Migration of Chemical Compounds from Packaging Materials into Packaged Foods: Interaction, Mechanism, Assessment, and Regulations.

The migration of chemical compounds from packaging polymers to food presents a multifaceted challenge with implications for food safety and public health. This review explores the interaction between packaging materials and food products, focusing on permeation, migration, and sorption processes. The different migration mechanisms of contact migration, gas phase migration, penetration migration, set-off migration, and condensation/distillation migration have been discussed comprehensively. The major migrating compounds are plasticizers, nanoparticles, antioxidants, light stabilizers, thermal stabilizers, monomers, oligomers, printing inks, and adhesives, posing potential health risks due to their association with endocrine disruption and carcinogenic effects. Advanced analytical methods help in the monitoring of migrated compounds, facilitating compliance with regulatory standards. Regulatory agencies enforce guidelines to limit migration, prompting the development of barrier coatings and safer packaging alternatives. Furthermore, there is a need to decipher the migration mechanism for mitigating it along with advancements in analytical techniques for monitoring the migration of compounds.

Evaluating machine learning performance in predicting sodium adsorption ratio for sustainable soil-water management in the eastern Mediterranean.

Soil salinization is a critical global issue for sustainable agriculture, impacting crop yields and posing a threat to achieving the Sustainable Development Goal (SDG) of ensuring food security. It is necessary to monitor it in detail and uncover its underlying factors at a regional scale. In this context, the present study aimed to evaluate soil health in the eastern Mediterranean region by using the Sodium Adsorption Ratio (SAR) as an indicator of soil salinity in three distinct soil horizons. The main objective of the research was to evaluate the performance of four machine learning (ML) models, including Random Forest (RF), Nu Support Vector Regression (NuSVR), Artificial Neural Network-Multi Layer Perceptron (ANN-MLP), and Gradient Boosting Regression (GBR), for accurate prediction of SAR following the Recursive Feature Elimination (RFE) as a feature selection method. Moreover, SHapely Additive exPlanations (SHAP) was applied as sensitivity analysis to identify the most influential covariates. Main findings of the research revealed that the average clay content in the surface horizon (H10-25cm) was 50.5% ± 10.4, which significantly increased to 57.5% ± 8.7 (p < 0.05). No significant mean differences were detected between the studied horizons for SAR and Na+. ML output revealed that NuSVR outperformed other algorithms in accurately predicting outcomes during both the training and testing stages. Moreover, Scenario 2 (SC2) with seven selected features from the RFE method facilitated highly accurate SAR predictions. Overall, the performance of ML models is ranked as NuSVR > GBR > ANN-MLP > RF. Lastly, SHAP sensitivity analysis identified CEC, Ca+2, Mg+2, and Na+ as the most influential variables for SAR prediction in both the training and testing stages. Hence, the research yielded valuable insights for efficient agricultural soil management at a regional level using state-of-the-art technology.

Exploring the Ecological Implications, Gastronomic Applications, and Nutritional and Therapeutic Potential of Juglans regia L. (Green Walnut): A Comprehensive Review.

The green walnut, which is frequently overlooked in favor of its more mature sibling, is becoming a topic of great significance because of its unique ecological role, culinary flexibility, and therapeutic richness. The investigation of the bioactive substances found in green walnuts and their possible effects on human health has therapeutic potential. Juglans regia L. is an important ecological component that affects soil health, biodiversity, and the overall ecological dynamic in habitats. Comprehending and recording these consequences are essential for environmental management and sustainable land-use strategies. Regarding cuisine, while black walnuts are frequently the main attraction, green walnuts have distinct tastes and textures that are used in a variety of dishes. Culinary innovation and the preservation of cultural food heritage depend on the understanding and exploration of these gastronomic characteristics. Omega-3 fatty acids, antioxidants, vitamins, and minerals are abundant in green walnuts, which have a comprehensive nutritional profile. Walnuts possess a wide range of pharmacological properties, including antioxidant, antibacterial, antiviral, anticancer, anti-inflammatory, and cognitive-function-enhancing properties. Consuming green walnuts as part of one's diet helps with antioxidant defense, cardiovascular health, and general well-being. Juglans regia L., with its distinctive flavor and texture combination, is not only a delicious food but also supports sustainable nutrition practices. This review explores the nutritional and pharmacological properties of green walnuts, which can be further used for studies in various food and pharmaceutical applications.

