Journal of Applied Agricultural Science and Technology

Tropical Almond–Based Yogurt Fortified with Celery: A Functional Food for Lipid Profile Improvement and Anti-Inflammatory Support

2025-11-10T15:20:41+07:00

The development of yogurt as a functional food has gained significant attention. Tropical almond (Terminalia catappa) is rich in fat and protein, while celery is known for its antioxidant, anti-inflammatory, hypolipidemic, and hypoglycemic properties. This study investigated the development of functional yogurt made from tropical almond milk fortified with celery extract. It employed a Completely Randomized Design (CRD) with varying celery extract concentrations (1%, 2%, and 3%) and fermented for 14, 17, and 20 hours. The results showed that after 17 hours of fermentation, total acid-producing bacteria reached 7.87 log CFU (colony forming unit)/ml, exhibiting acceptable sensory attributes and enhanced antioxidant activity. In vivo tests on Wistar rats revealed significant reductions in malondialdehyde (MDA) and interleukin-6 (IL-6) levels, which indicate anti-inflammatory and lipid-lowering effects. These findings highlight the potential of tropical almond-based yogurt as a novel functional food, paving the way for sustainable dietary interventions targeting metabolic health.

Phytochemical Screening and Antioxidant Capacity of Banana Peel Ethanol Extract of Ketip (Musa paradisiaca Forma Typiaca) on Sperm Concentration and Motility of Mice (Mus musculus)

2025-08-04T10:38:41+07:00

This study examines the effect of ethanol extract of banana peel ketip (Musa paradisiaca Forma Typiaca) on sperm concentration and motility of mice (Mus musculus) following cigarette smoke exposure. This study aims to determine the phytochemical content and antioxidant capacity of the extract after cigarette smoke exposure. This study began with extracting chemical compounds from the sample, followed by phytochemical screening to determine their content. The antioxidant capacity of the extract was examined using the DPPH method with a UV-Vis spectrophotometer and an in vivo test using adult male mice. Sperm concentration and motility data were analyzed by one-way ANOVA and Tukey’s HSD test. The phytochemical screening results showed that the ketip banana peel ethanol extract contains terpenoids, alkaloids, flavonoids, tannins, and saponins. The DPPH test results showed that the IC₅₀ value of the extract was 554.84 ppm. Statistical analysis of the in vivo data showed that the ethanol extract of ketip banana peel significantly increases sperm concentration (p value = 0.005486; F value 4.197422; F critical= 2.510158) and motility (P value= 0.0000; F value =41.59092; F critical= 2.510158) following cigarette smoke exposure. Tukey’s HSD analysis of sperm concentration (HSD score = 2.271) showed that the 5000 ppm extract significantly increases sperm concentration without cigarette smoke exposure and sperm concentration after 5 minutes of cigarette smoke exposure. Nevertheless, this treatment failed in restoring sperm concentration following 30 minutes of cigarette smoke exposure. This indicates that longer duration of cigarette smoke exposure causes severe damage to sperm production (spermatogenesis) that is difficult to restore, even with high-dose treatment. Tukey’s HSD analysis of sperm motility (HSD score = 0.207) showed that treatment with the ethanol extract of Ketip banana peel alone insignificantly increases sperm motility. The decrease in sperm motility after cigarette smoke exposure was significantly restored with high doses of the peel extract. These findings suggest that the sperm maturation stage, where the sperm motility is determined, was protected by antioxidant substances contained in the ethanol extract of Ketip banana peel.

Quality Assessment of Used Palm Cooking Oil Processed by Microfiltration Using Whatman Filter Papers with Different Pore Sizes

2025-12-27T17:06:27+07:00

Microfiltration is a preliminary treatment in the production of biodiesel. This method is characterized by its simplicity and its environmental friendliness. It can reduce foam production during the saponification process, which is generally concomitant with the esterification process. Furthermore, microfiltration process does not involve the use of chemicals. The micropore size of the filter greatly influences the quality of the biodiesel produced, given its impact on impurities present in the oil used. The present study sought to determine the effect of microporous membrane size on the quality of used frying oil. The treatment variables in this study were the micropore sizes of the Whatman filter paper used: 2.5 μm, 8 μm, 11 μm, 16 μm, 20 μm, and 25 μm. Meanwhile, the observation variables encompassed the free fatty acid (FFA) content, acid number, viscosity, and water content of the used cooking oil. The findings of the study indicate that the microfiltration treatment employing filter paper with 2.5 μm pore size yielded the best results, with free fatty acid (FFA) level, acid number, viscosity and water content of 0.00238%, 0.411 mg KOH/g, 3.2843 cSt and 0.00068%, respectively. In accordance with the stipulations outlined in the Indonesian National Standard (SNI) 7128:2015, the microfiltered oil obtained in this study is deemed suitable for use as a raw material in biodiesel production.

