JTEP (Jurnal Keteknikan Pertanian) P-ISSN: 2407-0475 E-ISSN: 2338-8439, previously named Agricultural Engineering Bulletin, is an official publication of the Indonesian Society of Agricultural Engineers (ISAE) in collaboration with the Department of Mechanical and Biosystem Engineering, Faculty of Agricultural Technology and Engineering, Bogor Agricultural University (The MoU can be downloaded here). JTEP starting in 2025 will be published four times a year in March, June, September, and December. JTEP is a peer reviewed journal that has been accredited SINTA 2 by the Ministry of Research, Technology and Higher Education Number 177/E/KPT/2024 which is valid for 5 (five) years since volume 11 issue 2, 2023 to volume 16 issue 1, 2028. JTEP has been registered in Crossref, Indonesian Publication Index (IPI), Google Scholar, and other scientific databases. JTEP receives manuscripts of research results or scientific review in agricultural engineering related to farm structures and environment, agricultural and biosystem engineering, renewable energy, postharvest technology, food engineering and agricultural information system. The articles sent by the author - must be an original script and is not being considered for publication by other journal or publishers - should be written in accordance with the writing guidelines and submitted online via https://journal.ipb.ac.id/index.php/jtep. Editors can revise the paper without changing the substance and content after a blind review process. For further information and correspondence, please contact the secretariate of Jurnal Keteknikan Pertanian, Department of Mechanical and Biosystem Engineering, Faculty of Agricultural Technology and Engineering, Bogor Agricultural University, Kampus IPB Darmaga Kotak Pos 220, Bogor 16002; Phone: +62 251 8624503 Fax: +62 251 8623026; E-mail: jtep@apps.ipb.ac.id
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Design and Fabrication of a Microcontroller-Based Automatic LED Grow Light Array System for Leafy Vegetables in Indoor Vertical Hydroponic
Indoor vertical hydroponic systems require precise and energy-efficient lighting to support optimal growth of leafy vegetables. This study presents the design and fabrication of a microcontroller-based automatic LED grow light system tailored for indoor hydroponics. A tailored LED grow light is necessary because each crop responds uniquely to light quality and intensity, and a customized spectrum ensures optimal growth while minimizing energy use. The system integrates a red–green–blue LED configuration (70:10:20%) with an ESP32 microcontroller, real-time clock (RTC), BH1750 light sensor, keypad interface, and LCD. The lighting cycle was programmed for 12 hours per day and tested continuously over two days. The system demonstrated accurate scheduling, with LED activation at 06:00 and deactivation at 18:00 and a timing deviation of only 1–2 seconds. During operation, the system maintained a stable photosynthetic photon flux density (PPFD) of 260–275 µmol/m²/s, producing an estimated daily light integral (DLI) of about 12 mol/m²/day, which is suitable for leafy vegetable production. Light distribution analysis using cubic interpolation showed that increasing the lamp height from 20 cm to 30 cm improved spatial uniformity, with the most uniform distribution achieved at 30 cm despite a slight reduction in intensity. The system consumed 2.65 kWh per day, covering four LED arrays and the control module. Overall, the proposed system offers a reliable, programmable, and energy-efficient lighting solution for indoor hydroponic environments, supporting sustainable crop production through precise scheduling and an optimized spectral configuration.
Copyright (c) 2025 Jurnal Keteknikan Pertanian https://creativecommons.org/licenses/by-sa/4.0/
Sustainable Urban Farming Rack Design Using Eco Friendly Materials with Variety Load
Vertical farming requires a structurally sound and environmentally sustainable racking system; however, existing research largely neglects the evaluation of the structural safety of eco-friendly racking materials under various operational loads. This gap necessitates further rigorous mechanical performance assessments to ensure the long-term reliability of the system. This study aims to develop a vertical farming racking design with an adequate safety factor by examining its structural response to various load scenarios. A design-construction methodology supported by SolidWorks simulations was used to evaluate stress distribution, strain behavior, and deformation patterns. Simulation results using SolidWorks software indicate that the maximum compressive stress at the loaded joint surface is 13.734 MPa, while the minimum stress is 1.149 MPa. The highest load occurs at the fourth (bottom) joint level due to pump-induced water pressure. The maximum strain recorded is 0.00491, with a minimum of 0.00041. The top shelf level exhibits a maximum displacement of 48.165 mm, while the minimum displacement is 0 mm. This shows that the material and shape of the frame that has been made are in the safe category with a safety factor (sf) of 2.4. These findings indicate that the proposed rack design maintains structural integrity within safe limits and is suitable for application in vertical farming systems.
Study the Application of Automatic Unpowered Fertigator (FONi) in Eggplant (Solanum melongena) Cultivation
Water scarcity, intensified by climate change and pollution, necessitates innovative irrigation approaches to sustain agricultural productivity. The Automatic Unpowered Fertigator (FONi) represents a solution that integrates automation without electricity, using evapotranspiration-driven subsurface irrigation to deliver water and nutrients directly based on plant demand. Unlike conventional systems, FONi operates entirely without external energy input, offering a low-cost and sustainable alternative for smallholder farmers. Previous applications in various crops have demonstrated significant water savings and increased productivity, indicating its strong potential as a scalable technology for resource-limited agriculture.This study evaluated the performance of FONi in cultivating four eggplant varieties under greenhouse conditions in Bekasi City, an area facing increasing competition for water resources. Over a 118-day growing period, plant growth, water use, crop coefficients (Kc), and productivity were monitored. Results showed Kc values ranging from 0.1 to 1.8, reflecting dynamic water demand throughout plant development. The long purple variety attained the greatest height (99.8 cm), while pondoh and white varieties achieved higher water productivity (up to 4.0 g/L) and land productivity approaching 1,120 g/m². Total irrigation water use was 1,329.3 liters, with an overall application efficiency of 98.9%. These findings demonstrate that integrating FONi with appropriate crop selection provides an efficient and sustainable strategy to optimize water use and enhance yield, supporting precision agriculture and climate-resilient food systems in drought-prone regions.
