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Journal of Applied Agricultural Science and Technology
Published by Green Engineering Society
ISSN : 26214709     EISSN : 26212528     DOI : https://www.jaast.org/index.php/jaast/article/view
Core Subject : Agriculture,
Agriculture, Biological Sciences & Forestry
Journal of Applied Agricultural Science and Technology (JAAST) is an international journal, focuses on applied agricultural science and applied agricultural technology in particular: agricultural mechanization, food sciences, food technology, agricultural information technology, agricultural economics, agricultural statistics, bioinformatics, farm structure, farm power, agricultural machinery, irrigation and drainage, land and water resources engineering, renewable energy, environment, crop production, and crop protection.
Arjuna Subject : Ilmu Pertanian dan Biologi (Semua) - Agronomi dan Ilmu Tanaman
Articles 157 Documents
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Organic and Biofertilizers as Replacements for Synthetic Fertilizers to Increase Rice Yield in Tidal Swamp Abduh, Andin Muhammad; Masganti, Masganti; Sari, Nukhak Nufita; Haris, Abdul; Ifansyah, Hairil; Mulyawan, Ronny
Journal of Applied Agricultural Science and Technology Vol. 8 No. 4 (2024): Journal of Applied Agricultural Science and Technology
Publisher : Green Engineering Society

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55043/jaast.v8i4.292

Abstract

Maintaining soil sustainability to increase and sustain land productivity can be achieved by minimizing synthetic fertilizers and maximizing organic fertilizers and biofertilizers, especially in suboptimal lands. Therefore, this study aimed to determine the effects of organic fertilizers and biofertilizers with reduced NPK (Nitrogen, Phosphate, Potassium) dosage on increasing rice yield in tidal swamp areas in Tebas Sungai Village, West Kalimantan. The procedures were carried out using a complete randomized block design, with several treatments consisting of 175 kg ha-1 NPK as a control (P0), 130 kg ha-1 NPK + 1.5 tons ha-1 cow manure (P1), 130 kg ha-1 NPK + 3.0 tons ha-1 cow manure (P2), and 130 kg ha-1 NPK + 25 kg ha-1 biofertilizers (P3). Based on assessment, the study area was then categorized as C overflow type. The results showed that the combination of NPK synthetic fertilizers with cow manure led to a 15.1%, 25%, 5.6%, and 5.4% increase in total tillers, total grains per panicle, weight of 1000 grains, and rice yield, respectively. In addition, the use of NPK fertilizers with biofertilizers increased total tillers, total grains per panicle, weight of 1000 grains, and rice yield by 24.6%, 56%, 7.7%, and 18%, respectively, compared to only NPK fertilizers. Based on these results, improving rice performance in tidal swamp areas could be achieved by integrating organic or biofertilizers with synthetic fertilizers.
The Influence of Different Light Intensity on the Growth of Zoysia matrella Seeds Utami, Sari Widya; Pratiwi, Artdhita Fajar; Aji, Galih Mustiko
Journal of Applied Agricultural Science and Technology Vol. 8 No. 4 (2024): Journal of Applied Agricultural Science and Technology
Publisher : Green Engineering Society

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55043/jaast.v8i4.303

Abstract

Zoysia matrella is a type of highly valued grass, but the seedling time is very long due to the slow growth rate. Several studies have been conducted using artificial light as a light source to accelerate indoor plant production. However, this technology is yet to be widely used for seed production. Therefore, this study aimed to obtain optimal light intensity from artificial light in accelerating Zoysia matrella seedling time. The treatment in the form of Light Emitting Diode (LED) illumination given to increase the growth of Zoysia seedlings consisted of 5 levels, namely 20, 40, 60, 80, and 100 (μmol/m2/s). The parameters studied were germination percentage, germination rate, and vegetative measurement in the form of seedling height in Zoysia nursery chamber equipped with artificial light. The results showed that the artificial illumination technology in the nursery chamber increased the speed of seedling time in the germination and growth phases of Zoysia seeds.
The Effect of Cultivation Media on Matriconditioning Technique and the Concentration of Onion Peel Waste PGR on the Viability and Yield Rice (Oryza sativa) Through the Metabolic Activity of the Seed Amany, Alfiyyah Nur; Setiyono, Setiyono; Sholikhah, Ummi; Ratnasari, Tri; Meliala, Susan Barbara Patricia Sembiring; Arum, Ayu Puspita; Savitri, Dyah Ayu
Journal of Applied Agricultural Science and Technology Vol. 9 No. 2 (2025): Journal of Applied Agricultural Science and Technology
Publisher : Green Engineering Society

