Maize is grown by millions of smallholder farmers in South Asia (SA) under diverse environments. The crop is grown in different seasons in a year with varying exposure to weather extremes, including high temperatures at critical growth stages which are expected to increase with climate change. This study assesses the impact of current and future heat stress on maize and the benefit of heat-tolerant varieties in SA. Annual mean maximum temperatures may increase by 1.4-1.8°C in 2030 and 2.1-2.6°C in 2050, with large monthly, seasonal, and spatial variations across SA. The extent of heat stressed areas in SA could increase by up to 12 % in 2030 and 21 % in 2050 relative to the baseline. The impact of heat stress and the benefit from heat-tolerant varieties vary with the level of temperature increase and planting season. At a regional scale, climate change would reduce rainfed maize yield by an average of 3.3-6.4 % in 2030 and 5.2-12.2 % in 2050 and irrigated yield by 3-8 % in 2030 and 5-14 % in 2050 if current varieties were grown under the future climate. Under projected climate, heat-tolerant varieties could minimize yield loss (relative to current maize varieties) by up to 36 and 93 % in 2030 and 33 and 86 % in 2050 under rainfed and irrigated conditions, respectively. Heat-tolerant maize varieties, therefore, have the potential to shield maize farmers from severe yield loss due to heat stress and help them adapt to climate change impacts.
An association mapping panel, named as CIMMYT Asia association mapping (CAAM) panel, involving 396 diverse tropical maize lines were phenotyped for various structural and functional traits of roots under drought and well-watered conditions. The experiment was conducted during Kharif (summer-rainy) season of 2012 and 2013 in root phenotyping facility at CIMMYT-Hyderabad, India. The CAAM panel was genotyped to generate 955, 690 SNPs through GBS v2.7 using Illumina Hi-seq 2000/2500 at Institute for Genomic Diversity, Cornell University, Ithaca, NY, USA. GWAS analysis was carried out using 331,390 SNPs filtered from the entire set of SNPs revealed a total of 50 and 67 SNPs significantly associated for root functional (transpiration efficiency, flowering period water use) and structural traits (rooting depth, root dry weight, root length, root volume, root surface area and root length density), respectively. In addition to this, 37 SNPs were identified for grain yield and shoot biomass under well-watered and drought stress. Though many SNPs were found to have significant association with the traits under study, SNPs that were common for more than one trait were discussed in detail. A total 18 SNPs were found to have common association with more than one trait, out of which 12 SNPs were found within or near the various gene functional regions. In this study we attempted to identify the trait specific maize lines based on the presence of favorable alleles for the SNPs associated with multiple traits. Two SNPs S3_128533512 and S7_151238865 were associated with transpiration efficiency, shoot biomass and grain yield under well-watered condition. Based on favorable allele for these SNPs seven inbred lines were identified. Similarly, four lines were identified for transpiration efficiency and shoot biomass under drought stress based on the presence of favorable allele for the common SNPs S1_211520521, S2_20017716, S3_57210184 and S7_130878458 and three lines were identified for flowering period water-use, transpiration efficiency, root dry weight and root volume based on the presence of favorable allele for the common SNPs S3_162065732 and S3_225760139.
Heat stress resilience has emerged as an important trait in maize hybrids targeted for post–monsoon spring cultivation in large parts of South Asia and many other parts of the tropics. Selection based on grain yield alone under heat stress is often misleading, and therefore an approach involving stress-adaptive secondary traits along with grain yield could help in the development of improved, stable heat stress tolerant cultivars. We attempted to identify reliable and effective secondary traits associated with heat stress tolerance in tropical maize and sources of heat stress tolerant germplasm. A panel of 99 elite maize inbred lines representing the wider genetic diversity of tropical maize and a set of 58 elite hybrids were phenotyped under natural heat stress and optimal temperature for grain yield and 15 secondary traits including 10 morpho-physiological traits and 5 yield attributes. Evaluation under natural heat stress was done during the spring season by adjusting the planting date so that the complete reproductive stage (from tassel emergence to late grain filling) was exposed to heat stress. The optimal temperature trial was planted during the monsoon season with no exposure to heat stress at any crop stage. Heat stress significantly affected most of the observed traits. Among the traits studied two yield attributing traits, i.e.- ears per plant (EPP) and kernel per row (KPR), and three morpho-physiological traits, i.e.- chlorophyll content (CC), leaf firing (LF) and tassel blast (TB) were found to be the key secondary traits associated with grain yield under heat stress. In addition, low anthesis-silking internal (ASI) is an important trait that needs to be added in the index selection for heat stress tolerance. The study identified nine promising heat stress tolerant maize inbred lines with desirable secondary traits and grain yield under severe heat stress, which could be used as source germplasm in heat stress tolerance maize breeding program.