Recent Insights into the Morphological, Nutritional and Phytochemical Properties of Indian Gooseberry (Phyllanthus emblica) for the Development of Functional Foods.

Aonla, commonly known as Indian gooseberry (Phyllanthus emblica), is a plant native to India with various therapeutic and dietary benefits. This review covers the taxonomical, morphological, and species-level classifications of aonla fruit, including its flower biology, maturation, harvesting, and yield metrics. It also discusses the nutritional, physico-chemical, and phytochemical characteristics and the total antioxidant and antimicrobial activities and mineral compositions of several aonla fruit cultivars. Additionally, the health benefits of aonla are reviewed, including its analgesic, antipyretic, antioxidative, anti-inflammatory, anti-aging, ulcerogenic, chemo-protective, neuroprotective, free radical scavenging, hypoglycaemic, and immunogenic properties, which make it beneficial in the treatment and prevention of various illnesses. Further various forms of fruit extract are also considered to be beneficial for the improvement of plant and animal health. Overall, aonla is a valuable fruit with significant potential for use in improving human health.

Phytochemical and pharmacological characteristics of phalsa (Grewia asiatica L.): A comprehensive review.

Phalsa is a tropical and subtropical fruit that is high in nutritional value and is primarily cultivated for its fruit. As, Phalsa fruit contain high number of vitamins (A and C), minerals (calcium, phosphorus, and iron), and fibre while being low in calories and fat. The fruit and seed of Phalsa contain 18 amino acids, the majority of which are aspartic acid, glutamic acid, and leucine. Based on in vivo and in vitro studies phalsa plant possess high antioxidant, anti-inflammatory, anticancer, antimicrobial, antidiabetic properties. However, antioxidant properties are found in the form of vitamin C, total phenolic, anthocyanin, flavonoid, and tannin. The phalsa plant's fruits and leaves have substantial anticancer action against cancer cell lines. Because of the presence of a broad range of physiologically active chemicals, investigations on phalsa plants revealed that some plant parts have radioprotective qualities. The anti-glycosidase and anti-amylase activity of aqueous fresh fruit extract was shown to be substantial. The phalsa plant contains an abundance of biologically active chemicals, allowing it to control microorganisms through a variety of processes. Phalsa methanolic leaf extract was revealed to have antimalarial and antiemetic effects. The hot and cold polysaccharide fractions extracted from the phalsa plant have potent hepatoprotective and therapeutic properties. Therefore, this review is based on the nutritional, bioactive, phytochemicals, and potential pharmacological uses of phalsa. The potential health benefits and economic potential of the phalsa berry's phytochemicals are promising areas for further study.

A Comprehensive Review on Bioactive Compounds Found in Caesalpinia sappan.

Sappan wood (Caesalpinia sappan) is a tropical hardwood tree found in Southeast Asia. Sappan wood contains a water-soluble compound, which imparts a red color named brazilin. Sappan wood is utilized to produce dye for fabric and coloring agents for food and beverages, such as wine and meat. As a valuable medicinal plant, the tree is also known for its antioxidant, anti-inflammatory, and anticancer properties. It has been observed that sappan wood contains various bioactive compounds, including brazilin, brazilein, sappan chalcone, and protosappanin A. It has also been discovered that these substances have various health advantages; they lower inflammation, enhance blood circulation, and are anti-oxidative in nature. Sappan wood has been used as a medicine to address a range of illnesses, such as gastrointestinal problems, respiratory infections, and skin conditions. Studies have also suggested that sappan wood may have anticarcinogenic potential as it possesses cytotoxic activity against cancer cells. Based on this, the present review emphasized the different medicinal properties, the role of phytochemicals, their health benefits, and several food and nonfood applications of sappan wood. Overall, sappan wood has demonstrated promising medicinal properties and is an important resource in traditional medicine. The present review has explored the potential role of sappan wood as an essential source of bioactive compounds for drug development.

Phytochemical Properties, Extraction, and Pharmacological Benefits of Naringin: A Review.

