Template-Type: ReDIF-Article 1.0
Author-Name: Sri Murniani Angelina Letsoin
Author-Workplace-Name: Department of Mechanical Engineering, Faculty of Engineering, Czech University of Life Sciences Prague, Prague, Czech Republic
Author-Name: David Herák
Author-Workplace-Name: Department of Mechanical Engineering, Faculty of Engineering, Czech University of Life Sciences Prague, Prague, Czech Republic
Title: The effect of parameter adjustment in sago palm classification-based convolutional neural network (CNN) model
Abstract: 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 with a P-value of 0.044 with respect to precision, recall, and F1-score. Thus, the general linear model (GLM) was tested specifically in trained Network-15 and Network-17, which have similar parameters except for the batch size. It indicated the two networks' differences based on their prediction results, classes, and actual images. Accordingly, a combination of learning rate (Lr) and batch size improved the reliability of the training and classification task.
Keywords: deep learning, detection, model, parameter, transfer learning
Journal: Research in Agricultural Engineering
Pages: 123-133
Volume: 70
Issue: 3
Year: 2024
DOI: 10.17221/65/2023-RAE
File-URL: http://rae.agriculturejournals.cz/doi/10.17221/65/2023-RAE.html
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Handle: RePEc:caa:jnlrae:v:70:y:2024:i:3:id:65-2023-RAE

Template-Type: ReDIF-Article 1.0
Author-Name: Venkatesh Mishra
Author-Workplace-Name: Department of Physics, Amity Institute of Applied Sciences, Amity University Uttar Pradesh, Noida, India
Author-Name: Satyendra Pratap Singh
Author-Workplace-Name: Department of Physics, Amity Institute of Applied Sciences, Amity University Uttar Pradesh, Noida, India
Author-Name: Sumit Kaur Bhatia
Author-Workplace-Name: Department of Mathematics, Amity Institute of Applied Sciences, Amity University Uttar Pradesh Noida, India
Author-Name: Vishal Singh Chandel
Author-Workplace-Name: Department of Applied Science & Humanities, Rajkiya Engineering College, Ambedkar Nagar, Uttar Pradesh, India
Author-Name: Rajiv Manohar
Author-Workplace-Name: Department of Physics, University of Lucknow, Lucknow Uttar Pradesh, India
Title: Detecting adulteration in mustard oil using low-frequency dielectric spectroscopy
Abstract: 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 and dielectric loss factor values. A paired sample t-test was used to analyse the effects of the frequency and adulteration on the dielectric parameters, with a significance level of 0.05 being set for the differences. Correlation coefficients (R2) > 0.96 were established using regression equations relating the dielectric constant, dielectric loss, and adulteration.
Keywords: dielectric constant, loss factor, regression, statistical analysis, temperature
Journal: Research in Agricultural Engineering
Pages: 134-142
Volume: 70
Issue: 3
Year: 2024
DOI: 10.17221/108/2023-RAE
File-URL: http://rae.agriculturejournals.cz/doi/10.17221/108/2023-RAE.html
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Handle: RePEc:caa:jnlrae:v:70:y:2024:i:3:id:108-2023-RAE

Template-Type: ReDIF-Article 1.0
Author-Name: Veronika Hartová
Author-Workplace-Name: Department of Vehicles and Ground Transport, Faculty of Engineering, Czech University of Life Science Prague, Prague, Czech Republic
Author-Name: Jan Hart
Author-Workplace-Name: Department of Vehicles and Ground Transport, Faculty of Engineering, Czech University of Life Science Prague, Prague, Czech Republic
Title: The effect of stimulants on the responsiveness and biorhythms of young operators of agricultural machinery
Abstract: 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). Furthermore, the effects on the physical condition of the tested persons (systolic blood pressure, diastolic blood pressure, blood pressure amplitude and heart rate) were investigated. The conducted experiments confirmed a statistically significant effect of all tested stimulants, except for tea, for which no statistically significant changes in the monitored parameters were observed.
Keywords: blood pressure, influences, fatigue, physical condition
Journal: Research in Agricultural Engineering
Pages: 143-154
Volume: 70
Issue: 3
Year: 2024
DOI: 10.17221/4/2024-RAE
File-URL: http://rae.agriculturejournals.cz/doi/10.17221/4/2024-RAE.html
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Handle: RePEc:caa:jnlrae:v:70:y:2024:i:3:id:4-2024-RAE

