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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.

Submission Deadline
01 Feb 2022 (Vol - 53 , Issue- 02 )
Upcoming Publication
31 Jan 2022 (Vol - 53 , Issue 01 )

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:

Azerbaijan Medical Journal Gongcheng Kexue Yu Jishu/Advanced Engineering Science
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

Three-objective Optimization of PMEDM Process for Machining SKD11 Tool Steel

Paper ID- AMA-07-09-2021-10697

This paper presents the results of a study on three-objective optimization when powder-mixing discharge machining (PMEDM) of SKD11 tool steel cylindrical parts. Three single-objective functions were selected for this problem. They are the minimum surface roughness (SR), the maximum material removal speed (MRS), and the minimum electrode wear rate (EWR). Besides, six main input parameters including the powder concentration, the powder size, the pulse on time, the pulse off time, the servo current, and the servo voltage were inves-tigated. In addition, the Taguchi method and Gray Relational Analysis (GRA) were used to design and analyze the experimental results. Finally, optimal input parameters to achieve the minimum SR, the maximum MRS, and the minimum EWR simultaneously have been suggested.

Multi-Objective Optimization of PMEDM Process for Minimum Surface Roughness and Minimum Electrode Wear Rate when Machining SKD11 Tool Steel

Paper ID- AMA-07-09-2021-10696

In this paper, a study on multi-objective optimization when powder-mixing discharge machining (PMEDM) of cylindrical parts made of SKD11 steel is conducted to achieve the minimum surface roughness (SR) and the speed minimum electrode wear rate (EWR). To solve this problem, an experiment was conducted with the use of the Taguchi method for design and the gray relational analysis (GRA) method to analyze the results. In addition, six input parameters including powder concentration, powder size, pulse generation time, pulse off time, servo current and voltage were taken to study their effect on SR and EWR. Moreover, optimal input parameters to achieve the minimum SR and minimum EWR simultaneously have been proposed.

Research and Test of Acoustic Signal Monitoring System of Fan Blade Based on BP Neural Network

Paper ID- AMA-07-09-2021-10695

Aiming at the difficult blade in daily maintenance of large-scale wind turbine, the sound signal of wind turbine blade can be detected by analyzing the non-contact fault of the blade. In this paper, a sound acquisition and transmission device is designed derived on stm32f103c8t6 single chip microcomputer. The device is arranged below the fan blade to collect the fan blade sound and transmit it to the PC through GPRS. The data is restored to the WAV format audio file on the PC. then LabVIEW software pre-processes the sound signal in the audio file and 1 / 6 octave processing to extract the acoustic characteristics of the blade, Finally, the BP neural network is trained and predicted by using the acoustic characteristics of fan blades in different states. The experimental results show that the training of BP neural network can be completed after 27 iterations, and the recognition rate of fault sound blades is more than 88%.

Genetic diversity analysis of recombinant inbred lines of bread wheat (Triticum aestivum L. Em. Thell) for stripe rust resistance using SSR markers

Paper ID- AMA-06-09-2021-10694

Molecular analysis revealed that out of 70 SSR primer pairs (including 40 Yr specific primers) used, 18 SSRs gave amplification. Seven Yr specific markers (Xgwm130 (Yr7), Xbarc 352 (Yr18), Xgwm 11 (Yr26), Xwmc 44 (Yr29), Xwmc 149 (Yr53), WKS1_I (Yr36) and Xcfb309 (Yr47) were polymorphic on RILs population. The amplified products varied from 120 bp to 350 bp. Cluster analysis at molecular level revealed that cluster I was the largest consisting of 39 RILs. This was followed by cluster X (33 RILs), cluster V (2 8 RILs), cluster VII (19 RILs), cluster IX (19 RILs), cluster VI (18 RILs) and cluster XI (18 RILs), cluster XII (15 RILs), cluster VIII (11 RILs), cluster III (7 RILs) and cluster XIII (5RILs). The scattered diagram on the molecular marker diversity analysis revealed that the fourteen RILs (50, 52, 56, 58, 59, 72, 97, 98, 118, 119, 120, 159, 184 and 193) were diverse. The grouping of recombinant inbred lines was not similar as in case of grouping based on morphological traits. Molecular Clustering as well as NTSYS-PC analysis clearly indicated that the recombinant inbred lines were scattered between the two parental wheat genotypes, WH711 and WH542, with an inclination towards WH542 (yellow rust resistant parent).

Determination of Optimum Farm Power and Machinery Requirement for Large Scale Sugarcane Production.

Paper ID- AMA-05-09-2021-10693

There was need to optimally determine farm power and machinery critically not only because of the high proportion of total cost attached to machinery but also of the infrequency and irrevocability of such decisions to reduce operational loss. Values of tractors with its equivalent implements field capacity, draft and power requirements, field operations ownership and operational cost for 1,300 ha Sunti sugarcane cultivation operations for 2017 and 2018 cropping seasons were determined based on farm size, weather, soil conditions and time available with regard to crop operation cultivation sequence. The available tractors and equivalent implements at site were found to be more than the number actually required except for the cane loaders, cane transporting wagons and all the cane harvesters were not in good condition, hence cane was 100% manually harvested for these cropping seasons. There was enough earth work equipment available for land clearing/development, road construction/maintenance, dyke, irrigation and drainage works. Result of field cropping operation sequencing calendar shows that operations were overlapping with multi-periods and peak periods in November to February. With reference to economic aspects of tractor utilization in this study, average use per tractor was lower than accepted range for large sized farm at peak months of operation period of November, January and February during tillage, sowing and harvesting. Actual number of tractors/implements used was more than optimum requirement, hence the farm has low number of total tractor use which made the system to have more tractors in proportion to the amount of work done.