Pre-harvest prediction of wheat’s protein content in Northeast Germany for market players based on weather information

Abstract

On the wheat market, fluctuations in the quality characteristic protein content are a major challenge for market operators since trade requires constant protein content. The determining factors for the annual variability of the protein content are meteorological factors. For this reason, understanding of the factors’ mode of action is of importance. In this article, the influence of weather parameters, such as temperature, precipitation and sunshine duration, on the wheat’s protein content is investigated and a pre-harvest prediction model for the protein content of wheat in north-east Germany is developed. For this purpose, a random intercept model based on weather information from 16 weather stations of the German federal state of Mecklenburg-Western Pomerania and protein data from the corresponding mean protein contents of 148,800 protein samples over the years 2004 to 2015 supplied by the surrounding farmers to the land trader, is estimated. The marginal R² is 0.523 and the conditional R² amounts to 0.540. Thus, 52.3% of the annual variance in the protein content can be explained by the variables contained in the model. Temperature in June has the highest positive effect on the protein content of wheat. The effect of precipitation is negative. The sunshine dura­tion has a significant influence on protein formation. However, no uniform direction of action of the sunshine duration can be determined over all spring months.

DOI: 10.1399/JfK.2018.02.01, https://doi.org/10.1399/JfK.2018.02.01