Search Results (109)

A breeding program was established in Cuba using 19 full-sib families of sweetpotato (Ipomoea batatas [L.] Lam.) introduced as botanical seed from the International Potato Center (CIP). The objective was to develop biofortified cultivars combining high yield, phenotypic stability, and high β-carotene content under tropical conditions. The program followed a four-stage pipeline: (1) F₁ population establishment and visual selection (1732 plants) for morphological and pest/disease resistance traits; (2) initial clonal evaluation (C1) of 103 genotypes, estimation of genetic parameters, and multi-trait selection; (3) advanced evaluation of 19 elite genotypes, including analysis of genetic correlations and stability across two seasons; and (4) multi-environment trials (13 locations) with AMMI, GGE biplot, and MGIDI analyses. General and specific combining abilities were estimated, and broad-sense heritability (H²) was calculated. Three new biofortified cultivars ‘INICIP Dorado-4’, ‘INICIP B-30’, and ‘INICIP B-60’ were selected. These combine high yields, high β-carotene content, and distinct profiles for specific agronomic niches, with a total cumulative phenotypic gain of +352.8% achieved over four selection stages within a three-year period. This pipeline constitutes a replicable model for resource-constrained regions, demonstrating the potential of CIP germplasm to drive sweetpotato biofortification. Full article

Spider mites (Oligonychus trichardti) are emerging as a major constraint to Urochloa forage productivity in East Africa; however, knowledge of genotypic variation and tolerance remains limited. Herein, 55 Urochloa genotypes were evaluated under field-infested and non-infested conditions across two seasons using an alpha-lattice design. Agronomic and physiological traits, including plant height (PH), tiller number (TN), the Normalized Difference Vegetation Index (NDVI), total dry weight (TDW), and mite damage indices (visual severity index (VSI) and stress tolerance index (STI)) were assessed. Infestation reduced biomass by 22.4% on average, with reductions of up to 45% in susceptible genotypes. Significant genotypic variation was detected for PH, TN, TDW, and VSI. Heritability estimates under mite infestation were moderate to high for all traits except TDW, suggesting that direct selection of these traits could be effective in breeding programs aimed at improving mite resistance. VSI showed a strong negative correlation with NDVI (r = −0.63), supporting its value as a phenotyping indicator of spider mite response. Additive main effects and multiplicative interaction (AMMI) analysis revealed significant genotype × environment interactions for TDW. The AMMI biplot identified Xaraes, ILRI_13369, and ILRI_14787 as high-yielding and stable genotypes, while the AMMI Stability Value (ASV) and the Weighted Average of Absolute Scores from the Best Linear Unbiased Prediction (WAASB) identified CIAT_16122, CIAT_664, ILRI_14801, ILRI_14787, and ILRI_13266 as the most stable and broadly adapted across environments. STI further highlighted ILRI_13751 (2.71) and ILRI_13531 (2.58) as highly tolerant under stress. Overall, the study reveals substantial exploitable genetic diversity and identifies stable, high-yielding, and mite-tolerant genotypes suitable for breeding to improve Urochloa productivity in East Africa. Full article

Barley remains the fourth most cultivated cereal crop worldwide and is valued for its versatility in malting and brewing, animal feed, human nutrition, and dietary supplements. The identification of genotypes suitable for breeding or specific end-use applications requires multi-environment testing to evaluate agronomic performance, grain quality, and trait stability. In this study, a panel of 50 winter barley genotypes (two-row and six-row) originating from diverse genetic backgrounds was evaluated over three growing seasons (2021–2023) under the environmental conditions of southeastern Romania. Seven traits were analyzed, including three phenological traits (heading time, flowering time and plant height), grain yield, and three quality parameters (thousand-grain weight, protein content, and starch content). Environmental conditions had a strong influence on phenological development and grain yield, whereas grain quality traits showed relatively greater stability, indicating a stronger genetic control. Multivariate analyses (Principal Component Analysis (PCA) and Genotype plus Genotype-by-Environment interaction biplot (GGE biplots)) revealed clear relationships among traits and highlighted contrasting adaptive strategies between the two barley types. In two-row barley, genotypes such as Idra and Sandra combined favorable yield performance with stable grain quality traits and therefore represent promising candidates for breeding programs and large-scale cultivation. In six-row barley, SU-Ellen and LG Zebra showed high productivity and strong starch accumulation, making them valuable genetic resources for yield-oriented breeding, although further improvement in nitrogen use efficiency may be beneficial. The 2022–2023 growing season represented the most restrictive environment, emphasizing the importance of stability under stress conditions. Genotypes located close to the Average Environment Coordination axis (AEC axis) during that season, such as Ametist (six-row) and Lardeya (two-row), may represent promising material for breeding programs targeting drought resilience. Overall, the results expand the phenotypic characterization of winter barley germplasm and identify valuable genetic resources that can support pre-breeding efforts and the development of climate-resilient barley cultivars. Full article