Template-Type: ReDIF-Article 1.0
Author-Name: Bitopi Biswas
Author-Workplace-Name: Precision and Automated Agriculture Laboratory, Department of Agronomy and Agricultural Extension, Rajshahi University, Rajshahi, Bangladesh
Author-Name: Mohammad Tariful Alam Khan
Author-Workplace-Name: Precision and Automated Agriculture Laboratory, Department of Agronomy and Agricultural Extension, Rajshahi University, Rajshahi, Bangladesh
Author-Name: Mohammad Billal Hossain Momen
Author-Workplace-Name: Precision and Automated Agriculture Laboratory, Department of Agronomy and Agricultural Extension, Rajshahi University, Rajshahi, Bangladesh
Author-Name: Mohammad. Rashedur Rahman Tanvir
Author-Workplace-Name: Precision and Automated Agriculture Laboratory, Department of Agronomy and Agricultural Extension, Rajshahi University, Rajshahi, Bangladesh
Author-Name: Abu Mohammad Shahidul Alam
Author-Workplace-Name: Precision and Automated Agriculture Laboratory, Department of Agronomy and Agricultural Extension, Rajshahi University, Rajshahi, Bangladesh
Author-Name: M Robiul Islam Islam
Author-Workplace-Name: Precision and Automated Agriculture Laboratory, Department of Agronomy and Agricultural Extension, Rajshahi University, Rajshahi, Bangladesh
Title: Advancements in fuzzy expert systems for site-specific nitrogen fertilisation: Incorporating RGB colour codes and irrigation schedules for precision maize production in Bangladesh
Abstract: 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 (CRD) with three replications was used to arrange the experimental pots, each receiving recommended doses of phosphorus, potassium, and sulfur, with urea applied per treatment instructions. Results revealed significant chlorophyll content and grain yield differences among the various nitrogen fertiliser rates. The highest grain yield (219.27 g.pot-1) was observed with N1, whereas the lowest (186.6 g.pot-1) was with N3. Similarly, irrigation frequencies significantly influenced chlorophyll content and cob characteristics, with I1 resulting in the highest grain yield (211.27 g.pot-1) and I3 the lowest (184.6 g.pot-1). Furthermore, the interaction between fertiliser application rates and irrigation frequencies had notable effects on various parameters, leading to the highest grain yield of 227.62 g.pot-1 with the combination of N1 and I1 and the lowest (168.00 g.pot-1) with N3 I3. The agricultural experiments were facilitated using the Matlab fuzzy toolbox, employing the Mamdani inference method. Fuzzy rules were delineated for nitrogen application rates and irrigation frequencies, with three fuzzy sets each. Membership functions were developed utilising Matlab's fuzzy interface system (FIS) editor and membership function editor, optimising leaf chlorophyll content, evaporation rate as input tiger N fertilisation, and irrigation frequencies as output for precise maize production in Bangladesh.
Keywords: fuzzy decision support system, leaf chlorophyll content, maize, nitrogen management
Journal: Research in Agricultural Engineering
Pages: 155-166
Volume: 70
Issue: 3
Year: 2024
DOI: 10.17221/35/2024-RAE
File-URL: http://rae.agriculturejournals.cz/doi/10.17221/35/2024-RAE.html
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Handle: RePEc:caa:jnlrae:v:70:y:2024:i:3:id:35-2024-RAE

