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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
07 Aug 2022 (Vol - 53 , Issue- 08 )
Upcoming Publication
31 Aug 2022 (Vol - 53 , Issue 08 )

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 Zhonghua er bi yan hou tou jing wai ke za zhi = Chinese journal of otorhinolaryngology head and neck surgery Interventional Pulmonology
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

Design and Experiment on Device of Shallow Turning and Subsoiling under Specific Agronomic Requirements of Potato

Paper ID- AMA-08-12-2021-10932

Aiming at the problems such as single working performance and poor effect of subsoiling and turning soil in the operation process of potato tillage machinery, a shallow turning and subsoiling device is designed and its main structure, working principle, and corresponding agronomic requirements are described. The conditions of plowing during shallow turning and the forces between subsoiler and furrow slice during subsoiling are analyzed. The factors that affecting the effect of plowing and the quality of subsoiling operation are determined. The rotating orthogonal combination experiment is used to optimize the key components, taking the plough body angle, plough body tillage depth, subsoiler tillage depth and machine operation speed as experimental factors, the plowing rate and the tillage depth stability as experimental indexes, analyzing field test results. The structure parameters and operation parameters of shallow turning and subsoiling device are optimized by optimization module in Design-Expert 8.0.6 software, the angle of plough body is 35°, the tillage depth of plough body is 179 mm, the tillage depth of subsoiler is 356 mm, and the machine operation speed is 1.16 m/s. The experimental results demonstrate that the plowing rate is 86.23% and the tillage depth stability is 92.17%. The soil tillage requirements before potato planting can be met, the reference for design and application of potato tillage machinery is provided.

Artificial Reproduction of Snout Otter Clam (Lutraria rhynchaena Jonas 1844): An Improvement for Spawning Induction

Paper ID- AMA-07-12-2021-10930

The snout otter clam Lutraria rhynchaena - “Tu hai” is one of the seafood sources with very high nutritional and commercial values in Viet Nam. Currently, it is being cultured commercially in the northern and the central provinces. For the limited availability of seed, however, it could have met the demand for consumption in the markets. This research was performed to trials and optimized method of spawning induction so as to record seed artificial reproduction. The broodstocks were stimulated to reproduce in some different methods such as high thermal shock by weak sunlight exposure, low thermal shock, and high pH shock in natural seawater. The results showed that pH shock at 9.5 for 20 minutes and the low thermal shock at 15oC for 20 minutes were suitable for spawning. Both of the above methods yielded 100% of the broodstocks to reproduce, the reproductive indexes were high and the ratio of unfully developed veliger larvae stage was low. These results suggested that these two methods of stimulation could be processes of the artificial production of “Tu hai” for commercial scale.

Implementation of Apple's automatic sorting system based on machine learning

Paper ID- AMA-07-12-2021-10929

In order to reduce post-harvest losses, the classification of fresh apples is crucial. Taking the hierarchical transmission control system as the object, the research was carried out on the verification of the bus network can flexibly expand the motor equipment, the stable and reliable operation of the motor, and the accuracy of Apple's classification. Combine Labview virtual instrument technology to realize the design of Apple's hierarchical transmission control system based on Controller Area Network technology. Fuzzy PID and traditional PID algorithms are used to simulate and realize the operation of brushless DC motor, and compare the advantages of brushless DC motor control based on fuzzy PID to ensure the safe and stable operation of the system. Using the machine learning algorithms model for color detection, the Support Vector Machine algorithm model finally achieved the classification of the three types of apple samples with a recognition rate of 96.7%.

Analysis of vibration transmission characteristics of cutting bench under multi-source excitation

Paper ID- AMA-07-12-2021-10928

Aiming at the vibration transmission problem of the cutting bench. The variation law of the various vibration signal when it is transmitted to the cutting bench was studied. The vibration characteristics under different forward speeds were compared and analyzed. Among the various working parts of the combine harvester, the moment that engine is started has the strongest impact on the vibration of the cutting bench, reaching 22.492 m/s2, and the vibration is transmitted rapidly. The maximum amplitude excitation frequencies corresponding to the engine, threshing drum and cutting bench are 38.086 Hz, 39.063 Hz and 40.039 Hz respectively. After the cutting bench was started, the vibration amplitude was up to 1.198 μm. From idle working state to high-speed working state, the maximum value of cutting bench vibration increased by 31.27%, and the root mean square value increased by 9.64%. There is a positive correlation between cutting bench and harvester’s forward speed. The maximum amplitude corresponding to idle working state is 3.629 μm. The corresponding maximum amplitude increases to 6.031 μm at high-speed working state. This paper provides a basis for vibration transmission analysis of combine harvester.

Calibration and Model Optimization of Simulation Contact Parameters of Potassium Fertilizer Particles Based on Discrete Element Method

Paper ID- AMA-07-12-2021-10927

To accurately obtain the contact parameters between the discrete element model of potassium fertilizer particles and improve the efficiency of the simulation test, the contact parameters between potassium fertilizer particles were calibrated and the potassium fertilizer particle model was optimized. Firstly, the nonstandard ball model of potassium fertilizer particles was established in EDEM 2020 software. Secondly, taking the contact parameters between the discrete element model of potassium fertilizer as the experimental factors and the accumulation angle as the response value, the central composite test was designed to obtain the contact parameters of the discrete element model of potassium fertilizer particles. Finally, based on the response surface method of the regression model, the particle size of the potassium fertilizer particle model and the smoothness of the filled particle model were optimized to obtain the optimal discrete element particle model of potassium fertilizer, and the verification tests before and after optimization were carried out. The experimental results show that the relative error between the optimized simulation test and the physical bench test is 0.58%, and the simulation time after optimization is saved by 67.16% compared with that before optimization. The optimized potash particle model improves the simulation efficiency on the premise of ensuring the accuracy of simulation, and the research results can be used as a reference for studying the characteristics of potash particle material by the discrete element method.