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Horticulturae
Special Issues
Advances in Postharvest Fresh-Keeping Technology and Metabolomics of Horticultural Plants
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Advances in Postharvest Fresh-Keeping Technology and Metabolomics of Horticultural Plants

A special issue of Horticulturae (ISSN 2311-7524). This special issue belongs to the section "Postharvest Biology, Quality, Safety, and Technology".

Deadline for manuscript submissions: closed (10 October 2024) | Viewed by 9499

Special Issue Editors

Dr. Tao Luo

E-Mail Website
Guest Editor
College of Horticulture, South China Agricultural University, Guangzhou 510642, China
Interests: multi-omics; metabolome; browning; sulfide metabolism; sulfur fumigation and alternative strategies; postharvest biology
Prof. Dr. Zhenxian Wu

E-Mail Website
Guest Editor
College of Horticulture, South China Agricultural University, Guangzhou 510642, China
Interests: multi-omics; preservation of litchi, longan and horticultural crops in South China; packaging; sulfur fumigation; postharvest biology
Dr. Xiaomeng Guo

E-Mail
Guest Editor
College of Horticulture, South China Agricultural University, Guangzhou 510642, China
Interests: multi-omics; secondary metabolism; postharvest quality deterioration of litchi, longan and horticultural crops in South China; postharvest biology

Special Issue Information

Dear Colleagues,

Horticultural plants are still alive when during and after harvesting and programmed and complex metabolic processes take place postharvest. The metabolic processes in horticultural crops are spatio-temporally specific, resulting in the formation or even deterioration of quality during postharvest ripening or senescence. Advanced preservation technologies have been widely explored and used to keep horticultural products fresh. However, systematic investigations into their effect on the metabolism of horticultural crops are still limited. The development and wide application of metabolomics technology has provided a powerful means for the study of the postharvest metabolism and regulation of horticultural crops. For this Special Issue, we welcome the submission of research on innovative post-harvest fresh-keeping technology, as well as metabolic analysis of fruits, vegetables, medicinal, aromatic and ornamental plants during postharvest handling, storage and logistics; this is not limited to physiological, biochemical and molecular regulation (at the transcription, post-transcription, translation or post-translation level) analysis.

Dr. Tao Luo
Prof. Dr. Zhenxian Wu
Dr. Xiaomeng Guo
Guest Editors

Manuscript Submission Information

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Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Horticulturae is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2200 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • horticultural crops
  • postharvest quality
  • preservation technology
  • regulation mechanism
  • metabolomics

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Published Papers (8 papers)

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17 pages, 1180 KiB  
Article
Chemical Profiles and Antimicrobial Properties of Essential Oils from Orange, Pummelo, and Tangelo Cultivated in Greece
by Eleni Anastasopoulou, Konstantia Graikou, Vasileios Ziogas, Christos Ganos, Fabrizio Calapai and Ioanna Chinou
Horticulturae 2024, 10(8), 792; https://doi.org/10.3390/horticulturae10080792 - 26 Jul 2024
Viewed by 1041
Abstract
In the framework of our studies on Citrus cultivars in Greece, the chemical composition of the essential oils (EOs) from the peels and leaves of orange, pummelo, and tangelo (mandarin × grapefruit hybrid) cultivated in Greece have been studied. All EOs have been [...] Read more.
In the framework of our studies on Citrus cultivars in Greece, the chemical composition of the essential oils (EOs) from the peels and leaves of orange, pummelo, and tangelo (mandarin × grapefruit hybrid) cultivated in Greece have been studied. All EOs have been analyzed through GC-MS, and a total of 47 and 87 metabolites were identified in the peels and leaves, respectively. These metabolites are classified into the chemical groups of terpenes, alcohols, aldehydes, esters, ketones, and organic acids. Limonene was the most abundant compound in the peel EOs. Moreover, bioactive polymethoxyflavones (PMFs) were isolated and structurally determined from the peels of orange and tangelo, highlighting them as a good potential source of natural PMFs. All EOs were evaluated for their antimicrobial activity against nine human pathogenic microorganisms (six bacteria and three fungi), showing an interesting profile. The EOs from the peels of all Citrus species exhibited a stronger antimicrobial activity compared to those from the leaves. The susceptibility of the assayed Gram-positive bacteria was observed to be greater than that of Gram-negative bacteria, while the fungi were also relatively less resistant than bacteria. The rootstock choice did not influence the EO profile of the fruit peel but exerted an influence on the chemical profile of the leaves. Full article
(This article belongs to the Special Issue Advances in Postharvest Fresh-Keeping Technology and Metabolomics of Horticultural Plants)
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Figure 1