Template-Type: ReDIF-Article 1.0
Author-Name: Fedir Melnychuk
Author-Workplace-Name: Department of Reclaimed Land Use, the Institute of Water Problems and Land Reclamation of the National Academy of Agrarian Sciences of Ukraine, Kyiv, Ukraine
Author-Name: Svitlana Alekseeva
Author-Workplace-Name: Department of Reclaimed Land Use, the Institute of Water Problems and Land Reclamation of the National Academy of Agrarian Sciences of Ukraine, Kyiv, Ukraine
Author-Name: Oleksandra Hordiienko
Author-Workplace-Name: Department of Reclaimed Land Use, the Institute of Water Problems and Land Reclamation of the National Academy of Agrarian Sciences of Ukraine, Kyiv, Ukraine
Author-Name: Oleksii Nychyporuk
Author-Workplace-Name: Green House, Kyiv, Ukraine
Author-Name: Andrii Borysenko
Author-Workplace-Name: Department of Hygiene and Ecology, the Hygiene and Ecology Institute of Bogomolets National Medical University, Kyiv, Ukraine
Author-Name: Nataliia Didenko
Author-Workplace-Name: Department of Reclaimed Land Use, the Institute of Water Problems and Land Reclamation of the National Academy of Agrarian Sciences of Ukraine, Kyiv, Ukraine
Title: The efficiency of unmanned aerial vehicles application for rapeseed productivity in Ukraine
Abstract: 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 applied using UAV provided effective protection of crops against cereal weeds. The spraying solution (herbicide) Evolution, together with Amigo Star, contributed to destroy of annual cereals by 94-100%, which was at level of effectiveness for ground sprayer application. The higher yield of rapeseed was 4.08 t.ha-1 for variant with spraying solution by UAV with a consumption rate of 15 L.ha-1 and corresponding indicator reaches 4.13 t.ha-1 with a rate of 200 L.ha-1 for ground-based spraying. The advantage of using UAVs is the quicker application, as well as a lower rate of water consumption for preparing spraying solution, compared to ground spraying.
Keywords: cereal, ground spraying, herbicide, high-precision technology
Journal: Research in Agricultural Engineering
Pages: 167-173
Volume: 70
Issue: 3
Year: 2024
DOI: 10.17221/87/2023-RAE
File-URL: http://rae.agriculturejournals.cz/doi/10.17221/87/2023-RAE.html
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Handle: RePEc:caa:jnlrae:v:70:y:2024:i:3:id:87-2023-RAE

Template-Type: ReDIF-Article 1.0
Author-Name: Ali Hajizadeh Namin
Author-Workplace-Name: Biosystem Engineering Department, Agricultural Research Institute, Iranian Research Organization for Science and Technology, Tehran, Iran
Author-Name: Abbas Akbarnia
Author-Workplace-Name: Biosystem Engineering Department, Agricultural Research Institute, Iranian Research Organization for Science and Technology, Tehran, Iran
Author-Name: Rouzbeh Abbaszadeh
Author-Workplace-Name: Biosystem Engineering Department, Agricultural Research Institute, Iranian Research Organization for Science and Technology, Tehran, Iran
Author-Name: Ali Zenouzi
Author-Workplace-Name: Biosystem Engineering Department, Agricultural Research Institute, Iranian Research Organization for Science and Technology, Tehran, Iran
Author-Name: Majid Masoumian
Author-Workplace-Name: Biosystem Engineering Department, Agricultural Research Institute, Iranian Research Organization for Science and Technology, Tehran, Iran
Title: Effect of physical energy on germination and seedling vigor of alfalfa seeds (Medicago sativa L.)
Abstract: 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 exposure) in terms of seedling length, germination rate index (GRI), vigor index, and seed germination. The results indicated that cold plasma treatment and a combination of plasma and magnetic field treatment significantly increased the germination rate compared to the control and other treatments. Furthermore, the combined treatment of plasma and electromagnetic fields, as well as the individual treatment with magnetic fields, resulted in a significant increase in root length and, consequently, the allometric coefficient. Non-thermal technologies are a promising approach to enhancing seed performance, particularly in terms of the rate of germination and seedling length.
Keywords: early growth, electromagnetic field exposure, magnetic field exposure, plasma exposure
Journal: Research in Agricultural Engineering
Pages: 174-180
Volume: 70
Issue: 3
Year: 2024
DOI: 10.17221/114/2023-RAE
File-URL: http://rae.agriculturejournals.cz/doi/10.17221/114/2023-RAE.html
File-Format: text/html
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Handle: RePEc:caa:jnlrae:v:70:y:2024:i:3:id:114-2023-RAE