Determination of yield and quality characteristics of some sugar beet (Beta vulgaris L.) varieties by different analytical methods

Abstract

Sugar beet is known globally as one of the most important sources of sucrose. Sugar beet, which provides raw materials to many industries, creating an important employment opportunity in the regions where it is cultivated. In this study, yield and quality parameters of eight different sugar beet varieties were determined by different analytical methods. The experiment was carried out in 2024 at the experimental field of the Faculty of Applied Sciences, Muş Alparslan University, utilizing a randomized block design with three replications. Following a seven-month vegetative period, yield and quality analysis of the harvested beets were carried out, allowing for the determination of relationships between variety and traits. Statistically significant and important differences were found among the sugar beet varieties in terms of the parameters analyzed. Notably, the Lamberta variety came to the forefront in terms of storage root yield parameters (root weight, root length, single plant weight). Consequently, this variety displayed the highest average root yield compared to other varieties. While the Agatella variety demonstrated high averages for dry matter content and polar sugar content, it exhibited lower storage root and sugar yields. These findings suggest a negative correlation between sugar content and storage root yield and sugar yield. Overall, the Lamberta variety stood out in terms of root yield, while the Annamira variety stood out in terms of sugar yield. As a result of the research, sugar beet varieties varied between root diameters of 9.11-15.41 cm, root lengths of 15.34-18.43 cm, root weights of 646-2892 g, dry matter content of 20.87-24.40%, polar sugar content of 16.68-19.41%, root yields of 5196-8229 kg/da, and sugar yields of 908-1348 kg/da. According to the “which-where-won” model of GGE biplot analysis, the studied traits were clustered under 3 mega environments.