International Journal of Plant Biology

15 pages, 25261 KB

Open AccessArticle

Capability of ISSR, SCoT and CEAP Markers for Genetic Diversity Assessment of Lavender (Lavandula angustifolia Mill.) Genotypes

by Mariya Todorova Zhelyazkova

Int. J. Plant Biol. 2026, 17(1), 8; https://doi.org/10.3390/ijpb17010008 - 21 Jan 2026

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Abstract

Lavender has been cultivated in Bulgaria for over a century. The high essential oil content and quality of Bulgarian lavender varieties have established the country as a leading global producer. Studies into the crop’s genetic diversity are essential for selecting varieties best suited [...] Read more.

Lavender has been cultivated in Bulgaria for over a century. The high essential oil content and quality of Bulgarian lavender varieties have established the country as a leading global producer. Studies into the crop’s genetic diversity are essential for selecting varieties best suited to specific environmental conditions, maximizing resilience and yield. Therefore, identifying appropriate genetic markers to monitor lavender diversity is a key prerequisite for developing effective crop selection strategies, particularly in response to the challenges posed by global climate change. In this study, we evaluate the versatility of markers for assessing genetic diversity of lavender genotypes. A total of 96, 97 and 96 bands were recorded using the 13 Start Codon Targeted Polymorphism (SCoT), 13 Inter-Simple Sequence Repeat (ISSR) and 14 Cis-Element Aligned Polymorphism (CEAP) primers, respectively. All amplification programs used were successful in the studied genotypes. Additionally, four informative primers of each marker system were applied for assessment of the within-field genetic variability in two lavender plantations from Bulgaria. This is the first report on the combined use and comparison of CEAP, SCoT and ISSR primers in lavender genotypes in Bulgaria. Full article

(This article belongs to the Section Plant Biochemistry and Genetics)

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20 pages, 2028 KB

Open AccessReview

Advances in Boron, Iron, Manganese, and Zinc Signaling, Transport, and Functional Integration for Enhancing Cotton Nutrient Efficiency and Yield—A Review

by Unius Arinaitwe, Dalitso Noble Yabwalo, Abraham Hangamaisho, Shillah Kwikiiriza and Francis Akitwine

Int. J. Plant Biol. 2026, 17(1), 7; https://doi.org/10.3390/ijpb17010007 - 20 Jan 2026

Cited by 4 | Viewed by 1828

Abstract

Micronutrients, particularly boron (B), iron (Fe), manganese (Mn), and zinc (Zn), are pivotal for cotton (Gossypium spp.) growth, reproductive success, and fiber quality. However, their critical roles are often overlooked in fertility programs focused primarily on macronutrients. This review synthesizes recent advances [...] Read more.

Micronutrients, particularly boron (B), iron (Fe), manganese (Mn), and zinc (Zn), are pivotal for cotton (Gossypium spp.) growth, reproductive success, and fiber quality. However, their critical roles are often overlooked in fertility programs focused primarily on macronutrients. This review synthesizes recent advances in the physiological, molecular, and agronomic understanding of B, Fe, Mn, and Zn in cotton production. The overarching goal is to elucidate their impact on cotton nutrient use efficiency (NUE). Drawing from the peer-reviewed literature, we highlight how these micronutrients regulate essential processes, including photosynthesis, cell wall integrity, hormone signaling, and stress remediation. These processes directly influence root development, boll retention, and fiber quality. As a result, deficiencies in these micronutrients contribute to significant yield gaps even when macronutrients are sufficiently supplied. Key genes, including Boron Transporter 1 (BOR1), Iron-Regulated Transporter 1 (IRT1), Natural Resistance-Associated Macrophage Protein 1 (NRAMP1), Zinc-Regulated Transporter/Iron-Regulated Transporter-like Protein (ZIP), and Gossypium hirsutum Zinc/Iron-regulated transporter-like Protein 3 (GhZIP3), are crucial for mediating micronutrient uptake and homeostasis. These genes can be leveraged in breeding for high-yielding, nutrient-efficient cotton varieties. In addition to molecular hacks, advanced phenotyping technologies, such as unmanned aerial vehicles (UAVs) and single-cell RNA sequencing (scRNA-seq; a technology that measures gene expression at single-cell level, enabling the high-resolution analysis of cellular diversity and the identification of rare cell types), provide novel avenues for identifying nutrient-efficient genotypes and elucidating regulatory networks. Future research directions should include leveraging microRNAs, CRISPR-based gene editing, and precision nutrient management to enhance the use efficiency of B, Fe, Mn, and Zn. These approaches are essential for addressing environmental challenges and closing persistent yield gaps within sustainable cotton production systems. Full article

