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 (2026)
07 May 2026 (Vol - 57 , Issue- 05 )
31 May 2026 (Vol - 57 , Issue 05 )
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
Automatic Hand Gesture Recognition using Support Vector Machine
The prehistoric cavemen‟s earliest form of communication was gesture. Human civilization has progressed to a point where verbal communication is quite well developed. On the other hand, nonverbal interaction has not lost its importance. Nonverbal interaction is not utilized only for physically handicapped people but also for a variety of uses like variety of fields, including aviation, surveying and music. It is the most effective way to communicate with the computer without the usage of other devices like keyboard or a mouse. Researchers all over the world are working on developing a reliable and well-organized gesture identification system, particularly hand gesture identification, for a variety of applications. Data collecting, gesture modelling, feature extraction, and hand gesture identification are the primary phases involved in hand gesture recognition system. With the processes listed above, there are various sub steps and approaches. Researchers have used a variety of algorithms or created their own. The current study effect examines the work done over previous two decades and makes a quick comparison to understand the problems and limitations that these systems face. Finally the properties of a reliable and efficient hand gesture system were defined.
Evaluation of tomato (Solanum lycopersicum L.) genotypes for genetic variability, heritability and genetic advance under semi-arid conditions of Haryana (India).
The present investigation was conducted to access the relative performance, genetic variability, heritability and genetic gain in selected set of tomato germplasm, consisting of twenty genotypes along with one standard check variety. The experiment was laid under completely randomized block design (RBD) in three replications at Regional Research Station Karnal, CCS Haryana Agricultural University, during the spring summer season of 2019-20. The observations were recorded for twenty-one parameters pertaining to the morpho-phenological, yield and quality traits in tomato. Statistics from analysis of variance showed substantial differences among the genotypes unveiling the plausible presence of significant genetic variability within the selected germplasm which could be positively exploited in crop improvement programmes. The cynosure of this investigation was yield per hectare (q) which observed moderate GCV (13.67), PCV (13.77) and high heritability (98.57%) coupled with high genetic advance (27.96%). The genotypes namely Castle Rock, PNR-7, DVRT-2, DVRT-6, H-86 and Punjab Upma were found superior in terms of both overall yield and quality, whereas, PHS, H-86, Pusa Gaurav and Palam Pink were found superior in terms of earliness and quality traits.
Backstepping Sliding Mode Control - RBF Neural Network for Dual-Mass Systems
The success of the two-mass system control problem heavily depends on the accuracy information of the load torque. In the paper, a radial basis function neural network structure is proposed to deal with load torque estimation. The estimated value is integrated with backstepping- sliding mode control to guarantee speed tracking performance in the presence of a non-rigid driving shaft. The stability of the closed-loop is proven analytically and illustrated numerically. In addition, the effectiveness of the proposed control is compared with a high gain observer-based structure.
Weed Dynamics and Productivity of Potato as Influenced by Organic Sources of Nutrients and Weed Management
A two year field experiment was conducted during Rabi seasons of 2015-16 and 2016-17 to study the response of organic sources of nutrients and weed management on productivity and weed dynamics of potato. Application of 100% organics (100% recommended N through different organic sources each equivalent to 1/3 of recommended N i.e. FYM+ vermicompost + non edible oil cake) + VAM recorded significantly higher plant height, tuber yield, soil organic carbon, available N, P and K and nutrient uptake which was statistically at par with 100% organics (100% recommended N through different organic sources each equivalent to 1/3 of recommended N i.e. FYM+ vermicompost + non edible oil cake) + marigold for potato on border as trap crop and 100% organics (100% recommended N through different organic sources each equivalent to 1/3 of recommended N i.e. FYM+ vermicompost + non edible oil cake). Whereas, the application of 50% recommended N through vermicompost + biofertilizers for N + rock phosphate to substitute the P requirement + PSB recorded higher net returns and B: C ratio. Amongst the weed management treatments, application of mustard seed meal @ 5 t/ha resulted in highest plant height, tuber yield and soil organic carbon which was statistically at par with application of rice bran @ 4 t/ha and weed free treatment. Significantly lowest weed density, dry weight and nutrient uptake by weeds was recorded with weed free treatment followed by the application of mustard seed meal @ 5 t/ha and rice bran @ 4 t/ha. Among the weed management treatments, highest weed control efficiency was recorded with the application of mustard seed meal @ 5 t/ha followed by rice bran @ 4 t/ha.
Effect of irrigation scheduling on growth, yield and wateruse efficiency of Shatavar (Asparagus racemosus)
Asparagus racemosus belonging to family Liliaceae and commonly known as Shatavar, Shatavari, Satmuli, is a perennial climber found in the tropical and subtropical parts of India. Its tubers contain pharmaceutically active ingredients (steroidal saponins) and thus used in both traditional and modern system of medicines. In ayurvedic system of medicines, it is used as a galactagogue, aphrodisiac, anodyne, diuretic, antispasmodic and nervine tonic. The present investigation was conducted to assess the effect of irrigation scheduling on growth and yield of Shatavar. The experiment was conducted under Randomized Block Design with ten treatments and three replications. In the present study, 3 irrigation water depths i.e., 40mm, 50mm and 60mm were used to achieve IW and CPE ratio of 0.75, 1.0 and 1.25 in each depth. Maximum dry tuber yield ha-1 of 3.30 ton was recorded, when 60mm irrigation was given at IW/CPE of 1.00 (T9) but was statistically alike to T10 (3.10 ton) and T8 (3.01 ton). Minimum dry tuber yield ha-1 of 1.63 ton was observed in rainfed (control). Irrigation at 60mm depth given at IW, CPE=0.75 is beneficial to increase tuber yield based upon comparable yield and less water consumption. The crop can be grown as rainfed based on non-significant difference in WUE in different irrigation schedules.