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Flat peaches have become popular worldwide due to their novelty and convenience. The peach flat fruit trait is genetically controlled by a single gene at the S locus, but its genetic basis remains unclear. Here, we report a 1.7‐Mb chromosomal inversion downstream of a candidate gene encoding OVATE Family Protein, designated PpOFP1, as the causal mutation for the peach flat fruit trait. Genotyping of 727 peach cultivars revealed an occurrence of this large inversion in flat peaches, but absent in round peaches. Ectopic overexpression of PpOFP1 resulted in oval‐shaped leaves and shortened siliques in Arabidopsis, suggesting its role in repressing cell elongation. Transcriptional activation of PpOFP1 by the chromosomal inversion may repress vertical elongation in flat‐shaped fruits at early stages of development, resulting in the flat fruit shape. Moreover, PpOFP1 can interact with fruit elongation activator PpTRM17, suggesting a regulatory network controlling fruit shape in peach. Additionally, screening of peach wild relatives revealed an exclusive presence of the chromosomal inversion in P. ferganensis, supporting that this species is the ancestor of the domesticated peach. This study provides new insights into mechanisms underlying fruit shape evolution and molecular tools for genetic improvement of fruit shape trait in peach breeding programmes.

Flat peach ( Prunus persica L. Batsch. var. Compressa Bean) is a climacteric fruit and is, as a result, susceptible to deterioration. This study aims to effectively monitor the quality of flat peaches by measuring the representative quality indices and identifying key volatile compounds correlated with quality changes. The six quality indices of flat peaches (sensory evaluation, firmness, soluble solid content (SSC), titratable acid (TA) content, SSC/TA, and vitamin C (Vc)) were analyzed during storage at 4 ℃. The quality of the flat peach samples was divided into two grades using cluster analysis (CA) and principal component analysis (PCA). Moreover, the volatile compounds in the samples were analyzed in situ using solid-phase microextraction coupled with gas chromatography–mass spectrometry (SPME–GC–MS). Additionally, an orthogonal partial least square–discriminant analysis (OPLS–DA) model was established to identify variations in volatile compounds in different quality flat peaches. Finally, a total of 37 volatile compounds were identified, and 13 key aroma components were screened out. These key volatile compounds could effectively differentiate the quality of the flat peach samples. The results were consistent with the grading results from the quality indices. Among them, methyl hexanoate, ( Z )-3-hexenyl acetate, β -ocimene, and linalool were closely related to the variation of peach quality and could be used as characteristic volatile compounds to evaluate the quality of flat peaches. These results are expected to provide a theoretical basis for the detection and quality evaluation of flat peaches in cold storage using quality indices or volatile compounds.

The flat peach ( (L.) Batsch.), characterized by its oblate shape and determined by a known genetic inversion, is a high-value cultivar gaining global market share. Mapping the intellectual landscape of its research is crucial to consolidate knowledge and direct future scientific and breeding programs. A comprehensive bibliometric analysis was conducted on a curated dataset of forty open-access research articles published between 2010 and 2024, sourced from Web of Science and Scopus. Following rigorous data deduplication, the bibliometrix R package was employed to analyze publication trends, collaboration networks, and keyword co-occurrence patterns. Collaboration networks were subsequently visualized and analyzed using VOSviewer. The analysis identified a striking surge in annual publications, particularly post-2019, underscoring growing interest. China was the unequivocal dominant force in production and citation impact. Key research themes clustered around \"fruit quality,\" \"genetics,\" and \"postharvest physiology,\" with \"quality\" exhibiting the strongest network centrality. The network analysis identified \"flat peach\" as a central hub, demonstrating the highest co-occurrence link strength and affirming its strong, multifaceted connections within the research domain. This first systematic bibliometric review delineates the rapid evolution of flat peach research, highlighting its core drivers and conceptual focus. The steep growth in output reflects rising academic and commercial interest. Critically, the analysis identifies significant gaps in molecular genomics, postharvest optimization, and climate resilience research. These findings provide a strategic, evidence-based roadmap to align future research priorities with market demands and sustainable cultivation challenges.

