Field Lecture (Statistics): Tessema Astatkie

Title:  Design and analysis of experiments for value addition of agricultural products: interdisciplinary collaborative research on essential oils from herbal plants with USA researchers 
Abstract:  Appropriately designed experiments are very important for discovering factors' effect on responses measured at the different stages of post-harvest management and value addition of agricultural products. Several types of statistical methods can be used to meet specific objectives of the study that match the specific experimental design used to produce the data. The most used designs of experiments and the types of analyses will be highlighted using examples from studies conducted on essential oils (EO) from several aromatic plants grown in the USA and Bulgaria. The examples illustrate the importance of designed experiments and appropriate types of analyses to unlock the effect of agronomic (pre-harvest), processing (post-harvest), and post-processing (re-utilization of waste) factors on EO content, composition, and antioxidant capacity.  The statistical methods used in these studies include Analysis of Variance (ANOVA), Repeated Measures Analysis, Analysis of Covariance (ANCOVA), Linear Regression, Nonlinear Regression, and Multivariate Analysis. The aromatic plants considered include American mayapple, Anise, Artemisia, Arvensis, Chamomile, Fennel, Garden Sage, Hyssop, Japanese Cornmint, Lavender, Lemongrass, Male and Female Juniper, Oregano, Palmarosa, Peppermint, Rose, Spearmint, Sunflower, Winter canola, Winter mustard, Hemp, Helichrysum arenarium, and Helichrysum italicum.  Since 2010, I published more than 90 EO papers with a team of researchers in the USA from this interdisciplinary collaborative work. Highlights of the key findings will also be presented. However, these kinds of collaborations have different types of challenges. Highlights of the type of challenges and how to manage them for a successful collaboration will be presented.