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Physical Quality of Chicken Corned Using Flaxseed Flour (
No full textFlaxseed flour (Linum usitatissimum) is known as a functional ingredient rich in dietary fiber, antioxidants, and fatty acids that support digestive health and improve food quality. Flaxseed flour is used as a filler to enhance texture and physical properties chicken corned. This study aimed to determine the optimal level of flaxseed flour addition in chicken corned, evaluated through pH, yield, water holding capacity (WHC), cooking loss, and color (L*, a*, b*). The materials used was corned from the meat of spent laying hens, formulated with different levels of flaxseed flour. The method used was a laboratory experiment using a Completely Randomized Design (CRD) with 4 treatments and 5 replications. The treatments were T0 (control), T1 (2% flaxseed flour), T2 (4% flaxseed flour), and T3 (6% flaxseed flour). The data were analyzed using Analysis of Variance (ANOVA), and then the significant difference continued with Duncant Multiple Range Test (DMRT). The results showed that flaxseed flour addition had a very significant effect (P<0.01) on all measured parameters. Increased flaxseed flour levels improved yield, WHC, and redness (a*) color, while reducing pH, cooking loss, lightness (L*) and yellowness (b*) color. It was concluded that the addition of 6% flaxseed flour gave the optimal chicken corned based on physical quality
Progressive Multi-target Optimization with Quality Gates (PMTO-QG) Using Machine Learning Classifier for Formulation Optimization and Physical Quality of Honey Powder
No full textThis study aimed to develop a predictive system for optimizing honey powder formulation through a Progressive Multi-Target Optimization with Quality Gates approach integrated with machine learning classifiers. The research was conducted using experimental dataset of honey powder production, including moisture content, HMF, bulk density, particle density, true density, solubility, and flowability. Three algorithms will be compared to see which is the best, namely Random Forest, Lasso Regression, and XGBoost used to classify and predict the best formulation. Quality gates were established as layered checkpoints to ensure each predicted formulation met the required standards before advancing to subsequent stages. Results from stage I analysis demonstrated that the PMTO-QG framework effectively filtered suboptimal formulations while improving prediction efficiency and accuracy compared to conventional trial-and-error methods. The system successfully identified formulations parameters within acceptable ranges, providing a robust foundation for subsequent experimental validation. The predicted formulation will be validated through physical tests including yield, particle size distribution, microstructure, color attributes, Tg temperature, stability tests, and sensory testing of powdered honey. This approach highlights the potential of integrating data-driven modeling and quality assurance checkpoints in functional food product development
Evaluation of Propolis as a Natural Preservative: Effects on The Nutritional Quality of Milk Jelly Candy
No full textPropolis is a bee product that bees collect from resin plant then secreted by bee saliva. Propolis has antioxidant, antifungal and antimicrobial activity so it is generally used as a natural preservative. The aim of this study was to determine and evaluate the nutritional content of milk jelly candy with added propolis at different concentrations. This study used a Completely Randomized Design (CRD) with 5 treatments and 5 replications. Data analysis used the ANOVA test and DMRT follow-up test. The treatments in this study were the levels of propolis addition P0 (0%), P1 (0.3%), P2 (0.5%), P3 (1%), and P4 (1.5%). The parameters included protein content, water content, fat content, ash content and carbohydrate content. The results showed that, addition of propolis at various concentrations had highly significantly (P<0.01) in protein content (17.51-18.48%), water content (37.67-49.5%), fat content (0.12-0.38%), ash content (0.75-0.83%), and carbohydrate content (31.14-43.09%). Increasing propolis levels improved fat content, ash content, carbohydrate content, but reduced in water content and protein content. The conclusion showed that the addition propolis as a natural preservative has almost the same effect as the use of synthetic preservatives, in some parameters has a better effect
Programmable flexible self-assembled micro/nano gratings: from fabrication strategies to tunable photonic functions
No full textThis review explores the development of programmable flexible self-assembled micro/nano gratings, focusing on their fabrication strategies, dynamic modulation mechanisms, and emerging photonic applications. Emphasis is placed on strain-driven self-assembly techniques using soft elastic substrates (e.g., PDMS), template-based replication methods, and functional composite integration for enhanced optomechanical performance. Key applications include tunable diffraction devices, strain/physical/chemical sensors, adaptive optical systems, and energy harvesting devices. A critical discussion is provided on material composition, structural design principles, and scalability challenges in grating fabrication. This review aims to consolidate recent advances in flexible grating technology, demonstrating how tailored micro/nano structures enable dynamic photonic functionality. Future directions and unresolved challenges in stability, integration, and multi-field coupling are outlined to guide next-generation programmable photonic systems
Convergence analysis and error estimates for the CSRK schemes to conserved gradient flows
No full textWe conduct a comprehensive convergence and error analysis of the second- and third-order unconditionally energy stable convex splitting Runge-Kutta (CSRK) methods for H−1 gradient flows with typical forms of free energy. Through the energy structure inherent to gradient flows, we are able to derive uniform-in-time bounds of the numerical solution in the H1, H2, and L6 norms. In turn, these functional bounds enable us to derive the associated estimates for the nonlinear error terms. Meanwhile, motivated by the fact that the diffusion coefficients are diagonally dominated in the CSRK numerical systems, the convergence results become available, based on a stage-by-stage analysis for the error evolutionary equations. The Cahn–Hilliard and phase-field crystal equations are two examples in the theoretical analysis. We also numerically compute some convergence results to validate the theorems proposed in this paper. This work deepens the theoretical foundation of CSRK methods and provides robust analytical tools for their application to conserved gradient flows
