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WOS Indexed (2023)
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. 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 Zhenkong Kexue yu Jishu Xuebao/Journal of Vacuum Science and Technology Wuhan Ligong Daxue Xuebao (Jiaotong Kexue Yu Gongcheng Ban)/Journal of Wuhan University of Technology (Transportation Science and Engineering) Zhonghua yi shi za zhi (Beijing, China : 1980)
29 Mar 2023 (Vol - 54 , Issue- 04 )
31 Mar 2023 (Vol - 54 , Issue 03 )
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 Asia Life Sciences Interventional Pulmonology 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
Industrial Engineering Teikyo Medical Journal Connected Health Tagliche Praxis Bulletin of National Institute of Health Sciences Journal of the Austrian Society of Agricultural Economics
Industrial and Commercial Design International Medical Journal Technology Reports of Kansai University Asia Life Sciences Open Access Journals Tobacco Science and Technology
Information Engineering Zhongguo Shiyou Daxue Xuebao (Ziran Kexue Ban)/Journal of China University of Petroleum (Edition of Natural Science) Tobacco Science and Technology Teikyo Medical Journal Connected Health International Medical Journal Technology Reports of Kansai University
Chemical Engineering Open Access Journals Tagliche Praxis Bulletin of National Institute of Health Sciences Journal of the Austrian Society of Agricultural Economics Azerbaijan Medical Journal
Food Engineering Zhenkong Kexue yu Jishu Xuebao/Journal of Vacuum Science and Technology Wuhan Ligong Daxue Xuebao (Jiaotong Kexue Yu Gongcheng Ban)/Journal of Wuhan University of Technology (Transportation Science and Engineering) Zhonghua yi shi za zhi (Beijing, China : 1980) Zhongguo Shiyou Daxue Xuebao (Ziran Kexue Ban)/Journal of China University of Petroleum (Edition of Natural Science)
Succession of Pea Insect Pests and their Natural Enemies in Rainfed Sub Tropics of Jammu and Kashmir region of N-W Himalayas
Major insect pests and their natural enemies, prevalent in field pea crop of Jammu and Kashmir sub tropical Kandi areas were recorded. This shall help in targeting the major insect pests at the right time/stage for applying appropriate protection measures. Experiments were conducted to record the pest and their natural enemies’ population fluctuation, at different phenophases of the crop. Eleven different pea varieties were sown in randomized block design, replicated thrice in a plot size of 3 x 4 m2, maintaining a plant to plant distance of 5-6 cm and row to row distance of 30 cm. Leaf miner and aphids were found to be the two major insect pests of pea in this region and the predator ladybird beetle, and parasitoid quite effectively kept the aphid population under check. Pea leaf miner infestation started with the 45 days old crop and its infestation varied among the different varieties. Lowest leaf miner infestation was recorded in US-10, which was at par with the variety Sweet pearl and MGS-10. However, significantly highest leaf miner infestation was in popular varieties Green Valley, Rachna and Prakash. Significantly highest per cent parasitization was recorded in GS-10 variety which was at par with KIWI-101, Prakash and Green Valley. However, per cent parasitization by aphid parasitoid ranged from 44.50 - 56.20 per cent during Rabi 2016-17 and 46.50 - 52.40 per cent during Rabi 2017-18 irrespective of the different varieties. Significantly superior predator counts were also observed in US-10, Varun Dhara, Rachna, DS-10 and MGS-10. Management strategies for leaf miner should preferably be started, when the crop is 45 - 50 days old as irrespective of the varieties, the leaf miner population started appearing after 35 - 40 days of sowing and reached its peak during 45 - 50 DAS. Fifty per cent of the aphid population is kept under check by its predator and parasitoid. Management strategies should be therefore modified accordingly, so as to cause least harm to the natural enemy population.
