Search Results (266)

Agave species are plants with great economic value and multiple possibilities of use as ornamentals, medicinal plants, and fibers, as well as being significant sources of bioethanol. However, their long life cycles hinder their conventional breeding. Therefore, biotechnology tools are the most effective means for clonal propagation and genetic improvement. In vitro micropropagation of A. sisalana via axillary shoot proliferation from bulbil explants was attained using Murashige and Skoog medium (MS) supplemented with cytokinins (CKs), such as 6-benzyladenine (BA), kinetin (KIN), or thidiazuron (TDZ). The optimum significant shoot proliferation (14.67 shoots/explant) was achieved on 1.0 mg L⁻¹ TDZ. The carry-over effect of CKs on subsequent rooting could be detected. Control and KIN treatments could enhance the rooting of shoots on shoot proliferation media. The regenerated plantlets were acclimatized directly with 100% survival. To mitigate this carry-over effect, that causes hindering further root growth and development, and promote healthy growth of roots, subculturing shoots onto a CK-free medium is a recommended practice. The shoots induced on all BA treatments, and TDZ at 0.5 and 1.0 mg L⁻¹ could be rooted after two subcultures on CK-free medium, then they were acclimatized with 100% survival. However, the higher concentrations of TDZ inhibited in vitro rooting even after two subcultures on CK-free medium, and the acclimatization percentage was reduced by increasing the TDZ concentration recorded from 10 to 0%. Full article

The fungal pathogen Puccinia striiformis f. sp. tritici, which causes yellow rust disease, poses a significant economic threat to wheat production not only in Uzbekistan but also globally, leading to substantial reductions in grain yield. This study aimed to develop yellow rust-resistance wheat lines by introgressing Yr10 and Yr15 genes into high-yielding cultivar Grom using the marker-assisted backcrossing (MABC) method. Grom was crossed with donor genotypes Yr10/6*Avocet S and Yr15/6*Avocet S, resulting in the development of F₁ generations. In the following years, the F₁ hybrids were advanced to the BC₂F₁ and BC₂F₂ generations using the MABC approach. Foreground and background selection using microsatellite markers (Xpsp3000 and Barc008) were employed to identify homozygous Yr10- and Yr15-containing genotypes. The resulting BC₂F₂ lines, designated as Grom-Yr10 and Grom-Yr15, retained key agronomic traits of the recurrent parent cv. Grom, such as spike length (13.0–11.9 cm) and spike weight (3.23–2.92 g). Under artificial infection conditions, the selected lines showed complete resistance to yellow rust (infection type 0). The most promising BC₂F₂ plants were subsequently advanced to homozygous BC₂F₃ lines harboring the introgressed resistance genes through marker-assisted selection. This study demonstrates the effectiveness of integrating molecular marker-assisted selection with conventional breeding methods to enhance disease resistance while preserving high-yielding traits. The newly developed lines offer valuable material for future wheat improvement and contribute to sustainable agriculture and food security. Full article

Cannabis sativa L. is a versatile plant with significant medicinal, industrial, and recreational applications. Its therapeutic potential is attributed to cannabinoids like THC and CBD, whose production is influenced by environmental factors, such as radiation, temperature, and humidity. Radiation, for instance, is essential for photosynthetic processes, acting as both a primary energy source and a regulator of plant growth and development. This review covers key factors affecting C. sativa cultivation, including photoperiod, light spectrum, cultivation methods, environmental controls, and plant growth regulators. It highlights how these elements influence flowering, biomass, and cannabinoid production across different growing systems, offering insights for optimizing both medicinal and industrial cannabis cultivation. Studies indicate that photoperiod sensitivity varies among cultivars, with some achieving optimal flowering and cannabinoid production under extended light periods rather than the traditional 12/12 h cycle. Light spectrum adjustments, especially red, far-red, and blue wavelengths, significantly impact photosynthesis, plant morphology, and secondary metabolite accumulation. Advances in LED technology allow precise spectral control, enhancing energy efficiency and cannabinoid profiles compared to conventional lighting. The photoperiod plays a vital role in the cultivation of C. sativa spp., directly impacting the plant’s developmental cycle, biomass production, and the concentration of cannabinoids and terpenes. The response to photoperiod varies among different cannabis cultivars, as demonstrated in studies comparing cultivars of diverse genetic origins. On the other hand, indoor or in vitro cultivation may serve as an excellent alternative for plant breeding programs in C. sativa, given the substantial inter-cultivar variability that hinders the fixation of desirable traits. Full article

