Cultivar specific nitrogen and potassium recommendations optimize yield and quality attributes in sugar beet

Abstract

This study aimed to investigate cultivar-specific responses to nitrogen and potassium fertilization in sugar beet (Beta vulgaris) to optimize yield, quality attributes, and fertilizer use efficiency. Five sugar beet cultivars (Indira, Carma, Mallak, Melodia, and Shantala) were evaluated under nine fertilization treatments combining three nitrogen and potassium levels (T1 (144 N,0 K); T2 (144 N,60 K); T3 (144 N,120 K); T4 (216 N,0 K); T5 (216 N,60K2);T6 (216 N,120 K); T7 (288 N,0 K); T8 (288 N,60 K); T9 (288 N,120 K)) in a split-plot design over two growing seasons (2020/2021 and 202120/22 ). Significant cultivar × treatment interactions (p < 0.001) were observed across all parameters. Root yield ranged from 55.72 t/ha (Indira) to 83.33 t/ha (Shantala under T2 treatment). Sucrose content varied from 18.10% (Indira) to 18.92% (Mallak), with corresponding purity levels of 79.93% and 76.39%. Principal component analysis revealed distinct cultivar-specific nutrient responses: lower nitrogen and potassium levels (T1 and T2) positively impacted quality attributes in Indira and Carma, while higher nitrogen and moderate potassium combinations (T3 and T6) enhanced yield attributes in Mallak and Shantala. Economic analysis showed optimal profitability with T3 treatment for Indira and Melodia (ROIs of 89.5% and 91.6%), T2 for Carma and Mallak (ROIs of 123.4% and 113.1%), and T1 or T6 for Shantala (ROI of 166%). Hierarchical clustering and correlation analysis identified strong positive relationships between root yield and biological yield (r = 0.94), recoverable sugar yield (r = 0.87), and sugar yield (r = 0.82). These findings provide valuable recommendations for cultivar-specific nutrient management strategies that farmers can implement to optimize both production efficiency and economic returns while reducing environmental impacts from excessive fertilization.

Keywords: Clustering heatmap; Cultivar selection; Multivariate analysis; PCA; Sugar beet (Beta vulgaris).

Fig. 1

Variation in Yield and Quality Traits Among Sugar Beet Cultivars. Boxplots depicting the distribution of root yield (RY, t/ha), biological yield (BY, t/ha), (C) sucrose content (SC, %), alkaline coefficient (AC), purity (%), shoot-to-root ratio (SLM), recoverable sucrose yield (RSY, t/ha), sugar yield (SY, t/ha), and total soluble solids (TSS, %) across five sugar beet cultivars (Indira, Carma, Mallak, Melodia, and Shantala). The boxplots show the median (horizontal line), interquartile range (box), and minimum/maximum values (whiskers), with outliers represented as individual points.

Fig. 2

Effect of Nitrogen and Potassium Fertilization on Yield and Quality Traits of Five Sugar beet Cultivars. RY : root yield (t / ha), BY : biological yield (t / ha), TSS : total soluble solids (%), SY: sugar yield (t / ha), SYE: sugar yield efficiency (%). T1: N1K1, T2: N1K2, T3: N1K3, T4: N2K1, T5: N2K2, T6: N2K3, T7: N3K1, T8: N3K2, T9: N3K3. Statistically significant differences (p < 0.001) were observed between treatments for all cultivars.

Fig. 3

Effect of Nitrogen and Potassium Fertilization on Yield and Quality Traits of Five Sugar beet Cultivars. AC : alkaline coefficient, SLM : Loss of sugar to molasses (%), RSY: Recoverable sugar (ton / ha). T1: N1K1, T2: N1K2, T3: N1K3, T4: N2K1, T5: N2K2, T6: N2K3, T7: N3K1, T8: N3K2, T9: N3K3. Statistically significant differences (p < 0.001) were observed between treatments for all cultivars.

Fig. 4

Principal component analysis biplots depict cultivar-specific relationships among yield, quality traits, and nitrogen-potassium fertilization regimes in five sugar beet cultivars (Indira, Carma, Mallak, Melodia, and Shantala). The first principal component (PC1) and its corresponding percentage of explained variance are shown on the x-axis for each cultivar. Traits like root yield (RY), biological yield (BY), total soluble solids (TSS), sugar yield (SY), sugar yield efficiency (SYE), sucrose (S), alkaline coefficient (AC), purity, sugar loss to molasses (SLM), and recoverable sugar yield (RSY) are represented by labeled points. The nine nitrogen-potassium treatment combinations (N1K1, N1K2, N1K3, N2K1, N2K2, N2K3, N3K1, N3K2, and N3K3) are color-coded for visual distinction.

Fig. 5

Hierarchical clustering heatmap illustrating the interrelationships between nitrogen-potassium fertilization treatment combinations (N1K1, N1K2, N1K3, N2K1, N2K2, N2K3, N3K1, N3K2, and N3K3) and yield and quality traits across five sugar beet cultivars (C1: Indira, C2: Carma, C3: Mallak, C4: Melodia, and C5: Shantala). The heatmap depicts the clustering patterns of the treatment combinations based on their associations with traits such as root yield (RY), biological yield (BY), total soluble solids (TSS), sugar yield (SY), sugar yield efficiency (SYE), SC (S), alkaline coefficient (AC), purity, sugar loss to molasses (SLM), and recoverable sugar yield (RSY). The color scale represents the strength of the associations, with red indicating positive relationships and blue representing negative relationships. The dendrogram on the left side illustrates the hierarchical clustering of the treatment combinations based on their similarity in trait associations across cultivars.

Fig. 6

Correlation matrix (a) and network visualization (b) provide illustrating the relationships among key yield and quality traits in sugar beets, including root yield (RY), biological yield (BY), total soluble solids (TSS), sugar yield (SY), sugar yield efficiency (SYE), SC, alkaline coefficient (AC), purity, sugar loss to molasses (SLM), and recoverable sugar yield (RSY). In the correlation matrix (a) the correlation coefficients are color-coded, with shades of blue indicating positive correlations and shades of red representing negative correlations. The intensity of the colors corresponds to the strength of the correlation, with darker shades denoting stronger relationships. Asterisks (***, **, *) indicate statistical significance at p < 0.001, p < 0.01, and p < 0.05, respectively.