Search Results (19)

Conventional spring sowing of sugar beet in Europe faces increasing constraints from summer drought, high temperatures, and Cercospora beticola pressure due to climate change. This two-year field trial (2021–2022 and 2022–2023) evaluated the feasibility of autumn-sown sugar beet at a northern Mediterranean site in Legnaro (Padua, NE Italy, 45°21′ N). Nine varieties were assessed across four sowing dates in 2021 (late September to early November) and two sowing dates in 2022 (late September and late October). Measurements included overwinter survival, bolting incidence at two reproductive stages, fresh root and above-ground biomass yield at sequential harvest dates, and root soluble solids (°Brix). Post-winter mortality was negligible following September and early-October sowings, moderate after late-October sowings (17.3% in 2021; 13.2% in 2022), and extremely high after early-November sowing (81.5%). These patterns indicated that winter survival was more strongly determined by crop developmental stage before winter than by seasonal minimal temperatures recorded in two seasons (−3.6 °C and −6.3 °C, respectively). Bolting incidence showed the opposite trend, reaching near-complete or complete expression in the earliest sowings regardless of variety choice. In late-October sowings, clear varietal differences emerged. Some varieties combined low bolting incidence with high root yields, reaching 81.1–84.4 t ha⁻¹ at the final harvest (early August 2023). Root juice soluble solids were higher in the drier 2021–2022 season (exceeding 20 °Brix in several cases) than in the wetter 2022–2023 season (consistently below 17.5 °Brix), reflecting dilution effects associated with the different seasonal precipitation. In the sequential harvest series of late-October 2022 sowing, later harvest dates were generally associated with lower soluble solids. These results indicate that, within the autumn sowing window evaluated, late-October sowing combined with appropriate varietal selection provided the best balance between overwinter survival, bolting incidence, and root yield at this northern Mediterranean latitude. Future multi-site studies, including spring-sown controls, could enable direct comparison with conventional sowing practice. Full article

Sugar beet cercospora leaf spot (CLS), caused by the fungus Cercospora beticola, is among the most economically important diseases of sugar beet, and the effectiveness of chemical disease management depends on the susceptibility of pathogen populations to fungicides. In this study, isolates of C. beticola from the Russian Federation were characterized based on QoI resistance, molecular detection of the G143A mutation, and phenotypic variability in radial growth, colony morphology, and aggressiveness. A total of 46 leaf samples were surveyed, and 196 isolates were obtained, from which a representative subset of 48 isolates was selected for detailed analysis. The selected isolates were characterized for in vitro radial growth and colony morphology, assessed for aggressiveness on sugar beet leaves, and tested for sensitivity to azoxystrobin based on EC50 values. The G143A mutation was detected by allele-discriminating real-time PCR and confirmed by sequencing of the cytB region. The G143A mutation was identified in 41 of 48 isolates (85.4%). In the mycelial bioassay, all isolates had EC50 values above 0.2 µg/mL, and 38 of 48 isolates (79.2%) had EC50 values exceeding 100 µg/mL. Additional validation with SHAM in a subset of 35 isolates did not alter the qualitative interpretation of resistance. Considerable variability was also observed in radial growth rate, aggressiveness, and colony appearance among isolates. These findings indicate widespread QoI resistance in the analyzed Russian isolate collection and provide a structured baseline for regional resistance monitoring and for more cautious use of FRAC 11 fungicides in integrated sugar beet disease-management programs. Full article

The use of plant protection products (PPPs) is the main method of controlling Cercospora leaf spot (CLS), as it constitutes a cheap and effective approach that is easy for farmers to follow. Unfortunately, it is widely recognized that the use of PPPs poses a risk not only to the environment but also to human health. The urgent need for sustainable development, recommended by the European Union and expressed in the “Farm to Fork Strategy”, includes a serious restriction on the use of PPPs. This strategy assumes a 50% reduction in the use of PPPs by 2030. These efforts have driven the exploration of innovative and effective plant protection strategies utilizing new active compounds. The examined substance, N-methyl-N-methoxyamide-7-carboxybenzo(1.2.3)thiadiazole (BTHWA), is a novel amide derivative of benzothiadiazole with the ability to induce systemic acquired resistance (SAR). This work presents a series of experiments conducted in the process of determining the appropriate technology for BTHWA use and proving its effectiveness in controlling CLS in sugar beet cultivation. It has been demonstrated that the application of treatments using BTHWA or BTHWA combined with a fungicide in a reduced number of treatments had the same effect on the reduction of plant infection with C. beticola and obtained root and technological sugar yields the same as those that resulted from the use of a full fungicidal treatment. The results provide grounds for reducing the use of fungicides by showing that the same effects can be attained by combining or replacing them with BTHWA. Full article

