Variability In Composition Research Articles

Combining video and GPS-tracking to study the spatial foraging distribution of a single-prey loading seabird

Seabirds are valuable indicators of marine ecosystem processes and studying seabird diets can shed light on natural or human-induced variability in food-web composition. Specifically single-prey loading seabird species such as terns have the potential to act as visual sentinels of prey availability offshore. However, obtaining diet information from remote bird colonies is often challenging and time consuming. In this pilot study we present a novel approach to combine two established methods to study seabird foraging ecology, providing a powerful and cost-effective tool to study the distribution of prey items available to seabirds. We combined GPS tracking data of Sandwich Terns (Thalasseus sandvicensis) with prey-observations from a hide in 2012 and 2013, and from semi-continuously recorded camera footage in 2017. By doing so, we identified 115 approximate catch locations of prey (86 herring/sprat Clupeidae, 29 sandeel Ammodytidae). Combining GPS-data and prey observations yielded detailed knowledge on the movements and chick diets of tracked birds as well as the spatial origin and lengths of captured prey items. Further catch distances of both Clupeidae and Ammodytidae resulted in deliveries of larger prey items and thus higher energy yield per trip, but also a higher energy expenditure per trip. We discuss the limitations and potential of our methodological approach to study foraging energetics during chick-provisioning of seabirds that carry prey items visible in their beaks.

Comparison of two isotopic hydrograph separation methods in the Hydrological Open Air Laboratory, Austria

AbstractExploring the contributions of new and old water to runoff during precipitation events in agricultural catchments is essential for understanding runoff generation, solute transport, and soil erosion. The aim of this study was to investigate the variability in the isotopic composition of precipitation and runoff in the 66 ha agricultural catchment in Austria, in the Hydrological Open Air Laboratory (HOAL), in order to compare two isotope hydrograph separation methods. The classical two‐component (IHS) and the ensemble hydrograph separation (EHS) were applied to multiple large events in May–October of 2013–2018 using δ18O and δ2H. The peak flow new water contributions obtained by IHS were compared with the average new water fraction from EHS. The average new water fraction calculated with EHS based on regular weekly sampling was close to zero, which can be explained by the large diffuse groundwater discharge into the stream between the events. When only investigating events with high temporal resolution sampling, the results suggest that EHS provided average new water fractions during peak flows (0.46 ± 0.04 for δ18O, 0.47 ± 0.03 for δ2H) that were close to the averages obtained by IHS (0.47 for δ18O, 0.50 for δ2H). New water fractions tended to be higher for larger rainfall intensities. High peak flow new water fractions could be explained by the agricultural land use and soils with low permeability promoting overland flow generation and by some of the tile drainage systems contributing to the delivery of water. In conclusion, a weekly sampling frequency was not sufficient in the HOAL but instead high‐resolution sampling during events was necessary to estimate the average new water contributions during events. While EHS may be a more robust approach compared to IHS, as it relaxes some of the assumptions of IHS, IHS can provide information on the variability of new water contributions of individual events.

Variability in Gut Microbiota Composition and Dietary Intake Before and After a Health Screening Colonoscopy

Variability in Gut Microbiota Composition and Dietary Intake Before and After a Health Screening Colonoscopy

Omnivore and vegetarians show similar body composition and skin physiology across body regions-A comparative analysis.

Skin physiology seems to be influenced by dietary choices and body composition, although links between these factors remain poorly characterised. In the present manuscript, we elaborate on the potential relationships among food groups, body composition and skin physiology in omnivores and vegetarians. This cross-sectional observational study involved 181 participants, 129 omnivores and 52 vegetarians. The main functions of the skin measured in our laboratory were transepidermal water loss, deep and superficial epidermal hydration, skin elasticity, and carotenoid content. Skin variables obtained from different body regions were made comparable by a new Proportional Skin Index calculated to respect their relative representativity. No statistical differences were found when comparing both groups' body composition and skin variables from different body regions, with the exception of the skin carotenoid content significantly higher in the vegetarian group (p<0.001). Although dietary patterns significantly differed between groups, with vegetarians consuming fewer animal-derived products and more plant-based foods, multiple linear regression analysis revealed no differences or association between the dietary pattern and the skin physiology. These findings highlight the need for further research to elucidate the specific impact of diet and food groups and body composition on skin physiology.

