ASEAN Journal of Scientific and Technological Reports

Comparative Assessment of Biofungicide Formulations: Strategies Towards Stable Biocontrol Products

2025-12-08T14:26:14+07:00

The growing demand for sustainable disease management in agriculture has driven continuous development in biofungicide formulation. Despite advances in microbial discovery and screening, the formulation stage remains a bottleneck for commercialization due to limited shelf life, low field efficacy, and scalability. This review critically examines the performance, suitability, and scalability of biofungicide formulations, encompassing conventional (dry and liquid) and alternative forms (cell-free supernatants, microbial metabolites, and encapsulated systems). Dry formulations provide stability and ease of handling, while liquid formulations enable rapid microbial deployment but require protective additives. Alternative approaches, including the use of purified metabolites and encapsulated microbes, address issues of microbial viability and delivery but face challenges in formulation standardization and large-scale production. This paper also highlights formulation improvement strategies that revolve in the use of sugars as co-solutes in encapsulated formulations and the use of spore-based agents to enhance field survival and efficacy. Future research should focus on linking formulation design with microbial physiology and ecological performance to develop scalable, stable, and high-performing biofungicides.

Energy, Protein and Fiber Digestibility of Arrowroot Plant (Maranta arundinacea L.) as Feed for Native Pigs

2026-03-11T12:59:21+07:00

Arrowroot is an underutilized tuber crop with high starch content and potential as an alternative feed ingredient for swine. This study evaluated the energy, protein, and fiber metabolizability of arrowroot-based feedstuffs in native pigs. Fifteen native pigs representing three age groups (2, 4, and 7 months) were assigned to five treatments in a randomized complete block design: fasted pigs for endogenous loss determination (control), commercial feed, ensiled arrowroot whole plant, arrowroot tuber meal, and fresh arrowroot whole plant. Commercial feed recorded the highest true COD_energy (92.54%), followed by fresh arrowroot whole plant (90.42%), arrowroot tuber meal (89.51%), and ensiled arrowroot whole plant (86.94%), although differences were not significant (p=0.1779). True COD_protein differed significantly (p=0.0034), with commercial feed (93.61%) and fresh arrowroot whole plant (88.27%) showing higher values compared with arrowroot tuber meal (72.50%) and ensiled arrowroot whole plant (68.27%). Fiber digestibility was generally high, with fresh arrowroot whole plant exhibiting the highest neutral detergent fiber (94.69%) and acid detergent fiber (96.07%) utilization. Voluntary feed intake was significantly higher in pigs fed commercial feed (304.17 g/day) compared with arrowroot-based diets, although fresh whole plant (232.08 g/day) and tuber meal (202.08 g/day) showed acceptable intake levels. These findings suggest that arrowroot, particularly in its fresh whole-plant form, has potential as an alternative energy and fiber source for native pigs under controlled digestibility conditions. However, since this study focused only on coefficient of digestibility (energy, protein, fiber), further research is needed to evaluate growth performance, feed efficiency, carcass characteristics, and economic feasibility.

Development and Evaluation of a Web-Based GIS-Enabled Demographic Profiling System for Data-Driven Local Government Policy Making

2026-03-07T23:00:47+07:00

effective local governance. However, many municipalities in the 2nd District of Samar have yet to gather and collate household data automatically. Advanced methods often yield siloed datasets that clutter analysis and reduce the likelihood of spatial visualization. Consequently, the information generated is less useful in formulating effective sub-national policies. Furthermore, current demographic information systems are not integrated with GIS or web-based applications, creating a disconnect between data collection and information generation. This study aimed to fill the gap by developing a web-based GIS-enabled demographic profiling system to strengthen evidence-based policy-making among local government units (LGUs) in the 2^nd District of Samar. The system integrates household-level demographic records and visualizes them through interactive GIS maps and dashboards for easier access, management, and spatial analysis. A descriptive research design was used to evaluate the system's functionality, reliability, usability, efficiency, maintainability, and portability, following the ISO 9126/25010 software quality framework. Further, the system's development follows the Waterfall System Development Life Cycle (SDLC) model. Results showed that the system met essential software quality standards and substantially improved how demographic data are accessed and analyzed. Thus, the system enhances Samar’s LGUs' ability to design well-informed, inclusive, and community-oriented local policies.

