Progeny Means Research Articles

Genomic predictions of genetic variances and correlations among traits for breeding crosses in soybean

Parental selection is perhaps the most critical decision a breeder makes, establishing the foundation of the entire program for years to come. Cross selection based on predicted mean and genetic variance can be further expanded to multiple-trait improvement by predicting the genetic correlation (rG\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$${r}_{G}$$\\end{document}) between pairs of traits. Our objective was to empirically assess the ability to predict the family mean, genetic variance, superior progeny mean and genetic correlation through genomic prediction in a soybean population. Data made available through the Soybean Nested Association Mapping project included phenotypic data on seven traits (days to maturity, lodging, oil, plant height, protein, seed size, and seed yield) for 39 families. Training population composition followed a leave-one-family-out cross-validation scheme, with the validation family genetic parameters predicted using the remaining families as the training set. The predictive abilities for family mean and superior progeny mean were significant for all traits while predictive ability of genetic variance was significant for four traits. We were able to validate significant predictive abilities of rG\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$${r}_{G}$$\\end{document} for 18 out of 21 (86%) pairwise trait combinations (P < 0.05). The findings from this study support the use of genome-wide marker effects for predicting rG\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$${r}_{G}$$\\end{document} in soybean biparental crosses. If successfully implemented in breeding programs, this methodology could help to increase the rate of genetic gain for multiple correlated traits.

Predicting superior crosses in winter wheat using genomics: A retrospective study to assess accuracy

AbstractIn plant breeding, selecting cross‐combinations that are more likely to result in superior lines for cultivar development is critical. This step, however, is subjective with decisions being based on available genomic and phenotypic data for prospective parents. Genomic prediction (GP) provides new opportunities to accelerate genetic gain for a target trait by identifying superior crosses through simulation of progeny performance. In this context, this study deployed GP using the phenotype and genotype of potential parents to predict the progeny genetic variance (VG) and means of overall, inferior 10%, and superior 10% (μ, μip, and μsp, respectively). This retrospective experimental design investigated whether the crosses that produced superior soft red winter wheat breeding lines would have been made if progeny simulations had guided crossing decisions of breeding programs. Here, data from historical wheat breeding lines were used to train GP models and predict VG and means for yield, test weight, heading date, and plant height for all combinations of 217 parents. Predicted and observed data for 670 lines derived from biparental crosses were compared to assess the accuracy of progeny simulations, and low‐to‐moderate prediction accuracy was observed for the four traits (0.25–0.52). Of the pedigrees that produced lines that were selected and advanced into later stage nurseries, 76% were predicted to give rise to progeny with above‐average yield. The moderate correlation found between predicted progeny means and observed line per se performance justifies using cross‐combination prediction as a tool to reduce crossing number and focus on segregating populations that harbor future cultivars.

Simultaneous measurements of radon, thoron and thoron progeny and induced cancer risk assessment in Djeno, Pointe-Noire, Republic of Congo.

In this study, the activity concentrations of radon (222Rn), thoron (220Rn) and thoron progeny were measured simultaneously in Djeno (Pointe-Noire, Republic of Congo) using RADUET detectors to evaluate the air quality and the radiological risks due to the inhalation of these radionuclides. Activity concentrations of radon progeny were calculated from those of radon. Indoor radon, thoron and progenies followed a lognormal distribution ranging between 20 and 40, 6 and 62, 8 and 17.6 and 0.4 and 19.6Bqm-3 for radon, thoron, radon progeny and thoron progeny, respectively. Mean values for radon were lower than the worldwide values estimated by the United Nation Scientific Committee on the Effects of Atomic Radiation (UNSCEAR), which are 40Bqm-3 (arithmetic mean) and 45Bqm-3 (geometric mean). Radon concentrations in the dwellings under study were below the World Health Organization and the International Commission on Radiological Protection recommended reference levels, which are, respectively, 100 and 300Bqm-3. The mean concentration of thoron was twice the world average value of 10Bqm-3 estimated by UNSCEAR. Thoron progeny mean concentration was sharply greater than the typical value (0.3Bqm-3) for indoor atmosphere provided by UNSCEAR. Annual effective dose ranges were 0.40-0.87mSv (arithmetic mean, 0.57±0.11mSv) for radon and 0.10-4.14mSv (arithmetic mean, 0.55±0.77mSv) for thoron. The mean value for radon was lower than the value (1.15mSv) estimated by UNSCEAR, while the mean value for thoron was five times higher than the UNSCEAR value (0.10mSv). The study showed that the use of the typical equilibrium factor value given by UNSCEAR to compute effective dose led to an error above 80%. Finally, the results of this study showed that the excess relative risk of radon-induced cancer was low, below 2% for the population under 55y. The results presented in the present study prove that the population of Djeno is exposed to a relatively low potential risk of radon- and thoron-induced cancer.

