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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
28 May 2022 (Vol - 53 , Issue- 06 )
Upcoming Publication
31 May 2022 (Vol - 53 , 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:

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
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

Effect of Integrated Nutrient Management on Yield and Yield attributes of chilli (Capsicum annuum L.)

Paper ID- AMA-08-08-2021-10578

India is the largest producer, consumer and exporter of chilli. The imbalance and continuous use of chemical fertilizers has detrimental effect on soil physical, chemical and biological properties thereby affecting the sustainability of crop production, besides causing environmental pollution Therefore, there is an urgent need to limit the usage of chemical fertilizers and the usage of organics should be increased which is needed to check the yield and quality levels. Keeping this in view, the present investigation was undertaken during the summer season of 2019-20 at the Research Farm of the Department of Vegetable Science, CCS Haryana Agricultural University, Hisar, Haryana to evaluate the effect of integrated nutrient management on the yield and yield attributes of chilli. The Seed material of chilli cv. “Kashi Anmol” was grown with thirteen different treatment combinations. The experimental results revealed that the application of Recommended NPK + Vermicompost @ 2 t/ha + Azotobacter (T3) which was at par with treatment T5 (50 % NPK + FYM @ 12.5 t/ha + Vermicompost @ 2 t/ha + Azotobacter) and T4 (Recommended NPK + FYM @ 12.5 t/ ha + Azotobacter) and performed superiorly over the other treatments with remarkably higher values for yield and all the yield attributes viz., fruit length (cm), fruit girth (cm), number of fruits per plant and average fruit weight (cm). Therefore, to reduce the cost of chemical fertilizers with maintaining sustainability of soil fertility and for higher yield and benefit-cost ratio the chilli crop may be supplied with 50 % Recommended NPK + FYM @ 12.5 t/ha + Vermicompost @ 2 t/ha + Azotobacter as per treatment (T5). During the investigation the net returns and benefit cost ratio was also found higher in these treatments.

RADAR TARGET CLASSIFICATION USING ALEXNET CNN AND MACHINE LEARNING MODELS

Paper ID- AMA-08-08-2021-10577

Classification of the radar targets using efficient convolution neural networks is proposed. It uses the time-frequency image features of the target for classification. Machine learning is an extremely time-consuming process as the feature extraction of the image needs strong knowledge of the subject and domain. To overcome this, deep learning is used to automate the process of feature extraction. The simple and complex targets are modelled using a dedicated machine learning algorithm, and their respective spectrogram images are created. These are partitioned into training and testing data sets for training the CNN (alexnet) and hybrid models of CNN where the feature extraction is done using CNN and classifying the target is done using machine learning algorithms like SVM, KNN. A frequency domain filter using CNN is used to pre-process the time-frequency image features for frequency smoothing and dimension reduction. The hybrid model of CNN with an SVM classifier resulted in high accuracy with good performance.

Effect of post-harvest treatments on physicochemical properties and relative economics of Indian Jujube fruits during ambient and cold storage

Paper ID- AMA-07-08-2021-10574

To study the effect of post-harvest treatments on physico-chemical properties and relative economics of Indian Jujube during ambient and cold Storage conditions fruits was conducted during 2019 at Department of Horticulture, S.K.N. College of Agriculture, Jobner, Rajasthan. Fruits samples were analysed in 3 days’ intervals for 12 days in ambient storage conditions and 21 days in cold storage conditions for various physico-chemical characteristics. Results revealed that decay loss of fruits increased with storage period whereas, marketability, fruit volume, pulp per cent, pulp: stone ratio and TSS: acid ratio showed a declining trend with advancement of storage period under ambient and cold storage conditions, respectively. Whereas, reducing sugars and non- reducing sugars showed an increase up to 9 days of storage in ambient storage conditions and up to 12 days of storage in cold storage conditions, but after 9 days of storage in ambient storage conditions and after 12 days of storage in cold storage conditions, a decline trend was observed. Economics calculated showed feasibility as on a total input of Rs. 2747.10 and Rs. 3313.20 is earned as gross returns with a net return of Rs. 384.10 with 1.21:1 B: C ratio on 9th day in ambient storage conditions and in cold storage conditions on 15th day of storage a total input of Rs. 3902.10 and Rs. 4457.75 is earned as gross returns with a net return of Rs. 555.65 with 1.14:1 B: C ratio. On the basis of these findings, it may be concluded that of ber fruits is possible for 9 days after in ambient storage conditions and 15 days after in cold storage conditions with treatment of fruits by 1.5% CaCl2 retained the physical, chemical and sensory qualities.

Experimental Observations Rheological Behavior Aluminum Oxide and Multiwall Carbon Nanotube Dispersants in a Mixture of Water and Ethylene Glycol Hybrid Nanofluid

Paper ID- AMA-07-08-2021-10572

Micro and nano colloidal suspensions in conventional fluids are identified as potential fluids for heat transfer cooling applications. The pumping power of any fluid mainly depends upon the viscosity of the working fluid. In this present work, the viscosity of the nanofluid is compared with conventional fluids. The hybrid nanofluid viscosity and shear stress are measured by varying the shear rate from 0-500s-1. The nanoparticles are composite MWCNT and aluminium oxide (10:90) ratio percent by weight or (13:87) ratio percent by volume. The coolant mixture of (80:20) % volume water and ethylene glycol has good antifreeze properties. The rheological properties are measured for volume fractions 0.004-0.028% and various temperatures from 25oC- 55oC. The findings showed that the viscosity increased with the loading of nanoparticles along with the decrease in temperature. Hybrid nanofluid's viscosity rises to 9.9% of base fluid at 25oC for premier volume fraction 0.028%. Shear stresses the shear strain rate following the linear trend for all the volume fractions, obeying Newton's Viscosity law called Newtonian fluids.

Toxicity Characteristics of Acetamiprid Insecticides Against Adult Earthworms, Eisenia Fetida

Paper ID- AMA-07-08-2021-10571

The use of neonicotinoides insecticides, particularly acetamiprid, in agriculture is increasing day by day to increase crop yields, but their excessive use has reduced beneficial soil fauna and flora, which directly or indirectly affects soil health. Crop yield is inversely proportional to invertebrate flora, with earthworms being the most affected organisms by pesticides. During pest management programmes in agricultural fields, through direct application as well as foliar wash-offs or drift, large amounts of acetamiprid active ingredients are typically deposited on the soil. Studies on the impacts of neonicotinoids pesticides have primarily focused on acetamiprid's effects on earthworm’s morphological parameters as well as behaviour. Acetamiprid LC50 values derived using the Probit analytical method were 0.165g/cm2, which is the pesticide concentration that kills 50% of earthworms. As the concentration of acetamiprid rises, so do the negative effects on earthworms, with bulging of the anterior end, body constriction, preclitellar swelling, clitellum bulging, tapered end swollen, oozing out of coelomic fluid, loosened segments, formation of a knot-like structure at the anterior end, cuticle rupture, and desegmentation among the changes. Furthermore, earthworms demonstrated dark coloration, leaking out of hemocoel, perforated cuticle, and epidermal peeling at an acetamiprid dosage of 0.240g/cm2.