Design and Statistical Analysis in Agricultural, Biological and Environmental Sciences

Dear Colleagues,

Scientific research in biological sciences, and especially, in agriculture, is a field that requires up-to-date methodological schemes both at the design and the statistical analysis stages of the experiments and studies. The efficient use of resources in agricultural research, as well as valid statistical analyses and inductive inferences, is always an important and “hot” issue that offers challenges for new research opportunities. Back in the early twentieth century, Sir Ronald Fisher, with his work at the Rothamsted Experimental Station (1919-1933), introduced the principles of experimentation in all applied sciences and created the foundations for modern statistical science. Nowadays, in the big data era, there is a plethora of multivariate and multidimensional data, data “cubes”, and a broad range of statistical and data analysis methods for managing and analyzing data arising in different branches of agricultural research. Thus, the aim of this Special Issue of Agronomy is to highlight the importance of and the opportunities for applied statistics in agricultural, biological, and environmental sciences. In addition, applications with new or improved methodological schemes and novel strategies in planning research, managing, analyzing, interpreting and visualizing data are currently of primary importance in the field. We welcome original research papers with methodological and/or statistical and/or data analysis orientation and content, systematic reviews, scoping reviews, and meta-analyses. We believe that there must be a balance between design and analysis, since both are equally important. 

Dr. George Menexes
Dr. Angelos Markos
Guest Editors

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