Synthesis and characteristics of densified GDC-LSO composite as a new apatite-based electrolyte for intermediate-temperature solid oxide fuel cells (IT-SOFC)

Developing solid-state ionic conductors with desirable charge-transport efficiency and reasonable durability is a fundamental and long-lasting challenge for solid-oxide fuel cells (SOFCs). Ceria-based electrolytes, as one of the most common types of electrolytes for intermediate-temperature solid-oxide fuel cells (IT-SOFCs), offer a high surface-exchange coefficient and faster kinetics in the triple phase boundaries (TPBs); however, they suffer to some extent of electronic conductivity in the reducing atmosphere and gradual phase transitions. Here in this work, we have reported a novel co-doped IT-SOFC electrolyte composite combining the apatite structure of Lanthanum Silicate (LSO) with the fluorite structure of Gadolinium-doped Ceria (GDC), which showed a high ionic conductivity and a minimal electronic leak. The resulting GDC-LSO composite electrolyte also achieved an OCV (open-circuit voltage) of 1 V at 800 °C, implying a significant improvement in the OCV values reported for the typical ceria-based electrolytes (∼0.75 V). The sample was prepared using 40 wt% GDC and 60 wt% LSO (40GDC-60LSO) showed a maximum electrical conductivity of 25 mS cm−1 at 800 °C with good densification properties (>95 % relative density). The cell electrochemical performance measurement was conducted using a 3.0 vol% humified H2 stream at the anode side while the cathode side was exposed to the air at 800 °C. The interdiffusion of cations between La3+ in the LSO phase and Ce4+ and Gd3+ in the GDC phase was detected by XRD and EDX results after sintering samples at 1500 °C for 4 h using 0.5 wt% PVA or 0.5 wt% Ethyl cellulose (EC) as the binder. The proposed GDC-LSO composite could help better understand the influence of compositional constituents and processing variables on the densification and electrical properties of the electrolyte materials for the IT-SOFCs.

A machine learning approach for predicting evaporation-induced composition variability in directed energy deposition in-situ alloying

This study addresses the challenge of compositional change due to evaporation in additive manufacturing, specifically focusing on directed energy deposition in-situ alloying. A machine learning model, capable of delivering high predictive accuracy and generalizability even with a limited dataset, was developed using data from 177 ferromanganese specimens fabricated in this study. To improve model interpretability, Surrogate SHAP, an innovative analysis technique, was introduced to clarify the relationships between process conditions and compositional changes. Furthermore, a machine learning-based process design method capable of predicting process conditions that meet specified compositional targets was developed. Experimental validation confirmed the model’s high predictive accuracy and its effectiveness in identifying optimal process conditions for achieving desired compositions. This research demonstrates the potential of machine learning to address traditional challenges in additive manufacturing and lays a foundation for further advancements in materials science and manufacturing process optimization.

Lipids and Fatty Acid Composition Reveal Differences between Durum Wheat Landraces and Modern Cultivars.