A Review : Utilization of By-Products from Areca Nut and Coconut Processing as Environmentally Friendly Biobriquettes

2025-07-08T09:24:04+07:00

Large quantities of by-products from areca nut and coconut processing generated annually have significant potential as solid fuel feedstocks due to their high lignocellulosic content. Optimal utilization of these residues can increase their added value and reduce the environmental impacts associated with organic waste. This study aimed to explore the manufacturing process and characteristics of biobriquettes made from biomass waste in the form of areca nut husk, coconut husk, and coconut shell. These raw materials were processed through the stages of cleaning, drying, carbonation, refining, mixing with adhesives, molding, and drying. The use of adhesives such as tapioca flour, sago, or palm oil liquid waste affects the quality of biobriquettes, including their moisture content, ash content, calorific value, density, and combustion rate. The results of the study revealed that biomass-based biobriquettes have several advantages, such as being cost-effective, environmentally friendly, and producing a high calorific value. This study provides scientific and practical benefits to the processing of biomass waste into renewable energy with high economic value. The utilization of this waste not only enhances renewable energy production but also reduces agricultural waste and environmental pollution.

Rice Deep Knowledge Graph-Based Expert System: An Intelligent Solution for Identifying Rice Pests and Diseases

2025-10-18T16:04:03+07:00

Accurate diagnosis of rice pests and diseases is essential but often challenging using traditional methods, which are time-consuming and prone to human error. In this study, we propose the Rice Deep Knowledge Graph (RiceDKG) Expert System, which integrates deep learning techniques, particularly Long Short Term Memory (LSTM), with a Knowledge Graph to enhance symptom pattern-based diagnosis accuracy. This hybrid approach captures relationships among rice plant symptoms while leveraging systematically constructed domain knowledge. The system was evaluated on a dataset of 25 test cases, encompassing various symptoms such as brown spots, leaf curling, and fungal damage. Evaluation results demonstrate an overall accuracy of 84%, with 21 out of 25 cases correctly diagnosed, compared to expert evaluations. These findings indicate that integrating LSTM with knowledge graphs improves the system's ability to handle diverse diagnostic scenarios.

Reclamation of Post-Gold Mining Land Using Mycotrichocompost and Biochar: Effects on Corn (Zea Mays L.) Growth and Yield

2026-01-21T18:40:18+07:00

Post-gold mining lands are severely degraded ecosystems requiring intensive restoration to recover their agricultural productivity and ecological functions. One promising approach to enhance soil biological, chemical, and physical properties is the application of biochar combined with mycotrichocompost. This study aims to evaluate the effects of biochar and mycotrichocompost on soil nutrient availability (N, P, K) and on the growth and yield of maize cultivated on post-gold mining soil. The study used a factorial randomized block design: level 1 giving Biochar (0 tons/ha, 4 tons/ha, 8 tons/ha, 12 tons/ha), and level 2 fertilizer application mycotrichocompost at different doses (0 tons/ha, 5 tons/ha, 10 tons/ha), resulting in 12 treatment combinations resulting in total 36 experimental units. Data were analyzed using analysis of variance (ANOVA), followed by Tukey's Honest Significant Difference (HSD) test at α = 0.05 using minitab 19. The addition of biochar and mycotrichocompost to former gold mining soil increased crop yields (9.93 tons/ha), plant growth (e.g., plant height: 152.3 cm and leaf length: 80.33 cm), physiological characteristics (e.g., chlorophyll a: 0.34 mg per gram of fresh leaf weight, chlorophyll b: 0.24 mg per gram of fresh leaf weight), and soil nutrient content (N: 0.14%, P: 271 ppm, and K: 1.87 ppm). In general, treatment A3B2 with a dose of 12 tons/ha of biochar plus 10 tons/ha of mycotrichocompost is the optimal combination.

