Search Results (152)

Milk jujube has become an increasingly popular tropical fruit. The sugar content, which is commonly represented by the soluble solid content (SSC), is a key indicator of the flavor, internal quality, and market value of milk jujubes. Traditional methods for assessing SSC are time-consuming, labor-intensive, and destructive. These methods fail to meet the practical demands of the fruit market. A rapid, stable, and effective non-destructive detection method based on visible/near-infrared (Vis/NIR) spectroscopy is proposed here. A Vis/NIR reflectance spectroscopy system covering 340–1031 nm was constructed to detect SSC in milk jujubes. A structured spectral modeling framework was adopted, consisting of outlier elimination, dataset partitioning, spectral preprocessing, feature selection, and model construction. Comparative experiments were conducted at each step of the framework. Special emphasis was placed on the impact of outlier detection and dataset partitioning strategies on modeling accuracy. A data-augmentation-based unsupervised anomaly sample elimination (DAUASE) strategy was proposed to enhance the data validity. Multiple data partitioning strategies were evaluated, including random selection (RS), Kennard–Stone (KS), and SPXY methods. The KS method achieved the best preservation of the original data distribution, improving the model generalization. Several spectral preprocessing and feature selection methods were used to enhance the modeling performance. Regression models, including support vector regression (SVR), partial least squares regression (PLSR), multiple linear regression (MLR), and backpropagation neural network (BP), were compared. Based on a comprehensive analysis of the above results, the DAUASE + KS + SG + SNV + CARS + SVR model exhibited the highest prediction performance. Specifically, it achieved an average precision (AP_p) of 99.042% on the prediction set, a high coefficient of determination (R_P²) of 0.976, and a low root-mean-square error of prediction (RMSEP) of 0.153. These results indicate that Vis/NIR spectroscopy is highly effective and reliable for the rapid and non-destructive detection of SSC in milk jujubes, and it may also provide a theoretical basis for the practical application of rapid and non-destructive detection in milk jujubes and other jujube varieties. Full article

Flavonoids are an important type of bioactive substance contained in jujubes. Flavonol synthase (FLS) is a key enzyme for the synthesis of flavonoids such as flavonols and anthocyanins. To study the biological functions of FLS in jujubes, we cloned the ZjFLS gene; analyzed its physicochemical properties and evolutionary relationships; and then conducted an expression characteristic analysis, subcellular localization, prokaryotic expression and heterologous overexpression in Arabidopsis thaliana. The results showed that the length of ZjFLS is 951 bp, and it encodes 316 amino acids. A sequence analysis revealed that ZjFLS exhibited a high degree of conservation in evolution. The results of a qRT-PCR analysis indicated that the ZjFLS gene could be expressed in different tissues of jujube: the expression level was the highest in the leaves, followed by the flowers, and the lowest was in the fruits. Within these expression levels, it was higher in young leaves than in mature leaves and higher in the white-ripe-stage fruits than in the semi-red-stage fruits. Subcellular localization indicated that the ZjFLS gene was located in the nucleus, cytoplasmic matrix, and cytoplasmic membrane. Our research findings show that the ZjFLS protein can be induced and obtained in the prokaryotic expression system and successfully purified. It mainly exists in the form of inclusion bodies and has a relatively low content in the soluble supernatant. The total flavonoid content of Arabidopsis thaliana strains with a heterologous overexpression of the ZjFLS gene was significantly higher than that of the wild type, confirming that the ZjFLS gene can promote the biosynthesis of flavonoid substances. Full article