The length of incubation period, i.e., the time between first contact of host and pathogen and the appearance of symptoms, varies among diseases and depends on environmental conditions. Cercospora beticola is the most important fungal pathogen in sugar beet production worldwide, as Cercospora leaf spot (CLS) reduces the leaf area contributing to yield formation. Using sugar beet cultivars differing in CLS resistance, a single infection period of C. beticola resulted in minor differences in the incubation period among host genotypes and among individual plants of cultivars, greater differences among leaves within plants, and substantial variation within individual leaves. Under greenhouse conditions not suitable for secondary infections, the first CLS lesions appeared 10 days after inoculation; however, the number of leaf spots and CLS severity further increased significantly for another 7 to 17 days. A geographic information system approach enabled the tracking of colony appearance and growth of all CLSs on inoculated leaves for up to 27 days. Asymptomatic colonization of leaves was associated with thick hyphae which switched to thin hyphae or melanization after lesion appearance. The lifestyle of C. beticola—intercellular tissue colonization, triggering of necrotic host reaction—is discussed considering the experimental results as well as literature resources. Full article

Studies were initiated to find new effective fungicides to use under field conditions to discover novel approaches for optimizing disease management in sugar beet crops. Cercospora leaf spot (CLS), a prevalent foliar disease in sugar beet crops worldwide, is caused by the fungal pathogen Cercospora beticola Sacc. This disease has become the most prevalent pathogen in sugar beet crops across nearly all European growing regions, including Hungary. The epidemic spread of this disease can cause up to 50% yield loss. The use of fungicides has been a cornerstone in managing CLS of sugar beet due to the limited efficacy of non-chemical alternatives. However, the emergence of fungicide-resistant strains of Cercospora beticola Sacc. in recent decades has compromised the effectiveness of certain fungicides, particularly those belonging to the QoI (FRAC Group 11) and DMI (FRAC Group 3) classes. Hungary is among the many countries where resistance to these fungicides has developed due to their frequent application. Picolinamides represent a novel class of fungal respiration inhibitors targeting Complex III within the Quinoine-Inside Inhibitor (QiI) group. Two innovative fungicides from this class, fenpicoxamid and florylpicoxamid (both classified under FRAC Group 21), were evaluated for their efficacy in managing CLS of sugar beet in Hungary during the 2020 and 2021 growing seasons. Both fungicides were applied as formulated products at various application rates and demonstrated superior efficacy in controlling CLS compared to untreated control plots and the reference fungicides difenoconazole and epoxiconazole. The results consistently demonstrated that all tested application rates of fenpicoxamid and florylpicoxamid effectively controlled CLS in sugar beet, exhibiting a clear dose–response relationship. Disease severity, as measured by the area under the disease progress curve (AUDPC), was significantly correlated with yield reduction but showed no significant association with root sugar content. Moreover, data from both study years indicated that picolinamide fungicides applied at a rate of 75 g ai/ha significantly outperformed difenoconazole (100 g ai/ha) in controlling the CLS of sugar beet. Additionally, higher application rates of picolinamides at 100–150 g ai/ha outperformed epoxiconazole at 125 g ai/ha in disease suppression. Fenpicoxamid is currently registered for use in cereals within Europe, and outside of Europe in Banana against Black Sigatoka (eff. Mycosphaerella fijiensis). Florylpicoxamid, while not yet registered in Europe, is undergoing approval processes in various countries worldwide for a range of crops and is continually being evaluated for potential market introduction. Additional details regarding the efficacy of florylpicoxamid against CLS in sugar beet were presented at ‘The 10th International Conference on Agricultural and Biological Sciences (ABS 2024, Győr-Hungary)’ in 2024. Full article