Grain quality traits in wheat (Triticum aestivum L.), including protein content, gluten strength, and carbohydrate composition, are key determinants of end-use performance and breeding potential. This study assessed the genetic variability, stability, and multivariate relationships of seed quality traits among elite F7 pure lines derived from six long-term cultivated wheat cultivars. Field trials were conducted across six contrasting environments to evaluate genotype, environment, and genotype × environment (G × E) effects on crude protein, fat, ash, starch, crude fiber, Zeleny sedimentation, carbohydrates, non-starch carbohydrates, and moisture. Combined ANOVA revealed that genotypic effects accounted for the largest proportion of variation, though significant environmental and G × E effects were also observed. Broad-sense heritability was high for protein, Zeleny, and carbohydrate content. Stability analysis using the Stability Index (SI) highlighted A1, A2, A4, C2, E1, and F2 as genotypes combining high mean performance with a consistent expression across all environments. Principal component analysis (PCA) illustrated key trait relationships and trade-offs, particularly the negative association between protein-related traits and carbohydrate accumulation, while revealing the partial clustering of genotypes with similar quality profiles. AMMI and GGE biplots further supported broad adaptation for some genotypes (e.g., E1, F4, E2 for crude protein; F3, F4, E2 for Zeleny) and trait- or environment-specific performance for others. Correlation analyses confirmed positive associations between protein and gluten strength, and negative correlations with carbohydrate traits. Overall, targeted pure-line selection effectively exploits intracultivar genetic variation, offering a practical strategy for identifying superior, resilient wheat lines for breeding programs across diverse environments. Full article

Cotton (Gossypium spp.) seeds are a valuable source of protein, oil, and minerals; however, seed-quality traits have received less attention than fiber traits, particularly in partially interspecific germplasm. This study evaluated the performance and stability of five cottonseed quality traits (1000-seed weight, crude protein, oil, ash, and crude fiber) in four partially interspecific Pa7 cotton lines (G. hirsutum × G. barbadense) and one commercial cultivar, grown under three irrigation levels and two nitrogen fertilization regimes across two Mediterranean growing seasons in Northern Greece. A strip–split plot factorial design with three replications was used, and year × irrigation combinations were treated as six distinct environments. Trait responses were analyzed using multi-way ANOVA, stability metrics (stability index and coefficient of variation), correlation analysis, principal component analysis (PCA), and genotype × environment interaction models (AMMI and GGE biplots). Multi-way ANOVA revealed significant effects of genotype, environment, and management practices, as well as their interactions, indicating complex regulation of cottonseed composition. Genotypic effects were significant for all traits, while environmental effects were particularly strong for protein content. The greater environmental sensitivity of protein content highlights the key role of nitrogen-related processes and indicates that optimized fertilization can partially offset environmentally induced variability in seed protein accumulation. Stability analysis showed that storage-related traits (protein, oil, ash, and crude fiber) were generally more stable across environments than 1000-seed weight. Among the genotypes, M4 consistently combined high trait performance with broad stability across environments, whereas M1 exhibited the greatest stability for 1000-seed weight. Multivariate and GEI analyses complemented univariate results by revealing trait associations, physiological trade-offs, and crossover responses among genotypes. Overall, using both stability indices and multivariate analyses enabled a detailed evaluation of cottonseed quality in partially interspecific material, supporting the identification of suitable genotypes and optimization of management practices under varying Mediterranean conditions. Full article

