This research aims to increase the effectiveness of adding Potassium Permanganate (KMnO4) as an oxidizer in the process of making bamboo charcoal briquettes. The research methodology includes several stages, starting from preparing bamboo waste raw materials, the carbonization process to produce charcoal, to printing briquettes with varying concentrations of KMnO4 (0, 5, 7.5 and 10%). Tests carried out include analysis of heating value, combustion rate, density, air content, compressive strength, ignition duration and ash content to determine the physical and chemical characteristics of the briquettes. The results showed that the addition of KMnO4 had a significant effect on the parameters tested. A KMnO4 concentration of 10% speeds up the ignition time of briquettes significantly to 15 seconds, but results in a decrease in the highest heating value from 5382 cal/g (at 0%) to 5131 cal/g and an increase in the highest ash content to 16.7 g. Treatment with a concentration of 5% showed the most optimal compressive strength value. The use of KMnO4 is effective in accelerating initial ignition but can reduce several other essential qualities such as heating value and ash content. Determining the right concentration is crucial to producing briquettes with balanced performance.
Conventional hydroponic fodder production relies on manual, non-predictive monitoring, complicating feed planning. This study presents a low-cost edge-computing platform for hydroponic fodder built on a repurposed Linux set-top box (STB), integrated with an environment-driven growth model through a Hardware-in-the-Loop (HIL) scheme. The STB edge node hosts the MQTT broker, time-series database, and monitoring dashboard, while temperature and light are acquired in real time by SHT30 and BH1750 sensors via an ESP32. No physical load cell is used; biomass is therefore simulated by a logistic ordinary differential equation (ODE) with temperature-dependent rate r(T) and light-dependent carrying capacity K(L), driven by real environmental data recorded over a single 10-day cultivation cycle (20-29 June 2026, with interpolated gaps flagged). The model is calibrated to two empirical anchor points (1 kg at day 0, 13 kg reference at day 10); this agreement is reported as a calibration/consistency check rather than out-of-sample predictive validation. Sensitivity analysis shows the endpoint is dominated by carrying capacity (S = 0.96), and a fourth-order Runge-Kutta solver deviates only 0.007 kg from a reference integrator. Crucially, the complete model is executed on the STB itself using only the Python standard library: a full 10-day simulation completes in 46.6 ms (43.7 microseconds per RK4 step) within 15 MB of RAM at a stable 50 C, demonstrating that the edge node alone suffices without cloud computation.
Red dragon fruit (Hylocereus polyrhizus) peel was an underutilized agro-industrial byproduct with high potential as a functional food ingredient due to its pigments and bioactive compounds; however, processing challenges limited its application. This study analyzed the effects of blanching and slicing pretreatments on the physical and functional properties of red dragon fruit peel flour produced using freeze drying. The results showed that the moisture content ranged from 7–12%, meeting standard flour requirements, and was not significantly affected by the treatments, confirming the effectiveness of freeze drying in moisture removal. Yield was significantly influenced by the pretreatments, with the highest value obtained in the blanching–sliced treatment (1.66%) and the lowest in the non-blanching–non-sliced treatment (0.91%). Color characteristics were also significantly affected, where blanching decreased lightness (L*) but increased redness (a*). The highest a* value (32.04) was observed in the blanching–sliced treatment, indicating improved betalain pigment stability due to enzyme inactivation. In contrast, water holding capacity (1.25–3.13%), oil holding capacity (21.17–37.13%), and swelling power (0.92–0.98 g/g) did not differ significantly among treatments. These findings indicated that the combination of blanching and slicing was the most effective pretreatment for enhancing yield and maintaining color stability. The study demonstrated the potential of freeze-dried dragon fruit peel flour as a functional food ingredient and supported the valorization of agricultural waste into value-added products.