(This article belongs to the Topic Recent Progress in Plant Nutrition Research and Plant Physiology: 2nd Edition)

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25 pages, 4095 KB

Open AccessArticle

Comparison of Machine Learning Methods for Marker Identification in GWAS

by Weverton Gomes da Costa, Hélcio Duarte Pereira, Gabi Nunes Silva, Aluizio Borém, Eveline Teixeira Caixeta, Antonio Carlos Baião de Oliveira, Cosme Damião Cruz and Moyses Nascimento

Int. J. Plant Biol. 2026, 17(1), 6; https://doi.org/10.3390/ijpb17010006 - 19 Jan 2026

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Abstract

Genome-wide association studies (GWAS) are essential for identifying genomic regions associated with agronomic traits, but Linear Mixed Model (LMM)-based GWAS face challenges in capturing complex gene interactions. This study explores the potential of machine learning (ML) methodologies to enhance marker identification and association [...] Read more.

Genome-wide association studies (GWAS) are essential for identifying genomic regions associated with agronomic traits, but Linear Mixed Model (LMM)-based GWAS face challenges in capturing complex gene interactions. This study explores the potential of machine learning (ML) methodologies to enhance marker identification and association modeling in plant breeding. Unlike LMM-based GWAS, ML approaches do not require prior assumptions about marker–phenotype relationships, enabling the detection of epistatic effects and non-linear interactions. The research sought to assess and contrast approaches utilizing ML (Decision Tree—DT; Bagging—BA; Random Forest—RF; Boosting—BO; and Multivariate Adaptive Regression Splines—MARS) and LMM-based GWAS. A simulated F₂ population comprising 1000 individuals was analyzed using 4010 SNP markers and ten traits modeled with epistatic interactions. The simulation included quantitative trait loci (QTL) counts varying between 8 and 240, with heritability levels set at 0.5 and 0.8. These characteristics simulate traits of candidate crops that represent a diverse range of agronomic species, including major cereal crops (e.g., maize and wheat) as well as leguminous crops (e.g., soybean), such as yield, with moderate heritability and a high number of QTLs, and plant height, with high heritability and an average number of QTLs, among others. To validate the simulation findings, the methodologies were further applied to a real Coffea arabica population (n = 195) to identify genomic regions associated with yield, a complex polygenic trait. Results demonstrated a fundamental trade-off between sensitivity and precision. Specifically, for the most complex trait evaluated (240 QTLs under epistatic control), Ensemble methods (Bagging and Random Forest) maintained a Detection Power (DP) exceeding 90%, significantly outperforming state-of-the-art GWAS methods (FarmCPU), which dropped to approximately 30%, and traditional Linear Mixed Models, which failed to detect signals (0%). However, this sensitivity resulted in lower precision for ensembles. In contrast, MARS (Degree 1) and BLINK achieved exceptional Specificity (>99%) and Precision (>90%), effectively minimizing false positives. The real data analysis corroborated these trends: while standard GWAS models failed to detect significant associations, the ML framework successfully prioritized consensus genomic regions harboring functional candidates, such as SWEET sugar transporters and NAC transcription factors. In conclusion, ML Ensembles are recommended for broad exploratory screening to recover missing heritability, while MARS and BLINK are the most effective methods for precise candidate gene validation. Full article

(This article belongs to the Section Application of Artificial Intelligence in Plant Biology)

