Journal of Science and Technology Mahasarakham University

The development of braised milkfish (Chanos chanos) in soy sauce standard recipe

2024-11-15T15:48:48+07:00

Milkfish specimens under the age of 8 months typically exhibit a smaller size and a significant proportion of bones in their flesh, which presents a challenge in culinary applications. The objective of this research is to develop a standardized recipe for braised milkfish in soy sauce that results in a more tender bone texture. The descriptive data on the physical characteristics of fish were collected. The physicochemical properties of braised milkfish in soy sauce, including moisture content, color value (L*, a*, b*), and Texture Profile Analysis (TPA), were determined. The sensory evaluation was applied to determine the preference of the standard recipes using 9-Point Hedonic scale and a just about right (JAR) scale. Nutritional value was evaluated according to Thai nutrition labeling standards. The results showed that the standard recipe for braised milkfish had a moisture content of 59.59%, and the color values L*, a*, and b* were 38.47, 6.08, and 14.58, respectively. The hardness value was 110.47 N, while gumminess and chewiness, which indicate the texture during chewing, were 50.87 N and 29.03 N, respectively. Sensory liking scores for overall appearance, aroma, taste, flavor, texture, and overall liking were 8.7, 8.4, 8.6, 8.3, 7.6, and 8.0, respectively, on the 9-point hedonic scale. The nutritional values according to the format of Thai nutrition labels showing this recipe (Serving size 125 grams) provided a total energy of 190 Kcal, 21 grams of protein, 50% of calcium, and 10% of iron. However, the recipe showed high sodium (40% of the daily value) and cholesterol (37% of the daily value). This research demonstrated that the potential for using small-sized, bone-rich milkfish to produce a braised milkfish in soy sauce had high sensory preference scores, high in protein and calcium content.

Species identification of marine crabs in reforested mangrove at Kung Krabaen Bay, Chanthaburi Province, using DNA barcodes

2024-10-28T06:54:57+07:00

The problem of mangrove forest destruction has led to a decline of biodiversity in Thailand, including animals such as marine crabs. Kung Krabaen Bay in Chanthaburi Province is one of the areas where
a mangrove reforestation project has been implemented. The study of marine crab species diversity in this area can be used as an indicator of the project success. Currently, the identification of marine crab species uses genetic data in conjunction with morphological characteristics to obtain more accurate information, as some species exhibit similar morphological traits. This study aimed to study the species identification of marine crabs in reforested mangrove at Kung Krabaen Bay, Chanthaburi Province using DNA barcodes. Fifty-eight samples of marine crab were species identified by analyzing the nucleotide sequence of the Cytochrome oxidase I (COI) gene on mitochondrial DNA. All 58 marine crabs were successfully PCR amplified and sequenced. The identity of all sequences was determined by comparing with GenBank genetic database. The results found that 11 species were identified. Ten species showed a high genetic similarity of 97.26% – 100%, including Scylla paramamosain, S. tranquebarica, S. olivacea, Portunus pelagicus, Thalamita crenata, Charybdis affinis, Venitus latreillei, Myomenippe hardwickii, Varuna yui and Clibanarius longitarsus. However, the remaining species, Neodorippe callida, did not have a nucleotide sequence of the COI gene in the GenBank database. The diversity of marine crab species in the reforested mangrove area of Kung Krabaen Bay, which comprised 11 species, was close to the 13 species found in the natural mangrove area of the bay. Three economically important crab species in the genus Scylla were identified as opposed to only one species previously reported. DNA barcoding significantly increases the confidence in identifying marine crab species. The diversity of crab species in the reforested mangrove which close to the natural areas indicates the abundance of the planted mangrove forest area in Kung Krabaen Bay, Chanthaburi Province. The results of this study can be used as basic data to monitor the success of mangrove reforestation and biodiversity, which will lead to planning for conservation and sustainable management of crab resources.

