Vietnam Journal of Agricultural Sciences

This study aimed to identify suitable composting materials for producing high-quality vermicompost leachate (VL) and to evaluate its effects on cucumber plants. The research consisted of two experiments. The experiment 1 investigated the effects of composting materials on vermicomposting efficiency. The experiment 2 evaluated the effects of VL concentrations on the growth and yield of cucumber. The experiment 1 consisted of three composting treatments using different substrates, namely cow manure combined with water spinach, household organic waste, and coatbutton flowers (Bidens pilosa L.). The results showed that the treatment using cow manure combined with water spinach (VL1) had the best performance, generating VL with the highest electrical conductivity (EC) (1958 µS cm-¹) and the greatest number of adult earthworms after composting (494 individuals). The experiment 2 using VL1-VL included treatments of C0-1 (applied water only, NF), C0-2 (applied fertilizer according to the recommended cultivation protocol, CF), C1 (applied 10% VL), C2 (applied 15% VL), and C3 (applied 20% VL). The results showed that increasing the concentration of the VL1 vermicompost leachate significantly improved growth parameters, including plant height, stem diameter, leaf area, dry biomass, and yield. Notably, the treatment with 20% VL1-VL produced growth and yield values comparable to the control treatment using 100% chemical fertilizer. These findings contribute to promoting the conversion of agricultural by-products into useful inputs for crop production, thereby helping to reduce organic waste and environmental pollution.

Rice (Oryza sativa L.) is a major staple crop whose production is increasingly constrained by environmental stresses. Therefore, there is a growing need for innovative strategies to enhance rice productivity sustainably. Silver nanoparticles (AgNPs) has emerged as a promising approach to improve stress tolerance and crop performance while potentially reducing fertilizer inputs and environmental impacts. In this study, IR64 rice seedlings were exposed to 0-100ppm AgNPs to assess their effects on free amino acid accumulation and metal uptake using high-performance liquid chromatography and inductively coupled plasma mass spectrometry. The responses were both concentration- and tissue-dependent, with increased total and non-essential amino acid levels but reduced essential amino acids at higher AgNP concentrations. The highest total amino acid concentration was obtained in rice plants grown in the 50 and 100ppm AgNP treatments, which reached approximately 22.8 mg g-1 plant dry weight. The highest amino acid content was detected in the serine family, which reached approximately 10 mg g-1, while the aromatic family produced the lowest (approximately 0.76 mg g-1). AgNP exposure reshaped metal uptake and partitioning in a metal- and tissue-specific manner, promoting metal sequestration in roots while suppressing root-to-shoot translocation. Calcium was the most abundant macroelement nutrient found in the roots of the plants. These findings provide insight into how AgNPs modulate amino acid metabolism and metal accumulation in rice, highlighting both their potential and limitations for agricultural applications.

This study was conducted to determine the probiotic characteristics of lactic acid bacteria isolated from various sources. A total of 282 LAB strains were isolated from 400 samples of fermented foods, chicken and swine intestines, and raw milk. Among these, 92 isolates (32.62%) exhibited inhibitory activity against enterotoxigenic Escherichia coli, and 10 strains were selected for further characterization due to their strong antibacterial abilities. MALDI-TOF MS revealed that the selected isolates belonged to Lactiplantibacillus plantarum, Levilactobacillus brevis, Pediococcus acidilactici, Pediococcus pentosaceus, and Enterococcus faecium. They were non-hemolytic and tolerant to acidic conditions and bile salts, with high survival rates (48.48-97.67%), auto-aggregation abilities (41.96-67.52%), and co-aggregation abilities (25.85-45.06%). These findings identified several LAB isolates with promising in vitro probiotic-related properties. However, further genomic, biosafety, and in vivo studies are required before practical applications.