Figure 1
<p>Fruits of <span class="html-italic">Citrus sinensis</span> (L.) Osbeck cv. Newhall on citrumelo rootstock (<b>A</b>), <span class="html-italic">Citrus sinensis</span> (L.) Osbeck cv. Newhall on <span class="html-italic">Poncirus trifoliata</span> rootstock (<b>B</b>), <span class="html-italic">Citrus sinensis</span> (L.) Osbeck cv. Valencia Ovale Porou on citrumelo rootstock (<b>C</b>), <span class="html-italic">Citrus sinensis</span> (L.) Osbeck cv. Valencia Ovale Porou on <span class="html-italic">Poncirus trifoliata</span> rootstock (<b>D</b>), <span class="html-italic">Citrus paradisi</span> × <span class="html-italic">Citrus tangerina</span> cv. Minneola on <span class="html-italic">Poncirus trifoliata</span> rootstock (<b>E</b>), <span class="html-italic">Citrus maxima</span> (Burm.) Merr. on <span class="html-italic">Poncirus trifoliata</span> rootstock (<b>F</b>). Bar: 10 cm.</p> Full article ">Figure 2
<p>Structures of isolated PMFs.</p> Full article ">Figure 2 Cont.
<p>Structures of isolated PMFs.</p> Full article ">
10 pages, 1116 KiB  
Article
Modelling the Growth of Listeria monocytogenes on Fresh-Cut Cucumbers at Various Storage Temperatures
by Ke Feng, Sarengaowa, Junyi Ma and Wenzhong Hu
Horticulturae 2024, 10(7), 667; https://doi.org/10.3390/horticulturae10070667 - 24 Jun 2024
Cited by 2 | Viewed by 767
Abstract
The primary objective of this study was to investigate the behavior of Listeria monocytogenes (L. monocytogenes) on fresh-cut cucumbers. Fresh-cut cucumber samples were inoculated with a mixture of six strains of L. monocytogenes. The inoculated samples were stored at 5, [...] Read more.
The primary objective of this study was to investigate the behavior of Listeria monocytogenes (L. monocytogenes) on fresh-cut cucumbers. Fresh-cut cucumber samples were inoculated with a mixture of six strains of L. monocytogenes. The inoculated samples were stored at 5, 10, 15, 20, 25, 30, and 35 °C. The results demonstrated that L. monocytogenes was able to grow on fresh-cut cucumbers at all the evaluated temperatures, although its growth decreased but was not inhibited at 5 °C. An extreme storage temperature of 35 °C considerably reduced the lag time. L. monocytogenes growth on fresh-cut cucumbers was controlled for several days by storage at a low temperature, mainly at 5 °C. Thus, this product should only be stored at low temperatures. The growth process was fitted by the Baranyi model, with the specific growth rates equally well-fitted to the Ratkowsky square-root model. The R-square and mean square error values for the corresponding Ratkowsky square-root models were 0.97 (R2 > 0.95) and 0.02, respectively. The Baranyi and Ratkowsky square-root models exhibited good relevancy. The predictive models developed in this study can be used to estimate the risk assessment of L. monocytogenes on fresh-cut cucumber. Full article
(This article belongs to the Special Issue Advances in Postharvest Fresh-Keeping Technology and Metabolomics of Horticultural Plants)
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Figure 1