This review describes the various innovative approaches implemented for naringin extraction as well as the recent developments in the field. Naringin was assessed in terms of its structure, chemical composition, and potential food sources. How naringin works pharmacologically was discussed, including its potential as an anti-diabetic, anti-inflammatory, and hepatoprotective substance. Citrus flavonoids are crucial herbal additives that have a huge spectrum of organic activities. Naringin is a nutritional flavanone glycoside that has been shown to be effective in the treatment of a few chronic disorders associated with ageing. Citrus fruits contain a common flavone glycoside that has specific pharmacological and biological properties. Naringin, a flavone glycoside with a range of intriguing characteristics, is abundant in citrus fruits. Naringin has been shown to have a variety of biological, medicinal, and pharmacological effects. Naringin is hydrolyzed into rhamnose and prunin by the naringinase, which also possesses l-rhamnosidase activity. D-glucosidase subsequently catalyzes the hydrolysis of prunin into glucose and naringenin. Naringin is known for having anti-inflammatory, antioxidant, and tumor-fighting effects. Numerous test animals and cell lines have been used to correlate naringin exposure to asthma, hyperlipidemia, diabetes, cancer, hyperthyroidism, and osteoporosis. This study focused on the many documented actions of naringin in in-vitro and in-vivo experimental and preclinical investigations, as well as its prospective therapeutic advantages, utilizing the information that is presently accessible in the literature. In addition to its pharmacokinetic characteristics, naringin's structure, distribution, different extraction methods, and potential use in the cosmetic, food, pharmaceutical, and animal feed sectors were discussed.

Extraction and Encapsulation of Phytocompounds of Poniol Fruit via Co-Crystallization: Physicochemical Properties and Characterization.

Poniol (Flacourtia jangomas) has beneficial health effects due to its high polyphenolic and good antioxidant activity content. This study aimed to encapsulate the Poniol fruit ethanolic extract to the sucrose matrix using the co-crystallization process and analyze the physicochemical properties of the co-crystalized product. The physicochemical property characterization of the sucrose co-crystallized with the Poniol extract (CC-PE) and the recrystallized sucrose (RC) samples was carried out through analyzing the total phenolic content (TPC), antioxidant activity, loading capacity, entrapment yield, bulk and traped densities, hygroscopicity, solubilization time, flowability, DSC, XRD, FTIR, and SEM. The result revealed that the CC-PE product had a good entrapment yield (76.38%) and could retain the TPC (29.25 mg GAE/100 g) and antioxidant properties (65.10%) even after the co-crystallization process. Compared to the RC sample, the results also showed that the CC-PE had relatively higher flowability and bulk density, lower hygroscopicity, and solubilization time, which are desirable properties for a powder product. The SEM analysis showed that the CC-PE sample has cavities or pores in the sucrose cubic crystals, which proposed that the entrapment was better. The XRD, DSC, and FTIR analyses also showed no changes in the sucrose crystal structure, thermal properties, and functional group bonding structure, respectively. From the results, we can conclude that co-crystallization increased sucrose's functional properties, and the co-crystallized product can be used as a carrier for phytochemical compounds. The CC-PE product with improved properties can also be utilized to develop nutraceuticals, functional foods, and pharmaceuticals.

Meteorological Drought Variability and Its Impact on Wheat Yields across South Africa.

Drought is one of the natural hazards that have negatively affected the agricultural sector worldwide. The aims of this study were to track drought characteristics (duration (DD), severity (DS), and frequency (DF)) in South Africa between 2002 and 2021 and to evaluate its impact on wheat production. Climate data were collected from the South African Weather Service (SAWS) along with wheat yield data from the Department of Agriculture, Forestry and Fisheries (2002-2021). The standard precipitation index (SPI) was calculated on 3-, 6-, 9-, and 12-month time scales, and the trend was then tracked using the Mann-Kendall (MK) test. To signify the climatic effects on crop yield, the standardized yield residual series (SYRS) was computed along with the crop-drought resilience factor (CR) on a provincial scale (2002-2021). The output of the SPI analysis for 32 stations covering all of South Africa indicates a drought tendency across the country. On a regional scale, western coastal provinces (WES-C and NR-C) have been more vulnerable to meteorological droughts over the past 20 years. Positive correlation results between SYRS and wheat yield indicate that the WES-C province was highly influenced by drought during all stages of wheat growth (Apr-Nov). Historical drought spells in 2003, 2009, and 2010 with low CR = 0.64 caused the province to be highly impacted by the negative impacts of droughts on yield loss. Overall, drought events have historically impacted the western part of the country and dominated in the coastal area. Thus, mitigation plans should be commenced, and priority should be given to this region. These findings can assist policymakers in budgeting for irrigation demand in rainfed agricultural regions.

