Research in Agricultural Engineering - Latest articles
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Enhancing the destructive egg quality assessment using the machine vision and feature extraction technique
Ehsan Sheidaee, Pourya Bazyar
Res. Agr. Eng., 2025, 71(2):95-104 | DOI: 10.17221/86/2024-RAE 
The rapid growth of the food industry necessitates rigorous quality control, particularly in egg production. This study explores advanced methodologies for egg quality assessment by integrating the Principal Component Analysis (PCA), Linear Discriminant Analysis (LDA), and k-Nearest Neighbour (KNN) with machine vision techniques. While traditional destructive methods like measuring the Haugh unit (HU) offer direct insights, but render eggs unusable, non-destructive techniques, such as imaging and spectroscopy, allow continuous quality monitoring. Over a 20-day period, egg samples were evaluated using a digital camera to capture key parameters like...
Perception of bimodal warning cues during remote supervision of autonomous agricultural machines
Anita Chidera Ezeagba, Cheryl Mary Glazebrook, Daniel Delmar Mann
Res. Agr. Eng., 2025, 71(2):69-79 | DOI: 10.17221/73/2024-RAE
Agricultural machines that are fully autonomous will still need human supervisors to monitor and troubleshoot system failures. Recognising the emergency as soon as possible is crucial to reduce adverse effects. The ability of humans to detect visual, auditory, or tactile cues is usually enabled by warning systems. The effectiveness of different warning cues varies in terms of prompting a quick response. The study’s objective was to compare the effectiveness of two bimodal warnings (i.e., visual-auditory and visual-tactile) at eliciting supervisor perception (which equates to level one situation awareness). Twenty-five participants engaged in...
Camera systems and their user recognition reliability when entering an agri-food complex
Jaroslav Mrázek, Jakub Vo¹áhlík, Eva Olmrová, Martin Pexa, Zdenìk Ale¹, Jakub Èedík
Res. Agr. Eng., 2025, 71(2):105-112 | DOI: 10.17221/35/2025-RAE
This study evaluates the efficiency of various facial recognition camera systems used to control access in agri-food production environments, focusing on their ability to identify individuals based on biometric facial traits. It is also important to prevent the movement of unwanted persons into the production premises in the agri-food complex. The main goal was to assess how these factors influence the recognition performance and to determine the most reliable system for preventing unauthorised entry. The results show notable performance disparities between the devices tested. It can be concluded in this research that there are statistically significant...
Stability of soil moisture sensors for agricultural crop cultivation
Sitti Nur Faridah, Muhammad Tahir Sapsal, Tisha Aditya A. Jamaluddin, Andini Dani Achmad, Muhammad Adi Surya
Res. Agr. Eng., 2025, 71(2):88-94 | DOI: 10.17221/33/2024-RAE
Soil water content is critical in plants’ morphological and physiological processes; therefore, water must always be available in appropriate quantities to meet plant growth needs. Soil moisture can be easily detected using sensors, which offer a practical solution for monitoring water content in the soil. However, using sensors for a long time, especially on agricultural land, will reduce sensor accuracy. This research aims to investigate the accuracy of soil moisture sensors during their use for cultivating crops. Using sensors in sandy clay soil can detect soil moisture levels with an accuracy of 93.80% and a precision of 90.81%. A reading...
Spoilage detection of tomatoes using a convolutional neural network
Ninja Begum, Manuj Kumar Hazarika
Res. Agr. Eng., 2025, 71(2):80-87 | DOI: 10.17221/31/2024-RAE
With the increasing productivity in agriculture, it has become extremely essential to look for an advanced technique that will help to minimise losses. Recently, deep learning has outperformed the task of recognition and classification of fruits and vegetables automatically from images, finding applicability in this study. This work, thus, attempts to develop an automatic spoilage detection CNN model for tomatoes. In this work, a deep learning-based CNN model is trained and validated on a self-prepared dataset for classifying tomatoes as edible and spoilt is proposed. The dataset consisted of 810 images, out of which 572 images were considered...