Dietary Lecithin Modulates Growth, Selected Hemato-immunological Indices, and Glutathione Peroxidase Activity of Hoven's Carp (Leptobarbus hoevenii)

2026-03-23T10:26:04+07:00

Beneficial effects of dietary phospholipids on growth performance, hemato-immunological parameters, and antioxidant status in Hoven's carp (Leptobarbus hoevenii) are reported in this study. Experimental fish were fed four isoproteic (40%) and isolipidic (13%) experimental diets supplemented with lecithin at 0, 1, 3, and 5% for 90 days. The results showed that at 30, 60, and 90 days into the feeding trial, fish fed dietary supplementation containing 3% or 5% lecithin showed significantly improved total length, mean body weight, feed conversion ratio, and specific growth rate compared to the control group (p<0.05). No significant differences in condition factor and survival rate were observed between fish receiving dietary lecithin at any tested concentration and the control group (p>0.05). A study on hemato-immunological parameters of fish fed the experimental diets for 90 days revealed the highest red blood cell count in those receiving the 1% lecithin diet (p<0.05), whereas the white blood cell count was significantly higher in fish fed 3% and 5% lecithin diets (p<0.05). In addition, fish fed a 3% lecithin diet showed significantly higher glutathione peroxidase activity than those fed with the control diet or the 1% lecithin diet (p<0.05). These findings suggest that dietary supplementation with lecithin modulates growth and some hematological and immunological parameters, as well as antioxidant activity, in this fish species. Based on the findings, dietary supplementation with lecithin at 3-5% could promote growth, stimulate the immune response, and enhance antioxidant activity in Hoven's carp.

Comparative Analysis of Forecasting Models for Hourly Solar Irradiance in Southern Thailand

2026-03-07T23:25:17+07:00

Accurate forecasting of short-term solar irradiance is essential to optimize energy supply, improve grid stability, and increase the economic viability of photovoltaic systems. This study compares several forecasting models for predicting hourly solar irradiance using real-world data from Southern Thailand. Eight models were evaluated, including six forecasting models (Prophet, LSTM, GRU, XGBoost, Random Forest, and SARIMA with walk-forward validation) and two benchmarks (Naive and Seasonal Naive), using RMSE, MAE, and MAPE metrics. The results demonstrate that ensemble-based machine learning models significantly outperformed traditional statistical and deep learning approaches. Specifically, XGBoost achieved the best performance with RMSE of 79.43 W/m², MAE of 59.63 W/m², and MAPE of 30.07%, followed closely by Random Forest with RMSE of 83.00 W/m² and MAPE of 29.36%. Compared to the best benchmark model, XGBoost reduced RMSE by 50.3% and MAPE by 47.1%. The GRU model outperformed LSTM, demonstrating greater efficiency in capturing short-term temporal dependencies. The findings confirm that ensemble methods effectively capture complex temporal patterns and nonlinear meteorological dependencies, making them highly suitable for real-time solar forecasting applications in tropical climates.

Enhancing Oil Palm (Elaeis guineensis Jacq.) Growth Using Microbial Consortia: Roles of Phosphate Solubilization and Nitrogen Fixation

