Search Results (15)

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

Expanding Coffea canephora cultivation to transitional altitudes offers a promising strategy to sustain coffee production under climate change. This study evaluated 27 genotypes cultivated under two water management regimes (fully and minimally irrigated) at 650 m altitude in Espírito Santo, Brazil, over eight harvests (2018–2025). A split-plot design was analyzed using a three-way mixed model (REML/BLUP) to estimate genetic parameters and predicted genotypic values. Adaptability and stability were assessed using the harmonic mean of relative performance of genotypic values (HMRPGV) and weighted average of absolute scores (WAASB) and integrated into a multi-trait selection index. Significant genotypic and temporal effects were detected, while the interaction between genotypes and water management regimes was non-significant, indicating consistent performance under different water regimes. Broad-sense heritability was moderate, with high selective accuracy. Genotypes 108 and 203 achieved the highest predicted yields (91.4 and 86.8 bags ha⁻¹) and superior adaptability. The multi-trait index identified six outstanding genotypes—108, 203, 201, 306, 303, and 302—combining high yield, broad adaptability, and temporal stability, resulting in an expected genetic gain of 8.17% in relation to the original population. These findings demonstrate that selected C. canephora genotypes are well adapted to transitional altitudes, supporting breeding programs for climate-resilient and high-yielding crops. Full article

In recent years, plantations of Aquilaria sinensis in China have been dominated by Qi-nan, yet there remains limited research on the growth evaluation and breeding of these clones. In this study, a multi-point joint variance analysis, an additive main effect and multiplicative interaction (AMMI) model, a weighted average of absolute scores (WAASB) stability index, and a genotype main effect plus a genotype-by-environment interaction (GGE) biplot were used to comprehensively analyze the yield, stability, and suitable environment of 25 3-year-old Qi-Nan clones from five sites in southern China. The results showed that all the growth traits exhibited significant differences in the clones, test sites, and interactions between the clones and test sites. The phenotypic variation coefficient (PCV) and genetic variation coefficient (GCV) of the clones’ growth traits at the different sites ranged from 16.56% to 32.09% and 5.24% to 27.06%, respectively, showing moderate variation. The medium–high repeatability (R) of tree height and ground diameter ranged from 0.50 to 0.96 and 0.69 to 0.98, respectively. Among the clones, Clones G04, G05, G10, G11 and G13 showed good growth performance and could be good candidates for breeding. Environmental effects were found to be the primary source of variation, with temperature and light primarily affecting growth, while rainfall influenced survival and preservation rates. Yangjiang (YJ) was found to be the most suitable experimental site for screening high-yield and stable clones across the different sites, whereas the tree height and ground diameter at the Chengmai (CM) site were significantly higher than at the other sites, and the Pingxiang (PX) and Zhangzhou (ZZ) sites showed poor growth performance. The findings suggest that Qi-nan clones are suitable for planting in southern China. There were also abundant genetic variations in germplasm resources for the Qi-nan clones. The five selected clones could be suitable for extensive planting. Therefore, large-scale testing is necessary for determining genetic improvements in Qi-nan clones, which will be conducive to the precise localization of their promotion areas. Full article

Drought stress is one of the biggest hardships in wheat cultivation because of the strong negative relationship between water deficit and crop yields owing to a lower grain weight, a shorter grain-filling period, a slower grain-filling rate, and reduced grain quality. Genotype–environment interaction (GEN:ENV) generates hardships in selecting wheat genotypes and ideotypes due to biased genetic estimates. Diverse strategies have been proposed to respond to the urgent need for concurrent improvements in yield performance and stability. This study’s purpose was to appraise genetic variation and GEN:ENV effects on yield and yield components to discover drought-stress-tolerant genotypes and ideotypes. This study evaluated 20 genotypes in three consecutive seasons under non-stressful and drought-stress conditions in a total of six ENVs. The broad-sense heritability ranged from 0.54 to 0.82 based on expected mean squares and ranged from 0.60 to 0.90 based on plot mean, but in the other three ways, it was usually greater than 0.90. The high values of (${\mathsf{\sigma }}_{\mathrm{gen}:\mathrm{e}\mathrm{n}\mathrm{v}}^2$) revealed the effect that broad-sense heritability has on the expression of traits. G01, G03, G06, G07, G08, G10, G12, G13, G16, G17, and G18 were stable genotypes for grain yield (GY), according to additive main effects and a multiplicative interaction biplot for the six ENVs. Based on scores in the weighted average of absolute scores biplot (WAASB), G02, G04, G05, G08, G10, and G18 were selected as stable and high-performance for GY, and they were all selected as the best genotype groups using the WAASB-GY superiority index. From the results obtained from principal component analysis and hierarchical clustering and from the tolerance discrimination indices, G02, G04, G05, G18, and G19 are genotypes that produce a suitable yield under non-stressful and drought-stress conditions. In essence, combining approaches that take into consideration stability and high performance can contribute significantly to enhancing the reliability of recommendations for novel wheat genotypes. Full article

