical properties and digestive properties were studied. Results of particle size distribution, XRD, DSC, FTIR, SEM and in vitro digestion showed that ORS-C was a B + C-crystal, and ORS-C had a larger particle size, the smallest span value, the highest relative crystallinity, the most ordered and stable double helix structure, the roughest surface shape and strongest digestion resistance compared to ORS-A and ORS-B. Correlation analysis revealed that the digestion resistance of ORS-C was strongly positively correlated with RS content, amylose content, relative crystallinity and absorption peak intensity ratio of 1047/1022 cm−1 (R1047/1022), and weakly positively correlated with average particle size. These results provided theoretical support for the application of ORS-C with strong digestion resistance prepared by ultrasound combined enzymatic hydrolysis in the low GI food application

An aboveground biomass partitioning coefficient model for rapeseed (Brassica napus L.)

Biomass partitioning is a pivotal part of the function-structure feedback mechanism. To improve the simulation of aboveground biomass partitioning in grBiomass partitioning is a pivotal part of the function-structure feedback mechanism. To improve the simulation of aboveground biomass partitioning in growth models for rapeseed (Brassica napus\ua0L.), we developed an aboveground biomass partitioning coefficient model for main stem and primary branches, and the stems, leaves, and pods on them, by quantifying the relationships between the biomass partitioning coefficient of major organs aboveground and physiological day of development (DPD). To realize this goal, dry matter data of organs were derived from an outdoor experiment with rapeseed cultivars Ningyou18 and Ningza19 under different fertilizer and transplanting density treatments in the 2012–2015 growing seasons. The model was fitted by calculating the partitioning coefficients of different organs as the ratio of the biomass of organs and their superior organs and normalizing\ua0DPD\ua0into the [0, 1] interval. Various model variables were parameterized to explain the effects of cultivar and environmental conditions on biomass partitioning coefficients for different organs. Our descriptive models were validated with independent experimental data, the correlation (r) of simulation and observation values all had significant level at\ua0P\ua0< 0.001, the absolute values of the average absolute difference (da) are all less than 0.062, except for the main-stem pods, primary branch, primary-branch leaves model, the ratio of\ua0da\ua0to the average observation (dap) are all less than 6.263%, and\ua0r\ua0are all greater than 0.9 except primary-branch leaves and primary-branch stems model. The results showed that most models have good performance and reliability for predicting biomass partitioning coefficient of the main stem, the primary branch, and the organs on them. This sets the stage for linking a growth model with the biomass-based morphological model, for the development of a functional-structural rapeseed model.owth models for rapeseed (Brassica napus L.), we developed an aboveground biomass partitioning coefficient model for main stem and primary branches, and the stems, leaves, and pods on them, by quantifying the relationships between the biomass partitioning coefficient of major organs aboveground and physiological day of development (DPD). To realize this goal, dry matter data of organs were derived from an outdoor experiment with rapeseed cultivars Ningyou18 and Ningza19 under different fertilizer and transplanting density treatments in the 2012–2015 growing seasons. The model was fitted by calculating the partitioning coefficients of different organs as the ratio of the biomass of organs and their superior organs and normalizing DPD into the [0, 1] interval. Various model variables were parameterized to explain the effects of cultivar and environmental conditions on biomass partitioning coefficients for different organs. Our descriptive models were validated with independent experimental data, the correlation (r) of simulation and observation values all had significant level at P < 0.001, the absolute values of the average absolute difference (d) are all less than 0.062, except for the main-stem pods, primary branch, primary-branch leaves model, the ratio of d to the average observation (d) are all less than 6.263%, and r are all greater than 0.9 except primary-branch leaves and primary-branch stems model. The results showed that most models have good performance and reliability for predicting biomass partitioning coefficient of the main stem, the primary branch, and the organs on them. This sets the stage for linking a growth model with the biomass-based morphological model, for the development of a functional-structural rapeseed model