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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
28 Sep 2022 (Vol - 53 , Issue- 10 )
Upcoming Publication
30 Sep 2022 (Vol - 53 , Issue 09 )

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

Standardization of Rugose Spiralling Whitefly field level images for Artificial Intelligence application on Coconut gardens

Paper ID- AMA-28-08-2021-10657

Coconut is referred as the tree of heaven, as it provides various products to the people. Coconut is grown in over 86 countries in the world with a production of 54 billion coconuts every year. Aleurodicus rugioperculatus Martin (Hemiptera: Aleyrodidae), commonly known as the Rugose Spiralling Whitefly (RSW), is commonly observed on coconut palm. The invasive pest RWS causes stress to coconut plant by removing nutrient and water and also produces honeydew which causes heavy loss to the coconut gardens. There is a need for early identification of RSW with the field level images using Artificial Intelligence. The images are collected from the field at three levels, 1. healthy leaflets 2. RSW infestation leaflets and 3. Scooty mould leaflets, of which the images are standardized by using Artificial Intelligence application, Random Forest Classifier is used to classify the images and it is an early warning system for better management of coconut gardens.

Mass Optimization on Two-stage Helical Gearboxes with First Stage Double Gearsets

Paper ID- AMA-27-08-2021-10655

One of the most significant factors affecting the cost of a gearbox is its mass, which can be changed by optimizing the gearbox ratios. Accordingly, to achieve the minimal mass of a gearbox, an optimization is needed for the partial gear ratios. The present study is aimed to minimize the mass of Two-stage Helical Gearboxes with First Stage Double Gear-sets via optimizing the second partial gear ratios. Several input factors are employed for the exploration of their effects on the optimum gear ratio of the second stage. An experimental simulation is created with the computer assistance to obtain a regression equation which then can help predict the results. The input factors and their interactions have been found to have great impacts on the response. Noticeably, the predicted values are consistent with the experiment results.

Design and experiment of end effector of Citrus picking robot

Paper ID- AMA-26-08-2021-10654

Automatic picking of fruit and vegetable crops can not only reduce the physical labor of fruit farmers in the harsh field environment, but also greatly improve the harvesting efficiency. Aiming at the problems of complex and changeable field environment and more damage of clustered citrus fruits after mechanized harvest, a new end actuator of three finger clamping cutting and picking robot is proposed in this study. The end actuator is mainly composed of clamping device and cutting device. The clamping device can realize the lossless clamping of citrus, and the cutting device can realize the rapid separation of fruit and stem. The citrus fruit is clamped and wrapped by a flexible clamping finger and then rotated to make the blade cut the fruit stalk. By analyzing the stress and shape of citrus fruit in the natural environment, the working space and structural parameters of flexible clamping fingers are analyzed, and the control motor is selected according to the stress analysis of clamping fingers. The end effector is mounted on the 6-axis mechanical arm, the stepping motor speed, the end effector speed and the picking angle are taken as the influencing factors, and the single fruit picking time and the picking success rate are taken as the evaluation indexes for the picking performance test. According to the analysis of the test results, it is concluded that the optimal parameters of the end effector are the stepping motor speed of 250r / min, the end effector speed of 160mm / min When the picking angle is 0 °, the picking performance is the best. The end effector of Citrus picking robot developed in this paper has simple structure, stable and reliable operation, and high integration with the manipulator, which can provide a reference for the overall development of Citrus picking robot.

Novel Semantic Computation Technique for Hierarchal Relationship Extraction in Taxonomies

Paper ID- AMA-26-08-2021-10653

Extracting semantic relationships between entities and objects has become very challenging with the development of Big Data, Semantic Search Engines, and Semantic Question Answering systems. It has become an important research topic in recent years and is more valuable in the fields of biomedicines, Taxonomies, Health Care Informatics, etc. When taxonomies are studied and examined semantically, the problem of relationship detection arises. This research presents a computation technique to make it fast and efficient by employing a very important Graph Theory technique. This technique is used in semantic hierarchal relationship extraction in taxonomy. Our study illustrates that the Depth First Search Algorithm can best contribute, to detect hierarchal relationships and can be applied in the performance improvement from a semantic aspect. The research proposes a simple computation technique SSM5 for hierarchal relationship detection from taxonomies using Ontology. The technique can be used in an extensive range of applications in domains like Taxonomies, Biomedical Literature Mining, Business Intelligence, Unstructured Electronic Text on the Web, and Semantic Information Retrieval.

Economic Analysis of Chickpea (Cicer arietinum L.) Production in Bundelkhand Region of Uttar Pradesh (India)

Paper ID- AMA-26-08-2021-10652

This paper studies the cost and returns of chickpea (Cicer arietinum L.) crop production in Banda District of Bundelkhand Region (U.P.). It attempts to estimates the cost of cultivation, cost of production and benefit cost ratio (BCR) of chickpea crops of different categories of chickpea growers they were categorized into four groups on the basis of their size of holdings and also 120 farmers were selected purposively for the study. The analysis of chickpea cultivation indicates that the cost of cultivation, cost of production, net return and Benefit Cost Ratio (BCR), which increases with increases the size of farms. The average of cost and returns indicates that the total of chickpea cultivation was incurred in Rs.35941.05/ha. and net income was received Rs. 23103.82/ha. by the farmers. Further the average Benefit Cost Ratio (BCR) was estimated 1:1.64, which also indicates that the per unit profits earn by the growers from chickpea production in the Banda District.