Biological activity of silk sericin protein and its application

2024-05-08T16:59:19+07:00

Silk sericin protein or Silk glue protein, a natural protein biopolymer produced by silkworms, has attracted significant attention particularly in biomedical and cosmeceutical applications over the past decade. Sericin possesses exceptional biocompatibility, biodegradability, and unique amino acid composition endowing it with a range of beneficial properties, making it a promising candidate for various biomedical and cosmeceutical applications. This comprehensive review looks insight into the multifaceted aspects of silk sericin, encompassing its structure, compositions as well as exploring various extraction methods. Biological properties including antioxidant activity and stimulating cell proliferation, therapeutic potential, and applications in tissue engineering and drug delivery were also discussed. Research attempts focused on improving the properties and applications of sericin-based biomaterials were also mentioned.

Effects of NAA and activated charcoal on root induction of Impatiens sirindhorniae Triboun & Suksathan

2024-12-02T08:36:20+07:00

Impatiens sirindhorniae are beautiful flowering plants and endemic plants that grow on limestone mountains. It was only found in Krabi province and Surat Thani province. Currently, its conservation status was classified as vulnerable species. Micropropagation allows the production of plantlet for preservation genetic resources. The objective of this research was to investigate the influence of NAA and activated charcoal on micro-propagation of I. sirindhorniae for producing plantlet for transplanting and conservation in their natural habitat. Shoots developed explant obtained from cultivation in sterile conditions, approximately 2.0 centimeters long and without root formation, were taken for root induction. Shoot explants were cultured on 1/3 strength of solidified MS medium, 2 shoots per bottle. The experiment was divided into 6 treatments viz. 1/3 MS supplemented with various concentrations of NAA (0, 0.5, 1.0, 1.5, and 2.0 mg/L) and 1 g/L of activated charcoal. The treatment with only 1/3 MS is control. After cultured for 4 weeks, the root induction rate, number of roots and root characteristics were recorded. Three replications, with ten bottles per replicate and two explants per bottle, were used for each treatment. CRD experiment in a completely randomized design was carried out. The root induction rate, root length and root width were highest in control (100%, 3.50 cm, 0.23 cm). However, plantlet cultured on media supplemented with activated charcoal (treatment 6) had root induction rate (100%), average number of roots per plant (5.58 roots) and root length (2.66 cm), not significantly different from the control. Therefore, it can be concluded that all concentrations of NAA had an inhibitory effect on root induction in I. sirindhorniae. While 1/3 MS supplemented with or without activated charcoal should be used on root induction in I. sirindhorniae.

Feasibility study on the utilization of phospholipids derived from para rubber seed oil for liposome particles formation

2024-11-22T10:11:40+07:00

Liposome particles can be synthesized using phospholipids as precursors. These particles have the capability to encapsulate crucial substances, prevent degradation and enhance stability of the substances. The primary aim of this research is to investigate the application of phospholipids derived from para rubber seed oil for the formulation of liposome particles. Oil was extracted from para rubber seeds of the RRIM 600 variety using hexane as a solvent. Phospholipids were separated from the oil through a heat and water degumming process. The type and quantity of phospholipids were analyzed via high-performance liquid chromatography technique. Liposome particles were synthesized using the reverse phase evaporation method, and the physical properties of liposome particles were measured by using dynamic light scattering technique. The morphology of liposome particles was examined through transmission electron microscopy. Additionally, the stability of the liposome particles was examined over a period of 0 to 12 weeks at 4^oC. The oil content in para rubber seeds was found to be 45.25±0.04 %w/w. The predominant phospholipids identified in the gums isolated from para rubber seed oil were phosphatidylcholine and phosphatidylethanolamine (22.36±3.10 and 17.39±0.51 mg/100g of oil). When synthesizing liposome particles using 0.1-2.0 %w/v of phospholipids, it was observed that a homogeneous yellow mixture was obtained, with particle dispersed in an aqueous phase. These liposomes exhibited a spherical shape, with sizes ranging from 524 to 644 nanometer. The polydispersity index ranged from 0.33 to 0.46. The z-potential of the particles ranged from -33 to -58 mV and the synthesized particles exhibited the highest stability for 8 weeks. In summary, the phospholipids derived from para rubber seed oil can be utilized to form liposome particles.