Decreasing efficacy of fungicides and the withdrawal of further hazardous active ingredients in pesticides from use have prompted the search for alternative methods of crop protection. Essential oils (EOs) are secondary metabolites of plants and have been proven to show antibacterial, antifungal, and pest-repellent properties. This study was undertaken to determine the activity of grapefruit, rosemary, pine, sage, and thyme EOs against the fungus Cercospora beticola, which is the most dangerous pathogen of sugar beet and the causal agent of Cercospora leaf spot. According to the determined Minimum Inhibitory Concentration (MIC), thyme EO was found the most effective against C. beticola. For most of the fungal isolates tested, the MIC of this EO was 0.313 mL/L. Thyme EO also inhibited the growth of multi-resistant isolates. Based on the results obtained, thyme EO was subjected to further testing in field conditions, where its efficiency in controlling C. beticola was also proven. The results indicate that the use of thyme EO may be a promising method for the protection of sugar beets, although it requires further optimization in the context of its inclusion in sustainable protection programs assuming a reduced number of synthetic fungicide treatments. Full article

Phytopathogenic fungi are living organisms that cause plant diseases and great damage to agricultural products. Despite the wide range of commercial fungicide products in use, there is a clear need for new and environmentally friendly fungicides. Here we propose a new ecological fungicide, copper alginate microspheres prepared by ionic gelation. The microspheres were characterized (morphology and topography, encapsulation efficiency, loading capacity, swelling behavior, rheology, kinetics and mechanism of copper ions release) and their in vitro antifungal potential against selected genera of phytopathogenic fungi was evaluated. Copper alginate microspheres inhibited spore germination of Botrytis cinerea. Compared to the control, the inhibition of B. cinerea spore germination (48%) was greater than that of the commercial fungicide Neoram^® (22%). The mycelial growth of Cercospora beticola and Phytophthora ramorum was also significantly inhibited by the addition of copper alginate microspheres. Novel fungicide offer effective disease control while minimizing environmental impact and promoting sustainable agriculture practices. Full article

Cercospora beticola Sacc. is an ascomycete pathogen that causes Cercospora leaf spot in sugar beets (Beta vulgaris L.) and other related crops. It can lead to significant yield losses if not effectively managed. This study aimed to assess rhizosphere bacteria from sugar beet soil as a biological control agent against C. beticola and evaluate their effect on B. vulgaris. Following a dual-culture screening, 18 bacteria exhibiting over 50% inhibition were selected, with 6 of them demonstrating more than 80% control. The bacteria were identified by sequencing the 16S rRNA gene, revealing 12 potential species belonging to 6 genera, including Bacillus, which was represented by 4 species. Additionally, the biochemical and molecular properties of the bacteria were characterized in depth, as well as plant growth promotion. PCR analysis of the genes responsible for producing antifungal metabolites revealed that 83%, 78%, 89%, and 56% of the selected bacteria possessed bacillomycin-, iturin-, fengycin-, and surfactin-encoding genes, respectively. Infrared spectroscopy analysis confirmed the presence of a lipopeptide structure in the bacterial supernatant filtrate. Subsequently, the bacteria were assessed for their effect on sugar beet plants in controlled conditions. The bacteria exhibited notable capabilities, promoting growth in both roots and shoots, resulting in significant increases in root length and weight and shoot length. A field experiment with four bacterial candidates demonstrated good performance against C. beticola compared to the difenoconazole fungicide. These bacteria played a significant role in disease control, achieving a maximum efficacy of 77.42%, slightly below the 88.51% efficacy attained with difenoconazole. Additional field trials are necessary to verify the protective and growth-promoting effects of these candidates, whether applied individually, combined in consortia, or integrated with chemical inputs in sugar beet crop production. Full article

Isolates of a variety of fungal plant pathogens (Alternaria radicina ICMP 5619, Cercospora beticola ICMP 15907, Dactylonectria macrodidyma ICMP 16789, D. torresensis ICMP 20542, Ilyonectria europaea ICMP 16794, and I. liriodendra ICMP 16795) were screened for antimicrobial activity against the human pathogenic bacteria Acinetobacter baumannii, Pseudomonas aeruginosa, Escherichia coli, Mycobacterium abscessus, and M. marinum and were found to have some activity. Investigation of the secondary metabolites of these fungal isolates led to the isolation of ten natural products (1–10) of which one was novel, (E)-4,7-dihydroxyoct-2-enoic acid (1). Structure elucidation of all natural products was achieved by a combination of NMR spectroscopy and mass spectrometry. We also investigated the antimicrobial activity of a number of the isolated natural products. While we did not find (E)-4,7-dihydroxyoct-2-enoic acid (1) to have any activity against the bacteria and fungi in our assays, we did find that cercosporin (7) exhibited potent activity against Methicillin resistant Staphylococcus aureus (MRSA), dehydro-curvularin (6) and radicicol (10) exhibited antimycobacterial activity against M. marinum, and brefeldin A (8) and radicicol (10) exhibited antifungal activity against Candida albicans. Investigation of the cytotoxicity and haemolytic activities of these natural products (6–8 and 10) found that only one of the four active compounds, radicicol (10), was non-cytotoxic and non-haemolytic. Full article