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55043/jaast.v9i2.184

Abstract

A major limiting factor for rice production in the tropics is the decline in seed quality due to storage duration and environmental conditions. Rice seeds are often stored for extended periods, making seed expiration unavoidable. Expired seeds frequently undergo quality deterioration. Therefore, an effective approach is needed to mitigate quality decline and sustain rice production. This study aims to evaluate the effectiveness of different matriconditioning techniques and various concentrations of onion peel waste-derived plant growth regulators (PGRs) in maintaining seed viability and rice yield. The research was conducted using a Completely Randomized Design (CDR) with a two-factor experimental setup and three replicates. The first factor was the matriconditioning medium, consisting of three levels: M1 (soil), M2 (soil + husk charcoal), and M3 (soil + husk ash). The second factor was the concentration of onion peel waste-derived PGR, consisting of four levels: K1 (0% – water), K2 (25% – 250 mL onion peel waste PGR per 1000 mL), K3 (50% – 500 mL onion peel waste PGR per 1000 mL), and K4 (75% – 750 ml onion peel waste PGR per 1000 mL). The results showed that matriconditioning with soil and husk charcoal, along with 25% onion peel waste-derived PGR, enhanced rice seed viability. Additionally, a 75% concentration of onion peel waste PGR significantly influenced the weight of 1000 grains and the total harvested grain weight.
The Analysis of Architectural YOLOv5 Convolutional Neural Networks for Detecting Apple Leaf Diseases Erkamim, Moh.; Subarkah, Muhammad Zidni; Soelistijono, R.
Journal of Applied Agricultural Science and Technology Vol. 9 No. 1 (2025): Journal of Applied Agricultural Science and Technology
Publisher : Green Engineering Society

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55043/jaast.v9i1.251

Abstract

Apple cultivation is crucial to agricultural economies, particularly in regions with sub-tropical climates, such as Indonesia, where apple farming is expanding rapidly. However, managing diseases and pests is essential for maintaining optimal crop yields, as they can significantly reduce production. Among the common diseases affecting apple trees are Scab, Black Rot, and Cedar Apple Rust, which primarily impact leaves and threaten the total health of the plant. Therefore, this research aimed to develop an effective model for detecting apple leaf diseases using the architectural YOLOv5 Convolutional Neural Networks (CNNs). The analysis was conducted between November 2022 and February 2023 at the Smart City Information System (SIKC) laboratory, including 120 apple leaf samples collected from Tawangmangu. Additionally, secondary data containing 30 images for each disease category, consisting of Healthy, Scab, Black Rot, and Cedar Apple Rust, were used as a benchmark. The performance of YOLOv5 was evaluated based on several metrics, including Precision, Recall, mAP@0.5, and mAP@0.5:0.95. The results showed that Cedar Apple Rust was the most prevalent disease identified among the samples. YOLOv5 performed exceptionally well in detecting disease symptoms, achieving a Precision score of 0.810, Recall of 0.981, mAP@0.5 of 0.950, and mAP@0.5:0.95 of 0.765 on the test dataset. These results showed that the proposed model was highly accurate and reliable for the early detection of apple leaf diseases, offering significant potential for improving disease management strategies and increasing the efficiency of apple production.
Performance Enhancement of Mixing Impellers Based on Mixture PPM Analysis Pratama, Aditya Tirta; Zuardi, Gunawan
Journal of Applied Agricultural Science and Technology Vol. 9 No. 1 (2025): Journal of Applied Agricultural Science and Technology
Publisher : Green Engineering Society

