Genotype-ideotype Distance Index Research Articles

Evaluation of Polyethylene Glycol (PEG-6000) Induced Drought Stress Tolerant Mungbean Genotypes by using Correlation, Principal Component, Hierarchical Clustering and Multi-Trait Genotype-Ideotypes Distance Index Analysis

Determining a plant's ultimate population under water stress requires seedling establishment and germination. The current study was aimed at identifying mungbean genotypes that were tolerant to drought stress. The treatments were: Factor A: polyethylene glycol 6000 (PEG-6000) inducing different levels of water potential (i.e., 0.0 (distilled water as a control), -0.7, -1, -2, and -4 bar) and Factor B: Thirty-three mungbean genotypes, collected from various national and international organizations. Each genotype's seeds were planted in a petri dish (9 cm diameter) containing sand bed and were moistened with appropriate amounts of water potential and left to develop into seedlings of all genotypes for up to 10 days. The findings showed that when PEG-6000 concentration was raised, germination, shoot and root length, and the associated fresh and dry weights decreased significantly. Among these tested genotypes, BMX-08010-2, BMX-08009-7, BMX-01015, BARI Mung-8, BARI Mung-2, and BU Mung-2 were found to be tolerant against drought stress based on their % germination and germination indices, as well as their seedling traits. Principal component analysis, multi-trait genotype-ideotype distance index (MGIDI), two-dimensional heat map, and hierarchical clustering analysis also revealed the same genotypes to be stable and capable of withstanding water deficiency stress. In response to water stress, the genotypes BARI Mung-1, BARI Mung-3, BU Mung-4, and BMX-05001 showed poor germination indices along with relatively poor seedling characteristics. The results of the present research provide criteria for the selection of drought-tolerant mungbean genotypes in future breeding programs.

Multi-trait selection for mean performance and stability in purple-fleshed sweet potato

Few purple-fleshed sweet potato (PFSP) cultivars are available for Brazilian growers, urging for the development of new and adapted cultivars. PFSP breeding programs should include multiple traits during the selection process to increase the chances of developing an adequate genotype, specially yield-related and quality-related traits. The objective was to select promising PFSP genotypes based on yield and tuberous-roots-related traits exploring genotype x environment interaction (GEI). Four experiments were carried out, in which 23 pre-selected PFSP genotypes were evaluated based on yield and quality traits, after screening among 2500 experimental genotypes. The first experiment adopted an augmented block design, with ‘Luiza’ interspersed as a control. From this first experiment, the 19 experimental genotypes with the best performance were selected for the following three experiments, which were conducted in a randomized block experimental design, with three replications each, including ‘Luiza’ as control. The best genotypes were selected in the first experiment using the multi-trait genotype-ideotype distance index (MGIDI). For the following experiments, the performance of the genotypes was assessed using deviance analysis, genotypic stability through weighted average of absolute scores (WAASB) index, and the multi-trait stability index (MTSI). In the first experiment, three factors were retained, being associated to commercial production of tuberous roots (‘K-104′, ‘K-25′ and ‘U1–29′), total production of tuberous roots (‘K-110′, ‘C-42′, ‘F-16′, and ‘U1–29′), and quality of tuberous roots (‘F-22′), respectively. Desired gains were observed for all traits. For the experiments II, III, and IV five factors were retained, being four related to quality of tuberous roots and one to yield components. The GEI was significant for yield-related traits and desired gains were observed for most traits. Due to high commercial tuberous root yield and low WAASB values, the genotypes ‘U1–29′, ‘K-98′, ‘F-22′, ‘K-57′, ‘C-36′, ‘U1–15′, ‘K-25′, and ‘U2–12′ were highly productive and stable. The genotypes selected by the MTSI index were ‘U1–15′, ‘U2–10′, ‘U1–29′, ‘K-98′, and ‘K-78′. The multi-trait selection enabled the identification of promising genotypes highlighting their strengths and weaknesses.

Biochemical and morpho-physiological insights revealed low moisture stress adaptation mechanisms in cotton (Gossypium hirsutum L.)

