Simple Root Measure Predicts Sugar Beet Quality Across Six Years of Trials

Sugar beet is one of the world’s most important industrial crops, supplying roughly a fifth of global sugar production, yet breeders have long struggled to identify which measurable traits reliably predict how much usable sugar a root will actually deliver to the factory. A new multi-year study now argues that the answer may be hiding in plain sight: the percentage of dry matter in the root. In an analysis spanning 47 field trials and 66 registered cultivars conducted between 2019 and 2024 at the Motahari Research Station in Karaj, Iran, researchers found that dry matter content behaves not as a passive byproduct of growth but as an integrative physiological marker, one that simultaneously reflects carbon assimilation, assimilate partitioning, and the regulation of mineral ions that can sabotage sugar extraction.

The team, led by Parviz Fasahat of the Sugar Beet Seed Institute in Karaj, together with colleagues from the Agricultural and Natural Resources Research Center of Khorasan Razavi, published the work in the journal Discover Plants. Their central hypothesis was that variation in dry matter across genotypes arises from underlying differences in photosynthetic efficiency, the allocation of sucrose to storage roots, and mineral ion homeostasis. If correct, dry matter could serve as a single, easily measured proxy for a suite of complex physiological processes that are otherwise difficult and expensive to assess, giving breeding programs a powerful screening tool.

The scale of the dataset lends the conclusion considerable weight. Dry matter percentage across the 66 cultivars ranged from 15.8 to 27.1 percent, with a mean of approximately 21.7 percent, a spread that reflects both substantial genetic diversity and the sensitivity of dry matter formation to environmental and management conditions. Root yield itself varied dramatically, from 49.7 to 140.8 tonnes per hectare with an average of 91.5 tonnes, while mean sugar content was 15.2 percent and white sugar content averaged 13.4 percent. Mineral impurities were similarly variable: sodium ranged from 0.7 to 11.9 milliequivalents per 100 grams, potassium from 2.2 to 7.2, and nitrogen from 0.3 to 7.1. This variability matters because excess sodium can induce salinity-like stress, elevated nitrogen shifts assimilate partitioning toward amino compounds rather than sugars, and fluctuating potassium levels influence osmotic adjustment and sugar translocation.

Using Spearman’s rank correlation on the pooled multi-year dataset, the researchers uncovered striking associations. Dry matter correlated strongly and positively with sucrose content (r = 0.88), white sugar content (r = 0.87), and the extraction coefficient of sugar (r = 0.78), the latter measuring how efficiently sucrose can actually be recovered during industrial processing. Moderate positive correlations appeared with sugar yield (r = 0.34) and white sugar yield (r = 0.54). On the negative side, dry matter was inversely associated with root yield (r = −0.22), sodium (r = −0.75), nitrogen (r = −0.31), and molasses sugar (r = −0.71), the fraction of sugar lost to crystallization because it remains trapped in impurity-laden molasses. Potassium (r = −0.05) and alkalinity (r = −0.09) showed weak, nonsignificant relationships, suggesting these traits are comparatively insensitive to dry matter variation.

Crucially, the team tested whether these relationships held up under different growing conditions rather than relying on a single season. Annual precipitation at the site ranged from 0.94 millimeters per day in 2022 to 1.75 in 2019, and maximum summer temperatures consistently exceeded 36 degrees Celsius, with relative humidity fluctuating considerably between seasons. Year-specific Pearson correlation analyses showed that the positive associations of dry matter with sugar content, white sugar content, and the extraction coefficient, together with its negative association with sodium, remained consistent across all six growing seasons. By contrast, the relationships between dry matter and yield-related traits, including root yield, sugar yield, and white sugar yield, varied substantially from year to year, indicating that productivity traits are far more environmentally sensitive than the technological quality attributes tied to dry matter.

