Previously, we showed that water extract (soymilk, except pH was increased to 8 from 6.5) of whole soybean could be used directly as a raw material for producing edible soy films by deposition of the film-forming solution (soy extract with enhancers). However, the strength of such soy films needed improvement because they were weak. The purpose of this study was to investigate how transglutaminase (TG) cross-linking reactions and film enhancers, including pectin (low- and high-methoxyl pectin), whey protein isolate (WPI), and soy protein isolate (SPI), improve the physical properties of soy films. Soy films prepared with TG had tensile strength (TS) of 3.01 MPa and puncture strength (PS) of 0.78 MPa, which were higher by as much as 51% and 30% than that of soy films without TG treatment, respectively. Pectin showed significant effects on the mechanical properties of TG-added soy films in terms of TS, PS, and % elongation. On the other hand, only TS and PS were increased by the addition of WPI or SPI. Heat curing had a significant effect on soy film\'s physical properties. TG treatment significantly reduced film solubility when soaked in water and various levels of acid (vinegar) and base (baking soda) solutions. Under the experimental conditions of 35 unit TG and 28 min of reaction, the degrees of cross-linking were evidenced by the disappearance of individual protein subunits, except the basic subunit of glycinin, and the reduction of 21% of lysine residues of the proteins. HIGHLIGHTS: Edible soy films were made with transglutaminase and about 21% lysine cross-linked. The mechanical strength of soy films was increased by incorporating film enhancers. Transglutaminase enhanced the mechanical properties of soy films.

The infrared spectroscopy (IR) signal of protein is prone to being covered by impurity signals, and the accuracy of the secondary structure content calculated using spectral data is poor. To tackle this challenge, a rapid high-precision quantitative model for protein secondary structure was proposed. Firstly, a two-dimensional correlation calculation was performed based on 60 groups of soybean protein isolates (SPI) infrared spectroscopy data, resulting in a two-dimensional correlation infrared spectroscopy (2DCOS-IR). Subsequently, the optimal characteristic bands of the four secondary structures were extracted from the 2DCOS-IR. Ultimately, partial least squares (PLS), long short-term memory (LSTM), and bidirectional long short-term memory (BILSTM) algorithms were used to model the extracted characteristic bands and predict the content of SPI secondary structure. The findings suggested that BILSTM combined with 2DCOS-IR model (2DCOS-BILSTM) exhibited superior predictive performance. The prediction sets for α-helix, β-sheet, β-turn, and random coil were designated as 0.9257, 0.9077, 0.9476, and 0.8443, respectively, and their corresponding RMSEP values were 0.26, 0.48, 0.20, and 0.15. This strategy enhances the precision of IR and facilitates the rapid identification of secondary structure components within SPI, which is vital for the advancement of protein industrial production.

The present study was aimed to investigate the interactions between soybean protein isolate (SPI) with resveratrol (RESV) and lutein (LUT). The binding forces, molecular interactions and functional properties were explored by multi-spectroscopic analysis, molecular docking and functional property indexes between SPI and RESV/LUT. The RESV/LUT quenched SPI chromophore residues with static mechanism and the endothermic reaction. The SPI- RESV/LUT complexes were formed through hydrogen bond, electrostatic and hydrophobic interactions. Molecular docking confirmed van-der-Waals force as one of the important forces. The interaction of RESV/LUT led to SPI\'s secondary structure alterations with a decrease in α-helix and random coil and an increase in β-sheet and β-turns. RESV/LUT developed foaming and emulsifying properties of SPI and showed a significant decrease of the surface hydrophobicity with RESV/LUT concentrations increase attributed to SPI\'s partial unfolding. Our study exposed molecular mechanisms and confirmations to understand the interactions in protein- RESV/LUT complexes for protein industrial base promotion.