With progressive climate change and the associated increase in mean temperature, heat stress tolerance has emerged as one of the key traits in the product profile of the maize breeding pipeline for lowland tropics. The present study aims to identify the genomic regions associated with heat stress tolerance in tropical maize. An association mapping panel, called the heat tolerant association mapping (HTAM) panel, was constituted by involving a total of 543 tropical maize inbred lines from diverse genetic backgrounds, test-crossed and phenotyped across nine locations in South Asia under natural heat stress. The panel was genotyped using a genotyping-by-sequencing (GBS) platform. Considering the large variations in vapor pressure deficit (VPD) at high temperature (Tmax) across different phenotyping locations, genome-wide association study (GWAS) was conducted separately for each location. The individual location GWAS identified a total of 269 novel significant single nucleotide polymorphisms (SNPs) for grain yield under heat stress at a p value of < 10–5. A total of 175 SNPs were found in 140 unique gene models implicated in various biological pathway responses to different abiotic stresses. Haplotype trend regression (HTR) analysis of the significant SNPs identified 26 haplotype blocks and 96 single SNP variants significant across one to five locations. The genomic regions identified based on GWAS and HTR analysis considering genomic region x environment interactions are useful for breeding efforts aimed at developing heat stress resilient maize cultivars for current and future climatic conditions through marker-assisted introgression into elite genetic backgrounds and/or genome-wide selection.
Spring maize area has emerged as a niche market in South Asia. Production of maize during this post-rainy season is often challenged due to heat stress. Therefore, incorporating heat stress resilience is an important trait for incorporation in maize hybrids selected for deployment in this season. However, due to the significant genotype × environment interaction (GEI) effects under heat stress, the major challenge lies in identifying maize genotypes with improved stable performance across locations and years. In the present study, we attempted to identify the key weather variables responsible for significant GEI effects, and identify maize hybrids with stable performance under heat stress across locations/years. The study details the evaluation of a set of prereleased advanced maize hybrids across heat stress vulnerable locations in South Asia during the spring seasons of 2015, 2016 and 2017. Using factorial regression, we identified that relative humidity (RH) and vapor pressure deficit (VPD) as the two most important environmental covariates contributing to the large GEI observed on grain yield under heat stress. The study also identified reproductive stage, starting from tassel emergence to early grain-filling stage, as the most critical crop stage highly susceptible to heat stress. Across-site/year evaluation resulted in identification of six high yielding heat stress resilient hybrids.
Rapid cycle genomic selection (RC-GS) helps to shorten the breeding cycle and reduce the costs of phenotyping, thereby increasing genetic gains in terms of both cost and time. We implemented RC-GS on two multi-parent yellow synthetic (MYS) populations constituted by intermating ten elite lines involved in each population, including four each of drought and waterlogging tolerant donors and two commercial lines, with proven commercial value. Cycle 1 (C 1) was constituted based on phenotypic selection and intermating of the top 5% of 500 S 2 families derived from each MYS population, test-crossed and evaluated across moisture regimes. C 1 was advanced to the next two cycles (C 2 and C 3) by intermating the top 5% selected individuals with high genomic estimated breeding values (GEBVs) for grain yield under drought and waterlogging stress. To estimate genetic gains, population bulks from each cycle were test-crossed and evaluated across locations under different moisture regimes. Results indicated that the realised genetic gain under drought stress was 0.110 t ha −1 yr −1 and 0.135 t ha −1 yr −1 , respectively, for MYS-1 and MYS-2. The gain was less under waterlogging stress, where MYS-1 showed 0.038 t ha −1 yr −1 and MYS-2 reached 0.113 t ha −1 yr −1. Genomic selection for drought and waterlogging tolerance resulted in no yield penalty under optimal moisture conditions. The genetic diversity of the two populations did not change significantly after two cycles of GS, suggesting that RC-GS can be an effective breeding strategy to achieve high genetic gains without losing genetic diversity.
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