Dynamic Thermofluid Study of Petrodiesel Droplet Combustion with Variations of Kesambi Biodiesel Composition Accompanied with TiO₂ Catalyst
The increasing global energy demand encourages the use of sustainable alternative fuels with combustion performance equivalent to petrodiesel. This study focuses on the droplet combustion characteristics of petrodiesel and biodiesel kesambi blends (B0, B10, B20, B30 B40 and B100), both without and with the addition of 100 ppm TiO₂ nanoparticle catalyst. Analysis was carried out on ignition delay, combustion duration, flame height, peak temperature, and flame visualization patterns. The results show that increasing the biodiesel fraction tends to prolong the combustion time and decrease the peak temperature, while the addition of TiO₂ provides significant improvements in the form of shorter ignition delay, higher peak temperature, and more stable flame. The novelty of this study lies in the use of a droplet approach to explore the role of TiO₂ catalyst in kesambi biodiesel, which is still limited in the literature. Thus, nanoparticle catalysts are proven to have great potential in increasing the efficiency and sustainability of the use of biodiesel–petrodiesel blends.
Biodiesel; Droplet; TiO2 Catalyst; Combustion Characteristics.
Portable NIR Spectroscopy for Cocoa Bean Re-fermentation Analysis: A Rapid and Reliable Technique
Portable near-infrared (NIR) spectrometers may examine samples directly on-site, speeding up data gathering. However, the NIR spectrometer has a limited wavelength, ranging from 740 to 1,070 nm, whereas previous studies used a longer wavelength. The research aims to determine the fermentation index, pH, and moisture content of fermented dry cocoa beans using a portable Near-Infrared (NIR) spectrometer. The NIR spectra were preprocessed using several methods, including the Savitzky-Golay first and second derivatives (SG 1 and SG2), Linear Baseline Correction (LBC), Multiplicative Scatter Correction (MSC), comparative Partial Least Square Regression (PLSR) modeling, and Artificial Neural Network (ANN). To simulate different fermentation levels, unfermented cacao beans underwent pretreatment fermentation for durations of 0, 24, 48, and 72 hours. The prediction outcomes of ANN models, when applied to dried fermented cocoa beans with data preprocessing, offered better results in comparison to PLSR models, with strong correlation, lowest RMSEC, and highest residual predictive value. The most effective method for predicting fermentation index was ANN combined with LBC preprocessing, while optimal pH models were applied using the SG2 method. The effective moisture content models were developed using MSC preprocessing. The analytical approach of portable NIR spectroscopy produced rapid and accurate results to determine the quality of ground-dried cacao bean fermentation.
The Effectiveness of Cocoa Pod Husk Activated Carbon as an Ethylene Adsorbent for Extending the Shelf Life of Cavendish Bananas
One of the abundant agricultural wastes in Indonesia that has not been optimally utilized is cocoa pod husk (Theobroma cacao L.). Cocoa pod husk is the main by-product of the cocoa bean processing. Cocoa pod husk has a high cellulose content, making it a suitable precursor for activated carbon production. Activated carbon can adsorb ethylene from climacteric fruits, extending fruit shelf life. This research aims to test the effectiveness of activated carbon derived from cocoa pod husk as an ethylene adsorbent to extend the shelf life of fruits, specifically Cavendish bananas. The research procedure consists of preliminary research and primary research. The initial research involved measuring ethylene production, synthesizing activated carbon from cocoa pod husk, testing the characteristics of the cocoa pod husk activated carbon, calculating the activated carbon's capacity for ethylene adsorption, and determining the optimal amount of cocoa pod husk activated carbon. The primary research involved testing Cavendish bananas' storage and display life by applying an ethylene adsorber bag (EAB) using perforated LDPE packaging until spoilage. The Cavendish banana samples originated from Klaten, Central Java, with a maturity level of 1. The test parameters included moisture content, weight loss, firmness, color, total soluble solids (TSS), and Total Titratable Acidity (TTA). The treatments in this study consisted of samples treated with EAB from cocoa pod husk and a control group without EAB. All treatments were performed in triplicate. The experimental design used was a Completely Randomized Design (CRD). The results showed that a well-defined porous structure, a rough surface, and numerous cavities characterize the cocoa pod husk activated carbon. It has an ethylene absorption capacity of 363 ppm/g. The ethylene production rate of Cavendish bananas observed during storage was 1,280 ± 227.5 ppm. The results showed that bananas treated with cocoa pod husk-activated carbon were still green on the 10th day compared to the control treatment, which had already spoiled. During the display period, Cavendish bananas could last up to 5 days before spoilage. Therefore, cocoa pod husk-activated carbon can delay ripening and spoilage, thus extending the shelf life of Cavendish bananas.