Cotton (Gossypium hirsutum L.) is a multipurpose crop. Abiotic stresses, especially extreme heat and drought, limit crop growth and thus reduce cotton yield by about 50%. In this study, 30 cotton genotypes were tested against low moisture stress in a pot experiment in triplicates along with control under wire house conditions. At the 3–4 leaf stage, different morpho-physiological and biochemical parameters were measured in order to select the low moisture stress-tolerant genotypes. For the selection of the best performing genotypes, Multi-Trait Genotype-Ideotype Distance Index (MGIDI) was used for the ranking of genotypes on the basis of multiple indices. For biochemical traits, 09 (TPC, TF, TSP, MDA, SOD, POD, CAT, APX, and Proline) out of 24 showed significant genotypic effects and were used for MGIDI. Eight genotypes (N-812 N-1296 N-696 N-377 N-121–896 N-T86, and N-3496) were observed to be best performing than others at 25% selection pressure (SI = 25%). For morpho-physiological traits, 14 out of 15 showed significant genotypic effects and used for MGIDI. Ten genotypes (N-1237 N-812 N-1296 N-696 N-9078 N-377 N-512 N-121 N-375, and N-896) were observed to be best performing at 35% selection pressure (SI = 35%). Six genotypes, i.e. N-812–1296 N-696 N-377 N-121, and N-896 were found common in both MGIDI analysis. In conclusion, three genotypes, i.e. N-696, N-896, and N-T86 proved to be most resilient to low moisture stress. Develop protocols, identified genotypes and markers that can be used for development of climate-smart cotton genotypes.

Genetic variability and diversity analysis for some agronomic traits of a sweet potato (Ipomoea batatas L.) collection: Insights for breeding superior genotypes

A study was conducted during the 2017 cropping season to assess the genetic variability of selected agronomic traits in sweet potato. A total of 355 sweet potato genotypes (351 from different countries of the world and four check varieties) were evaluated at Tuber Crops Research Sub Centre, Bangladesh Agricultural Research Institution, Bogura, Bangladesh. The experiment was conducted using an augmented randomized complete block design. Findings revealed positive correlations among five agronomic traits, namely the weight of marketable storage root per plant (MRW), weight of storage root per plant (RW), fresh weight of foliage per plant (FW), number of marketable storage root per plant (MRN) and number of storage root per plant (RN) suggesting their suitability for phenotypic selection. There was a positive skewness in most studied traits (FW, MRW, MRW and RW), indicating the presence of a few genotypes with exceptionally high values for those traits. By employing principal component analysis, the most influential traits in sweet potato genotypes were identified for first two components (Dim) showing significant contributions to Dim-1 and Dim-2 collectively accounting for 84.7 % of the total variance. Through cluster analysis, two main clusters (Cluster I and Cluster II) were identified among the studied genotypes, each characterized by distinct trait patterns. Cluster I demonstrated superior performance in all traits, while Cluster II exhibited lower values for all traits. Further sub-clustering within Cluster II (sub-clusters IIA and IIB) revealed additional variations of the collection. The Euclidean distance for inter-cluster (ranging from 7.94 to 11.39) and intra-cluster (ranging from 3.17 to 10.38) were determined utilizing the complete distance method. In restricted maximum likelihood (REML) model, all the traits were significantly influenced by genetic effects, with broad-sense heritability ranging from 32 % to 70 %. The REML displayed high selection accuracy, with values exceeding 91 % for studied traits. The Multi-Trait Genotype-Ideotype Distance Index (MGIDI) identified 18 genotypes, with Moz1.15 emerging as the best-performing genotype under a 5 % selection pressure. Among the selected genotypes, trait uniqueness was highest for FW (54 %), followed by RN (50 %), MRN (18 %), MRW (14 %), and RW (5 %). The selection gain for these top-ranked genotypes varied between 23.2 % and 69.2 %. Findings established the existence of useful genetic variability for selected agronomic traits of sweet potato that could be exploited for breeding, genetics study and conservation.

Heat stress tolerance in wheat seedling: Clustering genotypes and identifying key traits using multivariate analysis

