Search Results (152)

Breaking the maize yield plateau necessitates the development of density-tolerant varieties, for which recurrent selection is a key breeding strategy. However, a systematic understanding of how the interaction between selection density (parental screening environment) and evaluation density (variety testing environment) modulates genetic gain remains a critical knowledge gap. This study aimed to systematically elucidate this interaction and its impact on genetic gain and combining ability. We established two F2 base populations from distinct heterotic groups: Zheng 58 × LH196 (Stiff Stalk, SS) and Chang 7-2 × MBUB (Non-Stiff Stalk, NSS). Through bulk selection, we advanced populations for three cycles (C0, C2, C4) under three selection densities: low (60,000 plants/ha), medium (90,000 plants/ha), and high (120,000 plants/ha). Hybrids were generated using a double tester design and evaluated in multi-environment trials at Shijiazhuang in Hebei province and Xinxiang in Henan province in 2023 across matching density gradients. We employed analysis of variance (ANOVA) and general combining-ability (GCA) estimates to assess the genetic gains for yield and combining ability across 14 parental materials and 28 hybrids. Our results demonstrate that density compatibility between selection and evaluation environments is paramount. Genetic gain decreased by 0.89–26.52% with a density discrepancy of >30,000 plants/ha and plummeted by 19.71–77.44% when the discrepancy exceeded 60,000 plants/ha, underscoring the necessity of aligning selection density with the target environment. Under matched densities, population yield increased significantly with escalating density, with the high-density selection regime showing a maximum yield improvement of 53.78% from C0 to C4. Materials selected under high density exhibited superior performance and significantly higher combining ability (averaging a 238.35% increase) and genetic gain (averaging a 263.39% improvement) in medium-to-high-density environments, confirming strong positive selection pressure. Conversely, materials from low-density selection processes were better adapted to environments of ≤60,000 plants/ha. This study provides a crucial theoretical and practical foundation for establishing density-optimized recurrent breeding systems to directionally enhance genetic gain in maize. Full article

Plant height is a key agronomic trait influencing both seed production and yield in hybrid rice. In the elite japonica hybrid ‘Shenyou 26’, optimal plant height differences between the restorer line (‘Shenhui 26’) and the male sterile line (‘Shen 9A’) are critical for efficient pollination. In this study, we dissected the genetic basis of plant height variation using a doubled haploid (DH) population derived from ‘Shenyou 26’. Multi-environment phenotyping and QTL mapping identified seven QTLs associated with plant height, among which qPH1.1 and qPH9.1 were validated. qPH1.1 co-localized with the semi-dwarf gene SD1, and ‘Shen 9A’ carries a rare SD1-EQH allele that potentially confers reduced height relative to the SD1-EQ allele in ‘Shenhui 26’. qPH9.1 also contributed significantly to plant height variation, with the Shenhui26 allele increasing plant height in backcross validation. These findings indicate that plant height variation in ‘Shenyou 26’ is controlled by multiple loci, including SD1 allelic variants and other complementary QTLs, providing valuable resources for fine-tuning plant architecture in rice breeding. Full article

With the growing complexity of high-dimensional imbalanced datasets in critical fields such as medical diagnosis and bioinformatics, feature selection has become essential to reduce computational costs, alleviate model bias, and improve classification performance. DS-IHBO, a dynamic surrogate-assisted feature selection algorithm integrating relevance-based redundant feature filtering and an improved hybrid breeding algorithm, is presented in this paper. Departing from traditional surrogate-assisted approaches that use static approximations, DS-IHBO employs a dynamic surrogate switching mechanism capable of adapting to diverse data distributions and imbalance ratios through multiple surrogate units built via clustering. It enhances the hybrid breeding algorithm with asymmetric stratified population initialization, adaptive differential operators, and t-distribution mutation strategies to strengthen its global exploration and convergence accuracy. Tests on 12 real-world imbalanced datasets (4–98% imbalance) show that DS-IHBO achieves a 3.48% improvement in accuracy, a 4.80% improvement in F1 score, and an 83.85% reduction in computational time compared with leading methods. These results demonstrate its effectiveness for high-dimensional imbalanced feature selection and strong potential for real-world applications. Full article