Price Forecasting of Shallots Using the Machine Learning Approach of Random Forest Regression Supporting Price Stabilization
Shallots (Allium cepa L.) are a major horticultural commodity in Indonesia, with a production of 1.98 million tons in 2022, representing 13.59% of the total national vegetable production. Accurate forecasting of agricultural commodity prices is fundamental to sustainable development in the agricultural sector and contributes to broader economic stability. This study uses the random forest regression algorithm, a supervised machine learning technique that utilizes ensemble learning to combine multiple decision trees. This approach offers advantages in modeling non-linear relationships for agricultural price prediction while also reducing the risk of overfitting, resulting in more accurate and stable forecasts compared to individual decision trees. The purpose of this research is to develop and optimize a shallot price forecasting model using random forest regression. The optimized model, using 50 decision tree estimators, successfully predicted up to 15 months ahead of monthly prices and achieved an RMSE of 2363.15 and a MAPE of 8.71% in validation, then a MAPE of 10.31% in test evaluation.
FONi's Performances in the Hydroponic Cultivation of Various Vegetables
Land conversion, a phenomenon being encountered today, has led to a decline in the availability of agricultural land. On the other hand, population growth requires more food, which means more farmland is needed. Hydroponics is a method to grow crops intensively in any form of space without using soil, but only nutritious water as the growing medium. Hydroponics can produce high-quality crops and is easy to implement, making it popular in urban areas. However, it requires a continuous flow of water using electric pumps, which ultimately increases investment and operating costs. In this study, FONi (An Unpowered Automatic Fertigator) was tested to maintain water levels and flow rates as required by the plants. FONi is designed to replace the water lost by plant evapotranspiration, utilizing an automatic water valve. Here, FONi demonstrated good performance in growing three types of vegetables, namely water spinach (kangkung), choy sum (caisim), and spinach (bayam). The water productivity of each was 47.51 kg/m³, 43.80 kg/m³, and 21.25 kg/m³, respectively, and the land productivity was 1.35 kg/m², 0.97 kg/m², and 0.57 kg/m², respectively. The overall water efficiency was above 80%. By applying FONi, hydroponic cultivation activities at the research site, which had been suspended, can resume without incurring electricity costs.
Hydroponic, FONi, Land productivity, Water productivity, Water efficiency
Correlation Analysis Between Water Discharge and Suspended Load During The Rainy Season in The Downstream Ciliwung River, Jakarta
The Ciliwung River Basin originates at the foot of Mount Pangrango in West Java and flows downstream to Jakarta, with a catchment area of approximately 387 km². The downstream segment in Jakarta is highly vulnerable to sedimentation, which reduces flow capacity, damages infrastructure, and increases flood risk. These conditions highlight the urgency of analyzing the relationship between water discharge and total suspended solid (TSS) load in the downstream Ciliwung River as a scientific basis for river management in Jakarta. This study analyzed the correlation between water discharge and total suspended solids (TSS) in the downstream segment of the basin. Water samples were collected from three observation points, resulting in 11 observations and 33 samples in January 2025. The relationship between water discharge and TSS load was examined using linear regression correlation analysis in order to identify the degree of association and to establish the regression model between both variables. TSS ranged from 8.5 to 284.5 mg/L, while Water discharge varied from 2.55 to 45.47 m³/s. The correlation coefficients were obtained as 0.9721 at the upstream site, 0.9151 at the middle stream site, and 0.0006 at the downstream site. A strong positive correlation was found in the upstream and midstream segments, while the downstream segment showed no significant correlation, likely due to hydrological and tidal effects. These results contribute to a deeper understanding of sediment transport dynamics and can inform sustainable sediment management and dredging strategies in urban river systems.
Impact of Postharvest Processing on the Metabolite Profile of Arabica Green Coffee Beans
Postharvest techniques greatly affect the composition and quality of green coffee beans by altering some primary and secondary metabolites. This study aimed to assess the impact of three postharvest processing techniques (natural, honey, and fully washed) on the phenolic compounds, antioxidant activity, caffeine, protein, and color in Arabica green coffee beans from Solok Regency, Indonesia. Spectrophotometric and colorimetric analyses were performed. Data were analyzed using Duncan’s multiple range test, multivariate PCA, and heatmap clustering. Results showed that honey process had the highest polyphenol content of 3918.61 ± 349.85 mg GAE/g, whereas beans that were fully washed had the highest antioxidant activity (1.41 ± 0.21%) and caffeine content (1.41 ± 0.21%). Natural processing yielded the highest protein content (24.26 ± 0.40%). There were significant differences in the hue angle that were related to some of the biochemical differences among the treatments. This research emphasizes the importance of postharvest processing in defining the metabolite profile and quality features of green coffee beans. These findings can assist in formulating the processing steps to be used in refining coffee and maximizing its health-related advantages.
