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.
WOS Indexed (2025)
27 Nov 2025 (Vol - 56 , Issue- 11 )
30 Nov 2025 (Vol - 56 , Issue 11 )
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
Evaluation of Real-Time Target Path Adjustment in Autonomous Driving Performance for an Agricultural Autonomous Platform
This study developed and evaluated the performance of an autonomous driving system that enhances the work efficiency and precision in orchard work. The autonomous driving system includes a main controller equipped with an RTK-GPS and IMU, automatic steering wheel, interface box, and a one-touch switch. The experimental conditions included a one and two-stage variable driving test where the path-position deviation was altered to 10, 20, and 30 cm on both a standard paved road and test orchard field at a tractor speed of 2 km/h. On the test orchard field, adjusting the work path to 10 cm and 20 cm resulted in a positional error of approximately 2 cm between the initial adjustment and the return to the original driving path. For a 30 cm adjustment in the work path, position errors were noted at 10 cm for both the initial change and return, with heading angle errors of 4 degrees; however, the vehicle exhibited stable driving on the autonomous path after re-entering the initial path.
A Novel Optimization Design Method of Picking Robot Based on MBSE and Lean Thinking
Aiming at the problems of low efficiency and poor accuracy of the existing picking robot, this paper proposes a novel optimization design method based on MBES and lean thinking. Firstly, the optimization analysis is accomplished by deeply excavating the potential lean factors in robot design requirements. Then the functional architecture is established by operational analysis and system analysis. Based on the analysis results, the lean optimization design of the robot is studied. Specifically, by constructing the value flow of the picking process, the picking manipulator is optimized from a fully flexible arm to a rigid-flexible hybrid structure. Furthermore, in order to reduce the waste of time in the picking process, the DMAIC method is used to optimize the action of the picking equipment on both sides to operate separately, so as to improve the picking efficiency.
Impact of different spatial geometries of Gmelina arborea on performance of lentil varieties in Bundelkhand region
Gmelina arborea-based agroforestry provides farmers with increased economic benefits, improves soil health, helps counteract the decline in national forest cover, and offers raw materials for both industrial use and local community needs. The study examined three different spacings of Gmelina arborea: 5 m × 5 m, 5 m × 4 m, and 5 m × 3 m, under two growing conditions: sole cropping and intercropping. Data analysis revealed that lentil varieties grown in open conditions exhibited better growth and yield attributes than those grown in agroforestry. The analysis of various growth and yield characteristics indicated that growing environment significantly affected plant growth and yield attributes. Specifically, parameters such as plant height (37.76 cm), number of primary branches (5.34), root nodules per plant at 90 days after sowing (1.23), dry matter accumulation (9.43), days to physiological maturity (124.43), days to 50% flowering (77.1), pods per plant (87.6), straw yield (1732 kg ha-1), grain yield (1014 kg ha-1), and biological yield (2746 kg ha-1) were all higher in sole cropping as compared to agroforestry. IPL 316 lentil variety performed better compared to L 4727 in both cropping systems. Overall, Gmelina arborea-based agroforestry yielded greater economic returns than sole cropping.
Molecular Characterization, Assessment of Bread Wheat Genotypes Triticum aestivum L. Grown in Algeria using Microsatellites SSR Markers
Bread wheat (Triticum aestivum L.) genotypes was the most important cereal crop in Algeria. Twenty Algerian and introduce genotypes used in this study with a set of 18 wheat microsatellites molecular markers (Simple Sequence Repeat-SSR). This study is to use SSR marker to examine their utility in detecting DNA polymorphism and assessing genetic diversity. A total of 62 alleles were detected at 13 loci using 13 microsatellites primer pairs. The total numbers of alleles per locus (Na) ranged from 4 to 7 with a average of 4,7 alleles. The mean values of the number of effective alleles (Ne), and Shannon’s information index (I) were estimated at 3,425 and 1,31 respectively. The observed heterozygosity (Ho) values scored 1.00 at all loci, and the Polymorphic information content (PIC) values ranged from 0,60 at the locus WMC19 to 1,00 for the primer WMC25 averaging at 0.72. The mean observed heterozygosity (Ho) was slightly higher than the mean expected heterozygosity (He), determining a negative fixation index (F) at all loci, (average F=-0.45). Both groups of local bread wheat populations (Algerian) and those introduced from CYMMIT have almost the same number of alleles, (Na) 55,0 and 54,0 respectively. While the mean observed heterozygosity (Ho) was similar in the two groups, (He) was higher in Algerian genotypes, resulting in a negative fixation index (F) for both these two groups. The phylogenetic tree divided the 20 genotypes into two clusters. AMOVA revealed diversity within populations at 99% and between populations at 1%. The current populations were found to be highly structured. STRUCTURE analysis showed three groups at K =3. The first Group has the largest number of genotypes. The results proved the microsatellite markers SSR utility in detecting polymorphism due to the discrimination of various genotypes and estimating genetic diversity.
Development of a forest fire risk prevention plan (FFRPP) in the municipality of Dar Yaghmouracen, Algeria
Fires are the main problem affecting forests, as human presence in or near the forest largely determines the ignition and spread of fire. Therefore, the study of forest fire risk must be undertaken considering both the social and spatial aspects of fire risk through a specific approach. The proposed forest fire risk prevention plan (PPRIF) for the municipality of Dar Yaghmouracen, based on an assessment of hazards and stakes, delineates five risk zones. The high-risk and very high-risk zones represent 54.33% of the study area, while the low-risk zone accounts for 5.72%, and the moderate-risk zone covers 39.95%. Preventive measures are prescribed for each risk level, including the establishment of lookout posts, the clearing of brush along roadsides, and thinning and pruning activities. In light of the significant threat posed by wildfires in recent years, the ultimate goal of this initiative is to persuade the forestry administration to extend such preventive measures to other forests, in order to minimize human, environmental, and economic damage.