Secondary metabolites, including alkaloids, flavonoids, and tannins, are crucial for human health, agriculture, and ecosystem functioning. Their synthesis is often species-specific, influenced by both genetic and environmental factors. The increasing demand for these compounds across various industries highlights the need for advancements in plant breeding and biotechnological approaches. Transcription activator-like effector nucleases (TALENs) have emerged as a powerful tool for precise genome editing, offering significant potential for enhancing the synthesis of secondary metabolites in plants. However, while plant genome editing technologies have advanced significantly, the application of TALENs in improving secondary metabolite production and expanding genetic diversity remains underexplored. Therefore, this review aims to provide a comprehensive analysis of TALEN-mediated genome editing in plants, focusing on their role in enhancing secondary metabolite biosynthetic pathways and improving genetic diversity. The mechanisms underlying TALENs are examined, including their ability to target specific genes involved in the synthesis of bioactive compounds, highlighting comparisons with other genome editing tools such as CRISPR/Cas9. This review further highlights key applications in medicinal plants, particularly the modification of pathways responsible for alkaloids, flavonoids, terpenoids, and phenolic compounds. Furthermore, the role of TALENs in inducing genetic variation, improving stress tolerance, and facilitating hybridization in plant breeding programs is highlighted. Recent advances, challenges, and limitations associated with using TALENs for enhancing secondary metabolite production are critically evaluated. In this review, gaps in current research are identified, particularly regarding the integration of TALENs with multi-omics technologies and synthetic biology approaches. The findings suggest that while underutilized, TALENs offer sustainable strategies for producing high-value secondary metabolites in medicinal plants. Future research should focus on optimizing TALEN systems for commercial applications and integrating them with advanced biotechnological platforms to enhance the yield and resilience of medicinal plants. Full article

A vision-based autonomous system for emasculating okra enhances agriculture by enabling precise flower bud identification, overcoming the labor-intensive, error-prone challenges of traditional manual methods with improved accuracy and efficiency. This study presents a framework for an adaptive, automated bud identification method to assist the emasculation process, hybridized optical coherence tomography (OCT). Three YOLOv8 variants were evaluated for accuracy, detection speed, and frame rate to identify the most efficient model. To strengthen the findings, YOLO was hybridized with OCT, enabling non-invasive sub-surface verification and precise quantification of the emasculated depth of both sepal and petal layers of the flower bud. To establish a solid benchmark, gold standard color histograms and a digital imaging-based method under optimal lighting conditions with confidence scoring were also employed. The results demonstrated that the proposed method significantly outperformed these conventional frameworks, providing superior accuracy and layer differentiation during emasculation. Hence, the developed YOLOv8 hybridized OCT method for flower bud identification and emasculation offers a powerful tool to significantly improve both the precision and efficiency of crop breeding practices. This framework sets the stage for implementing scalable, artificial intelligence (AI)-driven strategies that can modernize and optimize traditional crop breeding workflows. Full article

As nutrient allocation trade-offs occur between reproductive and vegetative development in crops, optimizing their partitioning holds promise for improving agricultural productivity and quality. Herein, we characterize the phenotypic diversity of the fruitfulness trait and identify associated genes in tea plants (Camellia sinensis). Over three consecutive years, we monitored the fruitfulness of an F₁ hybrid population (n = 206) derived from crosses of ‘Emei Wenchun’ and ‘Chuanmu 217’. A marked variation was observed in the yield of individual plants, ranging from complete sterility (zero fruits) to exceptionally high fertility (1612 fruits). Using the high-resolution genetic linkage map and the fruitfulness data, we identified a stable major QTL designated as qFN5. To fine-map the underlying gene(s), artificial pollination experiments were conducted with extreme phenotype individuals (with the highest vs. lowest fruit numbers). Bulked segregant RNA sequencing (BSR-Seq) with ovules collected at two and seven days post-pollination (DPP) identified the genomic intervals that exhibit a high degree of overlap with qFN5. Analysis of expression dynamics combined with functional genomics data revealed a prominent candidate gene, CsETR2 (TGY048509), which encodes an ethylene receptor protein. When CsETR2 was overexpressed in Arabidopsis thaliana, the transgenic lines exhibited significantly decreased reproductive performance relative to the wild-type plants. Relative to the wild type, the transgenic lines exhibited a significant decline in several key traits: the number of effective panicles decreased by 72.5%, the seed setting rate dropped by 67.7%, and the silique length shortened by 38%. These findings demonstrate its role in regulating plant fruitfulness. Furthermore, yeast one-hybrid and dual-luciferase assays verified that CsMYB15 (TGY110225) directly binds to the CsETR2 promoter, thus repressing its transcription. In summary, our findings expand the understanding of genetic regulation underlying fruitfulness in tea plants and provide candidate target loci for breeding. Full article