To move beyond simple correlation, the researchers fitted separate linear mixed-effects models for each trait, treating dry matter as a fixed effect and cultivar as a random intercept to account for genetic variability. The models, estimated by maximum likelihood in SAS and validated with Akaike and Bayesian information criteria alongside residual diagnostics, confirmed the correlation picture. Dry matter exerted significant negative effects on root yield and sodium content, and highly significant positive effects on sugar yield, white sugar yield, sucrose content, white sugar content, and the extraction coefficient. Molasses sugar was negatively and significantly affected, while potassium and alkalinity showed no significant response. In other words, higher dry matter systematically improves the traits that matter in the factory while suppressing the impurities that erode them.

The correlation heatmap revealed further structure in the trait network. Sugar content, white sugar content, and extraction coefficient were tightly interlinked, with pairwise correlations exceeding 0.9, while sugar yield and white sugar yield moved together at r = 0.95. These synergies suggest that selecting for one quality trait is likely to bring parallel gains in the others. Conversely, the extraction coefficient showed strong negative associations with sodium, potassium, nitrogen, and molasses sugar, exposing the antagonism between recoverable sugar percentage and the compositional impurities that interfere with crystallization. Traits such as root yield, potassium, and alkalinity displayed generally weak correlations with most other parameters, meaning they can potentially be modified more independently in breeding schemes.

What do these statistical patterns mean mechanistically? The authors propose that high-dry matter genotypes allocate a greater proportion of photosynthates toward carbohydrate storage in the root, a process mediated by enhanced phloem loading and unloading through sucrose transporter proteins that regulate source-to-sink carbon flux. Such genotypes may show increased activity or expression of sucrose-phosphate synthase, invertases, and sucrose synthase, enzymes that promote sucrose loading and storage in root vacuoles. Meanwhile, the negative correlations with sodium and nitrogen point toward active ion homeostasis: efficient exclusion or compartmentalization of sodium ions through ion transporter families reduces toxicity and maintains osmotic balance, while lower nitrogen content signals a metabolic shift favoring carbon allocation to sucrose synthesis over amino acid biosynthesis. These adjustments likely improve both stress tolerance and extract purity.

The study is careful to acknowledge its constraints. All trials were conducted at a single location, so the findings speak to overall associations across a large multi-year dataset rather than formally quantifying genotype-by-environment interaction, and the pooled analysis was a deliberate choice given that objective. Even so, the interannual variation in rainfall, temperature, and humidity at the site was real and substantial, which makes the stability of the quality-related correlations all the more convincing. The authors suggest that the next steps should include transcriptomic profiling of sucrose transporter and ion channel genes, enzyme activity assays for carbon metabolism, and ionomic analyses to unravel the genotype-specific regulatory networks that drive dry matter variation. Recent genomic work on nearly a thousand Beta vulgaris germplasms has already confirmed extensive genetic diversity underlying dry matter and sucrose traits, with complex marker-trait associations pointing to multifactorial control.

For breeders, the practical message is that dry matter content deserves a more prominent place in selection programs than it has traditionally received. Because it is cheap and fast to measure, yet tracks the physiological processes governing sucrose accumulation and impurity regulation more faithfully than biomass traits do, it could serve as an early-generation screening criterion for genotypes with enhanced sugar quality and processing efficiency. The trade-off with root yield, though real, was modest and environmentally variable, whereas the quality benefits were robust across every season tested. In an era when sugar factories demand ever-higher extractable purity and growers face increasingly erratic climates, a single root measurement that integrates carbon metabolism and ion regulation may prove to be one of the most valuable indicators in the sugar beet breeder’s toolkit.

Subject of Research: Dry matter content as an integrative physiological and quality indicator in sugar beet

Article Title: Dry matter content as a key indicator of physiological and quality traits in sugar beet

Article References: Fasahat, P., Rezaei, J., Babaee, B., Yousefabadi, V.-A., & Sadeghzadeh Hemayati, S. (2026). Dry matter content as a key indicator of physiological and quality traits in sugar beet. Discover Plants, 3(1), Article 402. https://doi.org/10.1007/s44372-026-00865-w

Image Credits: AI Generated

DOI: 10.1007/s44372-026-00865-w

Keywords: sugar beet, dry matter, sucrose content, plant physiology, ion homeostasis, sugar yield, breeding, correlation analysis, mixed-effects models, root quality, molasses sugar, source-sink dynamics