2026-03-23T11:21:07+07:00

In Thailand, oil palm is a vital economic crop, primarily cultivated in the southern region. Farmers are expanding plantations by establishing new sites and replanting previous crop areas. Proper maintenance from the seedling stage is essential for growth. Agriculturists place rock phosphate at the planting hole base to speed seedling recovery after transplantation. Converting rock phosphate into water-soluble phosphate, essential for root development and pre-planting, is a labor-intensive process dependent on microbial activity. The objective of this investigation is to identify microbes capable of converting insoluble phosphate into a soluble form in water. Furthermore, oil palm seedlings require a significant amount of nitrogen. Therefore, nitrogen-fixing microorganisms are also screened. Several phosphate-soluble microorganisms have been identified, especially the NN311 strain, which is the most effective at releasing water-soluble phosphate, both qualitatively and quantitatively. For nitrogen fixation, strain NT7 performed best. NN311 was classified as Pseudomonas sp., whereas NT7 was classified as Bacillus sp., according to nucleic acid sequence analysis in comparison to the NCBI database. In the absence of antagonistic interactions between NN311 and NT7, they were assessed simultaneously in nursery research. The results indicated that the application of these microorganisms, individually or in combination, markedly enhanced seedling growth compared to the control group. Nonetheless, combining them yields optimal outcomes. The combination of NN311 and NT7 with rock phosphate in the planting hole enhances seedling growth post-transplantation. After 18 months, seedlings treated with both strains of bacteria exhibit much superior growth compared to those that do not receive microorganisms.

Development of High-performance Activated Carbon Derived from Longan Peel for Caffeine Removal in Ion-rich Hospital Wastewater

2026-04-08T17:58:55+07:00

This study presents the development of activated carbon derived from longan peel (LPAC) as an efficient and low-cost adsorbent for the removal of caffeine (CAF) from synthetic hospital wastewater. Longan peel was carbonized and chemically activated at 600 °C and 700 °C, producing LPAC-600 and LPAC-700, respectively. The structural, textural, and functional properties of the adsorbents were characterized using XRD, FTIR, N₂ adsorption–desorption analysis, and SEM. The results indicated that increasing the activation temperature significantly enhanced surface area, pore volume, and graphitic carbon structure, with LPAC-700 exhibiting the highest BET surface area (1401.8 m²/g) and mesoporosity. Batch adsorption experiments demonstrated that LPAC-700 achieved superior CAF removal compared to LPAC-600 in both deionized water and synthetic hospital wastewater, although ion-rich conditions reduced removal efficiency due to competitive adsorption. The optimal adsorbent dosage was 0.3 g/L, yielding up to 94.23% CAF removal at an initial concentration of 100 ppm. Solution pH strongly influenced adsorption, with maximum removal at pH 7, attributed to favorable π–π interactions and hydrogen bonding. These findings confirm that LPAC-700 is a promising bio-derived adsorbent for caffeine removal in complex wastewater systems.

A Contextual Framework for Agricultural IoT Adoption: Integrating TAM, Innovation–Decision Process, and Governmental Support in Smart Farming Contexts

2026-04-15T22:24:42+07:00

Agricultural Internet of Things (IoT) adoption in developing contexts remains constrained by a fragmented understanding of cognitive, behavioral, and contextual factors. A contextual framework is developed by integrating the Technology Acceptance Model (TAM), selected components of the Innovation–Decision Process (IDP), and key enabling conditions to explain continued use intention in smart farming environments. Data from 250 Thai agricultural stakeholders with prior exposure to or implementation experience with IoT-based agricultural applications were analyzed using partial least squares structural equation modeling (PLS-SEM). Results indicate that perceived usefulness is the strongest predictor of attitude toward use, which in turn drives continued use intention. Knowledge plays a critical role as a precursor, shaping perceived ease of use, persuasion, and perceived usefulness, underscoring the importance of cognitive readiness even among experienced users. Facilitating conditions significantly support continued use intention, whereas governmental support shows no direct effect. Perceived ease of use does not significantly influence attitude, suggesting that functional value may outweigh usability considerations in post-adoption or experience-based contexts. The framework offers a context-sensitive explanation of agricultural IoT adoption by linking cognitive processes with operational support mechanisms, while the model-fit results indicate that conclusions should be interpreted with appropriate caution.