Breeding Value of Quality Protein Maize Inbreds

The cultivar with high and positive breeding value can be used as a good parent for breeding of traits in hybridization programs because they can better transfer the desirable characteristics to the progeny in each case. To obtain the breeding value present investigation was carried out in maize with 33 inbreds of maize and seven inbreds of QPM lines to assess the breeding value of maize progenies for the better selection. The progeny values ranged from 62.04 (UMI 48 x CO 1) to 126.26 (CML 145 x CO 1). The breeding value ranged from 0.17 (UMI 48 x CO 1) to 0.39 (CML 145 x CO 1). CML 145 x CO 1 had high breeding value (0.39) with high progeny mean. UMI 48 x CO 1 had low breeding value (-0.17) with low progeny mean (90.80). The parent CML 145 was the superior most both for perse mean (P38=126.26) as well as for its hybrid progeny mean (C2= 168).

Comparison of genomic-enabled cross selection criteria for the improvement of inbred line breeding populations.

A crucial step in inbred plant breeding is the choice of mating design to derive high-performing inbred varieties while also maintaining a competitive breeding population to secure sufficient genetic gain in future generations. In practice, the mating design usually relies on crosses involving the best parental inbred lines to ensure high mean progeny performance. This excludes crosses involving lower performing but more complementary parents in terms of favorable alleles. We predicted the ability of crosses to produce putative outstanding progenies (high mean and high variance progeny distribution) using genomic prediction models. This study compared the benefits and drawbacks of seven genomic cross selection criteria (CSC) in terms of genetic gain for one trait and genetic diversity in the next generation. Six CSC were already published and we propose an improved CSC that can estimate the proportion of progeny above a threshold defined for the whole mating plan. We simulated mating designs optimized using different CSC. The 835 elite parents came from a real breeding program and were evaluated between 2000 and 2016. We applied constraints on parental contributions and genetic similarities between selected parents according to usual breeder practices. Our results showed that CSC based on progeny variance estimation increased the genetic value of superior progenies by up to 5% in the next generation compared to CSC based on the progeny mean estimation (i.e. parental genetic values) alone. It also increased the genetic gain (up to 4%) and/or maintained more genetic diversity at QTLs (up to 4% more genic variance when the marker effects were perfectly estimated).

Branching random walk with infinite progeny mean: A tale of two tails

We study the extremes of branching random walks under the assumption that the underlying Galton–Watson tree has infinite progeny mean. It is assumed that the displacements are either regularly varying or they have lighter tails. In the regularly varying case, it is shown that the point process sequence of normalized extremes converges to a Poisson random measure. We study the asymptotics of the scaled position of the rightmost particle in the nth generation when the tail of the displacement behaves like exp(−K(x)), where either K is a regularly varying function of index r>0, or K has an exponential growth. We identify the exact scaling of the maxima in all cases and show the existence of a non-trivial limit when r>1.

The Potential of Genome-Wide Prediction to Support Parental Selection, Evaluated with Data from a Commercial Barley Breeding Program.