Brassica carinata is an important and native oilseed crop in Ethiopia. The seed oil from B.carinata attracts global attention for its various industrial applications, mainly due to its high erucic acid levels and its superior agronomic traits. Since the demand for high erucic acid from oilseed brassica has been increasing in the world market due to its wider applications in bio-industries, the breeding target of B. carinata has recently been focused on enhancing its erucic acid. Several high erucic acid B. carinata genotypes have been screened from the pre-breeding activities. Such genotypes, however, need to be tested for their stable performance, for their erucic acid level, and other desirable traits under different environments. The aim of this study was to identify high erucic acid B. carinata genotypes with stable performance in multiple desirable traits. Thirty-two B. carinata genotypes were grown in a randomized complete block design with three replications at three locations for two years. The genotypes were evaluated for nine desirable traits related to seed oil quality (erucic acid and oil content), seed yield, and other agronomic traits. The results showed that the proportion of genotype by environment interaction (GEI) was clearly observed in erucic acid, which led to a stability and mean performance analysis for selecting the most stable and best-performing genotypes for the desired traits. For such an analysis, we used the multi-trait stability index (MTSI) along with the weighted average of absolute score BLUPs (WAASB). As revealed from the MTSI, five genotypes (G13, G18, G10, G22 and G5) were identified as the most stable in erucic acid, oil content, seed yield, and other agronomic traits. The selected genotypes showed on average 45.7% erucic acid, 3185 kg ha⁻¹ seed yield and 45.1% oil content with 4.3%, 25.8% and 6.9% positive selection gain, respectively. The negative selection gain of phenological traits and the plant height of the selected genotypes revealed their early maturity and their lower probability of being affected by lodging. Our findings demonstrated MTSI can be used to select high erucic acid B. carinata with a set of desirable traits, which would facilitate breeding efforts in developing novel and high erucic acid B. carinata varieties. Our results also showed that MTSI is an effective tool for selecting genotypes across different environments due to its unique ability to select multiple traits simultaneously. Full article

Identifying a congenially targeted production environment and understanding the effects of genotype by environmental interactions on the adaption of chickpea genotypes is essential for achieving an optimal yield stability. Different models like additive main effect and multiplicative interactions (AMMI 1, AMM2), weighted average absolute scores of BLUPs (WAASB), and genotype plus genotype–environment (GGE) interactions were used to understand their suitability in the precise estimation of variance and their interaction. Our experiment used genotypes that represent the West Asia–North Africa (WANA) region. This trial involved two different sowing dates, two distinct seasons, and three different locations, resulting in a total of 12 environments. Genotype IG 5871(G1) showed a lower heat susceptibility index (HSI) across environments under study. The first four interactions principal component axis (IPCA) explain 93.2% of variations with significant genotype–environment interactions. Considering the AMMI stability value (ASV), the genotypes IG5862(G7), IG5861(G6), ILC239(G40), IG6002(G26), and ILC1932(G39), showing ASV scores of 1.66, 1.80, 2.20, 2.60, and 2.84, respectively, were ranked as the most stable and are comparable to the weighted average absolute scores of BLUPs (WAASB) ranking of genotypes. The which–won–where pattern of genotype plus genotype–environment (GGE) interactions suggested that the target environment consists of one mega environment. IG5866(G10), IG5865(G9), IG5884(G14), and IG5862(G7) displayed higher stability, as they were nearer to the origin. The genotypes that exhibited a superior performance in the tested environments can serve as ideal parental lines for heat-stress tolerance breeding programs. The weighted average absolute scores of BLUPs (WAASB) serve as an ideal tool to discern the variations and identify the stable genotype among all methods. Full article

