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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 Kongzhi yu Juece/Control and Decision 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
04 Jun 2023 (Vol - 54 , Issue- 06 )
Upcoming Publication
31 May 2023 (Vol - 54 , Issue 05 )

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

Measurement of Intensity and Duration of Seed Dormancy in Different Rice Varieties by Probit Analysis

Paper ID- AMA-25-01-2022-11058

The purpose of this study was to look into the nature of seed dormancy variation in distinct maturity groups, such as early, medium, and late duration varieties. During kharif 2017, the field experiment was conducted with 54 rice varieties which were released by the Odisha University of Agriculture and Technology (O.U.A.T), Bhubaneswar and the National Rice Research Institute (N.R.R.I), Cuttack. The number of days required from the day of harvest to achieve 50 percent (DG50) and 80 percent (DG80) germination, as determined by probit analysis, which was used to evaluate the duration of dormancy. In seed biology, probit analysis is used to describe how seed germination progresses over time in response to environmental conditions (e.g. temperature, season etc). The DG50 and DG80 of the varieties ranged from 1 to 60 days and 4 to 79 days, respectively. The variety Khandagiri had the minimum dormancy period of 4 days, while the varieties CR Dhan 506 and CR Dhan 508 had the maximum of 79 days. The percentage of non-germinated seeds on harvest day (NGH0) and 7 days following harvest (NGH7) were used to determine the intensity of dormancy. The NGH0 and NGH7 ranged from 0.67% to 100% and 49.34% to 99%, respectively. Varietal variations in dormancy duration and intensity were indicated in these ranges. The majority of early varieties had a short dormancy period with low intensity, whereas the majority of mid to late varieties had a long dormancy period with high intensity. Dormancy duration and intensity had a strong positive relationship, and both had a strong positive relationship with days to flowering and days to maturity. Several late varieties were observed to have the highest seed dormancy, suggesting that they could be utilised as donors for transferring dormancy to other early varieties to avoid yield losses caused by viviparous germination.

Factors responsible for restraining stimulatory (Stand-Up) phase and strategic model to strengthen entrepreneurship-Study in context of food processing in rural Haryana

Paper ID- AMA-25-01-2022-11056

The core objective of present article is to identify the restraining factors affects the stand-up phase of food processing entrepreneurship and on the basis of outcomes reflected an integrated strategic model developed to strengthen the stimulation in entrepreneurship. For this purpose, 160 entrepreneurs engaged in Micro, small and medium units were selected from four industrially sound districts of Haryana. As being prominent agrarian state in India, food processing entrepreneurship was considerd the most favourable venture to stand-up. Data was collected personally through interview schedule. Analysis was done to understand the severity of percieved factors based on weighted mean score obtained and ranked them accordingly. Unhealthy economic situation in rural areas; heavy government taxes and poor implementation of schemes; ambiguity in selection of product were identified as highly serious factors whereas technically unsound, low awareness political unwill and untrained youth were few serious factors responsible for restraining entery to food processing entrepreneurship. The seriousness of the factors was based on computed Z score. On the basis of estimated outcomes, expert opinion and reviewed literature, a strategic model has framed to ensure the integrated efforts of all stakeholders associated with the development of entrepreneurship in the state.

Comparative efficacy of fungicides, biocontrol agents and plant extracts against wilt of clusterbean caused by Fusarium solani

Paper ID- AMA-25-01-2022-11054

On isolation, from diseased plants, the associated pathogen was identified as Fusarium solani and its pathogenicity was confirmed on susceptible cultivar RGC 197 by seed, soil and seed-cum-soil inoculations under artificially inoculated conditions. Comparative efficacy of fungicides by poison food technique shows that only carbendazim and carbendazim + mancozeb both fungicides gave complete inhibition of mycelial growth at 200 and 300 ppm while Fosetyl aluminium + Fluopicolide was found least effective at all concentration. Similarly the antagonistic activity of six biocontrol agents was tested by dual culture technique and results revealed that the maximum inhibition of mycelial growth (85.20%) was recorded by Trichoderma harzianum while theminimum was by Bacillus subtillis (64.00%). Among five plant extracts, Neem was found most effective in inhibiting mycelial growth (56, 78 and 80%) while Datura (40.00, 60.00 and 61.00%) were found least effective.

Design and Experimental Research on Distribution Mechanism of Liquid Manure Spreader

Paper ID- AMA-25-01-2022-11053

To solve the problems of high error on both sides and high coefficient of variation during the liquid manure distribution, This work designed a distribution mechanism integrating conveying, stirring and distribution functions, combing with the physical properties of selected liquid manure. Taking rotor speed, inlet flow and moving cutter structure as test factors, the Design-Expert 8.0.6 software was used to design "three-factor three-level quadratic regression" orthogonal test and establish response surface regression model. Through observing relative error and coefficient of variation, we performed uniform distribution characteristics test and parameter optimization of liquid manure. The results showed that the primary and secondary order of influencing factors on the relative error is rotor speed> inlet flow > moving cutter structure; the primary and secondary order of influencing factors on the coefficient of variation is inlet flow > moving cutter structure> rotor speed. Further, the optimization test indicated that 170 r/min rotor speed, 80 m3/h inlet flow, combined with arc-shaped moving cutter structure could output 10.50% relative error and 9.30% variation rate, which was less than 5% relative to the model predicted value.

Application of Different Deep Learning Algorithms in Forestry Production Management and Processing

Paper ID- AMA-25-01-2022-11052

Forest resources are the most precious natural resources of human beings. According to the national strategic planning and guidance, China's forest area increases continuously, quality rises steadily, and efficiency increases continuously. In recent years, the deep integration of artificial intelligence technology represented by deep learning and forestry production management and processing industry is one of the important trends to realize the green and intelligent development of forestry. This paper summarizes the research progress of target detection, recognition and classification based on different deep learning algorithms and models in forestry production management and processing, comprehensively compares the advantages and disadvantages of different model algorithms, and puts forward some research suggestions, such as establishing multi-source database, optimizing algorithm model, improving hardware configuration, etc., which provides a reference for the intelligent development of forestry industry.