Plants dynamically regulate ions in the tree to defend against abiotic stresses such as drought and saline-alkali, However, it is not clear how ‘Junzao’ jujube regulates ions to maintain a normal life cycle under saline-alkali stress. Therefore, in this study, the roots of 10-year old steer jujube trees were watered using a saline and alkaline gradient solution simulating the main salt (NaCl) and alkali (NaHCO₃) of Aral with NaCl:NaHCO₃ = 3:1 gradient of 0, 60, 180, and 300 mM, and three jujube trees with uniform growth were taken as samples in each treatment plot, and the ion contents of potassium (K), sodium (Na), calcium (Ca), magnesium (Mg), iron (Fe), manganese (Mn), zinc (Zn) and carbon (C) in each organ of the fruit at the dot red period (S1) and full-red period (S2) were determined, in order to elucidate the relationship between physiological adaptation mechanisms of saline-alkali tolerance and the characteristics of mineral nutrient uptake and utilisation in jujube fruit. The results showed that under saline-alkali stress, Na was stored in large quantities in the roots, Ca and Mg in the perennial branches at S1, Na and Fe in the leaves at S2, and K, Mg and Mn in the perennial branches. There was no significant difference in the distribution of C content in various organs of ‘Junzao’. Compared with CK (0 mM), under salinity stress, the K content in the leaves was significantly reduced at S1 and S2, and the K/Na ratios remained > 1.0. At S2, under medium and high concentrations of saline-alkali stress (180–300 mM), the K/Na is less than 1, and the ionic homeostasis was disrupted, and the leaves die and fall off, and the Na is excreted from the body. The selective transport coefficients SK/Na, SCa/Na and SMg/Na from root to leaf showed a downward trend at S1, but still maintained positive transport capacity. At S2, this stage is close to leaf fall, the nutrient transport coefficient is less than 1, and a large amount of nutrients are returned to the perennial branches and roots occurred. These results indicated that the mechanism of nutrient regulation and salt tolerance in jujube trees was different at different growth stages. Full article

To elucidate the molecular mechanisms that underlie jujube (Ziziphus jujuba) flavor synthesis, we integrated transcriptomic and metabolomic analyses on the ‘Lingwuchangzao’ cultivar across seven developmental stages. Our multi-omics approach detected 750 metabolites, categorized into 11 primary and 35 secondary classes, with K-means clustering revealing significant stage-specific variations in sugars, alcohols, and organic acids. KEGG enrichment analysis identified differentially expressed genes (DEGs) in key metabolic pathways, including carbohydrate metabolism and plant hormone signal transduction, showing dynamic changes during development. Weighted gene co-expression network analysis (WGCNA) further pinpointed gene networks related to starch/sucrose and carbon metabolism, and eight novel genes linked to starch and fatty acid metabolism. Notably, the white ripening stage (BS) emerged as the critical phase for flavor compound accumulation, offering new molecular insights and targets for quality improvement. Full article

The Chinese jujube (Ziziphus jujuba Mill.), an economically significant fruit tree native to China, is valued for both fresh and dried uses. In plants, 2n gametes serve as the fundamental basis for creating a sexual polyploid germplasm. This study investigated the 2n gametogenesis frequency in triploid hybrid jujubes through meiotic analysis of the hybrid strain Q161 and a two-year pollen analysis on hybrid progeny, assessing the natural 2n pollen frequencies to identify a high-2n-pollen germplasm and revealing the occurrence of 2n pollen. Meiotic analysis of the triploid hybrid Q161 (2n = 36) revealed cytological anomalies, including binucleate cells (22.80% abnormal tetrads), with natural 2n pollen production rates reaching 4.00% and 4.67% over two consecutive years. Scanning electron microscopy (SEM) revealed that the 2n pollen exhibited pronounced exine ornamentation with cerebroid sculpturing and tubercle-like structures at the apertures. Analysis of the triploid progeny for two consecutive years demonstrated a pollen viability of 30.45% and 23.83% (CV: 19. 39–29.69%), with the mean 2n pollen frequencies of 22.52% and 7.64%, peaking at 52.16% and 28.95% in elite individuals. Six triploid germplasm accessions with naturally elevated 2n pollen frequencies were identified. Under natural conditions, a triploid hybrid germplasm in Chinese jujube produces 2n pollen grains due to abnormal meiotic behavior, and a natural triploid germplasm with high pollen productivity was identified. This research provides a critical theoretical foundation for sexual polyploid breeding strategies. Full article

