Isolation and Characterization of Bacillus velezensis Strain P2-1 for Biocontrol of Apple Postharvest Decay Caused by Botryosphaeria dothidea

Botryosphaeria dothidea causes apple ring rot, which is among the most prevalent postharvest diseases of apples and causes significant economic loss during storage. In this study, we investigated the biocontrol activity and possible mechanism of Bacillus velezensis strain P2-1 isolated from apple branches against B. dothidea in postharvest apple fruit. The results showed strain P2-1, one of the 80 different endophytic bacterial strains from apple branches, exhibited strong inhibitory effects against B. dothidea growth and resulted in hyphal deformity. B. velezensis P2-1 treatment significantly reduced the ring rot caused by B. dothidea. Additionally, the supernatant of strain P2-1 exhibited antifungal activity against B. dothidea. Re-isolation assay indicated the capability of strain P2-1 to colonize and survive in apple fruit. PCR and qRT-PCR assays revealed that strain P2-1 harbored the gene clusters required for biosynthesis of antifungal lipopeptides and polyketides. Strain P2-1 treatment significantly enhanced the expression levels of pathogenesis-related genes (MdPR1 and MdPR5) but did not significantly affect apple fruit qualities (measured in fruit firmness, titratable acid, ascorbic acid, and soluble sugar). Thus, our results suggest that B. velezensis strain P2-1 is a biocontrol agent against B. dothidea-induced apple postharvest decay. It acts partially by inhibiting mycelial growth of B. dothidea, secreting antifungal substances, and inducing apple defense responses.

Apple Leaf Disease Identification with a Small and Imbalanced Dataset Based on Lightweight Convolutional Networks

The intelligent identification and classification of plant diseases is an important research objective in agriculture. In this study, in order to realize the rapid and accurate identification of apple leaf disease, a new lightweight convolutional neural network RegNet was proposed. A series of comparative experiments had been conducted based on 2141 images of 5 apple leaf diseases (rust, scab, ring rot, panonychus ulmi, and healthy leaves) in the field environment. To assess the effectiveness of the RegNet model, a series of comparison experiments were conducted with state-of-the-art convolutional neural networks (CNN) such as ShuffleNet, EfficientNet-B0, MobileNetV3, and Vision Transformer. The results show that RegNet-Adam with a learning rate of 0.0001 obtained an average accuracy of 99.8% on the validation set and an overall accuracy of 99.23% on the test set, outperforming all other pre-trained models. In other words, the proposed method based on transfer learning established in this research can realize the rapid and accurate identification of apple leaf disease.

Diagnosis of Typical Apple Diseases: A Deep Learning Method Based on Multi-Scale Dense Classification Network

Disease has always been one of the main reasons for the decline of apple quality and yield, which directly harms the development of agricultural economy. Therefore, precise diagnosis of apple diseases and correct decision making are important measures to reduce agricultural losses and promote economic growth. In this paper, a novel Multi-scale Dense classification network is adopted to realize the diagnosis of 11 types of images, including healthy and diseased apple fruits and leaves. The diagnosis of different kinds of diseases and the same disease with different grades was accomplished. First of all, to solve the problem of insufficient images of anthracnose and ring rot, Cycle-GAN algorithm was applied to achieve dataset expansion on the basis of traditional image augmentation methods. Cycle-GAN learned the image characteristics of healthy apples and diseased apples to generate anthracnose and ring rot lesions on the surface of healthy apple fruits. The diseased apple images generated by Cycle-GAN were added to the training set, which improved the diagnosis performance compared with other traditional image augmentation methods. Subsequently, DenseNet and Multi-scale connection were adopted to establish two kinds of models, Multi-scale Dense Inception-V4 and Multi-scale Dense Inception-Resnet-V2, which facilitated the reuse of image features of the bottom layers in the classification neural networks. Both models accomplished the diagnosis of 11 different types of images. The classification accuracy was 94.31 and 94.74%, respectively, which exceeded DenseNet-121 network and reached the state-of-the-art level.

Chemical Disinfection of Potato Cutting Machinery to Avoid Dissemination of Clavibacter sepedonicus

A potential cause of the dissemination of the potato ring rot bacterium Clavibacter sepedonicus (Cs) is the use of automated seed potato cutters. The present study focuses on the question of whether disinfection practices are sufficient to prevent the transmission of Cs from contaminated machine parts to a new tuber lot. The disinfection efficacy was determined by establishing the culturability of Cs that remained after spray application of sodium-p-toluenesulfochloramide solution on clean and fouled specimens of machinery material that had been provided with an imprint of Cs biofilm. Although conventional spraying, with the authorized concentration of sodium-p-toluenesulfochloramide, of inoculated rubber, PVC and lacquered steel led to a substantial decrease of colony forming units, the treatment was insufficient for complete eradication of Cs. The presence of dirt negatively affected the efficacy of the disinfectant.