Parental selection is at the beginning and contributes significantly to the success of any breeding work. The value of a cross is reflected in the potential of its progeny population. Breeders invest substantial resources in evaluating progeny to select the best performing genotypes as candidates for variety development. Several proposals have been made to use genomics to support parental selection. These have mostly been evaluated using theoretical considerations or simulation studies. However, evaluations using experimental data have rarely been conducted. In this study, we tested the potential of genomic prediction for predicting the progeny mean, variance, and usefulness criterion using data from an applied breeding population for winter barley. For three traits with genetic architectures at varying levels of complexity, ear emergence, plant height, and grain yield, progeny mean, variance, and usefulness criterion were predicted and validated in scenarios resembling situations in which the described tools shall be used in plant breeding. While the population mean could be predicted with moderate to high prediction abilities amounting to 0.64, 0.21, and 0.39 in ear emergence, plant height, and grain yield, respectively, the prediction of family variance appeared difficult, as reflected in low prediction abilities of 0.41, 0.11, and 0.14, for ear emergence, plant height, and grain yield, respectively. We have shown that identifying superior crosses remains a challenging task and suggest that the success of predicting the usefulness criterion depends strongly on the complexity of the underlying trait.

Strategy for Selection of Drought-Tolerant Arabica Coffee Genotypes in Brazil

This study aimed to establish a strategy for drought-tolerant selection in Arabica coffee genotypes in Brazil, combining field trials under natural conditions with controlled growth condition experiments. A group of genotypes was evaluated in the greenhouse using 28 morphological, anatomical, and physiological traits. In addition, the productivity of genotypes was evaluated in the field. Under water deficit in the greenhouse, 13 studied traits showed significant genetic variance. For these traits, the heritability coefficients estimated based on the progeny mean ranged from 65 to 92%. A selection index combined with predicted means was applied at these traits to select four progenies for drought tolerance under greenhouse conditions. Under field conditions, the selection applied to genetic values that favored positive genetic gains in four progenies, indicating the potential use of these cultivars for breeding advanced generations. The selection results of coffee plants under greenhouse conditions matched the selection results in the field in a water-deficit region by 50% based on productivity; thus, two genotypes (H419-3-3-7-16-11 and H516-2-1-1-7-2) were identified that have both the productivity and morpho-anatomical traits that confer greater drought tolerance. Finally, we discussed possible strategies for the development of drought-tolerant cultivars.

Phenotypic divergence among half-sib progenies of African mahogany.

Divergence studies are essential for the conservation of genetic resources and guidance in genetic improvement programs. This study aimed to assess the phenotypic dispersion of half-sib progenies using Gower's algorithm and the non-metric multidimensional scaling analysis based on qualitative and quantitative traits. Twenty-two half-sib progenies of African mahogany (Khaya senegalensis) were evaluated in a randomized block design with 22 treatments (progenies/origin), with 30 replications and one plant per plot, totaling 660 plants. The total tree height (cm), diameter at soil level (cm), chlorophyll A and B, presence of bifurcation, presence of lateral branches, stem tortuosity, and the phytosanitary and nutritional status according to a rating scale were evaluated. Data analysis was performed at the progeny mean level for the quantitative traits and the modal value was used for the qualitative traits. The technique used presented the distance between the progenies of K. senegalensis in a graphical form. The dispersion of the progenies in the graph is indicative that there is phenotypic variation in the progeny test, allowing to select individuals with characteristics of interest to improve mahogany for Piauí. Gower's algorithm applied to mixed data and non-metric multidimensional scaling are efficient methods to describe phenotypic similarities between progenies.