Elevated atmospheric heat is considered as one of the bottlenecks for global wheat production. Screening potential wheat genotypes against heat stress and selecting some suitable indicators to assist in understanding thermotolerance could be crucial for sustaining wheat cultivation. Accordingly, 80 diverse bread wheat genotypes were evaluated in controlled lab condition by imposing a week-long heat stress (35/25 °C D/N) at the seedling stage. The response of heat stress was evaluated using multivariate analysis techniques on 20 morpho-physiological traits. Results showed significant variations in the studied traits due to the imposition of heat stress. Eleven seedling traits that contributed significantly to the genotypic variability were identified using principal component analysis (PCA). A substantial correlation between most of the selected seedling attributes was observed. Hierarchical cluster analysis identified three distinct clusters among the tested wheat genotypes. Cluster 1, consisting of 33 genotypes, exhibited the highest tolerance to heat stress, followed by Cluster 2 (18 genotypes) with moderate tolerance and Cluster 3 (29 genotypes) showing susceptibility. Linear discriminant analysis (LDA) approved that nearly 93 % of the wheat genotypes were appropriately ascribed to each cluster. The squared distance analysis confirmed the distinct nature of the clusters. Using multi-trait genotype-ideotype distance index (MGIDI), all 12 identified tolerant genotypes (BG-30, BD-468, BG-24, BD-9908, BG-32, BD-476, BD-594, BD-553, BD-488, BG-33, BD-495, and AS-10627) originated from Cluster 1. Selection gain in MGIDI analysis, broad-sense heritability, and multiple linear regression analysis together identified shoot and root dry and fresh weights, chlorophyll contents (a and total), shoot tissue water content, root-shoot dry weight ratio, and efficiency of photosystem II (PS II) as the most vital discriminatory factors explaining heat stress tolerance of 80 wheat genotypes. The identified genotypes with superior thermotolerance would offer resourceful genetic tools for breeders to improve wheat yield in warmer regions. The traits found to have greater contribution in explaining heat stress tolerance will be equally important in prioritizing future research endeavors.

Characterization of early maturing elite genotypes based on MTSI and MGIDI indexes: an illustration in upland cotton (Gossypium hirsutum L.)

BackgroundGlobally, the cultivation of cotton is constrained by its tendency for extended periods of growth. Early maturity plays a potential role in rainfed-based multiple cropping system especially in the current era of climate change. In the current study, a set of 20 diverse Gossypium hirsutum genotypes were evaluated in two crop seasons with three planting densities and assessed for 11 morphological traits related to early maturity. The study aimed to identify genotype(s) that mature rapidly and accomplish well under diverse environmental conditions based on the two robust multivariate techniques called multi-trait stability index (MTSI) and multi-trait genotype-ideotype distance index (MGIDI).ResultsMTSI analysis revealed that out of the 20 genotypes, three genotypes, viz., NNDC-30, A-2, and S-32 accomplished well in terms of early maturity traits in two seasons. Furthermore, three genotypes were selected using MGIDI method for each planting densities with a selection intensity of 15%. The strengths and weaknesses of the genotypes selected based on MGIDI method highlighted that the breeders could focus on developing early-maturing genotypes with specific traits such as days to first flower and boll opening. The selected genotypes exhibited positive genetic gains for traits related to earliness and a successful harvest during the first and second pickings. However, there were negative gains for traits related to flowering and boll opening.ConclusionThe study identified three genotypes exhibiting early maturity and accomplished well under different planting densities. The multivariate methods (MTSI and MGIDI) serve as novel approaches for selecting desired genotypes in plant breeding programs, especially across various growing environments. These methods offer exclusive benefits and can easily construe and minimize multicollinearity issues.

Unraveling the impact of water deficit stress on nutritional quality and defense response of tomato genotypes.

Water deficit stress triggers various physiological and biochemical changes in plants, substantially affecting both overall plant defense response and thus nutritional quality of tomatoes. The aim of this study was to assess the antioxidant defense response and nutritional quality of different tomato genotypes under water deficit stress. In this study, six tomato genotypes were used and subjected to water deficit stress by withholding water for eight days under glass house conditions. Various physiological parameters from leaves and biochemical parameters from tomato fruits were measured to check the effect of antioxidant defense response and nutritional value. Multi-trait genotype-ideotype distance index (MGIDI) was used for the selection of genotypes with improved defense response and nutritional value under water deficit stress condition. Results indicated that all physiological parameters declined under stress conditions compared to the control. Notably, NBH-362 demonstrated resilience to water deficit stress, improving both defense response and nutritional quality which is evident by an increase in proline (16.91%), reducing sugars (20.15%), total flavonoids (10.43%), superoxide dismutase (24.65%), peroxidase (14.7%), and total antioxidant capacity (29.9%), along with a decrease in total oxidant status (4.38%) under stress condition. Overall, the findings suggest that exposure to water deficit stress has the potential to enhance the nutritional quality of tomatoes. However, the degree of this enhancement is contingent upon the distinct genetic characteristics of various tomato genotypes. Furthermore, the promising genotype (NBH-362) identified in this study holds potential for future utilization in breeding programs.

