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Jujube fruit may rapidly undergo maturity and senescence during storage, seriously affecting its commercialization. The study aimed to evaluate the role of acidic electrolyzed water (AEW) on energy and respiratory metabolism, and senescence in jujube fruit during cold storage. The results indicated that AEW improved ATP content and energy charge via increasing succinate dehydrogenase, cytochrome C oxidase, H+-ATPase, and Ca2+-ATPase activities and delayed jujube fruit senescence. The treatment was found to improve the activities of nicotinamide adenine dinucleotide kinase, 6-phosphogluconate dehydrogenase and glucose-6-phosphate dehydrogenase, and the content of NADPH, and reduce oxidative stress. Transcriptome analysis suggested that AEW regulated the expression of the genes associated with glycolysis, citrate cycle, pentose phosphate pathway, oxidative phosphorylation, ROS metabolism, transcription factors, phenylpropane biosynthesis, cell wall metabolism, and plant hormone signal transduction. Therefore, we concluded that AEW may delay the senescence of postharvest jujube fruit by regulating expression of the relevant genes and metabolic pathways. • AEW treatment promoted energy charge by activating energy metabolism-related enzymes. • AEW reduced cellular peroxidation by regulating pyridine nucleotide homeostasis. • AEW was involved in the regulation of differentially expressed genes associated with senescence. • AEW delayed senescence and maintained good quality of jujube fruit. [ABSTRACT FROM AUTHOR]

A hyperspectral imaging technique was used for acquiring reflectance images to identify common defects (bruise, insect-infestetation and cracks) on jujube fruit. Hyperspectral images of jujubes were evaluated from the regions of interest through principal component analysis (PCA) to select five optimal wavelengths (420,521,636,670,679 nm) from 300 samples in the spectral region of 400–1000 nm and four important wavelength (1028,1118,1359,1466 nm) in the region of 978–1586 nm. Compared with support vector machine (SVM) models, the soft independent modeling of class analogy (SIMCA) models of intact, cracked, bruised, and insect-infested jujubes based on five wavelengths in NIR showed good performance with high classification rates of 96%, 96%, 93.9% and 95.6%, respectively. This research demonstrates the feasibility of implementing hyperspectral imaging for identifying common defects and enhancing the product quality and marketability. [ABSTRACT FROM AUTHOR]

• The R spectra were transformed into two spectral units, A and K-M. • IVISSA algorithm was used to select characteristic wavelengths. • PLS-DA and SVM algorithms were used to identify sound and bruised jujubes. • A-Raw-iVISSA-PLS-DA was the optimal classification discriminant model. Bruising is one of the major challenges appearing in the postharvest grading and processing of Lingwu long jujubes, which leads to quality deterioration and microbial infection. In the present work, the spectra of reflectance (R), absorbance (A) and Kubelka-Munk (K-M) in Lingwu were obtained by hyperspectral imaging, and applied to non-destructively detect bruising symptoms. Spectra were preprocessed and characteristic wavelengths were selected by competitive adaptive reweighted sampling (CARS) and the interval variable iterative space shrinkage approach (iVISSA). Classification discriminant models were constructed by partial least squares-discriminant analysis (PLS-DA) and support vector machine (SVM). By comparison, the results revealed that the A-raw-iVISSA-PLS-DA model showed the lowest errors in cross-validation, while the number of feature variables was the lowest accounting for 28.8 %, and the accuracies of the calibration and cross validation were 88.9 % and 100.0 %, respectively. In particular, this study demonstrated the feasibility to detect the early bruising degree in Lingwu long jujubes based on absorbance spectrum. Consequently, it also laid a foundation for future studies about detecting early bruising in small fruit with a rapid and non-destructive spectral-optical measurement. [ABSTRACT FROM AUTHOR]