This study evaluated the antibacterial and bactericidal activities of fresh aqueous extracts prepared from guava (Psidium guajava) leaves and fruits against two important freshwater fish pathogens, Edwardsiella ictaluri and Flavobacterium columnare. For each bacterial species, three strains were revived from the bacterial collection maintained at the Faculty of Fisheries, Vietnam National University of Agriculture. They were confirmed by colony morphology, biochemical characteristics, and species-specific polymerase chain reaction (PCR). Fresh extracts were obtained by mechanically pressing 100g of guava leaves or fruits with 200mL of distilled water, yielding 163mL and 186mL of extract, respectively. Antibacterial activity was assessed using the agar well diffusion method. The inhibition zones produced by the fruit extract against E. ictaluri and F. columnare measured 21.4mm and 25.8mm, respectively, and were significantly smaller than those produced by the leaf extract (26.7mm and 30.8mm, respectively). Both extracts exhibited strong antibacterial activity, comparable to that of oxytetracycline (30µg). The minimum bactericidal concentrations (MBCs) of the fruit extract against E. ictaluri and F. columnare were 1:8 (12.5%) and 1:32 (3.13%), respectively. In contrast, the leaf extract showed bactericidal activity at lower concentrations, with MBCs of 1:16 (6.25%) for E. ictaluri and 1:64 (1.57%) for F. columnare. Overall, these findings demonstrate that fresh guava leaf extract, in particular, possesses strong antibacterial and bactericidal activities and has considerable potential for controlling bacterial diseases caused by E. ictaluri and F. columnare in freshwater aquaculture.

In the context of precision machining, predicting the remaining useful life (RUL) of cutting tools plays a critical role in optimizing production processes and reducing maintenance costs. This study proposed and developed four machine learning models for predicting tool RUL in milling operations, namely exponential Gaussian process regression (GPR), fine tree, linear regression, and quadratic support vector machine (SVM). The input dataset was constructed from sensor signals and key process parameters, including three-axis vibrations (vibration_x, vibration_y, vibration_z), acoustic emission signals, spindle load, cutting speed, feed rate, material hardness, and tool wear. The models were trained and evaluated using standard performance metrics, namely the coefficient of determination (R²), root mean square error (RMSE), and mean absolute error (MAE). Experimental results indicated that the linear regression model outperformed the other models, achieving an R² value of 1 and extremely low prediction errors (RMSE = 4.1 × 10⁻⁸; MAE = 3.2 × 10⁻⁸). The findings suggest that the proposed framework is both effective and highly applicable for tool condition monitoring, while also supporting the optimization of cutting parameters in milling processes.

In the context of the rapid development of Industry 4.0, the integration of industrial robots with machine vision technology is becoming an inevitable trend to enhance the level of automation in manufacturing. This paper presents the results of the control and implementation of a three-axis Cartesian robot integrated with a machine vision system for object sorting on a conveyor belt. The system was designed with a working area of ​​400 × 700 × 150mm and was capable of recognizing and sorting phone chargers based on surface print quality through image processing algorithms. Object tracking was employed to enable the robot to perform picking operations under a continuously moving conveyor belt. The experimental results showed that the system achieved a defect rejection rate of 96-98% under the tested conditions, demonstrating stable operation and its potential for practical applications. The research makes the contribution of a proposed integrated solution suitable for small and medium-scale sorting applications.

Hyacinth beans were used for developing a functional yoghurt-like product with a high level of gamma aminobutyric acid (GABA). Germinated hyacinth bean extract was fermented with three different yoghurt cultures, namely (1) Lyofast Y 258 A and (2) Lyofast Y 450 B, containing a combination of S. thermophilus and Lactobacillus delbrueckii ssp. bulgaricus, and (3) XPL-20 containing Lc. lactis ssp. cremoris, Lc. lactis ssp. lactis, and S. thermophilus, incubated to pH 4.5, and then stored at 4-6℃ for 21 days. The variations in GABA and phytic acid levels during cold storage were evaluated. The type of culture and storage time significantly influenced the GABA and phytic acid levels. The mixture of Lactococcus lactis ssp. cremoris, Lc. lactis ssp. lactis, and Streptococcus thermophilus produced a yoghurt-like product with the highest level of GABA (2.2 mg/g DM). In addition, the levels of GABA and phytic acid significantly decreased during cold storage. This study provides a foundation for the development of yoghurt-like products from water hyacinth beans with enhanced GABA content.