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55043/jaast.v9i1.266

Abstract

Achieving optimal fertilizer mixing is crucial for farmers, as it directly affects product quality, homogeneity, and overall production efficiency. However, the exact degree of mixing uniformity remains uncertain due to the lack of TDS meters or sensors in the field. This research aims to compare the performance of a novel paddle and PBT-4 impeller while generating empirical data that can serve as a reference for mixing NPK fertilizers. The findings will help farmers to determine the appropriate mixer and optimal mixing duration. The Define-Measure-Analyze-Improve-Control (DMAIC) approach was employed to develop and implement the proposed mixing impellers. Comparative analysis indicates that the novel paddle outperforms the PBT-4 impeller in mixture homogeneity, as evidenced by its lower Coefficient of Variation (COV) of 0.00163 compared to 0.0229. No significant difference was observed in the time required to reach steady ppm or settling time. Ppm is a crucial parameter for assessing mixing uniformity and product quality. While both the Paddle and 4-blade PBT exhibited similar mixing times, the Paddle demonstrated slightly superior performance in achieving uniformity.
Deep Learning Approaches for Plant Disease Diagnosis Systems: A Review and Future Research Agendas Riyanto, Verry; Nurdiati, Sri; Marimin, Marimin; Syukur, Muhamad; Neyman, Shelvie Nidya
Journal of Applied Agricultural Science and Technology Vol. 9 No. 2 (2025): Journal of Applied Agricultural Science and Technology
Publisher : Green Engineering Society

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55043/jaast.v9i2.308

Abstract

To identify novel advancements in plant diseases detection and classification systems employing Machine Learning (ML), Deep Learning (DL), and Transfer Learning (TL), this research compiled 111 peer-reviewed papers published between 2019 and early 2023. The literature was sourced from databases such as Scopus and Web of Science using keywords related to deep learning and leaf disease. A structured analysis of various plant disease classification models is presented through tables and graphics. This paper systematically reviews the model approaches employed, datasets utilized, countries involved, and the validation and evaluation methods applied in plant disease identification. Each algorithm is annotated with suitable processing techniques, such as image segmentation and feature extraction, along with standard experimental metrics, including the total number of training/testing datasets utilized, the quantity of disease images considered, and the classifier type employed. The findings of this study serve as a valuable resource for researchers seeking to identify specific plant diseases through a literature-based approach. Additionally, the implementation of mobile-based applications using the DL approach is expected to enhance agricultural productivity.
Groundwater Recharge Assessment in the Gunungsewu Karst Area Using the APLIS Method and a Modified Soil Physics Approach Mujiyo, Mujiyo; Surachman, Rinta Faradila; Sumani, Sumani; Ariyanto, Dwi Priyo
Journal of Applied Agricultural Science and Technology Vol. 9 No. 1 (2025): Journal of Applied Agricultural Science and Technology
Publisher : Green Engineering Society

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55043/jaast.v9i1.313

Abstract

Karst areas experience annual drought, making it essential to preserve potential groundwater recharge areas. This study aims to assess the level of groundwater recharge and its spatial distribution in karst regions, with a case study in the Gunungsewu karst area, Paranggupito sub-district, Wonogiri Regency. This research employed the APLIS method (Altitude, Slope, Lithology, Infiltration and Soil) and collected data by creating a Land Mapping Unit (LMU) map. The LMU was generated through an overlay of land use, soil type, slope, rock type, and rainfall, resulting in 20 LMUs. The observed parameters included elevation, slope, soil type, lithology, soil infiltration, and texture, with modification incorporating porosity as an actual soil parameter. Observations and sampling were conducted, and data analysis involved ANOVA and correlation tests to assess the influence of topography on groundwater recharge distribution and its correlation with soil characteristics. The research results indicate that groundwater recharge is classified into medium and high categories. The distribution of groundwater recharge is influenced by topography and soil infiltration, with the highest recharge occurring on slopes of 0-3% and high infiltration values.
Experimental Study on Soaked Corn Cobs as Feedstock for Biomass Gasification in an Open Downdraft Gasifier Kosim, Muhtar; Kasda, Kasda; Saputra, Dede Iman; Kurnia, Yuda; Setioputro, Novandri Tri
Journal of Applied Agricultural Science and Technology Vol. 9 No. 2 (2025): Journal of Applied Agricultural Science and Technology
Publisher : Green Engineering Society

