Novel Approach for Statistical Interpretation: A Case Study from Long-Term Crop Production Experiments (Hungary)

Abstract

In recent decades, the agricultural sector has witnessed rapid technological interventions from field to the production stage. Thus, the importance of these technological interventions must be strictly evaluated. The traditional statistical method often deems low statistical differences as a significant one, which cannot be considered effective from different perspectives. In this sense, the aim of this research was to develop a new statistical method for evaluating agricultural experiments based on different criteria; hence, the significant importance of the technological interventions can be clearly determined. Data were collected from of a long-term (13-year) crop production experiment (Central Europe, Hungary), which involved five different fertilization levels, along with non-fertilized treatment (control), two irrigation treatments (irrigated and non-irrigated), and 15–20 genotypes of maize. The output of this research showed that the classic statistical approach for testing the significant differences among treatments should be accompanied with our new suggested approach (i.e., professional test), which reflect whether treatments were professionally effective or not. Also, results showed that good statistical background is not enough for interoperating the analysis of agricultural experiments. This research suggested that erroneous conclusions can be avoided by merging classical and professional statistical tests, and correct recommendations could be provided to decision makers and farmers based on their financial resources.