Multi-trait index: selection and recommendation of superior black bean genotypes as new improved varieties

Common bean provides diet rich in vitamins, fiber, minerals, and protein, which could contribute into food security of needy populations in many countries. Developing genotypes that associate favorable agronomic and grain quality traits in the common bean crop could increase the chances of adopting new cultivars black bean. In this context, the present study aimed at selection of superior black bean lines using multi-variate indexes, Smith-Hazel-index, and genotype by yield*trait biplot analysis. These trials were conducted in Campos dos Goytacazes - RJ, in 2020 and 2021. The experimental design used was randomized blocks, with 28 treatments and three replications. The experimental unit consisted of four rows 4.0 m long, spaced at 0.50 m apart, with a sowing density of 15 seeds per meter. The two central rows were used for the evaluations. The selection of superior genotypes was conducted using the multiple trait stability index (MTSI), multi-trait genotype-ideotype distance index (MGIDI), multi-trait index based on factor analysis and genotype-ideotype distance (FAI-BLUP), Smith-Hazel index, and Genotype by Yield*Trait Biplot (GYT). The multivariate indexes efficiently selected the best black bean genotypes, presenting desirable selection gains for most traits. The use of multivariate indexes and GYT enable the selection of early genotypes with higher grain yields. These lines G9, G13, G17, G23, and G27 were selected based on their performance for multiple traits closest to the ideotype and could be recommended as new varieties.

High-Throughput Phenotyping for the Evaluation of Agronomic Potential and Root Quality in Tropical Carrot Using RGB Sensors

The objective of this study was to verify the genetic dissimilarity and validate image phenotyping using RGB (red, green, and blue) sensors in tropical carrot germplasms. The experiment was conducted in the city of Carandaí-MG, Brazil, using 57 tropical carrot entries from Seminis and three commercial entries. The entries were evaluated agronomically and two flights with Remotely Piloted Aircraft (RPA) were conducted. Clustering was performed to validate the existence of genetic variability among the entries using an artificial neural network to produce a Kohonen’s self-organizing map. The genotype–ideotype distance index was used to verify the best entries. Genetic variability among the tropical carrot entries was evidenced by the formation of six groups. The Brightness Index (BI), Primary Colors Hue Index (HI), Overall Hue Index (HUE), Normalized Green Red Difference Index (NGRDI), Soil Color Index (SCI), and Visible Atmospherically Resistant Index (VARI), as well as the calculated areas of marketable, unmarketable, and total roots, were correlated with agronomic characters, including leaf blight severity and root yield. This indicates that tropical carrot materials can be indirectly evaluated via remote sensing. Ten entries were selected using the genotype–ideotype distance (2, 15, 16, 22, 34, 37, 39, 51, 52, and 53), confirming the superiority of the entries.

Identification of new stable resistant sources and assessing agro-morphological performance of sponge gourd germplasm against Tomato Leaf curl New Delhi Virus incidence.

Tomato leaf curl New Delhi virus (TolCNDV) causes yellow mosaic disease, which poses a significant biotic constraint for sponge gourd cultivation, potentially resulting in crop loss of up to 100%. In the present investigation, 50 diverse genotypes were screened for 3 years under natural epiphytotic conditions. A subset of 20 genotypes was further evaluated across four different environments. The combined analysis of variance revealed a significant genotype × environment interaction. Eight genotypes consistently exhibited high and stable resistance in the preliminary screening and multi-environment testing. Furthermore, genotype plus genotype × environment interaction biplot analysis identified DSG-29 (G-3), DSG-7 (G-2), DSG-6 (G-1), and DSGVRL-18 (G-6) as the desirable genotypes, which have stable resistance and better yield potential even under diseased conditions. The genotype by yield × trait biplot analysis and multi-trait genotype-ideotype distance index analysis further validated the potential of these genotypes for combining higher yield and other desirable traits with higher resistance levels. Additionally, resistant genotypes exhibited higher activities of defense-related enzymes as compared to susceptible genotypes. Thus, genotypes identified in our study will serve as a valuable genetic resource for carrying out future resistance breeding programs in sponge gourd against ToLCNDV.

Multivariate analysis of yield and quality traits in sweet potato genotypes (Ipomoea batatas L.)

