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Sugarbeets account for 55 to 60% of U.S. sugar production. Cercospora leaf spot (CLS), primarily caused by the fungal pathogen , is a major foliar disease of sugarbeet. Since leaf tissue is a primary site of pathogen survival between growing seasons, this study evaluated management strategies to reduce this source of inoculum. Fall- and spring-applied treatments were evaluated over three years at two study sites. Treatments included standard plowing or tilling immediately post-harvest, as well as the following alternatives to tillage: a propane-fueled heat treatment either in the fall immediately pre-harvest or in the spring prior to planting, and a desiccant (saflufenacil) application seven days pre-harvest. After fall treatments, leaf samples were evaluated to determine viability. The following season, inoculum pressure was measured by monitoring CLS severity in a susceptible beet variety planted into the same plots and by counting lesions on highly susceptible sentinel beets placed into the field at weekly intervals (fall treatments only). No significant reductions in survival or CLS were observed following fall-applied desiccant. The fall heat treatment, however, significantly reduced lesion sporulation (2019-20 and 2020-21, < 0.0001; 2021-22, < 0.05) and isolation (2019-20, < 0.05) in at-harvest samples. Fall heat treatments also significantly reduced detectable sporulation for up to 70- (2021-22, < 0.01) or 90-days post-harvest (2020-21, < 0.05). Reduced numbers of CLS lesions were observed on sentinel beets in heat-treated plots from May 26-June 2 ( < 0.05) and June 2-9 ( < 0.01) in 2019, as well as June 15-22 ( < 0.01) in 2020. Both fall- and spring-applied heat treatments also reduced the area under the disease progress curve for CLS assessed the season after treatments were applied (Michigan 2020 and 2021, < 0.05; Minnesota 2019, < 0.05; 2021, < 0.0001). Overall, heat treatments resulted in CLS reductions at levels comparable to standard tillage, with more consistent reductions across year and location. Based on these results, heat treatment of fresh or overwintered leaf tissue could be used as an integrated tillage-alternative practice to aid in CLS management.

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.

Silicon (Si) can mitigate the deleterious impacts of various types of stresses on field crops. However, the potential of nano-silicon (nano-Si) in improving water stress and the relevant mechanisms remain unclear. Therefore, here, we examined the combined impacts of nano-Si and various irrigation regimes on antioxidant systems, osmolytes, photosynthesis-related parameters, and growth of sugar beet in a field trial. Treatments included three supplemental irrigation rates ( I 1 , I 2 , and I 3 ) arranged based on the crop evapotranspiration (100% ET C , 75% ET C , and 50% ET C ) and three doses of nano-Si: 0, 1, and 2 mM. Irrigation regime treatments were performed at the six-to eight-leaf stage (49 days after sowing), which continued until the harvest (180 days after sowing). Water stress brought about a detrimental impact on the sugar beet growth, the relative water content of leaves (LRWC), leaf area index (LAI), and photosynthetic performance. In contrast, Water deficiency enhanced hydrogen peroxide (H 2 O 2 ) and malondialdehyde (MDA) contents, which were followed by increasing antioxidant activities and osmolytes. Supplementation of nano-Si at low dose (1 mM) significantly increased chlorophyll contents, net photosynthesis (PN), glycine betaine (GB), flavonols (quercetin and rutin), and enzymatic antioxidants (superoxide dismutase, catalase, and guaiacol peroxidase). Furthermore, nano-Si at low dose (1 mM) decreased the amount of H 2 O 2 and MDA. Instead, the higher dose (2 mM) of nano-Si exerted toxic effects on severe water-stressed (50% ET C ) plants. The parallel increase in MDA and proline contents in sugar beet plants treated with two mM nano-Si along with severe water stress supports the view that proline augmentation presumably is a sign of stress injury instead of stress resistance. Overall, our results imply that nano-Si can play a protecting role in sugar beet plants during water stress by enhancing antioxidants, GB, and flavonols (quercetin and rutin). However, the concentration of nano-Si must be chosen with care.

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.

In this study, an analysis of scientific and technical literature was conducted to determine the norms of natural waste of raw materials in the sugar industry and products of their processing during storage in the Republic of Kazakhstan. The analysis showed the absence of regulatory documentation in this direction, and the available documentation on the norms of natural waste of raw materials in the sugar industry and products of their processing during storage was approved more than 30 years ago, during the Soviet Union. The study showed the structure of the gross harvest of sugar beet in Kazakhstan, the stages of the production cycle of beet sugar production and the products in which standardized indicators will be determined, as well as standardized indicators for the products of sugar beet processing at each stage of the production cycle of beet sugar production. These studies showed a loss of sugar beet mass during storage. In addition, according to the results of the studies, it was revealed that average daily losses ranged from 0.07 to 1.28% of sugar beet mass during storage for 60 days. The average daily indicator is 0.592% by mass of stored beets.

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.