Portable analogue-based electronic moisture meter for root-crop chips
James Roy Lesidan, Mencius Lesidan, Melvin Hagonob, Charlie Andan, Ma. Grace Sumaria, Ronaldo Almencion, Kebin Ysrael Martinez
Res. Agr. Eng., 2025, 71(2):113-120 | DOI: 10.17221/15/2025-RAE
Moisture content regulation of root crops is crucial in post-harvest processing operations, not only in the price stipulation but also to avoid aflatoxin contamination. To prolong their storage life, they are processed into dried chips to extend their usability in feed formulations and starches. In this study, we use the capacitance-based method to evaluate the performance of an analogue-based electronic meter for the cassava, sweet potato, and taro chips. The meter was calibrated against the oven-drying method, yielding high R2 values of the different root crops. The established calibration models were validated and revealed...
Use of thermal imaging camera for wild animal detection along roads
Jiøí Bro¾ovský, Veronika Hartová, Martin Kotek, Jan Hart, Jitka Kumhálová
Res. Agr. Eng., 2025, 71(1):60-67 | DOI: 10.17221/88/2024-RAE
Vehicle collisions with wild animals are a common problem on roads, having a significant impact on road safety and wildlife populations. Collisions with wild animals are one of the most frequent road accidents. According to police statistics, there were nearly 16 000 road accidents caused by collisions with animals in the Czech Republic in 2019. Collisions with deer are the most common. There are several technologies and measures that can help reduce the risk of a vehicle colliding with a wild animal. One of the technologies used is a night vision system based on infrared spectrum sensing. This technology is slowly becoming part of the...
Particle motion in mixed flow dryers: The effect of the wall inclination angle and friction
Adrienn Bablena, János Beke, István Keppler
Res. Agr. Eng., 2025, 71(1):50-59 | DOI: 10.17221/51/2024-RAE
In Europe, the weather patterns require harvested grain crops to be dried before storage to prevent significant quality loss. The uneven movement of grains inside the drying equipment is a key issue affecting the drying process, causing under- or over drying the harvested crops and thus leading to quality degradation and ultimately to financial losses. To characterise the unevenness of material flow, we introduced a dimensionless displacement ratio. This dimensionless parameter was suitable for comparing the uniformity of the material movement processes within the dryer. Using experimental investigations and numerical simulations, we determined the...
Development of smart micro-irrigation system using Arduino Uno for okra cultivation in Bangladesh
Sharmin Akter, Md Mostafizar Rahman, Rafatul Zannat, Md Masud Rana, Md Moinul Hossain Oliver, Md Aslam Ali
Res. Agr. Eng., 2025, 71(1):38-49 | DOI: 10.17221/18/2024-RAE
Conventional irrigation practices result in a substantial amount of water loss with okra cultivation. Although micro-irrigation can address this issue by delivering water directly near the rootzone, it requires manual operation. These issues, however, can be resolved with the introduction of a smart micro-irrigation system. This study aims to develop a smart micro-irrigation system for okra, in conjunction with the sub-components of drip irrigation, a microcontroller, and a soil sensor. The experiment was laid out with a randomised complete block design (RCBD) having three treatments: (i) control irrigation (T1), (ii)...
An effective machine learning model for the estimation of reference evapotranspiration under data-limited conditions
Saravanan Karuppanan, Saravanan Ramasamy, Balaji Lakshminarayanan, Sreemanthrarupini Nariangadu Anuthaman
Res. Agr. Eng., 2025, 71(1):22-37 | DOI: 10.17221/101/2023-RAE
Reference crop evapotranspiration (ETo) is a vital hydrological component influenced by various climate variables that impact the water and energy balances. It plays a crucial role in determining crop water requirements and irrigation scheduling. Despite the availability of numerous approaches for estimation, accurate and reliable ETo estimation is essential for effective irrigation water management. Therefore, this study aimed to identify the most suitable machine learning model for assessing ETo using observed daily values of limited input parameters in tropical savannah climate regions. Three...