The majority of all fungal formulations contain Trichoderma spp., making them effective biological control agents for agriculture. Chitosan, one of the most effective natural biopolymers, was also reported as a plant resistance enhancer and as a biocide against a variety of plant pathogens. An in vitro three-way interaction assay of T. atroviride, chitosan, and important plant pathogens (such as Cercospora beticola and Fusarium oxysporum) revealed a synergistic effect on fungistasis. Furthermore, chitosan coating on Beta vulgaris ssp. vulgaris seeds positively affected the onset and efficiency of germination. We show that priming with T. atroviride spores or chitosan leads to the induced expression of a pathogenesis-related gene (PR-3), but only supplementation of chitosan led to significant upregulation of phytoalexin synthesis (PAL) and oxidative stress-related genes (GST) as a defense response. Repeated foliar application of either agent promoted growth, triggered defense reactions, and reduced incidence of Cercospora leaf spot (CLS) disease in B. vulgaris. Our data suggest that both agents are excellent candidates to replace or assist common fungicides in use. Chitosan triggered the systemic resistance and had a biocidal effect, while T. atroviride mainly induced stress-related defense genes in B. vulgaris. We assume that both agents act synergistically across different signaling pathways, which could be of high relevance for their combinatorial and thus beneficial application on field. Full article

Cercospora leaf spots (CLSs) is a fungal disease of sugar beet caused by C. beticola, which damages leaves and leads to yield cut on sugar beet worldwide. BTB protein genes are critical to plant defense against bacterial infection. Here, 49 members of the BTB protein gene family were identified from the big data of the sugar beet genome, and bioinformatics was used to analyze the BTB protein family. Through molecular techniques, C. beticola of CLS was identified. In addition, the transcriptome data of sugar beet resistant and susceptible materials after C. beticola infection were obtained. Three BTB genes most significantly related to C. beticola stress were screened from the transcriptome data. The three genes are BvBTB1, BvBTB2, and BvBTB3, their full-length cDNA sequences were acquired by RT-PCR. The phenotypes of sugar beet resistant and susceptible materials under different spore concentrations of C. beticola were analyzed. Further, under the stress of C. beticola, qRT-PCR results showed that the expression levels of BvBTB1, BvBTB2, and BvBTB3 in roots and leaves were tissue-specific and expressed differently in various tissues. BvBTB1, BvBTB2, and BvBTB3 were overexpressed in the resistant and susceptible materials within five days after C. beticola infection: the peak appeared on the fifth day, and the highest expression was 25 times that of the control group. However, the lowest was 1.1 times of the control group, moreover, the expression in the resistant material was higher than that in the susceptible material. Overall, these results showed that BvBTB genes were involved in the response in sugar beet to C. beticola infection. Therefore, the study provided a scientific theoretical basis for developing new resistant varieties in sugar beet. Full article

Cercospora leaf spot (CLS), caused by the fungal pathogen Cercospora beticola, is the most important foliar pathogen of sugar beet worldwide. Extensive reliance on fungicides to manage CLS has resulted in the evolution of fungicide resistance in C. beticola worldwide, including populations in the Czech Republic. One important class of fungicides used to manage CLS is the sterol demethylation inhibitors (DMI). The aim of our study was to assess DMI resistance in C. beticola from the Czech Republic and elucidate the molecular basis of DMI resistance in this population. A total of 50 isolates were collected in 2018 and 2019 from the major sugar beet growing regions of the Czech Republic and assessed for in vitro sensitivity to the DMI fungicides propiconazole, prochloraz, and epoxiconazole. These analyses identified three strains that exhibited 50% effective concentration (EC₅₀) values > 1.0 μg mL^–1 against respective fungicides, which were therefore considered resistant. In contrast, strains that exhibited lowest EC₅₀ values were considered sensitive. To explore the molecular basis of resistance in these three strains, the cytochrome P450-dependent sterol 14α-demethylase (Cyp51) gene was sequenced. Sequence analysis identified a Y464S mutation in all three resistant strains. To assess whether Cyp51 gene expression may play a role in DMI resistance, selected strains were grown in vitro with and without fungicide treatment. These analyses indicated that Cyp51 gene expression was significantly induced after fungicide treatment. Thus, we conclude that Y464S point mutation along with induced Cyp51 gene overexpression is likely responsible for resistance against DMI fungicides in C. beticola from the Czech Republic. Full article

