Search Results (11)

Reliable fruit quality assessment is crucial for ensuring food safety and value in modern agriculture. However, many current approaches still rely heavily on visual cues, making it difficult to assess internal quality indicators such as sweetness or internal decay. To address this limitation, we propose HSAF-Net, a heterogeneous multimodal fusion framework integrating spiking neural networks (SNNs) and artificial neural networks (ANNs) for comprehensive, non-destructive fruit quality assessment. Specifically, the SNN encodes near-infrared (NIR) spectral signals to extract internal sugar-related features, whereas the ANN-based TH-YOLOv8 model detects external surface defects from high-resolution RGB images. A microsecond-level synchronous acquisition scheme is implemented to ensure precise alignment between the NIR and RGB modalities. To effectively combine heterogeneous features, we design a Heterogeneous Modality Attention (HMA) mechanism that dynamically fuses multi-source information based on task-specific relevance. Compared with image-only detection, the proposed framework explicitly separates internal biochemical sensing from external defect localization and then integrates their complementary decisions in a unified grading pipeline. Experimental results on 616 pear samples demonstrate that the HSAF-Net achieves 95.2% classification accuracy, 95.1% mAP95, and an internal defect miss rate as low as 7.5%, outperforming conventional single-modality and early-fusion baselines by a notable margin. The system maintains a real-time inference speed of 55 ms per sample on the Ascend Atlas 200DK A2 edge platform, validating its deployment potential. The current evaluation is based on crisp pear samples collected under controlled acquisition conditions; therefore, broader cross-variety and cross-season validation remains necessary before large-scale commercial deployment. This study presents an end-to-end multimodal SNN-ANN fusion architecture tailored for fruit grading and provides a scalable, high-precision solution for post-harvest quality assessment with broad applicability to other agricultural products. Full article

Mechanical damage remains a major constraint in low-damage harvesting and handling of the Korla fragrant pear, owing to its cultivar-specific bruise-sensitive traits (BSTs), namely its thin peel, crisp flesh, smooth epidermis, and high bruise sensitivity. This review synthesizes evidence from the Korla fragrant pear, other pear cultivars, apple, and related fresh produce to clarify damage mechanisms and engineering strategies for damage control. The reviewed studies show that injury is mainly governed by impact energy, compression load, contact stiffness, friction, fruit velocity, spacing, and transfer trajectory. Quasi-static compression and drop-impact tests provide essential thresholds, including elastic modulus, rupture force, absorbed energy, bruise area, and bruise volume, but Korla-specific data remain insufficient. Nondestructive techniques are complementary: RGB machine vision supports rapid surface screening, hyperspectral imaging improves early bruise detection, X-ray computed tomography quantifies internal bruising, and scanning electron microscopy verifies cellular damage mechanisms. FEM and DEM can predict stress distribution, deformation, collision behavior, and equipment-induced injury when calibrated with cultivar-specific parameters. Overall, apple- or general pear-based technologies require recalibration before application to the Korla fragrant pear. Future work should establish Korla-specific damage thresholds and validate detection, simulation, and conveying systems under real orchard and packing-line conditions. Full article

Subsequent to the harvesting of ‘Red Zaosu’ pears, a swift decline in quality becomes evident. This is characterized by the discoloration of the peel, the softening of the flesh and metabolic alterations during storage. To elucidate the regulatory roles of phytohormone in fruit preservation, postharvest pears were treated with 100 μmol/L abscisic acid (ABA), 100 μmol/L methyl jasmonate (MeJA) or their combination (ABA + MeJA). The results indicated that the phytohormone treatment groups exhibited varying degrees of efficacy in improving the postharvest quality of pear fruits. The combined treatments did not show synergistic effects, but rather inhibited anthocyanin accumulation and antioxidant enzyme (POD, CAT, APX, POD) activities and significantly reduced soluble solids, acidity and flavonoids, although peel brightness was maintained. ABA alone treatment promoted anthocyanin accumulation and peel coloring, but reduced fruit firmness, crispness, chewiness and soluble solids, enhanced total flavonoids and CAT activity and reduced malondialdehyde accumulation, while MeJA alone treatment inhibited anthocyanin synthesis and coloring, but also reduced firmness and soluble solids, and enhanced total flavonoids and CAT activity. The results indicate that ABA and MeJA exhibit differential regulatory effects on fruit quality when applied individually, and their combined application showed inferior effects compared to individual treatments. This finding provides a theoretical basis for optimizing combined phytohormone-preservation techniques. Full article

