Search Results (65)

Apple (Malus domestica) is a very important crop grown in Kazakhstan. Cytospora species are capable of causing destructive stem cankers on a wide range of woody plants, including apples, and can lead to twig and branch dieback. This study aimed to identify the Cytospora species responsible for canker disease of apple in Kazakhstan and to assess the susceptibility of major apple cultivars to these pathogens. Investigations were conducted in Almaty, Kazakhstan, during 2023 and 2024. Samples from symptomatic trees were collected, and nine Cytospora isolates were obtained from diseased apple trees. Multigene phylogenetic analysis based on combined sequence data of ITS, tef1-α, tub2, and LSU loci, together with morphological characteristics and pathogenicity assays, revealed two Cytospora species: C. leucostoma and C. sorbicola. The reactions of six apple cultivars (Gala, Golden Delicious, Red Delicious, Granny Smith, Fuji, and Jonaprince) to these species were evaluated, and statistically significant differences were found among cultivars (p < 0.05). The largest lesions occurred on Red Delicious and Fuji, indicating that these cultivars are the most susceptible. In contrast, lesion lengths on Jonaprince were significantly smaller than on all other cultivars, suggesting that Jonaprince is resistant to Cytospora species in Kazakhstan. This is the first report of C. leucostoma and C. sorbicola causing apple canker disease in Kazakhstan. Full article

Pomme fruits are propagated vegetatively, thereby facilitating frequent viral transmission. The causative agent of apple rubbery wood disease, apple rubbery wood virus 2 (ARWV2), can infect apple and pear. The branches of ARWV2-infected, symptomatic trees are flexible due to the decreased lignification of the xylem. In this research, we reanalysed our small RNA (sRNA) HTS datasets to survey the presence of ARWV2 in Hungary. Validation of HTS using RT-PCR revealed infection in several cultivars. The following RT-PCR-based survey revealed the infection of 17 trees, including not only apple, but also pears, one quince, and a rootstock, without showing any rubbery wood symptoms. Analysis of the sRNA datasets allowed us to profile the sRNA pattern of ARWV2-infected and non-infected trees, and characterise the differential expression pattern of vsiRNAs, sRNAs, and miRNAs targeting the lignin biosynthetic pathway. The results confirmed that the gene-expression changes in the genes that regulate lignification cannot be directly correlated with the presence of the virus, which can explain its frequent latent presence. The variable titre and sequence of the virus, and mixed-infection status of the trees, make its reliable diagnostics challenging, which could be achieved as a result of further research. Full article

The single greatest annual production cost for an established cider apple (Malus domestica Borkh.) orchard is the labor required to hand harvest. Reducing harvest labor time may increase the appeal and profitability of growing cider apples. Over-the-row mechanical harvest of cider apples using a modified Oxbo-Korvan 930 was evaluated in northwestern Washington, USA, in 2021, 2022, and 2023 in a fully mature cider apple orchard that was planted in 2014–2016. Sixteen cider apple cultivars grafted on ‘Geneva 935’ rootstock were summer hedged between 7 and 20 July each year of this study. Plant growth regulators were applied before harvest to equalize the timing of harvest among cultivars. There were no differences among cultivars for the percent of apples captured by the Oxbo-Korvan 930 harvester for the 3 years of this study. Across all years and cultivars studied, 82% of fruit were captured by the harvester. There also were no differences among cultivars for the percentage of fruit left on the tree by the harvester (9% of fruit on average), nor in the percentage of fruit dropped on the ground during harvest (9% of fruit on average). The overall mean number of branches broken during mechanical harvest across all cultivars was 1.4 per tree, and there were no differences among cultivars. ‘Sweet Alford’ had high spur removal (26 removed per tree), but excluding this outlier, only 6 spurs on average were removed per tree for all other cultivars. Laceration to fruit during mechanical harvest were positively correlated with mean fruit weight and mean fruit diameter. The overall average time required to mechanically harvest one tree in this orchard (1.8 m in-row spacing, 1495 trees·ha⁻¹) was 5.3 s, averaging 2.9 s per row-meter traveled. The average time required to manually harvest one tree was 229 s (3.8 min). The juice quality of the mechanically harvested apples that were kept in cold storage and pressed within 42 d of harvest did not differ largely or consistently from juice quality of apples that were pressed within 3 d of harvest, except that sugars (measured through ºBrix and specific gravity) increased with storage time, as expected. Mechanical harvest using the modified Oxbo-Korvan 930 appears to be a labor-efficient and effective method of harvesting cider apples, and testing is needed in commercial orchards to evaluate its viability compared to other harvest technologies. Full article