The Effect of Light Exposure Duration on the Oxidative Stability and Sensory Profile of Avocado (Persea americana)-Based Mayonnaise
Avocado-based mayonnaise presents a novel formulation aimed at reducing the saturated fat content typically associated with conventional emulsified condiments. This investigation sought to delineate the impact of light exposure duration on the oxidative integrity and sensory parameters of mayonnaise derived from Persea americana. Employing a completely randomized design (CRD) comprising a single experimental factor—duration of light exposure (0, 24, 48, and 72 hours) each treatment was replicated thrice to ensure experimental reliability and statistical robustness. Analytical endpoints included moisture content, pH, peroxide value, free fatty acid (FFA) concentration, and sensory attributes (color and aroma). Statistical analyses involved ANOVA followed by Duncan’s Multiple Range Test at a 5% significance threshold. The results revealed that prolonged exposure led to a statistically significant decline in sensory acceptance (color score: 6.07 to 3.47; aroma score: 6.20 to 3.67) and elevated oxidative markers including moisture content, peroxide value, and FFA. Among the tested conditions, treatments L1 and L2 preserved compositional and sensory quality within permissible SNI standards for FFA (<3%). The study underscores the necessity of light-protective packaging in mitigating oxidative degradation in avocado-based emulsions and emphasizes the relevance of optimizing environmental exposure parameters during storage and distribution of lipid-rich food emulsions.
Optimizing Coffee Flavor Through Roasting and Manual Brewing Using Chemical and Sensory Approach
The global popularity of coffee has led to growing attention on how processing and brewing techniques influence its sensory attributes. This study analyzed the chemical content of coffee and assessed the combination of roasting and manual brewing methods on coffee flavor. The coffee types used were Arabica coffee and Robusta coffee. The roasts used were light, medium, and dark roast with AeroPress, Siphon, and V60 manual brewing methods. The experiment was arranged in a factorial arrangement within a Randomized Complete Block Design (RCBD), where coffee varieties served as blocks, and the treatment combinations of roasting and brewing methods were randomly assigned within each block. Data analysis includes two-way analysis of variance, biplot analysis, and the compromise programming method. The results showed that the selection of roast level and brewing method had a significant influence on the coffee's chemical analysis and sensory profile. Light roasting and complex flavors were more acceptable than dark roasting, which tends to be heavy. Based on the panelists' preference analysis using the compromise programming method, RLS (Robusta-Light roast-Siphon) emerged as the optimal choice, indicating that this combination balances all coffee taste criteria. The combinations ALV (Arabica-Light roast-V60), ALA (Arabica-Light roast-Aeropress), and AMA (Arabica-Medium roast-Aeropress) which tends to similar and provide a balanced, complex flavor profile, including aroma, acidity, and high overall quality. Arabica coffee combination ADS (Arabica-Dark roast-Siphon), ADA (Arabica-Dark roast-Aeropress), and ADV (Arabica-Dark roast-V60) which have less optimal visual and balance because dark roasting reduces the sensory criteria of coffee.
roasting, manual brew, analysis sensory coffee, biplot, compromise programming
Analysis of Temperature and Airflow Distribution during Carrot Drying Using a Tray Dryer Based on CFD Simulation
Carrot (Daucus carota L.) is a highly nutritious vegetable that is prone to spoilage due to its high moisture content. Drying is an effective method to extend its shelf life, with the tray dryer being one of the commonly used technologies. However, the efficiency of the drying process greatly depends on the uniformity of temperature and airflow distribution within the drying chamber. This study aims to analyze the distribution of temperature and airflow inside a tray dryer using Computational Fluid Dynamics (CFD) during the drying of carrots. Simulations were conducted at three different temperatures (50°C, 60°C, and 70°C) and two air velocities (2 m/s and 3 m/s) using SolidWorks, ANSYS Fluent, and Origin software. The simulation results showed that both temperature and airflow were unevenly distributed, particularly in the middle and upper sections of the dryer. This non-uniformity can lead to inconsistent drying and reduced product quality. Validation was carried out by comparing simulation results with experimental measurements using relative error analysis. The error values obtained ranged from 1.41% to 3.82% for temperature and 0.5% to 2.41% for air velocity, all below 4%. These results indicate that the CFD model is sufficiently accurate and can be applied to support the design and optimization of more efficient drying equipment.
ANSYS Fluent, Pengeringan, Perpindahan Panas, Suhu dan Thermodinamika
Shelf-Life Estimation of Dried Sago Noodles Using the Accelerated Shelf-Life Testing (ASLT) Method
Indonesia holds significant potential for sago (Metroxylon sp.) development, especially in the eastern regions. Sago starch offers an alternative to wheat flour in noodle production, promoting local food diversification. This study aims to estimate the shelf-life of dried sago noodles using the Accelerated Shelf-Life Testing (ASLT) method based on selected quality parameters. Dried sago noodles were produced from sago starch sourced from Merauke, South Papua, and stored at 35°C, 45°C, and 55°C. Quality attributes—moisture content, aroma, and taste—were analyzed during storage to model degradation kinetics and determine activation energy (Ea) using the Arrhenius approach. Among the tested parameters, aroma exhibited the lowest activation energy (636.04 cal/mol), indicating it as the critical parameter for predicting shelf-life. Based on the regression of ln k versus 1/T, the shelf-life at 27°C (room temperature) was estimated at 49 days. The study concludes that aroma degradation is the key factor in determining the shelf-life of dried sago noodles, and that accurate sensory evaluation using trained panelists is crucial for improving the reliability of shelf-life prediction.