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 study evaluated the growth performance and physiological responses of 24 Korean landrace accessions of pak choi (Brassica rapa subsp. chinensis) under polyethylene glycol (PEG)-induced drought stress to identify indicators for selecting drought-resistance genotypes. Electrolyte leakage (EL) and chlorophyll fluorescence (Fv/Fm) analyses showed that resistance accessions (IT262109(11), IT279432(12), IT293143(20)) had minimal increases in EL and maintained high Fv/Fm values under stress, indicating superior membrane stability and photosystem II activity. In contrast, sensitive accessions exhibited a sharp rise in EL and a decline in Fv/Fm to approximately 0.3 under 25% PEG treatment, reflecting severe physiological damage. Principal component analysis (PCA) biplot based on integrated growth and photosynthetic parameters differentiated resistance and sensitive groups, with PC1 representing photosynthetic efficiency versus membrane injury. Growth trait responses interaction analysis using GGE biplot of six representative accessions (three resistance, three sensitive) demonstrated that resistance genotypes had smaller positional shifts across treatments, indicating greater growth stability, while sensitive genotypes showed pronounced variability and environment-specific responses. This study provides a framework integrating growth and physiological indicators for identifying drought-resistance pak choi accessions, offering valuable implications for breeding programs aimed at climate-resilient cultivar development. Full article

Durum wheat (Triticum durum Desf.) underpins semolina value chains in water-limited regions, yet Peru remains import-dependent due to constrained local adaptation. We evaluated eleven elite lines plus the commercial variety ‘INIA 412 Atahualpa’ across three contrasting semi-arid sites in Arequipa (Santa Elena, San Francisco de Paula, Santa Rita) during 2023–2024 to identify genotypes maximizing performance and stability. Grain yield, thousand-kernel weight (TKW), hectoliter weight, and plant height were analyzed with combined analysis of variance (ANOVA), the additive main effects and multiplicative interaction (AMMI) and genotype and genotype-by-environment (GGE) biplots, complemented by AMMI stability value (ASV) and weighted average of absolute scores and best yield index (WAASBY). Grain yield and hectoliter weight showed significant genotype × environment (G × E) interaction, while plant height was driven mainly by genotype and environment with limited interaction. For grain yield, AMMI (PC1: 55.2%) and GGE (PC1 + PC2: 90.2%) revealed crossover responses and three practical mega-environments: TD-053 “won” at San Francisco de Paula, TD-037 at Santa Elena, and TD-033 at Santa Rita. Additionally, WAASBY-integrated rankings favored TD-033 (93.7%) and TD-014 (84.72%), followed by TD-026/TD-020 (>57%), whereas TD-062 (9.1%) and TD-043/TD-061 underperformed. Quality traits highlighted TD-044 and TD-014 for high hectoliter weight and TD-014/TD-062 for high TKW with contrasting stability. Overall, TD-033 and TD-014 were adaptable across environments, providing selection guidance to strengthen Peru’s durum breeding pipeline under climate variability. Full article

Cotton production in Mediterranean regions is increasingly constrained by limited water availability, making it essential to identify genotypes that can maintain yield under reduced irrigation. In this study, four partially interspecific cotton lines (Pa7) and the commercial cultivar Celia were evaluated under two nitrogen rates designed to test resource-use efficiency and three irrigation regimes across two growing seasons in Greece. A strip–split plot design with three replications was used, and field data were analyzed with ANOVA, stability indices, and multivariate tools (Additive Main Effects and Multiplicative Interaction—AMMI, and Genotype plus Genotype × Environment—GGE biplots). Results showed that moderate irrigation consistently ensured stable seed cotton yields, whereas a higher water supply increased the plant height without proportional yield benefits, while fertilizer supplied in the specific quantities showed a lower impact on yield stability. Genotype × environment interactions were highly significant: Celia confirmed its high stability, while line M3 combined good stability with favorable agronomic traits. Yield was strongly associated with boll weight and lint percentage, indicating their usefulness as indirect selection criteria. These findings highlight the agronomic potential of partially interspecific cotton lines and demonstrate that moderate irrigation can sustain productivity while reducing water inputs, contributing to a more efficient use of resources in cotton production under water-limited conditions. These results provide practical insights for breeding and water management strategies aiming to sustain cotton productivity under Mediterranean water-limited conditions. Full article