Subsurface drip irrigation can improve crop water and fertilizer use efficiency, but it can cause soil hypoxia. We report on experiments performed in Aksu Prefecture, Xinjiang (41°17′ N latitude, 80°17′ E longitude), from April 2023 to October 2024 using oxygenated drip irrigation from the surface to 50 cm depth in an apple (Malus pumila Mill.) orchard, to examine the effects of drip irrigation on inter-root hypoxia, tree growth, fruit quality, and yield. Compared with surface oxygenated drip irrigation (CK), irrigating at 10 and 30 cm increased soil water content in the root system, elevated gibberellin, zeatin ribosides, and indoleacetic acid contents and reduced abscisic acid contents in new shoot tips. Compared with CK, branch and leaf nitrogen, phosphorus, and potassium contents were increased with irrigation at depths of 10 and 30 cm. The leaf nitrogen (N), phosphorus (P), and potassium (K) contents were increased by 18.03%, 22.42%, and 16.63%, respectively, in the treatment with a burial depth of 30 cm. Among treatments, irrigation at 30 cm produced the highest average daily plant water potential, and irrigation at 50 cm was the lowest. Maximum leaf soil–plant analysis development (SPAD) values occurred when irrigated at 30 cm, and minimum values occurred at 50 cm. For both years, the largest range of light flux utilization occurred when irrigated at 30 cm and the lowest when irrigated at 50 cm. Significant correlations between indoleacetic acid (IAA), total gibberellin (GA), zeatin riboside (ZRs), leaf N content, leaf K content, plant water potential (PWP), net photosynthetic rate (Pn), SPAD, and apple yield were determined by partial mantel analysis. A significant correlation was found between abscisic acid (ABA), IAA, GA, leaf P and K content, and apple quality. Principal component analysis revealed a burial depth of 30 cm had the highest principal component composite score, indicating that this burial depth, and oxygenation and fertilization regime most favored apple growth, yield, and quality. Full article

Computer vision is of wide interest to perform the phenotyping of horticultural crops such as apple trees at high throughput. In orchards specially constructed for variety testing or breeding programs, computer vision tools should be able to extract phenotypical information form each tree separately. We focus on segmenting individual apple trees as the main task in this context. Segmenting individual apple trees in dense orchard rows is challenging because of the complexity of outdoor illumination and intertwined branches. Traditional methods rely on supervised learning, which requires a large amount of annotated data. In this study, we explore an alternative approach using prompt engineering with the Segment Anything Model and its variants in a zero-shot setting. Specifically, we first detect the trunk and then position a prompt (five points in a diamond shape) located above the detected trunk to feed to the Segment Anything Model. We evaluate our method on the apple REFPOP, a new large-scale European apple tree dataset and on another publicly available dataset. On these datasets, our trunk detector, which utilizes a trained YOLOv11 model, achieves a good detection rate of $97\%$ based on the prompt located above the detected trunk, achieving a Dice score of 70% without training on the REFPOP dataset and 84% without training on the publicly available dataset.We demonstrate that our method equals or even outperforms purely supervised segmentation approaches or non-prompted foundation models. These results underscore the potential of foundational models guided by well-designed prompts as scalable and annotation-efficient solutions for plant segmentation in complex agricultural environments. Full article