Accelerated Shelf-Life Testing (ASLT), activation energy, Arrhenius equation, sago noodle, shelf-life modeling
Prediction of Chemical Content in Robusta Coffee Beans Using Near Infrared Spectroscopy and Artificial Neural Network
A rapid method to predict chemical content of robusta coffee is necessity, instead of chemical method that time consuming and expensive. This research aimed to predict chemical content of Pagar Alam robusta coffee beans using Near Infrared Spectroscopy (NIRS) and calibration through Principal Component Analysis-Artificial Neural Network (PCA-ANN). Reflectance of coffee bean was measured using NIR Flex N500 Spectrometer (1000–2500 nm), followed by determination of its chemical content using chemical method. The reflectance data were processed using spectra pre-treatment, then calibrated and validated with chemical content using PCA-ANN. The best model for moisture content was achieved with No1SG1 pre-treatment and 8 PC (r = 0.95; RPD = 2.95; consistency = 90.36%). Protein content can be predicted using 8 PC and No1SG1 pre-treatment (r = 0.92; RPD = 2.38; consistency = 96.78%). Good fat prediction employed No1SG1 pre-treatment and 10 PC (r = 0.93; RPD = 2.19; consistency = 80.08%). Ash content can be predicted using 8 PC and SG1 pre-treatment (r = 0.93; RPD = 2.29; consistency = 83.78%). The best carbohydrate prediction was obtained with No1SG1 pre-treatment and 5 PC (r = 0.93; RPD = 2.73; consistency = 108.85%). The results indicate that NIR spectroscopy can be used to predict accurately the chemical content of Pagar Alam robusta coffee beans.
Copyright (c) 2025 Jurnal Keteknikan Pertanian
Performance Comparison of Adaptive Neuro-Fuzzy Inference System (ANFIS) and Fuzzy Logic Based Microclimate Control System in Plant Factory
Population growth and the reduction of agricultural land necessitate the application of technology to enhance agricultural productivity. A plant factory is an advanced agricultural technology that enables indoor plant production by precisely regulating the microclimate for optimal growth. While fuzzy logic algorithms have been applied for microclimate control, the use of an adaptive neuro-fuzzy inference system (ANFIS) has not been explored. This research aims to develop a microclimate monitoring and control system based on ANFIS and fuzzy logic in a plant factory and compare their performance. The study involves five stages: designing control system schemes, developing hardware and software, testing, analyzing data, and comparing system performance. Microclimate data from both systems were analyzed using the Mean Absolute Error (MAE) metric and visualized through performance graphs. The results indicate that the plant factory with ANFIS control achieved MAE temperature values of 1.18°C and 1.48°C and MAE humidity values of 14.68% and 12.48%, while the fuzzy logic control system yielded MAE temperature values of 1.68°C and 1.60°C and MAE humidity values of 13.02% and 12.31%. Based on the MAE values, the ANFIS control system demonstrated better temperature regulation than fuzzy logic; however, neither system provided optimal microclimate control. These findings highlight the potential of ANFIS for improving temperature regulation in plant factories, suggesting the need for further refinement and optimization of control strategies to enhance overall system performance The research consists of five stages, namely designing ANFIS and fuzzy logic control system schemes, designing hardware, designing software, testing and analyzing data, and comparing the performance of the two control systems. Microclimate data from both control systems were then analyzed to see their performance by looking at the MAE (Mean Absolute Error) value. Analysis is also done by looking at the graph of running results. The results showed that the plant factory with ANFIS control system showed MAE temperature values of 1.18oC and 1.48oC and MAE humidity of 14.68% and 12.48% while the plant factory with fuzzy logic control system showed MAE temperature values of 1.68oC and 1.60oC and MAE humidity of 13.02% and 12.31%. The plant factory with ANFIS control system provides better performance in temperature regulation based on the MAE value obtained but has not provided good performance, either using ANFIS control system or using fuzzy logic control system.
Modification of a Rice Cooker into Black Garlic Aging Chamber and Performance Analysis
This study aimed to modify a conventional rice cooker into a temperature-controlled aging chamber for black garlic production. The modification involved disabling the automatic switch and replacing the internal sensor with an external DS18B20 sensor, connected to an STC-1000 digital thermostat. The system was designed to maintain consistent heating at three temperature settings: 60 °C, 70 °C, and 80 °C, and enabled real-time temperature monitoring using a thermo recorder. Results showed that the modified rice cooker with only a thermostat had a temperature fluctuation of 10.8 °C. When combined with 4 mm cardboard insulation, the fluctuation decreased significantly to 3.8 °C.
Keywords: Rice Cooker, Sensor, Heat, Thermostat, Thermocouple
Classification of Arabica Coffee Beans with Honey Processing Based on Starter Type Using Multi-Channel Spectra Sensor
Arabica coffee is significant commodity in Indonesia's agricultural sector, contributing as an income source for farmers and a major export revenue. The specialty coffee industry has begun to utilize microorganisms (starter) in the fermentation process, including the honey process, to obtain a distinctive flavor. However, the use of various starters in this process results in uniform coffee bean color, making it difficult to determine the authenticity of the type of starter used. This research classifies arabica coffee beans processed with different type of starter using multi-channel spectra sensor to ensure product quality and authenticity. This research uses arabica coffee beans that are still in the form of green beans in honey processed with three types of starters, namely Saccharomyces cerevisiae, Lactobacillus sp, and Rhizopus oryzae. Multi-channel spectra sensor with PLS-DA methods can classify arabica coffee beans processed in honey with 3 types of starters. The PLS-DA model built using de-trending pre-treatment was able to predict the calibration data of arabica coffee beans with starter types very well, with accuracy, sensitivity, specificity, and precision values, reaching 97%, 95%, 96%, 95%, respectively, and the PLS-DA model built using de-trending pre-treatment is able to predict the validation sample of arabica coffee beans with starter type very well, with accuracy, sensitivity, specificity, and precision values, reaching 100%.
