Agricultural Engineering Feed

Spectral-Luminescent Properties of Rapeseed Oil Obtained from Seeds Purified with an Electrostatic Field

Mon, 24 Aug 2026 00:00:00 GMT

Samples of rapeseed oil obtained by cold pressing from seeds treated with an electrostatic field of intensity E = (0.05-0.25) MV·m−1 for a duration of t = 3-30 s were analyzed. As a reference, the spectral-luminescent characteristics of rapeseed oil samples prepared similarly from control rapeseed that had not been treated with an electrostatic field were also recorded. The behaviour of rapeseed oil fluorophores, namely tocopherol, phenol, fatty acids, oxidation products, vitamins and pigments, which are part of its composition, was a source of information about the chemical composition of the seeds under study. It has been found that the fluorophores in rapeseed oil obtained from seeds pretreated with an electrostatic field with an intensity at E = (0.05-0.25) MV·m−1 for t = 3-30 s exhibit spectral-luminescent properties identical to those of rapeseed oil obtained from seeds that were not subjected to additional electrostatic field treatment. Specifically, the spectral-luminescent properties of the fluorophores in rapeseed oil (tocopherol, phenol, fatty acids, oxidation products, vitamins, and pigments) obtained from seeds treated with an electrostatic field with an intensity at E = (0.05-0.25) MV·m−1 for t = 3-30 s were identical to those of fluorophores in rapeseed oil obtained from rapeseed that had not been exposed to an electric field of the specified parameters. The results obtained indicate that additional cleaning of rapeseed using an electrostatic field under the specified conditions does not cause any changes in its chemical composition or in the nature of intermolecular interactions within it.

Correction

Thu, 02 Jul 2026 00:00:00 GMT

Correction

Thu, 02 Jul 2026 00:00:00 GMT

Hierarchical Causal Mapping and Prioritisation of Post-Harvest Fish Losses Risk in Aquaculture Supply Chain Using an Integrated FDM-Fdematel

Thu, 02 Jul 2026 00:00:00 GMT

Post-Harvest Fish Losses (PHFL) remain a significant constraint in the aquaculture supply chain, where rapid quality deterioration can reduce the value and availability of food, especially in tropical contexts such as Indonesia. Prior PHFL research is dominated by capture-fisheries studies and primarily descriptive evidence, leaving aquaculture-specific, multi-echelon causal mechanisms, particularly those related to processing capabilities and supporting infrastructure, that are not sufficiently prioritized. This study develops a causal mapping and prioritization framework for PHFL risk factors for a sustainable aquaculture supply chain using an integrated Fuzzy Delphi Method (FDM) and Fuzzy Decision -Making Trial and Evaluation Laboratory (FDEMATEL) approach. Judgments from 23 experts representing four echelons (farmers, intermediaries, processors, retailers/consumers) were elicited to screen and structure risks under uncertainty. FDM retained 17 key risk factors from 30 candidates. FDEMATEL then produced a prioritized causal structure, in which inadequate harvesting techniques and equipment (RF17), limited cold-chain availability (RF21), and inadequate handling techniques and equipment (RF18) emerge as the strongest causal drivers, shaping downstream outcomes related to safety, storage, and market performance. Theoretically, the study contributes a two-level (hierarchical) causal architecture (aspect and risk-factor levels) that moves beyond determinant lists to explain propagation pathways. Managerially, this provides evidence-based priorities for interventions in initial handling capabilities, cold chain continuity, and IT coordination/integration to guide investment and policy decisions for reducing PHFL in the aquaculture supply chain in Indonesia.

