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China is the world’s third largest sugar producing country after Brazil and India. During milling years 2004/2005 and 2013/2014, the average yearly sugar production in China was 11.64 MT, 49.86 % more that in the previous decade. However, the major increase came from Guangxi province, which produced 7.21 MT sugar per annum in average in recent decade, increased by 104.25 % compared to the production of 3.53 MT sugar per annum in average during 1994/1994 and 2003/2004. Sugarcane contributed more than 90 % of the total sugar production in recent decade. Chinese sugar industry encompasses 270 operating sugar mills, 233 sugarcane, and 37 sugar beet. In the milling year 2007/2008, the total sugar production in China reached 14.83 MT, which was 24.04 % higher than that in previous milling year; and cane sugar production reached 13.67 MT, which occupied 92.18 % of the total. However, the severe low temperature and drought occurred almost every year since 2008, which caused continuous in cane and sugar productivity in the subsequent years. The sugar production began recovering since 2011/2012, and reached 13.32 MT sugar in 2013/2014, still 10.18 % lower than that in 2007/2008. Guangxi is the largest sugarcane and sugar producer in China, 9.41 MT sugar in 2007/2008, and 8.56 MT sugar in 2013/2014. Besides, many products, such as pulp, paper, alcohol, yeast, xylitol, chemicals, cane juice, bio-manure, feed, and electricity are also produced from sugarcane. The sugar industry is also the major contributor to the socio-economic development of the major cane producing areas especially Guangxi, Yunnan and western Guangdong.

Background Beta vulgaris L. is one of the main sugar-producing crop species and is highly adaptable to saline soil. This study explored the alterations to the carbon and nitrogen metabolism mechanisms enabling the roots of sugar beet seedlings to adapt to salinity. Results The ionome, metabolome, and transcriptome of the roots of sugar beet seedlings were evaluated after 1 day (short term) and 7 days (long term) of 300 mM Na + treatment. Salt stress caused reactive oxygen species (ROS) damage and ion toxicity in the roots. Interestingly, under salt stress, the increase in the Na + /K + ratio compared to the control ratio on day 7 was lower than that on day 1 in the roots. The transcriptomic results showed that a large number of differentially expressed genes (DEGs) were enriched in various metabolic pathways. A total of 1279 and 903 DEGs were identified on days 1 and 7, respectively, and were mapped mainly to 10 Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways. Most of the genes were involved in carbon metabolism and amino acid (AA) biosynthesis. Furthermore, metabolomic analysis revealed that sucrose metabolism and the activity of the tricarboxylic acid (TCA) cycle increased in response to salt stress. After 1 day of stress, the content of sucrose decreased, whereas the content of organic acids (OAs) such as L-malic acid and 2-oxoglutaric acid increased. After 7 days of salt stress, nitrogen-containing metabolites such as AAs, betaine, melatonin, and (S)-2-aminobutyric acid increased significantly. In addition, multiomic analysis revealed that the expression of the gene encoding xanthine dehydrogenase (XDH) was upregulated and that the expression of the gene encoding allantoinase (ALN) was significantly downregulated, resulting in a large accumulation of allantoin. Correlation analysis revealed that most genes were significantly related to only allantoin and xanthosine. Conclusions Our study demonstrated that carbon and nitrogen metabolism was altered in the roots of sugar beet plants under salt stress. Nitrogen metabolism plays a major role in the late stages of salt stress. Allantoin, which is involved in the purine metabolic pathway, may be a key regulator of sugar beet salt tolerance.

Sugar beet pulp (SBP) is a valuable by-product of the sugar beet industry and is predominantly composed of cellulose, hemicellulose, and pectin. It is commonly used as livestock feed because of its palatability, good energy levels, and highly digestible fibers such as pectins and glucans. However, the utilization of SBP for the production of value-added products via biotechnological approaches is gaining significance in recent years owing to its potential as a cost-effective nutrient source and technological advancements in its processing. SBP can be used as a substrate for bio-production of microbial enzymes, single cell protein, alcohols (e.g., ethanol), methane/biogas, hydrogen, lactic acid, ferulic acid, and pectic oligosaccharides. SBP can also be used as a carrier for cell immobilization in fermentation processes. This review focused on recent developments in biotechnological valorization of SBP.