The worldwide agriculture industry is facing increasing problems due to rapid population increase and increasingly unfavorable weather patterns. In order to reach the projected food production targets, which are essential for guaranteeing global food security, innovative and sustainable agricultural methods must be adopted. Conventional approaches, including traditional breeding procedures, often cannot handle the complex and simultaneous effects of biotic pressures such as pest infestations, disease attacks, and nutritional imbalances, as well as abiotic stresses including heat, salt, drought, and heavy metal toxicity. Applying phytohormonal approaches, particularly those involving hormonal crosstalk, presents a viable way to increase crop resilience in this context. Abscisic acid (ABA), gibberellins (GAs), auxin, cytokinins, salicylic acid (SA), jasmonic acid (JA), ethylene, and GA are among the plant hormones that control plant stress responses. In order to precisely respond to a range of environmental stimuli, these hormones allow plants to control gene expression, signal transduction, and physiological adaptation through intricate networks of antagonistic and constructive interactions. This review focuses on how the principal hormonal signaling pathways (in particular, ABA-ET, ABA-JA, JA-SA, and ABA-auxin) intricately interact and how they affect the plant stress response. For example, ABA-driven drought tolerance controls immunological responses and stomatal behavior through antagonistic interactions with ET and SA, while using SnRK2 kinases to activate genes that react to stress. Similarly, the transcription factor MYC2 is an essential node in ABA–JA crosstalk and mediates the integration of defense and drought signals. Plants’ complex hormonal crosstalk networks are an example of a precisely calibrated regulatory system that strikes a balance between growth and abiotic stress adaptation. ABA, JA, SA, ethylene, auxin, cytokinin, GA, and BR are examples of central nodes that interact dynamically and context-specifically to modify signal transduction, rewire gene expression, and change physiological outcomes. To engineer stress-resilient crops in the face of shifting environmental challenges, a systems-level view of these pathways is provided by a combination of enrichment analyses and STRING-based interaction mapping. These hormonal interactions are directly related to the United Nations Sustainable Development Goals (SDGs), particularly SDGs 2 (Zero Hunger), 12 (Responsible Consumption and Production), and 13 (Climate Action). This review emphasizes the potential of biotechnologies to use hormone signaling to improve agricultural performance and sustainability by uncovering the molecular foundations of hormonal crosstalk. Increasing our understanding of these pathways presents a strategic opportunity to increase crop resilience, reduce environmental degradation, and secure food systems in the face of increasing climate unpredictability. Full article

Peanut (Arachis hypogaea L.) is a globally important oilseed cash crop, yet its limited genetic diversity and unique reproductive biology present persistent challenges for conventional crossbreeding. Traditional breeding approaches are often time-consuming and inadequate, mitigating the pace of cultivar development. Essential for double fertilization and programmed cell death (PCD), DUF679 membrane proteins (DMPs) represent a membrane protein family unique to plants. In the present study, a comprehensive analysis of the DMP gene family in peanuts was conducted, which included the identification of 21 family members. Based on phylogenetic analysis, these genes were segregated into five distinct clades (I–V), with AhDMP8A, AhDMP8B, AhDMP9A, and AhDMP9B in clade IV exhibiting high homology with known haploid induction genes. These four candidates also displayed significantly elevated expression in floral tissues compared to other organs, supporting their candidacy for haploid induction in peanuts. Subcellular localization prediction, confirmed through co-localization assays, demonstrated that AhDMPs primarily localize to the plasma membrane, consistent with their proposed roles in the reproductive signaling process. Furthermore, chromosomal mapping and synteny analyses revealed that the expansion of the AhDMP gene family is largely driven by whole-genome duplication (WGD) and segmental duplication events, reflecting the evolutionary dynamics of the tetraploid peanut genome. Collectively, these findings establish a foundational understanding of the AhDMP gene family and highlight promising targets for future applications in haploid induction-based breeding strategies in peanuts. Full article

