White Sugar Yield Research Articles

Evaluation of yield and stability of sugar beet (beta vulgaris L.) genotypes using GGE biplot and AMMI analysis

Rhizomania is the most destructive sugar beet disease in the world, and in recent years, it has widespread in most of the sugar beet growing areas in Iran. Since the control of this soil-borne disease is a difficult task, the use of resistant genotypes is known as the best measure against the disease. The ultimate goal of sugar beet breeders is to produce genotypes that can be used in both infected and non-infected fields without any reduction in terms of yield and quality. Twenty-one sugar beet genotypes along with four controls were evaluated in randomized complete block design with four replications in fields with natural infection to rhizomania in five research stations. Important sugar beet traits including root yield, sugar yield, sugar content, and white sugar yield were evaluated for two years (2021 and 2022). For all traits, location was the main source of variation that spanned 33 to 55% of the total sum of the square followed by the location×year×genotype accounted for 3–40% of the variation. Based on the results of analysis of variance, multivariate stability parameters were computed to evaluate the genotypes’ stability. The first two principal components (IPCA1 and IPCA2) generated by GGE biplot contributed for 31.3 and 17.5% difference in genotype×environment interaction for root yield, respectively. According to the GGE biplot, genotypes RM-11 and RM-12 were identified as the winning genotypes across environments for both root yield and white sugar yield traits whereas AMMI model identified RM-14 and RM-9 (for root yield) and RM-1 (for white sugar yield) as best genotypes. Based on the ideal genotype ranking, RM-11 and RM-10 were the best performer with a high mean yield as well as stability in the studied environments. The biplot rendered using the weighted average of absolute scores (WAASB) and root yield and white sugar yield identified RM-11 and RM-9 as superior genotypes in terms of yield and stability. The selected genotypes can be used in breeding programs to transfer the disease resistance and cultivar development.

Life cycle assessment of biochar and cattle manure application in sugar beet cultivation – Insights into root yields, white sugar quality, environmental aspects in field and factory phases

Sugar beet (Beta vulgaris L.) is a well-known sugar crop essential for supplying the global demand for sugar. Examining how different farming techniques affect the environment may help produce a high-quality crop with the least negative environmental effects. To this, the life cycle assessment (LCA) of biochar (B) and cattle manure (CM) applications at three different rates (5, 10, and 15 tons ha−1) compared with conventional chemical fertilization (CH) in the autumn and spring sugar beet crops has been studied. The system boundaries for LCA analysis were set from the cradle to the sugar factory gate. Based on the results, the highest amounts of root yield were obtained under CM10 and CM15 treatments with 24.5% and 23.2% increase in autumn cultivation and 34.8%, and 33.9% increase in spring cultivation, compared to CH. However, CM15 resulted in significantly lower sugar content (10.9%) than B5 (17%). Also, B utilization significantly reduced molasses content in sugar beet rather than CM in both cultivation periods. Further, biochar treatments (B5, B10, B15) significantly increased the white sugar yield in both cultivation times by 43.7%, 39.2%, and 36.1%, on average. Generally, the highest and the lowest global warming potential (GWP) were obtained from CM15 and B15 with 638.5 and 437.2 CO2-eq ton−1 root/sugar yields, respectively. These findings validate the hypothesis that using biochar in sugar beet production could reduce greenhouse gas emissions while increasing the amount of white sugar produced.

Unraveling genotypic interactions in sugar beet for enhanced yield stability and trait associations

The interaction between genotype and environment (GEI) significantly influences plant performance, crucial for breeding programs and ultimately boosting crop productivity. Alongside GEI, breeders encounter another hurdle in their quest for yield improvement, notably adverse and negative correlations among pivotal traits. This study delved into the stability of white sugar yield (WSY), root yield (RY), sugar content (SC), extraction coefficient of sugar (ECS), and the interplay among essential traits including RY, SC, alpha amino nitrogen (N), sodium (Na+), and potassium (K+) across 15 sugar beet hybrids and three control varieties. The investigation spanned two locations over two consecutive years (2022–2023), employing a randomized complete block design with four replications to comprehensively analyze these factors. The analysis of variance highlighted the significant effects of environment, genotype, and GEI at the 1% probability level. Notably, the AMMI analysis of GEI revealed the significance of the first component for WSY, RY, and SC, with the first two components proving significant for ECS. Within the linear mixed model (LMM), WSY, RY, SC, and ECS demonstrated significant effects from both genotype and GEI. In the WAASB biplot, genotypes 10, 8, 17, 6, 13, 14, 15, 7, 12, and 16 exhibited stability in WSY, while genotypes 9, 10, 6, 14, 7, 8, 13, 12, 18, and 15 displayed stability in RY. Additionally, genotypes 10, 15, 12, 13, 16, 17, 6, and 14 were stable for SC, and genotypes 8, 10, 7, 6, 13, 12, 16, 17, 15, 14, and 18 showcased stability in ECS, boasting above-average yield values. In the genotype by yield × trait (GYT) biplot, genotypes 15, 18, and 16 emerged as top performers when combining RY with SC, Na+, N, and K+, suggesting their potential for inclusion in breeding programs.