Cherry tomato (Solanum lycopersicum L. var. cerasiforme) is a highly perishable horticultural commodity that requires proper postharvest handling to maintain quality and extend shelf life. This study evaluated the effects of ozone pretreatment (ozone gas and ozonated water) combined with hypobaric storage at pressures of 26, 64, and 101 kPa on the quality of cherry tomatoes during storage. Observed parameters included color change (?E), total soluble solids (TSS), moisture content, vitamin C and total fungal count. Color measurement was performed using a computer vision method based on the CIE L*, a*, b* color system, TSS was measured using a refractometer, moisture content using the oven method, and vitamin C using UV-Vis spectrophotometry. Two-way ANOVA showed that ozone pretreatment and hypobaric pressure had no significant effect on color change and moisture content (p>0.05). However, hypobaric pressure significantly affected TSS (p<0.05), with 26 kPa maintaining the highest TSS value (5.06 °Brix). Both ozone pretreatment and storage pressure had highly significant effects on vitamin C content (p<0.05). Ozone gas and ozonated water treatments retained higher vitamin C contents (43.99 and 42.13 mg/100 g, respectively) than the control (34.62 mg/100 g). Similarly, the highest vitamin C content was observed at 26 kPa (47.21 mg/100 g). Both treatment factors also significantly reduced fungal growth during storage (p<0.05). Tukey’s post hoc test showed that ozone gas pretreatment at 26 kPa resulted in the lowest total fungal colony count. The combination of ozone pretreatment and hypobaric storage 26 kPa has the potential to be an effective postharvest technology for maintaining nutritional quality and extending the shelf life of cherry tomatoes during storage.
This study aims to formulate fruit detachment dynamics as the core concept for designing a selective vibratory mechanical harvester for robusta coffee. Plant-level average fruit removal force (FRF) and fruit mass data from five coffee plants were analysed for three maturity classes identified by color: red, orange, and green. An empirical FRF model was built using maturity code and fruit mass as predictors, after which a dynamic force model based on forced vibration, Fd = mA(2?f)², was used to simulate detachment behavior under different operating conditions. Model validation employed goodness-of-fit statistics and leave-one-out cross-validation, while selective harvesting performance was predicted through maturity-specific detachment probability curves. Mean FRF increased consistently with decreasing maturity, from 3.532 N in red fruits to 5.966 N in orange fruits and 8.034 N in green fruits, whereas fruit mass varied only slightly among stages. The empirical model showed high predictive accuracy (R² = 0.997; RMSE = 0.095 N), indicating that maturity status dominated the FRF response. Simulation results demonstrated that, at a vibration amplitude of 3 mm, equivalent threshold frequencies were approximately 99.9 Hz for red fruits, 129.9 Hz for orange fruits, and 151.3 Hz for green fruits. An optimum selective operating window of 3.60-5.91 N, equivalent to 101.0-129.4 Hz, was identified for maximizing ripe-fruit recovery while maintaining high harvest purity.
This study conducts a comparative performance evaluation of lightweight and medium variants of YOLO models, specifically YOLOv8, YOLOv10, and YOLOv12, for real-time chili ripeness detection using digital image analysis. A dataset comprising 1,450 images of Baskara chili peppers at four ripeness stages, namely green, yellow, orange, and red, was collected using a conveyor-based imaging system under controlled lighting conditions. The images were manually annotated with bounding boxes and divided into training, validation, and test sets in proportions of 73.1%, 18.3%, and 8.6%, respectively. All models were trained with identical parameters to ensure a fair comparison and evaluated using precision, recall, F1-score, mean Average Precision, and computational efficiency metrics. The results indicate that YOLOv12s achieved the highest overall performance, with a precision of 0.918, recall of 0.938, mAP@0.5 of 0.960, mAP@0.5:0.95 of 0.865, F1-score of 0.927, 21.2 GFLOPs, and an inference time of 3.1 ms. Evaluation on 125 additional images confirmed robust generalization, with a precision of 0.908, recall of 0.923, mAP@0.5 of 0.931, and mAP@0.5:0.95 of 0.849. Class-wise analysis showed that the green class achieved the highest detection accuracy, while the orange class was the most challenging due to visual similarity with adjacent ripeness stages. Overall, YOLOv12s achieved an optimal balance between detection accuracy and computational efficiency, making it promising for real-time chili sorting in smart agriculture applications.