Recognizing the interrelationship among variables becomes critical in genetic breeding programs, where the goal is often to optimize selection for multiple traits. Conventional multi-trait models face challenges such as convergence issues, and they fail to account for cause-and-effect relationships. To address these challenges, we conducted a comprehensive analysis involving confirmatory factor analysis (CFA), Bayesian networks (BN), structural equation modeling (SEM), and genome-wide selection (GWS) using data from 195 arabica coffee plants. These plants were genotyped with 21,211 single nucleotide polymorphism markers as part of the Coffea arabica breeding program at UFV/EPAMIG/EMBRAPA. Traits included vegetative vigor (VV), canopy diameter (CD), number of vegetative nodes (NVN), number of reproductive nodes (NRN), leaf length (LL), and yield (Y). CFA established the following latent variables: vigor latent (VL) explaining VV and CD; nodes latent (NL) explaining NVN and NRN; leaf length latent (LLL) explaining LL; and yield latent (YL) explaining Y. These were integrated into the BN model, revealing the following key interrelationships: LLL → VL, LLL → NL, LLL → YL, VL → NL, and NL → YL. SEM estimated structural coefficients, highlighting the biological importance of VL → NL and NL → YL connections. Genomic predictions based on observed and latent variables showed that using VL to predict NVN and NRN traits resulted in similar gains to using NL. Predicting gains in Y using NL increased selection gains by 66.35% compared to YL. The SEM-GWS approach provided insights into selection strategies for traits linked with vegetative vigor, nodes, leaf length, and coffee yield, offering valuable guidance for advancing Arabica coffee breeding programs. Full article

Maize (Zea mays L.), a vital global food crop, relies on its stomatal structure for regulating photosynthesis and responding to drought. Conventional manual stomatal detection methods are inefficient, subjective, and inadequate for high-throughput plant phenotyping research. To address this, we curated a dataset of over 1500 maize leaf epidermal stomata images and developed a novel lightweight detection model, StomaYOLO, tailored for small stomatal targets and subtle features in microscopic images. Leveraging the YOLOv11 framework, StomaYOLO integrates the Small Object Detection layer P2, the dynamic convolution module, and exploits large-scale epidermal cell features to enhance stomatal recognition through auxiliary training. Our model achieved a remarkable 91.8% mean average precision (mAP) and 98.5% precision, surpassing numerous mainstream detection models while maintaining computational efficiency. Ablation and comparative analyses demonstrated that the Small Object Detection layer, dynamic convolutional module, multi-task training, and knowledge distillation strategies substantially enhanced detection performance. Integrating all four strategies yielded a nearly 9% mAP improvement over the baseline model, with computational complexity under 8.4 GFLOPS. Our findings underscore the superior detection capabilities of StomaYOLO compared to existing methods, offering a cost-effective solution that is suitable for practical implementation. This study presents a valuable tool for maize stomatal phenotyping, supporting crop breeding and smart agriculture advancements. Full article