Renewable Energy from Various Oil Palm Varieties in Penajam Paser Utara, Indonesia
Oil palm has the potential to serve as a strategic energy source for the national energy transition. This study evaluates the potential of four oil palm varieties Sain, Lonsum, Dumpy, and Marihat in Penajam Paser Utara (PPU) Regency as sources of biodiesel, edible oil, and solid biomass. The methods applied include fat content analysis, fatty acid profile evaluation, and utilization scenarios based on 2023 production data of Fresh Fruit Bunches (FFB) and Crude Palm Oil (CPO). The results showed that the Lonsum and Sain varieties, which have high fat content and are predicted to be dominated by saturated fatty acids (palmitic and stearic acids) based on literature-reported fatty acid profiles, are most suitable for biodiesel production. In contrast, the Dumpy and Marihat varieties exhibited lower fat content but are predicted to contain higher proportions of unsaturated fatty acids (oleic and linoleic acids), making them more suitable for edible oil applications. The Dumpy variety also has lower moisture content, making it favorable for solid biomass applications. With proportional allocation and conversion of FFB waste into briquettes, the production potential is approximately ±41,200 tons of biodiesel, ±26,159 tons of edible oil, and ±115,104 tons of solid biomass annually. The total energy potential reaches approximately ±3.49 million GJ per year. These findings indicate significant opportunities for the development of self-sufficient energy agroindustry based on oil palm to support energy security and sustainable development in the buffer zones of Indonesia’s new capital city (IKN).
oil palm, biodiesel, solid biomass, renewable energy, self-sufficient agroindustry, Penajam Paser Utara
Non-Destructive Prediction of Moisture Content in Cascara Using NIR Spectroscopy with PLS and PCR
Coffee cherry pulp is a by-product of coffee processing that has not been optimally utilized. Coffee cherry pulp can be dried to produce a herbal tea product, known as cascara. As an herbal tea product, moisture content is one of the most important quality parameters for assessing the quality of cascara. Therefore, a method is required to measure the moisture content of cascara. One of the methods developed is NIR spectroscopy, which is non-destructive, fast, and does not require chemicals. The purpose of this research is to explore the application of NIR spectroscopy in predicting cascara moisture content using partial least squares (PLS) and principal component regression (PCR) methods and to evaluate the performance of each method in building an optimal calibration model. Pretreatment of the spectrum data was carried out with standard normal variate (SNV), gap-segment 2nd derivative (dg2), and a combination of SNV+dg2. The results showed that the best prediction of cascara moisture content used the PLS calibration technique with dg2 pretreatment and five factors 5. The values obtained were Rc2 = 0.96, RMSEC = 0.87 %, SEC = 0.87 %, Rp2 = 0.90, RMSEP = 1.22 %, SEP = 1.16 %, and RPD = 3.44. Meanwhile, the PCR method produced good predictions using SNV pretreatment, with a factor of 8. The prediction results were Rc2 = 0.89, RMSEC = 1.40 %, Rp2 = 0.90, RMSEP = 1.33 %, and RPD = 3.15. NIR spectroscopy can predict the moisture content of cascara nondestructively and rapidly.
Cascara, Moisture Content, NIR Spectroscopy, PCR, PLS
Challenges in the Implementation of Internet of Things (IoT) in Irrigation and Fertilizer Management System in Indonesia
Agriculture is critical to many countries' economies, especially related to gross domestic products (GDP) and employment. However, as a result of industrialization, leading to a problem in fulfilling the expanding global food supply demand. The Internet of Things (IoT) can enhance automatic data transfer in agricultural, improve production, increase quality, improve cost-effectiveness, and reduce environmental impact. However, the obstacles related to IoT application in agriculture have received little discussion especially in the development countries such as Indonesia. This research seeks to fill that gap by investigating the specific issues of adopting the Internet of Things (IoT) in the context of an irrigation and fertilizer management system in Indonesia. To fully study this, a stratified multistage random sampling was conducted to acquire significant insights and data. According to the interview results, respondents voiced worries regarding IoT deployment in agriculture, including, costs implementation (CI), their own knowledge (perceived knowledge (PK)), user experiences with the technology (perceived ease of use (PEU)) and intention of use (IU). The study finds weak CI-IU and PK-IU links but a strong PEU-IU correlation, underscoring the multifaceted factors influencing IoT adoption in agriculture. It is found that the easiness of the use of IoT is the main factors that influence Indonesian farmers to implement the IoT in their farmers. Although the cost of the implementation is an essential factor, easiness to use IoT is the most significant factor. Lastly, researchers, policymakers, and agricultural stakeholders can leverage these insights to advance IoT integration and sustainability in farming practices.
