Template-Type: ReDIF-Article 1.0 Author-Name: Richard Alvin Pratama Author-Workplace-Name: Department of Computer Engineering, Universitas Multimedia Nusantara,Tangerang, Banten, Indonesia Author-Name: Nabila Husna Shabrina Author-Workplace-Name: Department of Computer Engineering, Universitas Multimedia Nusantara,Tangerang, Banten, Indonesia Title: A novel ensemble convolutional neural networksfor rice disease identification Abstract: Rice is a crucial food commodity worldwide, particularly in Asian countries. However, various factors, such as drought, floods, and pest attacks, can lead to the emergence of diseases in rice plants. Accurately identifying these diseases poses a significant challenge for farmers, often leading to significant yield losses. Conventionally, farmers rely on manual methods based on their experience and visual inspections to identify rice diseases. However, this approach is highly ineffective, time-consuming, and prone to error. This study aimed to address this issue by proposing advanced deep learning techniques, an ensemble learning method, to automate and enhance the identification of rice plant diseases. The ensemble learning method was proposed by leveraging two state-of-the-art pre-trained models: EfficientNetV2B0 and MobileNetV3-Large. The proposed Average Ensemble method demonstrates superior performance compared with single models. The proposed Average Ensemble achieved superior performance with an average precision of 0.9339, a recall of 0.9330, an F1-score of 0.9328, and a test accuracy of 0.9330. The results of this study can be used to aid farmers and researchers in accurately identifying rice diseases, ultimately supporting better disease management practices, and enhancing the agricultural productivity. Keywords: ensemble deep learning, precision agriculture, rice plant disease identification Journal: Research in Agricultural Engineering Pages: 1-13 Volume: 72 Issue: 1 Year: 2026 DOI: 10.17221/59/2024-RAE File-URL: http://rae.agriculturejournals.cz/doi/10.17221/59/2024-RAE.html File-Format: text/html X-File-Ref: http://agriculturejournals.cz/RePEc/caa/references/rae-202601-0001.txt Handle: RePEc:caa:jnlrae:v:72:y:2026:i:1:id:59-2024-RAE Template-Type: ReDIF-Article 1.0 Author-Name: Bakhtiyar Ismailov Author-Workplace-Name: Department of Information Systems and Modelling, Faculty of Information Technologies and Energy, M. Auezov South Kazakhstan University, Shymkent, Kazakhstan Author-Workplace-Name: Department of Electronics and Instrumentation, Faculty of Energy Engineering and Technology, Fergana State Technical University, Fergana, Uzbekistan Author-Name: Abdushukur Urinboev Author-Workplace-Name: Department of Electronics and Instrumentation, Faculty of Energy Engineering and Technology, Fergana State Technical University, Fergana, Uzbekistan Author-Name: Khairulla Ismailov Author-Workplace-Name: Department of Information Systems and Modelling, Faculty of Information Technologies and Energy, M. Auezov South Kazakhstan University, Shymkent, Kazakhstan Author-Name: Akmaljon Kuchkarov Author-Workplace-Name: Department of Electronics and Instrumentation, Faculty of Energy Engineering and Technology, Fergana State Technical University, Fergana, Uzbekistan Title: Modelling the hydration process of wheat grain  with layer-dependent diffusion coefficients Abstract: This study develops and validates a multilayer diffusion model of wheat grain hydration that incorporates layer-dependent diffusion coefficients for bran, endosperm, and germ. The moisture transport is formulated using Fick's law with two interface formulations: (i) classical continuity of the concentration and flux and (ii) an interlayer resistance formulation that permits concentration discontinuities. Diffusion coefficients and geometric parameters were determined experimentally; A 3D grain model (structured-light scanning, COMSOL Multiphysics) informed the computational domain. Numerical solutions combined eigenfunction expansions with finite-difference discretisation near the interfaces. Across eight winter wheat varieties, the diffusion coefficients spanned 11.6 - 20.5 × 10-12m2.s-1 (mean 16.27 ± 3.08 × 10-12m2.s-1 ). Relative to the continuity model, the resistance model reduced the early-stage endosperm over-prediction by ~ 0.6-1.0 % (absolute) and lowered the whole-grain RMSE by ~ 20-30% over 0-240 min. These results support the role of thin moisture-retaining films as active barriers and yield smooth, real-time-ready outputs suitable for the automated control of pre-milling hydration; the framework is extensible to full 3D transient simulations. Keywords: grain hydration, interlayer resistance, multilayer model, moisture transport, COMSOL Multiphysics, modelling, micropyle Journal: Research in Agricultural Engineering Pages: 25-40 Volume: 72 Issue: 1 Year: 2026 DOI: 10.17221/101/2025-RAE File-URL: http://rae.agriculturejournals.cz/doi/10.17221/101/2025-RAE.html File-Format: text/html X-File-Ref: http://agriculturejournals.cz/RePEc/caa/references/rae-202601-0002.txt Handle: RePEc:caa:jnlrae:v:72:y:2026:i:1:id:101-2025-RAE Template-Type: ReDIF-Article 1.0 Author-Name: Romeica Noe Rimorin Author-Workplace-Name: Camarines Norte State College, Camarines Norte, Philippines Author-Name: Christian Mark Felix Author-Workplace-Name: Camarines Norte State College, Camarines Norte, Philippines Author-Name: Roger Jay Lamadrid De Vela Author-Workplace-Name: Camarines Norte State College, Camarines Norte, Philippines Title: The effects of temperature on biogas production rate and purity Abstract: This study investigated the effects of temperature on the performance of anaerobic digesters for biogas production. Digesters were filled with a 1 : 1 ratio of substrate to water, containing 15 kg of cow dung and 3 kg of crop waste, and maintained at temperatures of 50 ± 2 °C and 30 ± 2 °C, corresponding to the thermophilic and mesophilic biodigesters, respectively. The experiments run for 75 days, and biogas production rate and purity were measured. The thermophilic digester produced 48.4% more biogas and had a slightly higher pH (7.65) than did the mesophilic digester (7.37) by the end of the observation period. However, gas chromatography revealed that the CH4 and CO2 contents did not significantly differ between the two treatments. The CH4 concentration in the mesophilic environment was 42 ± 10%, whereas that in the thermophilic environment was 53.5 ± 10%. The CO2 composition was 32.5 ± 1% and 35.5 ± 1% for the mesophilic and thermophilic setups, respectively. These were supported by the wavelength (460 nm to 620 nm) of the flame colour, indicating that the biogas from both setups is predominantly composed of methane. In conclusion, thermophilic anaerobic digesters may have a relatively high biogas production rate, but the biogas purity is not significantly different from that of mesophilic digesters. Keywords: anaerobic digester, biomethane, methane, mesophilic, thermophilic Journal: Research in Agricultural Engineering Pages: 70-79 Volume: 72 Issue: 1 Year: 2026 DOI: 10.17221/104/2025-RAE File-URL: http://rae.agriculturejournals.cz/doi/10.17221/104/2025-RAE.html File-Format: text/html File-URL: http://rae.agriculturejournals.cz/doi/10.17221/104/2025-RAE.pdf File-Format: Application/pdf X-File-Ref: http://agriculturejournals.cz/RePEc/caa/references/rae-202601-0003.txt Handle: RePEc:caa:jnlrae:v:72:y:2026:i:1:id:104-2025-RAE Template-Type: ReDIF-Article 1.0 Author-Name: Elchyn Aliiev Author-Workplace-Name: Faculty of Engineering and Technology, Dnipro State Agrarian and Economic University, Dnipro, Ukraine Author-Name: Valentyn Holovchenko Author-Workplace-Name: Faculty of Engineering and Technology, Dnipro State Agrarian and Economic University, Dnipro, Ukraine Author-Name: Olha Aliieva Author-Workplace-Name: Department of Technical and Technological Support of Seed Production, Institute of Oilseed Crops of the National Academy of Agrarian Sciences of Ukraine, Zaporizhzhia, Ukraine Title: Research on the optimal design and process parameters of a castor seed cleaning machine Abstract: In the context of the modern EU bioeconomy, the use of industrial crops, particularly castor beans (Ricinus communis L.), is relevant for the production of industrial and energy products without