Influence of Basic 3D Printing Parameters on Mechanical Properties pf PLA Biopolymer Prints by FDM Method

Thu, 02 Jul 2026 00:00:00 GMT

With the rapid advancement of 3D printing technology and increasing demands for production efficiency, it is essential to verify the impact of key process parameters on the mechanical properties of printed parts. Optimizing print speed, temperature, and path orientation is critical to ensuring the repeatability and durability of manufactured components, especially in engineering and industrial applications. Polyactide (PLA) is a plant-based polymer that is one of the most popular materials used in 3D printing with FDM/FFF technology. The article presents the results of a study on the mechanical properties, specifically tensile strength and bending strength, of specimens manufactured using a Creality K2 Plus 3D printer with PLA. The tests were conducted in accordance with ISO 527-2 for tensile testing and ISO 178 for bending testing on a Stable Micro Systems TA-XT plus Texture Analyser. The filament for printing was extruded on an Artme3D MK3S filament extruder to a diameter of 1.75 mm. The specimens were printed in combinations involving changes in the three crucial printing parameters: temperature (190°C, 200°C, 210°C), printing speed (100 mm·s−1, 150 mm·s−1, 200 mm·s−1) and the layer angle (15°, 30°, 45°, 90°). The study showed that both tensile strength and bending strength are most affected by temperature. Moreover, the optimal printing parameters for the specimens were determined for tensile strength (T=210°C, V=150 mm·s−1, R=0°) and bending strength (T=200°C, V=200 mm·s−1, R=0°).

Optimization of Glucose Syrup from Cassava Peel Waste: Determining the Optimal Composition Using the Analytical Hierarchy Process-Weighted Product Method

Thu, 02 Jul 2026 00:00:00 GMT

Cassava is one of Indonesia's largest agricultural commodities. Currently, its use is primarily confined to tubers, resulting in the production of solid cassava peel waste. Notably, cassava peel contains a high carbohydrate content, comprising up to 50% of the carbohydrates found in the tubers. Additionally, the high cost of granulated sugar and the inability of the national sugar industry to meet Indonesia's sugar demand have become significant concerns. Consequently, this study aimed to explore the use of cassava peel waste as an alternative raw material for glucose syrup, which can potentially serve as a sugar substitute. Nine experimental treatments were tested to determine the optimal glucose syrup. The best glucose syrup was identified using an integration of the analytical hierarchy process (AHP) and weighted product method (WPM). AHP was employed to establish the weighted priorities of the criteria and sub-criteria, followed by WPM to determine the alternative weights and rank the options. The third treatment emerged as the best alternative, with a weight of 0.124, comprising 60 g cassava peel starch, 0.06 mL glucoamylase, and 2 mL α-amylase. The test results for the glucose syrup from this treatment included a reducing sugar content of 33.51%, moisture content of 64.419%, ash content of 0.137%, an organoleptic colour value of 3 (slightly cloudy), a taste rating of 3.93 (sweet), and an aroma rating of 2.93 (slightly odorous). The utilization of this waste is anticipated to enhance its economic value while mitigating its environmental impact.

The Effect of Plough Modernization on Fuel Consumption During Ploughing and Subsoil Bulk Density

Thu, 02 Jul 2026 00:00:00 GMT

This study attempts to address the problem of excessive soil compaction in the subsoil layer caused by the movement and operation of agricultural machinery by modernizing the plough design to combine two operations with high energy requirements, ploughing and subsoiling. The aim of this study was to modernize and develop the design of the share plough by adding an additional frame (heavy-duty tines) on which the mounted working elements (straight type chisel spike, two-heart type chisel spike, duck foot type chisel spike). The effect of the plough modernization was to destroy the plough pan, leading to a decrease in the bulk density of the soil in the subsoil layer. However, when tines with a duck foot (sweep) type chisel spike were used, an increase in soil bulk density was observed in the layer below the working depth of the tool. The modernization of the plough resulted in the increase in fuel consumption per units' area during ploughing related to the area cultivated. Using a modernized plough allows two energy-intensive operations – ploughing and subsoiling – to be combined in a single pass.

