Genetic Variances and Relationship among Traits of an Early Maturing Maize Population under Drought‐stress and Low Nitrogen Environments

Abstract

Drought and low soil nitrogen (low N) are major causes of low grain yield of maize (Zea mays L.) in sub‐Saharan Africa (SSA). An early maturing maize population, TZE‐Y Pop DT STR, had undergone four cycles of selection for drought tolerance, followed by four selection cycles for resistance to Striga hermonthica (Del.) Benth., which is normally conducted under low N (about 30 kg N ha‐1). The objectives of this study were to estimate residual genetic variances, predict future gains from selection, and investigate inter‐trait relationships in the population under drought‐stress, low N and across research environments. North Carolina Design I was used to develop 250 full‐sib progenies from the improved population, which were evaluated in three drought‐stress and two low N environments in Nigeria, 2011 to 2013. Additive genetic variances were not significant for most traits under the research conditions. The predicted gains from selection for grain yield were 5.3, 8.5 and 7.5% cycle‐1 under drought, low N, and across environments. These results suggested the absence of substantial genetic variability in the population to ensure progress from selection. Ears per plant (EPP), ear aspect (EASP), plant aspect (PASP), and stay green characteristic (STGR) were consistently identified as important secondary traits under both research conditions. We concluded that there is need to introgress new sources of favorable alleles for drought‐stress and low N tolerance into the population for guaranteed progress from selection, using EPP, EASP, PASP, and STGR in combination with yield in a selection index under drought‐stress and low N.

Gains in Grain Yield of Extra‐Early Maize during Three Breeding Periods under Drought and Rainfed Conditions

“…A plausible reason for this was that the emphasis of the breeding program was more on improvement in drought tolerance rather than performance of cultivars under rainfed environments. The results of this study are inconsistent with the findings of Talabi et al (2017), who identified ASI, EASP, PASP, STGR, and EPP as the primary traits directly responsible for the variability in grain yield of early-maturing full-sib progenies under drought stress. In addition to marker-assisted selection and genomic selection, several other strategies outlined by Masuka et al (2017b) for increasing genetic gains in ESA breeding pipeline are being used in WCA under the Drought Tolerant Maize for Africa (DTMA)/Stress Tolerant Maize for Africa (STMA) Project for accelerating genetic gains.…”

“…With the recent advances in molecular breeding techniques, marker-assisted selection and genomic selection schemes are presently being used to fast-track breeding processes and accelerate yield gains in our program. The difference in the findings may be explained by the differences in the genetic materials used for the present study; the cultivars evaluated in the present study were extra-early maturing, whereas Talabi et al (2017) evaluated early-maturing full-sib progenies. These include, among others, an increase in the size of the IITA maize breeding program to facilitate the use of higher selection intensity and an increase in the precision of selection to achieve higher heritability.…”

“…The implications of the results obtained in the present study are that the extra-early OPVs had better responses to selection for improved grain yield and drought tolerance than the early and intermediate-late varieties tested under drought stress. Badu-Apraku et al (2014) and Talabi et al (2017) used the path coefficient analysis (Wright, 1921;Dewey and Lu, 1959) to quantify the contributions of various agronomic traits to the variation in grain yield. A plausible reason for this was that the emphasis of the breeding program was more on improvement in drought tolerance rather than performance of cultivars under rainfed environments.…”

“…These include, among others, an increase in the size of the IITA maize breeding program to facilitate the use of higher selection intensity and an increase in the precision of selection to achieve higher heritability. An important observation from the findings of several researchers (Badu-Apraku et al, 2011Talabi et al, 2017) is that EASP is a key trait accounting for the variation observed in grain yield under diverse stress conditions. In the present study, the increased grain yields under drought and rainfed environments were associated with prolonged DA and DS, increases in EHT and PHT, and improvement in SL resistance, EASP, and PASP.…”

“…SPSS (SPSS, 2007) was used for the stepwise regression analyses to obtain information on the path coefficients and the causal relationships required for the path diagrams. Following the method proposed by Mohammadi et al (2003), the predictor traits were organized into first, second, and third order, based on their contributions to the total variation in grain yield, with minimized multicolinearity (Badu-Apraku et al, 2014;Talabi et al, 2017). To perform the stepwise regression analysis, grain yield was regressed on measured traits to identify traits with significant contributions to the total variation in grain yield at P £ 0.05, which were categorized as first-order traits.…”