The e-ROSA project seeks to build a shared vision of a future sustainable e-infrastructure for research and education in agriculture in order to promote Open Science in this field and as such contribute to addressing related societal challenges. In order to achieve this goal, e-ROSA’s first objective is to bring together the relevant scientific communities and stakeholders and engage them in the process of coelaboration of an ambitious, practical roadmap that provides the basis for the design and implementation of such an e-infrastructure in the years to come.
This website highlights the results of a bibliometric analysis conducted at a global scale in order to identify key scientists and associated research performing organisations (e.g. public research institutes, universities, Research & Development departments of private companies) that work in the field of agricultural data sources and services. If you have any comment or feedback on the bibliometric study, please use the online form.
You can access and play with the graphs:
- Evolution of the number of publications between 2005 and 2015
- Map of most publishing countries between 2005 and 2015
- Network of country collaborations
- Network of institutional collaborations (+10 publications)
- Network of keywords relating to data - Link
Effects of Soil Management Practices on Key Soil Quality Indicators and Indices in Pearl Millet (Pennisetum americanum (L.) Leeke)-Based System in Hot Semi-arid Inceptisols
Rainfed Inceptisol soils, despite their agricultural potential, pose serious problems, including soil erosion, low fertility, nutrient imbalance, and low soil organic matter, and ultimately lead to poor soil quality. To address these constraints, two long-term experiments were initiated to study conservation agricultural practices, comprising conventional and low tillage as well as conjunctive use of organic and inorganic sources of nutrients in Inceptisol soils of Agra center of the All-India Coordinated Research Project for Dryland Agriculture (AICRPDA). The first experiment included tillage and nutrient-management practices, whereas the second studied only conjunctive nutrient-management practices. Both used pearl millet (Pennisetum americanum (L.) Linn) as test crop. These experiments were adopted for soil quality assessment studies at 4 and 8 years after their completion, respectively, at the Central Research Institute for Dryland Agriculture (CRIDA), Hyderabad, India. Soil quality assessment was done by identifying the key indicators using principal component analysis (PCA), linear scoring technique (LST), soil quality indices (SQI), and relative soil quality indices (RSQI). Results revealed that most of the soil quality parameters were significantly influenced by the management treatments in both the experiments. In experiment 1, soil quality indices varied from 0.86 to 1.08 across the treatments. Tillage as well as the nutrient-management treatments played a significant role in influencing the SQI. Among the tillage practices, low tillage with one interculture + weedicide application resulted in a greater soil quality index (0.98) followed by conventional tillage + one interculture (0.94), which was at par with low tillage + one interculture (0.93). Among the nutrient-management treatments, application of 100% organic sources of nutrients gave the greatest SQI of 1.05, whereas the other two practices of 50% nitrogen (N) (organic) + 50% (inorganic source) (0.92) and 100% N (inorganic source) (0.88) were statistically at par with each other. The various parameters that emerged as key soil quality indicators along with their percentage contributions toward SQI were organic carbon (17%), exchangeable calcium (Ca) (10%), available zinc (Zn) (9%), available copper (Cu) (6%), dehydrogenase assay (6%), microbial biomass carbon (25%) and mean weight diameter of soil aggregates (27%). In experiment 2, SQI varied from 2.33 to 3.47, and 50% urea + 50% farmyard manure (FYM) showed the greatest SQI of 3.47, which was at par with 100% RDF + 25 kg zinc sulfate (ZnSO4) (3.20). Under this set of treatments, the key soil quality indicators and their contributions to SQI were organic carbon (19%), available N (20%), exchangeable Ca (3%), available Zn (4%) and Cu (17%), labile carbon (20%), and mean weight diameter of soil aggregates (17%). The quantitative relationship established in this study between mean pearl millet yields (Y) and RSQI irrespective of the management treatments for both the experiments together could be quite useful to predict the yield quantitatively with respect to a given change in soil quality for these rainfed Inceptisols. The methodology used in this study is not only useful to these Inceptisols but can also be used for varying soil types, climate, and associated conditions elsewhere in the world.
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