Genetic Relationship Assessment of Micropropagated Nymphaea colorata Peter Seedlings using HAT-RAPD

2026-04-19T14:44:13+07:00

Nymphaea colorata Peter and its natural hybrids are typical African waterlily cultivars with beautiful, blue-flowered shading, which were precisely selected to be subjects in this study. We have proposed to assess the genetic relationships and variability of in vitro seedlings derived from cross pollination of three N. colorata cultivars. The surface-sterilized mature seeds were cultured on half Murashige and Skoog’s (1/2MS) semi-solid medium supplemented with 1.5% (w/v) sucrose and 1.0 mg/L 6- (N⁶)-benzylaminopurine (6-BAP). After 4 weeks of culture, leafy-shooted seedlings (microgreens) were observed in all cultivars. For ex situ conservation and certain germplasm utilization, it is necessary to confirm that true-to-type waterlily species, wildtype and hybrid cultivars, are identified by their genetic backgrounds and genotyping. Thus, high-temperature random amplified polymorphic DNA (HAT-RAPD) markers were applied to examine genetic relationships among in vitro cultured seedlings compared with their field grown seed donor plants. Fourteen random primers were screened and selected from seventy-two universal primers for polymerase chain reaction (PCR) amplification and DNA fingerprinting. Genetic distances were represented as similarity coefficients ranging from 0.64 to 0.94 and then classified into two main clusters : the parental plant populations and their next generation populations. Therefore, HAT-RAPD might be effective for analyzing genetic relationships and variability in these waterlily cultivars. These scientific findings will support further conservation, breeding, genetic engineering and production of waterlily germplasm.

Development of a Sustainable Wood Treatment Process for Palmyra Palm Fronds toward Furniture Production

2026-04-13T20:25:36+07:00

This study investigated the potential of Palmyra palm frond wood preservation treatments as an alternative material for furniture production. The palm fronds were composed of 74.94 ± 2.05% moisture, 30.61 ± 17.67% cellulose, 23.54 ± 1.00% hemicellulose, and 45.36 ± 0.55% lignin. Specimens (2.5x2.5 cm) were treated with boron compounds (boric acid: borax, 1:1.5) or wood vinegar at concentrations of 1%, 3%, and 5%, and then tested for fungal resistance, termite resistance, and mechanical properties. The 3% boron compound treatment demonstrated optimal performance, with 55.62 ± 1.96% absorption after 6 days, significantly higher than 3% wood vinegar (46.91 ± 1.58%). Termite resistance testing revealed weight loss of 5.83 ± 0.17% for the 3% boron-treated samples compared to 11.21 ± 0.35% for wood vinegar and 23.90 ± 1.40% for untreated controls after 45 days. Mechanical testing showed numerically higher flexural strength values for boron-treated specimens (34.87 ± 4.48 N/mm²) than for controls (27.85 ± 1.10 N/mm²), although the difference was not statistically significant (p>0.05). Color stability remained acceptable with L-values decreasing from 68.60 ± 0.53 to 59.30 ± 0.44 after three months. Microscopic examination confirmed preservative penetration into the cellular structure. The optimized 3% boron compound treatment provided an economically viable and environmentally sustainable solution for utilizing abundant Palmyra palm resources in Southern Thailand, creating durable furniture components while reducing the pressure on endangered hardwood species.

FlexIoU: Modularity and Flexibility IoU for Bounding Box Regression in Agricultural Disease Detection