Pedigree selection under field conditions within Acala 1517-08 and its glandless derivatives for development of cotton resistant to Fusarium wilt caused by Fusarium oxysporum f. sp. vasinfectum race 4

The soil- and seed-borne fungus, Fusarium oxysporum f. sp. vasinfectum race 4 (FOV4), causes Fusarium wilt in cotton (Gossypium spp.) and represents a significant threat to cotton production in the US. The objectives of this study were to enhance FOV4 resistance in heterogeneous Acala 1517-08 and its derivatives through three cycles of pedigree selection in 2018, 2019 and 2020 under FOV4-infested field conditions. In 2017, in a field not infested with FOV4, 46, 12, and 23 single plants were selected for productivity from a base population of 1100–1400 plants of Acala 1517-08 and its derived glandless lines, Acala 1517-18 GLS and NM 13P1125, respectively. In 2018, the single plant selections, controls and other lines were tested in progeny-rows in an FOV4 infested field for disease responses including mortality rate (MR), root vascular staining (RVS), and disease incidence (DI), resulting in 41, 15, and 26 single plants selected from progenies of the three lines, respectively, based on RVS. These single plant selections were tested in 82 progeny-rows in the same field in 2019, and the second selection cycle based on RVS advanced 40, 16, and 37 plants selected from the progenies of the three lines, respectively, for further evaluation and the third selection cycle in a progeny test in 2020. In 2020, an average of 81–84% plants died in highly susceptible controls, Pima S-7 and Pima DP 744, due to FOV4 infections, while the resistant controls, Pima S-6, Pima PHY 841 RF and NuMex COT 17 GLS, incurred up to 19–24% mortality. As a result of the three cycles of single plant selection, a total of 12 progenies were identified to be as resistant as the resistant controls. On the progeny basis, MR between years was significantly correlated, and MR at different evaluation dates was also significantly correlated with one another and with mean RVS and DI within year. However, due to possible escapes of plants from FOV4 infections, the original RVS scores of individual plant selections were not correlated with their respective progenies; and no significant differences were detected among progeny means grouped based on RVS ratings for single plant selections. The results demonstrate that early plant mortality is a superior means of selecting against FOV4 susceptibility, while using RVS rating late in the season if excluding seedling MR may inflate and distort the resistance level of genotypes, rendering it less reliable in assessing FOV4 resistance in cotton. In addition, many single plants selected for FOV4 resistance with no RVS may be escapes, necessitating repeated progeny tests and selection. The importance of pedigree selection within germplasm, choice of resistant and susceptible checks, FOV4 inoculum density, and the use of RVS, and resistance versus tolerance in response to FOV4 infections under field conditions are discussed in detail.

Eastern Filbert Blight Resistance in American and Interspecific Hybrid Hazelnuts

Eastern filbert blight (EFB), caused by the fungus Anisogramma anomala, is a primary limitation to european hazelnut (Corylus avellana) cultivation in eastern North America. American hazelnut (Corylus americana) is the endemic host of A. anomala and, despite its tiny, thick-shelled nuts, is a potentially valuable source of EFB resistance and climatic adaptation. Interspecific hybrids (Corylus americana × C. avellana) have been explored for nearly a century as a means to combine EFB resistance with wider adaptability and larger nuts. Although significant progress was made in the past, the genetic diversity of the starting material was limited and additional improvements are needed for expansion of hazelnut (Corylus sp.) production outside of Oregon, where 99% of the U.S. crop is currently produced. Our objective was to determine if C. americana can be a donor of EFB resistance. We crossed 29 diverse EFB-resistant C. americana accessions to EFB-susceptible C. avellana selections (31 total progenies) to produce 2031 F1 plants. In addition, new C. americana germplasm was procured from across the native range of the species. The new collection of 1335 plants from 122 seed lots represents 72 counties and 22 states. The interspecific hybrid progenies and a subset of the American collection (616 trees from 62 seed lots) were field planted and evaluated for EFB response following field inoculations and natural disease spread over seven growing seasons. EFB was rated on a scale of 0 (no EFB) to 5 (all stems containing cankers). Results showed that progeny means of the interspecific hybrids ranged from 0.96 to 4.72. Fourteen of the 31 progenies were composed of at least one-third EFB-free or highly tolerant offspring (i.e., ratings 0–2), transmitting a significant level of resistance/tolerance. Several corresponding C. americana accessions that imparted a greater degree of resistance to their hybrid offspring were also identified. In addition, results showed that 587 (95.3%) of the 616 C. americana plants evaluated remained completely free of EFB. These findings confirm reports that the species rarely expresses signs or symptoms of the disease and should be robustly studied and exploited in breeding.