Accurate acquisition of the phenotypic information of trunk-shaped fruit trees plays a crucial role in intelligent orchard management, pruning during dormancy, and improving fruit yield and quality. However, the precise segmentation of trunks and branches remains a significant challenge, limiting the accurate measurement of phenotypic parameters and high-precision pruning of branches. To address this issue, a novel adaptive cuboid regional growth segmentation algorithm is proposed in this study. This method integrates a growth vector that is adaptively adjusted based on the growth trend of branches and a growth cuboid that is dynamically regulated according to branch diameters. Additionally, an innovative reverse growth strategy is introduced to enhance the efficiency of the growth process. Furthermore, the algorithm can automatically and effectively identify the starting and ending points of growth based on the structural characteristics of fruit tree branches, solving the problem of where to start and when to stop. Compared with PointNet++, PointNeXt, and Point Transformer, ACRGS achieved superior performance, with F₁-scores of 95.75% and 96.21% and mIoU values of 0.927 and 0.933 for apple and cherry trees. The results show that the method enables high-precision and efficiency trunk–branch segmentation, providing data support for fruit tree phenotypic parameter extraction and pruning. Full article

The accurate definition of tree growth descriptors is a crucial step in enhancing orchard management, allowing cultivar identification within an orchard and in new genotype selection for breeding programs. In apple, almond, and olive orchards, Terrestrial Laser Scanning (TLS) technologies have been already used to identify different architectural groups, but not in hazelnut yet. This study utilized TLS to investigate the canopy structure of hazelnut trees of four different Italian varieties, with and without leaves. TLS proved to be a sensor capable of collecting three-dimensional data from hazelnut field trials and allowed the definition and selection of hazelnut plant descriptors by morphological traits and morphological indexes. Nineteen descriptors, eight morphologic traits and 11 morphological indexes have been identified as reliable suitable descriptors of hazelnut cultivar and in breeding evaluations, according to Biodiversity, FAO and CIHEAM. Many of the selected descriptors are related to the tree habit, vigour and branching density. Two useful indexes have also been defined: Canopy Uprightness (CU) Index and the Index of Canopy Opening (ICO). The descriptors allowed us to distinguish the four studied hazelnut cultivars based on their growth habit; in particular the cultivar Tonda Gentile delle Langhe showed a growth habit that is a lot different from that of the other ones. Full article

Plant fungal diseases remain a major threat to global agricultural production, necessitating eco-friendly and sustainable strategies. Conventional chemical fungicides often lead to the development of resistant pathogen strains and cause environmental contamination. Therefore, the development of biocontrol agents is particularly important. In this study, we identified Burkholderia stagnalis YJ-2 from the rhizosphere soil of Woodsia ilvensis as a promising biocontrol strain using 16S rRNA and whole-genome sequencing. This strain demonstrated broad-spectrum antifungal activity against plant fungal pathogens, with its bioactive extracts maintaining high stability across a temperature range of 25–100 °C and pH range of 2–12. We used in vitro assays to further show that the metabolites of B. stagnalis YJ-2 disrupted the hyphal morphology of Valsa mali, resulting in swelling, reduced branching, and increased pigmentation. Fluorescence labeling confirmed that B. stagnalis YJ-2 stably colonized the roots and stems of tomato and wheat plants. Furthermore, various formulations of microbial agents based on B. stagnalis YJ-2 were evaluated for their efficacy against plant pathogens. The seed-coating formulation notably protected tomato seedlings from Alternaria solani infection without affecting germination (p > 0.1), while the wettable powder exhibited significant control effects on early blight in tomatoes, with the preventive treatment showing better efficacy than the therapeutic treatment. Additionally, the B. stagnalis YJ-2 bone glue agent showed a substantial inhibitory effect on apple tree canker. Whole-genome analysis of B. stagnalis YJ-2 revealed a 7,705,355 bp genome (67.68% GC content) with 6858 coding genes and 20 secondary metabolite clusters, including three clusters (YJ-2_GM002015-YJ-2_GM002048, YJ-2_GM0020090-YJ-2_GM002133, and YJ-2_GM06534-YJ-2_GM006569) that are related to the antifungal activity of YJ-2 and are homologous to the biosynthetic gene clusters of known secondary metabolites, such as icosalide, ornibactin, and sinapigladioside. We further knocked out core biosynthetic genes of two secondary metabolic gene clusters and found that only the YJ-2_GM006534-YJ-2_GM006569 gene cluster had a corresponding function in two potential antifungal gene clusters. In contrast to the wild-type strain YJ-2, only deletion of the YJ-2_GM006563 gene reduced the antifungal activity of B. stagnalis YJ-2 by 8.79%. These findings highlight the biocontrol potential of B. stagnalis YJ-2, supporting a theoretical foundation for its development as a biocontrol agent against plant fungal diseases and thereby promoting sustainable agricultural disease management. Full article