Figure 1
<p>Growth of <span class="html-italic">L. monocytogenes</span> on fresh-cut cucumbers at different temperatures: (<b>A</b>) 5 °C, (<b>B</b>) 10 °C, (<b>C</b>) 15 °C, (<b>D</b>) 20 °C, (<b>E</b>) 25 °C, (<b>F</b>) 30 °C, and (<b>G</b>) 35 °C. The black solid rhombuses represent the observed data points; the red thin solid curves were obtained using the Baranyi model.</p> Full article ">Figure 1 Cont.
<p>Growth of <span class="html-italic">L. monocytogenes</span> on fresh-cut cucumbers at different temperatures: (<b>A</b>) 5 °C, (<b>B</b>) 10 °C, (<b>C</b>) 15 °C, (<b>D</b>) 20 °C, (<b>E</b>) 25 °C, (<b>F</b>) 30 °C, and (<b>G</b>) 35 °C. The black solid rhombuses represent the observed data points; the red thin solid curves were obtained using the Baranyi model.</p> Full article ">Figure 2
<p>The relationship between the Ratkowsky square root of the growth rate and temperature of <span class="html-italic">L. monocytogenes</span>.</p> Full article ">
15 pages, 2783 KiB  
Article
Comprehensive Evaluation of the ‘Shixia’ Longan Quality under Postharvest Ambient Storage: The Volatile Compounds Played a Critical Part
by Jingyi Li, Tao Luo, Jianhang Xu, Difa Zhu, Dongmei Han and Zhenxian Wu
Horticulturae 2024, 10(6), 585; https://doi.org/10.3390/horticulturae10060585 - 3 Jun 2024
Viewed by 641
Abstract
Longan fruit generally undergoes rapid quality deterioration during the postharvest stage, with the manifestation of flavor loss as well as pronounced off-odor production. Nevertheless, the unapparent aroma makes people ignore the odor change in postharvest longan. Sensory analysis serves as an indispensable method [...] Read more.
Longan fruit generally undergoes rapid quality deterioration during the postharvest stage, with the manifestation of flavor loss as well as pronounced off-odor production. Nevertheless, the unapparent aroma makes people ignore the odor change in postharvest longan. Sensory analysis serves as an indispensable method combining instrumental detection and the perceptibility of human sensation in a comprehensive evaluation of quality during production and consumption. In this study, we established the evaluating data of the appearance, flavor, taste substances, volatile profiles, and deterioration of ‘Shixia’ longan throughout room-temperature storage using instrument assessment and descriptive measurements. Our results indicated that both the appearance state and the taste condition notably engendered confusion or trouble for consumers to judge under the quality transition period. Conversely, the development of odor was highly consistent with that of quality deterioration. Some unpleasant volatile substances including alcohol (ethanol), acid (acetic acid), and esters (acetic acid methyl ester and ethyl acetate) were probably the cause of off-odor during the storage. The result of the sensory evaluation also presents a more significant relevance between the overall quality and the odor. Generally, the work paved the way to reveal the importance of odor profiles for assessing the comprehensive quality condition of postharvest room-temperature stored longan. Full article
(This article belongs to the Special Issue Advances in Postharvest Fresh-Keeping Technology and Metabolomics of Horticultural Plants)
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Figure 1
<p>The appearance status of the SX longan during room-temperature storage. (<b>a</b>) The appearance of SX; (<b>b</b>–<b>e</b>) the chromatic analysis of the pericarp. Different letters indicate statistically significant differences according to one-way ANOVA with Tukey’s post hoc test, <span class="html-italic">p</span> &lt; 0.05.</p> Full article ">Figure 2
<p>Measurement of the pericarp browning index (<b>a</b>), aril breakdown index (<b>b</b>), cell relative electrolytic conductivity (<b>c</b>), and decay rate (<b>d</b>) of the SX longan during the ambient storage. Different letters indicate statistically significant differences according to one-way ANOVA with Tukey’s post hoc test, <span class="html-italic">p</span> &lt; 0.05.</p> Full article ">Figure 3
<p>Measurements of taste condition of the SX longan in storage period. (<b>a</b>) The detection of longan flavor change by electronic tongue. (<b>b</b>) The TSS content. (<b>c</b>) The Vc content. Different letters indicate statistically significant differences according to one-way ANOVA with Tukey’s post hoc test, <span class="html-italic">p</span> &lt; 0.05.</p> Full article ">Figure 4