Multiple abiotic stresses negatively impact wheat production all over the world. We need to increase productivity by 60% to provide food security to the world population of 9.6 billion by 2050; it is surely time to develop stress-tolerant genotypes with a thorough comprehension of the genetic basis and the plant’s capacity to tolerate these stresses and complex environmental reactions. To approach these goals, we used multivariate analysis techniques, the additive main effects and multiplicative interaction (AMMI) model for prediction, linear discriminant analysis (LDA) to enhance the reliability of the classification, multi-trait genotype-ideotype distance index (MGIDI) to detect the ideotype, and the weighted average of absolute scores (WAASB) index to recognize genotypes with stability that are highly productive. Six tolerance multi-indices were used to test twenty wheat genotypes grown under multiple abiotic stresses. The AMMI model showed varying differences with performance indices, which disagreed with the trait and genotype differences used. The G01, G12, G16, and G02 were selected as the appropriate and stable genotypes using the MGIDI with the six tolerance multi-indices. The biplot features the genotypes (G01, G03, G11, G16, G17, G18, and G20) that were most stable and had high tolerance across the environments. The pooled analyses (LDA, MGIDI, and WAASB) showed genotype G01 as the most stable candidate. The genotype (G01) is considered a novel genetic resource for improving productivity and stabilizing wheat programs under multiple abiotic stresses. Hence, these techniques, if used in an integrated manner, strongly support the plant breeders in multi-environment trials. Full article

Abiotic stress decreases crop production worldwide. In order to recommend suitable genotypes for cultivation under water deficit and heat stress conditions, an overall understanding of the genetic basis and plant responses to these stresses and their interactions with the environment is required. To achieve these goals, the multitrait genotype-ideotype distance index (MGIDI) was utilized to recognize abiotic-stress-tolerant wheat genotypes, and the weighted average of absolute scores (WAASB) index as well as the superiority index, which enables weighting between the mean performance and stability (WAASBY), were utilized to recognize high-yielding and stable genotypes. Twenty wheat genotypes were examined to determine the abiotic stress tolerance capacity of the investigated genotypes under nine test environments (three seasons × three treatments). Abiotic stress significantly decreased most morpho-physiological and all agronomic traits; however, some abiotic-stress-tolerant genotypes expressed a slight reduction in the measured traits as compared with the control group. G04, G12, G13, and G17 were identified as convenient and stable genotypes using the MGIDI index under all environments. Based on the scores of the genotype index (WAASB), G01, G05, G12, and G17 were selected as superior genotypes with considerable stability in terms of the grain yield (GY). G04, G06, G12, and G18 were classified as cluster (I), the productive and stable genotypes, using the WAASBY superiority index. The combined indices (MGIDI and WAASB) and (MGIDI and WAASBY) revealed genotypes G12 and G17 and genotypes G04 and G12, respectively, as the most stable candidates. Therefore, these are considered novel genetic resources for improving productivity and stabilizing GY in wheat programs under optimal conditions, water deficit, and heat stress. The genotype G12 was jointly expressed in all three indices. Stability measures using WAASB may help breeders with decision-making when selecting genotypes and conducting multi-environment trials. Hence, these methods, if jointly conducted, can serve as a powerful tool to assist breeders in multi-environment trials. Full article

Multi-environment trials (METs) are essential in plant breeding programs to evaluate crop productivity and adaptability in diverse environments. In this study, we demonstrated the practical use of METs to evaluate grain yield and yield-related traits using 276 Korean rice cultivars, divided into three maturity groups (81 early-, 90 medium-, and 105 medium–late-maturing cultivars) grown in three regions (Jeonju, Suwon, and Miryang) and two planting seasons (early and regular planting) for two years. Due to the narrow genetic variability of the commercial cultivars, which are cultivated in relatively similar environmental conditions, genotype-by-environment interaction (GEI) effects were not statistically significant. However, genotype and environment evaluation using GGE biplot analysis exhibited distinct patterns of mega-environment formation, winning genotypes, ranking genotypes, discriminating power, and representativeness according to the differences in planting seasons and regions. Moreover, the simultaneous selection of stable high-performance genotypes using a weighted average of absolute scores from the singular-value decomposition of the matrix of BLUPs (WAASB) and a multi-trait stability index (MTSI) revealed six recommended genotypes each for early-maturing (Manho, Namil, Unkwang, Odae 1ho, Sinunbong 1ho, and Jonong) and medium-maturing (Sobi, Cheongdam, Shinbaeg, Boramchal, Mimyeon, and Saemimyeon) cultivars, and four genotypes for medium–late-maturing cultivars (Hanmauem, Dami, Baegseolchal, and Hangangchalbyeo). The winning genotypes of each trait can be used as parents to develop regional specialty cultivars by fine-tuning favorable traits, and recommended genotypes can be utilized as elite climate-resilient parents that can aid breeders in improving yield potential and stability across the planting seasons and regions. Full article

