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
Line segmentation of Tibetan ancient documents is one of the key steps of character recognition. The adhesion between lines and broken characters often affect the effect of line segmentation. In this paper, we implement line segmentation for binary images of Tibetan ancient documents, and propose the energy minimization seam carving technology. The steps are as follows: (1) Radon transform is used to correct the skew; (2) The document image is projected horizontally, and the projection result is smoothed to accurately detect the position of the core area and the number of text lines; (3)The isolated upper vowel and broken stroke are classiﬁed to reduce the interference of seam carving path; (4) The gradient energy, distance from the core area energy, distance from the text area energy and passing through the text area energy are weighted to get the energy map; (5) Using seam carving technology, the text line is segmented in the line segmentation area of energy graph, and then combined with the processing in (3), ﬁnally the text line segmentation result is obtained. The experimental results show that the method proposed in this paper can solve the problems of line segmentation in Tibetan ancient documents, such as partial adhesion and stroke broken, a further improve the accuracy of line segmentation.
The increasing population will require more food to be consumed in the upcoming time due to which a need of new farming practices is required. Thus we here are enlisting the various agro ecological practices for sustainable agriculture in India. We then analyses the advantages and disadvantages for all these practices and the potential for the future use. Our major findings are firstly 9 categories of agroecological practices, secondly integration of these agroecological practices and the future prospects of all of these practices.
Agricultural productivity and technological changes are important for enhancing growth in agriculture and measurement of these would help to determine the direction of investments in agriculture. The measure that compares output with the levels of use of inputs would be the most ideal one. Keeping this in view, the total factor productivity (TFP) approach was used to decompose productivity. The analysis was performed for the state as a whole as well as for the 10 agro-climatic zones and comparisons were made between high and low productive zones. The constraints for achieving higher productivity were identified so as to suggest suitable policy options that could be adopted to achieve higher productivity. The study made use of both cross-section and time series data from 1997-2007 to 2008-2018 and were obtained from the Directorate of Economics and Statistics, planning department and the department of agriculture. The analysis considered 12 crops and comprised of variables such as area, production, prices, seeds, fertilizers, farm yard manure, maintenance and repair charges of fixed assets, irrigation charges, marketing costs, electricity, pesticides, diesel oil, depreciation, land rent and labour costs. The Tornqvist-Theil divisia chained indices for TFP The total factor productivity (TFP) in Odisha increased at the rate of 0.05 per cent per annum during the entire period of study. This trend was due to higher growth of output (0.38 per cent) in relation to the growth of input use (0.33 per cent). During the first phase, the TFP declined by 0.02 per cent per annum while in the second phase TFP increased by 0.18 per cent per annum. The variation in TFP among the zones around the trend was mainly due to variation in output. The growth in agricultural labour force in the state was positive and higher in the second phase when compared to the first phase. variables in order to identify the major determinants. These determinants of the TFP growth suggest areas for policymaking and the policy discussions should be indicative rather than directive. Government expenditure on Agricultural research, education and extension per ha, average rainfall in mm, percentage of irrigated crop area, and rural literacy percentage and cropping intensity were identified as the determinants of the TFP of all crops in the state. The R2 value of the regression model was 80.7% (significant at 5% level) implying that 81% variation in the TFP growth was explained had its own influence on the TFP.
Brassica are economically most important genus consisting of oilseeds, vegetables and forage crops. Brassica juncea L. commonly known as Indian mustard. The present study was carried out with 7-parents/strains (Varuna, Vardan, Basanti, Maya, NDR-8501-19, PR-21-15 and TPM-1) and 21crosses were obtained through diallel mating design (excluding reciprocal crosses). Total 28 genotypes (21 F1 + 7 parents) were investigated for 11 traits viz. days to 50% flowering, days to maturity, plant height (cm), length of main raceme (cm), number of primary branches per plant, number of secondary branches per plant, number of siliquae per plant, 1000-seed weight (g), protein content (%), oil content (%), and seed yield per plant (g). The estimates of average degree of dominance indicated presence of over-dominance for all traits. The variety Basanti and Varuna were found best general combiners in case of oil content in percent. The cross Basanti x PR-21-15 were found to be best for SCA for yield whereas, NDR-8501-19 x TPM-1 for oil content. Heterosis was observed in Vardan x PR-21-15 over better parent, while Maya x NDR-8501-19 showed heterosis over economic parent for yield.
G × E interaction is major cause of discrepancy in crop yield under different environments. International Rice Research Institute (IRRI) launched their fourth flagship project on Global Rice Array (GRA-IV) to identify climate resilient rice genotypes. Various non-parametric (Nassar and Huehn’s method, Huehn’s method and Thennarasu’s method), parametric (Wricke’secovalence, Francis and Kannenberg’s coefficient of variance and Eberhart and Russell’s method) and multivariate methods- Additive Main Effects and Multiplicative Interactions (AMMI) had been already designed to differentiate genotypes for their behavior under different environmental conditions. Due to differential ranking of genotypes in different models, the Average of Sum of Ranks (ASR) of all measures was used in combination with Yield Stability Index (YSI) in this study, to identify desirable, high yielding and stable rice genotypes. The present investigation consisted of 26 rice genotypes (from ‘Antenna Panel’- Global Rice Arrays-IV). Genotypes of ‘Antenna panel’ were designed to help in characterization and diagnosis of diversity and dynamics of evolving climate through the eye of the crop and thus predict future grain yield for that growing site. This experiment was carried out over three different environments of Northern tarai region (Norman Ernest Borlaug Crop Research Center), Pantnagar, Uttarakhand, India. Pooled analysis of variance (ANOVA) for grain yield over the three different test environments pointed out the existence of significant differences among genotypes, G (44.32 %), environments, E (8.36 %) and interactive G × E effects (47.32 %). The genotypes G 4, G 6, G 23, G 9 and G 21 were identified as most stable genotypes as they had lowest ASR values of 2.3, 2.7, 4.7, 5.6 and 5.9 respectively. The ASR method in combination with YSI revealed that G4 is the most desirable genotype as it was not only stable but also high yielding; such superior genotypes can be utilized in future breeding programs for numerous benefits.