<p>Quantification and multiple analysis of volatile components during storage. (<b>a</b>) The LDA results of electronic nose data. (<b>b</b>) The loading analysis of electronic nose data. (<b>c</b>) The dynamic changes in content and categories of the volatile substances from 0 DAS and 12 DAS. Multivariate statistical analysis: (<b>d</b>) PCA score plot; (<b>e</b>) cross-validation results. The intercept of the Q2 regression line of the cross-validation model with 200 tests of alignment was less than 0, indicating that the OPLS-DA discriminant model was not over-fitted and the model was relatively reliable; (<b>f</b>) VIP score plot: red bars represented volatile compounds with VIP &gt; 1 and green bars represented VIP &lt; 1. (<b>g</b>) The relative content analysis of the identified marked volatile components. Asterisks indicate significant difference between the two samples at the same time point: *, <span class="html-italic">p</span> &lt; 0.05; **, <span class="html-italic">p</span> &lt; 0.01.</p> Full article ">Figure 4 Cont.
<p>Quantification and multiple analysis of volatile components during storage. (<b>a</b>) The LDA results of electronic nose data. (<b>b</b>) The loading analysis of electronic nose data. (<b>c</b>) The dynamic changes in content and categories of the volatile substances from 0 DAS and 12 DAS. Multivariate statistical analysis: (<b>d</b>) PCA score plot; (<b>e</b>) cross-validation results. The intercept of the Q2 regression line of the cross-validation model with 200 tests of alignment was less than 0, indicating that the OPLS-DA discriminant model was not over-fitted and the model was relatively reliable; (<b>f</b>) VIP score plot: red bars represented volatile compounds with VIP &gt; 1 and green bars represented VIP &lt; 1. (<b>g</b>) The relative content analysis of the identified marked volatile components. Asterisks indicate significant difference between the two samples at the same time point: *, <span class="html-italic">p</span> &lt; 0.05; **, <span class="html-italic">p</span> &lt; 0.01.</p> Full article ">Figure 5
<p>The heatmap of the scores of the comprehensive sensory qualities of SX during storage.</p> Full article ">
17 pages, 5013 KiB  
Article
Evaluation of Quality and Microbial Communities in Fermented Chinese Mustard Greens from Guangdong Province, China
by Sarengaowa, Yongxi Kuang, Yun Ding, Hao Xie, Xinyang Tong, Wenzhong Hu and Ke Feng
Horticulturae 2024, 10(4), 399; https://doi.org/10.3390/horticulturae10040399 - 13 Apr 2024
Viewed by 1148
Abstract
Fermented Chinese mustard greens are popular fermented vegetable foods in Guangdong Province, China. In this study, the quality characteristics and microbial composition of fermented Chinese mustard greens from different regions, including Shantou (ST), Meizhou (MZ), Yunfu (YF), and Guangzhou (GZ), were evaluated. The [...] Read more.
Fermented Chinese mustard greens are popular fermented vegetable foods in Guangdong Province, China. In this study, the quality characteristics and microbial composition of fermented Chinese mustard greens from different regions, including Shantou (ST), Meizhou (MZ), Yunfu (YF), and Guangzhou (GZ), were evaluated. The colour and texture of fermented Chinese mustard greens were significantly different from those of ST, MZ, YF, and GZ. L* values were 48.62, 42.30, 32.43, and 34.02 in the stem parts of ST, MZ, YF, and GZ, respectively. The chewiness value was greater in GZ (131.26 N) than in MZ (53.25 N), YF (39.99 N), and GZ (24.22 N) zones. The microbial community structure determined by high-throughput sequencing (HTS) demonstrated that Firmicutes, Proteobacteria, and Campilobacterota were the predominant phyla. Lactobacillus was the most predominant microorganism in the MZ and GZ samples and accounted for a greater proportion of the microorganisms in the ST and YF samples. In addition to Lactobacillus, the relative abundances of Cobetia and Weissella were greater in the ST group, while those of Halomonas and Pediococcus were greater in the YF group. There was a significant correlation between the microbial composition and quality indices (colour and texture) among the samples from the four regions. The quality of the fermented Chinese mustard greens in MZ and GZ was significantly different from that of other samples in ST and YF. The Lactobacillus genus (Lactobacillus plantarum and Lactobacillus selangorensis) in MZ and GZ contributed to changes in colour (b*, C*, L*, a*) and texture (firmness and chewiness). This study provided a comprehensive correlation between quality and microbial composition of fermented Chinese mustard greens from different regions in Guangdong Province. The evaluation and correlation between quality and microbiota are helpful for guiding future improvements in fermentation processes and manufacturing high-quality fermented Chinese mustard greens. Full article
(This article belongs to the Special Issue Advances in Postharvest Fresh-Keeping Technology and Metabolomics of Horticultural Plants)
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Figure 1