Saccharum spontaneum L. (wild sugarcane) possesses advantages such as strong perenniality, high stress resistance, and broad adaptability, making it the most successfully utilized wild species in sugarcane hybrid breeding. However, previous exploitation of S. spontaneum has been limited. To further explore its breeding potential, this study employed recurrent selection to improve the population of S. spontaneum (S0) before its application in germplasm innovation. Subsequently, S1 (containing two S. spontaneum bloodlines) were developed and optimized. Using S1 as dual parents, S2 (containing three or more S. spontaneum bloodlines) were further created and selected. Genetic diversity among 199 materials from seven populations (S0, S1 and S2) was evaluated using simple sequence repeat (SSR) markers. The results showed that an unweighted pair-group method with arithmetic means (UPGMA) cluster analysis based on genetic distance classified the 199 S. spontaneum materials into seven groups, largely consistent with their original population divisions. Compared to their parents, the S1 population generated an average of 18.79 novel loci (mutation rate: 25.00%), while the S2 population produced an average of 15.40 novel loci (mutation rate: 19.00%). The polymer of S. spontaneum exhibited rich genetic diversity, with Nei’s gene diversity index of 0.3390 and Shannon information index of 0.5082. Due to the increased number of original parents and trait pyramiding, the polymer of S. spontaneum demonstrated expanded genetic backgrounds and enhanced heterogeneity. Furthermore, hybridization and recombination generated novel elite loci compared to their parents, further enriching the overall genetic background and diversity of the polymer of S. spontaneum. Full article

Peanut (Arachis hypogaea L.) protein, as a precursor to various amino acids and bioactive peptides, determines the flavor and nutritional quality of peanut products. Therefore, high protein content is one of the target traits in advanced peanut breeding programs. In this review, we summarized the characteristics of all currently available high-protein peanut varieties in China and provided a comprehensive analysis of the genetic, physical characteristics, and disease resistance. These varieties mostly were developed through interspecific hybridization or selected from mutants of self-pollinated parents, primarily using the cultivars “Silihong” and “Baisha 1016” as main parental lines. In terms of disease resistance, although most high-protein peanut varieties can resist two to four types of disease, few varieties exhibit resistance to multiple diseases, and some varieties show no resistance for tested disease or lack sufficient experimental validation. The genetic basis of high-protein peanuts is relatively narrow, relying mainly on a small number of parental varieties. The findings of this review provide important references for high-protein peanut breeding, highlighting the existing problems and challenges in current breeding efforts and emphasizing the importance of broadening the genetic base, enhancing disease resistance breeding, and optimizing overall quality. This review offers theoretical and practical guidance for future breeding of high-quality, high-yield, and high-protein peanut varieties, contributing to the sustainable development and quality improvement of the peanut industry. Full article

Fragrant rhododendron varieties remain relatively limited in current germplasm resources, constraining the enhancement of ornamental and aromatic characteristics in rhododendron breeding—this limitation has emerged as a critical bottleneck in the genetic improvement of rhododendrons. This research takes fragrant flower breeding as the breeding objective and conducts hybridization between varieties of the subgenus Tsutsusi, which can flower in multiple seasons and exhibit relatively strong resistance, and the fragrant R. moulmainense. Parallel intraspecific hybridizations within the subgenus Tsutsusi were implemented as experimental controls to quantify hybridization affinity. This study combines floral tube ontogeny histomorphological analysis, ovary paraffin sectioning, and optimized pollination protocols to address hybridization constraints, providing new insights for rhododendron intersubgeneric distant hybridization to create fragrant varieties. The results showed varying fertility among combinations, with some showing sterility or weak fertility due to low pollen germination and abnormal embryo development. Both pre- and post-fertilization reproductive barriers were observed, and different pollination methods significantly influenced ovary expansion and fruit set rates. Regarding limitations, this study lacks an in-depth analysis of reproductive isolation mechanisms, only describing phenotypic characteristics through morphological and histological methods, and it does not employ molecular techniques. The fundamental causes of reproductive isolation between subgenera therefore remain unclear. Additionally, there was no long-term monitoring of seedling emergence rates, hybrid plant growth potential, or flowering traits. This limits the ability to comprehensively evaluate the breeding value and genetic stability of distant hybrids. Full article

