Search Results (387)

In the arid cultivation region of Xinjiang, China, shrinkage disease severely compromises the quality, yield, and market value of jujube. Published research has achieved high accuracy in detecting larger lesions using RGB imaging and hyperspectral imaging (HSI). However, these methods lack sensitivity in detecting early and subtle symptoms of disease. In this study, a multi-source data fusion strategy combining RGB imaging and HSI was proposed for non-destructive and high-precision detection of early-stage jujube shrinkage disease. Firstly, a total of 317 fruits of the ‘Junzao’ cultivar were collected during multiple stages of natural infection, covering early-stage shrinkage disease detection across different growth stages, including both green and mature red fruits. Secondly, morphological features were extracted from RGB images in multiple dimensions, while a three-stage feature selection strategy combining Principal Component Analysis (PCA), the Successive Projections Algorithm (SPA), and the Genetic Algorithm (GA) was implemented to identify four key wavelengths from HSI. Thirdly, a hybrid convolutional neural network-multilayer perceptron (CNN-MLP) architecture was constructed, with dynamic feature weighting employed to achieve effective multimodal fusion and optimize detection performance. Experimental results demonstrated that compared to the MLP and CNN models, the proposed method achieved approximately 8.0% and 5.4% improvements in accuracy and 38.6% and 32.4% improvements in F1 scores, respectively. It offers a robust and scalable solution for early disease detection and postharvest quality assessment in jujube production. Full article

Severe leaf galling by the jujube gall midge Dasineura jujubifolia (Diptera: Cecidomyiidae) compromises photosynthesis and yield in arid-zone jujube orchards, yet Xinjiang-specific evidence to guide biological control has been scarce. Here we provide the first systematic characterization in Xinjiang (Hami, China) of D. jujubifolia and its parasitoid complex, integrating region-specific field surveys with gall dissection and laboratory assays. We documented five parasitoid wasps, including two species newly recorded in China—Pseudotorymus samsatensis (Hymenoptera: Torymidae) and Baryscapus adalia (Hymenoptera: Eulophidae). In Hami, the host completed 4–5 generations per year with a 19–24-day generation time. Functional roles were partitioned: P. samsatensis (dominant), Systasis parvula (Hymenoptera: Pteromalidae), and B. adalia were larval ectoparasitoids, whereas Aprostocetus sp. (Hymenoptera: Eulophidae) and Synopeas sp. (Hymenoptera: Platygastridae) were endoparasitoids. Time-series data revealed tight temporal synchrony between P. samsatensis and host peaks. Controlled experiments quantified daily emergence rhythms, diet-dependent adult longevity, and sex ratios, providing parameters to inform release timing and conservation in biological control programs. Collectively, these findings establish management-ready baselines for D. jujubifolia and its parasitoids in arid jujube systems and support conservation-oriented, reduced-pesticide integrated pest management (IPM). Full article

Magnetic biochar (Zn/Fe-BC) was prepared from jujube branches via an impregnation pyrolysis–coprecipitation technique to eliminate Cr(VI) from water. ZnFe₂O₄ was introduced through ZnCl₂-based impregnation and pyrolysis, which can regulate the microstructure of hydrocarbon frameworks. Furthermore, FeSO₄·7H₂O was used as the precursor for co-precipitation to embed Fe₃O₄ into the material, improving its reducibility and magnetism. The results demonstrated that Zn/Fe-BC exhibited excellent Cr(VI) removal efficiency. Under optimal conditions (an initial Cr(VI) concentration of 50 mg/L, pH 2, and an adsorbent dosage of 2 g/L), the maximum adsorption capacity of Zn/Fe-BC reached 27.85 mg/g, which was significantly higher than that of unmodified biochar (23.20 mg/g). Following five cycles of adsorption and desorption, the desorption efficiency was still higher than 60.35%. The following were the inhibitory effects of coexisting anions on the elimination of Cr(VI): CO₃²⁻ > PO₄³⁻ > SO₄²⁻ > NO₃⁻. According to kinetic and isothermal adsorption experiments, the adsorption process adhered to the Freundlich isotherm and followed a pseudo-second-order kinetic model, indicating a multilayer adsorption process. Cr(VI) removal by Zn/Fe-BC was driven by physical adsorption and chemical reduction, involving a synergistic combination of electrostatic attraction, reduction, complexation, precipitation, and pore filling. These findings demonstrate the potential of the Zn/Fe-BC magnetic biochar as an effective adsorbent for Cr(VI) remediation in water treatment applications. Full article

