Genetic trends in CIMMYT’s tropical maize breeding pipelines

Abstract

Fostering a culture of continuous improvement through regular monitoring of genetic trends in breeding pipelines is essential to improve efficiency and increase accountability. This is the first global study to estimate genetic trends across the International Maize and Wheat Improvement Center (CIMMYT) tropical maize breeding pipelines in eastern and southern Africa (ESA), South Asia, and Latin America over the past decade. Data from a total of 4152 advanced breeding trials and 34,813 entries, conducted at 1331 locations in 28 countries globally, were used for this study. Genetic trends for grain yield reached up to 138 kg ha−1 yr−1 in ESA, 118 kg ha−1 yr−1 South Asia and 143 kg ha−1 yr−1 in Latin America. Genetic trend was, in part, related to the extent of deployment of new breeding tools in each pipeline, strength of an extensive phenotyping network, and funding stability. Over the past decade, CIMMYT’s breeding pipelines have significantly evolved, incorporating new tools/technologies to increase selection accuracy and intensity, while reducing cycle time. The first pipeline, Eastern Africa Product Profile 1a (EA-PP1a), to implement marker-assisted forward-breeding for resistance to key diseases, coupled with rapid-cycle genomic selection for drought, recorded a genetic trend of 2.46% per year highlighting the potential for deploying new tools/technologies to increase genetic gain.

Genetic trends for yield and key agronomic traits in pre-commercial and commercial maize varieties between 2008 and 2020 in Uganda

“…Recent reports indicated that there is improvement in the grain yield performance (1.4% year -1 or 39 kg ha -1 yr -1 ) of the inbred lines that are used to develop new products that are allocated and released for commercial production (Worku et al, 2020). This genetic improvement is reflected in the recent analysis of genetic trends in CIMMYT's breeding pipeline in ESA of up to 138 kg ha -1 yr -1 (Prasanna et al, 2022b). In other studies, genetic gains of 40 kg ha -1 year -1 have been reported in West Africa (Badu-Apraku et al, 2015).…”

Genetic gains in early maturing maize hybrids developed by the International Maize and Wheat Improvement Center in Southern Africa during 2000–2018

“…In addition, per se performances of the lines were assessed for yield performance, stress tolerance, and combining other desirable agronomic traits during the process of line development as well as in organized inbred line performance field trials. The breeding schemes adopted in generating the inbred lines and hybrids used in this study were described in detail by Prasanna et al. (2022) .…”

“…These included 32 optimal (well-watered and well-fertilized), 14 low N stress, nine managed drought stress, and 13 environments that have undergone random stresses, including abiotic and biotic stresses ( Table 1 ). Random stress is a mixture of several uncontrolled stress conditions that have happened intermittently at any stage during crop growing season affecting the yielding potential of the crop ( Setimela et al., 2017 ; Prasanna et al., 2022 ). Geographical locations, weather, and soil parameters of the test locations are described in Figure 2 and Supplementary Table S1 .…”

“…However, the increased production was mainly attributed to expansion in the area under maize production, as opposed to other regions of the world where an increase in maize production is largely associated with increased yields ( Onyutha, 2019 ). Several studies indicated the potential of increasing maize productivity in Africa beyond the current levels through adoption of improved maize varieties and sustainable and intensive farming options ( Abate et al., 2017 ; Cairns et al., 2021 ; Epule et al., 2022 ; Prasanna et al., 2022 ).…”

Genetic gains in IRRI’s rice salinity breeding and elite panel development as a future breeding resource

“…Various approaches and methodology have been used to estimate the genetic gains with the historical data (de la Vega et al 2007 ; Mackay et al 2011 ; Sharma et al 2012 ; Piepho et al 2014 ; Laidig et al 2014 , 2017 ; Morais Júnior et al 2015 ; Streck et al 2018 ; Hoyos-Villegas et al 2019 ; Muralidharan et al 2019 ; Lozada and Carter 2019 ; Kumar et al 2021 ; Prasanna et al 2022 ; Rahman et al 2023 ). The methodology used in this study was selected based on the unbalanced structure of the data, availability of pedigree information, and poor connectivity over consecutive years.…”