Figure 1
<p>The colour of the stem and leaf parts of fermented Chinese mustard greens. (<b>A</b>) <span class="html-italic">L*</span>, (<b>B</b>) <span class="html-italic">C*</span>, (<b>C</b>) <span class="html-italic">a*</span>, (<b>D</b>) <span class="html-italic">b*</span>. ST is Shantou, MZ is Meizhou, YF is Yunfu, and GZ is Guangzhou. Means designated by the same letters (uppercase, among different samples; lowercase, among stem parts and leaf parts) are significantly different according to Duncan’s test. Bars represent the means ± SD (<span class="html-italic">n</span> = 3, <span class="html-italic">p</span> &lt; 0.05).</p> Full article ">Figure 2
<p>The firmness and chewiness of fermented Chinese mustard greens. ST is Shantou, MZ is Meizhou, YF is Yunfu, and GZ is Guangzhou. Means designated by the same letters (uppercase, among different samples) are significantly different according to Duncan’s test. Bars represent means ± SDs (<span class="html-italic">n</span> = 3, <span class="html-italic">p</span> &lt; 0.05).</p> Full article ">Figure 3
<p>Alpha diversity of the bacterial community of fermented Chinese mustard greens. (<b>A</b>) Shannon–non curve for each sample. (<b>B</b>) Coverage index. (<b>C</b>) Shannon index. (<b>D</b>) Chao1 values. (<b>E</b>) Ace index. (<b>F</b>) Simpson index. *** <span class="html-italic">p</span> &lt; 0.051. ST is Shantou, MZ is Meizhou, YF is Yunfu, and GZ is Guangzhou.</p> Full article ">Figure 3 Cont.
<p>Alpha diversity of the bacterial community of fermented Chinese mustard greens. (<b>A</b>) Shannon–non curve for each sample. (<b>B</b>) Coverage index. (<b>C</b>) Shannon index. (<b>D</b>) Chao1 values. (<b>E</b>) Ace index. (<b>F</b>) Simpson index. *** <span class="html-italic">p</span> &lt; 0.051. ST is Shantou, MZ is Meizhou, YF is Yunfu, and GZ is Guangzhou.</p> Full article ">Figure 4
<p>Beta diversity and Venn diagrams of the bacterial community of fermented Chinese mustard greens. (<b>A</b>) Principal coordinate analysis (PCoA). (<b>B</b>) Nonmetric multidimensional scaling (NMDS). Venn diagrams at the OTU (<b>C</b>) and genus (<b>D</b>) levels according to bacterial biodiversity. ST is Shantou, MZ is Meizhou, YF is Yunfu, and GZ is Guangzhou.</p> Full article ">Figure 5
<p>Composition of bacterial communities in fermented Chinese mustard greens at the phylum (<b>A</b>), genus (<b>B</b>), and species (<b>C</b>) levels. ST is Shantou, MZ is Meizhou, YF is Yunfu, and GZ is Guangzhou.</p> Full article ">Figure 5 Cont.
<p>Composition of bacterial communities in fermented Chinese mustard greens at the phylum (<b>A</b>), genus (<b>B</b>), and species (<b>C</b>) levels. ST is Shantou, MZ is Meizhou, YF is Yunfu, and GZ is Guangzhou.</p> Full article ">Figure 6
<p>LEfSe comparison of bacterial communities among fermented Chinese mustard greens. Histogram of the results of the microbiota with a threshold value of 2. ST is Shantou, MZ is Meizhou, YF is Yunfu, and GZ is Guangzhou.</p> Full article ">Figure 7
<p>Redundancy analysis (RDA) of bacterial communities among fermented Chinese mustard greens. ST is Shantou, MZ is Meizhou, YF is Yunfu, and GZ is Guangzhou.</p> Full article ">Figure 8
<p>Spearman correlation analysis of the quality indices and main species of bacterial communities among fermented Chinese mustard greens. The Spearman correlation coefficient r ranges from −0.5 to 0.5; r &lt; 0 indicates a negative correlation, and r &gt; 0 indicates a positive correlation. * <span class="html-italic">p</span> &lt; 0.05, ** <span class="html-italic">p</span> &lt; 0.01, *** <span class="html-italic">p</span> &lt; 0.001. ST is Shantou, MZ is Meizhou, YF is Yunfu, and GZ is Guangzhou.</p> Full article ">Figure 9
<p>The predictive functions of the bacterial community in fermented Chinese mustard greens (Pathway Level 3). ST is Shantou, MZ is Meizhou, YF is Yunfu, and GZ is Guangzhou.</p> Full article ">
12 pages, 4217 KiB  
Article
The Effect of Bacillus velezensis LJ02 Compounded with Different Fungi on the Growth of Watermelon Seedlings and Microbial Community Structure
by Weiwei Yu, Tianyi Wu, Ruokui Chang, Yujin Yuan and Yuanhong Wang
Horticulturae 2024, 10(3), 236; https://doi.org/10.3390/horticulturae10030236 - 28 Feb 2024
Viewed by 1216
Abstract
The application of beneficial microbial consortium can effectively improve plant disease resistance and its growth. Various fungi were compounded with Bacillus velezensis LJ02 and applied to watermelon plants in this paper. The results showed that the microbial consortium T2 (compounded Bacillus velezensis LJ02 [...] Read more.
The application of beneficial microbial consortium can effectively improve plant disease resistance and its growth. Various fungi were compounded with Bacillus velezensis LJ02 and applied to watermelon plants in this paper. The results showed that the microbial consortium T2 (compounded Bacillus velezensis LJ02 with Aspergillus aculeatus 9) can effectively control gummy stem blight and powdery mildew in watermelon, while the control effect reached 83.56% and 70.93%, respectively (p < 0.05). Compound treatment improved the diversity and richness of the rhizosphere microbial community structure, and the relative abundance of Caulobacterales and Xanthomonadaceae significantly increased after applying T2 to the soil. Meanwhile, the internode length was significantly decreased 28% (p < 0.05), and the maximum leaf length increased 10.33% (p < 0.05). In addition, the microbial consortium delays the maturity of watermelon vegetables. By studying the effects of microbial consortium on watermelon seedlings, our study provides a theoretical basis for the popularization and application of the compound inoculant. Full article
(This article belongs to the Special Issue Advances in Postharvest Fresh-Keeping Technology and Metabolomics of Horticultural Plants)
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Figure 1