Genotype by environment interaction and stability analysis for harvest date in sugar beet cultivars

This research assessed the quantitative and qualitative reactions of commercially grown sugar beets to four different harvest dates and their yield stability. The study followed a split-plot design within a randomized complete block design over 3 years. The main plot involved 10 sugar beet cultivars, while the subplot involved four harvest dates: August 13 (HD1), September 7 (HD2), October 3 (HD3), and November 12 (HD4). The study found that environmental conditions, genotypes, and harvest dates significantly affected various traits of sugar beet. Yearly environmental variations and their interactions with genotypes and harvest dates had substantial impacts on all measured traits at the 1% probability level. Additive main effect and multiplicative interaction analysis based on white sugar yield indicated that genotype and environment's additive effects, as well as the genotype–environment interaction, were significant at 1% probability level. Shokoufa and Arya, which exhibit high white sugar yield (WSY) and low first interaction principal component (IPC1) values, are identified as desirable due to their stability across different environments. Among the harvest dates in different years, the fourth and third dates showed a higher yield than the total average. Perfekta and Ekbatan exhibited high specific adaptability. According to the multi-trait stability index, Arta, Arya and Sina were recognized as stable and superior across all measured traits.

Optimizing an Organic Method of Sugar Beet Cultivation and Yield Gap Decrease in Northern Poland

In the period of 2016–2018, two series of field studies on organic sugar beet growing (Beta vulgaris L.) were carried out in northern Poland on Luvisol loamy soil (medium–heavy) soil in Bałcyny and Płonne. The aim of this study was to decrease the yield gap between organic and conventional beets. Factors to increase the yield of organic beet were differentiated fertilization (cattle farmyard manure (FYM), compost, and Bioilsa) and choice of varieties (Eliska, Jampol, and Sobieski). The reference point was the conventional cultivation of the same sugar beet varieties, fertilized with manure and NPK mineral fertilizers, the prevailing standard of sugar beet cultivation in Poland. High sugar beet root yields exceeding the average yield in Poland by 25–30% were obtained in both studies, both in conventional and organic cultivation. Higher root and white sugar yields were obtained in the study conducted at Płonne (with similar soil conditions to those at Bałcyny), but they were characterized by higher temperatures during the growing season. The lowest root yields in both experiments were obtained by fertilizing the organic beet with compost (66.1 t per ha in Bałcyny and 78.13 t per ha in Płonne), which were 10.8% and 8.5% lower than the conventional crop, respectively. Higher root yields in organic cultivation were obtained by fertilizing the sugar beet with FYM, which reduced the differences from conventional beet to 7.7% in the study in Bałcyny and 2.1% in the study in Płonne. Thus, the results showed no need to convert cattle FYM to compost. The highest root yields in organic cultivation were obtained by fertilizing the sugar beet with Bioilsa N 12.5 supplemented with mineral fertilization of K, Mg, and S (Patentkali). This fertilization provided a yield of 78.1 t of roots per ha in Bałcyny, which is a reduction in the yield gap to 1.4%, a statistically insignificant value. Moreover, in the study at Płonne, organic sugar beet fertilized with Bioilsa and Patentkali yielded 86.7 t of roots per ha, compared to 85.6 t per ha of conventional beet, so a yield gap was not seen here. The choice of varieties was also of great importance for root and pure sugar yields in both farming systems. The lowest yields were obtained from the Eliska variety, and at Bałcyny, a change of beet cultivar to Jampol increased the organic root yield from 68.8 t per ha to 76.0 t per ha, while reducing the yield gap from 10.1% to 2.2%. At Płonne, replacing the Eliska variety with Jampol reduced the yield gap between organic and conventional roots from 6.6% to 0.3%.