2026-04-13T20:34:06+07:00

Accurate bounding-box regression plays a crucial role in object detection, particularly in agricultural disease detection, where target objects are often small, irregular, and weakly bounded. Although Intersection over Union (IoU)-based losses such as CIoU and EIoU have improved localization performance, their fixed geometric penalty formulations limit adaptability to domain-specific object characteristics. In this work, we propose FlexIoU, a flexible and lightweight IoU-based regression loss that introduces tunable geometric penalties to enhance localization robustness. FlexIoU provides explicit control over center-distance, width, and height penalties, enabling more adaptive regression behavior for irregular lesion shapes commonly observed in agricultural imagery. The proposed loss integrates seamlessly into the YOLO training pipeline as a drop-in replacement for conventional IoU-based losses, without modifying classification or distribution focal loss components, thereby preserving inference efficiency. We evaluate FlexIoU within a YOLOv11 detection framework on a tomato leaf disease dataset under identical experimental settings and across three random seeds to ensure statistical reliability. Experimental results demonstrate that FlexIoU consistently outperforms the default YOLOv11 regression objective as well as CIoU and EIoU in terms of mAP@0.5:0.95 and overall detection balance, while maintaining stable inference speed comparable to baseline losses. These findings indicate that FlexIoU provides an effective and practical solution for improving bounding-box regression in agricultural disease detection. While the results demonstrate promising robustness across two tomato disease datasets, further validation on additional agricultural and general object detection datasets is required.

Carbon Footprint Assessment and GHG Reduction Guidelines for the Rubberwood Processing Industry in Yala Province

2026-04-13T20:33:47+07:00

This study presents a Cradle-to-Gate carbon footprint assessment (CFP) of a representative rubberwood (Hevea brasiliensis) processing factory in Yala Province, Thailand, conducted in accordance with the Life Cycle Inventory (LCI) framework and ISO 14067:2018. The functional unit was defined as one cubic meter (1 m³) of processed rubberwood leaving the factory gate. The total greenhouse gas (GHG) emission intensity was calculated as 40.83 kgCO₂-eq/m³, with raw materials and processing residues identified as the dominant emission sources, accounting for approximately 90% of total emissions. Electricity (2.33 kgCO₂-eq/m³) and diesel fuel (0.11 kgCO₂-eq/m³) constituted secondary contributors, while consumables and auxiliary materials contributed negligibly. The findings should be interpreted as a single-factory case study rather than an industry-wide representative baseline. Potential mitigation pathways, drawn from analogous studies, include optimized inventory management (15–30% reduction potential), biomass fuel substitution (50–85%), operational efficiency improvements through preventive maintenance and AI-assisted optimization (5–15%), and waste valorization through biochar conversion. These hotspots align with Thai national policy frameworks, including the Nationally Determined Contribution (NDC), Carbon Neutrality (2050), Net Zero (2065), the TGO Carbon Label Program, the EU Carbon Border Adjustment Mechanism (CBAM), the Bio-Circular-Green (BCG) economic model, and the energy policies under the Power Development Plan (PDP) and the Department of Alternative Energy Development and Efficiency (DEDE). The study provides empirical baseline data for the rubberwood processing sector and serves as a methodological reference for future, larger-scale assessments.

Trichoderma asperelloides TSUxPT3.5 Exhibits Antifungal Activity Against Plant Pathogenic Fungi and Enhances the Growth of Mini Cos Lettuce (Lactuca sativa L.)

2026-05-11T16:12:41+07:00

Trichoderma species are widely recognized as effective biological control agents due to their multifaceted antagonistic mechanisms and plant growth-promoting activities. In this study, an indigenous fungal strain, TSUxPT3.5, was isolated from organic agricultural soil in southern Thailand. Molecular identification based on multi-locus sequence analysis of the ITS, tef1, and rpb2 regions confirmed the strain as Trichoderma asperelloides. This fungus was further characterized for its plant growth-promoting traits through both direct and indirect mechanisms. Trichoderma asperelloides TSUxPT3.5 produced indole compounds and exhibited antagonistic activity against economically important plant pathogenic fungi, including Curvularia aeria and Corynespora cassiicola, causal agents of leaf spot disease in lettuce. Its biocontrol mechanisms involved competition for nutrients and space, production of cell wall-degrading enzymes (chitinase and cellulase), and emission of volatile organic compounds (VOCs). Among the detected VOCs, 2-ethylhexan-1-ol was the predominant compound. Additionally, 6-pentyl-2H-pyran-2-one, 2,4-Di-tert-butylphenol, and 2-methyl-1-propanol, a well-known antifungal metabolite, were also identified. Application of T. asperelloides TSUxPT3.5 significantly enhanced the growth of mini cos lettuce (Lactuca sativa L.), increasing fresh weight and improving plant vigor compared with the untreated control. In addition, disease severity was markedly reduced in treated plants. These findings demonstrate that the indigenous T. asperelloides TSUxPT3.5 possesses multifunctional antagonistic and plant growth–promoting traits, highlighting its potential as an eco-friendly biological control agent for sustainable lettuce production.

