Significance of field trials data cleaning process for making more reliable breeder decisions

Abstract

Field trials supposed to enable selection of the most successful genotypes which is critical because of the existence of Genotype by Environment interaction. To assess this interaction we are forced to conduct field trials in several environments and/or years. When we asses grain yield of maize hybrids during the breeding process, it is always based on multi-environment small plot field trial (MESPT). That is why this part of the breeding process is most demanding in terms of technical, financial and labor requirements. In this paper, one possible systematic approach to assessing multi-environment field trials conduction is described. The main goal of the described approach is to provide the best possible results with the use of reasonable resources. As the results of trials cannot be directly interpreted without previous statistical processing, quality of raw data as input for biometrical (statistical) analysis is essential for obtaining a relevant and objective measure of genotype relative value in terms of productivity and adaptability (reliability) of new advanced maize hybrids. There are many definitions of data quality but data is generally considered high quality if it is fit for intended uses in operations, decision making and planning. The main aim of this paper is to underline the importance of the data cleaning process in MESPT.

Keywords

• field inspection
• maize breeding
• plot scoring
• proper results
• raw data cleaning