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Photosynthetic Variability of Oblacinska Sour Cherry Ecotypes under Drought.

ABSTRACT: The selection of drought-tolerant sour cherry genotypes is essential for developing sustainable fruit production in today's climate-change conditions. The phenotypic heterogenic population of sour cherry Oblačinska, with high and regular yield suitable for mechanical harvesting and industrial processing, is a traditional and predominant cultivar in northern Croatia (Pannonian region) and Serbia commercial orchards. In this context, 2-year old virus-free sour cherry plants of 4 isolated Oblačinska sour cherry ecotypes (OS, 18, D6, and BOR) produced by micropropagation were exposed to severe drought in a greenhouse under semi-controlled conditions to evaluate its photosynthetic intra-varietal variability. Relative water content (RWC), chlorophyll fluorescence (ChlF), and photosynthetic pigments were evaluated during the ten days of the experiment. As a visible symptom of stress, the withering of plants was followed by a diminution of RWC and photosynthetic pigments in the drought exposed leaves of sour cherry ecotypes compared to the control treatment. ChlF elucidated variability in the photosynthetic efficiency within studied sour cherry ecotypes, highlighting PI_ABS, PI_total, and ψE₀ as the most sensitive and thus the most informative JIP parameters for drought screening. Among the investigated ecotypes, BOR proved to be the most sensitive. The Oblačinska sour cherry ecotype OS showed the highest tolerance to drought conditions and, therefore, can be used as a source of tolerance in sour cherry breeding programs.

SUBMITTER: Viljevac Vuletic M

PROVIDER: S-EPMC9268958 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:Determining and applying ‘good’ postharvest and quality control practices for otherwise highly sensitive fruits, such as sour cherry, is critical, as they serve as excellent media for a wide variety of microbial contaminants. The objective of this research was to report two series of experiments on the modified atmosphere storage (MAP) of sour cherries (Prunus cerasus L. var. Kántorjánosi, Újfehértói fürtös). Firstly, the significant effect of different washing pre-treatments on various quality indices was examined (i.e., headspace gas composition, weight loss, decay rate, color, firmness, soluble solid content, total plate count) in MAP-packed fruits. Subsequently, the applicability of near infrared (NIR) spectroscopy combined with chemometrics was investigated to detect the effect of various storage conditions (packed as control or MAP, stored at 3 or 5 °C) on sour cherries of different perceived ripeness. Significant differences were found for oxygen concentration when two perforations were applied on the packages of ‘Kántorjánosi’ (p < 0.01); weight loss when ‘Kánorjánosi’ (p < 0.001) and ‘Újfehértói fürtös’ (p < 0.01) were packed in MAP; SSC when ‘Újfehértói fürtös’ samples were ozone-treated (p < 0.05); and total plate count when ‘Kántorjánosi’ samples were ozone-treated (p < 0.01). The difference spectra reflected the high variability in the samples, and the detectable effects of different packaging. Based on the investigations with the soft independent modelling of class analogies (SIMCA), different packaging and storage resulted in significant differences in most of the cases even on the first storage day, which in many cases increased by the end of storage. The soft independent modelling of class analogies proved to be suitable for classification with apparent error rates between 0 and 0.5 during prediction regardless of ripeness. The research findings suggest the further correlation of NIR spectroscopic and reference parameters to support postharvest handling and fast quality control.

Project description:High-throughput genome scans are important tools for genetic studies and breeding applications. Here, a 6K SNP array for use with the Illumina Infinium® system was developed for diploid sweet cherry (Prunus avium) and allotetraploid sour cherry (P. cerasus). This effort was led by RosBREED, a community initiative to enable marker-assisted breeding for rosaceous crops. Next-generation sequencing in diverse breeding germplasm provided 25 billion basepairs (Gb) of cherry DNA sequence from which were identified genome-wide SNPs for sweet cherry and for the two sour cherry subgenomes derived from sweet cherry (avium subgenome) and P. fruticosa (fruticosa subgenome). Anchoring to the peach genome sequence, recently released by the International Peach Genome Initiative, predicted relative physical locations of the 1.9 million putative SNPs detected, preliminarily filtered to 368,943 SNPs. Further filtering was guided by results of a 144-SNP subset examined with the Illumina GoldenGate® assay on 160 accessions. A 6K Infinium® II array was designed with SNPs evenly spaced genetically across the sweet and sour cherry genomes. SNPs were developed for each sour cherry subgenome by using minor allele frequency in the sour cherry detection panel to enrich for subgenome-specific SNPs followed by targeting to either subgenome according to alleles observed in sweet cherry. The array was evaluated using panels of sweet (n?=?269) and sour (n?=?330) cherry breeding germplasm. Approximately one third of array SNPs were informative for each crop. A total of 1825 polymorphic SNPs were verified in sweet cherry, 13% of these originally developed for sour cherry. Allele dosage was resolved for 2058 polymorphic SNPs in sour cherry, one third of these being originally developed for sweet cherry. This publicly available genomics resource represents a significant advance in cherry genome-scanning capability that will accelerate marker-locus-trait association discovery, genome structure investigation, and genetic diversity assessment in this diploid-tetraploid crop group.

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Photosynthetic Variability of Oblacinska Sour Cherry Ecotypes under Drought.

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