Mathematical Modeling of the Germination and Growth of Leucaena Leucocephala under Different Substrates and Nursery Conditions

Fri, 29 May 2026 00:00:00 GMT

Livestock production in tropical regions is predominantly extensive and relies heavily on native or monoculture pastures, which often prove insufficient for ruminant nutrition. The incorporation of Leucaena leucocephala into silvopastoral systems represents a promising strategy due to its high forage quality; however, information on its early establishment under nursery conditions remains limited. This study aimed to model the germination dynamics and early seedling growth of L. leucocephala under different substrate compositions during the nursery phase. Germination percentage and daily plant height were recorded over a 30-day period. Treatment effects were evaluated using analysis of variance (ANOVA) and growth dynamics were described using nonlinear sigmoidal models (Gompertz, Logistic, von Bertalanffy, and Brody). Significant differences in germination rate among substrates were detected (p<0.05), whereas no significant effect of substrate on plant height was observed during the evaluation period (p>0.05). Among the evaluated models, von Bertalanffy, Gompertz, and Logistic functions provided the best fit for plant height based on R2 and AIC criteria. Although some models showed high R2 values for germination, elevated AIC values suggest limited biological adequacy. These findings highlight the usefulness of predictive modeling to support nursery management decisions, optimize substrate selection, and facilitate the establishment of L. leucocephala in sustainable silvopastoral systems.

Experimental Investigation of Single Flare in Brake Tubes

Thu, 16 Apr 2026 00:00:00 GMT

This study presents the results of experimental tests on single flare (SF) terminations in brake tubes with diameters of ∅4.75 mm and ∅6.35 mm, and wall thickness of 0.9 mm and 1 mm, respectively, using the FALCON toolset. The research aimed at determining the optimal range of initial tube protrusion that results in a flare diameter compliant with the BN-90 3617-09 standard. The paper provides a detailed description of the testing methodology It presents raw measurement data, statistical calculations, and their analysis. Conformity or nonconformity with the specification was assessed according to the guidelines outlined in the PN-EN ISO 14253-1:2018-02 standard. For tubes with the diameter of ∅4.75 mm and the wall thickness of 0.9 mm, the average measured flare diameters for the initial protrusion in the range of 4.4–5.0 mm fall within the tolerance specified by the standard. However, when accounting for measurement uncertainty, the required flare diameters are obtained for the initial protrusion in the range of 4.6–5.0 mm. In the case of tubes with the diameter of ∅6.35 mm and the wall thickness of 1.0 mm, the average measured flare diameters meet the standard requirements for the initial protrusion of 4.6–5.0 mm, whereas, considering the measurement uncertainty, the required flare diameters are obtained for the initial protrusion in the range of 4.8–5.0 mm.

Monitoring Environmental Parameters in Poultry Houses Using IoT

Thu, 16 Apr 2026 00:00:00 GMT

High gas levels in poultry houses, namely carbon dioxide (CO₂) and ammonia (NH₃), can cause stress, impair respiration in the birds, reduce egg production, and increase their disease susceptibility. Therefore, this study presents an IoT-based monitoring system built on an Arduino ESP32 microcontroller and integrated with DHT22, MQ-135, and MQ-137 sensors for measuring key environmental parameters in poultry houses. The system monitors temperature, humidity, NH3, and CO2 in both closed and open laying hen housing systems. Environmental data were stored in the cloud to enable remote, real-time monitoring and subsequent analysis. The results showed that closed housing systems are more suitable for regulating temperature and humidity while keeping gas levels within permissible limits inside poultry farms, thus leading to improved egg production. The proposed IoT-based monitoring system offers a practical tool for improving poultry management and reducing losses associated with poor air quality, ultimately helping farmers enhance production efficiency.

Application of Back-Propagation Artificial Neural Network and Particle Swarm Optimization Methods in Sprinkler Optimization

Thu, 16 Apr 2026 00:00:00 GMT

The aim of this paper was to analyze the primary and secondary order of influencing factors and to establish a BP neural network prediction model with different hydraulic performance indicators. Particle swarm optimization algorithm was used to test for the optimal hydraulic performance of the nozzle and validated by experiment. The orthogonal design covered the 200–300 kPa range, while the PSO algorithm selected 540 kPa based on the full dataset. The sprinkler was raised at a height of 1.4 m from the ground level in a square configuration. The optimal parameter combination for the square layout achieved higher uniformity and controlled maximum kinetic energy relative to the average sprinkling intensity. Results from the experiment gave 4.71 mm·h−1, 83.28% and 0.0078 W·m−2 for average sprinkler intensity, CU and maximum kinetic energy, respectively. Compared with the rangeanalysis- based scheme, the optimized configuration reduced average irrigation intensity while improving uniformity and kinetic energy performance. The maximum error between experimental results and optimization results was 3.29%, indicating that the optimization model is feasible and reliable. This study proposes a practical optimization framework for the design and operation of sprinkler irrigation systems.

