Search Results (26)

Colletotrichum fructicola is a member of the gloeosporioides complex and can act as a pathogen, causing anthracnose in various plants and as an endophyte residing in healthy plants. As a plant pathogen, C. fructicola has been frequently reported to cause anthracnose in chili fruit and tea plants, bitter rot in apples and pears, crown rot in strawberries, and Glomerella leaf spot in apples, which are the most common diseases associated with this pathogen. Over the years, C. fructicola has been reported to infect a wide range of plants in tropical, subtropical, and temperate regions, including various types of fruit crops, ornamental and medicinal plants, tree nuts, peanuts, and weeds. Several reports have also been made regarding endophytic C. fructicola recovered from different plant parts. Endophytic C. fructicola has the ability to switch to a pathogenic state, which may contribute to the infection of host and other susceptible plants. Due to the economic importance of C. fructicola infections, the present review highlighted C. fructicola as a plant pathogen and endophyte, providing a summary of its infections in various plants and endophytic ability to inhabit plant tissues. Several control measures for managing C. fructicola infections have also been provided. Full article

This study proposes an advanced plant disease classification framework leveraging the Attention Score-Based Multi-Vision Transformer (Multi-ViT) model. The framework introduces a novel attention mechanism to dynamically prioritize relevant features from multiple leaf images, overcoming the limitations of single-leaf-based diagnoses. Building on the Vision Transformer (ViT) architecture, the Multi-ViT model aggregates diverse feature representations by combining outputs from multiple ViTs, each capturing unique visual patterns. This approach allows for a holistic analysis of spatially distributed symptoms, crucial for accurately diagnosing diseases in trees. Extensive experiments conducted on apple, grape, and tomato leaf disease datasets demonstrate the model’s superior performance, achieving over 99% accuracy and significantly improving F1 scores compared to traditional methods such as ResNet, VGG, and MobileNet. These findings underscore the effectiveness of the proposed model for precise and reliable plant disease classification. Full article

Apple proliferation is among the most important diseases in European fruit production. Early and reliable detection enables farmers to respond appropriately and to prevent further spreading of the disease. Traditional phenotyping approaches by human observers consider multiple symptoms, but these are difficult to measure automatically in the field. Therefore, the potential of hyperspectral imaging in combination with data analysis by machine learning algorithms was investigated to detect the symptoms solely based on the spectral signature of collected leaf samples. In the growing seasons 2019 and 2020, a total of 1160 leaf samples were collected. Hyperspectral imaging with a dual camera setup in spectral bands from 400 nm to 2500 nm was accompanied with subsequent PCR analysis of the samples to provide reference data for the machine learning approaches. Data processing consists of preprocessing for segmentation of the leaf area, feature extraction, classification and subsequent analysis of relevance of spectral bands. The results show that imaging multiple leaves of a tree enhances detection results, that spectral indices are a robust means to detect the diseased trees, and that the potentials of the full spectral range can be exploited using machine learning approaches. Classification models like rRBF achieved an accuracy of 0.971 in a controlled environment with stratified data for a single variety. Combined models for multiple varieties from field test samples achieved classification accuracies of 0.731. Including spatial distribution of spectral data further improves the results to 0.751. Prediction of qPCR results by regression based on spectral data achieved RMSE of 14.491 phytoplasma per plant cell. Full article

In the present study, the most valuable cultivar ‘Aport krovavo-krasnyy’ was grafted onto M. sieversii genotypes harvested from 11 populations in Dzungarian Alatau and Ile Alatau to identify ones resistant to Erwinia amylovora. The wild apple populations included in the present research have not been previously explored. Seedling population 10, developed using rootstocks from a M. sieversii population growing in Turgen, demonstrated the highest resistance to Erwinia amylovora, showing no fire blight symptoms and no positive PCR results for E. amylovora during the eight years of monitoring in the Talgar field (Kazakhstan) from 2015 to 2022. The population from Steep Tract (seedling population 1) was also valuable for breeding and reduced the pathogen distribution to below 30%. Genotypes from a genetic reserve (seedling population 5) were the most susceptible among the researched populations, with a disease distribution level of 24–95%. In seedling population 5, trees affected at least twice by the pathogen exhibited wilting, shepherd’s crook formation, leaf necrosis, and occasional exudate droplets, while trees in other combinations primarily showed shoot wilting and leaf death. Fire blight disease also developed more rapidly within the plant in seedling population 5; by 2020, one tree nearly died after only two infections. Full article

