Fruit size is one of the essential quality traits and influences the economic value of apricots. To explore the underlying mechanisms of the formation of differences in fruit size in apricots, we performed a comparative analysis of anatomical and transcriptomics dynamics during fruit growth and development in two apricot cultivars with contrasting fruit sizes (large-fruit 'Sungold' and small-fruit 'F43'). Our analysis identified that the difference in fruit size was mainly caused by the difference in cell size between the two apricot cultivars. Compared with 'F43', the transcriptional programs exhibited significant differences in 'Sungold', mainly in the cell expansion period. After analysis, key differentially expressed genes (DEGs) most likely to influence cell size were screened out, including genes involved in auxin signal transduction and cell wall loosening mechanisms. Furthermore, weighted gene co-expression network analysis (WGCNA) revealed that was identified as a hub gene, which interacted with 1 , 3 , 4 , 3 and 1 . Hence, a total of 13 key candidate genes were identified as positive regulators of fruit size in apricots. The results provide new insights into the molecular basis of fruit size control and lay a foundation for future breeding and cultivation of larger fruits in apricot.
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http://dx.doi.org/10.3390/ijms24108748 | DOI Listing |
Sci Rep
January 2025
Department of Pharmacology and Toxicology, College of Pharmacy, King Saud University, 11451, Riyadh, Saudi Arabia.
Nanotechnology has experienced significant advancements, attracting considerable attention in various biomedical applications. This innovative study synthesizes and characterizes Ge/PLA/AuNCs (gelatin/PLA/gold nanocomposites) using Syzygium cumini extract to evaluate their various biomedical applications. The UV-Visible spectroscopy results in an absorption peak at 534 nm were primarily confirmed by Ge/PLA/AuNCs synthesis.
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January 2025
Plant Science Program, Biological and Environmental Science and Engineering Division (BESE), King Abdullah University of Science and Technology (KAUST), 23955-6900, Thuwal, Saudi Arabia.
The pomegranate (Punica granatum L.) is an ancient fruit-bearing tree known for its nutritional and antioxidant properties. They originated from the Middle East in regions having large farms including mountainous regions of Al-Baha in Saudi Arabia.
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January 2025
CSIR- Institute of Genomics and Integrative Biology, Mall Road, Delhi 110007, India; Academy of Scientific and Innovative Research (AcSIR), Ghaziabad 201002, India. Electronic address:
The expanding prevalence of microbial resistance to conventional treatments has triggered a race to develop alternative/improved strategies to combat drug-resistant microorganisms in an efficient manner. Here, the lethal impact of the biosynthesized gold nanoparticles (AuNPs) against multi-drug resistant (MDR) bacteria has been elucidated. AuNPs, synthesized from the extracts of the fruit, leaf and peel of the Citrus maxima plant, were physicochemically characterized by UV-Vis spectrophotometry, Dynamic Light Scattering (DLS), electron microscopy and spectroscopic techniques not only confirmed the production of AuNPs of size below 100 nm but also identified the phytochemicals adsorbed onto the surface of NPs.
View Article and Find Full Text PDFBraz J Biol
January 2025
Instituto Nacional de Pesquisas da Amazônia - INPA, Programa de Pós-graduação em Ecologia - PPGEco, Manaus, AM, Brasil.
Pentaclethra macroloba is a hyperdominant species with multiple uses in the Amazon. This species tolerates varying flood amplitudes, however the effect of flood topographic gradient on its ecophysiology remains unclear. We want to know if individuals from the high (10 trees) and low (20 trees) várzea show distinct phenological patterns as a function of the flood gradient, as well as their colonization strategies and their seed predators.
View Article and Find Full Text PDFFront Plant Sci
December 2024
School of Future Technology, Fujian Agriculture and Forestry University, Fuzhou, China.
In the cultivation of green chili peppers, the similarity between the fruit and background color, along with severe occlusion between fruits and leaves, significantly reduces the efficiency of harvesting robots. While increasing model depth can enhance detection accuracy, complex models are often difficult to deploy on low-cost agricultural devices. This paper presents an improved lightweight Pepper-YOLO model based on YOLOv8n-Pose, designed for simultaneous detection of green chili peppers and picking points.
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