Time point of virus yellows infection is crucial for yield losses in sugar beet, and co‐infection with beet mosaic virus is negligible under field conditions

AbstractBeet chlorosis virus (BChV), beet mild yellowing virus (BMYV) and beet yellows virus (BYV) transmitted by Myzus persicae cause virus yellows (VY) disease in sugar beet. M. persicae also transmits beet mosaic virus (BtMV), which is often associated with VY. So far, field trials to determine the effect of infection time point on yield have used 100% inoculation density and little is known about the yield effect of BtMV in mixed infections with VY species under field conditions. Therefore, we conducted sugar beet field trials using a new inoculation protocol with densities of 3%–10% in combination with different infection time points; we also tested the effect of BtMV/VY species mixed infections on white sugar yield (WSY). We observed a wide range of WSY losses for BChV (3.6%–26.8%), BMYV (1.7%–22.0%) and BYV (3.7%–37.0%) depending on infection time point, with no further significant losses after BBCH Stages 18/19, 35 and 39, respectively. Both the time of infection and area under disease progress curve showed excellent correlation with WSY losses for all VY species. BtMV had no significant effect on WSY losses either as a single infection or in mixed infections with BChV or BYV compared to control or single infections of these viruses. However, BMYV/BtMV mixed infection showed significantly increased WSY loss (+13.6%) compared to single BMYV infection. Our results can be used to predict yield losses in practical fields and to develop economic control thresholds for decision support systems.

Evaluation of sugar beet (Beta vulgaris L.) cultivars for some biochemical and agronomic traits under drought stress

This experiment aimed to evaluate quantitative and qualitative characteristics, tolerance to water deficit, and stability of white sugar in sugar beet cultivars. The experimental design was a split plot based on a randomized complete block design with three replications, where the irrigation levels (normal and water shortage) were assigned to the main plots and 18 sugar beet cultivars were assigned to the subplots. The result revealed that Palma achieved the maximum root and white sugar yield under normal and water deficit; furthermore, the highest indices of YP, YS, MP, STI, HM, YI, DI, REI and MRP belonged to the Palma cultivar. The results of the AMMI analysis based on white sugar yield showed that the additive effects of genotype and environment and the multiplicative effect of G×E accounted for 75.52, 17.05 and 6.76 % of the total data variance. Based on AMMI stability value, the Delta, Pars, Paya and Novodoro cultivars were recognized as stable varieties. Also, the first 2 significant components of the interaction effect (G×E) accounted for 99.12 % of interaction effects variation. Based on the biplot results of the first 2 significant components against white sugar yield, Azare and Merak were the appropriate cultivars. Finally, Based on the multi-trait stability index, Azara, Novodoro and Merak cultivars were selected as stable genotypes. In 2 years and 2 conditions, the Palma cultivar was identified as a cultivar with high yield and drought tolerance and low stability and the Merak cultivar was identified as a cultivar with white sugar yield and acceptable stability.

Does the Amount of Pre-Sowing Nitrogen Fertilization Affect Sugar Beet Root Yield and Quality of Different Genotypes?

There has always been a specific focus on nitrogen fertilization in sugar beet production due to its important effect on sugar beet root yield and quality. For stable sugar beet growth and satisfactory root yield and quality, balanced N fertilization is crucial. Thus, this study aimed to investigate spring N fertilization in two seasons as the following treatments: N0—control, N1—only pre-sowing fertilization, and N2—pre-sowing with topdressing. Four different genotypes were included in the study (Serenada, Colonia, Fred, and Danton). The experiment was set up in a plain area, belonging to the temperate climate zone in Eastern Croatia (Županja and Vrbanja), with the long-term mean (LTM) (March–October) air temperature around 16 °C and the total precipitation of 515 mm. Pre-sowing N fertilization had a smaller impact on root yield in the year with higher precipitation (31% higher than LTM). Therefore, the average yields with pre-sowing fertilization (N1) and pre-sowing fertilization with top dressing (N2) were very similar and were only 7% higher than those of the control. In a season with less rainfall (29% less than LTM), pre-sowing fertilization with top dressing (N2) had a more pronounced effect on the increase in sugar beet root yield, which was 17% higher compared to that of the control treatment. The sugar beet sucrose content and quality parameters (brei impurities, loss of sugar in molasses, extractable sugar) differed when N fertilization was applied among locations in both seasons. The white sugar yield was the highest at N2 treatment with pre-sowing and topdressing N fertilization. In general, according to the average of all locations and years of research, the Serenada hybrid achieved the highest average root yield (81.1 t ha−1), while Colonia exhibited the highest root sugar content (14.5%) and white sugar yield (9.7 t ha−1).