The flat peach has become more and more popular worldwide for its fruit quality with relatively low acidity, high sugar content and rich flavor. However, the draft genome assembly of flat peach is still unavailable and the genetic basis for its fruit flavor remains unclear. In this study, the draft genome of a flat peach cultivar ‘124 Pan’ was assembled by using a hybrid assembly algorithm. The final assembly resulted in a total size of 206 Mb with a N50 of 26.3 Mb containing eight chromosomes and seven scaffolds. Genome annotation revealed that a total of 25,233 protein-coding genes were predicted with comparable gene abundance among the sequenced peach species. The phylogenetic tree and divergence times inferred from 572 single copy genes of 13 plant species confirmed that Prunus ferganensis was the ancestor of the domesticated peach. By comparing with the genomes of Prunus persica (Lovell) and Prunus ferganensis, the expansion of genes encoding enzymes involved in terpene biosynthesis was found, which might contribute to the good fruit flavor traits of ‘124 Pan’. The flat peach draft genome assembly obtained in this study will provide a valuable genomic resource for peach improvement and molecular breeding.

Flat peach, a predominant fruit consumed in China, is highly susceptible to softening and perishable. The impact of 1-methylcycloproene (1-MCP) fumigation combined with ε-poly-L-lysine (ε-PL) on softening and postharvest reactive oxygen species (ROS) and phenylpropanoid pathway metabolisms in peaches and its relationship to disease resistance were investigated. Findings revealed that a combination of 1 µL L−1 1-MCP and 300 mg L−1 ε-PL effectively suppressed the activity of cell-wall-degrading enzymes and the disassembly of cell wall structure, thus maintaining higher firmness and lower decay incidence. Compared to the control group, the synergistic approach bolstered enzymatic responses linked to disease resistance and ROS-scavenge system, consistently preserving total phenolics, flavonoids, ascorbic acid, and glutathione levels. Concurrently, the accumulation of hydrogen peroxide and malondialdehyde was significantly diminished post-treatment. These results show that there is good synergistic effect between 1-MCP and ε-PL, which could effectively maintain the quality of flat peach fruit by modulating cell wall metabolism and enhancing the resistance.

An accurate and effective peach recognition algorithm is a key part of automated picking in orchards; however, the current peach recognition algorithms are mainly targeted at bare fruit scenarios and face challenges in recognizing flat peach bagged fruits, based on which this paper proposes a model for recognizing and detecting flat peach fruits in complex orchard environments after bagging, namely, YOLOv8n-CDDSh. First, to effectively deal with the problem of the insufficient detection capability of small targets in orchard environments, the dilation-wise residual (DWR) module is introduced to enhance the model’s understanding of semantic information about small target defects. Second, in order to improve the detection ability in complex occlusion scenarios, inspired by the idea of large kernel convolution and cavity convolution in the Dilated Reparam Block (DRB) module, the C2f-DWR-DRB architecture is built to improve the detection ability in occluded target regions. Thirdly, in order to improve the sensitivity and precision of aspect ratio optimization, and to better adapt to the detection scenarios of targets with large differences in shapes, the ShapeIoU loss function is used to improve the fruit localization precision. Finally, we validate the effectiveness of the proposed method through experiments conducted on a self-constructed dataset comprising 1089 samples. The results show that the YOLOv8n-CDDSh model achieves 92.1% precision (P), 91.7% Mean Average Precision (mAP), and a model size of 5.73 MB, with improvements of +1.5 pp (Precision) and +0.5 pp (mAP) over YOLOv8n, respectively. In addition, the detection performance is excellent in actual orchard environments with different light angles, shading conditions, and shooting distances. Meanwhile, YOLOv8n-CDDSh deployed on the edge computing device achieved precision = 87.04%, mAP = 91.71%, and FPS = 37.20, and can also maintain high precision in bagged fruit recognition under extreme weather simulations such as fog and rainstorms, providing theoretical and methodological support for the automated picking of bagged peaches.

The flat peach, an important commercial crop in the 143rd Regiment of Shihezi, China, is overwintered using plastic film mulching. Flat peaches are cultivated to boost the local temperate rural economy. The development of accurate maps of the spatial distribution of flat peach plantations is crucial for the intelligent management of economic orchards. This study evaluated the performance of pixel-based and object-based random forest algorithms for mapping flat peaches using the GF-1 image acquired during the overwintering period. A total of 45 variables, including spectral bands, vegetation indices, and texture, were used as input features. To assess the importance of different features on classification accuracy, the five different sets of variables (5, 15, 25, and 35 input variables and all 45 variables) were classified using pixel/object-based classification methods. Results of the feature optimization suggested that vegetation indices played a key role in the study, and the mean and variance of Gray-Level Co-occurrence Matrix (GLCM) texture features were important variables for distinguishing flat peach orchards. The object-based classification method was superior to the pixel-based classification method with statistically significant differences. The optimal performance was achieved by the object-based method using 25 input variables, with an overall accuracy of 94.47% and a Kappa coefficient of 0.9273. Furthermore, there were no statistically significant differences between the image-derived flat peach cultivated area and the statistical yearbook data. The result indicated that high-resolution images based on the overwintering period can successfully achieve the mapping of flat peach planting areas, which will provide a useful reference for temperate lands with similar agricultural management.