Phytochemical Characterization, Curcuminoid Quantification by HPLC, and Biological Activities of Ethanolic and Aqueous Extracts of Zingiber cassumunar and Curcuma longa Prepared by Ultrasonic-Assisted Extraction

2026-04-01T13:41:07+07:00

Zingiber cassumunar and Curcuma longa are widely used medicinal plants in Southeast Asia, with therapeutic properties attributed to curcuminoids, phenolics, and flavonoids. This study evaluated the effects of solvent type and ultrasonic pretreatment on extraction efficiency and phytochemical composition. Herbal powders were extracted using water and ethanol under ultrasonic conditions. Extraction yields were determined, and phytochemical contents were analyzed using HPLC for curcuminoids and UV–VIS spectrophotometry for total phenolic content (TPC) and total flavonoid content (TFC). The results demonstrated that extraction efficiency was significantly influenced by solvent selection. Ethanolic extraction produced higher yields and significantly greater concentrations of curcuminoids, phenolics, and flavonoids compared to aqueous extraction. Curcuminoids were predominantly detected in ethanolic extracts, with Curcuma longa showing the highest content (13.951% w/w). Similarly, TPC and TFC were markedly higher in ethanolic extracts (412,105.51 mg GAE/kg and 659,001.92 mg QE/kg, respectively), whereas aqueous extracts showed limited recovery due to poor solubility of hydrophobic and semi-polar compounds in water. The enhanced recovery observed with ethanol was attributed to improved solvent penetration and solubilization capacity, further enhanced by ultrasonic cavitation, which promoted cell wall disruption and mass transfer. Additionally, both aqueous and ethanolic extracts of Z. cassumunar and C. longa demonstrated significant anti-inflammatory activity (inhibition of nitric oxide production in LPS-stimulated macrophages) and antioxidant activity (reduction of intracellular ROS), regardless of solvent type. Overall, the combination of ethanol and ultrasonic pretreatment was identified as a more efficient, less solvent-intensive method for maximizing phytochemical extraction than conventional maceration, supporting its application in functional foods, nutraceuticals, and herbal pharmaceuticals.

Numerical Solutions of Fractional Integro-Differential Equations with Weakly Singular Kernel by Using a Hybrid of Block-Pulse Functions and Taylor Polynomials

2026-04-04T10:56:44+07:00

Fractional integro-differential equations (FIDEs) with weakly singular kernels arise in mathematical models of viscoelasticity, anomalous diffusion, and hereditary systems, yet closed-form solutions are rarely attainable. This study proposes a numerical scheme based on a hybrid combination of block-pulse functions and Taylor polynomials for solving both linear and nonlinear FIDEs with weakly singular kernels of the form , formulated within the Caputo fractional derivative framework. The fractional problem is transformed into an equivalent system of algebraic equations by constructing a Riemann–Liouville operational matrix and applying Newton–Cotes collocation nodes, yielding a computationally straightforward solver. Three illustrative examples were examined, including two linear equations with exact solutions and , and one nonlinear equation with an exact solution . The proposed method achieved absolute errors below across all test points using N = 1, 2 block-pulse intervals and M = 2, 3 Taylor polynomial terms. Comparison with the Legendre wavelet method (LWM) demonstrates that the present scheme matches or surpasses LWM accuracy at most collocation points while requiring fewer basis functions. These results confirm that the hybrid block-pulse–Taylor polynomial approach offers a reliable and efficient alternative for solving FIDEs encountered in applied science and engineering.