Apple canker disease, also named as apple Valsa canker, is one of the most destructive diseases for apples (Malus domestica Borkh.). Cytospora/Valsa spp. are the dominant causal agent of this disease, but many studies have revealed that fungi from some other genus can also cause typical apple canker symptoms. In this study, we performed fungal pathogen isolation from cankered ‘Fuji’ apple barks. Six representative morphologically different fungi (Strain 1–6) were further subjected to ITS sequencing and evolutionary analysis. Molecular identification results revealed that Strains 1–6 are Cytospora mali, Fusarium cf. solani, Alternaria alternata, C. mali, Diplodia seriata and F. proliferatum, respectively. All these fungi have been reported to be causal agents of apple diseases. By inoculating fungal plugs onto trunks of ‘Fuji’ apple trees, the pathogenicity of the six fungi were accessed. Only the inoculations of the two C. mali strains (Strain 1 and Strain 4) and the A. alternata strain (Strain 3) resulted in typical apple canker symptoms in trunks. It is worth noting that Strain 1 caused much more severe canker symptoms and higher pathogenicity incidence than the other two fungi. A. alternata has been identified as a pathogen causing diseases on apple fruits and leaves. By further assessing its pathogenicity on apple fruits and leaves, we verified that it can also cause typical fruit rot and leaf spot symptoms. To the best of our knowledge, this is the first report on apple canker disease caused by A. alternata in China. Our present study can provide a theoretical foundation for the prevention and control of apple canker disease. Full article

Leaf spot, a major apple disease, manifests in diverse symptoms. In this study, the pathogen was isolated from diseased ‘Yanfu 3’ apple leaves in Yantai, Shandong Province, and identified as Neopestalotiopsis clavispora through morphological observation, molecular identification, and multi-gene (ITS, TEF1α, and TUB2) phylogenetic analysis. Three isolates (YTNK01, YTNK02, and YTNK03) were selected for pathogenicity tests to verify Koch’s postulates. To our knowledge, this is the first report of N. clavispora being responsible for apple leaf spots in China, and the disease has been named ‘apple Neopestalotiopsis leaf spot’. Additionally, N. clavispora was found to infect crabapple, sweet cherry, grape, peach, and pear under laboratory conditions, indicating that these fruit trees may be potential hosts for N. clavispora in the field. The in vitro toxicity of ten fungicides to the pathogen was assessed using the mycelial growth rate method. All ten fungicides were effective in inhibiting the growth of N. clavispora. Among them, those based on pylocyanonitrile, propiconazole, pyraclostrobin, tebuconazole, diphenoxazole, and osthole showed higher toxicity to N. clavispora, with EC₅₀ values of 0.11, 0.41, 0.47, 1.32, 1.85, and 3.82 µg/mL, respectively. These fungicides could be used as alternatives to prevent this disease in production. Overall, these findings provide valuable insights into the characteristics of N. clavispora causing apple leaf spot and are crucial for developing effective management strategies. Full article

Apple replant disease (ARD) may cause significant losses both in commercial orchards and in fruit tree nurseries. The negative effects of ARD may be limited by using biofumigation. The aim of the study was to assess the influence of this treatment on the biological properties of replanted soil in a tree nursery. In two-year experiment, apple trees of the ‘Golden Delicious’ cultivar were used. The trees were planted into soil from two sites. The soil from one site had not been used in a nursery before (crop rotation soil). The other soil had been used for the production of apple trees (replanted soil). Three species of plants were used in the replanted soil as a forecrop: French marigold (Tagetes patula), white mustard (Sinapis alba), and oilseed radish (Raphanus sativus var. oleifera). The following parameters were assessed in the experiment: the enzyme and respiratory activity of the soil, the total count of bacteria, fungi, oomycetes and actinobacteria in the soil, as well as the count and species composition of soil nematodes. The vegetative growth parameters of the apple trees were also assessed. The biological properties of the replanted soil were worse than those of the crop rotation soil. In the replanted soil, the organic matter content, enzyme and respiratory activity as well as the count of soil microorganisms were lower. The biofumigants, used as a forecrop on the replanted soil, significantly increased its enzyme activity and respiratory activity. Dehydrogenase activity increased more than twofold. Growth parameters of the trees were significantly improved. The height of the trees increased by more than 50%, and the leaf area, weight and total length of side shoots were higher as well. The density of nematodes in the replanted soil after biofumigation was significantly reduced, with a larger reduction in the marigold fumigated soil. Eight of the eleven nematode species were completely reduced in the first year after biofumigation treatment. Full article

As a fruit tree with great economic value, apple is widely cultivated in China. However, apple leaf spot disease causes significant damage to apple quality and economic value. In our study, we found that MdMYB6-like is a transcription factor without auto-activation activity and with three alternative spliced variants. Among them, MdMYB6-like-β responded positively to the pathogen infection. Overexpression of MdMYB6-like-β increased the lignin content of leaves and improved the pathogenic resistance of apple flesh callus. In addition, all three alternative spliced variants of MdMYB6-like could bind to the promoter of MdBGLU H. Therefore, we believe that MdMYB6-like plays an important role in the infection process of the pathogen and lays a solid foundation for breeding disease-resistant cultivars of apple in the future. Full article