Genotype by environment and genotype by yield*trait interactions in sugar beet: analyzing yield stability and determining key traits association

The genotype by environment interaction significantly influences plant yield, making it imperative to understand its nature for the creation of breeding programs to enhance crop production. However, this is not the only obstacle in the yield improvement process. Breeders also face the significant challenge of unfavorable and negative correlations among key traits. In this study, the stability of root yield and white sugar yield, and the association between the key traits of root yield, sugar content, nitrogen, sodium, and potassium were examined in 20 sugar beet genotypes. The study was conducted using a randomized complete block design with four replications over two consecutive years across five locations. The combined analysis of variance results revealed significant main effects of year, location, and genotype on both root yield and white sugar yield. Notably, two-way and three-way interactions between these main effects on root yield and white sugar yield resulted in a significant difference. The additive main effect and multiplicative interaction analysis revealed that the first five interaction principal components significantly impacted both the root yield and white sugar yield. The linear mixed model results for root yield and white sugar yield indicated that the genotype effect and the genotype by environment interaction were significant. The weighted average absolute scores of the best linear unbiased predictions biplot demonstrated that genotypes 20, 4, 7, 2, 16, 3, 6, 1, 14, and 15 were superior in terms of root yield. For white sugar yield, genotypes 4, 16, 3, 7, 5, 1, 10, 20, 2, and 6 stood out. These genotypes were not only stable but also had a yield value higher than the total average. All key traits, which include sugar content, sodium, potassium, and alpha amino nitrogen, demonstrated a negative correlation with root yield. Based on the genotype by yield*trait analysis results, genotypes 20, 19, and 16 demonstrated optimal performance when considering the combination of root yield with sugar content, sodium, alpha amino nitrogen, and potassium. The multi-trait stability study, genotype 13 ranked first, and genotypes 10, 8, and 9 were identified as the most ideal stable genotypes across all traits. According to the multi-trait stability index, genotype 13 emerged as the top-ranking genotype. Additionally, genotypes 10, 8, and 9 were recognized as the most stable genotypes.

Plant Biostimulants as an Effective Tool for Increasing Physiological Activity and Productivity of Different Sugar Beet Varieties

Drought and high temperatures are among most dangerous attributes of climate change, which negatively affects the quantity and quality of sugar beet production. One of the most effective tools for eliminating unwanted effects is the application of biostimulants during the growing season. In this study, a 4 × 3 factorial scheme was adopted: Two biostimulant treatments, namely (i) pure extract from brown seaweed Ascophylum nodosum (B1) and (ii) concentrate from the seaweed Ascophylum nodosum and humus substances (B2), were compared to a control treatment (B0) in an experiment with four sugar beet varieties (Fischer, Fabius, Nicolaus, Lucius). The two-year research proved the significant influence of biostimulants on all monitored physiological and production parameters of sugar beet, with the exception of potassium content. Biostimulants positively influenced the results of root yield, polarized and white sugar yield, and the values of LAI (leaf area index), NDVI (normalized difference vegetation index), and PRI (photochemical reflectance index), while the positive effect on sugar content was only in the case of B1 treatment. The production potential fluctuated significantly depending on the observed interaction, but it can be concluded that the most limiting factor of production is the course of weather conditions. However, after treatment with biostimulants, an increased root yield (B2) and sugar content (B1) were found. Moreover, in this experiment, a strong positive relationship between root yield and physiological parameters (NDVI and PRI) and LAI was proven, while the relationship of sugar content to these parameters was weak. Monitoring of the physiological response to biostimulant application shows a high potential from the sustainability perspective in the context of sugar beet production. In addition, the impact on the height and quality of production was evident.