The high nutritional and medicinal value of apples has contributed to their widespread cultivation worldwide. Unfavorable factors in the healthy growth of trees and extensive orchard work are threatening the profitability of apples. This study reviewed deep learning combined with computer vision for monitoring apple tree growth and fruit production processes in the past seven years. Three types of deep learning models were used for real-time target recognition tasks: detection models including You Only Look Once (YOLO) and faster region-based convolutional network (Faster R-CNN); classification models including Alex network (AlexNet) and residual network (ResNet); segmentation models including segmentation network (SegNet), and mask regional convolutional neural network (Mask R-CNN). These models have been successfully applied to detect pests and diseases (located on leaves, fruits, and trunks), organ growth (including fruits, apple blossoms, and branches), yield, and post-harvest fruit defects. This study introduced deep learning and computer vision methods, outlined in the current research on these methods for apple tree growth and fruit production. The advantages and disadvantages of deep learning were discussed, and the difficulties faced and future trends were summarized. It is believed that this research is important for the construction of smart apple orchards. Full article

Rootstocks largely determine the tree architecture of the grafted scions, significantly affects yield, suitability for mechanical harvesting, and planting pattern of apple orchards. It is thus important to reveal the mechanisms behind the rootstocks influence on the tree architecture of scions in apple trees. This study analyzed the grafting survival rate, the physiological parameters including plant growth, photosynthesis and nutrient accumulation in the apple variety ‘Harlikar’ with eight apple rootstocks. We also explored the mechanism of scion architecture formation using transcriptomics based on different scion/rootstock combinations. The results indicated that ‘Harlikar’ had the lowest grafting survival rate with rootstock ‘M26’, with less callus formed at the graft interface, foliage etiolation, and weak photosynthetic capacity. While ‘Harlikar’ had better affinities with ‘M9-T337’, ‘M9-Nic29’, ‘M9-Pajam2’, ‘B9’, ‘71-3-150’, ‘Qingzhen 2’, and ‘Malus baccata’. Among these, the highest plant height and the highest number of lateral branches were observed in ‘Harlikar’ with rootstock ‘Qingzhen 2’, they were 1.12-times and 2.0-times higher than ‘Harlikar’ with vigorous rootstock ‘M. baccata’, respectively. The highest accumulations of total nitrogen, total phosphorus, and total potassium in scions were observed in ‘Harlikar’/‘Qingzhen 2’, they were 2.22-times, 2.10-times, and 11.80-times higher than that in ‘Harlikar’/‘M. baccata’. The lowest plant height was observed in ‘Harlikar’/‘71-3-150’, only 50.47% of ‘Harlikar’/‘Qingzhen 2’ and 56.51% of ‘Harlikar’/‘M. baccata’, and the lowest internode length was observed in ‘Harlikar’/‘M9-Nic29’, only 60.76% of ‘Harlikar’/‘Qingzhen 2’ and 79.11% of ‘Harlikar’/‘M. baccata’. The transcriptome, weighted gene co-expression network and KEGG enrichment analyses revealed that, compared to ‘Harlikar’/‘M. baccata’, most differentially expressed genes screened from ‘Harlikar’/‘Qingzhen 2’, ‘Harlikar’/‘71-3-150’, and ‘Harlikar’/‘M9-Nic29’ were enriched in hormone signal transduction pathways. Specifically, auxin-repressed protein gene ARP, cytokinin synthesis related genes CKXs and CYP92A6, and brassinosteroid synthesis related gene CYP87A3 were involved in the dwarfing of ‘Harlikar’/‘71-3-150’ and ‘Harlikar’/‘M9-Nic29’. Cytokinin synthesis related gene ARR-A and abscisic acid-responsive element binding factor gene ABF were the key to increased branching in ‘Harlikar’/‘Qingzhen 2’. In addition, acid phosphatase genes ACPs, and serine/threonine-protein kinase genes PBLs were involved in the vegetative growth of scions in ‘Harlikar’/‘Qingzhen 2’ by affecting the absorption and utilization of nutrients. These results provide theoretical guidance for cultivating high-quality ‘Harlikar’ apple trees and elucidate the molecular mechanisms regulating plant height and lateral branch formation in apple. Full article

