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.

Evaluating drought parameters at the basin level is one of the fundamental processes for planning sustainable crop production. This study aimed to evaluate both short-term and long-term meteorological drought parameters within the Vaippar Basin, located in southern India, by employing the standardized precipitation index (SPI). Gridded rainfall values developed from 13 rain gauge stations were employed to calculate the SPI values. Drought parameters, encompassing occurrence, intensity, duration, frequency, and trends, were assessed for both short-term and long-term droughts. The study findings indicated that the occurrence of short-term drought was 51.7%, while that of long-term drought was 49.82%. Notably, the basin experienced extreme short-term droughts in 1980, 1998 and 2016 and long-term droughts in 1981, 2013, and 2017. Utilizing an innovative trend identification method for SPI values, a significant monotonic upwards trend was identified in October and December for short-term drought and in December for long-term drought. This study defined the minimum threshold rainfall, which represents the critical amount required to prevent short-term drought (set at 390 mm) and long-term drought (set at 635 mm). The drought severity recurrence curves developed in this study indicate that when the SPI values fall below - 1.0, short-term drought affects 25% of the basin area, while long-term drought impacts 50% of the basin area at a 20-year recurrence interval. Additionally, the drought hazard index (DHI), which combines drought intensity and severity, demonstrated higher values in the northwestern regions for short-term drought and in the southern areas for long-term drought. The study\'s findings, highlighting areas of drought vulnerability, severity, and recurrence patterns in the basin, direct the attention for timely intervention when drought initiates.

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.

Uncertainty and uneven distribution of monsoonal rainfall and its consequences on crop production is a matter of serious concern in India, specifically, in the Indo-Gangetic plain region. In this study, drought patterns were investigated through standardised precipitation index (SPI) of varying timescales, using the India Meteorological Department (IMD) precipitation data (1901-2021). We analysed the spatio-temporal pattern of different drought characteristics (frequency, duration, severity, intensity) of the Indian Gangetic basin using run theory. The bivariate copula method has been incorporated to combine two drought properties (severity and duration). Copula integrates multivariate distribution and considers the dependency rate among the variables. The five most widely used copulas from various copula families, elliptical (normal, t-copula) and Archimedean (Clayton, Gumbel, Frank), were estimated for modelling, and the best fit copula was selected. The study revealed that seasonal drought is more frequent and intense in the Upper and Middle Gangetic Plain, whereas annual drought is quite scattered in nature. It is worthy to mention that downward drought trends were observed in this agricultural belts significantly after 1965; specifically, in the Upper, Middle, and Trans Gangetic Plain regions. With increasing drought duration and severity, the drought return period raised, but the frequency decreased gradually. Most of the droughts characterised by less duration and severity occurred with a return period below 10 years for the whole region. The major 100 + years return period droughts were to be found after 1960 and their frequencies were significantly higher after 2000. The most recent remarkable droughts with more than 100 years of return occurred during 2008-2011 and 2016-2018 in the Upper and Middle Gangetic plains, whereas in the Lower Gangetic plain, a hundred-year return period drought was occurred during 2010-2013. This study provides agroclimatic-zones-wise significant information of drought characteristics and its nature of occurrence in the Indian Ganga Basin. The results enhance the understanding of drought management and formulation of adaptive strategies to mitigate the adverse impact of droughts.

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.

In most arid and semi-arid environments, groundwater is one of the precious resources threatened by water table decline and desiccation, thus it must be constantly monitored. Identifying the causes influencing the variations of the subsurface water level, such as meteorological drought, is one approach for monitoring these fluctuations. In the present study, the effect of two meteorological drought indices SPI and SPEI on the fluctuations of the underground water level was evaluated, as was their relationship with the drought index of the subsurface water level (SWI) using multivariate linear regression and M5 decision tree regression. After calculating climatic and hydrological drought indices in a 6-month time window for a long-term statistical period (1989-2018), the semi-deep aquifers of Golestan province, which is located in northern Iran, were considered as a research location for this purpose. The results demonstrated that the effect of meteorological drought does not immediately manifest in the changes of the subsurface water table and the hydrological drought index. By adding the meteorological drought index with a 6-month lag step, the average air temperature, and the total rainfall from the previous 6 months as new variables, the correlation with the SWI index increases, so that in the best-case scenario, the M5 decision tree model provides the best result in predicting the SWI index. The second half of the year yielded a coefficient of determination of 0.92 and an error value of RMSE = 0.27 for the SPEI index. Among the meteorological drought indices, the SPEI index, which is based on precipitation and evapotranspiration, created a stronger link with the SWI index, which highlights the significance of potential evapotranspiration. It is a warning that, as a result of global warming, subsurface water tables in this region may fall in the future.