The efficient and non-destructive inspection of the chlorophyll content of grey jujube leaf is of great significance for its growth surveillance and nutritional diagnosis. Near-infrared spectroscopy combined with chemometric methods provides an effective approach to achieve this goal. This study took grey jujube leaves as the research object, systematically collected near-infrared spectral data in the range of 4000–10,000 cm⁻¹, and simultaneously measured their soil and plant analyzer development (SPAD) value as a reference index for chlorophyll content. Through various pretreatment and their combination methods on the original spectrum—smooth, standard normal variable transformation (SNV), first derivative (FD), second derivative (SD), smooth + first derivative (Smooth + FD), smooth + second derivative (Smooth + SD), standard normal variable transformation + first derivative (SNV + FD), standard normal variable transformation + second derivative (SNV + SD)—the effects of different methods on the quality of the spectrum and its correlation with SPAD value were compared. The competitive adaptive reweighted sampling algorithm (CARS) was adopted to extract the characteristic wavelength, aiming to reduce data dimensionality and optimize model input. Both BP neural network and RBF neural network prediction models were established, and the model performance under different training functions was compared. The results indicate that after Smooth + FD pretreatment, followed by CARS screening of the characteristic wavelength, the BP neural network model trained using the LBFGS algorithm demonstrated the best performance, with its coefficient of determination (R²) of 0.87 (training set) and 0.85 (validation set), root mean square error (RMSE) of 1.36 (training set) and 1.35 (validation set), and residual prediction deviation (RPD) of 2.81 (training set) and 2.56 (validation set) showing good prediction accuracy and robustness. Research indicates that by combining near-infrared spectroscopy with feature extraction and machine learning methods, the rapid and non-destructive inspection of the grey jujube leaf SPAD value can be achieved, providing reliable technical support for the real-time monitoring of the nutritional status of jujube trees. Full article

RipenessGAN is a novel Generative Adversarial Network (GAN) designed to generate synthetic images across different ripeness stages of jujubes (green fruit, white ripe fruit, semi-red fruit, and fully red fruit), aiming to provide balanced training data for diverse applications beyond classification accuracy. This study addresses the problem of data imbalance by augmenting each ripeness stage using our proposed Growth Day Embedding mechanism, thereby enhancing the performance of downstream classification models. The core innovation of RipenessGAN lies in its ability to capture continuous temporal transitions among discrete ripeness classes by incorporating fine-grained growth day information (0–56 days) in addition to traditional class labels. The experimental results show that RipenessGAN produces synthetic data with higher visual quality and greater diversity compared to CycleGAN. Furthermore, the classification models trained on the enriched dataset exhibit more consistent and accurate performance. We also conducted comprehensive comparisons of RipenessGAN against CycleGAN and class-conditional diffusion models (DDPM) under strictly controlled and fair experimental settings, carefully matching model architectures, computational resources, training conditions, and evaluation metrics. The results indicate that although diffusion models yield highly realistic images and CycleGAN ensures stable cycle-consistent generation, RipenessGAN provides superior practical benefits in training efficiency, temporal controllability, and adaptability for agricultural applications. This research demonstrates the potential of RipenessGAN to mitigate data imbalance in agriculture and highlights its scalability to other crops. Full article

