Infrastructure development can significantly affect land use change in peri-urban areas. This research evaluates land use dynamics in Jatinangor and surrounding areas during the construction of the Cileunyi–Sumedang–Dawuan (Cisumdawu) toll road between 2014 and 2022 and its implications for regional landscape development. Landsat 8 imagery from 2014 and 2022 was analyzed using remote sensing and GIS, including image pre-processing, supervised classification with the Maximum Likelihood Classification, and Kappa coefficient accuracy test. The resulting land use maps were compared to quantify spatial and temporal changes. The forest area decreased from 20,360.37 ha to 15,268.55 ha, whereas the residential and built-up areas increased from 7,502.09 ha to 10,033.35 ha. The area classified as paddy field/wetland increased from 7,679.87 ha to 8,355.14 ha, whereas mixed gardens and shrubs decreased from 2,121.16 ha to 1,772.10 ha. A 2,227.77 ha plantation area was mapped in 2022. Significant land use changes were observed in Jatinangor, Cileunyi, Rancaekek, Cimanggung, and surrounding areas during residential, educational, industrial, and infrastructure development. Classification accuracy was high, with kappa coefficients of 0.81 (2014) and 0.88 (2022). These findings provide valuable information to support sustainable land use planning, environmental management, and regional development in rapidly developing peri-urban areas.
Lack of comparative phytochemical data on key curcuminoids hinders the standardization and quality control of Curcuma -based commercial products. This study identified and quantified three major curcuminoids—bisdemethoxycurcumin (BDMC), demethoxycurcumin (DMC), and curcumin (CM)—across greenhouse-cultivated Curcuma longa , C. xanthorrhiza , and C. caesia . Dried rhizome powders were extracted with methanol using the Soxhlet method. Thin-layer chromatography (TLC; ethyl acetate:chloroform, 6:4) was employed for qualitative fingerprinting under 254 nm UV light, while high-performance liquid chromatography with diode array detection (HPLC-DAD) was optimized for quantitative analysis. All three species contained BDMC, DMC, and CM, but exhibited distinct accumulation patterns. Curcuma longa demonstrated the highest total curcuminoid content, with BDMC as the predominant compound (0.425 mg/g; 0.0425%), followed by DMC (0.142 mg/g; 0.0142%) and CM (0.062 mg/g; 0.0062%). Curcuma xanthorrhiza was characterized by a strong dominance of DMC (0.481 mg/g; 0.0481%), whereas C. caesia yielded only trace amounts of all three compounds (BDMC: 0.040 mg/g; DMC: 0.018 mg/g; CM: 0.015 mg/g). These species-specific variations highlight underlying differences in biosynthetic pathways and enzymatic activity. In conclusion, HPLC-DAD provides a highly reliable method for establishing phytochemical fingerprints, supporting species identification, quality control, and future pharmaceutical standardization of Curcuma species.
The present work investigates bacterial pathogens associated with infections in Clerodendrum inerme (L.) and evaluates their possible role in disease development using biochemical, molecular, and artificial intelligence (AI)-based approaches. Symptomatic leaves of C. inerme were selected, and bacterial isolates were cultured under laboratory conditions. The isolates were determined using Gram staining, motility, catalase, indole, methyl red,citrate utilization and carbohydrate fermentation. The molecular identification involved amplification of the 16S rRNA gene using PCR to obtain amplicons with a size of about 1500 bp. The biochemical and molecular analysis results were then used as input data for the AI models in predicting their ability to classify bacterial isolates depending on their phytopathogenicity. The biochemical and metabolic profiles showed that the isolates were gram-negative, non-motile, and catalase-positive rods. Predictive bacterial isolates were evaluated for their capacity to classify the isolates based on these parameters, although their accuracy in disease prediction can only be validated by experimentation since the validity of such models hinges on proper validation of the models. This method can also help future plant disease diagnosis and the development of sustainable strategies for protecting medicinal plants.
Recreational activities can influence river water quality through physical disturbance, sediment resuspension, chemical and microbial contaminants. This study investigated the associations between recreational intensity and physicochemical and microbial water quality in tropical recreational rivers in Kelantan, Malaysia. Water samples were collected over three consecutive months from upstream reference points and downstream recreational areas. Dissolved oxygen (DO), biochemical oxygen demand (BOD), chemical oxygen demand (COD), ammoniacal nitrogen (NH₃-N), total suspended solids (TSS), pH and total coliform were analysed. The Malaysian Department of Environment Water Quality Index (WQI) was calculated, and Spearman’s rank correlation examined relationships between visitor intensity and water quality. Upstream WQI values ranged from 86 to 94, while downstream values ranged from 86 to 93. All observations were classified as Class I or Class II and reported as clean. Upstream to downstream showed no consistent WQI deterioration. Visitor intensity was not significantly associated with overall WQI. However, total coliform showed a strong, statistically significant negative relationship with visitor intensity (ρ = −0.793, p = 0.002), indicating lower counts at higher visitor numbers. Overall, recreational activities did not severely degrade measured water quality during the study period. Continued routine monitoring is recommended to support sustainable management of tropical recreational rivers.
This study investigates the synthesis of activated carbon (AC) from waste PET bottles and evaluates its performance for COD reduction in textile wastewater. PET waste was carbonized and chemically activated using potassium hydroxide (KOH) at a PET:KOH ratio of 1:2, producing a black carbonaceous material with a 30% mass yield. Batch experiments were conducted using AC dosages of 1–5 g and contact times of 60–180 min. The highest COD reduction of 82.62% was achieved using 5 g of AC at a contact time of 180 min. The incorporation of UV irradiation further enhanced COD reduction to 93.81%, indicating improved treatment performance in the combined AC–UV system. Scanning electron microscopy (SEM) revealed an irregular surface morphology with a porous interconnected framework. The apparent pore diameters of pristine AC ranged from 7.9 to 25.5 µm, while AC after adsorption exhibited a narrower range of 13.7–21.9 µm. Under UV-assisted treatment, a broader apparent pore size distribution of 6.6–38.96 µm was observed, suggesting changes in the surface morphology following the combined treatment process. Overall, PET-derived AC demonstrates strong potential as a sustainable and low-cost adsorbent for textile wastewater treatment while supporting PET waste valorization and environmental remediation.