Improving sweet potato traits and genotype selection based on specific traits of interest is crucial to motivate farmers and rural households to enhance their livelihoods by increasing income and improving nutritional intake. This research offers a thorough analysis of genotype selection guidelines considering multiple traits of sweet potatoes, including vine length (VL), average root length (ARL), average root diameter (ARD), marketable storage root number (MRN), marketable storage root yield (MRY), non-marketable root number (NMRN), non-marketable root weight (NMRW), dry weight of root (DW), beta-carotene content (BC), vitamin C content (VC), starch content (ST), total sugar content (TS), total soluble solid (TSS), and titratable acidity (ACD). The findings showed that the genotype Moz1.15 achieved the highest MRY at 46.46 t/ha, H5.ej.10 displayed the top BC level at 48.94 mg/100 g, and Moz1.9 had the highest VC (23.89 mg/100 g). Furthermore, there was a significant positive correlation between VL and DW, TSS, ST, TS, and VC. Additionally, ARL, ARD, and MRN showed significant positive correlations with MRY. The principal component analysis (PCA) biplot further confirmed how traits were connected with each other. There were four separate clusters of genotypes found, each having its specific significant trait representation. The distance between these clusters ranged from 21.79 to 54.13, while within each cluster, the distances varied from 0 to 17.45. The factor analysis using the multi-trait genotype-ideotype distance index (MGIDI) showed that sweet potato traits played a substantial role in three distinct factors during both growing seasons (2020-21 and 2021-22). This allowed for the selection of genotypes capable of achieving favorable genetic gains ranging from 1.86% to 75.4%, alongside a broad-sense heritability (h2b) spanning from 64.9% to 99.8%. Through the application of the MGIDI index, a number of potential genotypes were identified, among which BARI Mistialu-12 and H9.7.12 stood out as consistently chosen across both years. These promising genotypes exhibited high performance while displaying their strengths and weaknesses in terms of their contributions to the identified factors. This thorough research offers valuable insights into the complex relationship between different traits in sweet potatoes and how genotype selection based on a multi-trait index can significantly assist in shaping upcoming breeding and cultivation strategies.

Estimation of Genetic Parameters and Identification of Leaf Blast-Resistant Rice RILs Using Cluster Analysis and MGIDI

Rice blast disease, caused by the fungus Magnaporthe oryzae, poses a significant threat to rice cultivation. One effective way to deal with this disease is to identify and introduce resistant varieties using different breeding methods. This study utilized a population of 153 recombinant inbred lines (RILs) derived from the crossing of the Shahpasand (SH) and IR28 varieties, characterized by susceptibility and resistance to leaf blast, respectively. In combination with 12 control varieties, these genotypes were subjected to an extensive evaluation of disease severity (5 stages), the area under the disease progress curve (AUDPC), type, and the infection rate in 2021 and 2022. Analysis of variance revealed significant genetic variation, highlighting the potential of the RIL population for identifying and selecting resistant lines. Employing cluster analysis and the multi-trait genotype-ideotype distance index (MGIDI), 17 lines were identified as the most resistant over a two-year evaluation period. The average AUDPC for these resistant lines was estimated at 2.435 ± 0.114, and lines 17 and 111 had the lowest AUDPC (1.526 and 1.630, respectively) and showed the least infection in two years. Conversely, lines 42 and 43 showed the highest AUDPC values (255.312 and 248.209) along with heightened sensitivity. The use of MGIDI yielded a substantial selection differential (SD) of −59.12% for traits related to leaf blast disease resistance, demonstrating the effectiveness of this method. Furthermore, new recombinant populations are expected to be developed in future plant breeding projects by crossing the most susceptible and resistant lines, which will be new sources of resistance to this disease.

Identification of Wheat Ideotype under Multiple Abiotic Stresses and Complex Environmental Interplays by Multivariate Analysis Techniques.

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.

Multivariate analysis and genetic dissection of staygreen and stem reserve mobilisation under combined drought and heat stress in wheat (Triticum aestivum L.).