Cowpea production in Nigeria, the world’s largest producer, is insufficient to meet domestic demand due to significant yield gaps caused by various production constraints. Several high-yielding improved cowpea varieties have been developed and disseminated among smallholder farmers to improve productivity, but their adoption is low because breeding efforts have not adequately incorporated farmers’ and consumers’ preferred traits. To address this, a study was conducted to evaluate the performance of newly developed cowpea lines and identify those with traits preferred by farmers and consumers. Twenty-four cowpea lines were evaluated in multiple environments under sole and intercropped systems in Nigeria. The study revealed significant (p < 0.001) genotypic and genotype-by-environment interaction effects for grain yield, fodder yield, and other key agronomic traits. Three genotypes consistently outperformed the standard check, with UAM15-2157-4 exhibiting a 57.6% higher grain yield and superior seed quality. UAM15-2157-4 produced the highest grain yield (1289 kg ha⁻¹) under the intercropping system. GGE biplot analysis identified UAM15-2157-4 as the most stable genotype across all tested environments. This genotype, along with other promising lines, possesses desirable traits such as Striga resistance, large seed size, and preferred seed coat color, making them suitable for release and adoption to improve cowpea productivity in the region. Full article

The present study aimed to determine the Genotype × Environment interaction (GEI), yield stability, and agronomic performance of 24 “Pinto” bean lines under semi-arid conditions in Central-West Mexico. All the lines possess a slow-darkening seed coat, a trait that prolongs visual quality and increases market value. The lines, which exhibit an indeterminate prostrate growth habit, were evaluated in three contrasting environments: irrigated, rainfed, and drought-stressed. A combined analysis of variance, Tukey’s test, and the additive main effects and multiplicative interaction (AMMI 2) model were applied to assess seed yield and agronomic traits. Average seed yield declined markedly across environments, from 2279 kg ha⁻¹ under irrigation to 593 kg ha⁻¹ under drought stress, with different lines performing best in each environment. AMMI 2 biplot analysis showed that the first two principal components explained 100% of GEI variability for seed yield, dry shoot biomass, total biomass, harvest index, pods per plant, and seeds per pod. Both genetic and environmental effects were significant, with notable GEI patterns. Despite pronounced environmental influence, several lines exhibited stable performance across environments. Line 11 consistently combined high yield and stability, positioning it as a strong candidate for cultivar registration and as a parent in breeding programs targeting semiarid regions. These results underscore the importance of multi-environment evaluation for identifying genotypes with broad or specific adaptation, contributing to genetic improvement and sustainable bean production under variable moisture regimes. Full article

A pivotal food crop in arid and semi-arid zones, proso millet boasts remarkable economic value, making the breeding of stable high-yield varieties critical for industrial sustainability. This study employed a randomized complete block design to conduct a two-year multi-environment trial on nine new varieties across six representative spring-sown test regions in China. Analytical tools, including additive main effects and multiplicative interaction (AMMI) biplots, AMMI stability values (ASV), genotype and genotype × environment (GGE) models, and genotype by yield–trait (GYT) biplots were utilized to assess genotype–environment (G × E) interactions and screen superior genotypes. AMMI variance analysis showed extremely significant effects of genotype, environment, and G × E on yield traits (p < 0.01). G × E principal component analysis identified JS8, PS3, PS6, and PM4 as dominant genotypes. Based on ASV indices, varietal stability rankings were PS5 > YS13 > JS8 > PS3 > PS6 > PM4 > others. GGE analysis indicated PM4 had the broadest adaptability across tested environments, while JS15 exhibited specific adaptability in Datong. Huairen and Shuozhou were validated as ideal testing environments via an ideal environment plot. GYT biplots further confirmed that YS13, JS15, PS3, and PM4 excelled in comprehensive yield–trait combinations. These findings offer a scientific foundation for ecological adaptability evaluation, breeding material selection, and commercial variety promotion. Full article