Durum wheat (Triticum turgidum L. ssp. durum) landraces, traditional local varieties representing an intermediate stage in domestication, are gaining attention due to their high genetic variability and performance in challenging environments. While major kernel metabolites have been examined, limited research has been conducted on minor bioactive components like lipids, despite their nutritional benefits. To address this, we analyzed twenty-two tetraploid accessions, comprising modern elite cultivars and landraces, to (i) verify if the selection process for yield-related traits carried out during the Green Revolution has influenced lipid amount and composition; (ii) uncover the extent of lipid compositional variability, giving evidence that lipid fingerprinting effectively identifies evolutionary signatures; and (iii) identify genotypes interesting for breeding programs to improve yield and nutrition. Interestingly, total fat did not correlate with kernel weight, indicating lipid composition as a promising trait for selection. Tri- and di-acylglycerol were the major lipid components along with free fatty acids, and their relative content varied significantly among genotypes. In particular, landraces belonging to T. turanicum and carthlicum ecotypes differed significantly in total lipid and fatty acid profiles. Our findings provide evidence that landraces can be a genetically relevant source of lipid variability, with potential to be exploited for improving wheat nutritional quality.

The Similarity Degree of the Anthropometric and Body Composition Variables of Brazilian and Mozambican Schoolchildren: A New Approach Using the Smoothed Jaccard Index Surface.

Brazil and Mozambique face similar socioeconomic challenges, including common indicators of undernutrition and overnutrition among children. This study evaluated the similarity degree of the anthropometric and body composition variables of Brazilian and Mozambican children by using the Jaccard index. A total of 1831 children of both genders aged 7-10 years from three Brazilian cities (Recife, Vitoria de Santo Antao, and Lagoa do Carro) and three Mozambican cities (Maputo, Boane, and Inhambane) participated in this study. Anthropometric (height, body mass, and waist circumference) and body composition (body fat percentage [%BF], lean mass, and fat mass) variables were measured and the Smoothed Jaccard Index Surface (SJIS) was used to evaluate the similarity degree. Brazilian children were taller and heavier and had a higher %BF and fat mass than Mozambican children. Children living in urban areas were taller than those living in rural zones in both countries. Brazilian and Mozambican children showed high similarity only between %BF and lean mass. Children from Recife and Maputo had high similarities among waist circumference, body mass, fat mass, height, and %BF. Finally, a high SJIS degree was observed among height and %BF for schoolchildren from rural and urban zones. Brazilian and Mozambican children exhibit differences in growth characteristics but a high degree of similarity when children from rural and urban zones are compared.

A Multiphase and Multicomponent Model and Numerical Simulation Technology for CO2 Flooding and Storage

In recent years, CO2 flooding has become an important technical measure for oil and gas field enterprises to further improve oil and gas recovery and achieve the goal of “dual carbon”. It is also one of the concrete application forms of CCUS. Numerical simulation based on CO2-EOR plays an indispensable role in the study of the mechanism of CO2 flooding and buried percolation, allowing for technical indicators to be selected and EOR/EGR prediction to be improved for reservoir engineers. This paper discusses the numerical simulation techniques related to CO2 flooding and storage, including mathematical models and solving algorithms. A multiphase and multicomponent mathematical model is developed to describe the flow mechanism of hydrocarbon components–CO2–water underground and to simulate the phase diagram of the components. The two-phase P-T flash calculation with SSI (+DEM) and the Newton method is adopted to obtain the gas–liquid phase equilibrium parameters. The extreme value judgment of the TPD function is used to form the phase stability test and miscibility identification model. A tailor-made multistage preconditioner is built to solve the linear equation of the strong-coupled, multiphase, multicomponent reservoir simulation, which includes the variables of pressure, saturation, and composition. The multistage preconditioner improves the computational efficiency significantly. A numerical simulation of CO2 injection in a carbonate reservoir in the Middle East shows that it is effective for researching the recovery factor and storage quantity of CO2 flooding based on the above numerical simulation techniques.