Figure 1
<p>Effects of different treatments on watermelon plants. (<b>a</b>) The steam length of watermelon. (<b>b</b>) The stem diameter of watermelon. Measurement of the diameter of the fourth stem section from the terminal bud toward the root. (<b>c</b>) The internode length of watermelon. The internode spacing was measured as the stem length of the fourth stem node from the terminal bud toward the root. Note: all analysis based on one-way analysis of variance (ANOVA) and Duncan’s multiple tests, <span class="html-italic">p</span> &lt; 0.05 was considered statistically significant; the columns with different letters indicate significant differences.</p> Full article ">Figure 2
<p>Effects of different treatments on watermelon leaves. (<b>a</b>) The maximum leaf length of watermelon. Measured leaf length directly from leaf base to leaf tip, excluding petiole, using vernier caliper. (<b>b</b>) The maximum leaf width of watermelon. Measured leaf length at the widest point on the leaf blade perpendicular to the main vein directly with a vernier caliper. Note: all analysis based on one-way analysis of variance (ANOVA) and Duncan’s multiple tests, <span class="html-italic">p</span> &lt; 0.05 was considered statistically significant; the columns with different letters indicate significant differences.</p> Full article ">Figure 3
<p>Effects of different treatments on watermelon fruits. (<b>a</b>) The weight of watermelon. Fruits are weighed when they reach harvest time. (<b>b</b>) The maturity of watermelon. (<b>c</b>) The soluble sugar content of watermelon. Watermelon internal fruits from different treatments; control treatment (CK) (<b>d</b>), T1 treatment (<b>e</b>), T2 treatment (<b>f</b>), T3 treatment (<b>g</b>). Note: all analysis based on one-way analysis of variance (ANOVA) and Duncan’s multiple tests, <span class="html-italic">p</span> &lt; 0.05 was considered statistically significant; the columns with different letters indicate significant differences.</p> Full article ">Figure 4
<p>Effect of different treatments on watermelon disease control. (<b>a</b>) Control effect of gummy stem blight. (<b>b</b>) Control effect of powdery mildew. Note: all analysis based on one-way analysis of variance (ANOVA) and Duncan’s multiple tests, <span class="html-italic">p</span> &lt; 0.05 was considered statistically significant; the columns with different letters indicate significant differences.</p> Full article ">Figure 5
<p>Metagenomic analysis of rhizosphere microorganisms. (<b>a</b>) Venn diagram of the quantity of OTUs in bacteria from soils treated with different treatments. (<b>b</b>) The highest 30 phylum microbial abundance among samples from different treatments. (<b>c</b>) The highest 30 genius microbial abundance among samples from different treatments. Note: In (<b>a</b>), the numbers in the figure represent the number of OTUs in the different treatments. In (<b>b</b>,<b>c</b>), the columns in the picture represent each treatment, and the different colors represent different species.</p> Full article ">Figure 6
<p>LEfSe analysis in rhizosphere soil under different treatments. (<b>a</b>) Histogram of LDA value distribution. (<b>b</b>) Branch diagram annotation for different treatments. Note: different color bars represent species with higher abundance in different treatments.</p> Full article ">
21 pages, 7730 KiB  
Article
Elucidating Softening Mechanism of Honey Peach (Prunus persica L.) Stored at Ambient Temperature Using Untargeted Metabolomics Based on Liquid Chromatography-Mass Spectrometry
by Xiaoxue Kong, Haibo Luo, Yanan Chen, Hui Shen, Pingping Shi, Fang Yang, Hong Li and Lijuan Yu
Horticulturae 2023, 9(11), 1210; https://doi.org/10.3390/horticulturae9111210 - 8 Nov 2023
Cited by 1 | Viewed by 1359
Abstract
Peach fruit softening is the result of a series of complex physiological and biochemical reactions that influence shelf life and consumer acceptance; however, the precise mechanisms underlying softening remain unclear. We conducted a metabolomic study of the flesh and peel of the honey [...] Read more.
Peach fruit softening is the result of a series of complex physiological and biochemical reactions that influence shelf life and consumer acceptance; however, the precise mechanisms underlying softening remain unclear. We conducted a metabolomic study of the flesh and peel of the honey peach (Prunus persica L.) to identify critical metabolites before and after fruit softening. Compared to the pre-softening profiles, 155 peel metabolites and 91 flesh metabolites exhibited significant changes after softening (|log2(FC)| > 1; p < 0.05). These metabolites were mainly associated with carbohydrate metabolism, respiratory chain and energy metabolism (citrate cycle, pantothenate and CoA biosynthesis, nicotinate and nicotinamide metabolism, and pentose and glucuronate interconversions), reactive oxygen species (ROS) metabolism, amino acid metabolism, and pyrimidine metabolism. During peach fruit softening, energy supply, carbohydrate and amino acid metabolism, oxidative damage, and plant hormone metabolism were enhanced, whereas amino acid biosynthesis and cell growth declined. These findings contribute to our understanding of the complex mechanisms of postharvest fruit softening, and may assist breeding programs in improving peach fruit quality during storage. Full article