Antioxidant activity of Carissa carandas Linn. fruit extract and its application in a liquid soap product

2024-10-07T10:00:17+07:00

Carissa carandas Linn. is a plant that has medicinal properties. Extracts from the fruit and leaves of this plant contain antioxidant active substances with high efficiency. The objectives of this research were to study the antioxidant activity of extracts of C. carandas L. fruit, investigate the effect of inhibiting the activity of the enzyme tyrosinase, and develop a liquid soap formula from extracts of C. carandas L. fruit tested according to TIS standards 14–2019. The research results found that C. carandas L. fruit extract made from 95% ethanol has a viscous consistency. It has a dark red color and smells like burnt sugar. It has a yield of 21.80%by mass. Testing the antioxidant activity of C. carandas L. extract using the DPPH method compared to standard vitamin C. It has an IC₅₀ value equal to 14.24 + 0.03 mg/mL and tested the effect of inhibiting the activity of the tyrosinase enzyme using the modified dopachrome method. It was found that the inhibition value of the tyrosinase enzyme of the C. carandas L. extract was 50%, equal to 14.37 +0.05 mg/mL. When used to develop a liquid soap product from C. carandas L. fruit extract and test the chemical properties of the liquid soap from C. carandas L. fruit extract, it was found that it has a total fat content of 15.40 percent by mass. It has an acidity-alkalinity of 4.5. No free alkalinity was found. There is an amount of substances that are not soluble in ethanol of 0.45 percent by mass, which passes the TIS 14-2019 standard criteria. Antioxidants from C. carandas L. fruit are very interesting because the C. carandas L. fruit has properties that are beneficial to skin health and contains extracts that have antioxidant effects that can be used in dietary supplements and cosmetics.

Assessment of fraudulent conduct during online exams using an artificial intelligence-based automatic student facial expression recognition system

2024-10-11T12:27:40+07:00

The primary issues arising from the disruption of traditional face-to-face examinations in the exam room and the shift to online exams are the unique facial expressions and behaviors of the students, which are difficult to understand with humans. The purposes of this research were to 1) develop a model of educational innovation for the assessment of fraudulent conduct during online exams, using Artificial Intelligence (AI) based on an Automatic Student Facial Expression Recognition (ASFER) system; 2) evaluate the effectiveness of the model through metrics such as accuracy, precision, recall, and F-measure; and 3) evaluate the effectiveness of the model in assessing fraudulent conduct during online exams, using AI based on an ASFER system during its actual use. The results revealed that 1) the model that was developed addressed the problem based on a deep learning method in artificial intelligence, consisting of six steps: data collection from online exam videos, data preparation by extracting frames, development of the Automatic Student Facial Expression Recognition Model, also known as STOU-ASFER using two algorithms: a convolutional neural network (CNN) and a multilayer perceptron (MLP) for classifying the results into those exhibiting a regular face and those exhibiting a face showing signs of fraudulent conduct, evaluation of the model using the four main metrics of accuracy, precision, recall, and F-measure, parameter optimization, and deployment for real-time alerts and summary reporting. 2) The evaluation of the model showed an accuracy value of 86.2%, a precision value of 77.34%, a recall value of 95.7%, and an F-measure of 85.6%, and 3) the evaluation of the model performed well in predicting fraudulent behavior in the simulated examination environment. However, the model needs to be improved for face detection when faces are randomly positioned and when small image sizes are encountered.

