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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. 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 Zhenkong Kexue yu Jishu Xuebao/Journal of Vacuum Science and Technology Wuhan Ligong Daxue Xuebao (Jiaotong Kexue Yu Gongcheng Ban)/Journal of Wuhan University of Technology (Transportation Science and Engineering) Zhonghua yi shi za zhi (Beijing, China : 1980)

Submission Deadline
24 Mar 2023 (Vol - 54 , Issue- 03 )
Upcoming Publication
31 Mar 2023 (Vol - 54 , Issue 03 )

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

A real-time image analysis for cherry fruit classification from colour features

Paper ID- AMA-31-10-2021-10819

An image analysis algorithm for the classification of cherries in real time, by processing its digitalized color images, was developed, and tested. A set of five digitalized images of color pattern, corresponding to five color classes defined for commercial cherries, was characterized. The algorithm performs the segmentation of the cheery image by rejecting the pixels of the background and keeping the image features corresponding to the fruit colored area. Histogram analysis was carried out for the RGB and HSV color spaces, wherein Red and Hue components showed differences between each of the specified color patterns, of the exporting reference system. This information allowed developing a hybrid Bayesian classification algorithm, based on the components R and H, and testing its accuracy with a set of cherry samples, within the color range of interest. The algorithm was implemented by means of a real time C++ code in Microsoft Visual Studio environment. When testing, the algorithm it showed 100% of effectiveness in classifying a sample set of cherries, pertaining to the five standardized cherry classes. The components of the hardware-software system for implementing the methodology are low cost, which permits an affordable commercial deployment.

Study on Feature Extraction of Pig Face Based on Linear Discriminant Analysis

Paper ID- AMA-29-10-2021-10818

Individual identification and behavioural analysis of pigs is a key link in the intelligent management of a piggery, for which the computer vision technology based on application and improvement of deep learning model has become the mainstream. However, the operation of the model has high requirements to hardwares, also the model is of weak interpretability, which make it difficult to adapt to both the mobile terminals and the embedded applications. This study proposes to first use the LDA method to extract the main features of the pig’s face, and then conduct an individual recognition test based on the face image, and reach an average accuracy of 64.9%, This method not only reduces the computational complexity but also is of strong interpretability, so it is suitable for both the mobile terminals and the embedded applications. In some way, this study provides a systematic and stable guidance for livestock and poultry production.

Agricultural Engineering: A Way Towards Brighter Future

Paper ID- AMA-26-10-2021-10816

Agricultural engineering is the branch of engineering that considers the engineering techniques in agriculture to enhance the productivity, resource utilization, pre and post-harvest operations. The three major sub-discipline of agriculture engineering are, farm machinery and energy in agriculture, agricultural structure and process engineering, irrigation and soil & water conservation engineering. It can help environment by sustainable use of farm input and energy in agriculture, results in; increased production, yield, best quality of farm produces and reduction in farm wastage. In a nutshell, incorporating the advanced or innovative technologies such as sensors, AI, robotics, machine learning etc., in the current farm mechanization scenario, improves the overall agricultural productivity by reducing the human drudgery. The paper discusses about the future of agricultural engineering and how it going to help in near future.

Effect of nutrient liquid concentration on the mechanics and growth and development of tomato leaf handle

Paper ID- AMA-26-10-2021-10815

To study the effects of different nutrient solution treatment on tomato growth, quality and leaf handle mechanics. Tomato as the test material, the use of greenhouse pearl rock matrix cultivation test, set up 3 treatment N1 (1.5 times the standard concentration of nutrients), N2 (1 times the standard concentration of nutrients), N3 (0.5 times the standard concentration of nutrition Liquid), combined with conventional measurement methods, analyzes the effect of nutrient concentration on tomato growth index, provides reference for nutrient management in matrix cultivation, and uses a texturer to bend and cut tomato leaf handles, which can provide theoretical basis for the development and development of tomato-related facilities and equipment.

The vehicle controller test system of dual-motor driving electric tractor

Paper ID- AMA-26-10-2021-10814

As the core of electric tractor, the performance of vehicle controller directly determines the power and economy of the tractor. The main purpose of the design and development of the test system was to test the CAN communication effect of the whole controller and the rationality of the established control strategy. The test system adopted modular design method, and designed the vehicle controller module, driver control module, power output module, fault monitoring module and display control module. The test system simulated the real working state of the tractor and tested the control strategy of the vehicle controller. When the load of the electric tractor changed, the control strategy would adjust the torque output of the motor in real time to ensure that the two motors are in the high-efficiency zone. The test system was used to test the vehicle controller of electric tractor, which laid a foundation for the development of the whole vehicle controller of electric tractor.