Understanding rates of genetic gain in sorghum [Sorghum bicolor (L.) Moench] in the United States

Estimating genetic gains in sorghum [Sorghum bicolor (L.) Moench] is necessary to assess whether the current rates of improvement will meet future production demands. The current study was conducted to determine the rate of genetic gain in yield and associated traits over the commercial hybrid era using sorghum germplasm from the Texas A&M sorghum breeding program and a US sorghum seed company. From the Texas A&M AgriLife program, 60 hybrids that represented a 50‐yr span of hybrid breeding were grown and evaluated in five environments across Texas in 2016. In a separate set of trials, 14 commercial hybrids representing a similar timespan were evaluated in three Texas environments in 2016. In both programs, grain sorghum yields increased 0.008 t ha−1 annually over their respective timespans. Traits that increased over time included yield potential per plant, heterosis, test weight, panicle size, and grain number per panicle, whereas leaf angle, days to maturity, plant height, and yield stability demonstrated little to no change. Overall, ∼60% of total yield gains in US sorghum production are attributed to genetic improvement through sorghum breeding. Compared with other major US field crops, the rate of genetic gain in sorghum has been slower, presumably due to a combination of factors, which include continually shifting production environments, changing priorities in traits, reduced research investments (compared with other crops), and less‐than‐optimized heterotic groups.

Although cyanogenic glucosides are considered to play important roles in plant growth, development, and resistance against abiotic and biotic stresses, their presence in high concentrations in feed and food can be fatal to animals and humans. Sorghum [Sorghum bicolor (L.) Moench] is cyanogenic, and the cyanide potential varies with environmental factors, management, and genetic background. Acyanogenic lines have not been identified to date in natural collections. Although the variability of cyanide potentials in seedlings and leaves of plants at early growth stages has been highly researched, few works have looked beyond these stages, especially under variable environmental factors such as water deficit stress. Here, we evaluated 40 diverse sorghum lines for leaf dhurrin and soluble sugar content at various crop developmental stages and variable water availability. Five lines were identified with little‐to‐very low leaf dhurrin content across developmental stages and water availability. Leaves of 30‐d‐old sorghum plants had less cyanide potential than at later stages. A brief preflowering water stress, imposed at booting to flowering, decreased leaf dhurrin and soluble sugar contents, whereas a brief postflowering water stress or prolonged preflowering water stress increased dhurrin and soluble sugar contents. Rapid and efficient screening of dhurrin levels within existing sorghum germplasms could lead to the identification of additional lines with very low to nondetectable dhurrin levels, which will have an enormous impact on sorghum breeding and increase the agronomic value of the sorghum crop.

Sorghum (Sorghum bicolor (L.) Moench) is a climate-resilient C4 cereal and a vital pillar of food and feed security in arid and semi-arid regions worldwide. In China, the development and widespread adoption of hybrid sorghum breeding have revolutionized the crop's productivity, playing a transformative role in enhancing both yield and quality. The success of hybrid sorghum, particularly through the utilization of cytoplasmic male-sterility (CMS) systems, has marked a milestone in agricultural innovation, enabling the large-scale production of high-performing hybrids. The implementation of dwarf breeding and the continuous renewals of sorghum hybrid varieties have been pivotal in driving these improvements. As we commemorate the 60th anniversary of the promotion and application of three-line hybrid sorghum, we recognize the groundbreaking contributions of Chinese researchers in advancing sorghum breeding science. This review highlights key scientific breakthroughs and systematically summarizes the evolution of sorghum breeding in China. By reflecting on both past achievements and prospective opportunities, we aim to inform strategies that will sustain and enhance sorghum's contribution to China's agricultural resilience and global food security.