Cercospora leaf spot (CLS) caused by Cercospora beticola is a devastating foliar disease of sugar beet (Beta vulgaris), resulting in high yield losses worldwide. Mycoviruses are widespread fungi viruses and can be used as a potential biocontrol agent for fugal disease management. To determine the presence of mycoviruses in C. beticola, high-throughput sequencing analysis was used to determine the diversity of mycoviruses in 139 C. beticola isolates collected from major sugar beet production areas in China. The high-throughput sequencing reads were assembled and searched against the NCBI database using BLASTn and BLASTx. The results showed that the obtained 93 contigs were derived from eight novel mycoviruses, which were grouped into 3 distinct lineages, belonging to the families Hypoviridae, Narnaviridae and Botourmiaviridae, as well as some unclassified (−)ssRNA viruses in the order Bunyavirales and Mononegavirales. To the best of our knowledge, this is the first identification of highly diverse mycoviruses in C. beticola. The novel mycoviruses explored in this study will provide new viral materials to biocontrol Cercospora diseases. Future studies of these mycoviruses will aim to assess the roles of each mycovirus in biological function of C. beticola in the future. Full article

Cercospora leaf spot (CLS; caused by Cercospora beticola Sacc.) is the most widespread and damaging foliar disease of sugar beet. Early assessments of CLS risk are thus pivotal to the success of disease management and farm profitability. In this study, we propose a weather-based modelling approach for predicting infection by C. beticola in sugar beet fields in Belgium. Based on reported weather conditions favoring CLS epidemics and the climate patterns across Belgian sugar beet-growing regions during the critical infection period (June to August), optimum weather conditions conducive to CLS were first identified. Subsequently, 14 models differing according to the combined thresholds of air temperature (T), relative humidity (RH), and rainfall (R) being met simultaneously over uninterrupted hours were evaluated using data collected during the 2018 to 2020 cropping seasons at 13 different sites. Individual model performance was based on the probability of detection (POD), the critical success index (CSI), and the false alarm ratio (FAR). Three models (i.e., M1, M2 and M3) were outstanding in the testing phase of all models. They exhibited similar performance in predicting CLS infection events at the study sites in the independent validation phase; in most cases, the POD, CSI, and FAR values were ≥84%, ≥78%, and ≤15%, respectively. Thus, a combination of uninterrupted rainy conditions during the four hours preceding a likely start of an infection event, RH > 90% during the first four hours and RH > 60% during the following 9 h, daytime T > 16 °C and nighttime T > 10 °C, were the most conducive to CLS development. Integrating such weather-based models within a decision support tool determining fungicide spray application can be a sound basis to protect sugar beet plants against C. beticola, while ensuring fungicides are applied only when needed throughout the season. Full article

Plant diseases can impact crop yield. Thus, the detection of plant diseases using sensors that can be mounted on aerial vehicles is in the interest of farmers to support decision-making in integrated pest management and to breeders for selecting tolerant or resistant genotypes. This paper investigated the detection of Cercospora leaf spot (CLS), caused by Cercospora beticola in sugar beet using RGB imagery. We proposed an approach to tackle the CLS detection problem using fully convolutional neural networks, which operate directly on RGB images captured by a UAV. This efficient approach does not require complex multi- or hyper-spectral sensors, but provides reliable results and high sensitivity. We provided a detection pipeline for pixel-wise semantic segmentation of CLS symptoms, healthy vegetation, and background so that our approach can automatically quantify the grade of infestation. We thoroughly evaluated our system using multiple UAV datasets recorded from different sugar beet trial fields. The dataset consisted of a training and a test dataset and originated from different fields. We used it to evaluate our approach under realistic conditions and analyzed its generalization capabilities to unseen environments. The obtained results correlated to visual estimation by human experts significantly. The presented study underlined the potential of high-resolution RGB imaging and convolutional neural networks for plant disease detection under field conditions. The demonstrated procedure is particularly interesting for applications under practical conditions, as no complex and cost-intensive measuring system is required. Full article