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.
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
This research is to determine the influence of the process parameters when machining SKD11 steel and proposes the optimized technical conditions to minimum surface roughness (Ra) in WEDM (Wire Electrical Discharge Machining) process. Process parameters such as cutting voltage (VM), pulse on time (Ton), pulse off time (Toff), servor voltage (SV), wire feed (WF) and cutting speed (SPD) were investigated as input variables. To find out the optimized paramaters, Taguchi method was used to design experimental plans. With this method, 18 experimental runs were conducted with six above process parameters. The experimental results show that surface roughness (Ra) is minimum with optimized parameter set as follows: SPD = 4 m/min, Ton = 6 s; Toff = 16 s; SV = 34 V; WF = 10 mm/min and VM = 6 V. The deviation value between calculation and experiment is 9.29 %.
Leaf mold is a common disease on tomato leaves, which seriously affects the quality and yield of tomatoes. In order to use hyperspectral technology to achieve early detection of leaf mold, 200 samples were first collected and the hyperspectral data of all leaf samples in the band of 927 to 1684 nm were obtained. According to the lesion area, all leaf samples were divided into 4 grades, and then the four pretreatment effects were compared, and the Savitzky-Golay convolution smoothing method was selected as the pretreatment method. Competitive adaptive reweighted sampling (CARS), iteratively retains informative variables (IRIV) and a combination of the two algorithms are used to select feature variables to establish tomato leaf mold hyperspectral support vector machine (SVM), CARS-SVM, IRIV-SVM, CARS-IRIV-SVM detection model. The results show that the detection accuracy of the four models for level 1 samples are all higher than 80.9%, and the recognition effect is good. The overall prediction accuracy rates of the four models are 79.41%, 86.76%, 85.29% and 92.65%. The CARS-IRIV-SVM model has the best results in identifying the characteristics of tomato leaf mold. The evaluation index of the model is Rp2=0.9103, RMSEP=0.138 and RPD=2.51, the prediction accuracy and overall accuracy of each level of the prediction set are 100%, 95.24%, 88.88%, 90.91% and 92.65%. The built model has high detection accuracy, indicating that the CARS-IRIV-SVM model based on hyperspectral technology is feasible for the classification and recognition of tomato leaf mold.
Teak has one of the most valuable timber in the world. It is native to India and the Southeast Asian region (Myanmar, Thailand, and Laos), where it is a major supply of wood. It is widely spread in tropical and subtropical regions of the world. It is mostly propagated through seeds. One of the main limitations of teak is delayed and sporadic germination due to dormancy. It exhibits physical dormancy due to presence of hard and stony endocarp in the drupe. To overcome the problem, true seeds that are available in the drupe need to be extracted and used for seedling production without any problem of dormancy. But extraction of true seed from the teak drupe is not an easy process and it demands more mechanical power. In order to address this issue, an experiment was conducted in view of developing a device to extract true seed from drupes without causing any mechanical damage to the true seed. Extracted true seeds were subjected to physical, physiological and chemical methods to observe the mechanical damage and germination test. It is concluded that among the four methods of extraction, power operated hammer mill with a pulley size of 3 inch with dry drupes recorded highest number of true seeds extraction when compared to all other methods. True seeds extracted by power operated hammer mill recorded higher germination of 48.0 and 51.0 % on 14 and 28 days after sowing with lesser mechanical damage.
Okra shoot and fruit borer, Earias spp. is the major pest of okra. It is important to understand to what extent, this pest causes damage in okra field, and how do they respond to the prevailing environmental conditions. We studied extent of damage by Earias spp., and its correlation with abiotic factors. The study was done at Department of Entomology, CCS Haryana Agricultural University, Hisar, Haryana, during kharif season, 2019. The study was carried out from August, 2019 (32nd standard meteorological week) to October 2019 (42nd standard meteorological week). The initiation of larval population was found to be from 32nd SMW, while it reached at its peak (8.67 larvae/ 5 plants) during 39th SMW. Infestation of fruits initiated from 34th SMW (0.48%), and increased gradually till 40th SMW (39.41%). Temperature was recorded to be the major factor affecting the population of this pest. Larval population showed a significant and negative correlation with the maximum (r= -0.568*), minimum (r= -0.643*) and average (r=-0.664*) temperature, along with evening relative humidity (r= -0.590*) and rainfall (r= -0.590*). This study provides basic knowledge about the incidence and damage caused by this pest, and its behaviour towards various abiotic factors.
Many countries ordered closure of all educational institutes due to COVID-19. A sample of 300 students was selected from all the 6 constituent colleges of Maharana Pratap University of Agriculture and Technology, Udaipur, Rajasthan. Students from 2nd and 3rd year were selected from which 50 students was selected randomly from each college to assess the benefits perceived by the students regarding e-learning platforms during COVID-19. Data collection was done through “Google Forms” which was sent on Whatsapp and e- mail. Frequency, percentage and mean per cent score were used for analysing the data statistically. On the basis of the data obtained it can be concluded that a flexible schedule and convenience (MPS 81.88) was found to be the major benefits perceived by the respondents in the e-learning followed by favourable for people with restricted mobility (MPS 81.11) and it also helps in an easy and quick share of educational material. A number of the respondents also believed that e-learning is helpful in saving time and money and in increasing general awareness of the respondents.