Lasiodiplodia theobromae is a pathogenic fungus associated with tropical perennial fruit plants worldwide. In apple trees, L. theobromae causes dieback and canker, a disease that affects the architecture of the wood producing the progressive death of branches and stems, from the tips to the base, invading the vascular tissue, manifesting necrotic lesions in the bark, impeding the flow of nutrients and water. The present work reports the whole genome de novo sequencing (WGS) of L. theobromae strain Bot-2018-LT45 isolated from apple trees with dieback symptoms. Genomic DNA of L. theobromae was sequenced using Illumina paired-end short-read technology (NovaSeq6000) and PacBio SMRTbell^TM (Single Molecule, Real-Time) long-read technology. The genome size was 44.17 Mb. Then, assembly and annotation revealed a total of 12,948 genes of which 11,634 encoded proteins. The genome was assembled into 34 contigs with an N50 (Mb) value of 3.23. This study is the first report of the L. theobromae genome de novo obtained from apple trees with dieback and canker symptoms in the Maule Region, Chile. This genetic information may set the basis for future study of the mechanisms of L. theobromae and establish the possibility of specific molecular improvements for the control of dieback and canker. Full article

Apples are widely consumed by people all over the world due to their taste and nutritional value. However, apple trees are prone to various environmental stresses, including fungal diseases. Among them, Cytospora canker (or Valsa canker) can cause dieback of branches and twigs. Although Kazakhstan is well known as an origin of apples, very little is known about canker diseases that spread across all commercial orchards. Therefore, an accurate identification of the causal agents of those diseases is needed for further application of informed disease management strategies. In this study, eleven isolates belonging to four Cytospora species were isolated from multiple cultivars, grown in six different orchards within the Almaty region, Kazakhstan. As a result of a multilocus phylogenetic analysis using ITS, LSU and tef1-α marker genes and morphological characterization, these isolates were described as Cytospora parasitica, Cytospora sorbina, Cytospora pruinopsis and Cytospora chrysosperma. Moreover, a pathogenicity test was conducted on detached twigs, and it demonstrated that two of these fungi were highly virulent. Overall, this paper is a first report of the causal agents of apple canker disease in Kazakhstan and could be a trigger for conducting future studies to better understand the disease epidemiology, as well as build management strategies. Full article

Nursery material intended for establishing intensive apple orchards should be characterised by a dominant and straight leader with an appropriate number of shoots that develop at the right height and are regularly spaced along the leader. The use of well-branched trees can lead to fruiting in the first year after planting. However, many apple varieties have difficulty forming lateral shoots due to strong apical dominance. The aim of the study was to assess the effectiveness of treatments stimulating the branching of maiden apple trees of the ‘Gloster’ variety. The research was carried out in 2017–2019 at a private nursery farm located in eastern Poland. The studied trees were subjected to a mechanical branching stimulation treatment, which consisted of pinching off 4–5 of the youngest leaves located below the growth cone, and chemical branching stimulation treatments, which consisted of applying growth regulator mixtures in the form of an aqueous solution, i.e., BA+GA₃ and BA+GA₄₊₇. The conducted studies showed that the type of branching-stimulating treatment had a significant effect on the height and trunk diameter of the maiden trees, the number of lateral shoots, the average length of one shoot and the sum of the lengths of all sylleptic shoots. The maiden trees treated with BA+GA₃ were characterised by the best quality among the analysed combinations. Maiden apple trees treated with BA+GA₃ were the tallest (2017—167.7 cm; 2018—175.3 cm; 2019—164.4 cm), produced the largest number of shoots (2017—6.5 pcs; 2018—6.8 pcs; 2019—6.3 pcs) and had the largest sum of lateral shoot lengths (2017—148.0 cm; 2018—155.4 cm; 2019—140.6 cm) among the evaluated combinations. The number of treatments and the concentration of applied growth regulators had a significant effect on the structure of the crown of the maiden apple trees of the ‘Gloster’ cultivar. Full article