competing with food crops. Castor oil is used for the production of biodiesel, lubricants, paints and coatings, cosmetics, and pharmaceuticals. In Ukraine, castor beans can be cultivated on low-yield soils, with seed yields ranging from 1.5 t/ha to 2.1 t/ha depending on the variety. However, the morphological features of the fruits and uneven ripening complicate the mechanisation of harvesting and seed cleaning processes. Existing equipment designed for other crops cannot be applied due to the risk of damaging the castor seeds. A design of a castor seed cleaning machine has been proposed, combining mechanical fruit shelling with the aerodynamic separation of the mixture. The machine is equipped with an eccentric crushing cone, rubber linings, a pneumatic separation channel, a cyclone, and an automated control unit. As a result of numerical modelling and experimental studies of the process of separating and cleaning castor seeds, dependencies were obtained for the productivity of the developed machine Q, power consumption P, specific energy consumption E, fraction of unshelled fruits (segments) ξf, content of the clean seed in the seed collector ψs-s depending on the distance between the reverse and crushing cones δ, rotation frequency of the crushing cone n, diameter of the feed opening Din, inclination angle of the crushing cone axis γ, and airflow velocity V. A multi-criteria optimisation method was applied to find the optimal operating modes: δ = 10.8 mm; n = 282 rpm; V = 3.6 m/s; Din = 98 mm; γ = 3.6°; β = 20.3°. The following results were achieved: E = 0.0394 MJ/kg; Q = 163.4 kg/h; P = 1 861 W; ξf = 0.099; ψs-s = 0.958. The obtained results confirm the efficiency of the proposed design for industrial implementation. Keywords: experiment, mechanical shelling, numerical simulation, productivity, quality, regression models, separation, specific energy Journal: Research in Agricultural Engineering Pages: 41-58 Volume: 72 Issue: 1 Year: 2026 DOI: 10.17221/121/2025-RAE File-URL: http://rae.agriculturejournals.cz/doi/10.17221/121/2025-RAE.html File-Format: text/html X-File-Ref: http://agriculturejournals.cz/RePEc/caa/references/rae-202601-0004.txt Handle: RePEc:caa:jnlrae:v:72:y:2026:i:1:id:121-2025-RAE Template-Type: ReDIF-Article 1.0 Author-Name: Shokhjakhon Khamidullaev Author-Workplace-Name: Department of Geodesy and Geoinformatics, Faculty of Land Recourses and Cadastre, "Tashkent Institute of Irrigation and Agricultural Mechanisation Engineers" National Research University, Tashkent, Uzbekistan Author-Name: Rustam Oymatov Author-Workplace-Name: Department of Geodesy and Geoinformatics, Faculty of Land Recourses and Cadastre, "Tashkent Institute of Irrigation and Agricultural Mechanisation Engineers" National Research University, Tashkent, Uzbekistan Author-Name: Ilhom Abdurahmanov Author-Workplace-Name: Department of Geodesy and Geoinformatics, Faculty of Land Recourses and Cadastre, "Tashkent Institute of Irrigation and Agricultural Mechanisation Engineers" National Research University, Tashkent, Uzbekistan Author-Workplace-Name: Namangan State Technical University, Namangan, Uzbekistan Author-Name: Ilkhom Aslanov Author-Workplace-Name: Department of Geodesy and Geoinformatics, Faculty of Land Recourses and Cadastre, "Tashkent Institute of Irrigation and Agricultural Mechanisation Engineers" National Research University, Tashkent, Uzbekistan Title: Estimating changes in the Khisar glacier, using remote sensing data and GIS technologies for the assessment of water use in agriculture (Surkhandarya valley, Uzbekistan) Abstract: Climate change is speeding up the melting and retreat of glaciers, which is a big threat to water security in dry and semi-dry areas like Uzbekistan. To understand how glaciers affect regional hydrological systems and to come up with adaptive water management strategies, it is important to keep an eye on how they change over time. This study examines the temporal changes of the Khisar Glacier in the Surkhandarya Basin by combining remote sensing data from different times with a GIS-based spatial analysis. We looked at Landsat images from 1990, 2000, 2010, and 