Extraction of proteins from six seaweeds of south-east coast of India: Proximate composition and effect of process variables on protein solubilisation

Extraction of proteins from six seaweeds of south-east coast of India: Proximate composition and effect of process variables on protein solubilisation

Intraspecific Chemical Variability and Antioxidant Capacity of Siparuna guianensis Aubl. Essential Oil from Brazil

Siparuna guianensis Aubl. is an essential-oil-producing plant with diverse ethnopharmacological uses and bioactive potential. This study aims to evaluate the intraspecific variation in the yield, chemical composition, and antioxidant capacity of S. guianensis essential oil (EO). The specimens (SG-1 to SG-6) were collected in June, five in the district of Outeiro and one in the Salvaterra municipality (Brazil). EOs were obtained by hydrodistillation. The chemical compositions were analyzed by gas chromatography coupled to a mass spectrometer (GC-MS). The DPPH radical scavenging tests and inhibition of β-carotene oxidation by linoleic acid were carried out to evaluate the antioxidant capacity of EOs. Principal components analyses were performed to verify the interrelationships between the studied specimens’ oil yields, chemical composition, and antioxidant capacity. Regarding chemical constituents, all studied samples showed the occurrence of spathulenol with an average concentration of 25.6 ± 15.6%. The samples that presented the highest amounts of this constituent were SG-5 (43.3%) and SG-1 (41.8%); the spathulenol amounts in other samples were 33.2% (SG-4); 13.8% (SG-2); 11.5% (SG-6) and 9.8% (SG-3). Moreover, there was no significant variability in yield and antioxidant capacity using DPPH and β-carotene/linoleic acid; both tests found insignificant values. This species presents a notable intraspecific chemical variability. Despite notable antitumor activities, the plant presents intraspecific chemical variability in composition, which suggests new studies to evaluate the impacts on bioactive compounds.

Driving gut microbiota enterotypes through host genetics

BackgroundPopulation stratification based on interindividual variability in gut microbiota composition has revealed the existence of several ecotypes named enterotypes in humans and various animal species. Enterotypes are often associated with environmental factors including diet, but knowledge of the role of host genetics remains scarce. Moreover, enterotypes harbor functionalities likely associated with varying abilities and susceptibilities of their host. Previously, we showed that under controlled conditions, 60-day-old pig populations consistently split into two enterotypes with either Prevotella and Mitsuokella (PM enterotype) or Ruminococcus and Treponema (RT enterotype) as keystone taxa. Here, our aim was to rely on pig as a model to study the influence of host genetics to assemble enterotypes, and to provide clues on enterotype functional differences and their links with growth traits.ResultsWe established two pig lines contrasted for abundances of the genera pairs specifying each enterotype at 60 days of age and assessed them for fecal microbiota composition and growth throughout three consecutive generations. Response to selection across three generations revealed, per line, an increase in the prevalence of the selected enterotype and in the average relative abundances of directly and indirectly selected bacterial genera. The PM enterotype was found less diverse than the RT enterotype but more efficient for piglet growth during the post-weaning period. Shotgun metagenomics revealed differentially abundant bacterial species between the two enterotypes. By using the KEGG Orthology database, we show that functions related to starch degradation and polysaccharide metabolism are enriched in the PM enterotype, whereas functions related to general nucleoside transport and peptide/nickel transport are enriched in the RT enterotype. Our results also suggest that the PM and RT enterotypes might differ in the metabolism of valine, leucin, and isoleucine, favoring their biosynthesis and degradation, respectively.ConclusionWe experimentally demonstrated that enterotypes are functional ecosystems that can be selected as a whole by exerting pressure on the host genetics. We also highlight that holobionts should be considered as units of selection in breeding programs. These results pave the way for a holistic use of host genetics, microbiota diversity, and enterotype functionalities to understand holobiont shaping and adaptation.4B2VhAArUR-Phf8Fa7EFRXVideo

Integrating Social Drivers of Health into Hospital Ratings with Application to the 100 Top Hospitals Study.

The objective was to investigate the relationship between social drivers of health (SDOH) and hospital performance within the 100 Top Hospitals study, exploring methods to recognize hospitals serving marginalized communities. Publicly available data sourced from the Centers for Medicare and Medicaid Services and the 2023 100 Top Hospitals study was used. The study employed multivariable hierarchical generalized linear regression models to assess the association between an SDOH composite variable derived using principal component analysis and overall hospital performance measures within the 100 Top Hospitals study. The analysis revealed a statistically significant association between SDOH factors and study ranking results. The SDOH composite variable is a significant predictor of performance within the 100 Top Hospitals study. Accounting for SDOH is essential to recognize high-performing hospitals serving marginalized communities. The findings suggest a need for broader considerations of SDOH in hospital ranking methodologies across various industry programs.

