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
Soil phosphorus (P) tests are used for P fertilization recommendations, environmental evaluations, and occasionally for legislation purposes. The basis of fertilization recommendation as function of soil P status was established in the 1950s-1960s. Since then the agroeconomic environment has altered: Environmental protection became increasingly important and P rock resources for fertilizers appeared exhaustible. Also, new insights in soil testing and fertilization recommendations reflecting more efficient use of P became available. However, these new insights seem hard to implement into agricultural practice, to a large extent because replacing existing soil tests and recommendations would imply a very significant effort with respect to introducing new tests and recommendations by fertilization trials in practice. The same would apply for environmental evaluations. Here, a novel, three-step schedule for introducing new soil tests is proposed: (1) establishing new promising soil tests, (2) creating regression models between the old and new soil tests, and (3) implementing the new soil test stepwise by fertilization trials. In this way, the knowledge based on the old soil tests can be used until the new soil tests and their subsequent crop responses are validated sufficiently. As a novel P test we considered combining soil P intensity [as reflected by P-calcium chloride (CaCl2)] with P capacity [as reflected by P-ammonium lactate (Al)] and P-buffering capacity (as reflected by P-Al/P-CaCl2 ratio) characteristics. Researchers tested whether this novel soil test can predict P water (Pw), P-calcium lactate / acetate (CAL), and P-Olsen values. To test the hypothesis, four datasets were used (two with Pw, one with P-CAL, and one with P-Olsen). In all datasets additional soil characteristics were available including soil type. Regression models with R-adj (2) from 0.80 to 0.93 were obtained by using P-Al, P-CaCl2, and soil type. It can be concluded that these regressions can be used as a helpful intermediate instrument when introducing fertilization recommendations based on new soil tests. Predicting one soil P test out of other soil characteristics, analogous to the predicted Pw, P-CAL, and P-Olsen, could also be helpful in comparing P statuses of agricultural land in different nations.
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