Harvesting winter jujubes is a key step in production, yet traditional manual approaches are labor-intensive and inefficient. To overcome these challenges, we propose SCC-YOLO, a lightweight method for winter jujube detection, 3D localization, and cross-platform deployment, aiming to support intelligent harvesting. In this study, RGB-D cameras were integrated with an improved YOLOv11 network optimized by ShuffleNetV2, CBAM, and a redesigned C2f_WTConv module, which enables joint spatial–frequency feature modeling and enhances small-object detection in complex orchard conditions. The model was trained on a diversified dataset with extensive augmentation to ensure robustness. In addition, the original localization loss was replaced with DIoU to improve bounding box regression accuracy. A robotic harvesting system was developed, and an Eye-to-Hand calibration-based 3D localization pipeline was implemented to map fruit coordinates to the robot workspace for accurate picking. To validate engineering applicability, the SCC-YOLO model was deployed on both desktop (PyTorch and ONNX Runtime) and mobile (NCNN with Vulkan+FP16) platforms, and FPS, latency, and stability were comparatively analyzed. Experimental results showed that SCC-YOLO improved mAP by 5.6% over YOLOv11, significantly enhanced detection precision and robustness, and achieved real-time performance on mobile devices while maintaining peak throughput on high-performance desktops. Field and laboratory tests confirmed the system’s effectiveness for detection, localization, and harvesting efficiency, demonstrating its adaptability to diverse deployment environments and its potential for broader agricultural applications. Full article

Carpomya vesuviana (Diptera: Tephritidae), a significant invasive forestry pest of Zizyphus crops worldwide, has spread globally across jujube-growing regions, causing substantial yield losses and economic damage. In China, it is classified as both an imported and forestry quarantine pest. Existing risk assessments have primarily focused on the potential geographical distributions (PGDs) of C. vesuviana, but its economic impact on host plants is unknown. Therefore, we used an optimised MaxEnt model based on species distribution records and relevant environmental variables to predict the PGDs of C. vesuviana under current and future climate scenarios. Meanwhile, we used the @RISK stochastic model to assess the economic impact of this pest on the Chinese jujube industry under various scenarios. The results showed that the human influence index (HII), mean temperature of the wettest quarter (Bio8), temperature seasonality (Bio4), and precipitation during the driest month (Bio14) were the significant environmental variables affecting species distribution. Under the current climatic scenario, the total suitable area of C. vesuviana reached 2171.39 × 10⁴ km², which is mainly distributed in southern and western Asia, southern Europe, central North America, western Africa, and eastern South America. Potentially suitable habitats will increase and shift to the middle and high latitudes of the Northern Hemisphere under future climatic scenarios. Under the no-control scenario, C. vesuviana could cause losses of 15,687 million CNY to the jujube industry in China. However, control measures could have saved losses of 5047 million CNY. This study provides a theoretical basis for preventive monitoring and integrated management of C. vesuviana globally and helps reduce its economic impact on the jujube industry in China. Full article

Postharvest Hupingzao jujubes are prone to softening and reddening during storage. To investigate the influence of glycine betaine on the fruit quality of cold-stored jujubes, the jujubes were immersed in a 15 mmol L⁻¹ glycine betaine solution for 10 min, then stored at 0 ± 1 °C for 100 days. The relevant physical and chemical quality indicators were determined every 20 days. The results indicated that glycine betaine treatment effectively maintained fruit firmness, reduced weight loss, slowed down the respiration rate, and lessened the redness of the fruit peel. Compared with the control group, the malondialdehyde and H₂O₂ contents in glycine betaine-treated fruit decreased by 26.65% and 9.04%, respectively. In addition, glycine betaine treatment elevated the contents of non-enzymatic antioxidants, including ascorbic acid, total flavonoids, total phenols, and proanthocyanidins. Meanwhile, the activities of superoxide dismutase, peroxidase, catalase, and ascorbate peroxidase in the jujube fruit were enhanced after glycine betaine treatment. In conclusion, glycine betaine treatment preserved the quality of the jujube fruits by enhancing the antioxidant metabolism. The results establish a scientific basis for the potential application of glycine betaine in postharvest fruit preservation, providing a strategy to mitigate storage-related quality deterioration. Full article