Multiscale Equation-Oriented Optimization Decreases the Carbon Intensity of Shale Gas to Liquid Fuel Processes.

Shale gas is revolutionizing the U.S. energy and chemical commodity landscape and can ease the transition to a sustainable decarbonized economy. This work develops an equation-oriented (EO) multiscale modeling framework using the open-source IDAES-PSE platform that tractably incorporates microkinetic detail in process design via reduced-order kinetic (ROK) models. Using multiobjective optimization with embedded heat integration and life-cycle analysis, we simultaneously minimize the minimum selling price of liquid hydrocarbons (e.g., liquid fuels/additives from shale gas) and process emissions (via a CO2 tax). Optimization reduces greenhouse gas emissions per MJ of fuel produced by over 35% compared to the literature and achieves a carbon efficiency of 87%. The optimizer changes the recycling rate, temperatures, and pressures to mitigate the effect of ROK model-form uncertainty on product portfolio predictions. Moreover, we show that the optimal process design is insensitive to changing CO2 tax rates. Finally, the EO framework enables a fast sensitivity analysis of shale gas composition variability across 12 regions of the Eagle Ford basin. These results highlight the benefits of the open-source EO framework: fast, scalable, customized, and reproducible system analysis and optimization for sustainable energy technologies beyond shale utilization.

Crop age is the main driver affecting alfalfa mosaic virus: The predominant virus in the alfalfa virome

AbstractThe alfalfa virome has been understudied. Existing research dealing with viral incidences within the crop primarily concentrate on local factors, rather than considering a broader perspective. In this comprehensive 2‐year study, we define the alfalfa virome and the main local and landscape factors affecting the incidence and annual increase of the Alfalfa mosaic virus (AMV), the most prevalent virus in alfalfa. The study was conducted in commercial alfalfa fields located along the highly productive northeast region of the Iberian Peninsula. For the first time in Europe, next‐generation sequencing revealed the presence of 14 different viruses representing the genera Cytorhabdovirus, Alphapartitivirus, Amalgavirus, Alfamovirus, Luteovirus, Enamovirus and Flavivirus. AMV was the most prevalent species, accounting for 89% of the identified viral contigs. Enzyme‐linked immunosorbent assays showed that the incidence of AMV varied between fields, with the average incidence doubling from 34% in 2019 to 65% in 2020. To assess the effect of local and landscape characteristics on the incidence of AMV and the observed annual increase, we selected different local variables and recorded landscape structure at three different buffer radii (250, 500 and 1000 m) from the centre of each field. Both the incidence and annual increase in AMV were driven mainly by local characteristics. The incidence of AMV showed a significant relationship with crop age and field area, whereas the annual increase was mainly influenced by crop age and the cumulative number of alate morphs of the aphid Acyrthosiphon pisum. Only one landscape composition variable, the percentage of alfalfa, showed a significant relationship with AMV incidence at the 250‐m scale. These results confirm the effect of local variables on the population structure of generalist viruses.