South Africa’s bioeconomy strategy identifies bio-innovation as a key driver of economic growth and social development, with plant breeding playing a central role in improving food security through the development of high-yielding, resilient, and high-quality crops. However, consumer perceptions of recent advances, particularly new breeding techniques (NBTs), remain underexplored. This study examines South African consumer attitudes towards plant breeding innovations, using a mixed-methods approach. The initial focus group interviews informed the development of a structured quantitative survey examining familiarity, perceptions, and acceptance of plant breeding technologies. Consumer awareness of plant breeding principles was found to be limited, with 67–68% of respondents unfamiliar with both conventional and modern plant breeding procedures. Despite this information gap, consumers expressed conditional support for modern breeding techniques, especially when associated with actual benefits like increased nutritional value, environmental sustainability, and crop resilience. When favourable effects were outlined, support for general investment in modern breeding practices climbed from 45% to 74%. Consumer purchase decisions emphasised price, product quality, and convenience over manufacturing techniques, with sustainability ranked last among the assessed factors. Trust in the sources of food safety information varied greatly, with medical experts and scientists being ranked highly, while government sources were viewed more sceptically. The results further suggest that targeted education could improve customer confidence, as there is a significant positive association (R² = 0.938) between familiarity and acceptance. These findings emphasise the significance of open communication strategies and focused consumer education in increasing the adoption of plant breeding breakthroughs. The study offers useful insights for policymakers, researchers, and industry stakeholders working on engagement strategies to facilitate the ethical growth and application of agricultural biotechnology in support of food security and quality in South Africa. This study contributes to a better understanding of South African consumers’ perceptions of plant breeding innovations and food safety. The research findings offer valuable insights for policymakers, researchers, and industry stakeholders in developing effective engagement and communication strategies that address consumer concerns and promote the adoption of products derived from diverse plant breeding technologies. Full article

The Phalaenopsis genus, a horticulturally vital group within the Orchidaceae, dominates global floriculture markets through strategic cultivar innovation, scalable propagation, and data-driven cultivation. This review systematically examines the breeding, propagation, cultivation management, and potential applications of Phalaenopsis while providing insights into future research directions. The main contents include the following: Breeding innovations—This review outlines the taxonomy of the Phalaenopsis genus and highlights its intergeneric hybridization potential, which offers vast opportunities for developing novel horticultural varieties. By establishing clear breeding objectives, researchers employ diverse breeding strategies, including conventional crossbreeding and biotechnological approaches (e.g., mutation breeding, ploidy manipulation, genetic transformation, and CRISPR/Cas9 editing). Propagation and cultivation management—Analyses of Phalaenopsis tissue culture protocols covering explant selection, media optimization, and regeneration systems are summarized. Key factors for efficient cultivation are discussed, including temperature, light, water, nutrient management, cultivation medium selection, and integrated pest/disease management. Scientific environmental control ensures robust plant growth, synchronized flowering, and high-quality flower production. Emerging applications—Phalaenopsis exhibits promising applications in functional bioactive compound extraction (e.g., antioxidants and antimicrobial agents). This review summarizes current advancements in Phalaenopsis breeding, cultivation, and potential applications. Based on technological progress and market demands, future research directions are proposed to support the sustainable development of the Phalaenopsis industry. Full article

Meeting the rising demand for staple grains now requires cultivars that combine high yield, enhanced nutritional value, and strong chemical resilience. Blue-kernel landraces from central Mexico are rich in anthocyanins yet remain highly susceptible to post-emergence herbicides, whereas modern hybrids detoxify these compounds through cytochrome P450 (CYP450) enzymes. We crossed the anthocyanin-rich variety Polimaize with a CYP450-tolerant hybrid and evaluated the two parents and their F₁ segregants (designated “White” and “Yellow”) under greenhouse applications of mesotrione (75 g a.i. ha⁻¹), nicosulfuron (30 g a.i. ha⁻¹), and their mixture. Across 160 plants, the hybrid retained 95% of control dry matter and showed ≤7% foliar injury under all treatments, whereas Polimaize lost 28% biomass and exhibited 36% injury after nicosulfuron. The Yellow class matched hybrid performance while maintaining a blue pericarp and a β-carotene-rich endosperm, demonstrating that nutritional and agronomic traits can be stacked. The White class displayed heterosis-driven compensatory growth, exceeding its untreated biomass by 60% with nicosulfuron and by 82% with the mixture despite transient bleaching. Chlorophyll and carotenoid fluorescence revealed rapid, zeaxanthin-linked photoprotection in all tolerant genotypes, consistent with accelerated CYP450-mediated detoxification. These findings show that broad-spectrum herbicide tolerance can be introgressed into pigment-rich germplasm through conventional breeding, providing a non-transgenic path to herbicide-ready, anthocyanin-rich maize. The strategy preserves local biodiversity while delivering cultivars suited to intensive, weed-competitive agriculture and offers a template for integrating metabolic resilience into other native crops. Full article

