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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

Domestication to De novo domestication: Step Towards Gene Editing Revolution

Paper ID- AMA-09-12-2021-10938

Domestication of wild species round the clock over millennium leads to high yielding varieties of crops well adapted to present growing conditions. Although, humans have benefited from modern technologies to improve agriculture capacities leads to higher production yet growing human population in 21st century needs feeds, cloth, shelter and fuels with limited land availability loaded with additional modern challenges, including climate change, abiotic and biotic stresses. Conventional plant breeding is continuous process focused towards satisfying global food security constrained by environmental calamities, linkage drag, narrow range and insufficiency of genetic diversity etc. De novo domestication through modern gene editing tools have facilitated the development of ideal engineered crops from wild species with desirable agronomic and productivity traits for universal food dependability and safety without loss of valuable genetic diversity. CRISPR/Cas-based gene editing tool intensify efficacy and efficiency of precise gene editing. It is viable tool that has elevated the likelihood of de novo domestication of wild species of crop plants resultant to ideal non-genetically modified crops that can accord to increased yield potential and biotic and abiotic stress resistant characters. De novo domestication helps in designing novel crop ideotype with retained biotic and abiotic stress potential of wild plant which generally losses due course of domestication, a major pitfall of traditional breeding. This review summarizes how de novo domestication through gene editing has been mobilized for trait improvement and harness useful alleles from wild species in different crops.

An integrated framework for apple recognition and localization using deep learning and machine vision

Paper ID- AMA-09-12-2021-10936

With the wide application of Internet of Things technologies, the apple harvesting method is transformed from manual to intelligent and automatic mode. The accurate apple recognition and localization in the orchard is the basic step for the automatic picking. However, most of the existing research focused on the one part of the detection system or just detection of apples in the orchard, which often lead to the not applicable in real-life environment or long computation time of detection. To meet these issue, an integrated framework for apple recognition and localization using deep learning and machine vision is proposed. Firstly, the two sided stereovision camera is configured to establish an automatic apple recognition and localization system. Secondly, the Yolo v3 algorithm is applied to fulfil the apple recognition target. Then, the three dimensional (3D) model reconstruction technology is used to achieve the apple localization goal. At last, a case from our lab is used to demonstrate the feasibility and effectiveness of the proposed method.

The Pivotal Role of Home Environment in Academically Bright Rural Young Adolescents’ Creative Endeavors

Paper ID- AMA-08-12-2021-10935

During the recent few decades educators and parents have emphasized on the special talents, needs and abilities of children. Therefore, solving problems in creative way is recognized as a major factor in achieving high educational aims which is only possible through creativity. Additionally, world requires innovators to solve global social, economic and environmental issues. Hence, both creativity and innovation have become areas of concern worldwide. Hence, the present study was designed in such a way to investigate the influence of home-environment related variables (number of siblings, birth order and land holding) on the young adolescents’ creativity. To achieve this aim, standardized Passi Test of Creativity (PTC, 2006) developed by B.K. Passi was implemented on 300 academically bright rural young adolescents (both boys and girls) aged between 12 and 14 years. Results findings elucidated significant differences in unusual uses flexibility across birth order of the adolescents. Unusual uses fluency, unusual uses flexibility and unusual uses creativity had significant differences across number of siblings. Highly significant differences were elucidated in young adolescents’ inquisitiveness level.

Development of Image Analysis method for physical characterisation and determination of fibre content by physicochemical analysis of banana pseudostem

Paper ID- AMA-08-12-2021-10934

Banana pseudostem varieties from triplod cultivars of Musa acuminata (A) and Musa balbisiana (B) were evaluated in this study for fibre content through image analysis techniques. The samples were dried at 600C in tray drier and were subjected to proximate analysis. At the moisture content of 95.60,94.65,93.20,93.20 and 97.40% for five different cultivars namely Poovan (AAB), Neypoovan (AAB), Rasthali (AAB), Karpuravalli (ABB) and Monthan (ABB) proximate analysis showed Monthan has the highest fibre content (38.4±0.32) and lowest fat content (3.5±0.02). Morphological analysis including size and colour was performed through image processing using LabView software and validated with standard measurements(p≤0.05). Acquired images were subjected to histogram representation through R, G and B components showed a wide range from 5 to 255 for different varieties. The results indicated that colour of Monthan variety (ΔE 57.88±0.3) is lowest compared to other varieties and hence more suitable for development of fibre enriched food products. Image processing was used to measure the external and internal properties of intact fibre in the banana pseudostem for its effective quality grading.


Paper ID- AMA-08-12-2021-10933

Dazomet can effectively suppress the outbreak of blight by killing a variety of nematodes and pathogens in the soil. There are few studies on the application dosage and the uniformity of dazomet by mechanized spreading. The motion model of dazomet, which can be the theoretical basis for experimental study, was obtained by analyzing the motion characteristic of dazomet in the centrifugal disc spreading process. Taking rotation speed of the spreading disk, opening degree, and forward speed as control factors, and the application dosage and the uniformity (transverse coefficient of variation) of dazomet in the designated spreading area as evaluation index, a bench test based on Box-Behnken Design (BBD) test method was carried out. Quadratic regression equations of application and uniformity amount with control factors were established respectively. In the end, a strategy to determine the combination of working parameters was proposed, and a verification test is carried out to confirm the accuracy and rationality of the strategy. The results indicate that the combination of working parameters based on the strategy meets the technical requirements of the dazomet spreading.