Spatial Heterogeneity of Rice Production Responses to ENSO Anomalies in Banten Province, Indonesia

2025-11-10T18:21:52+07:00

El Niño–Southern Oscillation (ENSO) anomalies are significant drivers of climate variability affecting agricultural production, although their impacts exhibit high spatial and temporal complexity. This study investigates rice production responses to ENSO phases in four districts of Banten Province, Indonesia—Pandeglang, Serang, Lebak, and Tangerang—during the 2000–2024 period. Utilizing descriptive statistics, OLS regression, and comparative time-series models (linear, quadratic, exponential, and moving average), the study evaluates how climatic signals are translated into production outcomes. Results reveal significant spatial heterogeneity. Although El Niño generally suppressed yields, regression analysis identifies Tangerang as the only district with a statistically significant vulnerability to drought-induced losses (β= -33,371 t/year). Conversely, the study identifies a "Triple-Dip" La Niña anomaly (2020–2023) where excessive rainfall reduced production in flood-prone districts such as Pandeglang, challenging the assumption that La Niña universally benefits rice yields. Methodologically, second- and third-order moving average models (MA(2) and MA(3)) consistently outperformed alternative specifications in capturing stochastic fluctuations. These findings underscore the localized nature of ENSO impacts and the inadequacy of generalized policies. The study therefore advocates spatially differentiated adaptation strategies, including localized early warning systems and improved drainage infrastructure, to mitigate drought and flood risks in Banten’s rice systems.

Application of Ultrasonic Technology in Modifying Tapioca Starch for Improving the Quality of Gluten-Free Noodles

2025-12-25T18:40:41+07:00

Excessive gluten intake may provoke health problems in susceptible individuals, requiring gluten-free noodle substitutes. Tapioca possesses the potential to serve as an alternative to wheat flour; nevertheless, its inherent stickiness, propensity to soften, and limited elasticity require modification. This study utilized tapioca flour modified by ultrasound at two frequencies (20 kHz and 40 kHz) and three duration intervals (40, 45, and 50 minutes). The altered starch was subsequently employed to prepare noodles including a blend of rice flour, eggs, and salt. The measured metrics comprise texture, water absorption capacity, cooking loss, water solubility index (WSI), and swelling power. Data were examined utilizing ANOVA, followed by an LSD test at a 5% significance threshold. The findings indicated that both sonication frequency and duration significantly influenced all evaluated parameters. Raising the frequency to 40 kHz and extending the sonication duration to 50 minutes enhanced texture (121.50 gf), water absorption capacity (34.48%), water solubility index (WSI) (7.03%), and swelling power (4.05%), while concurrently increasing cooking loss to 58.47%. Ultrasonic modification has proven to be an eco-friendly technique for enhancing the functional attributes of tapioca, with prospective applications in the diversification of gluten-free noodle products.

Shelf-Life Estimation of Black, Red and Yellow Honey Coffee Using Critical Moisture Content Approach

2026-01-04T13:53:10+07:00

Honey process is a newly developed coffee processing technique. Based on the washing intensity, honey coffee categorized into black, red, and yellow honey coffee. Once the green bean coffee obtained, they are roasted then ground. However, the shelfs-life of Arabica honey-processed ground coffee has not yet been estimated. Therefore, this study aimed to predict the shelf life of Arabica honey-processed ground coffee (black, red, and yellow honey) using the critical moisture content approach. The analysis in this study was conducted descriptively so that it can explain the predicted shelf life of honey ground coffee stored in metallized plastic packaging. The results indicated that the critical moisture content for yellow, red, and black honey ground coffee products was 5.55% (db), 7.44% (db), and 8.51% (db), respectively. The moisture sorption isotherm (MSI) curves were described by the linear equations y = 1.0672x - 0.741 for yellow honey, y = 2.3315x - 1.6017 for red honey, and y = 0.55x - 0.308 for black honey. Using the Labuza equation at 80% relative humidity (RH) and 30°C, the estimated shelf life of Arabica ground honey coffee in metallized plastic packaging ranges from 2.51 to 2.67 years.

