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AMA, Agricultural Mechanization in Asia, Africa and Latin America

Submission Deadline
26 Sep 2023 (Vol - 54 , Issue- 09 )
Upcoming Publication
30 Sep 2023 (Vol - 54 , 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:

Agricultural and Biological Sciences
Electrical Engineering and Telecommunication
Electronic Engineering
Computer Science & Engineering
Civil and architectural engineering
Mechanical and Materials Engineering

Chemical and Biological Control Measures against Cumin Wilt Incited by Fusarium oxysporum f. sp. cumini

Paper ID- AMA-05-01-2022-11000

Wilt of cumin incited by Fusarium oxysporum f. sp. cumini is one of the important disease and a big constraint in successful cultivation. An investigation was made to minimize this disease by use of systemic and non systemic fungicides. All the fungicides significantly inhibited the mycelial growth of Fusarium oxysporum f. sp. cumini as compared to check at 100, 200, 500 ppm concentration. Carbendazim was found significantly superior at 200 and 500 ppm with maximum inhibition of mycelial growth followed by carbendazim+mancozeb. As the concentration of fungicides increased, the inhibition of mycelial growth was also increased and maximum inhibition was observed at 500 ppm concentration. Hexaconazole was least effective. All the fungicides tested as seed dresser, reduced wilt incidence of cumin in both the years and carbendazim was found significantly superior with minimum disease and maximum yield over control followed by carbendazim+mancozeb. Pooled analysis of two years data revealed that the maximum disease control (72.24%) was recorded in the treatment soil application of FYM + seed treatment with Trichoderma with maximum per cent yield increase (218.34) followed by soil application of Neem cake + seed treatment with Trichoderma with (64.33%) disease control and (202.05%) yield increase. The control resulted maximum incidence of wilt (61.06%) with lowest yield (99.25kg/ha) as compared to all other treatments.

Comparative technical-economical evaluation of gasification-based treatment of municipal solid waste

Paper ID- AMA-03-01-2022-10998

A technical-economic analysis of municipal solid waste (MSW) gasification was carried out in the commune of Chillán, Chile. The MSW production was quantified and characterized in the 2015-2018 period. The percentage characterization of MSW corresponded to organic matter (61 %), other waste (17 %), plastic (10 %), paper and cardboard (8 %) and glass (4 %). In the analysis, the countercurrent fixed-bed gasification technology was selected, due to the simplicity of operation and less difficulty in controlling the operating parameters. Flow diagrams and gasification mass and energy balances were developed incorporating three preliminary processing options for the wet fraction of MSW: biodigestion, drying and pressing, prior to gasification. Total energy efficiencies were 54.2 %, 54.6 %, and 61.4 % respectively. Finally, a preliminary economic analysis was carried out considering income and costs for the three process alternatives. The approximate annual gross profits were estimated at 6,462,000 US $ ∙ year-1 for press-gasification, 6,139,000 US$ year-1 for drying-gasification and 4,600,000 US$ year-1 for biodigestion-gasification.

Allometric Equations For Predicting Biomass Of Young Canarium Tree (Canarium indicum L.) To Handle Climate Change

Paper ID- AMA-01-01-2022-10997

Canarium tree as a source of food, energy, health and cultural development has been widely discussed but not in terms of biomass content. In general, studies have not been carried out properly regarding its ability to provide environmental services, especially in dealing with climate change. Therefore, this study aims to determine the value of Biomass Expansion Factors (BEFs) and Root to Shoot ratio (R/S). Beside that, to determine the allometric equation for young Canarium to be used in dealing with climate change. This is done through the Monitoring Reporting and Verification (MRV) System under the United Nations Guidelines for Reducing Emissions from Deforestation and Degradation (UN REDD). There were 32 young canaries at seedling and sapling levels aged 9-21 months in the nursery area, with a diameter of 3.4 - 4.9 cm and a height of 1.32 - 2.48 m. Before determining the allometric equation, the classical assumption test is carried out first. Young canaries have R/S value 0.52 and BEF values 1.50. The allometric equation is Y1 = -700,200 + 209.149X1 + 3.922X2 where Y1 = biomass above ground level, X1 = diameter, X2 = height with R squared 0.386. To calculate the total above and below-ground biomass simultaneously, the following 3 steps were carried out: (1) Calculating above-ground biomass using the allometric equation Y1 = -700,200 + 209.149X1 + 3.922X2, (2) calculating below-ground biomass by utilizing R/S value 0.52 and (3) summing above and below-ground biomass.


Paper ID- AMA-31-12-2021-10996

Building a dynamic model to meet control requirements is a challenging problem. This paper presents a sliding mode control law and proves its stability for parallel robots containing parameter uncertainties and noise. Next, simple and complex dynamic models were built to establish the sliding mode control law. Finally, trajectory errors of the control using two different dynamic models are compared to conclude which model is more suitable.

A novel method for real-time monitoring of rice blast applied to rice field pesticide applicator

Paper ID- AMA-31-12-2021-10995

Variable rate application is an effective way to realize low-pollution and high-efficiency use of pesticides. Real-time and accurate identification of disease information is a key prerequisite that affects the development of variable application technology. At present, the identification of diseases is mainly determined by the method of artificial field sampling, which not only is time-consuming and laborious, but also has disadvantages such as poor representativeness, strong subjectivity, and poor timeliness. Rice blast, which is the most severely affected by rice, is chosen as the object in this paper. Firstly, this paper proposes a rice blast online monitoring and real-time spraying system suitable for rice field sprayer. The pesticide will be sprayed according to the severity of the disease during the sprayer doing field inspections. Secondly, existing convolutional neural networks have slow convergence speeds in the identification of small samples of rice blast, which is prone to problems such as over-fitting. To solve the meaning problem, this paper proposes a rice blast monitoring algorithm based on migration learning. The knowledge learned by the VGG-16 network on the ImageNet image data set is transferred to this model, and a brand-new fully connected layer is designed. Finally, experiments show that the accuracy of the constructed rice blast identification model can reach 97.18%. It provides a reference for the intelligent diagnosis of diseases.