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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

IoT based patient care model for highly communicable diseases in times of Covid19

Paper ID- AMA-26-06-2022-11496

As Covid-19 has become a matter of concern and provocation in the medical sector, the Internet Thing has enhanced humanity through advanced patient care in the healthcare zone. This is accomplished by the employment of a remote patient monitoring system. Consequently, the IoT-based monitoring systems are remarkably favorable for Covid-19 patients. The enactment of patient the health monitoring system is worthwhile as it remotely estimates the health condition of the patient. This has ameliorated the healthcare services by evading the physical contact, thereby facilitating the timely detection of coronavirus cases. The fundamental idea of this paper is to propose a patient monitoring system in times of Covid-19. The dataset of coronavirus patients is taken from API. This dataset comprises pulse rate and oxygen saturation, body temperature, and blood pressure monitor. The final evaluation and analysis have been done to depict the medical condition. The system will monitor mainly the pulse rate and the oxygen level, body temperature, and blood pressure monitor by the adoption of various sensors and the microprocessor Arduino Uno. In the presence of the ESP8266 Node MCU wi-fi module, Arduino will assemble the data from the numerous sensors and send this data to the server. The proposed design of this system is not only efficient in diminishing the fatality rates but also builds up the lives of humans the times of compulsion through its alert technique. Furthermore, this system will originate cautions to emergency services and the hospitals.

Preferences of Indigenous Fish Species according to Profitability by the Fish Farmers in Manipur, Northeast India

Paper ID- AMA-24-06-2022-11494

The current study was undertaken to determine the farmers' preferences for native fish species based on profitability in Manipur. The study involved 80 farmers from three villages in the Nambol block of Bishnupur district: Ishok, Oinam, and Naorem. A sample survey of farmers was conducted utilizing a personal interview method with a pretested and well-structured interview schedule. The respondents were chosen using a random sampling method. Ngakra, Pengba, Ngaton, Ngakichow, Nganap, and Ngasang are the six indigenous fish species. They're offered in pairs to the responders (fish farmers) in 15 different combinations. The respondents were asked to choose one Indigenous fish species over the other from each pair that they believe is more profitable. The Method of Paired Comparisons was used to analyze the data. According to the fish farmers, Ngakra is first in terms of profitability, followed by Pengba, Ngaton, Ngakichow, Ngasang, and Nganap.

Varietal screening of chickpea (Cicer arietinum L.) genotypes against gram pod borer under field environment condition

Paper ID- AMA-24-06-2022-11493

Chickpea is a valued food in terms of nutrition for an expanding world population. Wide range of insect pests and diseases leads to heavy losses in Chickpea Crop. It is infested by eleven insect pest species. Among these pests, the pod borer, Helicoverpa armigera (Hubner) (Lepidoptera) is the most deteriorating insect pest causing great losses in most of the chickpea growing areas of the world. It potentially causes serious damage to all plant parts at different growth stages which lead to devastating losses in yield up to 50 per cent or even more due to its incidence. Numerous control actions are taken in order to control this pest which predominantly includes the use chemical insecticides irrationally. The Indiscriminative use of Chemicals as a means of plant protection for such a long spell of time leads to numerous hostile effects that includes insecticidal resistance, environmental pollution, sudden outbreak and resurgence of pest, and also detrimental hazards to human life. To avoid such serious predicament, there is a very sincere need of promoting and enhancing the utilization of non-chemical measures as a core part of the pest control system, in view of which, continuous research efforts are needed to be focused on Development, promotion and enhancing the use of resistant plant material so as to overcome some serious issues emerging as a result of using chemical insecticides and thereby.


Paper ID- AMA-24-06-2022-11492

Global population is expected to reach more than 9 billion by 2050 which will require an increase in agricultural production by 70% to fulfil the demand. Only about 105 of this increased production may come from the availability of unused lands and the rest of 90% should be fulfilled by intensification of current production. In this context use of the latest technological solutions to make farming more efficient, remains one of the greatest necessities. In the future, a farmer’s skills will increasingly be a mix of technology and biological skills rather than pure agricultural. The importance of Artificial Intelligence (AI) in agriculture can be applied cross-disciplinarity and it can also bring a revolution in the farming trend than what we are seeing today. AI-powered solutions will not only enable farmers to do more with less, but they will also improve quality and ensure a faster go-to-market for crops.

Diversity Assessment of Seedling Origin Guava (Psidium guajava L.)

Paper ID- AMA-24-06-2022-11491

Diversity among seedling origin guava population growing in sub-tropical region of Jammu was assessed during the year 2017-18. Highest value of range was recorded as 165.34 for the character number of seeds per fruit followed by 90.47 for fruit weight, 88.47 for pulp percentage and 86.49 for fruit volume with mean values of 226.33, 142.7 g, 97.96 per cent and 146.9 cc respectively. Phenotypic coefficient of variation was higher than genotypic coefficient of variation for all the characters. Heritability values for different characters ranged between 37.14 to 81.14per cent. High heritability coupled with high genetic gain was recorded for tree volume, trunk girth, 100 seed weight, total soluble solids, acidity, ascorbic acid, and yield indicating additive gene action controlling these characters. On the basis of cluster analysis 70 genotypes were grouped into five clusters showing 124.71 to 185.20 inter-cluster and 274.40 to 834.74 intra-cluster distance. The clustering pattern also indicated that geographical diversity was not an essential factor for clustering of genotypes from a particular place into a specific cluster. Different characters contributed to a different extent towards total variability. Seed weight per fruit, Tree volume, pulp weight, non-reducing sugars, 100 seed weight, number of seeds per fruit and fruit weight were the major contributors towards total variation which contributed 37.55 per cent, 26.12 per cent, 12.80 per cent, 10.22 per cent, 5.25 per cent, 3.72 per cent and 3.14 per cent towards total variation in the population.