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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
01 Feb 2022 (Vol - 53 , Issue- 02 )
Upcoming Publication
31 Jan 2022 (Vol - 53 , Issue 01 )

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
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

Classification of Pesticide Residues in Cabbages based on Spectral Data

Paper ID- AMA-23-11-2021-10877

Pesticide residue in leafy vegetables like a cabbage can cause harmful effects to consumers. Thus, early detection and classification of pesticide residue could help consumers to choose residue-free cabbages. This research was performed to evaluate the performance of different classification methods to classify spectral data collected from 60 pesticide-free cabbage samples. Deltamethrin pesticide was sprayed on the samples at different dilution concentrations namely pesticide-free (PF), pesticide-low (PL), pesticide-medium (PM) and pesticide-high (PH). The spectral data of the cabbages was recorded using a spectrometer with an effective wavelength in the range of 400 to 1000 nm. The concentration of the pesticide residues in each cabbage sample was quantified using a gas chromatography with an electron detector (GC-ECD). Three classification methods investigated in this study were artificial neural network (ANN), support vector machine (SVM) and logistic regression (LR). The results show that LR, SVM and ANN yielded excellent classification accuracies of 95, 88 and 87%, respectively. This study revealed that the spectroscopic measurement coupled with classification methods are promising technique for detecting and classifying pesticides residues in cabbage samples.

Process Optimization of Ultrasonic-Assisted-Soxhlet-Extraction of Essential Oil from Citrus hystrix using Response Surface Methodology

Paper ID- AMA-23-11-2021-10876

The essential oil from Citrus hystrix leaves is used commercially in Malaysia as a flavor and aroma agent, perfumery, and medical preparations. The main objective for this study was to determine the optimum parameters of ultrasonic pre-treatment; amplitude, particle size of leaves and pre-treatment time prior to the Soxhlet extraction for Citrus hystrix essential oil via Response Surface Methodology (RSM). Fresh Citrus hystrix leaves were dried, blended and sieved to different particle sizes before undergoing ultrasonic pre-treatment and Soxhlet extraction procedure. The ultrasonic pre-treatment was carried out at amplitude ranging from 30% to 70%, particle sizes of 100 μm to 1000 μm, and pre- treatment time of 5 min to 30 min. Soxhlet extraction was conducted for 8 hours with a solid to liquid ratio of 1:20, at the reaction temperature of 68°C using hexane. Results show that the ultrasonic amplitude of 45%, pre-treatment time of 20 minutes, and particle sizes of 200 µm were found to be optimal extraction parameters in achieving maximum oil yield after Soxhlet extraction procedure (6.98 %). Treated leaves yielded 6.54 % of oil extract which was higher than untreated leaves (5.70 %). The functional groups related to the essential oil and powder of Citrus hystrix were limonene, aldehydes, and ester as determined by the Fourier Transform Infra-Red Spectroscopy (FTIR) analysis. The Scanning Electron Microscope (SEM) images reveals that oil glands of treated leaves powder of Citrus hystrix ruptured and cell wall degradation rather than untreated samples. Therefore, ultrasonic pre-treatment could be proposed as a promising pre-treatment method combining with the Soxhlet extraction to improve the essential oil yield of Citrus hystrix.

The Effect of Maturity Stages on Calorific Values of Malayan Yellow Dwarf

Paper ID- AMA-23-11-2021-10875

Coconut plantation has the potential to contribute for biomass energy from its waste such as coconut husks and shells. This research aimed to determine the calorific value of coconut shells and husks at different maturity stages and its relationship with moisture content as the first step in determining their acceptability as alternative fuel sources. A bomb calorimetry procedure was performed to measure gross calorific values (GCV) which was used to indicate the potential of the samples to produce biofuels. It was found that the coconut shell had the highest calorific value of 22.36MJ/kg at maturity stage 4 (eleven to twelve months of age) followed by inner husk at 18.96MJ/kg and outer husk at 17.65MJ/kg. The relationship between the average GCV and maturity stages of the whole samples yielded the regression of R2=0.971. This result shows that the average GCV increased as the maturity stages increased. While the mean calorific value obtained from the shells was 16.38MJ/kg which was comparable to certain wood species. The coconut shells, which are generally not fully utilized, abandoned, and discarded, have the potential to be used as energy sources, whilst the husks have a lesser calorific value but could be used as fuel for less energy intensive uses.

Formulation and Synthesis of Pyro-Oil Derived Insect Repellent

Paper ID- AMA-23-11-2021-10874

Despite the abundance of palm-based residues produced, by-products of thermochemical processing, such as bio-oil, may create value-added products to the palm industry. The palm-based derived from bio-oil contains high concentration of aromatic compounds. This study aims to assess the formulations of major insect repellent ingredients (bio-oil as carrier for inert ingredient as well as active ingredient (AI) from lemongrass oil), to test and recommend the most effective insect repellents formulation for the mosquito species studied. Five different cream formulations were created and tested, each with a different bio-oil and AI from lemongrass extract. Based on five different cream formulations, Set C demonstrated the most effective repellency with an equal ratio of bio-oil and lemongrass extract. Set C takes the longest time to repel mosquitoes from white mice, taking 20-21 minutes at a composition ratio of 2:2 to repel mosquitoes. A few tweaks can be made to improve insect repellency efficiency, such as varying the concentration and type of active ingredient and the number of mosquitoes sampled for experiment. Hence, this study adds to our understanding of palm-based residues management towards better environment.

Prediction of Soluble Solids Content of Jackfruit from Skin Surface Using Spectroscopic Method

Paper ID- AMA-23-11-2021-10873

Soluble solids content (SSC) of a jackfruit is a critical quality indicator to evaluate the ripeness of the fruit. To date, there is no portable and low-cost device is available to be used at a field for a rapid maturity screening of a jackfruit. The purpose of this study was to investigate the feasibility of utilizing a shortwave near infrared (SWNIR) spectroscopy to predict SSC of a jackfruit from its skin surface. In this study, 29 fresh jackfruit samples were used. The jackfruits were divided into five main sections from the stalk to bottom to represent different areas of the fruits (top, upper middle, middle, lower middle, and bottom). Then, each section was further divided into six portions, producing 870 skin portions altogether. The spectral data was obtained from these 870 skin portions using a SWNIR spectroscopy. The SSC for each portion was determined using a handheld digital refractometer. A correlation between the spectral data and SSC was developed using a partial least square (PLS) regression method. For the calibration model, the value of coefficient of determination (R2) and root mean square of calibration (RMSEC) were 0.94 and 0.50, respectively. While for the prediction model, the value of R2 and root means square of prediction (RMSEP) were 0.93 and 0.50, respectively. The results indicate that the spectral data correlated well with SSC values. Thus, it is concluded that the SWNIR spectroscopy has the ability to estimate SSC of the jackfruits from their outer skin surface.