Lantana camara L. is sold worldwide for ornamental purposes, although it is also characterized by high invasiveness potential. Genetic and molecular data available for L. camara are still poor, and breeding is performed through conventional methods. This study focused on a molecular genotyping analysis through the ddRADseq method on an experimental collection of lantana clonal lines to evaluate the potential of molecular techniques in performing marker-assisted breeding, in favour of variety registration and in guaranteeing plant variety protection for the species. Although high genetic uniformity was observed in the population, a unique molecular profile was assigned to every line, indicating the effectiveness of the approach used. Interestingly, low degrees of heterozygosity were observed. In addition, the possibility of inferring ploidy levels through SNP profiles was assessed since it would avoid the necessity of previous biological knowledge and the use of fresh materials. Ploidy analysis is of high interest for lantana breeding to obtain less invasive triploids. Flow cytometry and chromosome counting were used for inference assessment. An nQuack framework provided correct results for the majority of the clonal lines, confirming its effectiveness. These findings encourage the adoption of molecular systems to help breed minor species such as L. camara. Full article

Cadmium (Cd) pollution in paddy soils causes a great threat to safe rice production in China. In this review, we summarized the key advances in the research of Cd pollution sources and statuses in Chinese soil and rice, explore the mechanisms of Cd transformation in the rice–soil system, discuss the agronomic strategies for minimizing Cd accumulation in rice grains, and highlight advancements in developing rice cultivars with low Cd accumulation. Anthropogenic activity is a main source of Cd in farmland. Cd in soil solutions primarily enters rice roots through a symplastic pathway facilitated by transporters like OsNRAMP5, OsIRT1, and OsCd1, among which OsNRAMP5 is identified as the primary contributor. Subsequently, Cd translocation is from roots to grains through the xylem and phloem, regulated by transporters such as OsHMA2, OsLCT1, and OsZIP7. Meanwhile, Cd sequestration in vacuoles controlled by OsHMA3 plays a crucial role in regulating Cd mobility during its translocation. Cd accumulation in rice was limited by the available Cd concentration in soil solutions, Cd uptake, and translocation in rice plants. Conventional agronomic methods aimed at reducing grain Cd in rice by suppressing Cd bio-availability without decreasing soil Cd content have been proven limited in the remediation of Cd-polluted soil. In recent years, based on the mechanisms of Cd absorption and translocation in rice, researchers have screened and developed low-Cd-accumulation rice varieties using molecular breeding techniques. Among them, some new cultivars derived from the null mutants of OsNRAMP5 have demonstrated a more than 93% decrease in grain Cd accumulation and can be used for applications in the next years. Therefore, the issue of Cd contamination in the rice of China may be fully resolved within a few years. Full article

Developing high phosphorus (P) efficient rice varieties is essential for sustainable phosphate resource conservation. This study evaluated 16 rice cultivars from four breeding eras: ancient (<1940), early conventional (1940–2000), modern conventional (2000–2020), and hybrid rice (2000–2020). Using pot experiments in low-P soil, we examined two P treatments: P0 (no P application, simulating low-P stress) and P50 (50 kg hm⁻¹ P application, normal P input). We systematically compared agronomic traits, P distribution patterns, and P uptake efficiency across breeding generations. The result showed that modern breeding significantly increased root biomass, shoot biomass, and grain yield while reducing plant height. Low-P stress (P0) had minimal impact on growth traits but negatively affected P uptake, particularly plant P content and accumulation patterns. Under P0 treatment, modern conventional varieties maintained a higher stem P concentration (0.47–0.65 g·kg⁻¹ vs. 0.27–0.49 g·kg⁻¹ in hybrid varieties; 0.47–0.65 g·kg⁻¹ vs. 0.18–0.28 g·kg⁻¹ in ancient varieties, p < 0.05). P allocation strategies varied significantly across breeding eras. Root P accumulation ratios decreased from ancient to modern varieties, while modern conventional rice had the highest stem P storage (24.1–30.5%), and hybrid rice allocated the largest partition of 76.4–78.1% P to grains. Additionally, P uptake efficiency and P fertilizer productivity increased by 131.09% and 91.21% (p < 0.01) from ancient to modern conventional rice, with hybrids exhibiting the highest values for both parameters. Principal component analysis (PCA) revealed distinct trait clusters separating ancient, conventional, and hybrid rice based on the agronomic traits, P uptake, and rhizosphere soil parameters. Random forest analysis identified that, under low-P conditions, root P content was the strongest predictor of grain yield, whereas under normal P conditions, rhizosphere pH had the highest relationship to grain yield. These findings demonstrate that modern breeding has enhanced P adaptation through optimized root architecture and organ-specific P allocation strategies, which providing valuable insights for developing future P-efficient rice varieties. Full article