2024 to see how the size of the glaciers has changed and how that relates to weather and water variables. The results show that the glacier area has shrunk significantly, from 8.6 km2 in 1990 to 5.1 km2 in 2024, a 40.7% decrease over the past three decades. The mean annual temperature in the basin rose by about 1.9 °C during the same time, and the Surkhandarya River's average summer discharge fell by about 22%. These results show how closely rising temperatures, melting glaciers, and lower river flow are linked. They also show how vulnerable glacier-fed water systems are to climate change. Combining satellite observations with climate and hydrology data is a good way to keep an eye on glaciers and assess water resources over time. The GIS-based monitoring framework created in this study provides useful tools for planning how to adapt to climate change and manage water resources in a way that is good for the environment in the Surkhandarya region and other glacier-dependent basins in Central Asia. Keywords: agriculture, climate change, gis analysis, glacier retreat, khisar glacier, remote sensing, water resources Journal: Research in Agricultural Engineering Pages: 14-24 Volume: 72 Issue: 1 Year: 2026 DOI: 10.17221/141/2025-RAE File-URL: http://rae.agriculturejournals.cz/doi/10.17221/141/2025-RAE.html File-Format: text/html X-File-Ref: http://agriculturejournals.cz/RePEc/caa/references/rae-202601-0005.txt Handle: RePEc:caa:jnlrae:v:72:y:2026:i:1:id:141-2025-RAE Template-Type: ReDIF-Article 1.0 Author-Name: Sarah El Azizi Author-Workplace-Name: Laboratory CBM-VR, Faculty of Sciences and Techniques, University Abdelmalek Essaadi, Tangier, Morocco Author-Name: Halima Taia Author-Workplace-Name: Laboratory CBM-VR, Faculty of Sciences and Techniques, University Abdelmalek Essaadi, Tangier, Morocco Author-Name: Abdes-Samed Bernoussi Author-Workplace-Name: Laboratory CBM-VR, Faculty of Sciences and Techniques, University Abdelmalek Essaadi, Tangier, Morocco Author-Name: Mina Amharref Author-Workplace-Name: Laboratory CBM-VR, Faculty of Sciences and Techniques, University Abdelmalek Essaadi, Tangier, Morocco Author-Name: Edyta Wozniak Author-Workplace-Name: Space Research Centre of the Polish, Academy of Sciences, Warszawa, Poland Title: A spectral signature-based algorithm for the identifiability of crops and their cultivation conditions Abstract: Recent advancements in remote sensing techniques, especially the combination of hyperspectral imaging with analytical algorithms, have greatly improved precision agriculture. This study introduces some algorithms developed for identifying crops and evaluating their growth conditions, focusing on irrigation and fertilisation. The present approach is based on the concept of identifiability of a family of dynamic systems and the differentiation of plants using their spectral signatures. The method uses a repository of spectral data and applies a developed algorithm to compare the measured spectra with the reference database, enabling the identifiability and the recognition of both known and unknown crops. As an application of our approach, we have considered two different crops: mint and rosemary, under different irrigation and fertilisation conditions. The results show that the algorithm achieved a 100% identification rate across the four unknown samples. The minimum spectral distances obtained are 0.01 and 0.03 for rosemary and mint, respectively. Thus, the family of systems was identifiable with a tolerance of η < 0.03. The study concluded that the algorithm effectively classifies the crop type and deduces its growth conditions, demonstrating its effectiveness for agricultural monitoring. Keywords: hyperspectral imaging, remote sensing, precision agriculture, plant stress detection, spectral data analysis Journal: Research in Agricultural Engineering Pages: 56-69 Volume: 72 Issue: 1 Year: 2026 DOI: 10.17221/163/2025-RAE File-URL: http://rae.agriculturejournals.cz/doi/10.17221/163/2025-RAE.html File-Format: text/html X-File-Ref: http://agriculturejournals.cz/RePEc/caa/references/rae-202601-0006.txt Handle: RePEc:caa:jnlrae:v:72:y:2026:i:1:id:163-2025-RAE