The increasing global food demand in the context of climate change is a major concern of the 21st century. Developing crop varieties with improved adaptability to variable environmental conditions might be crucial to ensure food supply. Sorghum [Sorghum bicolor (L.) Moench] is a staple cereal crop in semi-arid regions of the world and is also grown worldwide as feed and bioenergy crop. Its drought-tolerance ability makes it a strategic crop for sustainable grain production. Modern approaches to quantitative genetics and statistical models such as genomic-assisted breeding techniques offer new opportunities for further improvements in crop productivity and adaptability. Compared to other major cereal crops such as maize and wheat, the application of these approaches remains largely unexplored for grain sorghum. The motivation of this thesis is to implement statistical models that exploit information from phenotypic, pedigree and genomic data for improving genetic evaluation and selection in sorghum breeding. Chapter 2 assessed the performance of a novel method for spatial analysis of plant breeding field experiments based on two-dimensional smoothing with P-splines. This method was evaluated in comparison with the conventional spatial models by considering the improvement in precision and predictions of genetic effects in early generation sorghum breeding trials. The Chapter shows that both spatial methods produced equivalent performance. Differences in model parameterization as well as the advantages of the new spatial approach for routine application are discussed. In Chapter 3, the impact of using pedigree and genomic information on prediction quality was explored for different traits in sorghum. For this, the Chapter proposes to use BLUP models fitting weighted combinations of pedigree and genomic relationship matrices, where the best-predictive combination is identified empirically in each prediction scenario. Results showed that the use of a merged pedigree–genomic matrix always improved predictive ability and unbiasedness of prediction relative to conventional G-BLUP, mainly for the traits with lower heritabilities. Based on these outcomes, the inclusion of pedigree information in genomic models is recommended to optimize predictions when the additive variation is not fully explained by markers. Chapter 4 presents an extension of the study in Chapter 3 to the context of multi-trait genomic prediction. Specifically, we assessed the capacity of multi-trait models to improve genomic prediction for grain yield and stay-green in sorghum by using information from correlated auxiliary traits. In general, results showed that genomic prediction for both target traits can be enhanced by combining information from specific sets of traits. Predictions from conventional multi-trait G-BLUP were also optimized by combining pedigree and genomic information. Chapter 5 investigated the effect of modelling genotype-by-environment interaction (G×E) on genomic prediction for grain yield in drought-stress and non-stress environments. Results indicated that accommodating G×E in genomic models was beneficial to improve the quality of prediction for specific adaptation as well as for broad adaptation to both types of environments. This Chapter also tested if better genomic predictions can be obtained by accounting for heterogeneous variances of marker effects. We found that weighting individual markers based on estimated locus-specific variances produced important improvements in predictive performance of genomic models, even for a largely polygenic trait such as grain yield. To conclude, this thesis deals with different challenging aspects that may affect genetic evaluation in modern sorghum breeding. Specifically, several statistical modeling strategies making use of different sources of information have been proposed and assessed. The findings presented in this thesis are expected to contribute to increase the efficiency of selection schemes not only for sorghum but for crops in general.

Key messagesWe investigate a method of extracting and fitting synthetic environmental covariates and pedigree information in multilocation trial data analysis to predict genotype performances in untested locations.Plant breeding trials are usually conducted across multiple testing locations to predict genotype performances in the targeted population of environments. The predictive accuracy can be increased by the use of adequate statistical models. We compared linear mixed models with and without synthetic covariates (SCs) and pedigree information under the identity, the diagonal and the factor-analytic variance-covariance structures of the genotype-by-location interactions. A comparison was made to evaluate the accuracy of different models in predicting genotype performances in untested locations using the mean squared error of predicted differences (MSEPD) and the Spearman rank correlation between predicted and adjusted means. A multi-environmental trial (MET) dataset evaluated for yield performance in the dry lowland sorghum (Sorghum bicolor (L.) Moench) breeding program of Ethiopia was used. For validating our models, we followed a leave-one-location-out cross-validation strategy. A total of 65 environmental covariates (ECs) obtained from the sorghum test locations were considered. The SCs were extracted from the ECs using multivariate partial least squares analysis and subsequently fitted in the linear mixed model. Then, the model was extended accounting for pedigree information. According to the MSEPD, models accounting for SC improve predictive accuracy of genotype performances in the three of the variance-covariance structures compared to others without SC. The rank correlation was also higher for the model with the SC. When the SC was fitted, the rank correlation was 0.58 for the factor analytic, 0.51 for the diagonal and 0.46 for the identity variance-covariance structures. Our approach indicates improvement in predictive accuracy with SC in the context of genotype-by-location interactions of a sorghum breeding in Ethiopia.