Kalanchoe daigremontiana, a medicinal plant rich in bioactive compounds, has the potential to serve as a feed supplement, reducing reliance on conventional livestock medications while potentially enhancing productivity. This study evaluated the effects of K. daigremontiana supplementation over 52 days on kidney and liver function, metabolism, weight changes, and reproductive efficiency in multiparous Alpine goats during the breeding season. Fifty-five goats were assigned to either a control (CTL, n = 27; 47.6 ± 1.1 kg) or a K. daigremontiana-supplemented (KAL, n = 28; 47.6 ± 1.3 kg) diet. The KAL group received K. daigremontiana at a dry matter-based inclusion rate of 2 kg t⁻¹ of feed, while the CTL group received no supplementation. Blood samples were collected at four time points to assess the biochemical markers of kidney and liver function. Pregnancy was achieved through natural mating, and reproductive efficiency was evaluated. Overall, liver and kidney function did not differ significantly between treatments (p > 0.05). However, KAL supplementation was associated with increased creatinine (p < 0.05), ALP (p < 0.001), and bilirubin (p < 0.05) at specific time points, whereas CTL goats exhibited higher BUN (p < 0.001), AST (p < 0.05), albumin (p < 0.001), total protein (p ≤ 0.05), and phosphorus (p < 0.01) on specific dates. Other metabolic markers, weight gain, and reproductive efficiency did not differ between treatments (p > 0.05). Overall, Kalanchoe daigremontiana supplementation had mild, transient effects on goat health without significantly impacting productivity. Further research is needed to explore its long-term effects and optimal dosage for livestock nutrition. Full article

Background/Objectives: Genomic prediction is a powerful approach that predicts phenotypic traits from genotypic information, enabling the acceleration of trait improvement in plant breeding. Traditional genomic prediction methods have primarily relied on linear mixed models, such as Genomic Best Linear Unbiased Prediction (GBLUP), and conventional machine learning methods like Support Vector Regression (SVR). Traditional methods are limited in handling high-dimensional data and nonlinear relationships. Thus, deep learning methods have also been applied to genomic prediction in recent years. Methods: We proposed iADEP, Integrated Additive, Dominant, and Epistatic Prediction model based on deep learning. Specifically, single nucleotide polymorphism (SNP) data integrating latent genetic interactions and genome-wide association study results as biological prior knowledge are fused to an SNP embedding block, which is then input to a local encoder. The local encoder is fused with an omic-data-incorporated global decoder through a multi-head attention mechanism, followed by multilayer perceptrons. Results: Firstly, we demonstrated through experiments on four datasets that iADEP outperforms existing methods in genotype-to-phenotype prediction. Secondly, we validated the effectiveness of SNP embedding through ablation experiments. Third, we provided an available module for combining other omics data in iADEP and propose a novel method for fusing them. Fourthly, we explored the impact of feature selection on iADEP performance and conclude that utilizing the full set of SNPs generally provides optimal results. Finally, by altering the partition of training and testing sets, we investigated the differences between transductive learning and inductive learning. Conclusions: iADEP provides a new approach for AI breeding, a promising method that integrates biological prior knowledge and enables combination with other omics data. Full article