Effect of some plant products on the biology of rice weevil Sitophilus oryzae (Linnaeus)
A laboratory study was conducted during 2020-21 in the laboratory of the Department of Entomology, Institute of Agricultural Sciences, SOADU, Bhubaneswar, Odisha, to identify plant powders which may prove effective against rice weevil, via; Azadirachta indica (A. Juss.) seeds and leaves, Pongamia pinnata (Linnaeus), Calotropis procera (Aiton), Annona reticulata (Linnaeus), Lantana camara (Linnaeus), Vitex negundo (Linnaeus) leaves, Capsicum annum (Linnaeus) dried fruits and Curcuma longa (Linnaeus) rhizome at 5% and 10% concentration. This study revealed that the pest could oviposit 3.55 to 24.52 eggs in different treatments. Lowest oviposition (8.06 and 3.55) was there in Neem Seed Kernel (NSK) Powder treatment. Chili powder and Calotropis leaf powder were also effective in reducing egg deposition. The egg to adult period was maximum in NSK Powder (34.5 and 41.3 days) and minimum in Lantana leaf powder recording 24.52 and 19.68 days. Adult emergence% was maximum in Lantana leaf powder (41.94 and 37.12) and minimum in NSK Powder (6.12 and 2.40). Longevity of males was found to be the highest in Lantana leaf powder (21.7 and 16.5 days) and lowest in NSK Powder (2.2 and 1.6 days). Same trend was also found in case of females with 22.2 and 18.9 days in Lantana leaf powder and 2.6 and 2.0 days in case of NSK Powder. Mortality was observed to be the most in NSK Powder ranging between 97.24 and 99.70% and minimum in case of Lantana leaf powder ranging between 23.87 and 46.57%, all at 5% and 10% concentration, respectively.
Prediction of Artificial Neural Network (ANN) in the optimization of quality attributes in heat pump-assisted dehumidified air-dried (HPD) Moringa oleifera by Principal Component Analysis (PCA)
Moringa oleifera (M. Oleifera) is a storehouse of essential nutrients like protein, fibre, vitamins, minerals, and phytochemicals. The moringa leaves can be consumed in cooked form or supplemented as a fine powder in processed food products. The conventional drying process takes more time and energy and that will affect the organoleptic property, product quality and safety. Hence, the study aims to apply advanced techniques like heat pump-assisted dehumidified air drying (HPD), running effectively and efficiently to achieve higher retention of nutritional properties. To develop a predictive model Artificial Neural Network (ANN) was chosen as a tool for drying at temperature and drying time varied at three levels. For this, The output variables of crude protein (%), crude fibre (%), and colour values (L*, a* and b*) as an input of drying temperature (45 to 65 °C) and drying time (45 to 75 minutes). Physicochemical and drying characteristics of moringa leaf were highly found at 55⁰C with special reference to maximum powder recovery, excellent flowability and better retention of nutrients like crude protein (29.64 %) and crude fibre (16.37 %). The values of coefficient of determination (R2 - 0.969 to 0.998), Root mean square error (RMSE - 0.02685 to 0.13541), Mean Absolute Error (MAE - 0.00912 to 0.0946) and Mean Absolute Percentage Error (MAPE - 0.04768 to 0.34129) were used to determine the potential and sensitivity analysis of training function and hidden layer for each response variable for their prediction with the highest accuracy.
Molecular Diversity Analysis among Alternaria brassicae Isolates from Different Locations of Madhya Pradesh
Alternaria blight incited by Alternaria brassicae (Berk.) Sacc. is wide range fungal pathogen that can infect the foliar and seed borne pathogen in crucifers. Molecular Diversity of Alternaria brassicae populations were fundamental to the understanding of epidemiology, host– pathogen interaction and resistance management. The present study was aimed to reveal genetic variability among 20 isolates of the Alternaria brassicae isolates collected from the state of Madhya Pradesh, by using Random Amplified Polymorphic DNA (RAPD) molecular markers. A total of 174 reproducible and scorable bands ranging from 100-3000 bp (base pair) were generated for all twenty A. brassicae isolates with 20 RAPD primers. The highest numbers of bands (15) were produced by primer OPE-03 while, lowest numbers of bands (4) were produced by primer OPA-13. The numbers of polymorphic bands produced were maximum (14) with the primers OPU-03 while minimum (1) with primers OPA-13 and OPA-19. On the basis of RAPD data the total percentage of polymorphism was 78.36% among all the isolates. RAPD marker based dendrogram categorised twenty A. brassiace isolates into two groups.
APPLE PRICE FORECASTING USING DIFFERENT TIME SERIES MODELS FOR SOLAN MARKET, HP, INDIA
Agriculture is the major occupation for the people of Himachal Pradesh. The apple is Himachal Pradesh's important fruit crop, accounting for almost 49% of the total area under fruit crops and 85% of total fruit production. Various price series models viz. HWMS, ARIMA, TDNN and Hybrid ARIMA-TDNN models were tried to price series of apple for Solan Market for study period from January 2008 to December 2020. Best model is selected based on lowest RMSE value. Key results show that Hybrid ARIMA-TDNN models were performs comparatively well over other models for forecasting of apple prices.