Vertical farming is a crop cultivation system with a tiered planting medium configuration designed to optimize accessibility, maintenance, and harvesting efficiency. The implementation of modern technology based on environmental sensors allows real-time monitoring of microclimate parameters to support precise irrigation management through estimation of evapotranspiration rates (ETo). This study aims to evaluate and estimate ETo values in vertical farming systems using a DNN architecture. Estimation is carried out through Python programming language simulations on the Google Colaboratory platform using a pre-trained DNN model (4 hidden layers) based on input data of average temperature (Tmean) and average relative humidity (RHmean) over a 4-hours duration. The implemented DNN model was validated against actual ETo data in previous studies to ensure the reliability of predictions. The results show that DNN-based evapotranspiration values are significantly influenced by temperature and relative humidity factors. Furthermore, evapotranspiration values, plant growth phases, and planting area are variables needed to calculate irrigation water requirements in the vegetative, generative, and final phases, which require 6.41 liters, 22.85 liters, and 21.73 liters, respectively. Thus, the use of the validated DNN model is proven to be a reliable predictive instrument for precisely determining crop water requirements to achieve more efficient irrigation management.
Oil palm is an important commodity in the industrial sector. Konawe Selatan Regency has begun to develop oil palm plantations in various regions, but land suitability analysis with a spatial approach has never been carried out. This study is important to support oil palm cultivation by taking into account environmental characteristics. This study utilizes Geographic Information Systems using parameters of temperature, rainfall, dry month, soil texture, soil depth, soil pH, slope, and erosion. Konawe Selatan Regency has oil palm suitability that is classified as very suitable (S1) 0.04%, quite suitable (S2) 40.41%, marginally suitable (S3) 31.19%, and not suitable (N) 28.36%. The limiting factors in this area are hotter and colder temperatures and steep slopes. Oil palm development must be carried out with primary consideration in conservation areas, considering that Konawe Selatan Regency has agronomic and ecological limitations.
Sugarcane bagasse is an abundant agricultural by-product in Indonesia due to high sugarcane production, particularly in major producing provinces. The limited utilization of bagasse may cause environmental problems, highlighting the need for sustainable waste management strategies. This study aimed to evaluate the potential of sugarcane bagasse as a raw material for biobriquettes and to analyze the effect of different charcoal binder compositions on the physical and mechanical properties of the briquettes. The research was conducted at the Biosystems Engineering Laboratory using carbonized sugarcane bagasse (biochar) molded into briquettes with a pressing pressure of 50 kg/cm². Four composition ratios were applied, namely 45:5, 46:4, 47:3, and 48:2 (g of charcoal : g of tapioca binder). The briquettes were evaluated based on density, dimensional stability, moisture content, mechanical strength using a drop test, and combustion rate. The results showed that briquettes with a composition of 45 g charcoal and 5 g binder exhibited the highest density (approximately 0.59 g/cm³) and the lowest drop test value, indicating strong mechanical integrity. All samples demonstrated low moisture content (0.35–1.94%), which contributes to efficient and stable combustion. Variations in material composition significantly influenced the stability and combustion characteristics of the briquettes. Overall, sugarcane bagasse shows strong potential as a sustainable and environmentally friendly raw material for producing high-quality biobriquettes as an alternative renewable energy source.
This study aims to examine how the addition of skimmed milk at different levels affects the physical, chemical and hedonic test characteristics. The research was conducted using a Complete Random Design (RAL) consisting of 4 treatments, namely: control (P0); skimmed milk 2.5% (P1); skimmed milk 5% (P2); and skimmed milk 7.5% (P3). The results showed that the addition of skimmed milk had a very pronounced effect on all parameters tested (P<0.01). The pH value increased from 5.48±0.02 (P0) to 5.51±0.04 (P1), 5.73±0.04 (P2), and 5.78±0.06 (P3). Yields increased from 4.9±0.47% (P0) to 8.4±0.34% (P1), 8.7±0.10% (P2), and 9.2±0.23% (P3). The higher the level of skim milk added, the yield and pH of the cheese increases, so that the amount of cheese produced is more and the pH is higher but the distinctive taste of the cheese decreases. However, the increase in skim milk also causes the cheese to become harder, the moisture content decreases, and the level of ductility or ability of the cheese to be drawn is significantly reduced. Based on the hedonic test, mozzarella cheese with the addition of skim milk of up to 7.5% was still acceptable to the panellists, despite a decrease in the ductility aspect. Thus, the addition of skimmed milk can be an alternative to increase the quantity of mozzarella cheese production, but it is necessary to pay attention to the balance between the quantity and texture quality of the cheese to keep it in accordance with the characteristics expected by consumers.