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18 pages, 1470 KB

Open AccessArticle

The Role of Phosphorus-Potassium Nutrition in Synchronizing Flowering and Accelerating Generation Turnover in Sugar Beet

by Aleksandra Yu. Kroupina, Pavel Yu. Kroupin, Mariya N. Polyakova, Malak Alkubesi, Alana A. Ulyanova, Daniil S. Ulyanov, Natalya Yu. Svistunova, Alina A. Kocheshkova, Gennady I. Karlov and Mikhail G. Divashuk

Int. J. Plant Biol. 2026, 17(1), 5; https://doi.org/10.3390/ijpb17010005 - 5 Jan 2026

Cited by 2 | Viewed by 1080

Abstract

Speed breeding technologies offer a promising avenue for accelerating crop improvement, yet their application to biennial crops like sugar beet remains constrained by extended generation cycles. This study examined the effects of supplemental phosphorus-potassium (PK) nutrition on the development of two hybrids under [...] Read more.

Speed breeding technologies offer a promising avenue for accelerating crop improvement, yet their application to biennial crops like sugar beet remains constrained by extended generation cycles. This study examined the effects of supplemental phosphorus-potassium (PK) nutrition on the development of two hybrids under a speed-breeding protocol. Plants received one of four nutritional regimes: PK supplementation, potassium (K) supplementation, standard Knop’s solution (KS), or nutrient deficiency (D). Digital phenotyping confirmed that adequate nutrition maintained photosynthetic health, as deficiency significantly reduced NDVI and increased PSRI by 75 days. The most notable, genotype-specific effects were observed in reproductive architecture. PK nutrition significantly increased the median number of flower stalks by 17% in Smart Iberia KWS (21.0 vs. 18.0) and substantially in Dubravka KWS (33.0 vs. 1.0). PK also supported root development, increasing mini-steckling weight by 45–183% under white light. In the generative phase, plants under PK nutrition consistently showed the highest progression to flowering and capsule formation. A consistent increase in median 1000-seed weight of 24–36% was associated with PK treatment. In conclusion, supplementing standard nutrition with phosphorus and potassium enhances key yield-related architectural traits and supports reproductive development in sugar beet under speed-breeding conditions, with the magnitude of response depending on genotype. This provides a practical basis for optimizing mineral nutrition to improve the efficiency of accelerated breeding protocols. This provides a practical basis for optimizing mineral nutrition to improve the efficiency of speed breeding protocols. Full article

(This article belongs to the Section Plant Reproduction)

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12 pages, 1422 KB

Open AccessArticle

Investigation of Watermelon Collection for Mutations Affecting Male Sterility

by Nikolay Velkov and Stanislava Grozeva

Int. J. Plant Biol. 2026, 17(1), 4; https://doi.org/10.3390/ijpb17010004 - 2 Jan 2026

Viewed by 1089

Abstract

Systems favoring cross-pollination, such as male sterility and female flowering type, are of great importance in the development of new hybrid cultivars and their seed production. The advantages of male sterility are expressed in the production of cheaper and competitive seeds. The presence [...] Read more.

Systems favoring cross-pollination, such as male sterility and female flowering type, are of great importance in the development of new hybrid cultivars and their seed production. The advantages of male sterility are expressed in the production of cheaper and competitive seeds. The presence of this characteristic in watermelon is not common, and in some cases, it is accompanied by negative manifestations. A collection of 150 watermelon genotypes was tested at the Maritsa Vegetable Crops Research Institute, Bulgaria, over the past nine years to search for a genetic source of male sterility. The results revealed that two mutations were found. The first mutation was in a plant of the Asar variety, which formed completely degenerated structures in the place of male and female flowers that were completely sterile. The other mutation affected male flowers, female flowers, and leaf shape. Male flowers produced a small amount of pollen. Female flowers were formed, but they were sterile and aborted at an early stage. The genotype can be propagated by pollination of the normal plants, which in the next generation segregate into mutant—25% and normal—75%. The gene source is phenotyped according to the main characteristics of the fruits and the vegetation period. The mutation found cannot be directly used in a breeding program, but it is of interest for studying this important trait. The success of detecting flowers that are sterile depends on the number of watermelon plants, which, for the conditions of the experiment, amounted to a minimum of 4492 plants at a probability level of P₃—0.95. Full article