Gelation, as an important functional property of soy protein isolate (SPI), can be improved by some green technologies in food manufacturing, including ultrasound, ultrahigh pressure and microwave treatments. This work investigated the effect of an alkaline solubilisation step in SPI extraction combined with sonication on protein properties. The TGase-induced gel of the modified SPI was prepared to explore the effect of ultrasound on gel properties, including structures, strength, water-holding capacity and rheological properties. Additionally, the differences between traditional ultrasound modification of SPI and current modification methods were analyzed. The results showed that the ultrasonication-assisted extraction method could result in a significant increase in extraction rate from 24.68% to 42.25%. Moreover, ultrasound-assisted modification of SPI gels induced with transglutaminase (TGase) exhibited significant improvement in mechanical properties, such as texture, water-holding capacity and rheological properties, In particular, SPI extracted at 400 W ultrasound intensity for 180 s showed the best overall performance in terms of gel properties. Our method efficiently uniformizes gel structure, enhancing mechanical properties compared to conventional ultrasound methods, which reduced energy consumption and costs. These findings provide insights into the production of high-gelation SPI in food manufacturing.

This study delves into analyzing drought patterns in Baluchistan by applying copula-based bivariate probabilistic models complemented by Severity Duration Frequency (SDF) curves. The calculation of the Standardized Precipitation Index (SPI) hinges on monthly aggregate precipitation data from ten distinct sites compiled over six-month periods. After evaluating various parametric distributions, the Log-Normal distribution emerges as suitable for modeling drought severity and duration. A range of bivariate copulas is employed to simulate the characteristics of drought severity and duration, which are then compared against observed data. Remarkably, the Gumbel copula classified as an extreme value copula-outperforms its counterparts according to diverse statistical benchmarks. By utilizing the dependence function, we derive the conditional distribution of drought variables: severity and duration. These conditional distributions subsequently inform the calculation of return periods, forming the basis for constructing SDF diagrams at fixed recurrence levels across the study region. The study\'s finding indicates that a severe drought could occur over the region with higher return periods for a specific duration. The implications of this research are significant, showcasing the potential of copula-based joint modeling techniques to generate frequency curves for drought severity and duration. This development holds promise for effective water resource management and the formulation of strategies to mitigate the impact of drought in vulnerable regions.

BACKGROUND: Plant protein is widely used in the study of animal protein substitutes and healthy sustainable products. The gel properties are crucial for the production of plant protein foods. Therefore, the present study investigated the use of soybean oil to modulate the gel properties of soybean protein isolation-wheat gluten composite with or without CaCl2 .
RESULTS: Oil droplets filled protein network pores under the addition of soybean oil (1-2%). This resulted in an enhanced gel hardness and water holding capacity. Further addition of soybean oil (3-4%), oil droplets and some protein-oil compounds increased the distance between the protein molecule chain. The results of Fourier transform infrared spectroscopy and intermolecular interaction also showed that the disulfide bond and β-sheet ratio decreased in the gel system, which damaged the overall structure of the gel network. Compared with the addition of 0 m CaCl2 , salt ion reduced the electrostatic repulsion between proteins, and local protein cross-linking was more intense at 0.005 m CaCl2 concentration. In the present study, structural properties and rheological analysis showed that the overall strength of the gel was weakened after the addition of CaCl2 .
CONCLUSIONS: The presence of appropriate amount of soybean oil can fill the gel pores and improve the texture properties and network structure of soy protein isolate-wheat gluten (SPI-WG) composite gel. Excessive soybean oil may hinder protein-protein interaction and adversely affect protein gel. In addition, the presence or absence of CaCl2 significantly affected the gelling properties of SPI-WG composite protein gels. © 2023 Society of Chemical Industry.