Understanding heavy metal behavior in arid saline soils is critical for phytoremediation in degraded lands. This study investigated metal distribution and plant enrichment in the Tarim Basin using 323 soil and 55 plant samples (Populus euphratica, Tamarix ramosissima, cotton, jujube). Analyses included redundancy analysis (RDA) and bioconcentration factor (BCF) assessments. Key findings reveal that elevated salinity (total salts, TS > 200 g/kg) and alkalinity (pH > 8.5) immobilized As, Cd, Cu, and Zn. Precipitation and competitive leaching reduced metal mobility by 42–68%. Plant enrichment strategies diverged significantly: P. euphratica hyperaccumulated Cd (BCF = 1.59) and Zn (BCF = 2.41), while T. ramosissima accumulated As and Pb (BCF > 0.05). Conversely, cotton posed Hg transfer risks (BCF = 2.15), and jujube approached Cd safety thresholds in phosphorus-rich soils. RDA indicated that pH and total salinity (TS) jointly suppressed metal bioavailability, explaining 57.6% of variance. Total phosphorus (TP) and soil organic carbon (SOC) enhanced metal availability (36.8% variance), with notable TP-Cd synergy (Pearson’s r = 0.42). We propose a dual-threshold management framework: (1) leveraging salinity–alkalinity suppression (TS > 200 g/kg + pH > 8.5) for natural immobilization; and (2) implementing TP control (TP > 0.8 g/kg) to mitigate crop Cd risks. P. euphratica demonstrates targeted phytoremediation potential for degraded saline agricultural systems. This framework guides practical management by spatially delineating zones for natural immobilization versus targeted remediation (e.g., P. euphratica planting in Cd/Zn hotspots) and implementing phosphorus control in high-risk croplands. Full article

Jujube (Ziziphus jujuba Mill.) is an important economic fruit tree in China, and its in vitro culture technology is the key to achieving large-scale seedling cultivation. PGRs (Plant growth regulators) play a central regulatory role in all stages of jujube micropropagation, including explant initiation, proliferation, and rooting. This article provides a comprehensive overview of recent advances in in vitro culture of jujube, with a focus on the recommended exogenous phytohormone ratios, their effects, and underlying regulatory mechanisms across distinct varieties during the key stages such as in vitro culture, shoot proliferation, and root formation. The primary culture of most jujube varieties usually employs the MS medium, and it is recommended that auxin and cytokinin be used in combination. During the initial cultivation stage, the use of NAA (1-naphthaleneacetic acid) or IBA (indole butyric acid) is recommended at concentrations ranging from 0.1 to 1.0 mg/L. At the same time, 6-BA (6-benzylaminopurine) is suggested, with a concentration range of 0.5 to 2.5 mg/L. In the subculture multiplication of most jujube varieties, MS medium is used, and auxin (such as NAA, IBA), and TDZ (thidiazuron) and cytokinin (e.g., 6-BA) are used in combination. The recommended concentration range for auxin remains between 0.1 and 1.0 mg/L, and for cytokinin 6-BA between 0.5 and 2.5 mg/L, while the recommended concentration of TDZ is suggested to be below 0.01 mg/L. Rooting induction for most jujube varieties has predominantly been achieved using 1/2 MS medium, with growth regulator concentrations typically ranging from 0.5 to 3.0 mg/L. Full article