(This article belongs to the Special Issue Advances in Postharvest Fresh-Keeping Technology and Metabolomics of Horticultural Plants)
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Figure 1
<p>The cell ultrastructure of peach fruit before (<b>A</b>) and after (<b>B</b>) softening.</p> Full article ">Figure 2
<p>PCA score chart (<b>A</b>) and heatmap (<b>B</b>) of all samples.</p> Full article ">Figure 3
<p>OPLS-DA score chart of PSP + PHP (<b>A</b>) and FSP + FHP (<b>B</b>). (<b>C</b>) FSP + PSP and (<b>D</b>) FHP + PHP.</p> Full article ">Figure 4
<p>Number of differential metabolites in peach fruit before and after softening.</p> Full article ">Figure 5
<p>The super class distribution of identified differential metabolites covering 11 groups categorized according to their molecular structure. (<b>A</b>) PSP/PHP; (<b>B</b>) FSP/FHP.</p> Full article ">Figure 6
<p>Top 40 differential metabolites in peach fruit before and after softening.</p> Full article ">Figure 7
<p>Metabolic pathways of the main metabolites in peel (<b>A</b>) and flesh (<b>B</b>) of peach fruit before and after softening. (Red indicates significantly up-regulated metabolites and blue significantly down-regulated metabolites in peach fresh after softening).</p> Full article ">Figure 7 Cont.
<p>Metabolic pathways of the main metabolites in peel (<b>A</b>) and flesh (<b>B</b>) of peach fruit before and after softening. (Red indicates significantly up-regulated metabolites and blue significantly down-regulated metabolites in peach fresh after softening).</p> Full article ">
19 pages, 1904 KiB  
Article
Analysis of Volatile Compounds in Different Varieties of Plum Fruits Based on Headspace Solid-Phase Microextraction-Gas Chromatography-Mass Spectrometry Technique
by Qin Zhang, Shouliang Zhu, Xin Lin, Junsen Peng, Dengcan Luo, Xuan Wan, Yun Zhang, Xiaoqing Dong and Yuhua Ma
Horticulturae 2023, 9(10), 1069; https://doi.org/10.3390/horticulturae9101069 - 23 Sep 2023
Cited by 3 | Viewed by 1734
Abstract
To investigate the differences in the volatile compounds of plum fruit samples from different cultivars, the volatile compounds of the ‘Fengtang’ plum, ‘Kongxin’ plum, and ‘Cuihong’ plum fruits were analyzed using headspace solid-phase microextraction–gas chromatography–mass spectrometry (HS-SPME-GC-MS). The results demonstrated that a total [...] Read more.
To investigate the differences in the volatile compounds of plum fruit samples from different cultivars, the volatile compounds of the ‘Fengtang’ plum, ‘Kongxin’ plum, and ‘Cuihong’ plum fruits were analyzed using headspace solid-phase microextraction–gas chromatography–mass spectrometry (HS-SPME-GC-MS). The results demonstrated that a total of 938 volatile compounds were identified in three plum fruits, including 200 terpenoids, 171 esters, 116 heterocyclic compounds, 89 hydrocarbons, 82 ketones and alcohols, 63 aldehydes, 54 aromatic hydrocarbons, 21 amines, 18 acids, 17 phenols, 10 nitrogenous compounds, 7 sulfur compounds, and other compounds, 470 of which were common to all the cultivars. Moreover, 704, 691, and 704 volatile substances were detected, respectively, in the ‘Fengtang’ plum, ‘Kongxin’ plum, and ‘Cuihong’ plum, with terpenoids, esters, and heterocycles as the main compounds, accounting for 62.12~72.03% of the volatile compounds. The results of principal component analysis (PCA) and cluster analysis (CA) illustrated that the ‘Fengtang’ plum and ‘Cuihong’ plum were similar in terms of volatile compounds; the ‘Kongxin’ plum compounds were different from those in the other cultivars. Orthogonal partial least squares discriminant analysis was performed, revealing the typical volatile compounds that differed among the plum fruits of the different varieties; thus, the three plum fruits could be better distinguished. These results can provide a theoretical basis for the studies of plum fruit flavor, quality, and geographical origin identification. Full article
(This article belongs to the Special Issue Advances in Postharvest Fresh-Keeping Technology and Metabolomics of Horticultural Plants)
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<p>Total ion flow diagram for QC sample nature spectrum analysis. Note: (<b>A</b>, <b>B</b>, and <b>C</b>) are total ion flow diagrams for ‘Fengtang’ plum, ‘Kongxin’ plum, and ‘Cuihong’ plum, respectively.</p> Full article ">Figure 2
<p>The PCA analysis diagram of different varieties of plum.</p> Full article ">Figure 3
<p>The cluster analysis of different varieties of plum.</p> Full article ">Figure 4
<p>Score plot and validation of OPLS-DA model of volatile compounds in different plum cultivars. Note: (<b>A</b>,<b>B</b>; <b>C</b>,<b>D</b>; <b>E</b>,<b>F</b>) were OPLS-DA score plots and validation plots for F vsC, C vsK, and F vs K, respectively.</p> Full article ">

