Key message Genome-wide association study (GWAS) demonstrated that multiple genomic regions influence grain quality traits under nitrogen-starved soils. Using genomic prediction, genetic gains can be improved through selection for grain quality traits. Abstract Soils in sub-Saharan Africa are nitrogen deficient due to low fertilizer use and inadequate soil fertility management practices. This has resulted in a significant yield gap for the major staple crop maize, which is undermining nutritional security and livelihood sustainability across the region. Dissecting the genetic basis of grain protein, starch and oil content under nitrogen-starved soils can increase our understanding of the governing genetic systems and improve the efficacy of future breeding schemes. An association mapping panel of 410 inbred lines and four bi-parental populations were evaluated in field trials in Kenya and South Africa under optimum and low nitrogen conditions and genotyped with 259,798 SNP markers. Genetic correlations demonstrated that these populations may be utilized to select higher performing lines under low nitrogen stress. Furthermore, genotypic, environmental and GxE variations in nitrogen-starved soils were found to be significant for oil content. Broad sense heritabilities ranged from moderate (0.18) to high (0.86). Under low nitrogen stress, GWAS identified 42 SNPs linked to grain quality traits. These significant SNPs were associated with 51 putative candidate genes. Linkage mapping identified multiple QTLs for the grain quality traits. Under low nitrogen conditions, average prediction accuracies across the studied genotypes were higher for oil content (0.78) and lower for grain yield (0.08). Our findings indicate that grain quality traits are polygenic and that using genomic selection in maize breeding can improve genetic gain. Furthermore, the identified genomic regions and SNP markers can be utilized for selection to improve maize grain quality traits.

African yam bean (AYB) is an affordable protein source capable of diversifying the food base in sub-Saharan Africa. However, research efforts made towards the crop's improvement and in expanding production are limited. This study characterized 169 AYB accessions at Jimma, Ethiopia, using 31 phenotypic characters. The analysis of variance revealed highly significant (P < 0.01) differences for days to 50% flowering, days to first flowering, leaf area, number of seeds per pod, pod length, seed thickness, total seed weight, petiole length and significant (P < 0.05) difference for terminal leaf length. Accession TSs62B produced the highest number of seeds per pod (17.65) and recorded the highest 100 seed weight (25.30 g), while 3A was the earliest to flower at an average of 84.50 d. Principal component analysis (PCA) of qualitative traits attributed 77.6% of observed variations to the first five principal components, of which the first two PC axes accounted for 53.6% of total variations. Cluster analysis and PCA biplot distinctly grouped the accessions into two major groups, cluster I had the highest number of accessions (108). The analytical approaches used confirmed considerable diversity across the germplasm with a distance matrix ranging from 0.37 to 0.85. The extent of diversity reflected in the current study provides breeders the baseline information to design breeding strategies, which might help identify materials for release as variety or parental lines for hybridization programmes.

Soils in sub-Saharan Africa are nitrogen deficient due to low fertilizer use and inadequate soil fertility management practices. This has resulted in a significant yield gap for the major staple crop maize, which is undermining nutritional security and livelihood sustainability across the region. Dissecting the genetic basis of grain protein, starch and oil content under nitrogen-starved soils can increase our understanding of the governing genetic systems and improve the efficacy of future breeding schemes. An association mapping panel of 410 inbred lines and four bi-parental populations were evaluated in field trials in Kenya and South Africa under optimum and low nitrogen conditions and genotyped with 259,798 SNP markers. Genetic correlations demonstrated that these populations may be utilized to select higher performing lines under low nitrogen stress. Furthermore, genotypic, environmental and GxE variations in nitrogen-starved soils were found to be significant for oil content. Broad sense heritabilities ranged from moderate (0.18) to high (0.86). Under low nitrogen stress, GWAS identified 42 SNPs linked to grain quality traits. These significant SNPs were associated with 51 putative candidate genes. Linkage mapping identified multiple QTLs for the grain quality traits. Under low nitrogen conditions, average prediction accuracies across the studied genotypes were higher for oil content (0.78) and lower for grain yield (0.08). Our findings indicate that grain quality traits are polygenic and that using genomic selection in maize breeding can improve genetic gain. Furthermore, the identified genomic regions and SNP markers can be utilized for selection to improve maize grain quality traits.

Advances in the fields of genomics and phenomics are currently creating significant foundations for the sustainable intensification of plant breeding initiatives targeting climate resilience. Genomics is a biological study that focuses on architecture, function, editing, mapping, and evolution of genomes. It can be applied extensively in climate resilience breeding for cost-effective, rapid, and high-through put genotyping, phenotyping, and trait mapping. The efficacy of genomics-assisted breeding (GAB) is strongly hinged on the high resolution and robustness of Next Generation Sequencing (NGS) and CRISPR/Cas9-based Gene Editing systems. The integration of genomics and phenomics in crop improvement can upscale the efficiency of breeding systems targeting climate resilience and hasten cultivar release cycle. Phenomics is an interdisciplinary field that focuses on the enhanced measurement of plant performance, growth, and composition. Similarly, phenomics has revolutionized the efficacy of plant breeding off-trial initiatives established to phenotypically characterize and study diversity levels of collected germplasm. Field phenomics tools such as the phenonet, phenomobile, and phenonetwork have proven to be efficient in capturing large sums of multiscale and multidimensional experimental data. The main purpose of this review article is to present a summarized account of the probable applications of integrated systems of genomics and phenomics in plant breeding for climate resilience in major crops.

The elevated research interest and increased cultivation of Hemp (Cannabis sativa) across the globe is significantly driven by its multidirectional industrial uses and medicinal properties. Scientific research publications focusing on hemp breeding plays a pivotal role in bridging the knowledge gap and opening new avenues for upscaling the efficiency of crop improvement initiatives. The identification of prevailing research trends and associations is critical in defining and mapping the trajectories of success in Hemp breeding. The advent of bibliometrics and scientometrics is currently providing a stead platform which fosters effective identification of current research patterns and examination of the applied methodologies, focus areas, and operational constraints. In the context of Hemp research, content assessments provide breeding initiatives with background data needed for exploring various traits of interest and for validating investments and related policies. The main thrust of this study is to perform a bibliometric and scientometric analysis of Scopus-indexed papers covering the field of ‘Hemp Breeding’, between calendar years 1908 and 2020. Data was analyzed using VOSviewer (Version 1.6.16) and Microsoft Excel (2019). The study found 152 papers composed of original articles (105, 69.08%), book chapters (23, 15.13%), conference papers (10, 6.58%), reviews (9, 5.92%), conference reviews (3, 1.97%) and books (2, 1.32%). A significant increment in research publications was observed after 1950. The assessment also indicated that most of the archived research was conducted or reported in the USA (13.82%), Italy (12.5%) and the Netherlands (11.18%). Furthermore, the highest number of papers over the studied period and topic were published by authors affiliated to Wageningen University & Research (16, 10.53%). Index keywords such as Cannabis sativa, hemp, genetic expression, genetic marker, and genetic diversity were covered extensively in the sampled journal editions. A comparative assessment of the results indicated that there is need to scale-up research initiatives targeting hemp trait improvements to cater for the projected high demand and climate change. This can be achieved through strengthening synergistic partnerships and knowledge exchanges across the hemp breeding value chain. This research will assist plant breeders in defining research requirements, determining evidence-based scientific gaps, and recognizing outstanding research institutions for potential intellectual sharing and cooperation.