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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. Lizi Jiaohuan Yu Xifu/Ion Exchange and Adsorption Fa yi xue za zhi Dianzi Yu Xinxi Xuebao/Journal of Electronics and Information Technology Research Journal of Chemistry and Environment

Submission Deadline
26 Jun 2024 (Vol - 55 , Issue- 06 )
Upcoming Publication
30 Jun 2024 (Vol - 55 , Issue 06 )

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
Transportation Engineering
Industrial Engineering
Industrial and Commercial Design
Information Engineering
Chemical Engineering
Food Engineering

Developing Soil quality indices for soil applied sulphur under major black gram (Vigno Munga. L) growing major contrasting soil series

Paper ID- AMA-31-03-2022-11251

The field experiments were conducted at two locations under Peelamedu and Vylogam series that shows; application of sulphur (S) along with recommended dose of fertilizer (RDF) has been significantly impact the soil quality. In Peelamedu series, the soils are swell shrink with low anion exchange capacity and high base saturation and reductant variables are such as Soil Microbial Biomass Nitrogen (SMBN), Actinomycetes, Acid Phosphatase, Alkalaine Phosphatase, SO42- - S, Soil Organic Carbon (SOC) and Bulk Density (BD) were retained in PC. And Vylogam series, high AEC with high sesquioxide (R2O3) ratio and the PC had 8 highly weighed variables such as soil N, P, K, SO42-, SOC, DTPA - Zn, DTPA - Fe and DTPA - Mn was selected as MDS for computing SQI. The soil quality indices were higher while applying sulphur @ 20 kg ha-1 as Potassium sulphate plus 0.5 per cent K2SO4 as foliar spray along with 100 per cent RDF in both the series.

Design and Experiment on Brush Roller Type Almond Peeling Machine

Paper ID- AMA-30-03-2022-11249

In order to solve the problem of low efficiency in peeling green husks and long–term piling up of green almonds, a brush roller type almond peeling machine was designed in this study. Driven by three–phase power and under the effect of the belt and bucket elevator, green almonds were uniformly conveyed to the peeling chamber by a screw feeder, then the almonds are subject to the reverse action between the microcone extrusion device and the roller and the green peels were partially separated from husks. On this basis, the steel brushes would peel the almonds and remove the impurities. The physical parameters of green almonds and hard shell almonds were measured, and based on the values of the parameters, the main working parts of the device were designed and analyzed, and their main structural parameters and working parameters were determined. The software Design–Expert was applied to design a three–factor–three–level response surface test on the designed brush roller type almond peeling machine. Test results showed that, the optimal working parameters of the device were: rotating speed of the principal axis was 307.5 r/min, the gap was 20.1 mm, production rate was 811.5 kg/h, peeling rate was 96%, damage rate was 2.28%. The research results can provide reference to the improvement of performance of peeling machines and design of primary processing equipment of almonds.

Biofortifying iodine in tomato with a strategy to prevent iodine deficiency disorder

Paper ID- AMA-29-03-2022-11247

A field experiment was conducted to investigate the potential of iodine biofortification in tomato fruits through fertilization of potassium iodate in soil, foliar form and chitosan complex forms. While foliar spray alone increases the iodine content in leaves, the chitosan iodate complex alone and soil application alone increased iodine content in roots and stems. However higher iodine accumulation in the tomato fruits was achieved through the combination of foliar and iodine chitosan forms, as electrostatic interaction between chitosan and iodate prevents volatilization and gradually increases the bioavailability of iodine from soil to fruits. The transfer factor was higher for iodate and chitosan complex from soil to plant. Further, the average and relative distribution of iodine in plants revealed that the chitosan iodate complex and foliar spray combination is proven to be the most effective, as it keeps adequate amounts of iodine in the roots, stems, and leaves while also increasing iodine content in the final fruit. Biofortifying iodine through iodate chitosan complex increases the iodine content in tomato fruit and introducing it in our daily diet may help to reduce iodine deficiency.

Agriculture and Use of Power in Rajasthan

Paper ID- AMA-27-03-2022-11246

Energy is a primary driver of economic growth and welfare. Provision of good quality energy is a means to improve the standard of living of the people. Power scenario in the country which had worsened over the years with the deficit at 10.1 per cent and the peak deficit at 12.7 per cent during 2009-10 has now improved somewhat, with a recorded deficit of 0.7 and peak deficit of 2.0 percent in 2017-18 state of Rajasthan has 10 per cent of India’s land, 5 per cent of its population and only 1 per cent of its water resources, a disadvantage by a factor for supply of irrigation water vis-a-vis agriculture area. To estimate the present status of farm power availability across the states at District level from secondary sources were analysed and the farm power availability at district level has been calculated. The percent change in farm power availability during 2007-08 and 2017-18. The average farm power availability in the State of Rajasthan during 2007-08 was 0.932 kW/ha and it increased to 1.414 kW/ha by the end of 2017-18, thus registering a 51.72 % increase in FPA in last tn year due to increase of solarisation and implementation of Sub-Mission on Agricultural Mechanization. Acute water shortage, erratic rainfall and recurring droughts in every district have exacerbated the situation. The development of Rajasthan’s Agriculture depends on its technological changes i.e.a change in the parameter of production function resulting directly from the use of new knowledge.

Satellite-based crop typing at cadastral level using traditional and machine learning methods

Paper ID- AMA-27-03-2022-11245

Crop typing at cadastral level is considered as an important input for precision farming, farm management, crop water requirement, crop yield assessment, and crop insurance settlement among others. Advances in satellite remote sensing, Geographic Information System (GIS), classification algorithms, and computational infrastructure provided us the opportunity to classify and map crop types at cadastral level. However, it remains a question that, which particular method of classification is best for a given site? especially when it comes to map the crops at cadastral level using satellite data. The current work is an attempt to answer this question using a combination of five data types (including, optical, SAR, merged optical and SAR, time series optical, and time series SAR), and four popular classification algorithms (including Unsupervised k-mean, supervised Maximum likelihood (MXL), Support vector machine (SVM), and Random Forest (RF)). Results reveal that the time series of optical and microwave data performs better with random forest classifiers (over all accuracy ranging between 67 to 73% and Kappa coefficient ranging from 0.54 to 0.60) as compared to other combinations and classifiers, when a 100% accuracy check approach (new approach) was used. The most of the errors occur at the margin pixels due to mixing. The current finding is applicable for a large part of the nation corresponding to heterogeneous cropping, especially during monsoon season.