Anaerobic bio-processing of agricultural waste for the biotechnological production of lactic acid and volatile fatty acid by landfill soil inoculums
Andriy Anta Kacaribu, Darwin Darwin, Yuliani Aisyah, Febriani
Res. Agr. Eng., 2025, 71(1):10-21 | DOI: 10.17221/52/2024-RAE
With the increase in the world population and the ensuing surge in organic waste, effective management strategies are crucial to prevent environmental pollution. This study aims to address this challenge by utilising organic waste (OW) as the substrate for the production of lactic acid (LA) and volatile fatty acids (VFAs) through anaerobic bioprocessing. The substrates used, included grass, starch, and fruit wastes inoculated with non-sterile inoculum landfill soil (LS). The anaerobic bioconversion was performed by varying the substrate to the inoculum. The results unveil that a digester loaded with 150 g·L–1 of fruit waste,...
Towards interpretability: Assessment of residual networks for tomato leaf disease classification
Raphael Berdin, Rob Christian Caduyac
Res. Agr. Eng., 2025, 71(1):1-9 | DOI: 10.17221/67/2024-RAE
The tomato occupies a prominent place in the Philippines’ agricultural economy. However, tomato leaf diseases are challenges in tomato crop production leading to economic losses. Among the tomato leaf diseases, early blight and Septoria leaf spot are prevalent in the Philippines due to the climate. Thus, the accurate identification of diseases affecting tomato leaves is essential. Currently, a visual inspection is the primary method for diagnosing tomato leaf diseases which is time-consuming and inefficient. This study aims to develop a quantized Residual Network with convolutional 50 layer (ResNet-50) based model to classify tomato leaves...
Ergonomic investigation on spraying task performance in paddy farming activities
Dian Mardi Safitri, Novia Rahmawati, Winnie Septiani, Nora Azmi, Azizah Nurul Hanifati, Ummi Noor Nazahiah binti Abdullah, Norashiken binti Othman
Res. Agr. Eng., 2024, 70(4):226-236 | DOI: 10.17221/80/2023-RAE
The commodity rice in Indonesia and the administration of rice fields are given particular focus by the government. Spraying activities are known to increase the risk of exposure to chemicals for farmers, resulting in a loss of working days for 3–7 days. It is necessary to carry out ergonomic interventions for spraying activities to make the activity safer for farmers. This research aims to identify the ergonomics and safety problems of spraying activities in rice field farming, to analyse and develop intervention parameters to solve issues in spraying activities, and to generate innovative design concepts to overcome spraying problems. Prospective...
Geometrical analysis of 3-point linkage of tractors for measurement and display of implement’s working depth
P K Pranav, Anmol Kumar, Abhishek Kumar Ansh, Sanjay Kumar
Res. Agr. Eng., 2024, 70(4):237-244 | DOI: 10.17221/23/2024-RAE
The display of the depth of operation on tractors' dashboards facilitates the operator in achieving precise operation. In this study, the depth of operation of a mounted implement was measured and digitally displayed on a tractor's dashboard. The change in depth of operation was sensed by measuring the rotation of the rocker arm of the tractor's hydraulic system. The measured angle of rotation was multiplied by a calibration factor to convert it into the actual depth of operation in centimetres. For the calibration factor, a geometrical analysis of the three-point linkage was carried out, and a mathematical relationship was established based...
Prediction of physicochemical characteristics of Lemon (Citrus limon cv. Montaji Agrihorti) using Vis-NIR spectroscopy and machine learning model
Jihan Nada Salsabila Erha, Dina Wahyu Indriani, Zaqlul Iqbal, Bambang Susilo, Dimas Firmanda Al Riza
Res. Agr. Eng., 2024, 70(4):218-225 | DOI: 10.17221/25/2024-RAE
Lemons are fruit products that grow well in Indonesia. Montaji Agrihorti is one of the lemon varieties found in Indonesia, a new variety developed by Balitjestro breeding. This lemon variety is seedless. In fact, lemons are harvested nearly all year-round. Equally important, evaluating the fruit's maturity level is crucial for determining the optimal harvest time. In this study, standardizing measurement on maturity level was conducted through Vis-NIR spectroscopy and machine learning models. In this case, non-destructive data from Vis-NIR spectroscopy were correlated with parameters related to fruit maturity and quality, such as soluble solid content...