Traditional biochemical analysis methods are not only resource-intensive and time-consuming, but are increasingly inadequate for meeting the demands of modern production and quality testing. In recent years, hyperspectral imaging (HSI) technology has been widely applied as a non-destructive detection method for fruit and vegetable quality assessment. This study, based on HSI technology, systematically investigates the distribution patterns of jujube quality parameters under various drying temperature conditions. It focuses on analyzing six key quality indicators: L*, a*, b*, soluble solid content (SSC), hardness, and moisture content. HSI was used to acquire reflectance (R), absorbance (A), and Kubelka–Munk (K-M) spectral data of jujubes at various drying temperatures, followed by several spectral preprocessing methods, including standard normal variate (SNV), baseline correction (baseline), and Savitzky–Golay first derivative (SG1st). Subsequently, a nonlinear support vector regression (SVR) model was used to perform regression modeling for the six quality parameters. The results demonstrate that the SG1st preprocessing method significantly enhanced the predictive capability of the model. For the predictions of L*, a*, b*, SSC, hardness, and moisture content, the best inversion models achieved coefficients of determination $R_p^2$ of 0.9972, 0.9970, 0.9857, and 0.9972, respectively. To further enhance modeling accuracy, deep learning models such as bidirectional long short-term memory (BiLSTM), bidirectional gated recurrent unit (BiGRU), and convolutional neural network–bidirectional gated recurrent unit (CNN-BiGRU) were introduced and compared comprehensively under the optimal spectral preprocessing conditions. The results demonstrate that deep learning models significantly improved modeling accuracy, with the CNN-BiGRU model performing particularly well. Compared to the SVR model, the $R_p^2$ values for L*, a*, b*, SSC, hardness, and moisture increased by 0.005, 0.007, 0.008, 0.011, 0.007, and 0.006, respectively; the $RPD$ values increased by 0.036, 0.04, 0.26, 0.462, 0.428, and 0.216. This study provides important insights into the further application of HSI technology in the quality monitoring and optimization of the jujube drying process. Full article

The long-term arid climate in Xinjiang poses a major challenge to sustainable jujube production. In this study, we systematically evaluated the impacts of deficit irrigation (DI) by comparing a full irrigation control (CK) with six DI treatments—mild DI (75% CK) and severe DI (50% CK) water deficits applied during either flowering + fruit setting or fruit enlargement stages. The key findings demonstrate that flowering + fruit setting DI effectively balances water conservation with productivity. Mild DI (75% CK) during flowering + fruit setting reduced irrigation by 72 mm while maintaining near-optimal photosynthesis (95% recovery post-rewatering) and significantly improving fruit quality (5.49–10.28% higher sugar content, 3.40–5.06% larger fruit volume), despite a moderate 4.22–11.36% yield reduction. In contrast, severe DI caused irreversible physiological stress (only 75% photosynthetic recovery), and fruit-enlargement-stage DI uniformly compromised both yield and fruit size. An economic analysis confirmed flowering + fruit setting mild DI as optimal, generating 17,139–20,550 RMB·ha⁻¹ profit through enhanced water use efficiency (WUE) and premium-quality fruit production. PLS-PM validation revealed that targeted flowering + fruit setting water deficit suppresses vegetative overgrowth while optimizing source–sink relationships, achieving a 23–31% WUE improvement without sacrificing marketable yield. Thus, mild DI during flowering + fruit setting is a climate-smart irrigation strategy for Xinjiang’s jujube industry, resolving water scarcity challenges with economic viability. Full article

A field experiment was conducted in 2023 and 2024 in Beijing, China, to investigate effects of soil water stress, applied before the fruit ripening stage, on the fruit total soluble solid accumulation and cracking of jujube trees. The experiment consisted of two variation factors: (a) irrigation levels (MDI and SDI, applied 80% and 50% of the irrigation volume, respectively) and (b) growth stages (stage 1, before the fruit enlargement stage, and 2, before the fruit ripening stage). The two irrigation levels were applied at each growth stage in a 2 × 2 factorial arrangement, plus a control treatment receiving 100% irrigation volume, resulting in five treatments per replicate. The findings indicated that pre-enlargement stage water stress enhanced the accumulation of total soluble solid content within fruits, which subsequently promoted faster fruit growth in from the early- to mid-August period. However, by late August, both the total soluble solid content and fruit growth rates had declined, thereby mitigating the risk of fruit cracking. During the fruit enlargement stage, the fruit total soluble solid content in SDI-2 increased by approximately 24% by the end of August compared to the control, leading to lower osmotic potential and higher turgor pressure during the following ripening stage. As skin growth ceased, high turgor pressure caused fruit cracking at the following ripening stage. The SDI-2 treatment demonstrated a fruit cracking rate approximately 1.5 times higher than that of the control. Pearson correlation analysis also indicated that fruit cracking was positively correlated with total soluble solids accumulated in August. Meanwhile, the yield of SDI-2 was reduced about 18%. Therefore, the adequate soil moisture during the fruit enlargement stage was crucial to minimize jujube fruit cracking and economic losses. Meanwhile, the deficit irrigation applied during the pre-enlargement stage could effectively conserve water resources and mitigate the occurrence of extensive jujube fruit cracking. Full article