Alternaria leaf blight has recently been described as an emerging fungal disease of apple trees which is causing the significant damage in the apple-growing areas of Tianshui and Jingning, Gansu, China. In the present study, the pathogen species involved in apple leaf blight and its biological characteristics were identified, and the inhibitory activity of different botanical fungicides against the pathogen was evaluated in vitro. Four strains were isolated from the symptomatic areas of necrotic apple leaves, and initially healthy leaves showed similar symptoms to those observed in orchards after inoculation with the ABL2 isolate. The ABL2 isolate was identified as Alternaria tenuissima based on the morphological characteristics of its colonies, conidiophores, and conidia, and this was also confirmed by multi-gene sequence (ITS, OPA10-2, Alta-1, and endoPG) analysis and phylogenic analysis. The optimum temperature, pH, carbon source, and nitrogen source for the growth of A. tenuissima mycelia were 28 °C, 6–7, soluble starch, and soy flour, respectively. In addition, the botanical fungicide eugenol exhibited the highest inhibitory effect on the mycelial growth and conidia germination of A. tenuissima, and the median effective concentration (EC₅₀) values were 0.826 and 0.755 μg/mL, respectively. The protective and curative efficacy of eugenol were 86.85% and 76.94% after inoculation in detached apple leaves at a concentration of 4 μg/mL. Our research provides new insights into the control of apple leaf blight disease by applying botanical fungicides. Full article

Apple proliferation (AP) is an economically important disease in many apple-growing regions caused by ‘Candidatus Phytoplasma mali’ which is spread by migrating psyllid vectors on a regional scale. As infected trees in orchards are the only inoculum source, the early eradication of those trees is one of the most efficient strategies to prevent further spread of AP. Remote sensing is a promising rapid and cost-effective tool to identify infected trees on a regional scale. AP-induced premature leaf reddening was evaluated as a reliable symptom for remote sensing by monitoring more than 20,000 trees in 68 different orchards with 20 representative cultivars from 2019 to 2022 in a highly AP-affected region in Southwest Germany. Specific AP symptoms were almost 100% correlated with molecular detection of ‘Ca. P. mali’ and these specific symptoms were almost 100% correlated with leaf reddening. ‘Ca. P. mali’ was detected in 71–97% of trees which showed partial or entire reddening without any other AP symptom. Experimental and field data showed that reddening was induced by cold night and warm day temperatures (about 5 °C vs. 20 °C) in September. Quantification of the phytoplasma by real-time PCR showed no correlation with the intensity of reddening in the leaf. PCR-RFLP subtyping revealed no influence of different ‘Ca. P. mali’ strains on the symptom expression. In conclusion, leaf reddening in late September/early October was a reliable symptom useful for remote sensing of AP. Full article

Apple foliar diseases are a group of diseases that affect the leaves of apple trees. These diseases can significantly impact apple tree health and fruit yield. Ordinary apple foliar diseases include frog_eye_leaf_spots, powdery mildew, rust, apple scabs, etc. Early detection of these diseases is important for effective apple crop management to increase the yield of apples. Therefore, this research proposes a fine-tuned EfficientNetB3 model for the quick and precise assessment of these apple foliar diseases. A dataset containing 23,187 RGB images of eleven different apple foliar diseases is used for experimentation. The proposed model is compared with four transfer learning models, i.e., InceptionResNetV2, ResNet50, AlexNet, and VGG16. All models are fine-tuned by adding different layers like the global average pooling layer, flatten layer, dropout layer, and dense layer. The performance of these five models is compared in terms of the precision, recall, accuracy, and F1-score. The EfficientNetB3 outperformed the other models in terms of all performance parameters. The best model is further optimized with the help of three optimizers, i.e., Adam, SGD, and Adagrad. The proposed model achieved the precision, recall, and F1-score values of 86%, 88%, and 86%, respectively, at 32 batch sizes and 10 epochs. This research formulated a model for an apple foliar disease diagnosis within sustainable agriculture. Full article

