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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

A Boundary Detection Algorithm of Agricultural Machinery Operation Area Based on Accelerated KNN

Paper ID- AMA-04-03-2022-11182

The acquisition of the operation area of agricultural machinery is the premise for the service pricing and granting government subsidies of agricultural machinery. The objective of this paper is to develop a KNN algorithm based on amending mechanism and pruning optimization (KAP) in the case of irregular fields, which could reduce error and accelerate the process. The algorithm consists of two stages. The first stage uses KNN, generating convex or non-convex hulls that represent the area occupied by arbitrary sets of points, to detect boundary, and the second stage uses amending mechanism to correct the results obtained in the previous stage to improve the accuracy. Only the points close to the boundary could affect the detection and amending results. Based on this, the pruning optimization is used to speed up operations without sacrificing accuracy in the two stages. According to a series of accurate experiment with repeatability, compared to traditional KNN, addition of amending mechanism can reduce the error by at least 2%. The use of pruning optimization accelerates the first stage by 30% - 100% and the second stage by 2-20 times.The results illustrate that the KAP algorithm could be competent for calculation in irregular field.

Brain Tumour detection using Advanced Morphological Techniques

Paper ID- AMA-04-03-2022-11181

Brain tumour segmentation and detection requires efficient and rugged algorithms. All tumour images may not have same pixel intensity and contrast values. To identify the tumor in the brain is challenging task. Here, Brain Tumour detection using Advanced Morphological Techniques have been developed with histogram Normalisation, Thresholding, Fast Fourier transform (FFT), Fast Fourier transform(FFT) techniques. In this research, Length, Area of tumor and brain have been calculated and also calculated the statistical parameters. Also, proposed technique has been compared with the K-NN, NSC IN Gaussian Case, K-Means with Euclidian.

Optimization of the Metering Device of a Garlic (Allium sativum L.) Planter

Paper ID- AMA-04-03-2022-11180

This study determined the planting practices of Ilocos Norte, Philippines garlic farmers. Most farmers use the Ilocos White variety of garlic as planting material. Garlic fields range from 0.1 to 1 hectare with an average of 0.82 hectares. Planting distance range from 15.24 to 20.32 centimeters, with an average of 17.93 centimeters. This study also developed a garlic planter metering device in accordance with farmers’ inputs with a focus on determining the metering device’s optimal picker speed. The optimum speed should have a high percent singulation and low percent missed hills. Singulation is the ability of the cup conveyor to deliver only one clove to the delivery chute. Missed hills are deliveries without any cloves. Test speeds included 0.02, 0.035, and 0.05 m/s. A constant speed motor with different pulley systems drove the garlic planter on a test rig. Using the Design Expert Version 11 Response Surface – I-optimal Linear and Quadratic models, the optimal picker speed was determined to be 0.037 m/s with predicted values of percent singulation and missed hills as 71.27% and 5.88%, respectively. A confirmation test determined the actual performance of the metering device at the optimal picker speed. The percent singulation and percent missed hills of the planter in the confirmation test were 70.59% and 7.59%, respectively. ANOVA showed that the predicted values had no significant differences to the actual values.

Correlation coefficient and path analysis studies in okra (Abelmoschus esculentus L. monech)

Paper ID- AMA-02-03-2022-11177

The current study used twenty-five okra genotypes to evaluate the genetic variability, heritability, and genetic advance as a percentage of the mean. During rabi 2020-21, all twenty-five genotypes were evaluated in a randomized block design with three replications. For all the features, analysis of variance revealed a significant level of variability across the genotypes, indicating a broad range of variability across the genotypes. Number of fruits per plant has recorded the highest GCV and PCV followed by number of nodes per plant. This suggested that the environment had the least impact on the manifestation of these features. High heritability coupled with high genetic advance as per cent of mean were observed for number of fruits per plant, plant height, fruit length, number of ridges per fruit, 100 seed weight, number of nodes per plant, number of branches per plant, average fruit weight, fruit yield, fruit diameter, number of locules per fruit, days to 50% flowering, peduncle length, stem diameter at final fruit harvest, days to first fruit harvest. While in correlation studies number of nodes per plant followed by number of branches per plant, fruit diameter, number of ridges per fruits, average fruit weight, 100 seed weight has shown positive and high significant association with fruit yield per plant. Elsewhere fruit length has negative and highly significance. Path analysis revealed that positive direct effect on fruit yield per plant per plant was observed by number of nodes per plant, number of branches per plant, fruit diameter, number of ridges per fruit, number of fruits per plant, average fruit weight, 100 seed weight. Whereas fruit length followed by days to 50% flowering, peduncle length, days to first fruit harvesting, stem diameter at final harvest, fruit length has shown the negative direct effect on the fruit yield per plant. As a result, these traits should be prioritised in the selection of high-yielding okra genotypes.

Research on field path tracking control technology based on multi-sensor fusion

Paper ID- AMA-02-03-2022-11176

Aiming at the problem of low automation of field transportation, the path planning and tracking control technology of tracked transfer vehicle are studied. A control system based on ROS (robot operating system) platform is designed. The system integrates the information of global satellite navigation system (GNSS) and inertial navigation system (INS), realizes the real-time acquisition of the actual position of tracked transfer vehicle in Hilly and Mountainous Orchard field with high precision, and adopts the fuzzy proportional integral derivative (PID) controller based on parameter optimization preview to realize path tracking. The test results show that under the condition of normal positioning signal, the average lateral deviation of transfer vehicle path tracking is 10cm; When the positioning signal is abnormal, the transverse deviation tracked by the transfer vehicle is 10.56cm, which can achieve the goal of automatic driving of the transfer vehicle in orchards in Hilly and mountainous areas.