Genotype-by-environment (GEI) analysis guides the recommendation of best-performing crop genotypes and production environments. The objective of this study was to determine the extent of GEI on seed yield in tepary bean for genotype recommendation and cultivation in drought-prone environments. Forty-five genetically diverse tepary bean genotypes were evaluated under non-stressed and drought-stressed conditions for two seasons using a 9 × 5 alpha lattice design with three replications in four testing environments. Data were collected on seed yield (SY) and days to physiological maturity (DTM) and computed using a combined analysis of variance, the additive main effect and multiplicative interaction (AMMI), the best linear unbiased predictors (BLUPs), the yield stability index (YSI), the weighted average of absolute scores (WAASB) index, the multi-trait stability index (MTSI), and a superiority measure. AMMI analysis revealed a significant (p < 0.001) GEI, accounting for 13.82% of the total variation. Genotype performance was variable across the test environments, allowing the selection of best-suited candidates for the target production environment. The environment accounted for a substantial yield variation of 52.62%. The first and second interaction principal component axes accounted for 94.8 and 4.7% of the total variation in the AMMI-2 model, respectively, of surmountable variation due to GEI. The AMMI 2 model family was sufficient to guide the selection of high-yielding and stable genotypes. Based on best linear unbiased predictors (BLUPs), yield stability index (YSI), superiority measure (Pi), and broad adaptation, the following tepary bean genotypes were identified as high-yielding and suited for drought-prone environments: G40138, G40148, G40140, G40135, and G40158. The selected tepary bean genotypes are recommended for cultivation and breeding in Malawi or other related agroecologies. Full article

Multi-environment field testing of chickpea accessions winter sown in Southern Spain showed that environmental effects on yield were more important than genotypic effects and GEI. The most detrimental factor on grain yield was ascochyta blight infection. We did not find a significant effect of low temperatures on yield in the environments studied, probably due to the mild winters in the area. On the contrary, we found detrimental effects of high temperatures at the reproductive stage, particularly with numbers of days with Tmax >30 °C. We found that genotypic effects were larger than the environmental on ascochyta infection as we included accessions previously selected for their levels of resistance or susceptibility. Biplots based on the WAASB/productivity ratio highlighted AS19, AS30, AS23, AS26, and AS18 accessions as the best for productivity and stability of yield, matching with those with a lower ascochyta blight infection. The MTSI index also identified these as the best accessions for the region. Full article

The faba bean (Vicia faba) is a temperate grain legume, that is regaining interest due to the high demand for food and feed uses and the environmental services provided. The parasitic weed broomrape (Orobanche crenata) appears as the major constraint to agricultural production in the Mediterranean Basin. The yield stability can be managed by adjusting agronomic practices and breeding for adaptation. In this study, we compared the performance of three susceptible faba bean accessions with that of eight lines previously selected for their broomrape resistance, in multi-environment field trials. Results confirmed that the grain yield in the region was negatively affected, mainly by broomrape infection, followed at a distance by ascochyta blight (Ascochyta fabae), whereas the grain yield was little affected by the low occurring levels of chocolate spot infection (Botrytis fabae). The yield was favored by rain at flowering and was reduced by low temperatures at pre-flowering and flowering, and by high temperatures at flowering and grain-filling. The combined ANOVA showed significant effects of the genotype, environment, and genotypex environment interaction. The weighted average of the absolute scores biplot (WAASB), a heat map with 21 scenarios based on the WAASB ratio and the multi-trait stability index (MTSI) were utilized to determine the mean performance and stability of the faba bean genotypes. Quijote, Navio6, Baraca and FaraonSC are proposed as ideal lines for cultivation in the region and to be further used in future breeding programs. Full article

