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
A field experiment was conducted at Udaipur during Kharif season of 2016 to study the effect of varying plant population and nutrient management on the nutrient uptake and quality of QPM hybrids. Results revealed that highest nitrogen and phosphorus content and grain and stover their uptake was found with the application of STCR which was followed by SSNM and RDF. N and P uptake in grain and total uptake of N and P was found significantly higher in HQPM-5 over PQMH-1. Hybrid HQPM-5, 1,00,000 plants ha-1 and application of STCR was found better in terms of cholorophyll content. Protein content was found highest with application of STCR over SSNM and RDF.
Among the different tomato varieties, infestation of fruit borer, H. armigera was lowest in Arka Vikash (0.94 larvae/plant), while highest in Karishma (2.11 larvae/plant). Similarly, the fruit damage on number and weight basis was recorded lowest Arka vikash (16.80 and 15.77 per cent) and maximum in Karishma (35.96 and 33.78 per cent). On the basis of per cent fruit damage, Arka Vikash and Kashi Amrit were categorized as moderately resistant, while NDTVR, Kashi Anupam, Hem Shona, Azad T-5 and RS-2 as moderately susceptible. With more than 30 per cent fruit damage, Pusa Ruby, Rocky and Karishma were categorized as susceptible.
Apparel industry is accused of being one of the most polluting industries. Not only production but consumption of garments also produces waste. The waste can be categorized as pre and post apparel waste. Pre apparel waste is manufacturing waste which is usually clean waste. Generally pre- apparel manufacturing waste comprises of damaged fabrics, edge trimmings, layout and cutting leftovers. Post apparel waste results from the finished garments which consist of quality rejects, garments damaged during storage, transportation and unsold apparel that the retailer no longer requires and decides to discard, either because they are damaged or have gone out of fashion. Therefore, the present research was conducted in Hisar district of Haryana state to study the existing upcycling practices of respondents for pre and post apparel waste. Fifty respondents were selected purposively from different areas to collect information regarding existing upcycling practices for pre and post apparel waste. All the respondents were engaged in tailoring activities stitching female garments and 74 per cent of them were also stitching children garments. All the respondents possessed pre apparel waste in the form of cutting leftovers and post-apparel waste in the form of rejected and damaged garments. All women upcycled pre-apparel waste i.e. layout or cutting leftovers small and large fabric pieces for repairs and alterations of garments followed by 84 per cent women who sold pre-apparel waste to rug weavers. Major problems faced by the respondents while upcycling pre and post apparel waste was lack of knowledge regarding construction, embellishment & designing techniques while the least faced problem was financial constraints.
The consumption of sprouts in the human diet has grown during the last years, but great concern raised from public health institutions, food industry and consumers regarding their safety since foodborne diseases caused by microorganisms have been reported. Copper metal as a contact surface was studied during the germination of alfalfa seeds (Medicago sativa L.) inside a rotating drum on a laboratory scale and compared with a plastic surface of food-grade. A system of three rotating drums was used inside a thermo-regulated chamber to germinate seeds. To evaluate the antibacterial activity of copper sheets, alfalfa seeds were inoculated with 4.2 log cfu g-1 of Escherichia coli and after 84 hours of germination sprouts were evaluated for E. coli, mesophilic aerobic bacteria, the content of copper and other minerals (potassium, calcium, magnesium, sodium, iron, manganese, and zinc), total mass, unit mass and length, and color. The contact of alfalfa sprouts with copper sheets allowed to reduce the E. coli load from 6.54 to <0.1 log cfu g-1. However, all sprouts exceeded in copper (> 10 ppm) according to Food Sanitary Regulations. Germinated mass and length decreased after copper treatments. No statistically significant differences were observed between treatments for the remaining quality parameters. Finally, it is concluded that copper was very efficient in reducing the microbial load of E. coli in alfalfa sprouts, complying with the regulations established by the Chilean Ministry of Health.
The acquisition of the operation area of agricultural machinery is the premise for the service pricing and granting government subsidies of agricultural machinery. The objective of this paper is to develop a KNN algorithm based on amending mechanism and pruning optimization (KAP) in the case of irregular fields, which could reduce error and accelerate the process. The algorithm consists of two stages. The first stage uses KNN, generating convex or non-convex hulls that represent the area occupied by arbitrary sets of points, to detect boundary, and the second stage uses amending mechanism to correct the results obtained in the previous stage to improve the accuracy. Only the points close to the boundary could affect the detection and amending results. Based on this, the pruning optimization is used to speed up operations without sacrificing accuracy in the two stages. According to a series of accurate experiment with repeatability, compared to traditional KNN, addition of amending mechanism can reduce the error by at least 2%. The use of pruning optimization accelerates the first stage by 30% - 100% and the second stage by 2-20 times.The results illustrate that the KAP algorithm could be competent for calculation in irregular field.