Introduction: Abiotic stresses significantly reduce crop yield by adversely affecting many physio-biochemical processes. Several physiological traits have been targeted and improved for yield enhancement in limiting environmental conditions. Amongst them, staygreen and stem reserve mobilisation are two important mutually exclusive traits contributing to grain filling under drought and heat stress in wheat. Henceforth, the present study was carried out to identify the QTLs governing these traits and to identify the superiors' lines through multi-trait genotype-ideotype distance index (MGIDI) Methods: A mapping population consisting of 166 recombinant inbred lines (RILs) developed from a cross between HD3086 and HI1500 was utilized in this study. The experiment was laid down in alpha lattice design in four environmental conditions viz. Control, drought, heat and combined stress (heat and drought). Genotyping of parents and RILs was carried out with 35K Axiom® array (Wheat breeder array). Results and Discussion: Medium to high heritability with a moderate to high correlation between traits was observed. Principal component analysis (PCA) was performed to derive latent variables in the original set of traits and the relationship of these traits with latent variables.From this study, 14 QTLs were identified, out of which 11, 2, and 1 for soil plant analysis development (SPAD) value, leaf senescence rate (LSR), and stem reserve mobilisation efficiency (SRE) respectively. Quantitative trait loci (QTLs) for SPAD value harbored various genes like Dirigent protein 6-like, Protein FATTY ACID EXPORT 3, glucan synthase-3 and Ubiquitin carboxyl-terminal hydrolase, whereas QTLs for LSR were found to contain various genes like aspartyl protease family protein, potassium transporter, inositol-tetrakisphosphate 1-kinase, and DNA polymerase epsilon subunit D-like. Furthermore, the chromosomal region for SRE was found to be associated with serine-threonine protein kinase. Serine-threonine protein kinases are involved in many signaling networks such as ABA mediated ROS signaling and acclimation to environmental stimuli. After the validation of QTLs in multilocation trials, these QTLs can be used for marker-assisted selection (MAS) in breeding programs.

Genetic gains in tropical maize hybrids across moisture regimes with multi-trait-based index selection.

Unpredictable weather vagaries in the Asian tropics often increase the risk of a series of abiotic stresses in maize-growing areas, hindering the efforts to reach the projected demands. Breeding climate-resilient maize hybrids with a cross-tolerance to drought and waterlogging is necessary yet challenging because of the presence of genotype-by-environment interaction (GEI) and the lack of an efficient multi-trait-based selection technique. The present study aimed at estimating the variance components, genetic parameters, inter-trait relations, and expected selection gains (SGs) across the soil moisture regimes through genotype selection obtained based on the novel multi-trait genotype-ideotype distance index (MGIDI) for a set of 75 tropical pre-released maize hybrids. Twelve traits including grain yield and other secondary characteristics for experimental maize hybrids were studied at two locations. Positive and negative SGs were estimated across moisture regimes, including drought, waterlogging, and optimal moisture conditions. Hybrid, moisture condition, and hybrid-by-moisture condition interaction effects were significant (p ≤ 0.001) for most of the traits studied. Eleven genotypes were selected in each moisture condition through MGIDI by assuming 15% selection intensity where two hybrids, viz., ZH161289 and ZH161303, were found to be common across all the moisture regimes, indicating their moisture stress resilience, a unique potential for broader adaptation in rainfed stress-vulnerable ecologies. The selected hybrids showed desired genetic gains such as positive gains for grain yield (almost 11% in optimal and drought; 22% in waterlogging) and negative gains in flowering traits. The view on strengths and weaknesses as depicted by the MGIDI assists the breeders to develop maize hybrids with desired traits, such as grain yield and other yield contributors under specific stress conditions. The MGIDI would be a robust and easy-to-handle multi-trait selection process under various test environments with minimal multicollinearity issues. It was found to be a powerful tool in developing better selection strategies and optimizing the breeding scheme, thus contributing to the development of climate-resilient maize hybrids.

Selection of elite purple waxy corn hybrids by MGIDI multivariate selection method in Vietnam

This study aims to select the elite purple waxy corn hybrids by Vietnam by multivariable selection method by multi-trait genotype-ideotype distance index (MGIDI) based on growth, yield, and quality traits for purple waxy corn varieties commercialisation in the North of Vietnam. The field experiment was arranged in a randomised complete block design with 3 replications and evaluated 25 crosses with two check varieties in the Spring and Winter season of 2021 in Hanoi. The results of the selection of purple waxy corn hybrids by MGIDI in the Spring and Winter 2021 season identified the two most promising hybrid combination having the MGIDI index with a commercial potential as THL01 (D161 x FP1, named VNUA261, MGIDI=1.449 in the Spring season and 1.869 in Winter season), and THL02 (Q2151 x FP1, named VNUA191, MGIDI=1.218 in Spring season and 0.404 in Winter season). The fresh corn harvest time of VNUA261 and VNUA191 ranged from 70-75 days and 66-73 days, respectively. Fresh corn yield of VNUA261 and VNUA191 reached 12.51-13.85 tons/ha and 12.24-13.56 tons/ha, respectively. Corn has good eating quality, thin pericarp (≤60 μm), and high anthocyanin content, in which VNUA261 reached 112.93-124.07 mg/100 g dry seed, VNUA191 reached 100.33-119.57 mg/100 g dry seed.