Herein, the first trial to investigate the possibility of using one type of sugar beet waste, named carbonation lime residue after calcination (CCR), as an additive for alkali-activated slag (AAS) cement was explored. For this reason, typical AAS cement was prepared, then slag was partially replaced with CCR at levels ranging from 2.5 to 15% by weight. To explore the effect of CCR on the properties of AAS pastes, typical traditional tests such as flowability, setting time, and compressive strength at various ages were measured. In addition, different types of durability such as accelerated aging, water-air cycles, water-hot air cycles, HCl attack, and cyclic wetting in 5% [Na.sub.2][SO.sub.4] and drying at 80[degrees]C (176[degrees]F) were explored. The results were analyzed with different advanced devices. The results showed that it is possible to use CCR as an additive, similar to CaO, for AAS cement. The flowability and setting time decreased with the inclusion of CCR. The inclusion of 5% CCR in AAS cement was the optimal content, which proved the best compressive strength, microstructure, and durability. On the contrary, the inclusion of 15% CCR showed a negative effect. The pronounced outcomes of this investigation may be the solution for sugar beet waste landfills and improving the properties of AAS cement. Keywords: alkali-activated slag; compressive strength; durability; setting time; sugar beet waste; workability.

Background Convolvulus sepium (hedge bindweed) detection in sugar beet fields remains a challenging problem due to variation in appearance of plants, illumination changes, foliage occlusions, and different growth stages under field conditions. Current approaches for weed and crop recognition, segmentation and detection rely predominantly on conventional machine-learning techniques that require a large set of hand-crafted features for modelling. These might fail to generalize over different fields and environments. Results Here, we present an approach that develops a deep convolutional neural network (CNN) based on the tiny YOLOv3 architecture for C. sepium and sugar beet detection. We generated 2271 synthetic images, before combining these images with 452 field images to train the developed model. YOLO anchor box sizes were calculated from the training dataset using a k-means clustering approach. The resulting model was tested on 100 field images, showing that the combination of synthetic and original field images to train the developed model could improve the mean average precision (mAP) metric from 0.751 to 0.829 compared to using collected field images alone. We also compared the performance of the developed model with the YOLOv3 and Tiny YOLO models. The developed model achieved a better trade-off between accuracy and speed. Specifically, the average precisions (APs@IoU0.5) of C. sepium and sugar beet were 0.761 and 0.897 respectively with 6.48 ms inference time per image (800 × 1200) on a NVIDIA Titan X GPU environment. Conclusion The developed model has the potential to be deployed on an embedded mobile platform like the Jetson TX for online weed detection and management due to its high-speed inference. It is recommendable to use synthetic images and empirical field images together in training stage to improve the performance of models.

Main conclusionAlthough sugar beet is a salt- and drought-tolerant crop, high salinity, and water deprivation significantly reduce its yield and growth. Several reports have demonstrated stress tolerance enhancement through stress-mitigating strategies including the exogenous application of osmolytes or metabolites, nanoparticles, seed treatments, breeding salt/drought-tolerant varieties. These approaches would assist in achieving sustainable yields despite global climatic changes.Sugar beet (Beta vulgaris L.) is an economically vital crop for ~ 30% of world sugar production. They also provide essential raw materials for bioethanol, animal fodder, pulp, pectin, and functional food-related industries. Due to fewer irrigation water requirements and shorter regeneration time than sugarcane, beet cultivation is spreading to subtropical climates from temperate climates. However, beet varieties from different geographical locations display different stress tolerance levels. Although sugar beet can endure moderate exposure to various abiotic stresses, including high salinity and drought, prolonged exposure to salt and drought stress causes a significant decrease in crop yield and production. Hence, plant biologists and agronomists have devised several strategies to mitigate the stress-induced damage to sugar beet cultivation. Recently, several studies substantiated that the exogenous application of osmolytes or metabolite substances can help plants overcome injuries induced by salt or drought stress. Furthermore, these compounds likely elicit different physio-biochemical impacts, including improving nutrient/ionic homeostasis, photosynthetic efficiency, strengthening defense response, and water status improvement under various abiotic stress conditions. In the current review, we compiled different stress-mitigating agricultural strategies, prospects, and future experiments that can secure sustainable yields for sugar beets despite high saline or drought conditions.

Soil salinity adversely affects the growth, yield, and quality parameters of sugar beet, leading to a reduction in root and sugar yields. Improving the physical and chemical properties of salt-affected soils is essential for sustainable cultivation and sugar beet production. A field experiment was conducted at the Delta Sugar Company Research Farm, El-Hamool, Kafr El-Sheikh, Egypt, to evaluate the response of sugar beet to the application of beet sugar filter cake treated with sulfuric and phosphoric acid-treated, phosphogypsum (PG), desaline, humic acid, and molasses under saline soil conditions. The application of treated filter cake enhanced root length, diameter, and leaf area. The application of molasses enhanced root length, diameter, and leaf area as well. Application of molasses increased sugar content and root yield. The application of either treated filter cake or molasses produced the highest recoverable sugar yield. Linear regression analysis revealed that the root yield, quality index, and recoverable sugar yield increased in response to the increased availability of either Ca 2+ or K content in the soil which increases in response to the application of soil amendments and molasses. The application of treated beet sugar filter cake and molasses increased the calcium, magnesium, and potassium availability in the soil. Treated filter cake is a promising organic soil amendment that enhanced the yield by 29% and yield-related traits of sugar beet by improving the physical and chemical properties of the soil.