Background Modern agriculture strives to sustainably manage fertilizer for both economic and environmental reasons. The monitoring of any nutritional (phosphorus, nitrogen, potassium) deficiency in growing plants is a challenge for precision farming technology. A study was carried out on three species of popular crops, celery ( Apium graveolens L., cv. Neon), sugar beet ( Beta vulgaris L., cv. Tapir) and strawberry ( Fragaria × ananassa Duchesne, cv. Honeoye), fertilized with four different doses of phosphorus (P) to deliver data for non-invasive detection of P content. Results Data obtained via biochemical analysis of the chlorophyll and carotenoid contents in plant material showed that the strongest effect of P availability for plants was in the diverse total chlorophyll content in sugar beet and celery compared to that in strawberry, in which P affects a variety of carotenoid contents in leaves. The measurements performed using hyperspectral imaging, obtained in several different stages of plant development, were applied in a supervised classification experiment. A machine learning algorithm (Backpropagation Neural Network, Random Forest, Naive Bayes and Support Vector Machine) was developed to classify plants from four variants of P fertilization. The lowest prediction accuracy was obtained for the earliest measured stage of plant development. Statistical analyses showed correlations between leaf biochemical constituents, phosphorus fertilization and the mass of the leaf/roots of the plants. Conclusions Obtained results demonstrate that hyperspectral imaging combined with artificial intelligence methods has potential for non-invasive detection of non-homogenous phosphorus fertilization on crop levels.

Integrating the governing chemistry with the genomics and phenotypes of microbial colonies has been a “holy grail” in microbiology. This work describes a highly sensitive, broadly applicable, and cost-effective approach that allows metabolic profiling of live microbial colonies directly from a Petri dish without any sample preparation. Nanospray desorption electrospray ionization mass spectrometry (MS), combined with alignment of MS data and molecular networking, enabled monitoring of metabolite production from live microbial colonies from diverse bacterial genera, including Bacillus subtilis, Streptomyces coelicolor, Mycobacterium smegmatis , and Pseudomonas aeruginosa . This work demonstrates that, by using these tools to visualize small molecular changes within bacterial interactions, insights can be gained into bacterial developmental processes as a result of the improved organization of MS/MS data. To validate this experimental platform, metabolic profiling was performed on Pseudomonas sp. SH-C52, which protects sugar beet plants from infections by specific soil-borne fungi [R. Mendes et al. (2011) Science 332:1097–1100]. The antifungal effect of strain SH-C52 was attributed to thanamycin, a predicted lipopeptide encoded by a nonribosomal peptide synthetase gene cluster. Our technology, in combination with our recently developed peptidogenomics strategy, enabled the detection and partial characterization of thanamycin and showed that it is a monochlorinated lipopeptide that belongs to the syringomycin family of antifungal agents. In conclusion, the platform presented here provides a significant advancement in our ability to understand the spatiotemporal dynamics of metabolite production in live microbial colonies and communities.

Arabinanases from glycoside hydrolase family GH93 are enzymes with exo-activity that hydrolyze the α-1,5 bonds between arabinose residues present on arabinan. Currently, several initiatives aiming to use byproducts rich in arabinan such as pectin and sugar beet pulp as raw material to produce various compounds of interest are being developed. However, it is necessary to use robust enzymes that have an optimal performance under pH and temperature conditions used in the industrial processes. In this work, the first GH93 from the thermophilic fungus Thermothielavioides terrestris (Abn93T) was heterologously expressed in Aspergillus nidulans, purified and biochemically characterized. The enzyme is a thermophilic glycoprotein (optimum activity at 70 °C) with prolonged stability in acid pHs (4.0 to 6.5). The presence of glycosylation affected slightly the hydrolytic capacity of the enzyme, which was further increased by 34% in the presence of 1 mM CoCl2. Small-angle X-ray scattering results show that Abn93T is a globular-like-shaped protein with a slight bulge at one end. The hydrolytic mechanism of the enzyme was elucidated using capillary zone electrophoresis and molecular docking calculations. Abn93T has an ability to produce (in synergism with arabinofuranosidases) arabinose and arabinobiose from sugar beet arabinan, which can be explored as fermentable sugars and prebiotics.Key points• Thermophilic exo-arabinanase from family GH93• Molecular basis of arabinan depolymerization