Development of superior lines of papaya from the Formosa group using the pedigree method and REML/Blup procedure

ABSTRACT Developing superior lines based on a simultaneous response from many traits of agronomic importance is a fundamental strategy to expand papaya cultivar supply, mainly the much-needed cultivars belonging to group Formosa. Our goal was to associate the pedigree method with REML/Blup procedure to select plants of progenies F2:3 with superior agronomic performance. The variance components and genetic parameters were estimated using REML approach, and the genetic values were predicted using Blup methodology. The combined selection was performed using the IG2 selection index based on weights associated with agronomic values to indicate the best progenies and lines. The heritability estimates of progeny mean were high in most traits and evidenced significant genetic variability between progenies. The narrow-sense individual heritability was moderate in traits such as commercial fruits and soluble solid contents, which indicates a favorable condition for selections within progenies. The index was consistent in the selection of six superior progenies according to the assessed traits. This index also enabled promising genetic gains in traits of great interest such as yield and pulp thickness. Although the progenies are derived from self generations, they proved to be superior in traits of significant importance such as yield, commercial fruits, and pulp thickness when compared to the Tainung-01 hybrid, which is a worldwide-planted cultivar used as a reference to Formosa representatives. Six lines were selected within the superior progenies to continue the Formosa group-lines development program. The association of the pedigree method with REML/Blup procedure can be useful to assist breeders in an autogamous breeding program.

Reimagining Maize Inbred Potential: Identifying Breeding Crosses Using Genetic Variance of Simulated Progeny

ABSTRACTProper choice of parents for breeding populations is essential in developing new maize (Zea mays L.) inbreds for improved hybrid performance. Breeders have frequently chosen parental combinations based on mid‐parent (MP) value, or predicted progeny mean, to combine favorable traits from the two parents. When two breeding populations have the same MP value, an accurate prediction of progeny variance may reveal which population has a greater potential for genetic gain. In this study we used available inbred genotypes and new hybrid phenotypes from 246 inbreds with expired Plant Variety Protection certificates and 39 historically important North American dent inbreds, all test crossed to Iodent inbred PHP02. We used the R package ‘PopVar’ to simulate biparental populations and perform genome‐wide prediction to predict the progeny mean, genetic variance, and superior progeny mean for grain yield, grain moisture, and test weight within each virtual population. Breeding crosses were ranked based on the mean grain yield of superior progeny and correlated trait responses for test weight and moisture. Results show that combining germplasm from different proprietors in new breeding crosses can produce inbreds with improved performance in a hybrid test cross. The simulation and prediction model presented in this study may help breeders to identify parental pairs with the greatest potential for genetic gain in hybrid crop breeding programs.

Validating Genomewide Predictions of Genetic Variance in a Contemporary Breeding Program

Predicting the genetic variance among progeny from a cross—prior to making said cross—would be a valuable metric for plant breeders to discriminate among possible parent combinations. The use of genomewide markers and simulated populations is one proposed method for making such predictions. Our objective was to assess the predictive ability of this method for three relevant quantitative traits within a breeding program regularly using genomewide selection. Using a training population of two‐row barley (Hordeum vulgare L.) lines, we predicted the mean (μ), genetic variance (VG), and superior progeny mean (μSP, mean of the best 10% of lines) of 330,078 possible parent combinations for Fusarium head blight (FHB) severity, heading date, and plant height. Twenty‐seven of these combinations were chosen to develop biparental populations, which were subsequently phenotyped for the same traits. We found that the predictive abilities (rMP) for μ and μSP were moderate to high (rMP = 0.46–0.69), whereas those for VG were lower (rMP = 0.01–0.48). Unsurprisingly, predictive ability was likely a function of trait heritability, as rMP estimates for heading date (the most heritable trait) were highest, and rMP estimates for FHB severity (the least heritable trait) were lowest. We observed strong negative bias when predicting VG (on average −83 to −96%), but the relative consistency of this bias across validation families indicates that it may have little impact when selecting crosses. We concluded that accurate predictions of VG and μSP are feasible, but as with any implementation of genomewide selection, reliable phenotypic data are critical.