Extensive research suggested that the core of how to use pesticides scientifically is the careful and accurate determination of the severity of crop diseases. The existing grading standards of plant leaf diseases have been excessively singular. Thus, the diseases roughly fall into general and severe grades. To address the above problems, this study considered the effect of the distribution of disease spots, and two evaluation indicators (termed the imbalance degree and main vein distance) were newly added to optimize the grading criteria of apple leaf diseases. Combined with other factors, the grade evaluation indicator was determined through PCA principal component analysis. A gradual multivariate logistic regression algorithm was proposed to evaluate apple leaf disease grade and an optimized apple leaf disease grade evaluation model was built through PCA-logistic regression analysis. In addition, three common apple leaf diseases with a total of 4500 pictures (i.e., black rot, scab, and rust) were selected from several open-source datasets as the subjects of this paper. The object detection algorithm was then used to verify the effectiveness of the new model. As indicated by the results, it can be seen from the loss curve that the loss rate reaches a stable range of around 70 at the epoch. Compared with Faster R-CNN, the average accuracy of Mask R-CNN for the type and grade recognition of apple leaf disease was optimized by 4.91%, and the average recall rate was increased by 5.19%. The average accuracy of the optimized apple leaf disease grade evaluation model was 90.12%, marking an overall increase of 20.48%. Thus, the effectiveness of the new model was confirmed. Full article

How soil is used affects its production characteristics in the future. Under ARD (Apple Replant Disease) conditions, replanted soil’s physical, chemical and biological properties deteriorate. Their improvement is possible through, for example, increasing the content of organic matter in the soil. The study aimed to assess the effect of two organic additives for replanted soil on its physical, chemical and biological properties, as well as on the vegetative growth of apple trees of the ‘Gala Schniga SchniCo(s)’ cultivar grafted on M.9 rootstock. The experiment was performed in 2021, in western Poland, on a nursery farm. The trees were planted in pots filled with soil from two stations: soil previously used for the production of apple trees (replanted soil) and nursery material (agricultural soil) unused for production so far. To fertilise it, three different portions of biocarbon and Carbomat Eco soil conditioner were added to the replanted soil. The experiment showed that apple trees grown on replanted soil had fewer side shoots, a smaller leaf area and a lower mass of leaves than those grown on agricultural soil. Furthermore, supplementation of replanted soil with organic additives caused a significant increase in its enzymatic activity and respiration, increased the rate of photosynthesis and improved several parameters determining the strength of vegetative growth in apple trees. Full article

Apple canker, caused by Neonectria ditissima (Tul. and C. Tul.) Samuels and Rossman, is a major disease of apples (Malus domestica) worldwide. N. ditissima infects through natural and artificial wounds. Infected wood develops canker lesions which girdle branches and main stems causing reduced yield and tree death. N. ditissima is difficult to control; removal of inoculum (cankers) is expensive and therefore seldom practiced, whilst effective chemical products are being banned and no biocontrol products have been found to be effective against N. ditissima. This study used cues from a previous apple endophyte community analysis to isolate and test fungal endophytes belonging to the genus Epicoccum as potential endophytic biocontrol agents. Epicoccum nigrum B14-1, isolated from healthy apple trees, antagonised N. ditissima in vitro and reduced the incidence of N. ditissima infections of leaf scars by 46.6% and pruning wounds by 5.3% in field conditions at leaf fall. Autumn application of B14-1 conidia increased E. nigrum abundance in apple tissues at 10–20 days post-inoculation by ca. 1.5×, but this returned to control levels after one year. E. nigrum B14-1 did not cause detrimental effects on apple foliage, buds, fruit, or growth and could therefore present a new biocontrol agent to manage N. ditissima in commercial apple production. Full article

Anthocyanins are severity indicators for apple mosaic disease and can be used to monitor tree health. However, most of the current studies have focused on healthy leaves, and few studies have estimated the anthocyanin content in diseased leaves. In this study, we obtained the hyperspectral data of apple leaves with mosaic disease, analyzed the spectral characteristics of leaves with different degrees of Mosaic disease, constructed and screened the spectral index sensitive to anthocyanin content, and improved the estimation model. To improve the conciseness of the model, we integrated Variable Importance in Projection (VIP), Partial Least Squares Regression (PLSR), and Akaike Information Criterion (AIC) to select the optimal PLSR model and its independent variables. Sparrow Search Algorithm-Random Forest (SSA-RF) was used to improve accuracy. Results showed the following: (1) anthocyanin content increased gradually with the aggravation of disease. The reflectance of the blade spectrum in the visible band increased, the red edge moved to short wave, and the phenomenon of “blue shift of spectrum” occurred. (2) The VIP-PLSR-AIC selected 17 independent variables from 21 spectral indices. (3) Variables were used to construct PLSR, Back Propagation (BP), Support Vector Machine (SVM), Random Forest (RF), and SSA-RF to estimate anthocyanin content. Results showed the estimation accuracy and stability of the SSA-RF model were better than other models. The model set determination coefficient ($R^2$) was up to 0.955, which is 0.047 higher than that of the RF model and 0.138 higher than that of the SVM model with the lowest accuracy. The model was constructed at the leaf scale and can provide a reference for other scale studies, including a theoretical basis for large-area, high-efficiency, high-precision anthocyanin estimation and monitoring of apple mosaics using remote sensing technology. Full article