Seedling production is an important stage for tropical fruit crops, including sugar apple (Annona squamosa), and is strongly influenced by light quality. Light fluctuations in tropical environments often inhibit seedling growth, indicating the need for a more stable lighting system. This study aimed to evaluate the effects of LED design models and light spectra on the morphology of sugar apple seedlings. The experiment used a two-factor Completely Randomized Design (CRD), consisting of LED models (static and dynamic) and light spectra (blue, red, and white), with eight replications for each treatment. The study was conducted in a screenhouse with 60% shading. Observed parameters included plant height, leaf number, stem diameter, canopy width, root length, and biomass. The results showed that the static system provided the best relationship with canopy development (R² = 0.757), while the dynamic system produced higher light intensity but had the potential to cause photochemical stress. White light gave the best growth response (R² = 0.851), followed by red, whereas blue showed the lowest relationship. Correlation analysis indicated that static lighting supported more stable vegetative growth. Overall, static LED with white spectrum was the most effective combination for early growth of sugar apple seedlings under the conditions of this study and is recommended for tropical fruit seedling production.
Beluntas (Pluchea indica Less) leaves possess significant potential as functional food ingredients, yet their storage stability in vegetable leather form requires rigorous quantification. This study analytically determines the shelf life of beluntasand seaweed vegetable leather using a kinetic modeling approach based on the Accelerated Shelf Life Testing (ASLT) Arrhenius model.A two-factor experimental design evaluated three packaging systems (Aluminum Foil, Aluminum Foil-Polyethylene, and Polypropylene) across three isothermal conditions (30, 35 and 40 °C). Quality degradation was monitored via protein content, Vitamin C, and browning index at 7day intervals for 28 days. Statistical regression was performed using the Data Analysis Toolpak to ensure model reliability. Kinetic analysis revealed thatvitamin C degradation,identified as the critical quality indicator, followed first-order kinetics. The model was validated by high coefficients of determination (R2up to 0.9721) and low Root Mean Square Error (RMSE) values (0.0352–0.1738). The calculated activation energy (Ea) ranged from 14.72 to 19.44 kJ/mol, explaining the product's temperature sensitivity. At 30 °C, the predicted shelf life was 16.87 days for aluminum foil, 12.96 days for combination packaging, and 9.96 days for polypropylene.
Milk can be utilized as a raw material in yoghurt production. The fermentation process of yoghurt involves Lactobacillus bulgaricusand Streptococcus thermophilusas lactic acid-producing microorganisms. The fermentation temperature is a crucial factor affecting the quality of yoghurt; therefore, an accurate temperature control system is required, one of which can be achieved through the implementation of the fuzzycontrol method. The optimal temperature in the fermentation process ranges between 38–45°C. This variation was determined to achieve effective temperature control during the fermentation process.The addition of sweet corn extract is also applied to enhance the flavor of the product. This study aims to analyze the effect of implementing a fuzzy Neo-based temperature control system and the variation of sweet corn extract concentration on the physicochemical properties of yoghurt. The fermentation process was carried out at temperatures of 39.97 and 44.99°C with the addition of 30and 60% sweet corn extract. The results showed that the best treatment was obtained from yoghurt produced with fuzzy-based temperature control at 44.99°C and 30% sweet corn extract addition (F-30%-44.99°C), which exhibited a pH value of 4.3, total soluble solids of 11.5°Brix, viscosity of 124 m.Ps, and lactic acid content of 0.7905%.