(This article belongs to the Section Plant Biochemistry and Genetics)

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24 pages, 6307 KB

Open AccessArticle

Adaptability, Yield Stability, and Agronomic Performance of Improved Purple Corn (Zea mays L.) Hybrids Across Diverse Agro-Ecological Zones in Peru

by Gilberto Garcia, Fernando Montero, Maria Elena Torres, Selwyn Alvarez, Wildo Vasquez, Abraham Villantoy, Yoel Ruiz, Fernando Escobal, Hector Cántaro-Segura, Omar Paitamala and Daniel Matsusaka

Int. J. Plant Biol. 2026, 17(1), 3; https://doi.org/10.3390/ijpb17010003 - 25 Dec 2025

Cited by 3 | Viewed by 1484

Abstract

Purple corn (Zea mays L.) is a nutraceutical crop of increasing economic importance in Peru, yet its productivity is highly influenced by genotype × environment (G × E) interactions across heterogeneous agro-ecological zones. Therefore, selecting suitable genotypes for specific environments is essential [...] Read more.

Purple corn (Zea mays L.) is a nutraceutical crop of increasing economic importance in Peru, yet its productivity is highly influenced by genotype × environment (G × E) interactions across heterogeneous agro-ecological zones. Therefore, selecting suitable genotypes for specific environments is essential to optimize variety deployment and maximize site-specific yield. Five purple-maize genotypes (INIA-601, INIA-615, Canteño, PMV-581, and Sintético-MM) were evaluated in four contrasting Peruvian sites using a randomized complete-block design. Grain yield, field weight, anthesis–silking interval (ASI), plant height, and ear-rot incidence were analyzed with combined analysis of variance (ANOVA), the additive main effects and multiplicative interaction (AMMI), genotype and genotype-by-environment (GGE) biplots, Weighted Average of Absolute Scores (WAAS), weighted average of absolute scores and best yield index (WAASBY), and Y × WAAS indices. Environment accounted for 90.1% of field-weight variation (p < 0.0001) and 50.2% of grain-yield variation (p < 0.001), while significant G × E interactions (3.93% and 18.14%, respectively) justified bilinear modeling. AMMI1 and GGE “which-won-where” biplots identified INIA-615 and PMV-581 as broadly adapted, with INIA-615 achieving the highest WAASBY and positioning in quadrant IV of Y × WAAS (high yield, high stability). INIA-601 and Sintético-MM exhibited exceptional stability (low ASV) but moderate productivity; Canteño showed limited adaptability. Chumbibamba emerged as a key discriminating, high-productivity location. From an agronomic perspective, INIA-615 is recommended for high-productivity valleys such as Sulluscocha and Santa Rita, where its yield potential and stability are maximized. These findings underscore the potential of integrating multivariate stability metrics with physiological and disease-resistance traits to guide the selection of superior purple corn cultivars. Overall, INIA-615 represents a robust candidate for enhancing yield stability, supporting sustainable intensification, and expanding the nutraceutical value chain of purple corn in the Andean highlands. Full article

(This article belongs to the Section Plant Physiology)

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19 pages, 1565 KB

Open AccessArticle

Multifunctional Maize Rhizobacteria: Isolation, Characterization and Prospects for Sustainable Agriculture

by Zhuldyz Batykova, Aida Kistaubayeva, Malika Abdulzhanova, Gulina Doktyrbay, Laila Saidullayeva, Zhamila Baimirzayeva, Moldir Turaliyeva and Zhuldyz Ibraimova

Int. J. Plant Biol. 2026, 17(1), 2; https://doi.org/10.3390/ijpb17010002 - 23 Dec 2025

Viewed by 1096

Abstract

The increasing environmental challenges facing modern agriculture necessitate development of sustainable, eco-friendly alternatives to chemical inputs. This study aimed to isolate and characterize rhizophilic bacterial strains from the rhizosphere of the maize hybrid Turan 480 SV (Zea mays L.), with a focus on [...] Read more.