Spatial-temporal dynamic impact of changes in rainfall erosivity and vegetation coverage on soil erosion in the Eastern Mediterranean.

In Syria, soil erosion (SoEr) by water is one of the major challenges for sustainability. Thus, the main goals of this research were to evaluate the spatial changes of SoEr between 2000 and 2018 in the whole coastal basin (CB) of Syria and to provide a soil water erosion risk map for the study area. For this purpose, monthly rainfall data, the SoilGrids dataset, satellite image derived NDVI layers, and Digital Elevation Model (DEM) were collected. Through the integration of these layers into the Revised Universal Soil Loss Equation (RUSLE), under a Geographic Information System (GIS), soil loss was assessed. Also, the contribution of land cover changes and R factor on SoEr were evaluated. The outcomes of this assessment illustrated that the R factor ranged from 800 to 2600 MJ mm ha-1 h-1 yr-1, while the soil erodibility factor (K factor) ranged from 0.048 to 0.035 ton ha MJ-1 mm-1. The C factor (vegetation coverage) values ranged between 0.07 and 1 with a spatial average value of 0.44 for the 2000-2009 period and 0.39 for the 2010-2018 interval. The output of RUSLE revealed that average annual SoEr was of 21.35 ton ha-1 y-1 (± 38) for 2000-2009 and 22.47 ton ha-1 y-1(± 41.8) for 2010-2018. Interestingly, the increased SoEr caused by the R factor was dominant (34.65%), followed by changes in both C factor and R factor (13.34%). However, decrease of SoEr rates is due to the increase of the C factor accounting for 36.82% of the CB. The outcome of this research can provide constructive spatial insights for rehabilitation plans for the post-war phase of Syria.

Predicting Modified Fournier Index by Using Artificial Neural Network in Central Europe.

The Modified Fournier Index (MFI) is one of the indices that can assess the erosivity of rainfall. However, the implementation of the artificial neural network (ANN) for the prediction of the MFI is still rare. In this research, climate data (monthly and yearly precipitation (pi, Ptotal) (mm), daily maximum precipitation (Pd-max) (mm), monthly mean temperature (Tavg) (°C), daily maximum mean temperature (Td-max) (°C), and daily minimum mean temperature (Td-min) (°C)) were collected from three stations in Hungary (Budapest, Debrecen, and Pécs) between 1901 and 2020. The MFI was calculated, and then, the performance of two ANNs (multilayer perceptron (MLP) and radial basis function (RBF)) in predicting the MFI was evaluated under four scenarios. The average MFI values were between 66.30 ± 15.40 (low erosivity) in Debrecen and 75.39 ± 15.39 (low erosivity) in Pecs. The prediction of the MFI by using MLP was good (NSEBudapest(SC3) = 0.71, NSEPécs(SC2) = 0.69). Additionally, the performance of RBF was accurate (NSEDebrecen(SC4) = 0.68, NSEPécs(SC3) = 0.73). However, the correlation coefficient between the observed MFI and the predicted one ranged between 0.83 (Budapest (SC2-MLP)) and 0.86 (Pécs (SC3-RBF)). Interestingly, the statistical analyses promoted SC2 (Pd-max + pi + Ptotal) and SC4 (Ptotal + Tavg + Td-max + Td-min) as the best scenarios for predicting MFI by using the ANN-MLP and ANN-RBF, respectively. However, the sensitivity analysis highlighted that Ptotal, pi, and Td-min had the highest relative importance in the prediction process. The output of this research promoted the ANN (MLP and RBF) as an effective tool for predicting rainfall erosivity in Central Europe.

Assessing the impacts of agricultural drought (SPI/SPEI) on maize and wheat yields across Hungary.

This study examined the physical properties of agricultural drought (i.e., intensity, duration, and severity) in Hungary from 1961 to 2010 based on the Standardized Precipitation Index (SPI) and the Standardized Precipitation Evapotranspiration Index (SPEI). The study analyzed the interaction between drought and crop yield for maize and wheat using standardized yield residual series (SYRS), and the crop-drought resilient factor (CDRF). The results of both SPI and SPEI (-3, -6) showed that the western part of Hungary has significantly more prone to agricultural drought than the eastern part of the country. Drought frequency analysis reveals that the eastern, northern, and central parts of Hungary were the most affected regions. Drought analysis also showed that drought was particularly severe in Hungary during 1970-1973, 1990-1995, 2000-2003, and 2007. The yield of maize was more adversely affected than wheat especially in the western and southern regions of Hungary (1961-2010). In general, maize and wheat yields were severely non-resilient (CDRF < 0.8) in the central and western part of the country. The results suggest that drought events are a threat to the attainment of the second Sustainable Development Goals (SDG-2). Therefore, to ensure food security in Hungary and in other parts of the world, drought resistant crop varieties need to be developed to mitigate the adverse effects of climate change on agricultural production.

