Kalasin University Journal of Science Technology and Innovation

Wet Bulb Globe Temperature (WBGT) of Work in The Car Garage, Somdet Municipality, Kalasin Province

Anurak Pintong, Chairat Sriboonjan — Mon, 19 Jan 2026 00:00:00 +0700

This research was a cross – sectional study. The objectives were to measure and assess the wet bulb globe temperature (WBGT), heat index and workload in car garages by comparing them with standards, to compare WBGT between large and small car garages, and to study the effects of heat stress in the workplace on employees in car garages. Heat stress in the workplace was measured using a WBGT meter, with measurement methods in accordance with the standards of the management of occupational safety, health, and working environment concerning heat, lighting, and sound (B.E. 2559). The study was conducted during October to November 2018. The results showed that the large and small car garages had WBGT values of 28.68+0.70 ^๐C and 29.76+1.02 ^๐C respectively and heat index values of 34.68+1.08 ^๐C and 37.32+1.47 ^๐C respectively. The workload of employees in both car garage showed that the staff involved with engine maintenance and replacement of spare parts, car parts and assemblies had moderate workloads and the staff involved in knocking and breaking car parts had heavy workloads. The comparison of WBGT with the standard showed that the employees in all departments received WBGT levels not exceeding the standard. Comparison between garages showed that the small car garage had significantly higher WBGT than the large car garage (p-value < 0.05). Heat stress in the workplace affected both physical and psychological aspects of employees.

Effects of Striped Catfish and Nile Tilapia Mince Ratios on Fish Ball Quality

Jukkarin Treeinthong, Piyachat Wiriyaampaiwong — Tue, 10 Feb 2026 00:00:00 +0700

This research aimed to evaluate the effects of different ratios of unwashed striped catfish mince (UW-SC) and washed Nile tilapia mince (W-NT) on the gel properties of mixed fish gels and the quality of fish balls. The mince ratios were varied at 25:75, 50:50, and 75:25 (UW-SC:W-NT) and subjected to two heating conditions: heating at 40 °C for 20 min followed by 90 °C for 20 min (40/90 °C), and heating at 60 °C for 20 min followed by 90 °C for 20 min (60/90 °C). These treatments were compared with Nile tilapia gel heated at 40/90 °C (0:100) and striped catfish gel heated at 60/90 °C (100:0). Subsequently, the optimal formulation was selected for consumer acceptance testing (100 panelists) and nutritional value analysis. The results indicated that the incorporation of UW-SC at levels of 50% or higher significantly increased hardness of mixed fish gels (p < 0.05). The mixed fish gels at ratios of 25:75 (40/90 °C) and 75:25 (60/90 °C) exhibited the highest gel strength (p < 0.05). Increasing the proportion of UW-SC tended to decrease cohesiveness, breaking distance, whiteness, and expressible water. However, sensory evaluation revealed that all mixed fish ball formulations received moderate overall liking scores, with no significant differences among treatments (p>0.05). Based on textural properties, taste, and overall liking, the formulation with a 75:25 ratio of UW-SC:W-NT subjected to the 60/90 °C heating condition was selected as the most suitable for consumer acceptance testing with 100 panelists. Consumer acceptance testing demonstrated an acceptance rate of 92% and a purchase decision of 79%. Nutritional analysis showed that mixed fish balls contain 14.81% protein, with low fat, cholesterol, and sodium contents, and was safe for consumption. Therefore, blending striped catfish mince and Nile tilapia mince at an appropriate ratio represents a promising approach for producing fish balls with desirable textural quality and high consumer acceptance.

Antimicrobial activity of mulberry (Morus alba) leave extract against foodborne pathogens in fermented fish (Pla-som)

Fri, 06 Mar 2026 00:00:00 +0700

Acute diarrhea and food poisoning are caused by the consumption of food or water contaminated with pathogenic microorganisms. These conditions remain major public health problems and are responsible for numerous deaths worldwide each year. Pla-som is a one kind of fermented fish that often contaminated with pathogens from the production process occurred both in raw materials and environments might harmful to the consumers. Pla-som is a traditional fermented fish product that is often contaminated with pathogens during the production process, originating from raw materials and the surrounding environment, which may pose health risks to consumers. This research aimed to evaluate the efficacy of mulberry (Morus alba) leave extract from MonPai cultivar in inhibiting the growth of foodborne pathogenic bacteria such as Bacillus cereus, Escherichia coli, Staphylococcus aureus, and Salmonella spp. in pla-som. The results revealed that ethanolic extract, aqueous extract, and powdered leaves of the MonPai cultivar at a concentration of 100 µg/g exhibited antibacterial activity. The most pronounced inhibitory effect was observed against S. aureus in 100 g of pla-som, with statistically significant differences (P < 0.05). The colony counts were 213 ± 80.83, 300 ± 95.40, and 340 ± 70.00 CFU/g, respectively. The inhibition percentages were 52.67%, 33.33%, and 24.44%, respectively. In summary, incorporating mulberry leaf extracts into fermented fish products prior to consumption may help inhibit pathogenic bacteria in the gastrointestinal tract and reduce the risk of diarrhea and food poisoning associated with the consumption of raw fermented fish.

Development of Boosting Algorithm Machine Learning Models for Diabetic Retinopathy Classification Using Symlet Wavelets

Chatchawarn Srimontree, Tanarat Chotiphan — Sat, 14 Mar 2026 00:00:00 +0700

This research aims to 1) develop and evaluate the performance of boosting machine learning models, and 2) classify retinal images with diabetic retinopathy using symlet wavelet transform feature extraction from 10 sub-bands. A total of 60 symlet features were obtained by extracting six statistical measures, namely mean, standard deviation, energy, entropy, skewness, and kurtosis, from each of the 10 sub-bands. The feature set was fed into three boosting machine learning algorithms, specifically XGBoost, LightGBM, and CatBoost, for classification model development and performance comparison. Model performance was assessed through 10-fold cross-validation and confusion matrix analysis to determine accuracy, sensitivity, specificity, and F1-score metrics for optimal model selection. Comparative performance evaluation demonstrated that the LightGBM model achieved the best overall performance across nearly all evaluation metrics, with an accuracy of 94.47%, sensitivity of 95.24%, specificity of 93.69%, and F1-score of 94.56%. These findings suggest that integrating symlet wavelet features with boosting-based machine learning algorithms provides a promising approach for diabetic retinopathy screening and diagnosis.