Time Study Analysis on Rice Milling Process at Rice Milling Unit (RMU) “Teaching Industry” Unsoed
Rice is a major food crop in Indonesia that requires special attention in the milling process to ensure efficiency of working time. This study aims to identify the division of work elements in the rice milling process, determine the standard time used by operators, and provide recommendations for improving the work system in the Unsoed “Teaching Industry”. Research data were collected by measuring the time of each work element in the rice milling process using a stopwatch. The work elements are divided into two groups: rice milling elements and rice packaging elements. The analysis methods used include data adequacy and uniformity tests as well as calculations of standard time and normal time. The results of the analysis show that the standard time for the rice milling process is 5,920.55 seconds per 100 kg of rice, while the standard time for the rice packaging process reaches 27,549.81 seconds per 100 kg of rice. The time required is still relatively long compared to previous studies, so several improvements are recommended, including eliminating unnecessary work elements, carrying out thorough maintenance of the tools in the RMU, and placing a bucket in the outlet hole when changing sacks to reduce the time to collect scattered rice. In addition, in the rice packaging process, the element of rice sorting can be eliminated. Other recommendations include improving the working environment by encouraging workers to wear masks during the rice milling process.
Sawitania Christiany Dwi Utami Boru Situmorang
Utilization of Greenhouse Solar Dryer For Curing Process of Sweet Potato
Sweet potato (Ipomoea batatas L.) Cilembu is an export commodity with a high economic value. However, approximately 50% of Cilembu sweet potato harvests do not meet export quality. One of the reasons was uncontrolled curing process. Temperature and Relative Humidity (RH) are environmental factors that significantly influence the curing process. The purpose of this study was to develop a control method and conduct a temperature and RH performance test in a drying house in accordance with the needs of the curing process, and to analyze the effects of temperature, RH, and curing time on the quality of sweet potatoes. The study was conducted experimentally in three stages: tool performance testing, preliminary research, and main research. The experimental design used was a completely randomized factorial design with three factors: temperature (30°C and 35°C), RH (80% and 90%), and curing time (3 days and 5 days). The quality parameters observed were physical damage, skin color, texture, water content, and Total soluble solids. The results of the study showed that the drying house with additional controllers connected to the thermostat and hygrostat was able to control the temperature and RH in the drying house according to the needs of the curing process in the drying house for 24 h. During the storage period, treatment with the curing process increased the Total Soluble Solids value when compared to the control. The curing process at a temperature of 30°C (T1), humidity of 90% (H2), and curing period of 3 days (D3) was able to maintain the quality of sweet potatoes during storage.
The Effectiveness of Zero Energy Cool Chamber in Extending the Shelf Life of Cherry Tomatoes with Packaging Treatment
Cherry tomatoes are of high economic value due to their better nutrition, sweet flavor, and crunchy texture. They are in modern markets due to specific demand and intensive cultivation. Periodic harvesting poses distribution and storage challenges as cherry tomatoes are perishable, leading to price fluctuations and quality deterioration. Temporary storage is required to maintain quality before marketing. Zero Energy Cool Chamber (ZECC) is a low-cost and environmentally friendly cold storage alternative. This study aims to determine the combination of zeolite particle size combined with sand as a cooling medium on the ZECC wall that produces a shelf room temperature according to the temporary storage needs of cherry tomatoes. Cherry tomatoes were stored in retail (250 g) and bulky (1500 g) packaging to assess the effectiveness of the packaging in maintaining quality. Parameters measured included moisture content, texture, color, vitamin C content, and organoleptic. The results showed that chamber 1 (zeolite No. 1 mesh 14-20) was more stable than chamber 2 (zeolite No. 2 mesh 8-16). When loaded, the temperature of chamber 1 ranged from 24.6°C to 27.7°C with RH 94.7% to 95.4%. Retail packaging gave the best results with an organoleptic score of 4.03-4.16 on day 15, higher than the control. The vitamin C content in the retail packaging reached 35.83 mg/100 g, higher than the control (28.94 mg/100 g).
Portable Minapadi Model and Its Performance for Urban Farming
The conversion of agricultural land to non-agricultural uses has threatened the food supply of urban areas. While there are many unused open spaces in the areas that would have the potential to produce certain foods that are regularly consumed. It is then necessary to introduce cultivation techniques that match the area’s conditions and operable by the people with no, or less experience in farming. This study aims to come up with a portable Minapadi (paddy and fish) culture deemed suitable for urban farming and identify its performance to produce rice as well as fish. The model was tested for one season (99 days) with the main parameters observed being water balances, rice and fish production and revenue. Applying automatic irrigation without using electricity, the irrigation water consumption was 738 mm with an efficiency of 54%. Land and water productivity were 3.62 tons/ha and 0.96 kg/m³, respectively. The fish survival rate was 85% with total production of 3.34 kg and feed efficiency of 2.74. This model earned IDR7,054.94/m³ for rice and IDR36,989.82/m³ for fish with total revenue of IDR44,044.76/m³. These results confirmed that this minapadi model has potential application to support the development of urban agriculture.
Analysis of Headloss in Controlled Recirculating Aquaculture System for Fish Heatcheries
Conventional fish hatchery has many challenges such as large land use, excessive water use, environmental pollution and a controlled maintenance system, making the fish hatchery process inefficient. The application of the development of the Controlled Water Recirculation System (SRAT) can be a solution to overcome this problem. This study aims to obtain a water balance model, and determine the amount of pressure loss that occurs in the SRAT piping network, in order to improve the performance of SRAT by maintaining the uniformity of water discharge in each water tank in the SRAT. At first, the average discharge was 2,134 L/min with a uniformity value of only 79%. After the intervention of the model, the uniformity value increased to 99% with an average of 1,869 L/min. It can be concluded that the model built can maintain the uniformity of water discharge in each tub contained in the SRAT
Improvement of cured vanilla pod qualities (Vanilla Planifolia A.) with a combination of advanced sweating and drying methods”.