Climate change poses significant challenges to agriculture in Türkiye, where diverse climatic conditions demand resilient forage crops to meet rising roughage demands. This study evaluates the performance of Hungarian vetch (Vicia pannonica Crantz), a cold- and drought-tolerant legume, to enhance sustainable forage production. Eight genotypes (Line-5, Line-16, Line-23, Line-28, Tarm White, Aegean White, Budak, and Oguz) were tested in Bilecik and Bingol during the 2015–2016 and 2016–2017 growing seasons using a randomized complete block design with three replications. Key traits such as pods per plant, thousand-seed weight, biological yield, seed yield, straw yield, and harvest index were analyzed using Genotype plus Genotype-by-Environment (GGE) biplot analysis based on Principal Component Analysis (PCA). The distribution of these traits was also examined using box plots. Results showed significant variations: pods per plant ranged from 17.5 to 21.7, thousand-seed weight from 26.8 to 42.6 g, biological yield from 5710 to 8780 kg ha⁻¹, seed yield from 826 to 1132 kg ha⁻¹, straw yield from 4997 to 7643 kg ha⁻¹, and harvest index (HI) from 13.9% to 21.0%. Aegean White excelled in seed yield, while Line-16 showed the highest harvest index. GGE biplot analysis highlighted harvest index as the primary variance contributor, emphasizing genotype-environment interactions for selecting adaptable cultivars for sustainable agriculture. Full article

Lentil (Lens culinaris Medikus) is a critical food crop offering high protein and essential micronutrients. However, its productivity and nutritional quality are increasingly threatened by climate change. In this study, 36 lentil genotypes were evaluated across two Moroccan locations under normal, heat stress, and combined heat and drought stresses. Significant effects of genotype, environment, and their interactions were observed on seed yield, seed size, cooking time, and nutritional quality. Heat and drought stresses caused substantial reductions in seed yield (up to 40% under combined stress), protein content, iron, and zinc concentration, and increased phytic acid levels, which negatively impacted iron and zinc bioavailability. Cooking time significantly decreased under stress conditions, with up to 54% reduction under combined heat and drought stresses at Annoceur research station. Correlation analysis revealed complex trade-offs among yield, nutritional quality, and cooking traits under stress conditions. Principal component analysis and GGE biplot analyses identified genotypes with superior yield, micronutrient concentration, and cooking time stability across environments. Genotypes such as G32, G3, and G36 combined high iron and zinc levels; G13 and G30 showed low phytic acid, while G 15 exhibited the shortest cooking time. These genotypes also demonstrated adaptability across the tested environment. This study highlights the potential of selecting climate-resilient, nutrient-dense lentil genotypes to support breeding efforts aimed at improving food security in the face of global climate variability. These genotypes can be suggested as elite climate-resilient parental lines to support breeders in enhancing lentil yield, nutritional quality, and stability under multiple stress conditions. Full article

Flowering represents the most important process in the reproductive stage of fruit trees, including olive trees. Previous studies have demonstrated that the genotype–environment interaction (GEI) has a considerable influence on olive flowering time. This study investigated the GEI and genetic parameters influencing olive flowering phenology in Southwestern China (a non-Mediterranean region), using multi-trait-based stability selection methods. Sixteen olive cultivars from five countries were evaluated over two years in two distinct climatic regions of Southwestern China. Flowering phenology was assessed based on three parameters: full-bloom date (FBD), flowering-period length (FP), and full-bloom-period length (FBP). In the analyses, the best linear unbiased prediction (BLUP) to predict genetic value and genotype + genotype by environment interaction (GGE) biplot methods to visualize and assess stability and performance were employed across four environments. The results showed that genotype, environment, and GEI had highly significant effects on flowering traits, with GEI accounting for 54.12% to 89.62% of the variance. Heritability values were low (0.0589 to 0.262), indicating that genetic factors had limited control over flowering phenology compared to environmental factors. A stability analysis using a mean performance and stability (MPS) index identified genotypes with earlier flowering dates and longer flowering periods. Multi-trait selection using a multi-trait mean performance and stability (MTMPS) index further highlighted six superior genotypes with high performance and stability across environments. The findings emphasize the critical role of environmental factors on olive flowering phenology, highlighting the challenges in breeding for stable flowering traits. This study demonstrates the effectiveness of multi-trait selection methods in identifying genotypes with superior performance and stability under different environmental conditions. These results provide valuable insights for olive breeding programs, particularly in non-Mediterranean regions, suggesting that targeted selection and multi-trait evaluation could enhance the adaptability and productivity of olive cultivars under changing climatic conditions. Full article