The apple tree (Malus × domestica Borkh.) belongs to the Rosaceae. Due to its adaptability and tolerance to different soil and climatic conditions, it is cultivated worldwide for fresh consumption. The priorities of apple growers are high-quality fruits and stable yield for high production. About 90 to 95 percent of fruits should fall or be eliminated from apple trees to avoid overcropping and poor-quality fruits. Apple trees engage in a complex biological process known as yield self-regulation, which is influenced by several internal and external factors. Apple buds develop in different stages along the branches, and they can potentially give rise to new shoots, leaves, flowers, or fruit clusters. The apple genotype determines how many buds will develop into fruit-bearing structures and the capacity for yield self-regulation. Plant hormones such as ethylene, cytokinins, auxins, and gibberellins play a crucial role in regulating the fruit set, growth, and development, and the balance of these hormones influences the flowering intensity, fruit size, and fruit number on the apple tree. Apple growers often interfere in the self-regulation process by manually thinning fruit clusters. Different thinning methods, such as by hand, mechanical thinning, or applying chemical substances, are used for flower and fruit thinning. The most profitable in commercial orchards is the use of chemicals for elimination, but more environmentally sustainable solutions are required due to the European Green Deal. This review focuses on the biological factors and genetic mechanisms in apple yield self-regulation for a better understanding of the regulatory mechanism of fruitlet abscission for future breeding programs targeted at self-regulating yield apple varieties. Full article

Aiming to accurately identify apple targets and achieve segmentation and the extraction of branch and trunk areas of apple trees, providing visual guidance for a picking robot to actively adjust its posture to avoid branch trunks for obstacle avoidance fruit picking, the spindle-shaped fruit trees, which are widely planted in standard modern apple orchards, were focused on, and an algorithm for apple tree fruit detection and branch segmentation for picking robots was proposed based on an improved YOLOv8s model design. Firstly, image data of spindle-shaped fruit trees in modern apple orchards were collected, and annotations of object detection and pixel-level segmentation were conducted on the data. Training set data were then augmented to improve the generalization performance of the apple detection and branch segmentation algorithm. Secondly, the original YOLOv8s network architecture’s design was improved by embedding the SE module visual attention mechanism after the C2f module of the YOLOv8s Backbone network architecture. Finally, the dynamic snake convolution module was embedded into the Neck structure of the YOLOv8s network architecture to better extract feature information of different apple targets and tree branches. The experimental results showed that the proposed improved algorithm can effectively recognize apple targets in images and segment tree branches and trunks. For apple recognition, the precision was 99.6%, the recall was 96.8%, and the mAP value was 98.3%. The mAP value for branch and trunk segmentation was 81.6%. The proposed improved YOLOv8s algorithm design was compared with the original YOLOv8s, YOLOv8n, and YOLOv5s algorithms for the recognition of apple targets and segmentation of tree branches and trunks on test set images. The experimental results showed that compared with the other three algorithms, the proposed algorithm increased the mAP for apple recognition by 1.5%, 2.3%, and 6%, respectively. The mAP for tree branch and trunk segmentation was increased by 3.7%, 15.4%, and 24.4%, respectively. The proposed detection and segmentation algorithm for apple tree fruits, branches, and trunks is of great significance for ensuring the success rate of robot harvesting, which can provide technical support for the development of an intelligent apple harvesting robot. Full article