Modeling and optimization of dynamic isothermal compressibility features on flowability of Canarium schweinfurthii Engl nutshell powder
James Chinaka Ehiem, Victor Ifeanyichukwu Obiora Ndirika, Udochukwu Nelson Onwuka, Raghavan Vijayan
Res. Agr. Eng., 2024, 70(4):209-217 | DOI: 10.17221/24/2024-RAE
The compressibility features (bulk density, tapped bulk density, porosity, coefficient of compressibility and Hauser ratio) of Canarium schweinfurthii engl. nutshell powder as it affects flowability during densification process were investigated. Three different moisture contents (10.13, 15.07 and 20.11% wet basis; w.b.) and particle sizes of 0.659 7, 1.26 and 2.05 mm were considered at pressure range of 2 to 10 MPa. The compressibility relationship with the factors were modelled and the optimum flow conditions were also determined. The obtained results showed that particle size and moisture content had incremental influence on the...
Modelling of energy demand prediction system in potato farming using deep learning method
Riswanti Sigalingging, Nasha Putri Sebayang, Noverita Sprinse Vinolina, Lukman Adlin Harahap
Res. Agr. Eng., 2024, 70(4):198-208 | DOI: 10.17221/115/2023-RAE
Agriculture and energy are intricately connected, with agriculture being a significant energy consumer and supplier. In this comprehensive study, SPSS and Jupyter Notebook were used to model and predict the energy requirements of potato plants during cultivation. A system using deep learning methods, specifically the Convolutional Neural Network (CNN), was also developed to accurately predict the classification of potato plant growth phases using image data. The CNN model, developed with 100 epochs and 5 layers, used 1 125 image data of potato plants, categorising them into two classes: the vegetative phase, with an energy requirement of 4 195.80 MJ·ha–1,...
Control of odour and gaseous emissions from livestock buildings: Recent research and developments
Roger Jay Lamadrid De Vela
Res. Agr. Eng., 2024, 70(4):181-197 | DOI: 10.17221/55/2024-RAE
One major challenge in the continuous growth of the livestock industry is the increased emission of odorous gases, which is not just a nuisance but also a cause of serious health and environmental concerns. Several strategies which aim to: (i) reduce the formation of odorous gases; (ii) enhance dispersion of odour; (iii) capture odour and gases to prevent escape to the environment; and (iv) reduce odour and gaseous concentrations, are developed. These are achieved with the use or employment of one or more of: (i) diet manipulation techniques; (ii) additives and adsorbents; (iii) covers; (iv) shelterbelts...
Effect of physical energy on germination and seedling vigor of alfalfa seeds (Medicago sativa L.)
Ali Hajizadeh Namin, Abbas Akbarnia, Rouzbeh Abbaszadeh, Ali Zenouzi, Majid Masoumian
Res. Agr. Eng., 2024, 70(3):174-180 | DOI: 10.17221/114/2023-RAE
Recently, non-thermal technologies have emerged as a means to ensure the safety of agricultural products while also promoting plant growth and reducing pathogenic and chemical contamination of seeds. An experiment was conducted to investigate the effect of various treatments on the germination characteristics of alfalfa seeds. The experiment utilised a completely randomised design with five treatments and three replications, including cold plasma exposure, direct current (DC) electromagnetic field, magnetic field, and a combination of plasma exposure with magnetic and electromagnetic fields. The treated seeds were compared to the control seeds (without...
The efficiency of unmanned aerial vehicles application for rapeseed productivity in Ukraine
Fedir Melnychuk, Svitlana Alekseeva, Oleksandra Hordiienko, Oleksii Nychyporuk, Andrii Borysenko, Nataliia Didenko
Res. Agr. Eng., 2024, 70(3):167-173 | DOI: 10.17221/87/2023-RAE
In modern conditions, high-precision technologies, such as unmanned aerial vehicles (UAVs), are the basis for increasing the efficiency of agricultural land use and crop productivity. Nowadays, new technology development needs to be improved, so the study and the implementation of various innovations in this field are quite relevant and important. The research aimed to find effective pesticides and a selection of spraying solution norms to increase rapeseed yield. The least significant difference test was used to separate the means of the dependent variables in response to predictor variables at P ≤ 0.05. It was established that herbicides...