Influence of Forest Conditions on the Spread of Scots Pine Blister Rust and Red Ring Rot in the Priangarye Pine Stands

Scots pine blister rust and red ring rot are common on Scots pine throughout its entire range. Specialists do not explain a significant variation in the prevalence of the diseases uniquely since it depends on complex ecological and silvicultural factors. The aim of this research is to study the influence of forest growth conditions on the incidence of Scots pine blister rust and red ring rot in pine stands of the Priangarye (territory located along the lower reaches of the Angara within the Krasnoyarsk Krai). The research methods included a detailed forest pathological examination of prevailing pine forest types, specific symptom-based macroscopic diagnosis of the diseases, data analysis using parametric and non-parametric statistical tests. Forest growth conditions indicators included type of forest, habitat conditions, and bonitet class of forest stands. The incidence of Scots pine blister rust and red ring rot in pine forests of the Priangarye reaches the extent of moderate and severe damage, respectively. The prevalence of Scots pine blister rust is significantly higher in low-bonitet lichen pine forests; the incidence rate increases along the gradient of decreasing fertility and soil moisture level. The incidence of red ring rot is significantly higher in herb-rich pine forests, in gradations of maximum soil fertility and medium soil moisture. The revealed patterns are explained by the bioecological characteristic features of pathogens (for red ring rot—additionally by factors of structural immunity in pine trees). The results of the research should be recognized in the organization of forestry practice.

Complete Genome Sequence of a Novel Ourmia-like Mycovirus Infecting the Phytopathogenic Fungus Botryosphaeria Dothidea

In this study, we describe the full-length genome sequence of a novel ourmia-like mycovirus, tentatively designated Botryosphaeria dothidea ourmia-like virus 1 (BdOLV1), isolated from the phytopathogenic fungus, Botryosphaeria dothidea strain P8, associated with apple ring rot in Shanxi province, China. The complete BdOLV1 genome is comprised of 2797 nucleotides, a positive-sense (+) single-stranded RNA (ssRNA) with a single open reading frame (ORF). The ORF putatively encodes a 642-amino acid polypeptide with conserved RNA-dependent RNA polymerase (RdRp) motifs, related to viruses of the family Botourmiaviridae. Phylogenetic analysis based on the RdRp amino acid sequences showed that BdOLV1 is grouped with oomycete-infecting unclassified viruses closely related to the genus Botoulivirus in Botourmiaviridae. This is the first report of a novel (+)ssRNA virus in B. dothidea related to the genus Botoulivirus in the family Botourmiaviridae.

Selenium Nanocomposites in Natural Matrices as Potato Recovery Agent

The paper presents a study of the effect of chemically synthesized selenium nanocomposites (Se NCs) in natural polymer matrices arabinogalactan (AG) and starch (ST) on the viability of the potato ring rot pathogen Clavibacter sepedonicus (Cms), potato plants in vitro, and the soil bacterium Rhodococcus erythropolis. It was found that the studied Se NCs have an antibacterial effect against the phytopathogenic Cms, reducing its growth rate and ability to form biofilms. It was revealed that Se NC based on AG (Se/AG NC) stimulated the growth and development of potato plants in vitro as well as their root formation. At the same time, Se did not accumulate in potato tissues after the treatment of plants with Se NCs. The safety of the Se NCs was also confirmed by the absence of a negative effect on the growth and biofilm formation of the soil bacterium R. erythropolis. The obtained results indicate that Se NCs are promising environmentally safe agents for the protection and recovery of cultivated plants from phytopathogenic bacteria.

The Full-length Genome Sequence of a Novel Mitovirus From the Causal Agent Botrosphaeria Dothidea of Pear Ring Rot Disease

Here, we describe a novel mycovirus, Botryosphaeria dothidea mitovirus 2 (tentatively designated as BdMV2), isolated from Botryosphaeria dothidea FJ strain causing pear ring rot disease in Fujian Province, China. The complete genome nucleotide sequence of BdMV2 is 2538 nt in length and contains a single 2070 nt open reading frame (ORF) encoding a putative RNA-dependent RNA polymerase (RdRp) of 689 amino acid (aa) using fungal mitochondrial genetic code. BLASTp analysis revealed that the RdRp of BdMV2 shares 28.91%–69.36% (query sequence coverage more than 90%) sequence identity to those of members in the genus Mitovirus, and the closest similarity is 69.36% and 68.79% with the corresponding protein aa sequences of Rhizoctonia solani mitovirus 10 and Macrophomina phaseolina mitovirus 4, respectively. Phylogenetic analysis based on the RdRp aa sequences further revealed that BdMV2 is a newly member in the genus Mitovirus of the family Narnaviridae. To our knowledge, BdMV2 is thus a novel mitovirus from the causal agent B. dothidea of pear ring rot disease.