As a destructive and economic disaster in the world, drought shows an increasing trend under the continuous global climate change and adverse health effects have been reported. The interactive effects between drought and air pollutants, which may also be harmful to respiratory systems, remain to be discussed. We built the generalized additive model (GAM) and distributed lag nonlinear model (DLNM) to estimate the effects of drought and air pollutants on daily upper respiratory infections (URTI) outpatient visits among children under 6 in three cities of Gansu province. The Standardized Precipitation Index (SPI) based on monthly precipitation (SPI-1) was used as an indicator of drought. A non-stratified model was established to explore the interaction effect of SPI-1 and air pollutants. We illustrated the number of daily pediatric URTI outpatient visits increased with the decrease in SPI-1. The interactive effects between air pollutants and the number of daily pediatric URTIs were significant. According to the non-stratified model, we revealed highly polluted and drought environments had the most significant impact on URTI in children. The occurrence of drought and air pollutants increased URTI in children and exhibited a significant interactive effect.

Astringency is one of the most important organoleptic characteristics of red wines, and its intensity evaluation method has been the focus of research in recent years. An artificial saliva system was developed to establish an accurate and reliable evaluation method for the astringency intensity of dry red wines based on saliva precipitation index (SPI). To achieve this, five key protein families, which presented high reactivities and sensitivities in protein-tannin binding reactions, were selected from human whole saliva. The concentrations of the five proteins (proline-rich protein, α-amylase, lactoferrin, lysozyme, and albumin) and pH were optimized using response surface methodology based on the human salivary conditions to simulate the real salivary environment. The artificial saliva precipitation index method was applied to 60 commercial dry red wines and it exhibited a high correlation (CoefASPI = 0.94) with the sensory scores, indicating better performance than the traditional SPI method and other analytical approaches.

The present study aims to assess the recent changes and trends in the extreme climate indices in the Kashmir basin using the observational records from 1980 to 2016. The extreme climate indices were computed using the ClimPACT2 software and a total of 39 indices were selected for the analysis having particular utility to various sectors like agriculture, water resources, energy consumption, and human health. Besides adopting the station scale analysis, regional averages were computed for each index. In terms of the mean climatology, an increase has been observed in the annual mean temperature with a magnitude of 0.024 °C/year. Further, differential warming patterns have been observed in the mean maximum and minimum temperatures with mean maximum temperature revealing higher increases than mean minimum temperature. On the other hand, the annual precipitation shows a decrease over most of the region, and the decreases are more pronouncing in the higher altitudes. The trend analysis of the extreme indices reveals that in consonance with the rising temperature there has been an increase in the warm temperatures and decrease in the cold temperatures across the Kashmir basin. Furthermore, our analysis suggests a decrease in the extreme precipitation events. The drought indices viz., Standardised Precipitation Index (SPI), and Standardised Precipitation Evapotranspiration Index (SPEI) manifest decreasing trends with the tendency towards drier regimes implying the need for better water resource management in the region under changing climate.

The aim of this study is to establish food 4D printing products with the property of automatic flavor change by the post-printing application of microwave as an external thermal stimulus. The combination of a formulation comprised of soybean protein isolate (SPI), k-carrageenan (CAR) and vanilla flavor (VNL) was used as printing material. The change in flavor profile was observed by the level of external heat stimulus as a 4D effect. The results of e-nose revealed a significant difference (P < 0.05) in sensors 2, 5, 6, 9, 10, 12 and 13 in the sample added with vanilla flavor meanwhile GC-MS detected 25 volatiles compounds. Notably, four new generated flavor compounds (1-Octen-3-ol, Maltol, Ethyl maltol and eugenal) were identified when added with vanilla flavor. Moreover, e-tongue results indicated the taste characteristics of the sample with vanilla flavor presenting more intense bitterness, astringency, umami, richness and saltiness. The rheological property and water distribution (LF-NMR) determined at different concentrations levels of carrageenan showed that SPI gel made with 3% (w/v) carrageenan was the most suitable for 3D printing among all three concentrations considered in this study. Overall, the results can conclude that the addition of carrageenan and post-printing microwave heating at an optimum level of microwave power enhanced the printability and flavor of SPI gel.