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Techno Agriculturae Studium of Research
Published by Yayasan Adra Karima Hubbi
ISSN : 30479835     EISSN : 30482321     DOI : 10.70177/agriculturae
Core Subject : Agriculture,
Agriculture, Biological Sciences & Forestry
Techno Agriculturae Studium of Research is an international forum for the publication of peer-reviewed integrative review articles, special thematic issues, reflections or comments on previous research or new research directions, interviews, replications, and intervention articles - all pertaining to the Research in agriculture, includes a wide range of studies and analyzes related to production, resource management, agricultural technology, environmental sustainability, agricultural policy, and more. All publications provide breadth of coverage appropriate to a wide readership in agriculture research depth to inform specialists in that area. We feel that the rapidly growing Techno Agriculturae Studium of Research community is looking for a journal with this profile that we can achieve together. Submitted papers must be written in English for initial review stage by editors and further review process by minimum two international reviewers.
Arjuna Subject : Ilmu Pertanian dan Biologi (Semua) - Ilmu Pertanian dan Biologi (Lain-Lain)
Articles 5 Documents
 1 
Search results for , issue "Vol. 2 No. 3 (2025)" : 5 Documents clear
Integration of Sustainable Agriculture Concept and Local Ecological Knowledge in Shifting Cultivation Farming System; Review of Environmental Anthropology Study Kamakaula, Yohanes; Palinggi, Yunita
Techno Agriculturae Studium of Research Vol. 2 No. 3 (2025)
Publisher : Yayasan Adra Karima Hubbi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70177/agriculturae.v2i3.2339

Abstract

Shifting cultivation systems are often considered unsustainable practices, yet many indigenous communities have developed this agricultural model ecologically and socially. In this context, it is important to review how local ecological knowledge plays a role in shaping sustainable agricultural systems and how the integration of sustainable agriculture concepts can strengthen these local practices. This study aims to explore the relationship between sustainable agricultural principles and local ecological practices in shifting cultivation, using an environmental anthropology approach. The main focus is to explore the meaning, values, and strategies of traditional agriculture as part of an adaptive social-ecological system. The research method used is qualitative ethnographic with participatory observation techniques, in-depth interviews, and case studies in shifting cultivation farming communities in the interior. The results of the study show that the shifting cultivation system contains the principles of diversification, land rotation, ecological control based on customary norms, and spiritual values towards nature. This system has indirectly created ecological and social sustainability without the intervention of modern technology. The conclusion of this study confirms that sustainability does not always have to be constructed through a technocratic approach, but can be built through recognition of local ecological practices.
WASTEWATER TREATMENT TECHNOLOGY FOR AGRICULTURAL IRRIGATION IN SPAIN Tu, Bui Minh; Peng, Nam; Mai, Nguyen Thi
Techno Agriculturae Studium of Research Vol. 2 No. 3 (2025)
Publisher : Yayasan Adra Karima Hubbi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70177/agriculturae.v2i3.1998

Abstract

Water scarcity in Spain has become a major challenge for the agricultural sector, thus encouraging the use of treated wastewater as an alternative source of irrigation. This study aims to evaluate the effectiveness of wastewater treatment technology on agricultural productivity, environmental impact, and farmers’ income in Spain. The research method used is an experimental quantitative design with data collection from wastewater treatment plants, field tests on soil quality, as well as interviews and questionnaires to farmers in the research area. The results show that the use of treated wastewater increases crop yields by 10-15% and reduces the use of chemical fertilizers by 20%, without causing a negative impact on soil and groundwater quality. Farmers’ acceptance of this technology is also quite high, driven by real economic benefits. In conclusion, wastewater treatment technology in Spain has the potential to be a sustainable solution to the water crisis in the agricultural sector, although more research is needed to understand the long-term impact on the environment.
APPLICATION OF VIRTUAL REALITY TECHNOLOGY IN AGRICULTURAL TRAINING IN SWITZERLAND Aung, Hnin Thiri; Hlaing, Nandar; Lin, Tun
Techno Agriculturae Studium of Research Vol. 2 No. 3 (2025)
Publisher : Yayasan Adra Karima Hubbi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70177/agriculturae.v2i3.2001

