Shallots (Allium cepa L. var. aggregatum) are an important horticultural commodity in Indonesia whose production is highly susceptible to drought stress. This study aims to evaluate the effect of salicylic acid (SA) induction on improving morphological traits and yield components traits under drought conditions and to analyze genetic variability in five shallot varieties. The experimental design used was a Completely Randomized Design-Split Plot Design with 3 replications. The main plot treatment was the variety factor (V) and the subplot factor was the salicylic acid concentration factor (S). The V factor consisted of 5 varieties, namely V1 = Bima Brebes, V2 = Bima Juna, V3 = Tajuk, V4 = Nganjuk Bauci and V5 = Superphilip. While the S factor consisted of 2 levels, namely S0 = without SA (control), and S1 = 1 mM salicylic acid. Each treatment combination was planted under drought stress conditions. The parameters observed included Leaf length , Leaf Number/clump/, dry leaf weight, dry root weight, bulbs number, dry bulbs weight. And dry bulbs weight/clump. Data analysis was carried out using ANOVA and continued with Duncan's advanced test at the 5% level to determine differences between treatments, in addition to calculations of genetic and phenotypic variance, genetic diversity coefficients and broad-sense heritability estimates. The results of the study confirmed that salicylic acid can improve morphological traits and yield components in all varieties. The V1 variety (Bima Brebes) resulting from SA induction tends to have the best improvement in both morphology and yield components. The genetic diversity coefficient has a value ranging from 8.32-31.66%, where high values of Genetic Variation Coefficient (GVC) (>20%) are found in the traits of leaf number/clump, dry leaf weight, dry root weight, bulbs number, dry bulbs weight and dry bulbs weight/clump. Traits with high GVC values can possibly be used as selection parameters. In addition, high broad-sense heritability values (>50%) were found for the Leaf Number/clump, bulbs dry weight, and bulbs dry weight/clump, with estimated values of 52.37%, 50.67%, and 60.19%, respectively. The high broad-sense heritability estimates indicate that these three traits are predominantly genetically controlled.
Altitude-associated changes in microclimate may influence leaf gas exchange and water relations in rice. This study evaluated transpiration rate and stomatal conductance of rice (Oryza sativa L. cv. Inpari Sembilan) along an altitudinal gradient in South Tapanuli Regency and Padangsidimpuan City, North Sumatra, Indonesia. Measurements were conducted at six locations ranging from 316 to 647 m above sea level, with 20 plants sampled at each location. Microclimatic variables, including air and leaf temperatures, relative humidity, photosynthetically active radiation (PAR), and leaf-to-air vapor pressure deficit (VPD), together with transpiration rate (E) and stomatal conductance (gs), were measured on fully expanded flag leaves using a portable photosynthesis system. Transpiration rate and stomatal conductance showed a non-linear pattern along the elevation gradient, with the highest values observed at intermediate elevations. The highest E (0.886 mmol H₂O m⁻² s⁻¹) and gs (0.055 mol m⁻² s⁻¹) were recorded at Sibong-bong (393 m asl), whereas lower values occurred at both lower and higher elevations. Mean VPD decreased from 2.37 kPa at 316 m to 1.45 kPa at 647 m asl. Quadratic regression indicated a relatively weak relationship between elevation and transpiration rate (R² = 0.218), suggesting that elevation alone explained only a limited proportion of the observed variation. Overall, rice leaf gas exchange varied considerably along the altitudinal gradient, with intermediate-elevation sites showing more favorable conditions for transpiration and stomatal conductance. These findings indicate that local microclimatic factors, particularly temperature, humidity, radiation, and VPD, should be considered together with elevation when evaluating physiological responses of rice across different agroecological environments.