Researching the photosynthetic activity of sunflower (Helianthus annuus L.) is essential for understanding how different genotypes respond to environmental conditions and utilise solar energy for growth and productivity. The objective of this study was to gain insight into and quantify the adaptation of ten sunflower hybrids during the flowering stage under field conditions. As part of an ongoing sunflower breeding programme, this research aimed to assess genotypic differences in photosynthetic performance and yield-related traits in response to variable environmental conditions. During the flowering stage, chlorophyll a fluorescence (ChlF) parameters revealed significant genotypic differences in energy fluxes, particularly in ABS/RC, DI₀/RC, ET₀/RC, and RE₀/RC. Those results indicate variability in light-harvesting efficiency and electron transport capacity. Although specific photochemical efficiency indicators (e.g., TR₀/RC, TR₀/ABS, ET₀/TR₀) showed slight variation, energy dissipation and photosystem I-related parameters differed significantly among hybrids. Leaf temperature and chlorophyll content also varied and showed moderate correlations with fluorescence-based indicators. Yield components (plant height, head diameter, and seed mass per head) displayed significant differences among sunflower hybrids, with notable opposite patterns between plant height and head size. Revealed strong relationships between photosynthetic performance (PI_TOTAL, RE₀/ABS) and yield traits, particularly plant height and number of seeds per head, were confirmed with correlation analysis. Principal Component Analysis (PCA) distinguished the hybrids into distinct groups. The analysis confirmed physiological and morphological variability among hybrids, enabling effective screening of genotypes for breeding purposes. Photosynthesis is a key physiological trait that directly influences biomass accumulation and seed yield, making it a critical parameter in evaluating the performance and adaptability of various sunflower genotypes. Thus, this study demonstrates the integrative value of combining ChlF, thermal, and agronomic traits for identifying high-performing sunflower hybrids under optimal field conditions. Full article

The increasing demand for novel cut chrysanthemum cultivars has underscored the significance of precision breeding techniques, with particular emphasis on hybridization and molecular tools. This study aimed to assess the cross-compatibility of selected chrysanthemum cultivars and to evaluate the genetic, quantitative, and qualitative diversity among the resulting F₁ progenies. A total of six hybrid combinations were generated using five commercial parental cultivars. Ploidy levels were determined via flow cytometry and chromosome counting, confirming that all parents were allohexaploid (2n = 6x = 54). Pollen viability and germination rates varied significantly among male parents, influencing hybridization success. A total of 30,391 seeds were obtained, with germination rates ranging from 2.69% to 10.73%, depending on the cross combination. F₁ progenies showed considerable phenotypic variability in flowering time, flower stalk length, flower diameter, and branch weight. Molecular characterization using eight iPBS primers revealed a high polymorphism rate (93%) with a mean Polymorphism Information Content (PIC) value of 0.614, confirming substantial genetic diversity among genotypes. Cluster and principal coordinate analyses demonstrated that most F₁ genotypes grouped closely with their maternal parents, although unique genomic variations were also detected. The integration of morphological and molecular data provides valuable insights for selecting superior genotypes and optimizing breeding strategies. This study highlights the importance of evaluating hybridization potential and genetic diversity in the development of commercially viable cut chrysanthemum cultivars. Full article

Fruit tree rootstock breeding is prolonged by extended juvenile phases, high heterozygosity, limited germplasm diversity, and hybrid incompatibilities, often requiring four decades to release new cultivars. Direct somatic embryogenesis (DSE) in established peach rootstocks presents a promising avenue for rapid genetic transformation and breeding. However, peach is highly recalcitrant to in vitro regeneration, posing major challenges for organogenesis and somatic embryogenesis (SE). This study evaluated the effects of 2,4-dichlorophenoxyacetic acid (2,4-D) and Kinetin (KIN) on SE %, SE productivity, and callus % rate in the widely used Guardian^® peach rootstock. A 5 × 3 full factorial completely randomized design was used to test 15 different combinations of 2,4-D and KIN on immature cotyledons, classified as upper or lower based on their position on the preculture medium. Media formulation containing a higher concentration (3.2 µM) of 2,4-D and KIN induced SE in ~50% of lower and ~85% of upper cotyledons. Optimal SE productivity occurred with higher KIN (3.2 µM) and reduced 2,4-D (2.6 µM). Callus formation peaked with 1.8 µM 2,4-D and 3.2 µM KIN. This highly reproducible research establishes a robust whole plant regeneration system via DSE in Guardian^® peach rootstock using immature cotyledons, providing a foundation for expedited trait manipulation through biotechnological approaches. Full article