Abstract

Virtual reality (VR) technology has shown great potential in various sectors, including the agricultural sector which requires practical training. This study aims to evaluate the effectiveness of VR technology in improving the skills of farmers in Switzerland through agricultural training. This study uses a quasi-experimental method by comparing the group that uses VR training and the control group that uses conventional methods. The results showed that participants who took part in VR-based training had significant skill improvements and higher levels of satisfaction compared to traditional methods. Despite the challenges of early adaptation to VR technology, participants generally found the learning experience to be more interactive and effective. The conclusion of this study states that VR can be an effective tool in developing farmers’ technical skills in a safer, more flexible, and interactive way. More research is needed to explore the long-term use of VR in agricultural training.  
THE USE OF ARTIFICIAL INTELLIGENCE FOR PREDICTING COFFEE BEAN QUALITY BASED ON DIGITAL IMAGES AND SENSOR DATA Silamat, Eddy; Zaman, Khalil; Akhtar, Shazia
Techno Agriculturae Studium of Research Vol. 2 No. 3 (2025)
Publisher : Yayasan Adra Karima Hubbi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70177/agriculturae.v2i3.2442

Abstract

The increasing global demand for high-quality coffee requires more efficient and objective methods to evaluate bean quality. Traditional sensory and manual inspection techniques are time-consuming, subjective, and prone to inconsistency. This study aims to develop and validate an Artificial Intelligence (AI)-based predictive model for assessing coffee bean quality using digital image processing and sensor data. The research employs a quantitative experimental approach by integrating convolutional neural networks (CNNs) for visual analysis and machine learning regression models to process multispectral sensor data related to moisture, color, and aroma parameters. A dataset of 5,000 labeled coffee bean samples from three regional plantations was used for training and validation. The results demonstrate that the hybrid AI model achieved an accuracy rate of 96.8% in predicting bean grades compared to expert cupping scores, outperforming traditional visual grading methods by 18%. Furthermore, the integration of digital imaging and IoT-based sensors significantly reduced evaluation time and human error. The findings highlight AI’s potential to revolutionize coffee quality control by enabling automated, consistent, and scalable assessment systems that support sustainable agricultural practices.
A GIS-BASED DECISION SUPPORT SYSTEM FOR SUSTAINABLE LAND USE PLANNING AND CLIMATE CHANGE ADAPTATION IN THE BRANTAS RIVER WATERSHED Hakim, Dani Lukman; Santos, Luis; Reyes, Maria Clara
Techno Agriculturae Studium of Research Vol. 2 No. 3 (2025)
Publisher : Yayasan Adra Karima Hubbi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70177/agriculturae.v2i3.2522

Abstract

The Brantas River Watershed, a vital socio-economic region in East Java, Indonesia, faces escalating environmental pressures from unplanned urbanization and intensive agriculture. These challenges are exacerbated by climate change, leading to increased land degradation, soil erosion, and severe flood events, which threaten the watershed’s long-term sustainability and the livelihoods of millions. This study aimed to develop and validate a Geographic Information System (GIS)-based Decision Support System (DSS) to aid policymakers in formulating integrated, evidence-based strategies for sustainable land use planning and climate change adaptation within this critical watershed. The DSS was constructed by integrating a multi-criteria evaluation (MCE) framework within a GIS environment. Key geospatial datasets (land cover, soil type, slope, rainfall projections) were weighted using the Analytical Hierarchy Process (AHP). The system models land suitability and vulnerability to environmental hazards under various climate change scenarios. The developed DSS successfully generated high-resolution maps identifying priority zones for conservation, reforestation, and sustainable development. The model revealed that 22% of the upper watershed area is at high risk of landslides under projected rainfall patterns. The optimized land use plan proposed by the DSS demonstrated a potential to reduce surface runoff by up to 35%, significantly mitigating flood risk. The GIS-based DSS is a powerful and effective tool for integrated watershed management. It provides a dynamic, scientifically-grounded platform for strategic planning, enabling policymakers to balance ecological protection with socio-economic needs and enhance the climate resilience of the Brantas River Watershed.

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