Multi-Trait Selection and Stability in Norway Spruce (Picea abies) Provenance Trials in Romania

Provenance trials replicated in multiple environments allow the selection of populations with high and stable performances. In this study, two methods have been applied to select stable Norway spruce provenances with high performances in three provenance trials established in Romania in 1972, where 81 provenances have been tested. Four traits were assessed: total and pruned height, diameter at breast height and survival rate. Two multi-trait indices have been used: multi-trait genotype-ideotype distance index (MGIDI) for each provenance trial and multi-trait stability index (MTSI) across provenance trials. The selection differential was between 0.2 and 17.8% better than each site means. Several Norway spruce provenances showed stability and high performances, as confirmed by both selection indices. Our results provide valuable information for the genetic improvement program and seed transfer guidelines based on assisted migration in this ecologically and economically important forest tree species.

Detection of High-Performance Wheat Genotypes and Genetic Stability to Determine Complex Interplay between Genotypes and Environments

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.

Biofortificação do grão de trigo para aminoácidos essenciais

Abstract The objective of this work was to select wheat genotypes aiming to increase the essential amino acids in their grains. The study was carried out in the 2019 crop year, in a randomized complete block design, organized in a 5x5 factorial arrangement – five environments in the state of Rio Grande do Sul, Brazil (Cachoeira do Sul, Cruz Alta, Santo Augusto, São Gabriel, and Vacaria), and five wheat genotypes ('BRS Parrudo', 'Marfim', 'Quartzo', 'TBIO Mestre', and 'TBIO Sinuelo') –, with two replicates. Polar metabolites were extracted from the flour of the ground wheat grains, derivatized, and evaluated by gas chromatography-mass spectrometry. Both variance components and genetic parameters were estimated for the metabolites. To select the genotypes for the traits of interest, the multi-trait index based on factor analysis and ideotype design, the multi-trait genotype-ideotype distance index, and the multi-trait stability index were applied. The wheat genotypes express a high genetic variability and selection possibility for gentiobiose, butyric acid, galactopyranosyl, phenylalanine, tryptophan, leucine, and isoleucine. The 'Marfim' genotype remains stable for essential amino acid levels in the studied environments. The 'Quartzo' genotype stands out in the expression of leucine, isoleucine, phenylalanine, and tryptophan in its grains.

Harnessing on Genetic Variability and Diversity of Rice (Oryza sativa L.) Genotypes Based on Quantitative and Qualitative Traits for Desirable Crossing Materials.

Yield is a complex parameter of rice due to its polygonal nature, sometimes making it difficult to coat the selection process in the breeding program. In the current study, 34 elite rice genotypes were assessed to evaluate 3 locations for the selection of desirable rice cultivars suitable for multiple environments based on genetic diversity. In variance analysis, all genotypes have revealed significant variations (p ≤ 0.001) for all studied characters, signifying a broader sense of genetic variability for selection purposes. The higher phenotypic coefficient of variation (PCV) and genotypic coefficient of variation (GCV) were found for yield-associated characteristics such as the number of grains panicle-1 (GP), panicles hill-1 (PPH), and tillers hill-1 (TILL). All of the characters had higher heritability (greater than 60%) and higher genetic advance (greater than 20%), which pointed out non-additive gene action and suggested that selection would be effective. The most significant traits causing the genotype variants were identified via principal component analysis. In the findings of the cluster analysis, 34 elite lines were separated into 3 categories of clusters, with cluster II being chosen as the best one. The relationship matrix between each elite cultivar and traits was also determined utilizing a heatmap. Based on multi-trait genotype-ideotype distance index (MGIDI), genotypes Gen2, Gen4, Gen14, Gen22, and Gen30 in Satkhira; Gen2, Gen6, Gen7, Gen15, and Gen30 in Kushtia; and Gen10, Gen12, Gen26, Gen30, and Gen34 in Barishal were found to be the most promising genotypes. Upon validation, these genotypes can be suggested for commercial release or used as potential breeding material in crossing programs for the development of cultivars suitable for multiple environments under the future changing climate.