Advancements in fuzzy expert systems for site-specific nitrogen fertilisation: Incorporating RGB colour codes and irrigation schedules for precision maize production in Bangladesh
Bitopi Biswas, Mohammad Tariful Alam Khan, Mohammad Billal Hossain Momen, Mohammad. Rashedur Rahman Tanvir, Abu Mohammad Shahidul Alam, M Robiul Islam Islam
Res. Agr. Eng., 2024, 70(3):155-166 | DOI: 10.17221/35/2024-RAE
The research was conducted at the Department of Agronomy and Agricultural Extension, Rajshahi University, from December 2021 to April 2022. The objective was to develop a fuzzy expert system for site-specific N fertilisation using leaf colour code (RGB) and irrigation frequencies for maize yield. The experiment encompassed two primary factors: nitrogen fertiliser application rates (N1: 100%, N2: 75%, N3: 50% of conventional rates) and irrigation frequencies (I1: 100%, I2: 75%, I3: 50% of pan evaporation). A completely randomised design...
The effect of stimulants on the responsiveness and biorhythms of young operators of agricultural machinery
Veronika Hartová, Jan Hart
Res. Agr. Eng., 2024, 70(3):143-154 | DOI: 10.17221/4/2024-RAE
Fatigue behind the wheel has been addressed repeatedly for at least 15 years. Various research projects, studies, and systems have been developed to prove the effect of fatigue on the number of accidents and possibly to inform drivers that this situation has occurred. The article examines the influence of stimulants on the fatigue of young agricultural machinery drivers. Commonly available means for reducing driver fatigue were chosen as stimulants (coffee, tea, maté, guarana, energy drink, lemon extract with sugar). A special test station with automatic reaction time evaluation was developed to test drivers’ reaction ability (responsiveness)....
Detecting adulteration in mustard oil using low-frequency dielectric spectroscopy
Venkatesh Mishra, Satyendra Pratap Singh, Sumit Kaur Bhatia, Vishal Singh Chandel, Rajiv Manohar
Res. Agr. Eng., 2024, 70(3):134-142 | DOI: 10.17221/108/2023-RAE
This paper presents a dielectric spectroscopy approach for analysing the quality of food products. This study aimed to detect the adulteration in mustard oil using dielectric spectroscopy in the 1 to 10 MHz frequency range at a temperature of 30 to 50 °C. The dielectric data were used to predict the adulteration in oils at the given frequency range. The finding indicates that using data analysis techniques can further improve the capacity of dielectric sensing to detect adulterated edible oil. Using MATLAB R2021a, linear relationships between the frequency and adulteration percentage variables were obtained to predict the dielectric constant...
The effect of parameter adjustment in sago palm classification-based convolutional neural network (CNN) model
Sri Murniani Angelina Letsoin, David Herák
Res. Agr. Eng., 2024, 70(3):123-133 | DOI: 10.17221/65/2023-RAE
In our study location, Merauke Regency, the easternmost city in Indonesia, the sago palm is associated with different types of ecosystems and other non-sago vegetation. During the harvesting season, the white flowers blossoming between the leaves on the tops of palm trees may be distinguished manually. Four classes were determined to address the visual inspections involving different parameters that were examined through the metric evaluation and then analysed statistically. The computed Kruskal-Wallis test found that the parameters vary in each network with a P-value of 0.00341, with at least one class being higher than the others, i.e., non-sago...
Influence of soil tillage technology on tillage erosion
Jaroslav Korba, Pavel Bro¾, Josef Hùla, Petr Novák, Václav Novák
Res. Agr. Eng., 2024, 70(2):104-110 | DOI: 10.17221/64/2023-RAE
Tillage-induced erosion has negative impacts on the soil environment and production of the soil under intensive farming. Tillage erosion was evaluated during soil tillage performed by two technologies, i.e. conventional tillage and reduced tillage, commonly used in the Czech Republic. A field experiment was aimed at evaluating the soil particle translocation and magnitude of the vector angle. Aluminium cubes with an edge length of 16 mm were used as tracers. After each soil tillage operation, a metal detector searched these tracers in the topsoil. During the experiment, agricultural practices were always carried out on their respective...