Flesh texture is an important quality trait and is related to people’s preference for fruit, especially for crisp pears. Puncture tests were carried out on 156 crisp pear fruit germplasm samples to analyze the diversity level of texture traits, to clarify the correlation between sensory description evaluation and instrumental traits, and to explore the effects of fruit ripening, size, and shelf life on the change in flesh texture. The results showed that puncture parameters were significantly different between crisp pear cultivars, and the work associated with the flesh limit compression force had the highest coefficient of variation (0.281). There was a significant correlation between puncture parameters and sensory evaluation scores. The correlation between sensory score and flesh firmness was the highest, with a correlation coefficient of 0.708, indicating that hardness can significantly influence the sensory evaluation of texture. Cluster analysis based on sensory evaluation and puncture determination could divide the germplasm resources of crisp pear into five texture categories: loosen, crunchy, crisp, tight–crisp, and dense. A comprehensive texture score model, constructed by principal component analysis, showed consistency with sensory evaluation scores and proved that the combination of a puncture test and sensory evaluation is the best way to identify and evaluate the texture of crisp pear. Further analysis of the influencing factors of flesh texture showed that fruit maturity and shelf life had significant effects on flesh quality. This study provides an important reference for the standardization, evaluation, and utilization of crisp pear variety resources. Full article

The “Qixiadaxiangshui” pear (Pyrus bretschneideri Rehd.1) is a highly valued cultivar known for its crisp texture, abundant juice, and rich aroma. In this study, we reported the first complete chloroplast genome sequence of the “Qixiadaxiangshui” pear, which is 159,885 bp in length with a GC content of 36.58%. The genome exhibits a typical circular quadripartite structure, comprising a large single-copy region (LSC), a small single-copy region (SSC), and a pair of inverted repeat regions (IRs). A total of 131 genes were identified, including 84 protein-coding genes, 8 rRNA genes, and 37 tRNA genes. We also identified 209 simple sequence repeats (SSRs) and several mutation hotspots, such as ndhC-trnM-CAU and trnR-UCU-atpA, which can be applied in molecular identification and phylogenetic studies of Pyrus. Comparative genomic analysis showed high conservation among ten pear cultivars. Phylogenetic analysis indicated that the “Qixiadaxiangshui” pear is closely related to germplasm Dangshansuli, Wonwhang, and Yali, suggesting a recent common ancestor. These findings provided valuable insights into the genetic diversity and evolutionary dynamics of the Pyrus species and contribute to the conservation and breeding of pear germplasm resources. Full article

Sugar content is an essential indicator for evaluating crisp pear quality and categorization, being used for fruit quality identification and market sales prediction. In this study, we paired a support vector machine (SVM) algorithm with genetic algorithm optimization to reliably estimate the sugar content in crisp pears. We evaluated the spectral data and actual sugar content in crisp pears, then applied three preprocessing methods to the spectral data: standard normal variable transformation (SNV), multivariate scattering correction (MSC), and convolution smoothing (SG). Support vector regression (SVR) models were built using processing approaches. According to the findings, the SVM model preprocessed with convolution smoothing (SG) was the most accurate, with a correlation coefficient 0.0742 higher than that of the raw spectral data. Based on this finding, we used competitive adaptive reweighting (CARS) and the continuous projection algorithm (SPA) to select key representative wavelengths from the spectral data. Finally, we used the retrieved characteristic wavelength data to create a support vector machine model (GASVR) that was genetically tuned. The correlation coefficient of the SG–GASVR model in the prediction set was higher by 0.0321 and the root mean square prediction error (RMSEP) was lower by 0.0267 compared with those of the SG–SVR model. The SG–CARS–GASVR model had the highest correlation coefficient, at 0.8992. In conclusion, the developed SG–CARS–GASVR model provides a reliable method for detecting the sugar content in crisp pear using hyperspectral technology, thereby increasing the accuracy and efficiency of the quality assessment of crisp pear. Full article

Breeding programmes count on stable trained panels that support breeding evaluation selections. This work aimed to evaluate the performance of a small expert panel in the join IRTA-PFR breeding programme to validate its use in the sensory assessments of fruit pear genotypes during the selection process. A breeding F1 population of 80 pear seedlings from this programme was used. Descriptors and standard references used for sensory evaluations of pear attributes were previously defined by the four members of the expert panel. A General Procrustes Analysis (GPA) was applied to analyse the relations between instrumental and sensory traits. The results showed a good relationship between sensory attributes such as firmness and crispness with penetrometer measures. A high correlation was also found between sensory sourness and titratable acidity (TA). Panel performance was evaluated in terms of reproducibility, homogeneity, and panel consonance. The results indicated that the experts were very consistent and had a good performance. The work demonstrates, for the first time, that a small expert trained panel could be efficiently used in pear breeding programmes and allows for the selection process in a more economical and available way in contrast to the larger sensory panels conventionally used. Full article

