Xin Qi^1,#, Yu Wang^1,#, Xing Zhang¹, Xiaoshuang Wei¹, Xinyang Liu¹, Zhennan Wang¹, Zhenhui Wang^1,*, Fenglou Ling^2,*

Phyton-International Journal of Experimental Botany, Vol.93, No.7, pp. 1767-1779, 2024, DOI:10.32604/phyton.2024.052844

Abstract DNA methylation is an important epigenetic regulatory mechanism, it regulates gene expression by recruiting proteins involved in gene repression or by inhibiting the binding of transcription factor(s) to DNA. In this study, a novel methyltransferase 2a gene (Zmet2a) was cloned in maize and identified by polymerase chain reaction-base (PCR-base) using a bioinformatics strategy. The Zmet2a cDNA sequence is 2739 bp long and translates to 912 amino acid peptides. The Zmet2a protein revealed that it contains BAH and CHROMO structural domains, is a non-transmembrane protein that is hydrophilically unstable, and has no signal peptide structure. Meanwhile, we verified More >

Adel A. Rezk^1,2,*, Mohamed M. El-Malky³, Heba I. Mohamed^4,*, Hossam S. El-Beltagi^1,5

Phyton-International Journal of Experimental Botany, Vol.93, No.7, pp. 1733-1748, 2024, DOI:10.32604/phyton.2024.052739

Abstract Twenty-four rice genotypes were examined to assess genetic variability, heritability, and correlations for seven-grain quality traits, eight nutritional elements, and protein. ANOVA revealed significant differences for the quality traits studied. For every trait under study, the phenotypic coefficient of variation was higher than the correspondence genotypic coefficient of variation. Heritability in a broad sense varied from 29.75% for grain length to 98.31% for the elongation trait. Hulling percentage recovery had a highly significant positive correlation with milling and head rice percentage. Consequently, milling percentage had a highly positive correlation with head rice percentage. In amylose… More >

Pengcheng Li^1,2,#, Tianze Zhu^1,#, Yunyun Wang^1,2, Shuangyi Yin¹, Xinjie Zhu¹, Minggang Ji¹, Wenye Rui¹, Houmiao Wang¹, Zefeng Yang^1,2,*, Chenwu Xu^1,2,*

Phyton-International Journal of Experimental Botany, Vol.93, No.7, pp. 1441-1453, 2024, DOI:10.32604/phyton.2024.052219

Abstract The nutritional composition and overall quality of maize kernels are largely determined by the key chemical components: protein, oil, and starch. Nevertheless, the genetic basis underlying these nutritional quality traits during grain filling remains poorly understood. In this study, the concentrations of protein, oil, and starch were studied in 204 recombinant inbred lines resulting from a cross between DH1M and T877 at four different stages post-pollination. All the traits exhibited considerable phenotypic variation. During the grain-filling stage, the levels of protein and starch content generally increased, whereas oil content decreased, with significant changes observed between… More >

Yolotzin Apatzingán Palomino-Hermosillo¹, Ángel Elpidio Díaz-Jasso², Rosendo Balois-Morales¹, Verónica Alhelí Ochoa-Jiménez^1,3, Pedro Ulises Bautista-Rosales¹, Guillermo Berumen-Varela^1,*

Phyton-International Journal of Experimental Botany, Vol.93, No.7, pp. 1717-1732, 2024, DOI:10.32604/phyton.2024.052216

Abstract Soursop (Annona muricata L.) is a tropical fruit highly valued for its unique flavor, nutritional value, and health-promoting properties. The ripening process of soursop involves complex changes in gene expression and metabolite accumulation, which have been studied using various omics technologies. Transcriptome analysis has provided insights into the regulation of key genes involved in ripening, while metabolic compound analysis has revealed the presence of numerous bioactive compounds with potential health benefits. However, the integration of transcriptome and metabolite compound data has not been extensively explored in soursop. Therefore, in this paper, we present a comprehensive analysis… More >

Mingchuan Yang¹, Jia Zheng², Wenhui Yu¹, Yanghua Li², Yali Wang¹, Zilu Zhang¹, Zhenhui Kang^1,*

Phyton-International Journal of Experimental Botany, Vol.93, No.7, pp. 1503-1521, 2024, DOI:10.32604/phyton.2024.051718