Evaluation of the quantitative and qualitative characteristics of sugar beet cultivars in different sowing times and transplanting and direct-seeding systems

To study the characteristics of sugar beet cultivars in transplanting and direct-seeding systems on three different sowing times (March 29, April 8, and April 18), a split plot experiment based on randomized complete blocks in three replications was carried out in Miandoab and Bokan regions, Northwest of Iran in 2016. The results showed that the highest nitrogen content was observed between the two test locations in the Bukan area. Results showed that the low root sodium, alkalinity, and molasses content was recorded for transplanting system. The minimum content of root sodium, nitrogen, and molasses sugar was observed in the plants sown on March 29. The Dorotea cultivar showed the highest root yield, sugar yield, and white sugar yield and the lowest root nitrogen and molasses sugar content compared to Isabella and Ekbatan. The highest white sugar content, coefficient of sugar extraction, sugar yield, root yield, and white sugar yield were recorded in the transplanting system with the sowing time of March 29; however, the highest content of root potassium and sugar content was observed in the transplanting system sown on April 18. The highest root yield was observed in the Dorotea cultivar, with a sowing time of March 29. Among the locations in the cultivar and planting system interaction treatments, the highest sugar content was found in the Bukan area's Dorotea cultivar in the transplanting system. Finally, the highest sugar yield was related to the transplanting system on March 29 in the Bukan area. It can be stated that an early sowing time (March 29), transplanting, and Dorotea variety were identified as the most appropriate treatments to improve the economic traits of sugar beet.

Zinc amendment increases the yield and industrial quality of Beta vulgaris L. cultivated in Northeast China

The sugar beet (Beta vulgaris L.) is a major industrial crop in Northeast China, but long-term or recurrent cultivation practices with low zinc (Zn) inputs have resulted in a decline in its cumulative yield and industrial quality. Hence, Zn fertilization is gaining interest in the commercial production of sugar beets; however, the efficacy and mechanism of Zn in enhancing the yield and industrial quality of sugar beets remain underexplored. A field experiment was conducted for two consecutive years (2019 and 2020) in black and albic soils of Northeast China with three levels of Zn fertilizer (0 kg ha−1, 30 kg ha−1, and 60 kg ha−1) using sugar beet cv. KWS1176. The application of Zn improved the photosynthetic performance and biomass of sugar beets and promoted the accumulation of dry matter in the roots. Zinc fertilization remarkably increased the sugar beet root yield in black and albic soils by 14.50% and 5.75%, respectively. Furthermore, the K and Na contents decreased in sugar beet roots cultivated in both soil types by augmenting Zn, whereas the sugar content increased significantly. The application of Zn considerably increased the biological sugar and white sugar yield by 15.25%, and 16.71% on average in black soil and 6.75% and 5.90% in albic soil, respectively. Correlation analysis showed that the root and white sugar yields were closely related to Zn accumulation in sugar beet roots. The amendment of cultivable lands with Zn fertilizer, preferably at a rate of 30 kg ha−1, is an effective strategy to simultaneously improve the root yield and quality of sugar beets, with better efficacy in black soils than in albic soils. Our findings provide a scientific basis for nutrient management in sugar beet planting and a step forward toward the sustainable development of the sugar industry.

Stability analysis and selection of sugar beet (Beta vulgaris L.) genotypes using AMMI, BLUP, GGE biplot and MTSI

The methods utilized to analyze genotype by environment interaction (GEI) and assess the stability and adaptability of genotypes are constantly changing and developing. In this regard, often instead of depending on a single analysis, it is better to use a combination of several methods to measure the nature of the GEI from various dimensions. In this study, the GEI was investigated using different methods. For this purpose, 18 sugar beet genotypes were evaluated in randomized complete block design in five research stations over 2 years. The additive effects analysis of the additive main effects and multiplicative interaction (AMMI) model showed that the effects of genotype, environment and GEI were significant for root yield (RY), white sugar yield (WSY), sugar content (SC), and extraction coefficient of sugar (ECS). The multiplicative effect's analysis of AMMI into interaction principal components (IPCs) showed that the number of significant components varies from one to four in the studied traits. According to the biplot of the mean yield against the weighted average of absolute scores (WAAS) of the IPCs, G2 and G16 for RY, G16 and G2 for WSY, G6, G4, and G1 for SC and G8, G10 and G15 for ECS were identified as stable genotypes with optimum performance. The likelihood ratio test showed that the effects of genotype and GEI was significant for all studied traits. In terms of RY and WSY, G3 and G4 had high mean values of the best linear unbiased predictions (BLUP), so they were identified as suitable genotypes. However, in terms of SC and ECS, G15 obtained high mean values of the BLUP. The GGE biplot method classified environments into four (RY and ECS) and three (WSY and SC) mega-environments (MEs). Based on the multi-trait stability index (MTSI), G15, G10, G6, and G1 were the most ideal genotypes.