Jujube (Ziziphus jujuba Mill.) is a nutritionally rich and economically significant fruit, highly valuable for its flavor, bioactive compounds, and therapeutic properties. However, it is highly perishable and has a short postharvest lifespan. This review aims to provide knowledge for preserving quality and improving postharvest storage by integrative strategies aimed at extending the shelf life of jujube. The literature was collected from recent peer-reviewed studies on postharvest physiology and handling technologies of jujube fruit. Key physiological factors, influencing postharvest deterioration such as water loss, softening, browning, and decay, are discussed, along with the underlying biochemical and enzymatic mechanisms driving quality decline. Conventional strategies such as cold storage, MAP, and CA effectively slow respiration, delay reddening, and extend storage up to 2–4 months, while emerging approaches such as ozone and cold plasma treatments reduce microbial decay and maintain antioxidant activity. Edible coatings like chitosan, aloe vera, and composites cut weight loss by 20–40%, and chemical regulators such as 1-MCP and calcium dips further delay ripening, preserve firmness, and enhance postharvest quality. Emphasis is placed on integrating innovative technologies with physiological insights to optimize storage conditions, control microbial contamination, and maintain nutritional integrity. The significance of this review lies in integrating physiological insights with innovative preservation methods, offering practical guidance for researchers, growers, and industry stakeholders to achieve sustainable, safe, and market-oriented solutions for jujube storage. Full article

Parkinson’s disease (PD) is a neurodegenerative disease that is closely related to genetic and environmental factors, among which pesticide exposure is considered an important risk factor. Fresh jujube and hawthorn, as widely consumed fruits, may contain pesticide residues, but the potential effects of long-term low-dose intake on PD are not yet clear. This study combines network toxicology and molecular docking technology to elucidate the molecular mechanism of PD induced by residual pesticides in fresh jujube and hawthorn. Firstly, common risk pesticides (such as organophosphates and pyrethroids) in fresh jujube and hawthorn were screened through the database. Subsequently, a “pesticide target—PD” interactive network was constructed using network toxicology to predict key targets and related pathways. Finally, molecular docking technology was used to verify the binding ability of pesticide molecules to PD-related proteins. The results indicate that some pesticides (such as chlorpyrifos and cypermethrin) may increase the risk of PD by affecting lipid metabolism and oxidative stress response. This study provides a new approach for assessing the neurotoxicity of pesticide residues and suggests the need to pay attention to the potential impact of dietary pesticide exposure on PD, providing a scientific basis for food safety regulation and PD prevention strategies. Full article

Moderate ozone exposure has emerged as a sustainable strategy to enhance postharvest quality in perishable fruits. This study investigated the effects of ozone treatment (2.14–19.27 mg/m³) on flat jujube during 70-day cold storage (0 °C). Results demonstrated that following 70 days of storage, the ideal ozone concentration (10.72 mg/m³, T2) led to a decrease in weight loss of 44.8% and preserved 66.7% firmness when compared to the control check (CK) group. The T2 group suppressed the respiration rate and delayed declines in total soluble solids (TSSs) and titratable acid (TA). Mechanistically, ozone enhances enzymatic activity, with T2 elevating superoxide dismutase (SOD), catalase (CAT), and peroxiredoxin (POD) activities while reducing the accumulation of reactive oxygen species (ROS) and lipid peroxidation. Total phenolics and flavonoids in T2 remained 42% and 52% higher than CK at 56 days, correlating with elevated 2,2-Diphenyl-1-picrylhydrazyl (DPPH) and 2,2′-Azinobis-(3-ethylbenzthiazoline-6-sulphonate) (ABTS) scavenging activities. Browning inhibition (25% lower than the CK group) is linked to suppressed polyphenol oxidase (PPO) activity and phenolic oxidation. Principal component analysis (PCA) confirmed ozone’s efficacy in delaying senescence via ROS homeostasis and antioxidant synergy. These findings establish moderate ozone as a novel, eco-friendly intervention to extend jujubes’ shelf life, emphasizing its dual role in quality preservation and oxidative stress regulation. Full article

