Relationships among Traits of Tropical Early Maize Cultivars in Contrasting Environments

Abstract

Secondary traits can improve precision with which drought or low soil nitrogen (low‐N) tolerant maize (Zea mays L.) genotypes are identified, compared to measuring only grain yield under each stress. The objective of this study was to identify secondary traits for indirect selection for yield improvement under drought and/or low‐N. Two sets of experiments were conducted at four locations in Nigeria for 2 yr. In the first experiment, cultivars were evaluated under low (30 kg ha−1) and high (90 kg ha−1) N and drought and well‐watered environments in the second experiment. Most reliable traits for selection for yield under drought were ear aspect (EASP), plant aspect (PASP), anthesis‐silking interval (ASI), and number of ears per plant (EPP). Days to anthesis (DYA) and silking (DYS) were the most reliable under well‐watered environments. Under low‐N, most reliable traits were DYA, DYS, stay green characteristic (LDTH), ASI, plant height (PLHT), EPP, EASP, and PASP whereas PLHT, EPP, PASP, and EASP were most reliable traits under high‐N environments. The ASI, EPP, EASP, and PASP were identified as most reliable traits for simultaneous selection of drought and low‐N tolerant genotypes. Under drought, cultivars TZE‐Y DT STR C4, TZE‐W DT STR C4, and TZE Comp 3 DT C1F2 were outstanding and closest to the ideal cultivar. Seven cultivars were closest to the ideal under low‐N, two of which were among the three selected under drought stress. Faster progress in selecting for improved grain yield is possible using EPP, EASP, PASP, and ASI under either drought or low‐N.

Identification of early-maturing maize inbred lines based on multiple traits under drought and low N environments for hybrid development and population improvement

“…Important conditions for making valid conclusions from the 'mean-vs.-stability' view of the GGE biplots (Figs. 2,3 and 5,and 6) were that all traits should be presented in such a way that large values were more desirable, all traits were viewed as equally important, and were on one side of the average-trait-vector (Badu-Apraku et al 2011a). These requirements were all met in the present study.…”

“…Breeding and promotion of the adoption of maize germplasm with tolerance to low soil N is very important for increased maize production and productivity (Betra´n et al 2003) and for reducing input costs. In the farmer's field, drought, Striga and low soil nutrient deficiency do occur simultaneously, and when this happens the combined effect can be devastating (Cechin and Press 1993;Kim and Adetimirin 1997;Badu-Apraku et al 2011a). Therefore, maize varieties targeted to the Striga-prone areas of WCA must also be resistant or at least tolerant to drought and low N. Fortunately, improvement for drought tolerance also resulted in specific adaptation and improved performance under low N conditions, suggesting that tolerance to either stress involves common adaptive mechanism (Ba¨nziger et al 1999).…”

Comparative Performance of Early‐maturing Maize Cultivars Developed in Three Eras under Drought Stress and Well‐watered Environments in West Africa

“…Therefore, to preempt the possibility of making the populations unnecessarily earlier maturing, a restricted selection index consisting of high grain yield, EPP, early flowering, shorter ASI, and shorter plants was used in the breeding program to improve the populations for drought tolerance (Menkir and Akintunde, 2001;Badu-Apraku et al, 2011a, 2012a. Therefore, to preempt the possibility of making the populations unnecessarily earlier maturing, a restricted selection index consisting of high grain yield, EPP, early flowering, shorter ASI, and shorter plants was used in the breeding program to improve the populations for drought tolerance (Menkir and Akintunde, 2001;Badu-Apraku et al, 2011a, 2012a.…”

Genetic diversity in cultivated yam bean (Pachyrhizus spp.) evaluated through multivariate analysis of morphological and agronomic traits

“…Multivariate statistical analyses (MVA) will be advantageous in analyzing genetic diversity and classifying germplasm collections (Acquaah 2007;Mohammadi and Prasanna 2003). Recently, several studies have been conducted to assess the genetic diversity based on morphological traits and using multivariate procedures including principal component analysis (PCA) (Badu-Apraku et al 2011;Zeba and Isbat 2011;Hailu et al 2006), discriminant function analysis (DFA) (Francisco et al 2011;Safari et al 2008), multivariate analysis of variance (MANOVA) Ukalska et al 2006), and partial least squares (PLS) (Jaradat and Weyers 2011). MANOVA analyses differences among populations for a given trait, and the distinctiveness is studied with a number of vector variables combined (Acquaah 2007;Zhu 1990).…”