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:
Breed conservation needs technology dissemination which necessitates training. Training imparted to farmers based on training need assessment (TNA) desirably impact farming activities. Hence, the study aimed to assess the training needs of farmers on Umblachery breed cattle farming. Totally 120 farmers were selected using simple random sampling technique for the study from Nagappattinam and Thiruvarur districts, the breeding tract of Umblachery. Identified training needs were classified under eight different areas and incorporated in the structured interview schedule to determine the training need index (TNI). The data were collected through personal interview and analysed. The results reveal that the farmers perceived training on communication and marketing of Umblachery cattle as most important followed by feeding management (II), calf management (III), clean milk production (IV), herd health management (V), breeding management (VI), housing management (VII) and animal selection (VIII) with mean score of 2,56, 2.50, 2.27, 2.26, 2.12, 2.09, 1.98 and 1.88 respectively. The findings would help the stakeholder institutes, which impart training to Umblachery breed cattle farmers, in designing training curriculum for making the training impactful.
Nutrient concentrations in plant tissues are often regarded as the most reliable measure of the nutritional quality of different crops. Leaf nutrition analysis is an excellent way to establish balanced fertilisation techniques. The current study seeks to assess macronutrient content in ten varieties of pot gerbera cultivated on three different growing conditions after 90 days of planting. The experiment was conducted in the polyhouse at the Centre for Protected Cultivation Technology (CPCT), ICAR-Indian Agricultural Research Institute (IARI), New Delhi, from February to May 2022 and 2023, using a completely randomised design with a factorial concept. The results showed that the leaves of var. Glorious Orange grown in Cocopeat + Perlite + Vermiculite (3:1:1) (M2V2) had the highest total leaf nitrogen content (2.45 %), whereas the leaves of var. Bighorn grown in Cocopeat + Perlite + Vermiculite (3:1:1) (M2V9) had the highest leaf phosphorous content (0.42 %). However, the leaves of var. Glorious Yellow exhibited the highest leaf potassium content (3.53 %) when grown in Cocopeat + Perlite + Vermiculite (3:1:1) (M2V4) than in any other treatment combination. There was no significant relationship between varieties and growing media.
Linseed is an important Rabi season oilseed crop next to rapeseed and mustard in terms of area and production. During the last two decades, flax has attracted great attention to human health mostly because of its desirable fatty acid composition. Genetic variability is crucial in the breeding or selection program of any crop. The success of any genetic program lies in exploiting genetic variability. Diversity analysis of flax is an important component for efficient management and utilization of its genetic resources, and proper handling of the seed certification programs. The present research work the linseed genotypes and understanding its diversity on both morphological and molecular levels and understanding the properties of the linseed. Based on divergence analysis, the genotypes viz., SLS 108, PKDL-167, SLS 111, JLS 67, SLS 123, SLS 118 and TL142 were identified as promising genotypes indicating vast genetic divergence regarding cluster means, intra and inter-cluster distance and per se performances. At the molecular level, twelve SSR markers were found polymorphic. The polymorphic information content (PIC) values were ranged between 0.0555 to 0.6732 with an average PIC value of 0.4020 per primer. This depicted that there is considerable genetic variability amongst the genotypes used in the molecular study and also, this was similar to the results of D2 analysis done based on quantitative data. Unique allele was found for marker Lu-1, Lu-4, Lu-7 and Lu-8 in genotypes JLS-9, PKDL-167, SLS-16 and SLS-115 and the size was about 90 bp, 800 bp, 170 bp and 220 bp, respectively. These markers can be used for selective amplification and identification of the above specific trait/genotypes.
This research adds to our understanding of the therapeutic plants that are employed in conventional phytotherapy. The 250 persons that were questioned were included in the questionnaire that we used to do this. Many people have questions about us, especially in relation to the use of medicinal plants. This poll suggests that 63.33% of respondents take conventional medications. This finding demonstrates the value of medicinal herbs in the field of modern medicine. The collected data allowed for the identification of sixty-three medicinal plants, grouped into thirty-two families (the most common being Lamiaceae), three of which are dominant: Apiaceae, Lamiaceae, and Asteraceae. The leaves and the entire plant are the portions that are used the most. Most popular techniques are infusion and decoction.
In the current work, we explore the use of remote sensing and GIS techniques, specifically focusing on the Normalized Difference Vegetation Index (NDVI) to monitor the vegetation dynamics. By integrating satellite imagery and GIS, NDVI provides valuable insights into vegetation health and vigor. This study highlights the process of acquiring, pre-processing, and analyzing satellite images to derive NDVI values. The method used in our investigation offers a robust and efficient technique to assess the vegetation changes among Boutaleb Mountains. The superposition of the NDVI’ layers allowed us to estimate the regression of the vegetation cover between 2010 and 2020, which up to 3226 ha for the dense and sparse vegetation. The significant regression of the vegetation cover over the study period obliges the concerned administration to put in place a management and conservation plans for the natural heritage of the Boutaleb Mountains.