Heterosis and combining ability are two important considerations in the utilization of heterosis, which can be used to generate excellent hybrid resource candidates and is very important in ...conventional hybrid breeding. In this study, the combining ability, heritability, and heterosis of eight major agronomic traits were analyzed in 10 tomato parents and 45 crosses between them. As well as TY-301, a recognized and official excellent variety that is currently selling well on the market was used as a control to conduct a control heterosis analysis, with the goal of selecting ideal parents with high combining ability and new hybrids with commodity value, high yield, early maturity, and high quality. The results showed that both additive and nonadditive genetic effects are involved in the expression of the traits and that the additive genetic effect is dominant in trait inheritance. Although general combining ability (GCA) and specific combining ability (SCA) were not correlated, and the strength of heterosis depends on SCA, the sum of the parental GCA values (GCAsum) did predict heterosis for some traits with higher predictive accuracy than did SCA. Compared with heterosis, GCAsum can better predict hybrid performance. Finally, the parent 17,969 was the breeding material with the best comprehensive trait performance, especially in yield. We screened a high-yielding candidate combination 17,927 × 17,969 and a precocious and good taste candidate combination 17,666 × 17,927. This information may play an important role in the selection of superior parents and hybrid combinations based on combining ability and heterosis analysis.
Eighteen hybrids generated from crossing six lines with three testers were studied along with their parents for combining ability and gene action involved in the expression of characters in barley to ...identify suitable parents and desirable hybrid combinations. Observations were recorded for days to ear emergence, days to maturity, the number of productive tillers per plant, ear length (cm.), grains per spike, biological yield per plant (g.), harvest index (%), 1000-grain weight and grain yield per plant (g.). The mean squares for General Combining Ability (GCA) and Specific Combining Ability (SCA) effects were found highly significant for all the traits studied. Among the parents, tester NDB-1173 and lines RD-2909, RD-2899 and RD-2768 were good general combiners for grain yield and its component traits. On the basis of SCA effects, RD-2909 x NDB-943, NDB-1618 x NDB-1173, RD-2768 x NDB-3, HUB-240 x NDB-1173 and RD-2899 x NDB-943 for grain yield were observed as most promising crosses.
Prediction of single-cross performance has been a major goal of plant breeders since the beginning of hybrid breeding. Recently, genomic prediction has shown to be a promising approach, but only ...limited studies have examined the accuracy of predicting single-cross performance. Moreover, no studies have examined the potential of predicting single crosses among random inbreds derived from a series of biparental families, which resembles the structure of germplasm comprising the initial stages of a hybrid maize breeding pipeline. The main objectives of this study were to evaluate the potential of genomic prediction for identifying superior single crosses early in the hybrid breeding pipeline and optimize its application. To accomplish these objectives, we designed and analyzed a novel population of single crosses representing the Iowa Stiff Stalk synthetic/non-Stiff Stalk heterotic pattern commonly used in the development of North American commercial maize hybrids. The performance of single crosses was predicted using parental combining ability and covariance among single crosses. Prediction accuracies were estimated using cross-validation and ranged from 0.28 to 0.77 for grain yield, 0.53 to 0.91 for plant height, and 0.49 to 0.94 for staygreen, depending on the number of tested parents of the single cross and genomic prediction method used. The genomic estimated general and specific combining abilities showed an advantage over genomic covariances among single crosses when one or both parents of the single cross were untested. Overall, our results suggest that genomic prediction of single crosses in the early stages of a hybrid breeding pipeline holds great potential to redesign hybrid breeding and increase its efficiency.
This study was conducted to estimate heterosis and combining ability for yield and some economic-related characteristics in tomato. For this purpose, six tomato lines with their 15 direct hybrids ...resulted from half-diallel mating were cultivated during the 2017 and 2018 seasons in Al-Jamasah station, Tartous agricultural research center, Syria. Results showed that most of the hybrids were characterized by significant desirable heterosis compared to mid-parents and the best-parent for most of the studied traits. Heterosis reached 49.03 and 33.4% for single plant yield, -31.2 and -29.27 for the number of days to the beginning of flowering, 89.73 and 61.77% for the number of fruits per cluster, 15.72 and 9.30% for fruit height, 27.29 and 24.18% for fruit diameter, 32.55 and 24.18% for the number of locales per fruit comparing to mid-parents and best-parent, respectively. The hybrids T2×T6, T2×T8, and T8×T16 were significantly superior and could be promising hybrids for improving yield potential. Variations related to general and specific combining ability were highly significant, indicating the role of additive and non-additive gene action in the inheritance of the studied traits. Furthermore, the ratio (σ2GCA/σ2SCA) showed the control of additive gene action in the inheritance of fruit weight, fruit height, fruit diameter, and the number of fruits per cluster, while non-additive gene action controlled the inheritance of single plant yield, the number of days to flowering and the number of locales per fruit.