CHIRPS-Based Spatio-Temporal Rainfall Analysis as a Basis for Evaluating Cropping Pattern Suitability in Coastal West Sumatra

2026-01-29T19:12:32+07:00

Rainfall variability, in terms of amount, distribution, and timing, can increase the risk of crop failure and reduce crop yields. This study aims to analyze CHIRPS (Climate Hazards Group InfraRed Precipitation with Stations) rainfall dynamics across several coastal areas of West Sumatra and to evaluate agroclimatic zones to assess the suitability of climate-adaptive cropping patterns. Monthly rainfall data for the period 1995-2024 were analyzed using the IDW interpolation method to produce rainfall distribution maps. This study also classified agroclimatic zones using Oldeman's classification to assess the suitability of cropping patterns. The analysis showed significant annual rainfall fluctuations, with high rainfall dominating the 1995-2014 period and a decline in the 2015-2024 period. Changes in monthly rainfall patterns, particularly the increase in rainfall from March to May during the 2015-2024 period, may affect planting times and irrigation management. The three regions studied (Padang Pariaman, Pariaman, and Padang) are in climate zone A1, with more than 9 consecutive wet months, allowing year-round rice cultivation. However, rainfall fluctuations require adjustments in planting timing and the selection of secondary crops that are more drought-resistant. The results of this study provide a stronger basis for agricultural planning that is more adaptive to climate change, with recommendations for adjustments to the planting calendar and irrigation management to ensure the sustainability of efficient and sustainable agricultural production.

Detection of Spodoptera exigua (Hübner) Larval Infestation on Leeks and Shallots: A Case Study in North Tapanuli and Karo, North Sumatra, Indonesia

2025-08-08T15:48:05+07:00

North Sumatra Province is the eighth largest producer of shallots (Allium cepa) in Indonesia (1.09%, 53,962 tons). Declining shallot production is primarily caused by attacks by pests and pathogens, which are responsible for 20–100% decreases in yields. Spodoptera exigua larvae are among pests with significant effects on shallot productivity. This study aimed to determine the effectiveness of various methods of monitoring Spodoptera exigua infestation on shallots, particularly of the Batu Ijo and Brebes varieties, including the use of yellow sticky traps, blue ball traps, sweep nets, and hand-picking, for the purpose of increasing farmers' income in North Tapanuli and Karo, Sumatra Utara. The research was conducted in Parhorboan Village, Pagaran Sub-district, North Tapanuli Regency, and Juhar Sub-district, Karo Regency, North Sumatra, from June to July 2024. To be precise, it was conducted in three farmers' planting areas, using the diagonal slice method with five sub-plots and observations with one-week intervals at the sampling locations. The results showed that the infestation by S. exigua larvae was higher on shallots than on leeks. The highest average number of larvae recorded on leeks was 0.78 larva per plant, while shallots had an average of 1.84 larvae per plant. Furthermore, the highest average percentage of S. exigua larval infestation on leeks was 16.78%, while the infestation on shallots reached 32.15%. The intensity of S. exigua infestation fell within the 3–5 categories, which correspond to medium to very high levels. The independent sample t-test results showed significant differences in both the population and infestation percentage of S. exigua larvae in the leek and shallot planting areas.

Applications of Internet of Things, Remote Sensing, and AI for Precision Agriculture and its Adoption Status in Nepal

2025-08-02T15:54:42+07:00

Modern technologies combined with precision agriculture have made revolutionary advances in the field of agriculture. The Internet of Things (IoT), remote sensing, wireless sensor networks, machine learning, and smart farm management systems have brought agriculture into a new era. In this context, the purpose of this review is to summarize the most recent advanced tools and their potential directions for further research by synthesizing the recent literature. Sensors, robotics, global positioning systems (GPS), satellites, and aerial imaging drones have facilitated data-driven actions, programmed management, and real-time monitoring in agricultural systems. These tools, when combined with Artificial Intelligence (AI) and machine learning, enable real-time decision-making and smart farm management. Some advanced applications include computer-based image recognition in weed control robots, early pest and disease detection through image identification, irrigation based on field water, fertilizer application through soil nutrient mapping, livestock health tracking through behavioral biometrics, and yield prediction analytics to inform breeding and harvest planning. The emergence of "digital agriculture" paradigms, such as Agriculture 4.0, signifies the convergence of interconnected intelligent farm management systems. In Nepal’s setting, the growing use of mobile apps and Information and Communication Technology (ICT)-enabled advice services provides smallholder farmers with crucial, location-specific information even in the absence of advanced technical infrastructure. Precision agriculture technologies have enormous promises to meet the country’s food demand. However, data privacy, technical proficiency, and technology accessibility must be resolved simultaneously. The discussion of policies and collaborative tactics required to ensure precision agricultural technology empowers rather than displaces poor food producers. Seventy-three scholarly articles on the topics of IoT, AI and precision agriculture were reviewed to introduce relevant concepts, ideas and implementations to offer a framework for the application of novel technologies in the Nepali agricultural landscape.