Cured vanilla pods are raw food materials that are used as flavor and aroma agents in various foods, such as ice cream, cookies, and syrup. Cured vanilla pods are produced by farmers through long post-harvest handling, including harvesting, withering, sweating, and drying, with high variation in quality. This research aims to study the combination of advanced sweating and drying methods to improve the quality of cured vanilla pods and shorten the drying time. Approximately 33 kg of harvested vanilla pods was subjected to a withering process by soaking in hot water at a temperature of 60-65°C for 2 min, followed by a sweating process for 48 h. Subsequently, the vanilla pods were treated with three duration times of advanced sweating (4,6, and 8 days) and two drying methods (greenhouse effect/GHE solar dryer and tray dryer). These processes were continued until the water content reached 30-35%. Physicochemical measurements and organoleptic tests were carried out to monitor the quality change of the vanilla pods during the treatments. The results showed that adding advanced sweating for 4, 6, and 8 days in the drying process significantly affected the water content, color, and vanillin content of cured vanilla pods. Vanilla pods treated with advanced sweating for 8 days in the tray dryer method produced the best quality cured vanilla pods with a shorter drying time of 8 days, compared with traditional drying for 20 days and the GHE solar dryer for 10 days to reach the desired water content (35%).
advanced sweating, drying, quality, vanilla pod, vanillin
Low-Temperature Carbonization on Biochar from Agricultural Waste for Heavy Metal Removal
Biochar from agricultural waste has many applications in the field of agricultural and wastewater treatment. In this study, biochar derived from exhausted kahwa coffee (EKC) was produced at low carbonization temperatures (200–400°C) for the removal of copper (II) ions (Cu2+) from aqueous solutions. The EKC biochar exhibited a removal efficiency of 92.5% under optimal conditions. The biochar was also subjected to surface characterization for further investigation of the varied capacity removal of the EKC biochar at low temperatures. BET analysis was performed on the EKC biochar to gather information on the surface area and pore size, and the structure of the formed pores was imaged using SEM. Furthermore, the elemental content and functional groups on the surface of the EKC biochar were determined by EDX and FT-IR analyses. The results showed that the surface and pore sizes of the EKC biochar had an interplay with the capacity removal of the EKC biochar during low-temperature carbonization. Meanwhile, it was also confirmed that the elemental ion content and the surface functional groups showed a stronger relation to the removal capacity of the EKC biochar at each low temperature applied.
Biochar, carbonization, exhausted kahwa coffee (EKC), low temperature, surface characterization
Software Development of Palm Oil Seed Authentication System Based on Ultrasonic Waves
Fake palm oil seeds pose a substantial economic threat, which makes their authentication crucial. However, distinguishing between genuine and fake seeds remains a challenge. This study explored the potential of ultrasonic technology to measure shell thickness as a distinguishing factor based on the reported variations between the two types. Ultrasonic wave measurement software was developed using Arduino Uno to facilitate the analysis. The results highlight the complexity of accurately measuring the seed shell thickness owing to high attenuation. Micro-CT imaging confirmed the presence of pores within the seed structure, which significantly scattered and absorbed ultrasonic waves, limiting the penetration depth and accuracy. Despite these obstacles, the developed software exhibited promising capabilities, accurately determining the thickness or propagation speed with a high-resolution time-of-flight measurement of up to 62.5 nanoseconds. Additionally, the software is capable of sampling ultrasonic signals at frequencies up to 178 kHz. Although the software performs well under specific conditions, further advancements in ultrasonic technology are necessary to mitigate porosity-related limitations and enhance the effectiveness of seed authentication methods, particularly in transducer selection and measurement techniques such as Harmonic or QSC testing.
Palm oil seed, Ultrasound, Arduino uno, Software, Fake Seeds
Estimating the Shelf Life of Instant Tempe in Various Packaging and Storage Temperature using the Arrhenius Model
Tempe is a nutritious food that is popular with many people. The problem is that tempe has a short shelf life and must be consumed immediately. Instant tempe is one of the innovative tempe products with a longer shelf life. This research aims to analyze the shelf life of instant tempe in various packages and at different storage temperatures using the Arrhenius model. The method used in this research was laboratory experimental, using 378 samples of instant tempe which were packaged in vacuum packaging, non-vacuum packaging, and cup packaging, and stored at cold temperature (12°C), room temperature (27°C), and hot temperature. (35°C). There are nine treatment combinations regarding the relationship between packaging and temperature, each treatment is carried out 3 times. Measurements for each treatment are carried out until the instant tempe cannot ferment to become tempe ready for consumption. This shows that the fungus Rhizopus oligosporus has died. The research results show that the CIE L* value of instant tempe decreases as the storage period for instant tempe increases. The shelf life of estimation results using the Arrhenius model for vacuum packaging and storage temperatures of 12°C, 27°C, and 35°C respectively is 36.98 days, 6.88 days, and 3.00 days. The use of non-vacuum packaging and storage temperatures of 12°C, 27°C, and 35°C were respectively 15.84 days, 5.63 days, and 2.38 days. In comparison, the use of cup packaging and storage temperatures of 12°C, 27 °C, and 35°C respectively are 17.62 days, 6.31 days, and 2.80 days.
Shelf life, Instant tempe, Storage temperature, Packaging, Arrhenius model.