Genetic parameters to production characters of palm heart in half-sibs progenies of palm peach

ABSTRACT: The peach palm (Bactris gasipaes) is a palm tree that produces palm heart originated of Amazonia with economic, social and environmental sustainability. To obtain improved cultivars it is necessary the evaluation and selection of genotypes with characteristics that support producers, manufacturing and consumers. In this context, the objective of this study was to estimate genetic parameters for palm heart production traits of peach palm considering half sibs progenies. Twenty progenies of Putumayo macrocarpa race were evaluated in seven cultivation cycles. The experiment was designed in complete randomized blocks, with 40 repetitions and one plant per plot. The genetic parameters were estimated by REML/BLUP methodology. Low genetic variability was observed in the population, possibly due to the narrow genetic base from original population. However, considering the significant genetic effect and the progeny mean heritability, the selection performed between progenies is more efficient than individual selection. The high number of measurements required for most of the evaluated characters becomes impractical in peach palm breeding programs. The number of palm heart per plant can be used to perform indirect selection for total production of palm heart.

Estimation of genetic parameters and selection for rooting capacity in peach

Abstract One of the most important criteria in the improvement of rootstocks is easiness of propagation. The objective of the present study was to verify the existence of genetic variability and the possibility of gains with selection in the rooting capacity among peach genotypes. Seventy-seven genotypes of peach belonging to five F3 families were evaluated. Rooting percentage (RP), number of roots per cutting (NR) and mean root length (RL) were evaluated. Genetic values ​​were estimated. The nineteen genotypes with the lowest rank summation index were selected to estimate the genetic gains. The variables RP, NR and RL had progeny mean heritabilities of 0.53, 0.60 and 0.83, respectively. Of the individuals selected, 89.5% belonged to the 713 (Talisma x Adafuel) family. The estimation of the genetic and phenotypic parameters show the possibility of success by selecting superior genotypes, with gains of 9.09, 17.47 and 24% for RP, NR and RL, respectively.

Use of genomic selection and breeding simulation in cross prediction for improvement of yield and quality in wheat (Triticum aestivum L.)

In wheat breeding, it is a difficult task to select the most suitable parents for making crosses aimed at the improvement of both grain yield and grain quality. By quantitative genetics theory, the best cross should have high progeny mean and large genetic variance, and ideally yield and quality should be less negatively or positively correlated. Usefulness is built on population mean and genetic variance, which can be used to select the best crosses or populations to achieve the breeding objective. In this study, we first compared five models (RR-BLUP, Bayes A, Bayes B, Bayes ridge regression, and Bayes LASSO) for genomic selection (GS) with respect to prediction of usefulness of a biparental cross and two criteria for parental selection, using simulation. The two parental selection criteria were usefulness and midparent genomic estimated breeding value (GEBV). Marginal differences were observed among GS models. Parental selection with usefulness resulted in higher genetic gain than midparent GEBV. In a population of 57 wheat fixed lines genotyped with 7588 selected markers, usefulness of each biparental cross was calculated to evaluate the cross performance, a key target of breeding programs aimed at developing pure lines. It was observed that progeny mean was a major determinant of usefulness, but the usefulness ratings of quality traits were more influenced by their genetic variances in the progeny population. Near-zero or positive correlations between yield and major quality traits were found in some crosses, although they were negatively correlated in the population of parents. A selection index incorporating yield, extensibility, and maximum resistance was formed as a new trait and its usefulness for selecting the crosses with the best potential to improve yield and quality simultaneously was calculated. It was shown that applying the selection index improved both yield and quality while retaining more genetic variance in the selected progenies than the individual trait selection. It was concluded that combining genomic selection with simulation allows the prediction of cross performance in simulated progenies and thereby identifies candidate parents before crosses are made in the field for pure-line breeding programs.