The Role of Latent Heat Buffering in the Generation of High-Silica Rhyolites

Abstract The physical process of crystal-melt separation is responsible for the accumulation of small to very large volumes (&amp;gt;100 km3) of eruptible rhyolitic melt in the shallow crust. Granitic intrusions, although providing a terminal, time-integrated image of melt segregation processes, host an unmatched record of the physical properties controlling mechanisms and rates of interstitial melt extraction from a crystal-rich source. We applied mass balance calculations and thermodynamic modeling simulations to an extensive bulk rock geochemistry dataset (&amp;gt;150 samples) collected in a Permian upper-crustal granitoid intrusion of the Italian Southern Alps. Textural and geochemical evidence indicate that this intrusion constituted a single, zoned magma body, with a crystal-rich base and a thick (~2 km), high-silica cap (75–77 wt% SiO₂). The large compositional variability of the crystal-rich materials suggests variable degrees of melt extraction efficiency and corresponding terminal porosities. Specifically, the loosely bimodal distribution of porosity values (φ) indicates that at least two distinct melt segregation mechanisms were operating in this system, which produced both high (0.65–0.45) and low terminal porosities (0.45–0.25) in the crystal-rich, cumulate materials. Modeling of latent heat budget shows that coexistence of cumulate products with differing terminal porosity signature can be explained by melt segregation processes taking place at different depths across a thick, interconnected magmatic reservoir with an initial homogenous water content (~4 wt% H2O). Deep in the mush column, low water activities (aH₂O &amp;lt; 0.5) promoted thermal buffering of cooling magma at high crystallinities, enabling residual melt extraction by percolation through a crystalline framework accompanied by compaction. Instead, at shallower depths, high water activities (aH₂O &amp;gt; 0.5) ensured prolonged magma residence at porosities that promoted crystal melt separation via hindered settling. Distinct melt extraction processes, acting synchronously but at different depths in vertically extensive silicic mush columns, can account for the large volumes of residual, haplogranitic melt mobilized during the relatively short lifespan of upper crustal magma reservoirs (~105 years).

Impact of Vancomycin trough levels monitoring on uncomplicated methilcillin-resistant Staphylococcus aureus bacteremia in chronic kidney disease on hemodialysis, retrospective cohort

BackgroundCKD patients on hemodialysis (HD) with Staphylococcus aureus (SA) bacteremia present high morbidity, mortality and increased risk of MRSA. Vancomycin is the antibiotic of choice in these cases, it has a narrow therapeutic margin and inadequate dosage generates a risk of toxicity, therefore, the recommendation is to dosage it through serum levels.MethodsThis is a retrospective cohort study in 3 hospitals of third level of complexity in the city of Medellin in which there were differences in the measurement and implementation of vancomycin25 dosage based on trough levels (VL) in patients with chronic kidney disease on hemodialysis (CKD- HD) with uncomplicated bacteremia based infection by methilcillin-resistant Staphyloccocus aureus (MRSA). The primary outcome was the composite of hospital mortality, clinical response (fever, hemodynamic instability and altered consciousness), complications associated with bacteremia, or bacteriological response failure (positive cultures at first week follow-up) at 7 days. The composite variables were analyzed individually as secondary outcomes.ResultsThe main unadjusted outcome (OR 1.3, CI 0.6 - 2.7) and adjusted for age, Charlson index, loading dose, initial dose, dosing frequency and MIC to vancomycin (OR 1.2, CI 0.5 - 2.7). Regarding adjusted secondary outcomes: clinical response (OR 1.4 CI 0.3 - 5.8), death (OR 1.3 CI 0.3 - 4.6) and complications (OR 0.9, CI 0.37 - 2.2).ConclusionsWe conclude that the measurement of trough levels in patients with HD-CKD does not modify the composite outcome. The main limitation is the sample size and type of study, randomized control trials may be required to confirm the results presented.

National-scale antimicrobial resistance surveillance in wastewater: A comparative analysis of HT qPCR and metagenomic approaches