Facial Emotion Recognition – A Comprehensive Review of Deep Learning and Traditional Learning Approaches with Emerging Challenges

2026-01-31T22:58:01+07:00

In the domains of computer vision and artificial intelligence, facial expression-based emotion recognition (FER) has emerged as a key research area and industrial challenge. Its growing importance is evident in applications such as intelligent surveillance, healthcare monitoring, interactive systems, and mental health assessment. This review systematically examines 95 research papers published between 2014 and 2024, focusing exclusively on studies employing facial imagery for FER. The reviewed works encompass traditional machine learning, deep learning, and hybrid approaches, and analyze their methodologies for preprocessing, data augmentation, and temporal feature extraction. Traditional machine learning methods such as SVM, KNN, and Random Forest achieved average accuracies ranging from 85% to 93%, with the best reaching 99% on the CK+ dataset. Deep learning architectures, including VGG16, ResNet-50, MobileNetV2, and DenseNet-161, reported accuracy improvements of up to 99.5% across benchmark datasets such as FER2013 (35,887 images), CK+, JAFFE, KDEF, and RAF-DB (≈40,000 images). Hybrid models combining CNN feature extraction with classifiers such as SVM and GMM achieved 3–6% improvements in recognition accuracy over standalone CNN or SVM systems, reaching 99.69% on CK+ and 99.53% on JAFFE. By comparing benchmark datasets, algorithms, and performance metrics, this study highlights the significant evolution from handcrafted feature-based systems to fully automated deep learning pipelines. The findings provide a quantitative synthesis of the current state of FER research, offering both newcomers and advanced researchers a comprehensive understanding of the field’s progress, challenges, and future opportunities.

Baseline Assessment of Dairy Cow Welfare Using Animal and Resource-based Indicators in Camarines Sur, Philippines

2026-03-02T07:50:33+07:00

The increasing interest in dairy cattle production raises animal welfare issues that need to be assessed and addressed on the farm. No prior studies have assessed the welfare status of dairy cows in small-hold dairy systems in Camarines Sur, Philippines; hence, this study. On-farm animal- and resource-based indicators were applied using the Welfare Quality® Assessment Protocol for dairy cattle to assess herd-level welfare, with binary data reported as percentages of farms. The welfare criteria for animal-based indicators were assessed by observing the dairy cows on the farm. Sixteen dairy farms were assessed, with a total dairy cow population of 125 (mean: 7.8, median: 7.5, mode: 8). The welfare criteria for resource-based indicators were assessed by evaluating the farm resources. The majority of the dairy farms visited have well-fed dairy cows (87%), with low injury rates (13-20%) and disease rates (0-13%). Additionally, they were provided with a comfortable (76-93%) and sufficient (67-100%) resting area, thereby avoiding agonistic behavior (0%). Some dairy farmers need education on the benefits of clean and accessible water and facilities (73-100%) to improve dairy cow welfare. The majority of dairy farmers considered the importance of comfort, protection from adverse weather (67-87%), and spatial requirements (67-100%). However, grooming facilities were absent, compromising dairy cow welfare. The animal-based indicators on the farm reflected better dairy cow welfare; however, some dairy farmers should improve the resource-based indicators to provide their cows with better welfare.

Study of Surface Water Quality Using Biological Indicators Inside the Ruean Thai Pond Area, Nakhon Si Thammarat Rajabhat University