Genetic parameters and performance of sugarcane families under cold stress in the South of Brazil

Abstract: The objective of this work was to estimate the genetic parameters for the performance prediction of sugarcane (Saccharum spp.) families under natural cold stress, in Southern Brazil, and to identify the best combinations of parents aiming at the selection for tolerance to cold. Fifty-three full-sib families were evaluated in an incomplete block design, with five replicates per family, in the municipality of Pelotas, in the state of Rio Grande do Sul, Brazil. Harvest occurred in August 2013, nine months after planting and after cold spells with negative temperatures down to -2.2ºC. Statistical analyses, performed with the mixed model methodology, detected significant differences among families. Heritability estimates among progeny means were higher than those of individual heritability. Estimates of genetic progress for the traits megagrams of stalks per hectare, megagrams of brix per hectare, and number of stalks indicated gains of 93.8, 91.0, and 53.3%, respectively. A set of eight promising families that combine high estimates for yield and cold stress tolerance was obtained.

Heterosis and genetics parameters for yield and nutritional components in half-sibling maize progenies

The growing demand for maize creates a challenge to breeders, requiring the development of higher yielding and higher quality genotypes. The objective of this work was to estimate the most relevant heterosis, variance components and genetic parameters, and to use a multivariate approach to define narrow sense heritability profiles for yield and nutritional components in half-sib maize progenies. The experimental design used was random blocks, with a male parent (hybrid tester), five inbred lines (S5) as maternal parents and the progenies (hybrid Top Cross), totalizing 11 maize genotypes arranged in six replicates. Agronomic and nutritional characters were evaluated. Half-sibling progenies reveal greater additive genetic contribution to phenotypic expression through grain width and thickness, iron content, total flavonoids and carotenoids, soluble solids, and methionine. Narrow sense heritability values between and within progenies are higher for manganese content, glycine, proline and tryptophan. Regardless of the inbreeding line S5 used, heterosis gains are obtained for insertion of spike height, number of grain rows per spike, stem diameter, and zinc content, total carotenoids, soluble solids and pH. Specific heterosis’s evidenced for grain yield, glycine, serine, threonine, and phenylalanine. The multivariate approach used defines eight-character profiles regarding their genetic trends and indicates narrow sense heritability of the progeny mean as the major cause for this distinction.

A Novel Approach to Boost the Seed Cotton Yield via Irradiation to Enhance the Boll Weight and Boll Number in Diploid Cotton

Diplod cotton especially Gossypium herbeceum are poor seed cotton yielders and also have poor fiber properties while in parallel diploids have good buffering capacity towards the fluctuating environment. Hence an attempt has been made to enhance the yield levels in diploid cotton using gamma rays as an additional variability creating agent. Here a total of one hundred and ten progenies comprising of irradiated (F4M4 45), unirradiated (F4 52) and irradiated jayadhar (M4 13) were evaluated at Main Agricultural Research Station, UAS, Dharwad to obtain information on mean, variance, range, genetic variability, heritability and genetic advanced for thirteen traits. The mean, range and variance among progenies, F4M4 progenies exhibited relatively higher progeny mean performance and wider range of values for most the traits under study (seed cotton yield 60.89, 32-96 and 228.72). The high estimates of PCV and GCV were recorded for M4 generation for boll weight (20.82 and 20.29) and seed cotton yield (42.7 and 40.6) show simple irradiation helps to improve these traits whereas, F4M4 progenies recorded high PCV and GCV for seed index (11.2 and 10.29) indicating hybridization followed by irradiation has an additional advantage to improve this trait. The high heritability coupled with high genetic advance was noticed for seed cotton yield and yield components as well as fibre quality traits among progenies. When the assessment was made across the progenies for important traits to know how much percent has progressed to next generation the F4M4 contributed higher number of superior progenies for boll weight traits (10 progenies) and fibre length (7 progenies). The best performing progenies will be stabilizes over location and tested for their superiority with the existing variety.