Review

Jump to: Research

19 pages, 819 KiB  
Review
Research Progress on Physical Preservation Technology of Fresh-Cut Fruits and Vegetables
by Dixin Chen, Yang Zhang, Jianshe Zhao, Li Liu and Long Zhao
Horticulturae 2024, 10(10), 1098; https://doi.org/10.3390/horticulturae10101098 (registering DOI) - 16 Oct 2024
Viewed by 390
Abstract
Fresh-cut fruits and vegetables have become more popular among consumers because of their nutritional value and convenience. However, the lower shelf life of fresh-cut fruits and vegetables due to processing and mechanical damage is a critical factor affecting their market expansion, and advances [...] Read more.
Fresh-cut fruits and vegetables have become more popular among consumers because of their nutritional value and convenience. However, the lower shelf life of fresh-cut fruits and vegetables due to processing and mechanical damage is a critical factor affecting their market expansion, and advances in preservation technology are needed to prolong their shelf life. Some traditional chemical preservatives are disliked by health-seeking consumers because of worries about toxicity. Chemical preservation is inexpensive and highly efficient, but sometimes it carries risks for human health. Biological preservation methods are safer and more appealing, but they are not applicable to large-scale production. Physical fresh-keeping methods have been used for the storage and transportation of fresh-cut fruits and vegetables due to the ease of application. This review discusses current research in fresh-keeping technology for the preservation of fresh-cut fruits and vegetables. Preservation methods include low temperature, modified atmosphere packaging, cold plasma, pulsed light, ultrasonics, ultraviolet light, and ozonated water. As promising alternatives to chemical methods, these novel processes have been evaluated singly or combined with natural preservatives or other methods to extend the shelf life of fresh-cut fruits and vegetables and to provide references and assessments for further development and application of fresh-cut fruit and vegetable preservation technology. Full article
(This article belongs to the Special Issue Advances in Postharvest Fresh-Keeping Technology and Metabolomics of Horticultural Plants)
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<p>Effects of various physical treatments for the preservation of appearance, flavor, texture and other qualities of fresh-cut fruits and vegetables.</p> Full article ">
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