Development and Evaluation of a Yolo Algorithm-Based Robotic Sprayer for Real-Time Weed Detection

Sat, 14 Feb 2026 00:00:00 GMT

Weed control with chemicals is a challenging process that should be performed in a rational way to reduce their negative impact on the surrounding environment. The growth of artificial intelligence algorithms encourages researchers to develop smart spraying robots that detect and spray weeds and distinguish them from the main crop which leads to sustainable use of these chemicals and achieves some of the sustainable development goals. However, few studies are available to comprehensively compare different versions of YOLO algorithm to detect weed. In this research, seven versions of YOLO algorithms were evaluated for their performance to detect and spray four types of weeds, namely, Cultivated licorice (Glycyrrhiza glabra L.), Dyer’s Croton (Chrozophora verbascifolia), Lambsquarters (Chenopodium album L.), and Puncturevine (Tribulus terrestris L.) using a locally manufactured remotely controlled spraying robot. The results showed that YOLOv6n surpassed other algorithms which achieved the highest precision (0.89), recall (0.80), F1-score (0.84), mAp@0.50 (0.86), inference speed (18.83 fps), in addition to the field indicators including true positive rate (0.83), false negative rate (0.17), false positive rate (0.19), true negative rate (0.81).

Design and Performance Evaluation of a Four-Row Vacuum Seeder Powered by a Walking Tractor for Precision Soybean Planting

Sat, 14 Feb 2026 00:00:00 GMT

A previously developed two-row vacuum-type seeder showed promising singulation performance but its operational productivity was limited due to its low row capacity. This study aimed to design, develop, and evaluate a four-row vacuum-type soybean seeder to improve sowing capacity while maintaining high precision. The seeder, mounted on and powered by a walking tractor, used a centrifugal suction blower to generate vacuum pressure for four seed metering devices. Seed disks were driven by a chain-and-sprocket mechanism linked to the tractor’s wheel shaft. Bench tests were conducted at two seed disk speeds (12.7 and 26.1 rpm) and six blower speeds (3500, 4000, 4500, 5000, 5500, and 6000 rpm) using two soybean varieties. Singulation efficiency and the percentages of multiple and missing seeds were recorded. Results showed that higher vacuum pressures (>1.70 kPa) at lower disk speeds (12.7 rpm) significantly improved singulation, achieving 99–100% efficiency with minimal missed and multiple seeds (<1.25%) and no seed damage. Higher disk speeds (26.1 rpm) reduced accuracy. Field tests at three blower speeds (5000–6000 rpm) and two tractor speeds (Low-1 and Low-2) confirmed consistent seed spacing (19.2–19.6 cm) and optimal planting depth (4.8–4.9 cm), with minimal variation due to wheel slip. The best field performance (98% singulation) was achieved at Low-1 tractor speed and 6000 rpm blower speed. Increasing tractor speed enhanced field capacity from 0.16 to 0.31 ha·h⁻¹. The results validate the prototype’s effectiveness for precise and efficient soybean planting.

Model-based Assessment of Manual Raspberry Harvesting Efficiency Using the CIOSTA Methodology in Tunnel-Grown Production Systems