Optimizing growing media quality is essential for vegetative growth of geranium (Pelargonium hortorum), particularly under limited substrate volume in pot cultivation. Rice husk-based substrates are widely used in Indonesia due to their availability and low cost; however, their high C/N ratio may induce nitrogen immobilization and restrict plant growth. In addition, eco-enzyme application has the potential to accelerate organic matter decomposition and nutrient mineralization, thereby reducing the adverse effects of high C/N ratios and improving nitrogen availability for plant growth. A factorial completely randomized design was used to evaluate three eco-enzyme concentrations (0, 15, and 30 mL L⁻¹) and three substrate compositions of cocopeat, goat manure, and rice husk biochar (1:1:0, 1:1:1, and 1:1:2). Data were analyzed using ANOVA and Tukey’s HSD test (p ≤ 0.05). Increasing the proportion of rice husk biochar reduced bulk density and increased total porosity and air space relative to lower biochar proportions, whereas water-holding capacity decreased. Eco-enzyme application accelerated organic matter decomposition, as indicated by reduced organic matter content and C/N ratio, while stabilizing growing media pH within the near-neutral range by the end of the experiment. Application of 30 mL L⁻¹ eco-enzyme to the medium balanced composition (1:1:1) increased plant height, number of leaves, leaf area, dry weight, and water use efficiency up to 55.2% compared to the control media. Thus, the experiment proves the synergistic effect of eco-enzyme treatment and organic substrate composition on improving the quality of the growing media and promoting vegetative growth in a limited amount of substrate.
Land productivity assessment is important for understanding variation in Salak Sidempuan production under different soil and climatic conditions. This study aimed to classify Salak Sidempuan productivty using soil fertility and annual rainfall data and to compare the performance of five machine learning algorithms. Data from 500 Salak Sidempuan tree observations were collected from Marancar, West Angkola, and South Angkola, South Tapanuli, Indonesia. The predictor variables consisted of soil pH, organic carbon, nitrogen, phosphorus, potassium, and annual rainfall, while productivity was divided into low, moderate, and high classes. Decision Tree, Random Forest, Support Vector Machine, XGBoost, and LightGBM were optimized using 5-fold cross-validation on the training dataset and evaluated using an independent testing dataset. Among the evaluated models, Random Forest achieved the highest performance, with an accuracy of 66.40%, precision of 67.01%, recall of 66.47%, and F1-score of 66.46%. Feature importance analysis showed that annual rainfall had the highest relative contribution (24.8%), followed by C-organic (22.1%) and nitrogen (17.6%), while potassium, phosphorus, and soil pH contributed 13.9%, 11.8%, and 9.8%, respectively. These findings indicate that soil fertility and rainfall variables provide useful information for distinguishing Salak Sidempuan productivity classes. However, the moderate classification performance indicates that the selected variables do not fully explain productivity variation. The results therefore provide an initial data-driven assessment of Salak Sidempuan productivity based on the environmental variables included in the study.
Maize and chili polyculture systems have the potential to enhance agroecosystem productivity, but their effectiveness is strongly influenced by the dynamics of arthropods, including phytophages, predators, parasitoids, decomposers, and pollinators. This study inventoried arthropod communities by analyzing the abundance of ecological groups and calculating diversity, evenness, and dominance index. The aim was to provide an ecological foundation to strengthen integrated pest management and support the implementation of sustainable agriculture in line with Asta Cita's development direction. The research was conducted at the Agro Training Centre, Faculty of Agriculture, Sriwijaya University. To obtain samples in the maize–chili polyculture system, several types of traps were used, including yellow sticky traps, methyl eugenol traps, pitfall traps, pan traps, light traps, sweep nets, and visual traps, which were placed in each planting bed. All traps except the light trap were installed between 06:00 and 07:00 and operated for 24 hours, except for the light trap, which was installed at 18:00 and operated for 12 hours. The diversity index obtained was H' = 1.15, indicating a medium category; the evenness value (E = 0.48) showed that species distribution was uneven; and the dominance index (D = 0.30) suggested the presence of a sub-dominant species. The most frequently captured species was Bactrocera sp 1, belonging to the order Diptera and functioning as a phytophage. Clustering analysis indicated a correlation between Bactrocera sp 1 and Bactrocera sp 2. Overall, the dominant arthropod functional group in the maize–chili polyculture system was phytophagous species.
