Variation for agronomic traits, biomass allocation, and carbon storage in sorghum (sorghum bicolor [L.] moench) genotypes.

Abstract

Sorghum (Sorghum bicolor [L.] Moench, 2n = 2x = 20) is an ancient grain crop of Africa cultivated worldwide. The productivity of sorghum is low (< 1.5 t/ha) under smallholder farming systems in the region due to severe drought stress, poor soil health, diseases, insect pests, and noxious weeds. Besides its grain production for food, feed, and industrial raw materials, sorghum produces relatively high biomass for the biofuel and bioplastic industry. Sorghum’s high biomass production can transfer atmospheric carbon (C) to the soil throughout its growth stages, thereby enhancing soil fertility and crop productivity through atmospheric C sequestration. There is a need to select sorghum genotypes with optimised agronomic traits, high biomass production and water and nutrient use efficiencies to enhance economic yield and carbon sequestration capacity. Therefore, the overall aim of this study was to screen and select sorghum genotypes with better agronomic traits, biomass allocation, and C storage. The specific objectives of the study were: i. to quantify the extent of variation in biomass allocation and C storage between major crops, including sorghum for crop production, and C sequestration potential through a meta-analysis. ii. to assess agronomic performance, biomass production and carbon accumulation in selected sorghum genotypes for production and breeding. iii. to assess the extent of genetic variability for agronomic and carbon storage traits in selected sorghum genotypes to identify the best candidates for production or breeding. iv. to assess the trend and magnitude of relationships between agronomic and carbon storage traits in sorghum to identify grain yield and carbon storage contributing traits and to guide future sorghum variety development and release. A metanalysis was conducted from 40 global studies that reported on the allocation of plant biomass and C between roots and shoots of sorghum, maize, and wheat cultivars. Key statistics were calculated to determine the variability among the cultivars for total plant biomass (PB), shoot biomass (SB), root biomass (RB), root-to-shoot biomass ratio (RS), total plant carbon content (PCc), shoot carbon content (SCc), root carbon content (RCc), total plant carbon stock (PCs), shoot carbon stock (SCs), root carbon stock (RCs), and root-to-shoot carbon stock ratio (RCs/SCs). Maize exhibited the highest variability for PB (with a coefficient of variation [CV] of 31.2% and a mean of 4.2±1.3 Mg ha-1 yr-1), followed by wheat (CV of 24.2% and mean of

1.5±0.4 Mg ha-1 yr-1) and sorghum (16.8% and 2.0±0.8 Mg ha-1), respectively. A similar trend was observed for PCs, with maize (CV of 40.1% and mean of 1.6±0.7 Mg ha-1) showing the highest total plant C stock variability, followed by wheat (24.4% and 0.2±0.1 Mg ha-1), and sorghum (16.3% and 0.9±0.3 Mg ha-1), respectively. Maize exhibited the highest variability for RS (with a CV of 24.4% and mean of 0.1±0.03), while wheat exhibited the highest variability for RCs/SCs (30.92% and 0.2±0.05). The meta-analysis revealed that maize and sorghum have the highest variability for total plant biomass and plant carbon stocks, while wheat exhibits the highest variability for the below-ground biomass and carbon stocks. In the first experiment, 50 sorghum genotypes were evaluated using a 5 x 10 alpha lattice design with two replications at three locations (Silverton, Ukulinga, and Bethlehem) in South Africa during the 2022/23 growing season. The following agronomic and carbon storage traits were assessed: days to 50% heading (DTH), days to 50% maturity (DTM), plant height (PH), PB, SB, RB, RS, GY, HI, GCc, SCc, RCc, PCs, SCs, RCs, RCs/SCs, and grain carbon stock (GCs). A combined analysis of variance revealed significant (P < 0.05) genotype x location interaction for DTH, DTM, PH, PB, SB, RB, RS, and GY. Genotypes AS115, AS251, and AS134 were the best performing with the highest GY of 5.08 g plant-1, 21.83 g plant-1, and 21.42 g plant-1, respectively. Genotypes AS122 and AS27 ranked first and second, respectively, for all the carbon stock parameters except for RCs, whereas genotype AS108 had the highest RCs of 8.87 g plant-1. The principal component analysis identified GY, DTH, PH, PB, SB, RB, RCs, RCs/SCs, PCs, SCs, and GCs as the most discriminated traits among the test genotypes. The cluster analysis using agronomic and carbon-related parameters delineated the test genotypes into three genetic groups. The selected sorghum genotypes are recommended for further breeding and variety release adapted to various agroecologies in South Africa. Data from field experiments were computed to deduce variance components, heritability, and genetic advance to guide genotype selection. Higher phenotypic coefficient of variation (PCV) were recorded for PH (68.91%), followed by GY (51.8%), RB (50.51%), RS (41.96%), RCs/SCs (44.90%), and GCs (41.90%). In contrast, higher genotypic coefficient of variations (GCV) were recorded for GY (45.92%), followed by RB (39.24%), RCs/SCs (38.45), and RCs (34.62). The high PCV and GCV values suggest the availability of genetic variability among the test genotypes for the assessed traits. High to moderate broad-sense heritability and genetic advance were observed for HI (83.76 and 24.53%), GY (78.59 and 9.98%), PB (74.14 and 13.18%) and PCs (53.63 and 37.57%), respectively, suggesting a marked genetic contribution to the traits. High broad-sense heritability combined with increased genetic advance were

computed for PB, RB, GY, HI, RS, GCs, RCs, and RCs/SCs, indicating that genetic effects primarily control these traits. In the third experimental chapter, correlation and path coefficient analyses were computed to discern the trend and magnitude of associations of assembled traits to guide simultaneous selection for enhanced grain yield, its components and carbon storage. Significant (P < 0.05) positive phenotypic and genotypic correlations were observed between GY with HI at r = 0.79 and r = 0.76, DTH (r = 0.31 and r = 0.13), PH (r = 0.27 and r = 0.1), PB (r = 0.02 and r = 0.01), RB (r = 0.06 and r = 0.05), respectively. Further, the path analysis revealed significant positive direct effects of SB (0.61) and RB (0.46) on GY. The RS exerted a positive significant genotypic indirect effect (0.26) on GY through SB. The overall association analyses revealed that PB, SB, RB, RS, RCs, and RCs/SCs significantly influenced GY performance and are the principal traits when selecting sorghum genotypes with high carbon storage capacity. The present study identified the following promising genotypes: AS251, SS27, AS134, AS203, and AS563 for their high biomass production, grain yield, and C sequestration potentials. The identified genotypes could be advanced for cultivar development and further evaluated for net carbon contribution to the soil.