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55043/jaast.v9i2.330

Abstract

Fossil fuels, which account for 83% of Indonesia's total energy supply, are depleting and environmentally unsustainable. Corn cob biomass, with an annual yield of 4.34 million metric tons, presents a viable alternative. Through gasification at temperatures of 700–1200°C, corn cobs can be converted into combustible gas or syngas. To enhance syngas yield, the corn cob gasification process can be optimized by increasing moisture content through soaking. However, experiments with soaked corn cobs have shown a significant decline in temperature and gasification zone performance. The gasification temperature decreased from 1024°C to 614°C, falling below the 700°C threshold. Additionally, the gasification zone shifted significantly downward in the reactor. This reduction is attributed to the high moisture content of the corn cobs, which exceeded 30%, reaching 56.78%, allowing the gasification process to last for 48 minutes. Before the gasifier ceased operation, syngas production achieved a promising average thermal power of 1.76 kW with an efficiency of 7.14%. These findings indicate that soaked corn cobs can serve as biomass gasification feedstock, provided the moisture content does not exceed 30%.
Effectiveness of Fly Ash, Dolomite, and Organic Fertilizers in Enhancing Oil Palm Seedling Growth Pramudya, Yudhi; Hanum, Farrah Fadhillah; Muhammad, Azrian Makmum; Wardhana, Budi Setya; Pamungkas, Saktiyono Sigit Tri
Journal of Applied Agricultural Science and Technology Vol. 9 No. 1 (2025): Journal of Applied Agricultural Science and Technology
Publisher : Green Engineering Society

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55043/jaast.v9i1.335

Abstract

Oil Palm (Elaeis guineensis Jacq.) is a crucial plantation commodity in Indonesia's economy. The increasing global demand for oil palm has driven the expansion of oil palm plantations. However, this expansion is often constrained by limited fertile land. Fly ash, a byproduct of coal combustion, contains essential nutrients such as calcium, magnesium, and silica. Several studies suggest that fly ash potentially improves soil physical and chemical properties, as well as enhance nutrient availability for plants. This research aims to evaluate the effectiveness of adding fly ash in various growing media, dolomite, and organic fertilizers on the growth of oil palm seedlings. The study employs a Completely Randomized Design (CRD) with several treatment combinations, including fly ash, organic fertilizer, dolomite, and NPK 16:16:16 fertilizer doses. The results indicate that combining fly ash and organic fertilizer is the best choice for improving oil palm seedling growth. Additionally, adding NPK 16:16:16 fertilizer at 36 grams per polybag yields excellent growth results. Interaction analysis indicates significant effects of these combinations on seedling growth improvement. This preliminary study is expected to provide foundational information useful for further research on utilizing fly ash and other organic materials in oil palm cultivation and the potential application of this technology on a larger scale.
Properties of Instant Sourdough from Papaya (Carica papaya L.) Natural Starter and Its Effect on Bread Characteristics Yanti, Rini; Suroto, Dian Anggraini; Manikharda, Manikharda; Putri, Yuniar Wika Perdana
Journal of Applied Agricultural Science and Technology Vol. 9 No. 1 (2025): Journal of Applied Agricultural Science and Technology
Publisher : Green Engineering Society

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55043/jaast.v9i1.341

Abstract

Sourdough is made from water and wheat flour, fermented by lactic acid bacteria and yeast. Papaya can serve as a natural starter for producing sourdough. This study aims to assess the impact of drying on pH levels, total titratable acidity (% TTA), the viability of lactic acid bacteria (LAB), yeast viability, specific volume, and the texture profile of gluten and gluten-free bread. Three types of starters were used: P (fermented water from papaya and flour), G (fermented water from papaya, sugar, and flour), and W (mineral water and flour) to make type I sourdough (before drying). Type III sourdough (dried) was obtained using spray drying (S), cabinet drying (C), and freeze-drying (F). The pH, %TTA, LAB, and yeast viability were measured, while the specific volume and texture profiles of the breads were evaluated. Spray drying significantly affected the pH of the A sample and LAB viability in the W and G samples. Cabinet drying significantly affected the %TTA and yeast viability in the G sample. Freeze-drying significantly affected the LAB and yeast viability in the W and G samples, as well as yeast viability and %TTA in the P sample. Instant sourdough can be produced using spray, cabinet, or freeze drying and is suitable for making both gluten-containing and gluten-free bread. Variations in starter type and drying methods influence the bread's physical characteristics, including specific volume and texture profile. The drying methods significantly affected hardness, gumminess, chewiness, cohesiveness, springiness index, and resilience in both gluten-containing and gluten-free bread samples.

Page 12 of 16 | Total Record : 157

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