Mon, 15 Dec 2025 00:00:00 GMT

The aim of this study was to assess how raspberry cultivar and work organization influence the efficiency of manual harvesting under intensive tunnel-grown production. The research was carried out in July and August 2022 on a 20-hectare plantation and included four cultivars: Kwanza, Malling Bella, Enrosadira, and Diamond Jubilee.The CIOSTA methodology was applied, combining detailed time measurements and full-day work observations, which enabled an indepth analysis of effective time, auxiliary time, transport time, and work losses. In July, the average total harvest time was 240.7 rbh·ha⁻¹, while in August it decreased to 153.2 rbh·ha⁻¹. The highest efficiency was recorded for the Diamond Jubilee cultivar (K07 = 0.82), whereas the lowest values were observed for Malling Bella in July and Enrosadira in August. Transport-related activities accounted for the largest share of time losses, which is reflected in the transport utilization coefficient Kt (0.43-0.44). The results indicate that harvest efficiency depends not only on the cultivar and its yield potential but also on work organization and internal logistics. The findings confirm that the structure of the harvesting proces-particularly transport Logistics-plays a key role in determining overall efficiency. The presented analysis provides valuable input data for developing simulation and optimization models that support the design of improved work organization solutions in horticultural farms. The study aligns with current research trends in organizational and logistical analysis within horticultural production and forms a basis for creating model approaches to soft-fruit harvesting systems.

The State and Prospects of Digital Transformation in the Agricultural Sectors

Mon, 15 Dec 2025 00:00:00 GMT

The purpose of the study is to analyse trends and directions of digitalisation of agriculture, with a focus on technologies that contribute to improving the efficiency and sustainability of the industry. The methodology includes an analysis of the state of digitalisation of agriculture, key technologies, barriers to implementation, and development prospects based on statistical data and industry reports. The paper analyses the most developed crop and livestock industries in Kazakhstan, such as the production of cereals, oilseeds, dairy, and beef cattle, with a focus on the use of drones, the Internet of Things, artificial intelligence, and blockchain. The technical features of technologies, implementation costs, payback periods, and infrastructural requirements are considered. A comparative analysis of digitalisation in Kazakhstan and other countries is conducted, which identifies the main barriers, such as high costs, insufficient infrastructure, and a low level of digital literacy. It is determined that drones contribute to optimising field monitoring and accurate resource allocation, the Internet of Things provides data collection and analysis for real-time process management, artificial intelligence is used for forecasting and automation, and blockchain increases the transparency of supply chains. These technologies have improved resource management, increased yields, and minimised environmental impacts. The main barriers hindering the digitalisation of agriculture were high technology costs, insufficient infrastructure, low levels of digital literacy among industry workers, and resistance to change on the part of farmers.

Dynamic Simulation and Experimental Validation of Hydraulic Performance for a Valve-Regulated Proportional Fertigator

Mon, 15 Dec 2025 00:00:00 GMT

With the sustainable development of precision agriculture, the valve regulated proportional fertigator has attracted research attention due to its high efficiency combined with low cost and incidence of damage. In order to investigate the hydraulic performance of the fertigator, the internal flow, force and motion of the piston were analysed by means of dynamic simulation and experimental validation. Results show that the inlet flow of fertilizer first increased and then decreased with the increase of the three-way valve angle under the same pressure conditions. The area with the highest flow velocity of 13 m/s in the fertigator concentrates on the inlet one-way valve and three-way valve part, while the fertilizer extraction part and the outlet part were in the low flow velocity area. The movement frequency increased with the increase of the threeway valve angle, except the middle part that showed variations in the wave change. With the increase of the inlet pressure, the variations in the three-way valve angles were also increased. At the initial stage of piston motion, the driving force was much greater than the resistance, and the driving force and the resistance fluctuated from the initial maximum to the same stable value. The resultant force of the piston fluctuates from the initial maximum driving force of 242 N to 0 N, and then the piston accelerates from 0 N to the minimum driving force of 8.5 N. When the resultant force was reduced, the acceleration also decreased. However, when the acceleration was reduced to zero (0), the piston started to move uniformly, which is useful for achieving consistency in the spread of fertilizer application in the artificially drained catchment. The maximum relative error between simulation and experiment was 15%. However, there was no difference in the overall trend, so we can draw a reasonable and accurate conclusion of the simulation. The study could be useful for achieving uniformity in the spread of fertilizer application in the artificially drained catchment.