Sorghum [Sorghum bicolor (L.) Moench] is an important staple food for human consumption and a source of animal feed in the semiarid regions of the world. Sustained positive rates of crop improvement are necessary to supply food and feed to a growing population. However, land allocated to sorghum and its inclusion in production systems has been in constant decline. Here we report the rate of sorghum genetic gain in a commercial breeding program in the United States and provide evidence that a modest yield improvement is an important factor limiting land allocation to this crop. A 6‐year study that evaluated 50 sorghum genotypes commercialized between the decades of 1960 and 2010 was conducted in 19 environments within the US Sorghum Belt region. Yield varied between 500 and 850 g m−2. Here we show a positive rate of genetic gain of 2.63 g m−2 y−1 on average across three different maturity groups grown in the United States. Rates ranged from 2.1 to 4.3 g m−2 y−1 across maturity groups. This result contrasts with a stagnant rate of crop improvement for many regions of the world, yet the rates are insufficient to reverse the negative trend in planted area. Breeding technologies are proposed to hasten genetic gain in sorghum to reverse the loss of on‐farm agricultural biodiversity.

The global focus on enhancing sorghum [Sorghum bicolor (L.) Moench] for biomass-related traits is increasing due to its potential contribution to the growth and sustainability of the ethanol and biogas production chain. Heterosis has been widely used in sorghum breeding, especially in improving biomass yield using efficient crossing and selection methods. The objective of this study was to assess the heterosis potential of elite sorghum accessions. Ten hybrids were established using five reciprocal crosses of seven elite breeding accessions. The hybrids and the parental lines were significant of great variation for plant height (PH), panicle length (PL), number of leaves (NL), and stem diameter (SD). Most hybrids had high positive mid-parent heterosis for biomass-related traits, while better parental heterosis ranged from -7.90 to 31.16 for PH, 17.14 to 79.59 for PL, -39.68 to 13.20 NL, and -19.19 to 104.23% for SD. Four hybrids (P6×P4, P4×P6, P6×P5, and P5×P6) exhibited plant heights greater than the best parent (P5:322.33 cm). Reciprocal cross effects had a significant impact on PH and SD, with a wide range of -10.23 to 39.35% and -37.50 to 30.55%, respectively. The results indicated that heterosis could be come true for the characters of plant height, panicle length, and number of leaves, and stem diameter that contributes great impact on having high biomass.

Sorghum (Sorghum bicolor) is an economically important cereal crop that can be used as human food, animal feed, and for industrial use such as bioenergy. In sorghum breeding programs, development of cultivars with desirable seed quality characteristics is important and development of rapid low-cost screening methods for seed nutritional traits are desired, since most standard methods are destructive, slow, and less environmentally friendly. This study investigates the feasibility of single kernel NIR spectroscopy (SKNIRS) for rapid determination of individual sorghum seed components. We developed successful multivariate prediction models based on partial least squares (PLS) regression for protein, oil, and weight in sorghum. The results showed that for sorghum protein content ranging from 8.92% to 18.7%, the model coefficients of determination obtained were (RMSEC= 0.44) and (RMSEP= 0.69). The model coefficients of determination for oil prediction were (RMSEC= 0.23) and (RMSEP= 0.41) for oil content ranging from 1.96% to 5.61%. For weight model coefficients of determination were (RMSEC= 0.007) and (RMSEP= 0.007) for seeds ranging from 4.40 mg to 77.0 mg. In conclusion, mean spectra SKNIRS can be used to rapidly determine protein, oil, and weight in intact single seeds of sorghum seeds and can provide a nondestructive and quick method for screening sorghum samples for these traits for sorghum breeding and industry use.