Development and deployment of high-yielding maize varieties with native resistance to Fall armyworm (FAW), turcicum leaf blight (TLB), and gray leaf spot (GLS) infestation is critical for addressing ...the food insecurity in sub-Saharan Africa. The objectives of this study were to determine the inheritance of resistance for FAW, identity hybrids which in addition to FAW resistance, also show resistance to TLB and GLS, and investigate the usefulness of models based on general combining ability (GCA) and SNP markers in predicting the performance of new untested hybrids. Half-diallel mating scheme was used to generate 105 F
hybrids from 15 parents and another 55 F
hybrids from 11 parents. These were evaluated in two experiments, each with commercial checks in multiple locations under FAW artificial infestation and optimum management in Kenya. Under artificial FAW infestation, significant mean squares among hybrids and hybrids x environment were observed for most traits in both experiments, including at least one of the three assessments carried out for foliar damage caused by FAW. Interaction of GCA x environment and specific combining ability (SCA) x environment interactions were significant for all traits under FAW infestation and optimal conditions. Moderate to high heritability estimates were observed for GY under both management conditions. Correlation between GY and two of the three scorings (one and three weeks after infestation) for foliar damage caused by FAW were negative (-0.27 and -0.38) and significant. Positive and significant correlation (0.84) was observed between FAW-inflicted ear damage and the percentage of rotten ears. We identified many superior-performing hybrids compared to the best commercial checks for both GY and FAW resistance associated traits. Inbred lines CML312, CML567, CML488, DTPYC9-F46-1-2-1-2, CKDHL164288, CKDHL166062, and CLRCY039 had significant and positive GCA for GY (positive) and FAW resistance-associated traits (negative). CML567 was a parent in four of the top ten hybrids under optimum and FAW conditions. Both additive and non-additive gene action were important in the inheritance of FAW resistance. Both GCA and marker-based models showed high correlation with field performance, but marker-based models exhibited considerably higher correlation. The best performing hybrids identified in this study could be used as potential single cross testers in the development of three-way FAW resistance hybrids. Overall, our results provide insights that help breeders to design effective breeding strategies to develop FAW resistant hybrids that are high yielding under FAW and optimum conditions.
The experiment was aimed to study the combining ability of different parental lines in 8x8 diallel cross, carried out in Kharif 2016 at ICAR-CICR Regional Station, Sirsa, Haryana, India. Eight ...parental genotypes (RS-2013, RST-9, RS-810, F-1378, F-2164, F-2228, LH-2076 and LH-2108) were crossed in complete diallel fashion. Fifty-six F1 hybrids along with their parents were grown during Kharif-2017. Genotypes showed significant (p≤0.01) differences for mean squares values for all the traits under study. Mean squares due to GCA were higher in magnitude than SCA for majority of the traits and their inheritance was mainly governed by additive type of gene action and partially by non-additive. F-2228, F-2164 and LH-2108 were the parents with best general combining abilities and their combinations produced best F1 hybrids such as F-2228 x LH-2108, F-2164 x F-2228, RS-2013 x F-2228 and reciprocal hybrids like F-2228 x F-1378, F-2228 x RS-2013 and LH-2108 x F-2164 which performed very well in direct and reciprocal combinations.
Prediction models based on pedigree and/or molecular marker information are now an inextricable part of the crop breeding programs and have led to increased genetic gains in many crops. Optimization ...of IRRI’s rice drought breeding program is crucial for better implementation of selections based on predictions. Historical datasets with precise and robust pedigree information have been a great resource to help optimize the prediction models in the breeding programs. Here, we leveraged 17 years of historical drought data along with the pedigree information to predict the new lines or environments and dissect the G × E interactions. Seven models ranging from basic to proposed higher advanced models incorporating interactions, and genotypic specific effects were used. These models were tested with three cross-validation schemes (CV1, CV2, and CV0) to assess the predictive ability of tested and untested lines in already observed environments and tested lines in novel or new environments. In general, the highest prediction abilities were obtained when the model accounting interactions between pedigrees (additive) and environment were included. The CV0 scheme (predicting unobserved or novel environments) reveals very low predictive abilities among the three schemes. CV1 and CV2 schemes that borrow information from the target and correlated environments have much higher predictive abilities. Further, predictive ability was lower when predicting lines in non-stress conditions using drought data as training set and/or
vice-versa
. When predicting the lines using the data sets under the same conditions (stress or non-stress data sets), much better prediction accuracy was obtained. These results provide conclusive evidence that modeling G × E interactions are important in predictions. Thus, considering G × E interactions would help to build enhanced genomic or pedigree-based prediction models in the rice breeding program. Further, it is crucial to borrow the correlated information from other environments to improve prediction accuracy.
Information on gene action controlling quantitative traits is important for effective selection. A five-parent diallel cross, which generated 10 F1 hybrids of okra (Abelmoscus esculentus) were ...evaluated during the early and late planting seasons of 2019 in Ibadan, Nigeria. Data obtained were subjected to diallel analysis and genotype by yield-trait (GYT) biplot analysis to estimate combining ability effects and identify stable hybrids for measured traits respectively. Genotype mean squares were significant (p≤0.01) for all most measured traits. Furthermore, General Combining Ability (GCA) and Specific Combining Ability (SCA) mean squares were significant (p≤0.05/0.01) for most measured traits, indicating the influence of additive and non-additive gene actions in expression of these traits. Preponderance of non-additive gene effects shows the high influence of the environment on most of the considered traits in this study. Iwo Nla had the most desirable GCA estimates of -0.98 and 1.14, for days to 50% flowering (DTF), number of fruits per plant (NoF) respectively while IK11 had the most desirable GCA values for mature-fruit width (0.21) and 1000-seed weight (5.71). SCA estimates were most desirable for NH47-4 × LD88, NH47-4 × Iwo Nla, with values of -4.21 and 4.32 for DTF and NoF respectively. Hybrids NH47-4 × Iwo Nla and IK11 × Clemson associated with higher NoF x trait might be useful for improvement of number of fruits per plant in this population.
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