Improving sugar beet yield, quality, and water use efficiency by nursery and transplanting practice under semi‐arid conditions

AbstractTransplanting is a useful technique to produce sugar beet (Beta vulgaris L.) in arid and semi‐arid regions that face water scarcity and salinity. The major challenge in transplanting is to improve the economic benefits that smallholder farmers have in the self‐production of transplants. The objective of this study was to evaluate the yield, quality, and water use efficiency (WUE) of sugar beet in response to transplanting and different options in transplant production process. Two field experiments were conducted at two sites. The first experiment investigated the effects of seedling age at transplanting, volume of the substrate, and transplanting date. The second experiment investigated the effects of substrate media and transplant production conditions on sugar beet yield and quality. In both experiments, transplanting was compared to the direct seeding on the conventional planting date at both sites. The highest white sugar content (12.1% and 13.5%) and white sugar yield (10.2 and 12.1 t ha−1) were obtained from plants transplanted in mid‐May at sites 1 and 2, respectively. Also, root yield, total sugar content, and WUE were higher in transplanting than direct seeding. The 40‐day‐old transplants produced in 22 mL cell volume when transferred to the field in mid‐May had higher WUE than the direct seeding. The transplants produced outside the greenhouse (uncontrolled conditions) had nearly the same yields as those produced inside a greenhouse under controlled conditions. We suggest that using readily available substrates and not requiring greenhouse conditions for transplant production is a cost‐effective way for smallholder farmers to produce their own seedlings.

Evaluation of resistance and determination of stability of different sugar beet (Beta vulgaris L.) genotypes in rhizomania-infected conditions.

Plant diseases are considered one of the main factors reducing yield and quality of crops, which are constantly developing and creating more virulent races and cause the resistance of more genes to break. Identifying resistance sources and including them in breeding programs will improve resistant genotypes. Rhizomania is the most common, widespread, and devastating disease of sugar beet in Iran and worldwide. Breeding genotypes with disease resistance genes is one of the most important ways to deal with this destructive disease. Twenty sugar beet genotypes along with five controls were evaluated in a randomized complete block design with four replications in rhizomania-infected conditions in four regions of Mashhad, Shiraz, Miandoab, and Hamedan for 2 years. The results of genotypic reaction to rhizomania showed that the genotypes with resistance reaction were much more frequent than those with susceptibility reaction. The analysis of multiplicative effects of the AMMI model showed that the first six components were significant and explained 98.80% of the interaction variations. The biplot obtained from the mean white sugar yield and the first interaction principal component confirmed the superiority of the RM5 genotype due to its high white sugar yield and stability in infected conditions. The results obtained from the first three principal components biplot showed that the RM9 genotype with a mean white sugar yield of 11.91 t. ha-1 was a genotype with vast general stability in all disease-infected environments. Based on the results of the MTSI index, RM3, RM17, RM9, RM13, and RM15 are introduced as stable genotypes under rhizomania-infected conditions. In conclusion, it seems that the studied genotypes have valuable and useful genes inherited from their parents to deal with rhizomania disease. Applying these genotypes in sugar beet breeding programs can effectively prevent the threat of rhizomania.

Quantity and Quality Changes in Sugar Beet (Beta vulgaris Provar. Altissima Doel) Induced by Different Sources of Biostimulants.

The application of biostimulants in agriculture is considered an economically and ecologically acceptable and, above all, a sustainable method of cultivation of field crops. This study aimed to investigate the impact of biostimulating agents on the production and growth parameters of the sugar beet. In 2018 and 2019, an experiment was conducted in which the effect of four types of treatment (B0–B3) on two varieties of sugar beet (Alpaca, Gorila) was observed. The results show that the beets treated with treatment type B3 (combination of humic acids, essential amino acids, biopolymers, and soil bacteria) had the significantly highest yield of roots compared with the control type. However, parameters such as sugar content, polarized sugar yield, white sugar content, and white sugar yield were the highest in condition B2, treated with an agent containing soil bacteria. Furthermore, biostimulants positively affected the leaf area index, with significant growth observed, especially in condition B3. Another important finding was that in the interaction analysis, the biostimulants had positive effects in dry conditions and on elevated values of traits of Alpaca variety caused by treatment in condition B2. In terms of relationships between individual parameters, an interesting finding was that there was only a weak relationship between root yield and sugar content (Rs = 0.0715), which indicates that biostimulants increase production size while maintaining or increasing its quality.