Sugar beet is the most important crop for sugar production in temperate zones. The plant microbiome is considered an important factor in crop productivity and health. Here, we investigated the bacterial diversity of seeds, roots, and rhizosphere of five sugar beet hybrids named Eduarda (ED), Koala (KO), Tibor (T), Tajfun (TF), and Cercospora -resistant (C). A culture-independent next-generation sequencing approach was used for the further investigation of seed-borne endophytes. Hybrid-associated bacteria were evaluated for their plant growth–promoting (PGP) characteristics, antagonistic activity towards Cercospora beticola and several Fusarium strains in dual culture assays, and drought and salinity tolerance. High-throughput sequencing revealed that the Proteobacteria phylum was most dominant in the seeds of all hybrids, followed by Cyanobacteria and Actinobacteriota . The predominant genus in all hybrids was Pantoea , followed by Pseudomonas , Acinetobacter , Chalicogloea , Corynebacterium , Enterobacter , Enterococcus , Glutamicibacter , Kosakonia , and Marinilactibacillus . Unique genera in the hybrids were Pleurocapsa and Arthrobacter (T), Klebsiella (TF), Apibacter (ED), and Alloscardovia (KO). The genera that were most represented in one hybrid were Weissella and Staphylococcus (TF); Streptococcus (T); Gardnerella , Prevotella , and Rothia (KO); and Gilliamella , Lactobacillus , and Snodgrassella (ED). Thirty-two bacteria out of 156 isolates from the rhizosphere, roots, and seeds were selected with respect to various plant growth–promoting activities in vitro , i.e., nitrogen fixation, phosphate solubilization, siderophore production, indole-3-acetic acid production, 1-aminocyclopropane-1-carboxylic acid deaminase activity, hydrogen cyanide production, exoenzymatic activity (amylase, protease, lipase, cellulase, xylanase, mannanases, gelatinase, and pectinase), mitigation of environmental stresses, and antifungal activity. Mixta theicola KO3-44, Providencia vermicola ED3-10, Curtobacterium pusillum ED2-6, and Bacillus subtilis KO3-18 had the highest potential to promote plant growth due to their multiple abilities (nitrogen fixation, phosphate solubilization, production of siderophores, and IAA). The best antagonistic activity towards phytopathogenic fungi was found for Bacillus velezensis C3-19, Paenibacillus polymyxa C3-36 and Bacillus halotolerans C3-16/2.1. Only four isolates B. velezensis T2-23, B. subtilis T3-4, B. velezensis ED2-2, and Bacillus halotolerans C3-16/2.1 all showed enzymatic activity, with the exception of xylanase production. B. halotolerans C3-16/2.1 exhibited the greatest tolerance to salinity, while two B. subtilis strains (C3-62 and TF2-1) grew successfully at the maximum concentration of PEG. The current study demonstrates that sugar beet–associated bacteria have a wide range of beneficial traits and are therefore highly promising for the formulation of biological control and PGP agents.

Purpose Salt stress often reduces plant efficiency in nutrient utilization, particularly nitrogen (N), leading to physiological disorders, primarily those related to phytohormones. Hence, the current study assessed the combined effect of indole-3-acetic acid (IAA) and N in inducing salt stress tolerance in sugar beet. Methods Using a split-plot in randomized complete block design replicated thrice, the effect of three IAA levels (0, 150, and 300 mg L − 1 , denoted IAA 0 , IAA 150 and IAA 300 , respectively) and three N fertilization rates (240, 290, and 340 kg N ha − 1 , abbreviated as N 240 , N 290 and N 340 , respectively) on sugar beet’s growth, nutritional status, and quality and sugar quality in saline soil was explored. Results Findings exhibited that IAA 300 × N 340 was the best combination for enhancing root diameter, leaf fresh weight, and leaf area index. Ionic homeostasis, expressed as the leaf K⁺/Na⁺ and Ca²⁺/Na⁺ ratios, reached its highest values with N 340 (1.21 and 0.51, respectively), exceeding those observed with N 240 and N 290 . The IAA 0 or IAA 150 × N 340 gave the highest juice sodium content (34.0 and 33.8 mmol kg⁻¹, respectively), while N 240 across all IAA treatments recorded the lowest ones. The IAA 300 × N 340 was the most effective practice for enhancing yields and N use efficiency in sugar beet, resulting in the highest root yield (97.6 t ha⁻¹), pure sugar yield (14.50 t ha⁻¹), and N use efficiency (0.342 kg root kg⁻¹ N), significantly outperforming other IAA × N interactions. Conclusion In conclusion, progressive increases in IAA and N caused the enhancements sugar beet growth, yield, and related quality, since IAA at 300 mg L − 1 plus N at 340 kg N ha − 1 had the favorable synergism in this respect.

