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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

Application of Different Deep Learning Algorithms in Forestry Production Management and Processing

Paper ID- AMA-25-01-2022-11052

Forest resources are the most precious natural resources of human beings. According to the national strategic planning and guidance, China's forest area increases continuously, quality rises steadily, and efficiency increases continuously. In recent years, the deep integration of artificial intelligence technology represented by deep learning and forestry production management and processing industry is one of the important trends to realize the green and intelligent development of forestry. This paper summarizes the research progress of target detection, recognition and classification based on different deep learning algorithms and models in forestry production management and processing, comprehensively compares the advantages and disadvantages of different model algorithms, and puts forward some research suggestions, such as establishing multi-source database, optimizing algorithm model, improving hardware configuration, etc., which provides a reference for the intelligent development of forestry industry.

Effect of soil and foliar application of zinc and iron on Yield, Quality and Economics of Maize

Paper ID- AMA-23-01-2022-11049

A field experiment was conducted during two consecutive Kharif, seasons of 2018 and 2019 at Instructional Farm, Rajasthan College of Agriculture, Udaipur. The experiment was laid out under a split-plot design with three replications, including seven levels of soil application in main plots and four levels of foliar spray in the subplot. Significantly highest grain, stover and biological yield (4068.47, 6532.07 and 10600.54 kg ha-1) in the main plot under treatment 25 kg ZnSO4 ha-1 + 25 kg FeSO4 ha-1. In subplot highest grain, stover and biological yield (4068.47, 6532.07 and 10600.54 kg ha-1) were observed under treatment 0.5% ZnSO4 ha-1 + 0.5% FeSO4 ha-1. The interactive effect of soil and foliar application of zinc and iron significantly increases the grain and stover yield. The highest grain and stover yield (4609.45 and 7749.30 kg ha-1) was found with treatment combination S6F3. Harvest index was found non-significant in both soil and foliar application. The highest protein content (11.08 % and 11.07 %) was found in S6 and F3 treatments in the main and subplot, respectively. The highest net return and B:C ratio were found under soil application of 25 kg ZnSO4 ha-1 + 25 kg FeSO4 ha-1 (₹ 61986.1 and 2.53) and foliar application of 0.5% ZnSO4 ha-1 + 0.5% FeSO4 ha-1 (₹ 63479.1 and 2.70).

Deciphering Molecular Characterization in Wheat Genotypes using ISSR Marker

Paper ID- AMA-23-01-2022-11047

A total of 37 allele was amplified with each primer thus produced on an average 7.4 polymorphic bands and The number of alleles per locus ranged from 5 to 12. The polymorphism index content (PIC) value varied from 0.675 to 0.868. ISSR primers performed well in the detection of in wheat genetic diversity can be recommended for future wheat improvement program. Genomic DNA was extracted from thirty three wheat genotypes using CTAB procedure and amplified using five ISSR primers. Matrix similarity of genotypes was calculated by using NTSYSpc.2.1 with Sanh-clustering using the UPGMA (Unweighted Paired Group Method Using Arithmetic Averages) method. The prime aim of this study were to determination of the genetic polymorphism, genetic diversity, selection promising diverse progenitor, identification of putative and informative markers can be recommended for future crop improvement program.

Effect of different environmental Condition on Seed Yield and Its Attributes in Sesame (Sesamum Indicum L.)

Paper ID- AMA-23-01-2022-11046

The analysis of Sesame (Sesamum Indicum L.) yield and yield attributes in three environmental conditions produced by three different dates of sowing viz., normal, late and very late sowing for yield and its attributes by performing (half diallel fashion excluding reciprocals). To achieve the objectives of the present investigation, ten diverse parents along with their 45 F1 progenies were evaluated in a randomized block design with three replications during kharif 2020-21 at S.K.N. College of Agriculture, Jobner (Rajasthan) in Kharif 2019-20. This Analysis of variance revealed that the existence of significant genotypic differences among the genotypes and F1’s in individual environment. The mean of seed yield per plant was decreased by 19.40% and 32.38% in normal to late environmental condition among the parents and hybrids respectively. In normal to very late environmental condition 60.32% and 65.41% reduction was observed among the parents and hybrids respectively.

A Sustainability approach of Income, Expenditure and Employment through different activities adopted under watershed programme in Nagaland

Paper ID- AMA-23-01-2022-11044

The present study was conducted in Dimapur and Kohima districts of Nagaland. The maximum area covered under watershed in these two districts, further Dhansiripar and Medziphema from Dimapur Distract, Kohima Tseminyu from Kohima distract of Nagaland were randomly selected. After that a multi stage simple random sampling technique method was adopted for 320 respondents, out of total numbers, 160 beneficiaries and 160 non-beneficiaries were selected from the study area. Further study reveals that average income of beneficiaries were found to be maximum with 22.75 per cent through plantation crop and forestry, while it was recorded least through service as 3.450 per cent of the total income, respectively. The overall trend shows maximum (40.37 per cent), followed by animal husbandry as 21.72 per cent contributed towards the employment generated on the beneficiary watershed programme. The maximum pair wise limits was Rs 22911.14 and minimum of Rs 129.32 as the limit, which were found statistically significant at 5 per cent level for ‘Z’ 2-tailed test method. Even between the selected enterprises the maximum benefit-cost ratio was recorded on C of Rs 3.13 and minimum on E with Rs 1.25 against every investment of rupee, whereas the BCR indicate the maximum on A to D comparisons after eliminate D with 3.28 against the investment of every Rupee investment.