Few studies have examined the comprehensive factors affecting consumers’ behaviors toward sustainable fashion, especially in developing countries. This study identified the factors affecting intention to purchase sustainable fashion among Generation Z in Vietnam, a demographic segment playing a pivotal role in shaping modern consumer trends. Data were collected from 216 respondents through an online survey and analyzed using multiple linear regression. The findings revealed that environmental concern plays a crucial role in motivating the young generation to purchase sustainable fashion. Also, awareness of sustainable fashion significantly and positively affects the tendency to engage in sustainable purchasing. In contrast, price sensitivity negatively impacts purchase decisions, indicating that financial barriers remain a major obstacle to sustainable consumption. Gender and education were also associated with purchasing behaviors toward sustainable fashion. Moreover, the high shopping frequency reflects a gap between current consumer behaviors and sustainability goals. Based on these results, this study recommends targeted policies to enhance public awareness and facilitate consumer intention to purchase sustainable fashion. These include educational campaigns, financial support initiatives, and eco-labeling strategies to promote responsible consumption habits among the youth in the future.

This study examined the influence of digital human capital on organic fertilizer adoption among vegetable-farming households in Phuc Loc commune, Hanoi, Vietnam. Employing a fractional logit model, the study analyzed the determinants of adoption intensity, measured as the share of organic fertilizer expenditure in total fertilizer costs. Findings revealed that digital information utilization and learning capacity were primary drivers, significantly reducing information asymmetry and technical risks. The results suggest that promoting green agricultural practices requires systematic investment in the farmers’ human capital, particularly digital skills.

African swine fever (ASF) continues to cause billions of dollars in global losses each year, disrupting pork supply chains and food security across Asia. This review analyzes the persistent gap between laboratory success and field performance of African swine fever vaccines, emphasizing live attenuated vaccines (LAVs) and hybrid next-generation platforms. It synthesizes recent findings on gene-deleted LAVs, encapsulin-based subunits, and mRNA or nanoparticle boosters that collectively aim to balance efficacy, safety, and DIVA compatibility. Key challenges include inconsistent protective efficacy, undefined immune correlates, and biosafety risks such as virulence reversion or recombination. Manufacturing constraints—dependence on porcine cell substrates, quality assurance, and scalability—compound system-level obstacles related to fragmented regulation and limited pharmacovigilance. Vietnam’s supervised rollout of NAVET-ASFVAC and AVAC ASF LIVE, with millions of doses deployed under strict monitoring, exemplifies a risk-managed model for national implementation. Looking ahead, coordinated regional governance, standardized challenge models, and harmonized regulatory frameworks are essential to translate next-generation hybrid vaccines into safe, scalable, and equitable ASF control strategies.

The use of plant-based feed additives (PBFAs) in Nile tilapia aquaculture is gaining attention as a sustainable alternative to synthetic inputs, with reported benefits for growth, immunity, and disease resistance. This review synthesizes evidence on PBFAs, including crude powders, extracts, essential oils, and purified bioactives, from plants such as garlic, ginger, aloe vera, and moringa. Their effects involve interconnected pathways, including immunomodulation, antioxidant defense, antimicrobial activity, host–microbiome modulation, molecular signaling, and reproductive or endocrine regulation, thereby supporting growth performance, feed efficiency, physiological resilience, reproductive indices, and survival after pathogen challenge. However, commercial adoption is constrained by phytochemical variability, limited standardization, incomplete understanding of species- and context-dependent responses, and regulatory gaps. Future work should prioritize mechanistic validation, optimized formulation, and practical delivery strategies for sustainable Nile tilapia production.