This study focuses on the analysis of carrageenan-based edible films with the addition of candelillawax and zinc oxide nanoparticles (NP-ZnO) and their effects on physical and mechanical properties. The edible films were formulated using kappa carrageenan and additional ingredients such as Tween 60, Span 60, glycerol, and distilled water. This research used a completely randomized design (CRD) consisting of two factors NP-ZnO as the first factor with consentrate levels of 1, 2, 3%, resulting in 9 treatment combinations with 3 replications. The data analysis was performed using the software minitab to obtain mean values and standard deviations, which were presented in graphical form for the physical and mechanical propertyresults. The edible filmwas cast into plastic petri dishes nd then dried in an oven at 50°Cfor 2 days. The observed parameters included thickness, color, water vapor transmission rate (WVTR), water absorption capacity (WAC), water solubility (WS), tensile strength, and elongation. The results showed that the addition of candelillawax and NP-ZnO affected the physical and mechanical properties of the film. Increasing the concentration of candelillawax and NP-ZnO increased the thickness value from 0.078 to 0.1 mm and increased the ΔE value from 19.67 to 23.57. Meanwhile, the WAC value decreased from 82.65% to 63.95%, the WS value decreased from 84.43to 66.80%, and the WVTR value decreased from 22.5 to 19.56 5 g/m2.d. in contrast, tensile strength increased from 1.831to 4.6 MPa, while the elongation value decreased from 48.93 to 28.25%.
This study aims to evaluate the operational performance of a 7000-liter fiberglass biodigester that was revitalized and modified at the Power and Agricultural Machinery Laboratory, Faculty of Food Technology and Agroindustry, University of Mataram. The fiberglass biodigester was developed as an alternative to conventional concrete biodigesters, which are prone to structural damage and exhibit limited operational efficiency, particularly in earthquake-prone regions. The research was conducted as an observational case study through performance monitoring of the biodigester during 40 days of continuous operation following system repair and modification. Cow manure was used as the substrate, mixed with water at a 1:2 ratio (by volume). The monitored parameters included fermentation temperature, substrate pH, gas pressure, daily biogas volume, gas composition, and combustion quality. The results showed that the biodigester operated stably at temperatures ranging from 27 to 31 °C and near-neutral pH conditions, with a maximum daily biogas production of 4.43 m³/day and an average of 1.73 m³/day throughout the monitoring period. The methane content ranged from 52 to 61%, while hydrogen sulfide concentration was reduced to approximately 150 ppm after gas purification, indicating that the biogas was suitable for combustion with a heating value of up to 21 MJ/m³. These findings demonstrate that the fiberglass biodigester exhibits good operational performance and has strong potential for application as a renewable energy system at campus and community scales, supporting sustainable livestock waste management.
Palm oil mills used sand cyclones to reduce the sand content in sludge. High sand content (>5% in samples) and low efficiency caused pipe erosion, potential damage to decanter machines, increased maintenance costs, and reduced equipment lifespan. This study aimed to analyze the impact of flushing periodicity on the sand content in the sand cyclone outputs and to determine the optimal flushing periodicity. The experiment was conducted with six flushing time variations (P0 to P5) tested on sand cyclone 1 (SC1) and sand cyclone 2 (SC2). For SC1: P0 had a flushing time of 3.75 minutes, while P1, P2, and P3 were set at 4.25 minutes, and P4 and P5 at 4.75 minutes. For SC2, P0 had 7.50 minutes, P1 was 7.00 minutes, P2 was 7.50 minutes, P3 was 8 minutes, P4 was 7.50minutes, and P5 was 8.00 minutes. Each treatment was replicated six times. The observed parameters included flushing water requirement, residual oil content, emulsion, moisture content, non-oil solids (NOS), and sand content. The results indicated that flushing periodicity significantly affected flushing water consumption, residual oil levels, emulsion formation, moisture content, NOS, and sand separation. The optimal flushing periodicity was able to reduce sand content in the sand cyclone overflow to 2.50%. To achieve maximum efficiency, a flushing frequency of 15 times per hour with a duration of 4.25 minutes is required for SC1, while for SC2 a flushing frequency of 8 times per hour with a duration of 7.50 minutes is required.