Droughts frequently occurring in India have significant societal, economic, and environmental effects. The lack of direct measurements of groundwater in location and time hinders quantitative methods to analyse the intricate nature of groundwater drought. This work used the datasets derived from the Gravity and Climate Experiment (GRACE and GRACE-FO) and Global Land Data Assimilation System (GLDAS) to extensively analyse Groundwater Storage changes in the Lower Gangetic Basin (LGB) using unique hydrological parameters between the years 2003 and 2022. The analysis highlights that the GRACE-derived terrestrial water storage anomaly in the LGB decreased significantly (-12.12 mm/yr), and the amount of Groundwater Storage Anomaly (GWSA) decreased similarly (-10.80 mm/yr), while in the GRACE-FO period, a positive trend has been noticed in TWSA (33.96 mm/yr) and GWSA (64.8 mm/yr) respectively. A drought indicator called the GRACE-derived groundwater drought index (GGDI) has been computed for the entire LGB region. A traditional drought study viz. Standardised Precipitation Index (SPI) was performed over LGB to justify the results of the GGDI. The results from GGDI study effectively matched the periods of significant drought occurrences with the 12-month SPI time series. From the GGDI, this study examined groundwater drought\'s spatial distribution, temporal evolution, and trend (Modified Mann Kendall trend) aspects. According to research findings, the LGB experienced three major drought periods between 2009-2010, 2019 (moderate), and 2015-2016 (severe). The study offers reliable quantitative data on the evolution of GRACE-derived groundwater drought, which may add a new perspective to additional drought research in the densely populated study area, which depends majorly on agriculture, livestock and less skilled water-intensive industries such as leather and textile industries in a sub-tropical climate. This paradigm incorporates changes in groundwater resources caused by human activities and climate change, paving the way for measuring progress towards sustainable use and water security.

Based on the physical and geographical conditions, the Baltic Region is categorised as a humid climate zone. This means that, there is usually more precipitation than evaporation throughout the year, suggesting that droughts should not occur frequently in this region. Despite the humid climate in the region, the study focused on assessing the spatio-temporal patterns of droughts. The drought events were analysed across the Baltic Region, including Sweden, Finland, Lithuania, Latvia, and Estonia. This analysis included two drought indices, the Standardized Precipitation Index (SPI) and the Streamflow Drought Index (SDI), for different accumulation periods. Daily data series of precipitation and river discharge were used. The spatial and temporal analyses of selected drought indices were carried out for the Baltic Region. In addition, the decadal distribution of drought classes was analysed to disclose the temporal changes and spatial extent of drought patterns. The Pearson correlation between SPI and SDI was applied to investigate the relationship between meteorological and hydrological droughts. The analysis showed that stations with more short-duration SPI or SDI cases had fewer long-duration cases and vice versa. The number of SDI cases (SDI ≤ -1) increased in the Western Baltic States and some WGSs in Sweden and Finland from 1991 to 2020 compared to 1961-1990. The SPI showed no such tendencies except in Central Estonia and Southern Finland. The 6-month accumulation period played a crucial role in both the meteorological and hydrological drought analyses, as it revealed prolonged and widespread drought events. Furthermore, the 9- and 12-month accumulation periods showed similar trends in terms of drought duration and spatial extent. The highest number of correlation links between different months was found between SPI12-SDI9 and SPI12-SDI12. The results obtained have deepened our understanding of drought patterns and their potential impacts in the Baltic Region.