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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
16 Aug 2022 (Vol - 53 , Issue- 08 )
Upcoming Publication
31 Aug 2022 (Vol - 53 , Issue 08 )

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

Geotagged Application for Durian Trees using Aerial Imagery and Vegetation Indices Algorithm

Paper ID- AMA-24-11-2021-10894

Durian demand has increased considerably, and it has gained popularity in the market. Under Industrial Revolution 4.0, precision agriculture is expanding globally with a wide range of digital technologies that provide the farming industry with information to improve farm productivity. The objectives of this study are to geotag the durian trees and to compare several Vegetation Indices (VIs) algorithms (Visible-Band Difference Vegetation Index (VDVI), Visible Atmospherically Resistant Index (VARI), Normalized Green-Red Difference Index (NGRDI), Red-Green Ratio Index (RGRI), Modified Green-Red Vegetation Index (MGRVI), Excess Green Index (ExG), Color Index of Vegetation (CIVE), and Vegetativen (VEG)). One hundred sixty durian trees at the Durian Valley in Kluang (Johor), were tagged, which consist of four sample trees for each treatment. Every two weeks of ground data such as the height of trees, canopy width, girth’s diameter, node distance, pH value, moisture content, electrical conductivity (EC) reading, and leaf sizes were exported into the QGIS software and joined with the tagged durian trees. The aerial imagery data captured the durian plantation area using Red Green Blue (RGB) sensor with a 100 m flight attitude. pH, EC, and moisture content were interpolated using Inverse Distance Weighted (IDW) technique. The processed image by VIs and geotagged trees could help farmers to identify the problem areas in the farm and monitor durian plantation effectively.

Study on a Real-Time Plant Detection Companion Computer of an Agriculture and Forestry Surveillance Drone based on Neural Network Approach

Paper ID- AMA-24-11-2021-10893

The paper presents the results of the study of a plant detection program on agriculture and forestry surveillance quadcopter companion computers. The plant detection program uses an optimized convolution neural network to process the drone camera input video frame by frame and can process up to 38 FPS on the companion computer. The inference speeds up efficiently compared to the original SSD Mobilenet Lite V2 reach approximately 304 times. This performance is satisfied by most real-time applications for agriculture and forestry monitoring flight missions. The network was integrated on a NDIVIA Jetson Nano embedded computer and succeeded in detecting “coconut tree” in different simulation scenarios of a drone flight in real-time. The results demonstrate that the proposed approach could be used for further development of a fully plant detection system using only cameras. They also showed that a good outcome is achievable needing only cheap devices and can be implemented easily on forestry monitoring drones or agricultural drones which are familiar nowadays in Vietnam.

Preliminary Analysis of Physical and Flowability Properties in Measuring Caking Formation of Commercial Soft Brown Sugars

Paper ID- AMA-24-11-2021-10892

Soft brown sugar is a sugar product with a distinctive brown colour due to the presence of molasses, known for its added flavour and faster caramelization properties. It is widely used as an ingredient for baking goods. The problem of caking in soft brown sugar has been causing quality deterioration as well as interfering with manufacturing and handling processes in the industry. The aim of this study is to determine the possible factors leading to the caking of sugar in terms of physical properties and flowability properties. These factors are moisture content that is related to colour absorbance as an indication of molasses content, mean particle size, and flowability properties. The moisture content was found to be approximately proportional to the colour absorbance. The mean particle size and moisture content influenced the flowability of the soft brown sugar samples. Compaction of brown sugar into compacts was conducted to imitate industrial warehouse storage conditions in order to investigate the factors of caking. High moisture and fine mean particle sizes were the factors that caused formation of solid bridges between particles hence caking found in this study. In conclusion, the factors that caused caking were high moisture content and fine particle size of brown sugar samples.

Characterization of Silane Treated Nanosized Carica Papaya Seeds Modified Pullulan Composites

Paper ID- AMA-24-11-2021-10891

Combination of natural polymer with antimicrobial agents from plants for various applications have attracted many researchers due to its non-toxic properties. In this study, the effects of nano sized Carica papaya (CP) seeds (1% to 5% wt.%) from agro-industrial papaya waste modified biodegradable pullulan on thermal and mechanical properties of the composites were investigated. The effect of silane treatment upon nano sized CP seeds for improving adhesion were examined. Mechanical and thermal properties of the nanosized CP modified pullulan were assessed via tensile test, Differential Scanning Calorimetry (DSC) and Thermogravimetric Analysis (TGA). Characterization of the film was conducted via Fourier Transform Infrared Spectroscopy (FTIR) and the surface morphology via Field Emission Scanning Electron Microscope (FESEM). Tensile strength and elongation at break of pullulan increase at the expense of Young modulus with increasing CP loading. Silane treatment further increased the tensile strength and Young modulus and slightly decreased the elongation at break. The addition of CP seeds reduced the thermal stability of pullulan. The C-H, O-H, C-O-C, and C=O bond at the peaks of 2925.4 cm-1, 3286.1 cm-1, 1031.7 cm-1, and 1556.3 cm-1, respectively, were confirming the presence of pullulan and CP seeds. Si-O-C and Si-O-Si bonds appeared at the peak 1031.7 cm-1 shows the presence of 3-Aminopropyltrymethoxysilane. Morphological analysis showed that most of the CP seeds at all compositions were bounded well by the pullulan matrix due to silane treatment. Overall, the composition which exhibits an adequate thermal stability and highest tensile strength was silane treated CP modified pullulan at 5% CP content.

Optimal Treatment Systems for Palm Oil Mill Effluent (POME) using Optimization Modelling

Paper ID- AMA-24-11-2021-10890

Proper treatment system for palm oil mill effluent (POME) is crucial to protect waterways systems and enhance sustainability. Conversion of POME into electricity can utilize POME and generate economic return to the palm oil mill. Optimization modelling can demonstrate optimal operation processes and estimate potential economic return. The objective of this study is to analyze the potential treatment system of POME using a mixed-integer programming (MILP) model. The developed model considered multiple factors such as capital cost, maintenance cost, technology capacity, conversion ratio, and electricity price. General Algebraic Modelling System (GAMS) software version 26.1.0 major release was selected to optimize the developed MILP model. Based on case study, the developed model selects the anaerobic lagoon system (ALS) with biogas and the anaerobic digester (AD) as the most profitable treatment system for POME. The profit gained from the selected system was RM 2,153 900.00. The payback period for the investment was about 9.69 years with a return of investment (ROI) value of 97.71%.