AMA, Agricultural Mechanization in Asia, Africa and Latin America
AMA, Agricultural Mechanization in Asia, Africa and Latin America (AMA) (issn: 00845841) is a peer reviewed journal first published online after indexing scopus in 1982. AMA is published by Farm Machinery Industrial Research Corp and Shin-Norinsha Co. AMA publishes every subjects of general engineering and agricultural engineering.
WOS Indexed (2025)
27 Nov 2025 (Vol - 56 , Issue- 11 )
30 Nov 2025 (Vol - 56 , Issue 11 )
Aim and Scope :
AMA, Agricultural Mechanization in Asia, Africa and Latin America
AMA, Agricultural Mechanization in Asia, Africa and Latin America (ISSN: 00845841) is a peer-reviewed journal. The journal covers Agricultural and Biological Sciences and all sort of engineering topic. the journal's scopes are in the following fields but not limited to:
Agricultural and Biological Sciences
Electrical Engineering and Telecommunication
Electronic Engineering
Computer Science & Engineering
Civil and architectural engineering
Mechanical and Materials Engineering
Transportation Engineering
Industrial Engineering
Industrial and Commercial Design
Information Engineering
Chemical Engineering
Food Engineering
Heterogeneous machine learning curve fitting for accurate fault location in VSC HVDC bipolar system
Exploring advanced diagnostic methods for High Voltage Direct Current (HVDC) systems is essential to swiftly identify and address faults. A robust fault location system that can accurately pinpoint issues is crucial for minimizing downtime and improving overall system reliability. To achieve this, we propose a novel approach which involves leveraging a heterogeneous combination of machine learning and curve-fitting methods. This innovative method addresses the complexity and non-linearity of fault location and detection by utilizing machine learning algorithms to identify patterns and anomalies, while curve-fitting techniques, along with trust region optimization, refine these predictions to enhance precision. The synergy between these techniques not only improves fault location accuracy but also ensures rapid response times, thereby significantly enhancing the reliability and efficiency of HVDC systems. Results from the comparative analysis demonstrate that the proposed method, using peak current signals sampled at 135 kHz, achieves the lowest error rate max average error MAE of 0.316% , and coefficient of determination of 0.99 when the range of maximum average error in existing fault location methods is between 0.78% and 5.69%.
A Trend-Based Approach for Day-Ahead Electricity Price Forecasting and Peak/Off-Peak Hours estimation in the Local Electricity Market
Electricity prices forecasting (EPF) has gained significant attention due to its relevance in various domains, such as optimizing energy management, electricity contract pricing, demand management, and informed decision-making. In this study, We have investigated the implementation of an EFP method in the local electricity market involving prosumers and suppliers, To achieve this, we propose a novel trend based approach that combines Bidirectional Long Short-Term Memory (BI-LSTM) for day-ahead electricity price forecasting with the k-means method for identifying off-peak and peak hours. To validate our methodology, we attempted to approximate the electricity prices of the local electricity market in Germany by introducing a variation factor that allowed us to consider additional costs added to the wholesale market price (such as taxes, supplier profits, etc.). we used real data from both "ENTSO_E transparency platform" and “EUROSTAT”, we also conducted extensive tests from 2019 to 2023. the model was trained using different subsets of data, and prediction time length. We also explored two clustering approaches with two k-mean configuration using a series of 24 and 12 hour, distinguishing between daytime and nighttime periods. This trend based approach enabled us to show that we can achieve a reasonable estimation of peak and off-peak hours,, with an average accuracy of 20 out of 24 correct clustered hours over a 5-year testing period, Despite the deviation observed between the actual and predicted values by BI-LSTM. However, we noticed that the increase in renewable energy sources, particularly solar and onshore wind, impacted the model's outcomes in 2020, especially in daytime, But in subsequent years such as 2022 and 2023, after retraining the model with data that accounts for the increasing influence of renewable energies, we observed improved accuracy and adaptability. The model became more capable of estimating Peak/Off-Peak Hours, even amidst the changing dynamics introduced by the intermittent nature of solar and onshore wind energy sources.
MODELLING, SIMULATION AND HARMONIC STUDY OF AN SVC IN AN IRON INDUSTRY FURNACE
The SVC is designed to reduce disturbance caused by changes in voltage variations during normal operation of transmission lines and industrial transmission lines and industrial distribution systems. Disturbances can be caused by line faults or non-linear components such as thyristors and components such as thyristors and rapid variations in active or reactive loads. The SVC injects or absorbs reactive power in the busbar where it is installed, so as to satisfy the reactive power demand of the system. The main problem with these compensators is that the TCR introduces very strong harmonics into the network, resulting in electrical losses or even malfunctions on the electrical supply network. This research work is motivated by the desire to improve the electrical power quality of an industrial system by controlling reactive power and voltages in compliance with Cem standards (IEEE Standard 519-1992). This research describes the method used to study the harmonic performance of the SVC when the TCR is the harmonic source under consideration. The maximum voltage and the harmonic distortion of the current on the 400 kV bus caused by the harmonics generated by the TCR will be calculated. There are several solutions for compensating for these harmonics, including filtering. This solution has been known for a long time. In order to verify the performance of the proposed method, the simulation results obtained for an industrial network with compensation by an SVC without filtering were compared with those obtained with filtering.
Characterization of Rice (Oryza sativa L.) Genotypes based on Badh2 Gene Specific Marker and its Effect on Aroma Intensity
One of rice's most significant quality attributes is fragrance, and the gene badh2 (betaine aldehyde dehydrogenase) is responsible for this phenotype. In order to meet the growing demand for fragrant rice, one of the main goals of the present rice breeding programmes is to improve fragrant rice. A dominant Badh2 allele encoding betaine aldehyde dehydrogenase inhibits the synthesis of 2-AP, and the recessive allele induces 2-AP formation. The present investigation was performed to evaluate the genotype having functional Badh2 gene and non-functional Badh2 gene and its effect on aroma intensity which was tested by 1.7 % KOH a sensory method. In this study, those genotypes which gave approx. 355 bp band on Badh2 gene specific marker have trace or no aroma. Those genotypes that gave approx. 257 bp band with Badh2 gene specific marker had aroma in high intensity and those genotypes that gave both 355 and 257 bp band had aroma but less in compare to those genotypes that gave 257 bp band on Badh2 gene specific marker. Change in functionality of Badh2 causes change in aroma intensity and its presence.
Design and Evaluation of seeding machine
The use of seeding machine in the family sector presents technical and economic viability. This technology was developed as animal traction seeder for direct sowing of Corn (Zea Mays) and Cowpea (Vigna Unguiculata). The seeder can also be calibrated for other types of crops. The performance of the developed seeding machine was evaluate based on seeds, spacing indexes, field efficiency, field capacity, crop productivity as a function of the speed and working depth of the seeder and cost-benefit. The field design adopted was in randomized blocks, in a 4x5 factorial scheme, with four replications and five treatments, totaling twenty observations employed. The operational performance of the seeding machine was evaluated with four levels of quantity of seeds in the deposit (25%, 50%, 75% and 100%), showing good performance in the distribution of corn and cowpea seeds in holes, the other factor evaluated was the seeding depths (1 and 3 cm for cowpea, 3 and 5 cm for corn) in relation to speed (2; 3 and 5 km/ h). The results showed lower spacing and failed seed deposition values, and higher than acceptable values with the use of shallower and greater depths and lower speeds, with a consequent increase in the final population. However, the average field capacity and efficiency of the seeding machine were 0.12 ha/hr (8.33 hr/ha) and 71%, respectively, the value of production revenue estimated was to 65% and 69%, showing that the seeding machine is economically profitable.