‘Shannongsu’ and ‘Xincixiang’ were two new late-ripening pear cultivars with high quality, that were bred by our team. In order to clear the postharvest storage characteristics, mature pears were collected and stored at room temperature. Several fruit characteristics were evaluated over time, such as firmness, ethylene release rate, content of aroma components, softening-related enzyme activity, and gene expression. Both ‘Shannongsu’ and ‘Xincixiang’ were crisp and juicy stored after 60 d at room temperature, which exhibited excellent storage characteristics. The storability may be comprehensive result of low levels of ethylene production, aroma synthesis, softening-related activities, and gene expression. The research cleared the storage characteristics of ‘Shannongsu’ and ‘Xincixiang’ at room temperature for the first time, which will provide scientific theoretical guidance for fruit production and marketing. Full article

The Cuiguan pear is called “June snow” and the skin is thin; the meat is crisp and juicy; the taste is thick and fresh; and the juice is rich and sweet. In this study, the volatile organic compounds and the sensory and physicochemical parameters of the Cuiguan pear from four different regions of China (Sichuan (SC), Shangdong (SD), Chongming (CM), Zhuanghang (ZH)) were assessed. The highest differences in the physicochemical parameters were observed between four regions. The volatile fingerprints of GC-IMS showed great differences in the volatile of the Cuiguan pear, which suggested that the aroma of pears could be largely impacted by origin areas. (E)-ethyl-2-hexenoate can be used to distinguish between the ‘CM’ and pears from other regions. High contents of 2-heptanone, 1-pentanol, 1-butanol, 3-methylbutanol, butyl 2-methylbutanoate, heptyl acetate and butyl acetate were observed in the ‘SD’. Dimethyl trisulfide, 6-methyl-5-hepten-2-one, 3-hydroxy-2-butanone, 1-penten-3-one, beta-pinene, γ-terpinene, propanal, (e)-2-pentenal, (e)-2-heptenal, 1-pentanol and 3-methyl-1-pentanol were primarily contained in the ‘ZH’. Principal component analysis showed that there was very good discrimination based on the information obtained from GC-IMS for four samples. These findings were in agreement with the sensory analysis. In the opinion of the respondents to the consumer test, ‘ZH’ resulted in the most appreciated sample based on the average scores of the acceptability. This study provides some reference for the development and utilization of the Cuiguan pear. Full article

To improve the accuracy of discrete element simulation parameters for the mechanized picking and collection of pears, the study calibrated the simulation parameters of pears by the method of combining a physical experiment and simulation. Based on the intrinsic parameters of four kinds of pears (Snow pears, Crisp pears, Huangguan pears and Qiuyue pears), their simulation models were constructed by the Hertz-Mindlin with a bonding model. The simulation parameters between pears and the contact material (PVC, EVA foam material) were calibrated by the methods of free fall collision, inclined sliding and rolling, respectively. The experiments of pear accumulation angle were carried out. It was obtained to process the image of pears with Matrix Laboratory software. In order to determine the optimal value interval of influencing factors of the pear accumulation angle, the steepest ascent experiment was carried out. Considering the coefficient of collision recovery, the coefficient of static friction and the coefficient of rolling friction between pears, five-level simulation experiments of the pear accumulation angle were designed for each factor by the method of orthogonal rotation combination. The regression model of the error between the measured value and the simulated value of the pear accumulation angle was established, and the influence of three factors on the pear accumulation angle was analyzed. The results showed that the static friction coefficient and rolling friction coefficient between pears have significant effects on the pear accumulation angle. Therefore, the optimal model of minimum error was constructed according to constraint condition, and the coefficient of collision recovery, coefficient of static friction and coefficient of rolling friction between pears were obtained. The accumulation angle verification experiments were carried out by the method of bottomless barrel lifting. The results showed that the relative error between the simulated and measured accumulation angle of four kinds of pears were 1.42%, 1.68%, 2.19% and 1.83%, respectively, which indicated that the calibrated simulation parameters were reliable. The research can provide a basis for the design and parameters optimization of harvesting machinery of pears. Full article

Intestinal symbiotic bacteria have played an important role in the digestion, immunity detoxification, mating, and reproduction of insects during long-term coevolution. The oriental fruit moth, Grapholita molesta, is an important fruit tree pest worldwide. However, the composition of the G. molesta microbial community, especially of the gut microbiome, remains unclear. To explore the differences of gut microbiota of G. molesta when reared on different host plants, we determined the gut bacterial structure when G. molesta was transferred from an artificial diet to different host plants (apples, peaches, nectarines, crisp pears, plums, peach shoots) by amplicon sequencing technology. The results showed that Proteobacteria and Firmicutes are dominant in the gut microbiota of G. molesta. Plum-feeding G. molesta had the highest richness and diversity of gut microbiota, while apple-feeding G. molesta had the lowest. PCoA and PERMANOVA analysis revealed that there were significant differences in the gut microbiota structure of G. molesta on different diets. PICRUSt2 analysis indicated that most of the functional prediction pathways were concentrated in metabolic and cellular processes. Our results confirmed that gut bacterial communities of G. molesta can be influenced by host diets and may play an important role in host adaptation. Full article