A Methodological Comparison of Evapotranspiration Estimation for Coconut MATAG (
No full textThis study was conducted at Universiti Putra Malaysia (UPM), located at a latitude of 3° N, in a rain shelter nursery on the rooftop of the Faculty of Engineering. The primary aim was to compare the performance of three evapotranspiration (ETc) estimation methods Blaney-Criddle, Hargreaves-Samani, and Penman-Monteith for Coconut MATAG (Cocos nucifera) seedling growth during nursery stages. The study spanned two cultivation seasons, each lasting 12 to 15 weeks, to account for potential seasonal variations. Data were collected from January to December 2023. The methodology involved calculating monthly ETc values using a crop coefficient (Kc) of 0.8, with climatic data gathered from a centrally located weather station within the rain shelter nursery to minimize the influence of direct rainfall. The findings revealed that the Blaney-Criddle method consistently provided the highest ETc estimates (7.67 mm/day in March to 8.1 mm/day in July), while the Hargreaves-Samani method yielded lower values (3.28 mm/day in February and December to 3.76 mm/day in July). The Penman-Monteith method showed moderate estimates, ranging from 3.84 mm/day in January to 4.96 mm/day in July. The study highlights the significant variability among methods, emphasizing the importance of selecting an appropriate estimation model for irrigation planning in tropical coconut MATAG nurseries
Qualitative and Semi-Quantitative Testing and Analysis of Sugar Content in Several Sweetened Beverages
No full textThe increasing popularity and availability of sweetened beverages has contributed to a higher risk of metabolic diseases. This study analyzed the sugar content of various sweetened beverages using sequential laboratory tests. Qualitative analysis employed glucose paper strips to detect glucose presence, while semi-quantitative analysis used a refractometer to estimate total sugar content based on a standard curve. A total of 53 samples was selected due to their accessibility in the market and frequently consumed by the community, classified into nine categories by subject matter experts, were tested. Qualitative results indicated that 33 samples contained glucose, whereas 20 samples did not. Semi-quantitative analysis revealed that estimated total sugar content often exceeded the values stated on packaging labels, particularly in health supplement drinks, ready-to-drink coffee, and ready-to-drink tea. Several samples lacked sugar content information on their packaging despite exhibiting high sugar levels. The highest estimated total sugar content was observed in the energy drink category, followed by ready-to-drink tea and fruit juice. These results underscore the necessity for increased consumer awareness regarding excessive sugar intake and highlight the importance of regulatory oversight of nutritional labeling. Further analysis utilized a data mining approach, specifically the K-Medoids Clustering algorithm. The dataset was represented in two dimensions: qualitative features (glucose test results, binary Yes/No) and quantitative features (estimated total sugar content). Silhouette Score evaluation determined that three clusters were optimal. The first cluster comprised all samples without glucose, while the remaining two clusters separated glucose-containing samples by high and low sugar content. These results demonstrate the potential of data mining techniques to enhance sugar content analysis and characterize sweetened beverage test data
Application of multivariate and univariate data analysis to evaluate the response of chili (
No full textChili peppers (Capsicum annuum L.) are a strategic horticultural commodity in Indonesia that greatly influences consumption patterns. This commodity also affects market dynamics. One effective approach to increasing productivity is through the application of plant growth regulators (PGRs). This study evaluated the effects of two types of PGR: Atonik, which contains nitrophenol compounds (sodium para-nitrophenolate, sodium ortho-nitrophenolate, and sodium 5-nitroguaiaolate), and Agrogibb, which contains gibberellic acid (GA₃), as well as a combination of the two. This experiment used TM999 curly red chili peppers. This experiment was designed to assess growth parameters and crop yield. Data analysis was performed using univariate and multivariate approaches. Multivariate analysis (PCA) showed a clear separation between treatments. Univariate analysis (ANOVA and Tukey's post hoc test) confirmed that the 60 mg/L Agrogibb treatment provided a significant increase in growth in several parameters observed. The results of the univariate and multivariate tests reinforced each other, showing that Agrogibb had a better and more dominant effect on chili plants. Correlation analysis revealed a strong positive relationship between vegetative traits, such as plant height, number of leaves, and branch development. These parameters can serve as reliable predictors in determining chili crop yield performance. This approach demonstrates the potential of statistical integration in optimizing agricultural productivity and supporting chili production development in Indonesia
Diversity, density, and ecological significance of mangrove species in Bali Barat National Park
No full textThis study assessed the condition of mangrove ecosystems in the Bali Barat National Park, focusing on Menjangan Island and Terima Bay, which are important for coastal protection and biodiversity conservation. Vegetation data were collected using the Line Transect Plot method, covering the trees, saplings, and seedlings. A total of 14 mangrove species were recorded, with 9 species in Terima Bay and 5 species on Menjangan Island. Analysis using the Important Value Index (IVI) revealed that Excoecaria agallocha was the most dominant species in Terima Bay, whereas Xylocarpus granatum dominated Menjangan Island, reflecting high adaptability to local conditions. Most individuals were found in the sapling category, suggesting good natural regeneration, whereas the highest density occurred at the seedling stage. Differences in the associated biota between sites indicated habitat heterogeneity. Overall, mangrove ecosystems in the Bali Barat National Park remain relatively healthy, providing essential ecosystem services and supporting diverse species. These findings highlight the importance of continued conservation, monitoring, and management interventions to maintain mangrove structure, regeneration, and biodiversity, thus reinforcing their role in climate resilience and nature protection