Randomised controlled trials involving healthy participants were conducted to investigate the impact of cooking and ingestion patterns on the physiological response and preloading effect of air-dried jujube (AJ). The participants’ postprandial glycaemic and insulinemic responses were tested after ingestion of cooked or uncooked air-dried jujube containing 50 g (as a sole food source) or 15 g (as a preload food prior to a rice meal) of available carbohydrates. Compared with the uncooked AJ, the cooked air-dried jujube (CAJ) induced a 34.5% higher glycaemic peak, 57.1% greater glycaemic variability, and a 159.1% larger negative area under the glycaemic response curve when ingested as the only food in a meal. When eaten as a preload prior to a rice meal, the CAJ reduced the postprandial glycaemic peak by 25.17%. The CAJ preload enhanced insulin production in the 15 min after preloading but did not increase the total amount of postprandial insulin secretion. The result suggests that when taken as preload, the loose matrix of cooked fruits may exhibit glycaemic benefits by eliciting early insulin production and may therefore be conducive to the blood glucose management of a carbohydrate-laden meal. Full article

This study presents an improved detection model based on the YOLOv5 (You Only Look Once version 5) framework to enhance the accuracy of Jishan jujube detection in complex natural environments, particularly with varying degrees of occlusion and dense foliage. To improve detection performance, we integrate an SE (squeeze-and-excitation) attention module into the backbone network to enhance the model’s ability to focus on target objects while suppressing background noise. Additionally, the original neck network is replaced with a BIFPN (bi-directional feature pyramid network) structure, enabling efficient multiscale feature fusion and improving the extraction of critical features, especially for small and occluded fruits. The experimental results demonstrate that the improved YOLOv5 model achieves a mean average precision (mAP) of 96.5%, outperforming the YOLOv3, YOLOv4, YOLOv5, and SSD (Single-Shot Multibox Detector) models by 7.4%, 9.9%, 2.5%, and 0.8%, respectively. Furthermore, the proposed model improves precision (95.8%) and F1 score (92.4%), reducing false positives and achieving a better balance between precision and recall. These results highlight the model’s effectiveness in addressing missed detections of small and occluded fruits while maintaining higher confidence in predictions. Full article

Mycotoxin contamination in medicinal plants can lead to toxicity, reduced therapeutic efficacy, and economic losses. This contamination has emerged as a significant issue, drawing attention from researchers and research centers worldwide. Over recent decades, numerous analytical studies have addressed mycotoxin contamination in these herbs, evaluating various methods to determine their presence quantitatively and qualitatively. While several reviews have summarized these studies, they often overlook a comprehensive exploration of the mechanisms and influencing factors of mycotoxin contamination in medicinal herbs. Therefore, this review aims to delve into the mechanisms of aflatoxin and ochratoxin contamination in some of the most widespread medicinal herbs, including jujube fruits, lotus seeds, and licorice roots. The factors influencing these mechanisms were also examined, including the physical composition and maturity stages of the herbs. This review concluded that aflatoxin and ochratoxin A contamination of medicinal herbs involves complex interactions between the herbs’ natural defenses, fungal pathogenicity, chemical composition, physical characteristics, and individual plant differences at various maturity stages. Understanding these mechanisms of contamination, and their association with maturity, nutrient profile, and physical development, advances our comprehension of mycotoxin contamination in medicinal herbs. Full article

The susceptibility and mechanism of aflatoxin (AF) contamination in Ziziphus jujuba var. spinosa, whose seeds are important for medicinal use, were evaluated in this study. First, the susceptibility of intact fruits, classified into four maturity groups, to AF accumulation was assessed through artificial contamination with an aflatoxigenic Aspergillus flavus strain. AF analysis revealed that mid-mature fruits were highly susceptible to AF contamination. Next, AF accumulation in seed parts was examined by artificially inoculating A. flavus on intact fruits, showing AF presence in seeds after 30 days of incubation. The susceptibility of jujube kernels to AF accumulation in seed parts was then studied. The artificial inoculation of A. flavus on kernels, classified into three groups based on the pedicel condition, showed no correlation between AF contamination and the pedicel condition, with large fluctuations within each group. Finally, the effect of the hilar region morphology on AF contamination in seeds was investigated. The microscopic investigation of artificially contaminated seeds and AF quantification revealed that variations in AF concentration were linked to differences in the hilar region morphology. Full article