Wastewater serves as an important reservoir of antimicrobial resistance (AMR), and its surveillance can provide insights into population-level trends in AMR to inform public health policy. This study compared two common high-throughput screening approaches, namely (i) high-throughput quantitative PCR (HT qPCR), targeting 73 antimicrobial resistance genes, and (ii) metagenomic sequencing. Weekly composite samples of wastewater influent were taken from 47 wastewater treatment plants (WWTPs) across Wales, as part of a national AMR surveillance programme, alongside 4 weeks of daily wastewater effluent samples from a large municipal hospital. Metagenomic analysis provided more comprehensive resistome coverage, detecting 545 genes compared to the targeted 73 genes by HT qPCR. It further provided contextual information critical to risk assessment (i.e. potential bacterial hosts). In contrast, HT qPCR exhibited higher sensitivity, quantifying all targeted genes including those of clinical relevance present at low abundance. When limited to the HT qPCR target genes, both methods were able to reflect the spatiotemporal dynamics of the complete metagenomic resistome, distinguishing that of the hospital and the WWTPs. Both approaches revealed correlations between resistome compositional shifts and environmental variables like ammonium wastewater concentration, though differed in their interpretation of some potential influencing factors. Overall, metagenomics provides more comprehensive resistome profiling, while qPCR permits sensitive quantification of genes significant to clinical resistance. We highlight the importance of selecting appropriate methodologies aligned to surveillance aims to guide the development of effective wastewater-based AMR monitoring programmes.

Barriers to Abortion among Women and Girls in Selected Districts of Nepal.

Even after two decades of legalization of abortion in Nepal, most women and girls still do not have knowledge on abortion legality and face abortion barriers. This study will explore perceived barriers to safe abortion and the factors associated with it. A Mixed method study design was conducted in 30 wards of 20 Municipals of seven districts of Lumbini and Sudurpaschim provinces. Quantitative data was analyzed for 673 women of reproductive age of 15-49 years. For qualitative data, key informant interviews were conducted. The analysis was done on five different barriers and a composite variable was created from them. Most women and girls perceived social (34.6%), followed by family (30.6%), physical (30.6%), personal (29.5%), and health facility (14.9%) barriers to access safe abortion services. The key finding was that women and girls with knowledge on abortion legality were more likely to perceive barriers to abortion (AOR:2.31, CI:1.574-3.394). Women and girls with higher educational and economic status as well as Dalit women were less likely to perceive barriers to abortion services whereas never married women and girls perceived more barriers in accessing abortion services. Women and girls perceived several barriers to access safe abortion services. Women who have better knowledge on abortion legality recognize more barriers regarding abortion. This highlights the importance of raising awareness of women and girls on abortion rights to empower them in recognizing and advocating for the removal of the obstacles that stop them from getting abortion services.

Nutrient Composition and Quality Assessment of Royal Jelly Samples Relative to Feed Supplements.

Royal jelly is a substance secreted by the hypopharyngeal and mandibular glands of nurse honey bees, serving as crucial nutritional source for young larvae, queen honey bees, and also valuable product for humans. In this study, the effect of the feed supplements on the nutritional composition and qualities of royal jelly was investigated. Two types of royal jelly samples were acquired: one from honey bees fed with sugar syrup as a feed supplement and the other from honey bees fed with honey. The production, harvesting, and storage of all royal jelly samples followed standard procedures. Parameters for quality assessment and nutritional value, including stable carbon isotopic ratio, moisture content, 10-hydroxy-2-decenoic acid (10-HDA) level, carbohydrate composition, amino acid composition, and mineral contents, were analyzed. The results revealed that despite variability in moisture content and carbohydrate composition, fructose was lower (2.6 and 4.1 g/100 g as is for sugar-fed and honey-fed royal jelly, respectively) and sucrose was higher (7.5 and 2.7 g/100 g as is for sugar-fed and honey-fed royal jelly, respectively) in the sugar-fed group. The stable isotope ratio (-16.4608‱ for sugar-fed and -21.9304‱ for honey-fed royal jelly) clearly distinguished the two groups. 10-HDA, amino acid composition, and total protein levels were not significantly different. Certain minerals, such as potassium, iron, magnesium, manganese, and phosphorus were higher in the honey-fed group. Hierarchical analysis based on moisture, sugar composition, 10-HDA, and stable carbon isotopes categorized the samples into two distinct groups. This study demonstrated that the feed source could affect the nutritional quality of royal jelly.