Evaluating model performance for sentiment analysis on game reviews

2024-12-09T17:35:26+07:00

This research aimed to examine game reviews and compare the characteristics of classification models using Thai language data, particularly in contexts with limited resources. The experiment evaluates the performance of machine learning models, including Naïve Bayes, support vector machines, and 1D-CNN, and compares them with transformer-based models, namely BERT Multilingual and WangchanBERTa, in analyzing game-related reviews using a dataset primarily consisting of Thai-language comments. This research employs Bag of words, TF-IDF, and word2vec techniques to generate text transformations for machine learning models and CNN model. In contrast, transformer models employ pre-trained embeddings. The experimental results indicate that WangchanBERTa achieves the highest overall performance, with an accuracy of 82.16%, a precision of 87.06%, a recall of 86.18%, and an F1-score of 86.62%. Meanwhile, the support vector machine method employing the Bag of Words technique demonstrates the best performance among the machine learning models, with an accuracy of 81.26%. The experimental findings within the text transformation methods indicate that feature extraction is a critical factor in optimizing the performance of machine learning models. The study reveals that feature extraction methods focusing exclusively on individual words, such as Bag-of-Words and TF-IDF, demonstrate greater effectiveness in feature extraction compared to context-aware approaches such as word2vec. An analysis of the experimental results reveals that the accuracy of the best-performing models in both categories differs by approximately 1%. The machine learning models achieve accuracy levels comparable to those of the transformer models while requiring fewer resources, making them well-suited for resource-constrained environments.

A comparative study on imputation methods for clustering with missing data

2024-12-08T10:27:59+07:00

Managing missing data by data imputation always challenges the subsequent data analysis process. Especially when a small amount of important data cannot be eliminated. In General, missing data can be imputed by filling its central value, such as the mean or mode value, although such methods might be unsuitable for every dataset with various distributions. Therefore, machine learning approaches to predict missing values are an interesting option. In this research, the impact of five missing data imputation methods was experimented with by clustering data with three missing rate levels. Two simulated 2D datasets and one real-world bank customer dataset were used in this work. Five missing data imputation methods, including Mean/Mode, K-Nearest Neighbors (KNN), Multivariate Imputation by Chained Equations (MICE), KNN, MICE Random Forest, and MICE Bayesian Ridge methods, were compared. After imputation, the data were clustered by both Hierarchical Clustering and Density-based Spatial Clustering of Applications with Noise (DBSCAN) Clustering approaches with various parameter setups for comparison. The experimental results show that KNN, MICE KNN, and MICE Random Forest imputation methods usually perform well, and consistently yield high values of Adjusted Rand Index (ARI), Normalized Mutual Information (NMI), Fowlkes-Mallows Index (FMI), and Purity regardless of data missing rate level. In addition, each clustering method may be suitable for each dataset differently. Therefore, using both an appropriate clustering approach and an imputation method to fill up data in this study, rather than traditional mean and mode imputation techniques, can expressively enhance clustering performance values ranging from 0.81 to nearly 1.

Influence of rubber content and compaction energy on the permeability and compressive strength of coarse-grained soil

2024-09-12T14:08:26+07:00

This research focuses on studying and improving the properties of coarse-grained soil by mixing it with Preservative natural rubber latex to reduce water seepage in coarse-grained soils. Excavated ponds in areas with coarse-grained soil experience high water leakage, preventing them from retaining water for use during the dry season. Rubber latex content was used at ratios of 0%, 1%, 2%, and 3% by weight of dry soil. The samples were compacted using standard compaction energies of 25%, 50%, 75%, and 100% for each ratio, then cured in open air for 3 days. The samples were subsequently tested for permeability coefficient under pressure, using a criterion of a permeability coefficient (k₂₀) equal to 0.5 cm/hr, and for compressive strength. The results showed that, in soil without rubber latex improvement, the permeability coefficient decreased as compaction energy increased. In soils improved with rubber latex, the permeability coefficient decreased at the same compaction energy as the rubber latex content increased. The prediction for the amount of rubber latex required to improve soil properties to meet the evaluation criteria indicated that compaction energies of 25%, 50%, 75%, and 100% needed at least 2.85%, 2.57%, 2.39%, and 2.15% rubber latex content, respectively. The sample improved with 1% rubber latex at 100% compaction energy had the highest compressive strength value of 1.51 ksc. These findings can be applied by using the improved soil as lining material for the bottoms and walls of ponds, which will enhance water retention efficiency for farmers in coarse-grained soil areas outside irrigation zones.