Integrated Ultrasound-Assisted Convective–Microwave Drying for the Dehydration of Medicinal Plants

Mon, 15 Dec 2025 00:00:00 GMT

Ultrasound-assisted convective-microwave drying (UACMD) is an emerging hybrid drying method that combines hot-air convection, microwave heating and ultrasound cavitation to enhance moisture transfer and preserve bioactive compounds in medicinal herbs. This review summarizes its advantages, including a 30-80% reduction in drying time, improved energy efficiency, and better retention of antioxidants, essential oils, and color. However, challenges, such as thermal degradation and scale-up complexity remain. Future developments emphasize the integration of smart controls (artificial intelligence, computer vision, and hyperspectral imaging) and the tailoring of protocols for specific herb types, positioning UACMD as a sustainable and high-performance solution for modern herbal drying.

Environmental Footprint and Water Footprint in Studies on the Impact of Agricultural Production on the Natural Environment

Wed, 26 Nov 2025 00:00:00 GMT

In the face of growing challenges related to climate change, environmental degradation, and limited natural resources, the assessment of the environmental impact of various economic sectors is becoming increasingly important. Agriculture, as one of the key branches of food production, significantly contributes to environmental degradation, water resource consumption, and ecosystem transformation. In this context, the concepts of Environmental Footprint (EF) and Water Footprint (WF) are particularly important, serving as tools for the quantitative assessment of the pressure exerted by agricultural production on the environment. The environmental footprint encompasses various impact indicators, such as greenhouse gas emissions, eutrophication, acidification, abiotic resource consumption, and biodiversity loss. The water footprint, on the other hand, focuses on quantifying freshwater use throughout the product life cycle, considering blue, green, and grey water. The combined use of these tools allows for a comprehensive analysis of the impact of agricultural practices on the natural environment and the identification of areas requiring improvement towards sustainable development. Consequently, they help shape environmental policies and sustainable resource management strategies. The aim of this article is to present current methods for assessing environmental and water footprints in agricultural production and to discuss the main factors influencing their values. The article also presents the current state of research in this field and practical examples of how these tools are applied in evaluating different farming systems.

Investigation of the Physical Properties of Fluids for Removing Industrial Contaminants

Sun, 05 Oct 2025 00:00:00 GMT

The aim of this study was to investigate the influence of concentration and temperature on the physical properties of selected industrial cleaning fluids, focusing on parameters relevant to the cleaning process, such as viscosity, shear stress, density, activation energy, and wettability. Four cleaning agents from the company Noyen were examined, including both concentrated products and their 10% aqueous solutions. The rheological properties of the fluids were evaluated using a rotational viscometer; density was measured with a pycnometer; surface tension and wettability were assessed using a goniometer; and activation energy was determined based on the Arrhenius equation. The results of the viscosity and shear stress tests indicated that all tested fluids exhibited Newtonian behaviour in both concentrated and diluted forms. Surface tension and wettability analysis showed good wetting properties for all tested fluids (contact angle <55°), although significant differences in wettability were observed depending on the type of surface and the specific fluid used.

Innovative Technology for the Inactivation of Allergenic Compounds on Component Surfaces of a Prototype Processing Line for the Manufacture of Products with Controlled Allergenicity

Wed, 10 Sep 2025 00:00:00 GMT

The study aimed to develop and validate effective procedures for cleaning and allergen deactivation in a prototype processing line for crisp-coated meat products. Reliable cleaning methods are critical for ensuring food safety and preventing cross-contamination when conventional and allergen-controlled products are manufactured on the same line. Critical points along the processing line were identified through preliminary assessments. At these points, allergen residues were monitored using immunoassay-based tests targeting major food allergens, including gluten, soy, milk, nuts, sesame, and others. Several cleaning procedures were compared with regard to their ability to eliminate allergenic proteins from equipment surfaces. Lower-concentration protocols proved inadequate, particularly in high-risk areas such as cutting, mixing, and cooling zones. In contrast, the optimized procedure achieved complete removal of allergens at all critical points. This outcome was further confirmed during validation trials involving thirty pilot production batches, where no allergenic proteins were detected in environmental swabs or final products. The results demonstrate that carefully designed cleaning strategies can enable dual use of processing lines for both standard and allergen-controlled products. The validated procedure offers a cost-effective and practical solution for the food industry, supporting compliance with regulatory requirements and improved consumer safety.