Phenotyping of crops is important due to increasing pressure on food production. Therefore, an accurate estimation of biomass during the growing season can be important to optimize the yield. The potential of data acquisition by UAV-LiDAR to estimate fresh biomass and crop height was investigated for three different crops (potato, sugar beet, and winter wheat) grown in Wageningen (The Netherlands) from June to August 2018. Biomass was estimated using the 3DPI algorithm, while crop height was estimated using the mean height of a variable number of highest points for each m2. The 3DPI algorithm proved to estimate biomass well for sugar beet (R2 = 0.68, RMSE = 17.47 g/m2) and winter wheat (R2 = 0.82, RMSE = 13.94 g/m2). Also, the height estimates worked well for sugar beet (R2 = 0.70, RMSE = 7.4 cm) and wheat (R2 = 0.78, RMSE = 3.4 cm). However, for potato both plant height (R2 = 0.50, RMSE = 12 cm) and biomass estimation (R2 = 0.24, RMSE = 22.09 g/m2), it proved to be less reliable due to the complex canopy structure and the ridges on which potatoes are grown. In general, for accurate biomass and crop height estimates using those algorithms, the flight conditions (altitude, speed, location of flight lines) should be comparable to the settings for which the models are calibrated since changing conditions do influence the estimated biomass and crop height strongly.

Cercospora leaf spot, caused by the fungal pathogen Cercospora beticola, is the most destructive foliar disease of sugar beet worldwide. This review discusses C. beticola genetics, genomics, and biology and summarizes our current understanding of the molecular interactions that occur between C. beticola and its sugar beet host. We highlight the known virulence arsenal of C. beticola as well as its ability to overcome currently used disease management strategies. Finally, we discuss future prospects for the study and management of C. beticola infections in the context of newly employed molecular tools to uncover additional information regarding the biology of this pathogen. Taxonomy Cercospora beticola Sacc.; Kingdom Fungi, Phylum Ascomycota, Class Dothideomycetes, Order Capnodiales, Family Mycosphaerellaceae, Genus Cercospora. Host range Well‐known pathogen of sugar beet (Beta vulgaris subsp. vulgaris) and most species of the Beta genus. Reported as pathogenic on other members of the Chenopodiaceae (e.g., lamb's quarters, spinach) as well as members of the Acanthaceae (e.g., bear's breeches), Apiaceae (e.g., Apium), Asteraceae (e.g., chrysanthemum, lettuce, safflower), Brassicaceae (e.g., wild mustard), Malvaceae (e.g., Malva), Plumbaginaceae (e.g., Limonium), and Polygonaceae (e.g., broad‐leaved dock) families. Disease symptoms Leaves infected with C. beticola exhibit circular lesions that are coloured tan to grey in the centre and are often delimited by tan‐brown to reddish‐purple rings. As disease progresses, spots can coalesce to form larger necrotic areas, causing severely infected leaves to wither and die. At the centre of these spots are black spore‐bearing structures (pseudostromata). Older leaves often show symptoms first and younger leaves become infected as the disease progresses. Management Application of a mixture of fungicides with different modes of action is currently performed although elevated resistance has been documented in most employed fungicide classes. Breeding for high‐yielding cultivars with improved host resistance is an ongoing effort and prudent cultural practices, such as crop rotation, weed host management, and cultivation to reduce infested residue levels, are widely used to manage disease. Useful website https://www.ncbi.nlm.nih.gov/genome/11237?genome_assembly_id=352037 The hemibiotrophic fungus Cercospora beticola applies various virulence strategies to infect sugar beet and is currently only managed in‐field through integrated practices.