Molecular variation within known genes controlling specific functions provide candidate gene-based markers which are tightly linked with the trait of interest. Unigene-derived microsatellite markers, with their unique identity and positions, offer the advantage of unraveling variation in the expressed component of the genome. We characterized ≥12-bp-long microsatellite loci from 13,899 unique sequences of sorghum [Sorghum bicolor (L.) Moench] available in the NCBI unigene database for their abundance and possible use in sorghum breeding. Analysis of 12,464 unigenes (≥200-bp) using MISA software identified 14,082 simple sequence repeats (SSRs) in 7,370 unigenes, from which 1,519 unigene SSR markers were developed. The average frequency of SSR was 1 per1.6 kb and 1.0 per 1.1 unigene; hexamers followed by trimers were found in abundance, of which 33.3% AT-rich and CCG repeats were the most abundant. Of the 302 unigene SSRs tested, 60 (19.8%) were polymorphic between the two parents, M35-1 and B35 of a recombinant inbred line (RIL) mapping population. A mapping population consisting of 500 RILs was developed using the above two parents, and a subset of random 245 RILs was used for genotyping with polymorphic SSRs. We developed a linkage map containing 231 markers, of which 228 (174 genomic and 54 genic) were microsatellites and three were morphological markers. Markers were distributed over 21 linkage groups, and spanned a genetic distance of 1235.5 cM. This map includes 81 new SSRs, of which 35 (21 unigene and 14 genomic) were developed in the present study and 46 from other studies. The order of the SSR markers mapped in the present study was confirmed physically by BLAST search against the whole-genome shotgun sequence of sorghum. Many unigene sequences used for marker development in this study include genes coding for important regulatory proteins and functional proteins that are involved in stress-related metabolism. The unigene SSR markers used together with other SSR markers to construct the sorghum genetic map will have applications in studies on comparative mapping, functional diversity analysis and association mapping, and for quantitative trait loci detection for drought and other agronomically important traits in sorghum.

Crossing sorghum [Sorghum bicolor (L.) Moench] obtained from different areas of Ethiopia were done in 2004/05 cropping season. In 2005/06 evaluation of 15 F1s with their parents were done in a randomized complete block design with three replications at Bako. The study was conducted to estimate combining ability and determine type of gene actions involved in the inheritance of yield and yield components traits. Analysis of variance revealed that mean squares due to genotypes, parents and crosses were highly significant (P<0.01) for all the traits except for 100 kernel weight that were significant for crosses. Mean squares due to general combining ability (GCA) and specific combining ability (SCA) were highly significant for all characters studied, except non significant SCA for 100 kernel weight. For yield, three of the parents, 212646, 69543 and 69193 had the best general combiner and incorporating these parents for grain yield per panicle in sorghum breeding may be importatnt. Based on specific combining ability analysis for grain yield per panicle five hybrids 69543 x 223506, 212646 x 223506, 97MW5122 x 212646, 97MW5122 x 69543 and 212646 x 69193 were the best in the experiment. The estimate of variance components showed that the variance due to SCA was higher in magnitude than GCA in the case of days to maturity, panicle width, panicle weight, kernel number per panicle and grain yield. Therefore, these traits were predominantly under the control of non-additive type of gene actions. Whereas variance of GCA was higher than SCA in the case of days to flowering, plant height, leaf number per plant, leaf length, leaf width, leaf area, panicle length and 100 kernel weight indicating that additive type of gene action was playing a greater role in the inheritance of these traits. Keywords: Combining Ability; Diallel; Gene Action; Sorghum bicolor

New sources of genetic diversity must be incorporated into plant breeding programs if they are to continue increasing grain yield and quality, and tolerance to abiotic and biotic stresses. Germplasm collections provide a source of genetic and phenotypic diversity, but characterization of these resources is required to increase their utility for breeding programs. We used a barley SNP iSelect platform with 7,842 SNPs to genotype 2,417 barley accessions sampled from the USDA National Small Grains Collection of 33,176 accessions. Most of the accessions in this core collection are categorized as landraces or cultivars/breeding lines and were obtained from more than 100 countries. Both STRUCTURE and principal component analysis identified five major subpopulations within the core collection, mainly differentiated by geographical origin and spike row number (an inflorescence architecture trait). Different patterns of linkage disequilibrium (LD) were found across the barley genome and many regions of high LD contained traits involved in domestication and breeding selection. The genotype data were used to define ‘mini-core’ sets of accessions capturing the majority of the allelic diversity present in the core collection. These ‘mini-core’ sets can be used for evaluating traits that are difficult or expensive to score. Genome-wide association studies (GWAS) of ‘hull cover’, ‘spike row number’, and ‘heading date’ demonstrate the utility of the core collection for locating genetic factors determining important phenotypes. The GWAS results were referenced to a new barley consensus map containing 5,665 SNPs. Our results demonstrate that GWAS and high-density SNP genotyping are effective tools for plant breeders interested in accessing genetic diversity in large germplasm collections.