The increasing environmental challenges facing modern agriculture necessitate development of sustainable, eco-friendly alternatives to chemical inputs. This study aimed to isolate and characterize rhizophilic bacterial strains from the rhizosphere of the maize hybrid Turan 480 SV (Zea mays L.), with a focus on their plant growth-promoting and biocontrol traits. A total of 23 bacterial isolates were obtained, including 15 Gram-negative and 8 Gram-positive strains. Among these, three strains—CR14, CR18 and CR22—were selected for detailed analysis. All three demonstrated significant indole-3-acetic acid (IAA) production, phosphate and zinc solubilization, nitrogen fixation and antifungal activity. CR14 synthesized 56.01 mg L⁻¹ of IAA and demonstrated the highest zinc solubilization, while CR18 exhibited superior phosphate solubilization and protease activity. CR22 produced the highest IAA (61.46 mg L⁻¹) and demonstrated strong cellulase and amylase activity. In antagonism tests, CR14 suppressed Alternaria alternata with an 80 mm inhibition zone, while CR18 and CR22 effectively inhibited both A. alternata and Fusarium graminearum. Phylogenetic analysis based on 16S rRNA sequencing identified CR18 as Serratia quinivorans, CR14 as Pantoea agglomerans and CR22 as Pantoea sp. The functional diversity of rhizobacteria holds promise as bioinoculants for enhancing maize growth and protecting against soil-borne pathogens in sustainable agriculture. Full article

(This article belongs to the Section Plant–Microorganisms Interactions)

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14 pages, 1142 KB

Open AccessArticle

Quantitative Genetics of Vachellia nilotica (L.) P. J. H. Hunter & Mabb. (Fabaceae) in Provenance/Progeny Trial

by Isaac Theophile Ndjepel Yetnason, Adrian Christopher Brennan, Dorothy Tchatchoua Tchapda and Chimene Abib Fanta

Int. J. Plant Biol. 2026, 17(1), 1; https://doi.org/10.3390/ijpb17010001 - 19 Dec 2025

Viewed by 553

Abstract

(1) Background: In the Sudano-Sahelian zone of Cameroon, which is affected by drought and forest decline, Vachellia nilotica leaves and seeds are fodder for livestock. (2) Methods: A provenance and progeny study on growth performance and heritability of V. nilotica was carried out [...] Read more.

(1) Background: In the Sudano-Sahelian zone of Cameroon, which is affected by drought and forest decline, Vachellia nilotica leaves and seeds are fodder for livestock. (2) Methods: A provenance and progeny study on growth performance and heritability of V. nilotica was carried out to provide a reliable database for tree selection, improvement programs, and the creation of future forested areas in this region. Open-pollinated seeds from 120 mother trees (10 half-sib families per provenance) representing twelve provenances, 50–100 km apart, were used for a progeny trial near Maroua, the Far North region of Cameroon. The experimental design was a Fisher block. (3) Results: The results reveal significant differences among provenances only for the number of leaves, and the variability was marked by coefficients of variation ranging from 0.24−0.63. Narrow-sense heritability was measured, varying from 0.01 ± 0.009 to 0.74 ± 0.02, and genetic gain reached 21.83 at the selection intensity of 5% for the number of leaves per plant. The phenotypic coefficient of variation varied between 14% and 90%. Half-sib families were classified into three subgroups using hierarchical ascending classification, and provenances were grouped into five groups using principal component analysis. (4) Conclusions: These results could contribute to initiating tree selection, but more provenances, longer-term experiments, and molecular genetic testing are needed to complement these nursery-level observations. Full article

(This article belongs to the Section Plant Ecology and Biodiversity)

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Int. J. Plant Biol., Volume 17, Issue 1 (January 2026) – 8 articles

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