Saline–alkali soils in southern Xinjiang present significant challenges for sustainable jujube cultivation, necessitating innovative fertilization strategies to improve soil health and enhance fruit quality. This study investigated the synergistic effects of biochar–nitrogen (N) co-application on soil amelioration and the improvement of jujube quality in saline–alkali jujube orchards. A field experiment was conducted using different biochar application rates (0, BC1, BC2) combined with various N fertilizer types (conventional nitrogen N1, N2, UI-N (urease inhibitor), and NI-N (nitrification inhibitor)), which systematically analyzed soil physicochemical properties, nutrient dynamics, enzyme activities, microbial community structure, and jujube fruit yield and quality parameters. The BC1 biochar application rate emerged as the optimal threshold for soil carbon and N sequestration, with BC1 + N2 treatment achieving the highest total carbon and total nitrogen concentrations, representing increases of 12.4% and 21.42%, respectively, compared to controls. Biochar–N co-application significantly enhanced soil available nutrients, with BC1 + UI-N treatment producing the greatest soil organic matter increase within the BC1 group (9.20–14.51% enhancement). Notably, the treatments modulated soil microelement profiles, suppressing potentially toxic Cu and Mn while enhancing the availability of beneficial Mg and Fe. Soil enzyme activities responded differently, with urease and sucrase activities reaching maximum levels under BC2 + N1 and BC1 + UI-N treatments, respectively. Microbial community analysis revealed that biochar–N combinations significantly restructured both bacterial and fungal communities, with BC1 + NI-N treatment demonstrating superior bacterial α-diversity across all indices. Soil enzyme activities exhibited distinct response patterns, with urease and sucrase activities reaching their peak under the BC2 + N1 and BC1 + UI-N treatments, respectively. Moreover, the co-application of biochar (BC1) with N fertilizer significantly improved fruit performance, increasing per-tree yield by 24.23% and fruit vitamin C content by 16.47%, compared to the control. This study demonstrates that moderate biochar application (BC1) combined with urease inhibitor- enhanced N fertilizer (UI-N) represents an optimal fertilization strategy for saline–alkali jujube orchards, achieving simultaneous soil amelioration and fruit quality enhancement through coordinated regulation of soil–microbe–plant interactions. The established quantitative relationships provide a scientific foundation for the implementation of precision agriculture in arid saline–alkali regions, offering significant implications for sustainable specialty fruit production and soil health restoration in environmentally challenged agricultural systems. Full article

Understanding the regulatory mechanisms of water–nitrogen coupling effects on soil–plant–microbe systems in arid regions is crucial for sustainable agricultural development. This study systematically investigated the interactive effects of field capacity (75% vs. 45%) and nitrogen application rates (100 vs. 300 kg ha⁻¹) combined with different enhanced-efficiency nitrogen fertilizers (EENFs) on rhizosphere soil fertility and microbial community structure of Jujube (Ziziphus jujuba Mill.) seedlings through a two-year pot experiment. Two-year-old jujube seedlings were employed with five treatments: NS (urea), NM (urease inhibitor), XH (nitrification inhibitor), W (microbial fertilizer), and CK (control), to analyze soil physicochemical properties and microbial community responses. Soil available N accumulated under high-N/adequate moisture but declined under drought. NM curbed NH₃ volatilization by 32.38–43.22%, while XH increased NH₄⁺-N by 35.76%. Drought raised microbial α-diversity (bacteria + 33.88–37.5%, fungi + 43.62–68.75%). NM demonstrated optimal performance in ammonia volatilization (32.38–43.22% reduction), while XH showed notable efficacy in ammonium-N regulation (35.76% enhancement). Microbial α-diversity exhibited enhanced responses under drought stress, with bacterial and fungal community improvements reaching 33.88–37.5% and 43.62–68.75%. Redundancy analysis showed environmental factors explained more community variance under water stress (bacteria: 79.19→88.76%; fungi: 64.64→92.52%). These findings provide theoretical support for jujube cultivation in arid zones, demonstrate the potential of targeted EENFs, and offer new insights for precision water–fertilizer and microbial management. Full article