Digital image processing for preliminary detection of infected porang (Amorphophallus muelleri) seedlings
Aryanis Mutia Zahra, Noveria Anggi Nurrahmah, Sri Rahayoe, Rudiati Evi Masithoh, Muhammad Fahri Reza Pahlawan, Laila Rahmawati
Res. Agr. Eng., 2024, 70(2):111-121 | DOI: 10.17221/79/2023-RAE
Porang (Amorphophallus muelleri) is an Indonesian parental plant tuber developed vegetatively from bulbils during dormancy and harvested through petiole detachment for the industrial production of glucomannan. Pathogenic fungi and whiteflies can cause infection during harvesting and storage, destructing plant cells as well as reducing seed quality and crop yields. Therefore, this study aimed to develop a calibration model for detecting infected and non-infected porang bulbils using a computer vision system. Image parameters such as colour (red, green, blue – RGB and hue, saturation, intensity – HSI), texture (contrast, homogeneity,...
Study on parameters affecting vibration in height adjustment of a combine harvester header model
Kittikhun Prasertkan, Prathuang Usaborisut, Krittatee Jindawong, Kiatkong Suwannakij, Anusorn Iamrurksiri
Res. Agr. Eng., 2024, 70(2):92-103 | DOI: 10.17221/53/2023-RAE
In Thailand, vibration problems often occur with rice combine harvester automatic header height adjusting systems. This study aimed to identify parameters for reducing the vibration and managing response time for harvesting speed configuration. An experimental combine harvester header model was designed to automatically adjust three parameters: total movement time, time ratio, and final phase distance within vertical movement ranges of 200, 250, or 300 mm. These parameters were controlled using a proportional flow control valve and a professional learning community (PLC) control unit. The results showed that increased time ratio, final phase...
Application of the physical properties of local cowpea varieties in the development of a multi-variety cowpea cleaner
Babatunde Olusola Adetifa, Elizabeth Ayobami Olumomi, Taiwo Moses Samuel, Ayoola Abiola Babalola
Res. Agr. Eng., 2024, 70(2):82-91 | DOI: 10.17221/51/2023-RAE
Cowpea, an annual legume widely grown and consumed in Nigeria, has been observed to contain between 27–33% impurities when freshly harvested and threshed. This poses a threat to humans when consumed and in large-scale agricultural processing. Therefore, this study is aimed at developing and evaluating the performance of a multi-variety cowpea cleaner (MVCC). Using standard methods, some selected engineering properties of the cowpea varieties were examined and used in the design of the MVCC. The cowpea had a moisture content of 8–14%, depending on the locations and varieties. Other properties investigated include the length, width, thickness,...
Drying and color kinetics of decorticated queen pineapple (Ananas comosus Linn.) fiber bleached with hydrogen peroxide solution
Roger Jay Lamadrid De Vela, Arnold Recidocruz Elepano
Res. Agr. Eng., 2024, 70(2):73-81 | DOI: 10.17221/47/2023-RAE
The drying and colour kinetics of H2O2-bleached pineapple fibres were studied to determine an optimum drying condition and appropriate drying and colour kinetic models. The experiments were conducted under drying air temperatures of 40, 50 and 60 ºC, air velocities of 0.27, 0.38 and 0.42 m×s–1 and hydrogen peroxide (H2O2) concentrations of 1, 3 and 5% by volume arranged in a three-factor factorial experimental design. Colour values were quantified by the CIELab system where L* is the lightness value, a* is redness/greenness and b* is yellowness/blueness....
Location-specific technology transfer model in an agricultural technology park, Indonesia
Harmi Andrianyta, Elisa Anggraeni, Sapta Raharja, Sukardi Sukardi
Res. Agr. Eng., 2024, 70(2):61-72 | DOI: 10.17221/7/2023-RAE
Diversity in the characteristics of agricultural locations has the potential to develop. Unfortunately, the weak transfer of technology based on the characteristics of the location indicates that this potential cannot grow properly. This research aims to synthesise a technology transfer model for an agricultural technology park (ATP) by considering site-specific conditions. This cross-case study was conducted at selected ATP locations. Model synthesis uses the system development life cycle stages of initiation, analysis, and design. The resource-based view approach was broken down into several variables during the analysis stage. Three location-specific...