Local landrace and breeding germplasm is a useful source of genetic diversity for regional and global crop improvement initiatives. Sorghum (Sorghum bicolor L. Moench) in western Africa (WA) has diversified across a mosaic of cultures and end uses and along steep precipitation and photoperiod gradients. To facilitate germplasm utilization, a West African sorghum association panel (WASAP) of 756 accessions from national breeding programs of Niger, Mali, Senegal, and Togo was assembled and characterized. Genotyping-by-sequencing (GBS) was used to generate 159,101 high-quality biallelic single nucleotide polymorphisms (SNPs), with 43% in intergenic regions and 13% in genic regions. High genetic diversity was observed within the WASAP (π = .00045), only slightly less than in a global diversity panel (GDP) (π = .00055). Linkage disequilibrium (LD) decayed to background level (r2 < .1) by ∼50 kb in the WASAP. Genome-wide diversity was structured both by botanical type and by populations within botanical type with eight ancestral populations identified. Most populations were distributed across multiple countries, suggesting several potential common gene pools across the national programs. Genome-wide association studies (GWAS) of days to flowering (DFLo) and plant height (PH) revealed eight and three significant quantitative trait loci (QTL), respectively, with major height QTL at canonical height loci Dw3 and SbHT7.1. Colocalization of two of eight major flowering time QTL with flowering genes previously described in U.S. germplasm (Ma6 and SbCN8) suggests that photoperiodic flowering in West African sorghum is conditioned by both known and novel genes. This genomic resource provides a foundation for genomics-enabled breeding of climate-resilient varieties in WA.

The breeding of sorghum, Sorghum bicolor (L.) Moench, aimed at improving its nutritional quality, is of great interest, since it can be used as a highly nutritive alternative food source and can possibly be cultivated in regions with low rainfall. The objective of the present study was to evaluate the potential and genetic diversity of grain-sorghum hybrids for traits of agronomic and nutritional interest. To this end, the traits grain yield and flowering, and concentrations of protein, potassium, calcium, magnesium, sulfur, iron, manganese, and zinc in the grain were evaluated in 25 grain-sorghum hybrids, comprising 18 experimental hybrids of Embrapa Milho e Sorgo and seven commercial hybrids. The genetic potential was analyzed by a multi-trait best linear unbiased prediction (BLUP) model, and cluster analysis was accomplished by squared Mahalanobis distance using the predicted genotypic values. Hybrids 0306037 and 0306034 stood out in the agronomic evaluation. The hybrids with agronomic prominence, however, did not stand out for the traits related to the nutritional quality of the grain. Three clusters were formed from the dendrogram obtained with the unweighted pair group method with arithmetic mean method. From the results of the genotypic BLUP and the analysis of the dendrogram, hybrids 0577337, 0441347, 0307651, and 0306037 were identified as having the potential to establish a population that can aggregate alleles for all the evaluated traits of interest.

Utility of indirect and direct selection traits for improving Striga resistance in two sorghum recombinant inbred populations

ABSTRACTDrought associated with climate change has increasingly endangered the sustainability and potential of agriculture, notably crop production. Therefore, there is a need to develop adaptive and resilient crop varieties for sustainable crop production and food systems. Sorghum [Sorghum bicolor (L.) Moench] is a vital crop in drought‐prone areas, supporting the livelihoods of over 750 million people globally. Sorghum grain yield is low in arid and semi‐arid regions, with a mean of 0.9 t/ha compared to the global average of 2.5 t/ha due to a lack of improved varieties tolerant to recurrent drought and heat and biotic constraints and desirable product profiles. Integrative breeding for early maturity, high harvest index, and water use efficiency (WUE) is an economical and sustainable strategy to improve sorghum productivity and mitigate drought effects. These are crucial proxy traits that can guide sorghum improvement for drought tolerance, but current information regarding their simultaneous selection and breeding progress is sparse and scattered; hence, the review aims to address this gap. The paper highlights innovations and advances in sorghum improvement and progress towards early maturity, high harvest index, and WUE. The first section examines the impact of drought on sorghum production, integrative pre‐breeding and breeding of sorghum, opportunities for breeding early‐maturing, high‐yielding, and water‐use‐efficient sorghum varieties, and the associated breeding progress and genetic gains. Further, it outlines the opportunities and challenges of the available breeding methods for developing climate‐smart, early‐maturing, and drought‐tolerant sorghum varieties. The information presented in this paper can guide agronomists and breeders in developing and deploying new‐generation sorghum varieties with integrative traits adapted to arid and semi‐arid regions.