Technological developments provide significant opportunities to utilisemeasurement equipment to enhance the effectiveness and efficiency of agricultural production. Accurate soil content measurement is very important for evaluating soil quality, helping farmers understand soil conditions and take appropriate steps to improve or maintain it. Calibration is required to ensure that the measuring instruments used provide accurate readings. The objective of this research was to calibrate the soil comprehensive sensor type RS485. The parameters tested are WET sensor, pH sensor, and temperature sensor. Data analysis was conducted using spatial interpolation, linear regression, and multiple linear regression. The calibration results obtained the calibration function YWET=1.0946×WETs(R20.9566)for the WET sensor, YpH=0.8834×pHs(R20.9845)for the pH sensor, and YT=0.9934×Ts(R20.9963)for T sensor. The results of the spatial interpolation analysis using the calibration function indicate an improvement in the accuracy between the tested sensor and the calibrator compared to before calibration. The improvement in the accuracy of the parameter values was obtained by performing multiple linear regression analysis involving all sensors. The equations WETe4, pHe4, and Te4were chosen as the best estimated equations that can improve the accuracy of sensor readings. The results of spatial interpolation analysis of the functions WETe4, pHe4, and Te4showed a better improvement in accuracy compared to the calibration function. The equations WETe4, pHe4, and Te4 can be used as alternative functions to approximate the correct values in the use of soil comprehensive sensor type RS485. The spatial interpolation analysis conducted can provide an illustration of values based on colordistribution to understand of the distribution of those values.
Salt-affected soils are marginal environments that constrain plant growth by reducing nitrogen (N) and phosphorus (P) availability and uptake efficiency. This study aimed to evaluate the effects of integrated fertilization combining inorganic, organic, andbiofertilizers on N and P uptake and nutrient use efficiency in Biosalin rice grown under saline conditions. The experiment was conducted in West Lombok, Indonesia, using a randomized complete block design with nine treatments and three replications. Measured parameters included canopy dry weight, nutrient content, nutrient uptake, and recovery efficiency of N and P. The results showed that treatment M8 (50% inorganic fertilizer + cattle manure + phosphate-solubilizing bacteria + ACC-deaminase) produced the highest biomass and nutrient use efficiency. In contrast, treatment M4 resulted in the highest nutrient uptake but lower efficiency. These findings indicate that greater nutrient uptake does not necessarily translate into improved plant growth under saline conditions, and that nutrient use efficiency is a more critical determinant of plant performance. The integration of organic and biofertilizers significantly enhanced nutrient efficiency and enabled a 50% reduction in inorganic fertilizer application. Therefore, integrated fertilization represents a more efficient and sustainable strategy for rice cultivation in salt-affected soils.
Curcuma is a rhizome widely used as herbal medicine due to its various health benefits, including increasing appetite and promoting overall health. Herbal medicine in liquid form has a limited shelf life at room temperature and specific refrigeration temperatures. These limitations make traditional herbal medicine difficult to reach a broader market, necessitating alternatives with longer shelf lives, such as herbal tea bags. This study was conducted to investigate the drying of curcuma into curcuma powder packaged in filter paper, making it more convenient for brewing and longer-lasting. The drying of curcuma in this study utilized a microwave. In addition to being influenced by microwavepower, the quality of curcuma dissolution is also affected by geometric shape variability. The results of the study showed bulk density values between 0.54-0.61 g/mL; solubility values of 99.56-99.62%; moisture content of 9-11.33%; brightness levels of 21.05-28.96; redness levels of 1.42-2.53; and yellowness levels of 5.00-6.41. Microwavepower significantly influenced all parameters, while geometric shape only affected brightness, redness, and yellowness. The best treatment combination is 3.49 mm (medium) and microwavepower of 322 W (low).
Fruit powdered drinkproducts can be made by combining pineapple juice (SN) and sweet orange juice (SJ). This study aims to evaluate the chemical, physical, and organoleptic characteristics of powder beverages with various SN and SJ compositions, and determine the optimal formulation. The research method used a Complete Randomized Block Design (CRBD) with one factor repeated four times. The factor studied was the ratio of SN and SJ in six levels: 100%:0% (P1), 80%:20% (P2), 60%:40% (P3), 40%:60% (P4), 20%:80% (P5), and 0%:100% (P6). Data were analyzed using analysis of variance (ANOVA) and followed by Least Significant Difference (LSD) test at 5% significance level. Results showed that SN and SJ combinations significantly influenced chemical, physicaland sensory parameters. The P5 formulation (20% SN: 80% SJ) was selected as the optimal treatment with the best characteristics across all tested parameters.