Sterilization can induce flavor deterioration in flat peach juice (FPJ) and lead to the formation of warmed‐over flavor (WOF). The effects of pasteurization (PS), high‐temperature sterilization (HTST), high hydrostatic pressure (HHP), and ultrasonic sterilization (US) on FPJ flavor were investigated using flavoromics and multivariate statistical analyses. E‐tongue and E‐nose indicated that nonthermal sterilizations effectively preserved the original flavor profile. HS–GC–IMS and HS–SPME–GC–MS identified aldehydes and ketones as dominant VOCs in FPJ. HHP primarily enhanced 4‐octanone, (+)‐citronellal, and mesitylene, which contributed positively to the overall flavor with honey and floral aromas; US preserved fruity, sweet flavor but generated lipid oxidation products associated with WOF; HTST caused the most extensive loss of characteristic aroma compounds, accompanied by flavor deterioration and increased contribution of WOF. The findings of this research offer valuable insights into identifying appropriate sterilization methods aimed at augmenting the organoleptic and gustatory properties of flat peach juice.

Accurately identifying the morphology and spatial distribution of flat peach inflorescence is crucial for guiding precise flower thinning operations. In this study, based on the YOLOv8 framework, a flat peach inflorescence detection model (RBCN-YOLO) was developed for detecting all growth stages, from bud to initial flowering and full flowering. The model optimized the neck network architecture by incorporating RepBlock and BiFusion modules, integrating the CAFM module into the backbone network, and combining the NWD loss function with the CIoU loss function. The improved model showed better detection performance in remote viewing angles, backlight conditions, and complex scenarios. Moreover, it demonstrated good real-time performance on edge devices. Based on this model, a flower thinning strategy was designed by combining the density classification algorithm, inflorescence membership categorization, and interval flower-thinning requirements. The results showed that the RBCN-YOLO model achieved a mAP@0.5 of 82.9% and an F1 score of 78.9%. These scores represented improvements of 3.0% and 2.4%, respectively, compared to YOLOv8. Notably, the model performance in the initial flowering stage showed the most significant improvement, with the mAP@0.5 increasing from 65.1% to 70.7%. Additionally, the flower thinning strategy based on RBCN-YOLO achieved a flower thinning ratio of 54.55%, with a thinning accuracy of 78.84%. To further enhance the application of the research, a visualization system with integrated object detection and flower thinning functions was designed. This study provides a valuable reference for flower-thinning operations in flat peach orchards.

The flat peach is a high economic value table fruit possessing excellent quality and a unique aroma. This article investigated the quality characteristics and aroma fingerprinting of flat peaches (Qingpan, QP; Ruipan 2, R2; Ruipan 4, R4; Wanpan, WP) from Xinjiang in terms of taste, antioxidant capacity, and volatile aroma compounds using high-performance liquid chromatography (HPLC) and HS-SPME-GC-MS. The results showed that the flat peaches had a good taste and high antioxidant capacity, mainly due to the high sugar–low acid property and high levels of phenolic compounds. This study found that sucrose (63.86~73.86%) was the main sugar, and malic acid (5.93~14.96%) and quinic acid (5.25~15.01%) were the main organic acids. Furthermore, chlorogenic acid (main phenolic compound), epicatechin, rutin, catechin, proanthocyanidin B1, and neochlorogenic acid were positively related to the antioxidant activity of flat peaches. All flat peaches had similar aroma characteristics and were rich in aromatic content. Aldehydes (especially benzaldehyde and 2-hexenal) and esters were the main volatile compounds. The aroma fingerprinting of flat peaches consisted of hexanal, 2-hexenal, nonanal, decanal, benzaldehyde, 2,4-decadienal, dihydro-β-ionone, 6-pentylpyran-2-one, 2-hexenyl acetate, ethyl caprylate, γ-decalactone, and theaspirane, with a “peach-like”, “fruit”, and “coconut-like” aroma. Among them, 2,4-decadienal, 2-hexenyl acetate, and theaspirane were the characteristic aroma compounds of flat peaches. The results provide a theoretical basis for the industrial application of the special aroma of flat peaches.