Increasing the maize production capacity to ensure food security is still the primary goal of global maize planting. The purpose of this study was to evaluate genotypes with high yield and stability in summer maize hybrids grown in the Huanghuaihai region of China using additive main effects and multiplicative interaction (AMMI) analysis and best linear unbiased prediction (BLUP) technique. A total of 18 summer maize hybrids with one check hybrid were used for this study using a randomized complete block design (RCBD) with three replicates at 74 locations during two consecutive years (2018–2019). A three-way analysis of variance (ANOVA) and an AMMI analysis showed that genotype (G), environment (E), year (Y) and their interactions were highly significant (p < 0.001) except G × E × Y for all evaluated traits viz., grain yield (GY), ear length (EL), hundred seed weight (HSW) and E × Y for hundred seed weight. The first seven interaction principal components (IPCs) were highly significant and explained 81.74% of the genotype by environment interaction (GEI). By comparing different models, the best linear unbiased prediction (BLUP) was considered the best model for data analysis in this study. The combination of AMMI model and BLUP technology to use the WAASB (weighted average of absolute scores from the singular value decomposition of the matrix of BLUP for GEI effects generated by linear mixed model) index was considered promising for similar research in the future. Genotypes H321 and Y23 had high yield and good stability, and could be used as new potential genetic resources for improving and stabilizing grain yield in maize breeding practices in the Huanghuaihai region of China. Genotypes H9, H168, Q218, Y303 and L5 had narrow adaptability and only apply to specific areas. The check genotype Z958 had good adaptability in most environments due to its good stability, but it also needs the potential to increase grain yield. Significant positive correlations were also found between the tested agronomic traits. Full article

Drought, ultraviolet-B (UV-B), and nitrogen stress are significant constraints for sweetpotato productivity. Their impact on plant growth and development can be acute, resulting in low productivity. Identifying phenotypes that govern stress tolerance in sweetpotatoes is highly desirable to develop elite cultivars with better yield. Ten sweetpotato cultivars were grown under nonstress (100% replacement of evapotranspiration (ET)), drought-stress (50% replacement of ET), UV-B (10 kJ), and low-nitrogen (20% LN) conditions. Various shoot and root morphological, physiological, and gas-exchange traits were measured at the early stage of the crop growth to assess its performance and association with the storage root number. All three stress factors caused significant changes in the physiological and root- and shoot-related traits. Drought stress reduced most shoot developmental traits (29%) to maintain root growth. UV-B stress increased the accumulation of plant pigments and decreased the photosynthetic rate. Low-nitrogen treatment decreased shoot growth (11%) and increased the root traits (18%). The highly stable and productive cultivars under all four treatments were identified using multitrait stability index analysis and weighted average of absolute scores (WAASB) analyses. Further, based on the total stress response indices, ‘Evangeline’, ‘O’Henry’, and ‘Beauregard B-14’ were identified as vigorous under drought; ‘Evangeline’, ‘Orleans’, and ‘Covington’ under UV-B; and ‘Bonita’, ‘Orleans’, and ‘Beauregard B-14’ cultivars showed greater tolerance to low nitrogen. The cultivars ‘Vardaman’ and ‘NC05-198’ recorded a low tolerance index across stress treatments. This information could help determine which plant phenotypes are desirable under stress treatment for better productivity. The cultivars identified as tolerant, sensitive, and well-adapted within and across stress treatments can be used as source materials for abiotic stress tolerance breeding programs. Full article

In order to ensure an ongoing and long-term breeding progress of soybean, stable sources of major quality traits across multi-environments need to be identified. Here, a panel of 135 soybean genotypes was tested in three different Chinese environments, including Beijing, Anhui, and Hainan during the 2017 and 2018 growing seasons to identify stable genotypes for cultivation under varying environmental conditions. The weighted average of absolute scores biplot (WAASB) for the best linear unbiased predictions of the genotype-environment interaction and multi-trait stability index (MTSI) were utilized to determine the stability of the soybeans for seven seed composition traits viz; protein content, oil content, and five fatty acids (palmitic, stearic, oleic, linoleic, and linolenic acids). Based on the WAASB index, the following genotypes were identified as stable genotypes for some specific traits; ZDD12828 and ZDD12832 for protein content, WDD01583 and WDD03025 for oil content, ZDD23040 for palmitic acid, WDD00033 for stearic acid, ZDD23822 for oleic acid, ZDD11183 for linoleic acid, and ZDD08489 for linolenic acid. Furthermore, based on MTSI at a selection intensity of 10%, 14 soybean genotypes were selected for their average performance and stability. Overall, the MTSI was shown to be a powerful and simple tool for identifying superior genotypes in terms of both performance and stability, hence, identifying stable soybean genotypes for future breeding programs of quality traits. Full article