Assessing the WEPP model performance for predicting daily runoff in three terrestrial ecosystems in western Syria.

Soil erosion is one of the main threats facing the agriculture and natural resources sector all over the world, and the same is true for Syria. Several empirical and physically based tools have been proposed to assess erosion induced soil losses and runoff driving the processes, from plot to regional spatial scales. The main goal of this research is to evaluate the performance of the Water Erosion Prediction Project (WEPP) model in predicting runoff in comparison with field experiments in the Al-Sabahia region of Western Syria in three ecosystems: agricultural lands (AG), burned forest (BF) and forest (FO). To achieve this, field experimental plots (2∗1.65∗0.5 m) were prepared to obtain runoff observation data between September 2012 and December 2013. In addition, the input data (atmospheric forcing, soil, slope, land management) were prepared to run the WEPP model to estimate the runoff. The results indicate that the average observed runoffs in the AG, BF and FO were 12.54 ± 1.17, 4.81 ± 0.97 and 1.72 ± 0.16 mm/event, respectively, while the simulated runoffs in the AG, BF and FO were 15.15 ± 0.89, 9.23 ± 1.48 and 2.61 ± 0.47mm/event, respectively. The statistical evaluation of the model's performance showed an unsatisfactory performance of the WEPP model for predicting the run-offs in the study area. This may be caused by the structural flaws in the model, and/or the insufficient site-specific input parameters. So, to achieve good performance and reliable results of the WEPP model, more observation data is required from different ecosystems in Syria. These findings can provide guidance to planners and environmental engineers for proposing environmental protection and water resources management plans in the Coastal Region in Syria.

Evaluation of Organic Wastes as Substrates for Rearing Zophobas morio, Tenebrio molitor, and Acheta domesticus Larvae as Alternative Feed Supplements.

Studies have focused on identifying combinations of insects and organic waste to optimise bio-conversion. Here, the effects of different diets (10% chicken feed complemented with 90% vegetable waste, garden waste, cattle manure, or horse manure) on growth and survival rates, and nutritional value of Zophobas morio and Tenebrio molitor larvae, and Acheta domesticus were investigated. Compared with chicken feed, organic waste decreased the individual larval weight, although green waste showed fewer negative effects than the manure. The macronutrient concentrations in garden waste were moderate compared with chicken feed, and vegetable waste was the poorest diet in terms of nutrient concentration, as revealed by the principal component analysis (PCA). There was no difference in weight between larvae reared on garden waste and those reared on vegetable waste. Tenebrio molitor and A. domesticus showed the maximum growth rates at 71-101 and 36-66 days of age at 22.5 ± 2.5 °C, respectively. The PCA showed that the protein and fibre concentrations were inversely proportional to fat concentration in the larvae. Acheta domesticus was rich in proteins, whereas Z. morio and T. molitor were rich in fat. Feeding nutrient-poor diets resulted in a lower protein and a higher fat concentration in the larvae.

Soils of the Southern Syria - A big database for the future land management planning.

As non-renewable natural resources, restoring Syrian soil quality is a vital issue for sustainable future planning after conflict ends. The data provided in this research exhibit features and physiochemical properties for soils from the southern part of Syria until the Jordanian border, which can provide decision-makers with sufficient information for rehabilitation stage after conflict in a regional scale. The data were collected from 107 representative soil profiles covering diverse agroecosystems throughout the area (i.e. Dara and Alswieda governorates). The most important data findings of this research included the first detection of Palygorskite {(Mg,Al)2Si4O10(OH)•4(H2O)} in Syrian soils, which is considered a strong evidence for the direct effects of the climate change on agroecosystem. Vertisols, Inceptisols, Entisols, Mollisols, and Aridisols were the most widespread soil types in the area. Overall, the database involves the field morphological characteristics, physicochemical, and mineralogical analyses.