AMMI Analysis of the Effects of Different Insecticidal Treatments against Agrotis spp. on the Technological Yield from Sugar Beet

The aim of this study was to analyze the effects of different variants of insecticidal treatment against Agrotis spp. caterpillars on the technological yield from sugar beet using the AMMI (Additive Main Effect and Multiplicative Interaction) model. Data for the analysis of sugar beet yield and different insecticidal treatments were obtained from a trial in Winna Góra between 2011 and 2018. White sugar yield was estimated for each variant of treatment, and it was found to be directly proportional to the root weight and polarization. The content of potassium in molasses had an inversely proportional effect on the sugar yield in the variant of treatment based on phenological observations with calculated heat sums, as well as in controls. The content of α-amino-N had an inversely proportional effect on the technological yield of sugar for each variant of tested chemical treatments. The content of α-amino-N had a statistically significant effect on the sugar beet yield for all tested experimental combinations. AMMI analysis used to estimate the interaction of treatments based on environmental conditions showed the additive effect of the applied treatments on the quality parameters of white sugar yield from sugar beet. These effects were demonstrated for polarization and the content of sodium in molassigenic substances. Regarding the AMMI model, the results of the analysis of variance showed a significant interaction between treatment and year for all considered characteristics in the experiment.

Boron Improves the Industrial Quality of Sugar Beet (Beta Vulgaris) and Increases the White Sugar Yield: A Case Study in Northeast China

Boron Improves the Industrial Quality of Sugar Beet (Beta Vulgaris) and Increases the White Sugar Yield: A Case Study in Northeast China

Sugar Beet Root Yield and Quality with Leaf Seasonal Dynamics in Relation to Planting Densities and Nitrogen Fertilization

This study aimed to analyze the seasonal dynamics of sugar beet leaf and root yield and quality in different plant populations and the nitrogen fertilization rate. The field trials were set as four different planting densities (60,000 to 140,000 plants ha−1) and three different spring nitrogen fertilization rates: no fertilization, pre-sowing (45 kg ha−1 N), and pre-sowing with top dressing (99 kg ha−1 N in 2014 and 85.5 kg ha−1 N in 2015. The changes of leaf growth were done measuring leaf area (LA), leaf area index (LAI), specific leaf area (SLA), and leaf area ratio (LAR). The highest LAI in 2014 was determined on 30 July at 140,000 plants ha−1 (9.35 m2 m−1) and in 2015 on 20 June at 100,000 plants ha−1 (4.83 m2 m−2). In both years, the SLA and LAR was highest at the end of May. In relation to plant density, higher plant densities had on average the highest root yield, sucrose content, and white sugar yield. In both years, pre-sowing with top dressing spring nitrogen fertilization resulted in the highest root (95.0 t ha−1) and white sugar yield (11.4 t ha−1), whereas the highest sucrose content was after pre-sowing fertilization (14.9%).

EFFECT TO CROP ROTATION AND FERTILIZATION SYSTEM IN YIELD AND TECHNOLOGICAL QUALITY IN SUGAR BEET (BETA VULGARIS L.)

he quality of sugar beet roots is estimated by the concentrations of K, Na and ?-amino nitrogen in cell fluid since sucrose content in the cell vacuole is the result of a balance of other active osmotic compounds (K and Na ions). Along with the increasing dose of organomineral fertilizers, sugar losses in molasses increase, the thin juice purity decreases, and, accordingly, white sugar yield decreases. Therefore, the optimal dose of fertilizers within the organomineral fertilization system on the typical leached chernozem (in the zone of sufficient soil moisture) was 40 t/ha of cattle manure + N90P110K130, which provides sugar yield of 6.37, 6.32, and 6.48 t/ha. Analysis of sugar yield per hectare under the conditions of insufficient soil moisture shows the importance of the right decision on short crop rotation. Thus, the highest sugar yield (5.73 t/ha) was observed in the grain – grass – hoed crop rotation against the background of 25 t/ha of cattle manure + N90P120K90. However, increased fertilizer doses, 25 t/ha of cattle manure + N135P180K135, causes a reduction in sugar yield and is not efficient in terms of additional input