In the context of global climate change and efforts toward “carbon peak and carbon neutrality,” forest resource protection and restoration have become fundamental to ecological civilization. The genetic improvement of trees, as the primary component of forest ecosystems, holds strategic importance for ecological security, resource supply, and carbon neutrality. Traditional tree breeding techniques, including selective and hybrid breeding, have established robust technical systems through extensive practice. However, these methods face limitations such as extended cycles, reduced efficiency, and constrained genetic gains in meeting contemporary requirements. Modern biotechnologies, including genomic selection (GS), gene editing (CRISPR/Cas9), and marker-assisted selection (MAS), substantially enhance the precision and efficiency of genetic improvement. Nevertheless, exclusive reliance on either traditional or modern methods proves insufficient for addressing complex environmental adaptation and rapid breeding requirements. Consequently, the integration of traditional breeding with modern biotechnology to develop intelligent, sustainable, and efficient breeding strategies has emerged as a central focus in tree genetics and breeding. An integrated “step-by-step” approach warrants promotion, supported by a multi-source data sharing platform, an optimized core germplasm repository, and a “climate-soil-genotype” matching model to facilitate the region-specific deployment of improved varieties. Full article

To address the issues of low efficiency, insufficient coverage, and high energy consumption in wheat sowing path planning for large-scale irregular farmland, this study proposes an improved hybrid particle swarm optimization algorithm (TLG-PSO) for autonomous operational path planning. Building upon the standard PSO, the proposed method introduces a Tent chaotic mapping initialization mechanism, a Logistic-based dynamic inertia weight adjustment strategy, and adaptive Gaussian perturbation optimization to achieve precise control of the agricultural machinery’s driving orientation angle. A comprehensive path planning model is constructed with the objectives of minimizing the effective operation path length, reducing turning frequency, and maximizing coverage rate. Furthermore, cubic Bézier curves are employed for path smoothing, effectively controlling path curvature and ensuring the safety and stability of agricultural operations. The simulation experiment results demonstrate that the TLG-PSO algorithm achieved exceptional full-coverage operation performance across four categories of typical test fields. Compared to conventional fixed-direction path planning strategies, the algorithm reduced average total path length by 6228 m, improved coverage rate by 1.31%, achieved average labor savings of 96.32%, and decreased energy consumption by 6.45%. In large-scale comprehensive testing encompassing 1–27 field plots, the proposed algorithm reduced average total path length by 8472 m (a 5.45% decrease) and achieved average energy savings of 44.21 kW (a 5.48% reduction rate). Comparative experiments with mainstream intelligent optimization algorithms, including GA, ACO, PSO, BreedPSO, and SecPSO, revealed that TLG-PSO reduced path length by 0.16%–0.74% and decreased energy consumption by 0.53%–2.47%. It is worth noting that for large-scale field operations spanning hundreds of acres, even an approximately 1% path reduction translates to substantial fuel and operational time savings, which holds significant practical implications for large-scale agricultural production. Furthermore, TLG-PSO demonstrated exceptional performance in terms of algorithm convergence speed and computational efficiency. The improved TLG-PSO algorithm provides a feasible and efficient solution for autonomous operation of large-scale agricultural machinery. Full article

The genus Paphiopedilum (Orchidaceae) has high ornamental value due to its long flowering period, brilliant flower color, and peculiar floral morphology. Guangxi is the center of ecological diversity of Paphiopedilum, and therefore it is urgent to conduct rescue studies on the genetic resources and genetic structure of this genus in Guangxi. In this study, the genetic diversity of 39 populations from eight Paphiopedilum species in Guangxi was analyzed using ten selected EST-SSR primer pairs and fluorescent PCR amplification. The results show that genetic diversity varied among species, with large differences in expected heterozygosity (He). The highest genetic diversity was observed in P. barbigerum (I = 0.923; He = 0.480), while P. dianthum (I = 0.179; He = 0.098) showed the lowest diversity. From the genus perspective, molecular variance analysis (AMOVA) revealed that 57% of the genetic variation occurred among populations and 43% within populations, with inter-population variation being the main source of genetic variation. From a species perspective, genetic differentiation varied, with inter-individual differentiation ranging from 79% to 95%. The percentage of molecular variance indicated that genetic variation mainly occurred among individuals, which was the main source of total variation. According to the principle of maximum likelihood, the optimal K value was determined to be 6, and 760 Paphiopedilum samples were divided into six subgroups. The results of this study not only identify priority populations for conservation and establish a germplasm repository to preserve existing resources, but also provide references for research on asexual reproduction, seed propagation, and hybrid breeding of Paphiopedilum, thereby promoting the conservation and sustainable utilization of Paphiopedilum germplasm resources. Full article