2026-03-16T23:28:44+07:00

Biological monitoring using macroinvertebrate bioindicators provides an ecologically integrative approach to water quality assessment, capturing cumulative pollution effects that physicochemical measurements alone cannot reflect. This study assessed the surface water quality of the Ruean Thai Pond, a natural spring-fed water body within Nakhon Si Thammarat Rajabhat University, using aquatic macroinvertebrate assemblages. Five sampling stations were established along the pond. Sampling was conducted four times over two months (September–October 2021), totaling 20 station-sampling events. Aquatic insect larvae and associated bioindicator organisms were collected using brick substrates and colander nets, then identified to family level and classified into water quality categories according to the Stream Detective Manual (Green World Foundation, 2018). A total of 13 bioindicator types (morphotypes) representing 5 orders and 9 families were recorded. Ephemeroptera was the most diverse order with 3 families (Leptophlebiidae, Potamanthidae, Baetidae), followed by Gastropoda and Trichoptera (2 families each), and Caridea, Odonata, and Hemiptera (1 family each). "Very clean water" bioindicators — branched-gill and feathered-gill mayfly larvae (Leptophlebiidae, Potamanthidae) and cased and uncased caddisfly larvae (Odontoceridae, Hydropsychidae) — dominated Stations 2–5, accounting for 54–78% of total bioindicator counts. Station 1 (pond entrance station) was the only station classified as "fair–clean," where fair-category organisms (n = 30) outnumbered very-clean-category organisms (n = 0). Four of five stations (80%) were consistently classified as "very clean water" across all sampling rounds, yielding an overall classification of "very clean" for the Ruean Thai Pond. These findings provide a preliminary wet-season biological assessment for university water resource management and for downstream community water-use planning.

Participatory Extension Approaches for Good Manufacturing Practices (GMP) Adoption in Rural Fish Processing: Evidence from Southern Thailand

2026-04-23T18:51:42+07:00

Dry-fermented catfish (pla-duk-ra) is a potential value-added product in Southern Thailand; however, it faces food safety hazards because small-scale backyard operations dominate and lack supporting regulations.

This study evaluated a participatory extension approach to promote Good Manufacturing Practices (GMP) within the Banphabontam Agricultural Innovation Community Enterprise (BAICE). The original GMP evaluation involved the design of facilities, control of equipment, process operations, cleanliness and sanitation, maintenance, and personnel practices. None of the six domains achieved a score of 60%, indicating that all areas remained below the minimum acceptable level. Participatory extension led to the implementation of various improvements, such as facility redesign, workflow zoning, hygiene training, and basic sanitation systems. Following the upgrade, BAICE achieved GMP certification and formal recognition as a licensed food producer. The refined layout separated wet and dry zones, improved drainage and pest control, and established distinct storage and preparation spaces. These interventions increased workers’ hygiene awareness and responsibility without altering the sensory characteristics or cultural identity of pla-duk-ra. This initiative exemplifies community-driven food safety enhancement through participatory extension. It demonstrates how scientific principles and traditional knowledge can align to improve product quality, regulatory compliance, and market potential. Findings from the BAICE case provide practical, context-specific evidence that may inform GMP implementation and rural food system improvement in similar community-based food enterprises. The results align with national agendas to support the development of sustainable food and highlight that extension work plays a crucial role in making traditional foods safe, competitive, and sustainable products.

Analysis of Electromagnetic Shielding Effectiveness of Multilayer to Protect Against Lightning Strike Effect on Aerospace Applications

2026-01-04T21:54:14+07:00

When lightning strikes in aerospace applications, the structural integrity and electrical systems of aircraft are put at great risk. Lightning creates very powerful electromagnetic pulses that conventional aluminium structurescan't handle. This work examines how well mesh topologies protect multilayer metal matrix composites (MMCs) that include conductive and ceramic reinforcements, such as Al₂O₃, SiC, and fly ash, within an Al6061 matrix. The composite structure has layers of metallic mesh coated with nickel to improve electromagnetic shielding and heat dissipation further. This investigation presents a theoretical and computational analysis of the efficacy of electromagnetic shielding, utilising Schelkunoff’s theory in conjunction with a transmission-line model to evaluate multilayer MMC mesh structures. The suggested multilayer Al6061-based metal matrix composite (MMC) structures reinforced with SiC, Al₂O₃, and fly ash exhibit improved electromagnetic shielding effectiveness in the X-band frequency range (8-12 GHz). The shielding performance is around 96.12dB better than that of regular aluminium structures due to improved absorption and impedance mismatch. This work demonstrates a useful way to build sophisticated aeronautical structures utilising lightweight, highly effective shielding materials.