Abstract Sorghum is not only an important bio-energy crop but also a vital raw material for brewing. Exogenous copper affects the growth and metabolism of crops in specific ways. This study identified 8475 differentially expressed genes (DEGs) by high-throughput transcriptome sequencing in the sorghum cultivar ‘Jinnuoliang 2’ after 24 h of treatment with 10 mM CuSO. Using GO analysis, 476 genes were functionally annotated, which were mainly related to catabolism and biosynthetic processes. Additionally, 90 pathways were annotated by employing the KEGG analysis. Among them, glutathione metabolism and peroxisome were induced, while photosynthesis, photosynthesis-antenna protein, and… More >

Shoukai Lin^1,3,4,*, Yifan Xiong², Shichang Xu^1,2, Manegdebwaoaga Arthur Fabrice Kabore², Fan Lin⁵, Fuxiang Qiu^1,2,*

Phyton-International Journal of Experimental Botany, Vol.93, No.7, pp. 1485-1502, 2024, DOI:10.32604/phyton.2024.050990

Abstract The SWEET (sugar will eventually be exported transporter) family proteins are a recently identified class of sugar transporters that are essential for various physiological processes. Although the functions of the SWEET proteins have been identified in a number of species, to date, there have been no reports of the functions of the SWEET genes in woodland strawberries (Fragaria vesca). In this study, we identified 15 genes that were highly homologous to the A. thaliana AtSWEET genes and designated them as FvSWEET1–FvSWEET15. We then conducted a structural and evolutionary analysis of these 15 FvSWEET genes. The phylogenetic analysis enabled us… More >

Jiawen Li^1,2, Yuesheng Huang¹, Yayi Lu¹, Leijun Wang^1,*, Yongqi Ren¹, Rongjun Chen¹

CMC-Computers, Materials & Continua, Vol.80, No.1, pp. 1581-1599, 2024, DOI:10.32604/cmc.2024.052666

Abstract In the context of the accelerated pace of daily life and the development of e-commerce, online shopping is a mainstream way for consumers to access products and services. To understand their emotional expressions in facing different shopping experience scenarios, this paper presents a sentiment analysis method that combines the e-commerce review keyword-generated image with a hybrid machine learning-based model, in which the Word2Vec-TextRank is used to extract keywords that act as the inputs for generating the related images by generative Artificial Intelligence (AI). Subsequently, a hybrid Convolutional Neural Network and Support Vector Machine (CNN-SVM) model… More >

Bingfei Fu^*

CMC-Computers, Materials & Continua, Vol.80, No.1, pp. 1407-1424, 2024, DOI:10.32604/cmc.2024.052656

Abstract Discovering floating wastes, especially bottles on water, is a crucial research problem in environmental hygiene. Nevertheless, real-world applications often face challenges such as interference from irrelevant objects and the high cost associated with data collection. Consequently, devising algorithms capable of accurately localizing specific objects within a scene in scenarios where annotated data is limited remains a formidable challenge. To solve this problem, this paper proposes an object discovery by request problem setting and a corresponding algorithmic framework. The proposed problem setting aims to identify specified objects in scenes, and the associated algorithmic framework comprises pseudo… More >

Yunjing Liu^1,, Erhu Zhang^1,2,,*, Jingjing Wang³, Guangfeng Lin², Jinghong Duan⁴

CMC-Computers, Materials & Continua, Vol.80, No.1, pp. 1633-1653, 2024, DOI:10.32604/cmc.2024.052611

Abstract Recovering high-quality inscription images from unknown and complex inscription noisy images is a challenging research issue. Different from natural images, character images pay more attention to stroke information. However, existing models mainly consider pixel-level information while ignoring structural information of the character, such as its edge and glyph, resulting in reconstructed images with mottled local structure and character damage. To solve these problems, we propose a novel generative adversarial network (GAN) framework based on an edge-guided generator and a discriminator constructed by a dual-domain U-Net framework, i.e., EDU-GAN. Unlike existing frameworks, the generator introduces the… More >

Chunwei Tian^1,2,3,4, Haoyang Gao^2,3, Pengwei Wang², Bob Zhang^1,*

CMC-Computers, Materials & Continua, Vol.80, No.1, pp. 105-118, 2024, DOI:10.32604/cmc.2024.052097

Abstract Generative adversarial networks (GANs) with gaming abilities have been widely applied in image generation. However, gamistic generators and discriminators may reduce the robustness of the obtained GANs in image generation under varying scenes. Enhancing the relation of hierarchical information in a generation network and enlarging differences of different network architectures can facilitate more structural information to improve the generation effect for image generation. In this paper, we propose an enhanced GAN via improving a generator for image generation (EIGGAN). EIGGAN applies a spatial attention to a generator to extract salient information to enhance the truthfulness… More >