Red jujube is a nutritious food, known as the “king of all fruits”. The quality of Chinese red jujube is closely associated with its place of origin. To classify Chinese red jujube more correctly, based on the combination of adaptive boosting (Adaboost) and common vectors linear discriminant analysis (CLDA), Adaboost-CLDA was proposed to classify the near-infrared (NIR) spectra of red jujube samples. In the study, the NIR-M-R2 spectrometer was employed to scan red jujube from four different origins to acquire their NIR spectra. Savitzky–Golay filtering was used to preprocess the spectra. CLDA can effectively address the “small sample size” problem, and Adaboost-CLDA can achieve an extremely high classification accuracy rate; thus, Adaboost-CLDA was performed for feature extraction from the NIR spectra. Finally, K-nearest neighbor (KNN) and Bayes served as the classifiers for the identification of red jujube samples. Experiments indicated that Adaboost-CLDA achieved the highest identification accuracy in this identification system for red jujube compared with other feature extraction algorithms. This demonstrates that the combination of Adaboost-CLDA and NIR spectroscopy significantly enhances the classification accuracy, providing an effective method for identifying the geographical origin of Chinese red jujube. Full article

The spectral information extracted from hyperspectral images is characterized by redundancy and complexity, while the spectral morphological features extracted from the spectral information help to simplify the data and provide rich information about the material composition. This study is based on using spectral morphological features to quantitatively detect the water content of winter jujubes, and it extends the research scope to the composite effect of spectral morphological features on the basis of previous research. Firstly, a multiple linear regression analysis was carried out on different characteristic bands. Secondly, the multiple regression terms with high significance levels were used as the characteristic variables to be fused with the extracted characteristic wavelength variables for the data fusion. Finally, a partial least squares model was established for the water content of the winter jujubes. The results of the study show that a quantitative relationship can be established between the spectral morphology characteristics and the water content of winter jujubes. The coefficients of determination of the regression equations under the characteristic bands with center wavelengths of 1024 nm, 1146 nm, 1348 nm, and 1405 nm were 0.8449, 0.7944, 0.7479, and 0.9477, respectively. After fusing the spectral morphological features, the partial least squares modeling effects were all improved. The optimal model was the fusion model at a center wavelength of 1146 nm with a correlation coefficient of 0.9942 for the calibration set and 0.8698 for the prediction set. The overall results showed that the wave valley is more reflective of the fruit quality, and the morphological characteristics of the wave valley are more suitable than those of the wave peak for the quantitative detection of the moisture content of winter jujubes. Full article

Low-temperature storage is an effective method to extend the shelf life of harvested winter jujube fruit; however, the quality of winter jujube fruit decreases after refrigeration. To enhance the quality of winter jujube with minimum qualitative deterioration during cold storage, this study investigated the effects of different melatonin concentration (100, 150, and 200 µmol/L) treatments on the storage quality of winter jujube (during the white ripening stage) at 0 ± 1 °C (RH, 90 ± 5%) for 90 days. The relative indexes of the fruit quality and the antioxidant system were measured every 15 days. The results showed that different concentrations of melatonin treatments could maintain the fruit’s firmness, retard the fruit’s redness, and inhibit the decrease in weight, total soluble solid (TSS), titratable acidity (TA), and the contents of total phenols, flavonoids, glutathione, and ascorbic acid; they also inhibited the increase in relative conductivity, malondialdehyde (MDA), and hydrogen peroxide (H₂O₂) content of jujube fruits and enhanced antioxidant enzyme activities (superoxide dismutase (SOD), catalase (CAT), ascorbate peroxidase (APX), glutathione reductase (GR), and peroxidase (POD)). As a whole, the 200 µmol/L melatonin treatment had the best effect. Therefore, melatonin treatment can maintain the cold-stored quality of postharvest winter jujube by improving its antioxidant capacity. Full article