Characterising variation in wheat traits under hostile soil conditions in India

Intensive crop breeding has increased wheat yields and production in India. Wheat improvement in India typically involves selecting yield and component traits under non-hostile soil conditions at regional scales. The aim of this study is to quantify G*E interactions on yield and component traits to further explore site-specific trait selection for hostile soils. Field experiments were conducted at six sites (pH range 4.5-9.5) in 2013-14 and 2014-15, in three agro-climatic regions of India. At each site, yield and component traits were measured on 36 genotypes, representing elite varieties from a wide genetic background developed for different regions. Mean grain yields ranged from 1.0 to 5.5 t ha⁻¹ at hostile and non-hostile sites, respectively. Site (E) had the largest effect on yield and component traits, however, interactions between genotype and site (G*E) affected most traits to a greater extent than genotype alone. Within each agro-climatic region, yield and component traits correlated positively between hostile and non-hostile sites. However, some genotypes performed better under hostile soils, with site-specific relationships between yield and component traits, which supports the value of ongoing site-specific selection activities

Novel sources of variation in grain yield, components and mineral traits identified in wheat amphidiploids derived from thinopyrum bessarabicum (Savul. & rayss) Á. löve (poaceae) under saline soils in India

© 2020 by the authors. Licensee MDPI, Basel, Switzerland. Salt-affected soils constrain wheat production globally. A wild wheat species, Thinopyrum bessarabicum (Savul. & Rayss) Á. Löve (Poaceae), and its derivatives are tolerant of high external NaCl concentrations but have not been tested yet in field conditions. The aim of this study was to study the performance of amphidiploids derived from T. bessarabicum for grain yield (GYD), yield components and grain mineral composition traits under normal and saline soil conditions. Field experiments were conducted at Karnal (pH(water) = 7.3) and Hisar (pH(water) = 8.3) sites in 2014–2015 and 2015–2016 in India. Grain samples were analysed using inductively coupled plasma–mass spectrometry (ICP-MS). Yield and yield component traits of amphidiploids were typically greater at Karnal than Hisar. The GYD was greater at Karnal (1.6 t ha−1) than Hisar (1.2 t ha−1) in 2014–2015. However, GYD was greater at Hisar (1.7 t ha−1) than Karnal (1.1 t ha−1) in 2015–2016. Mean grain zinc (Zn) concentration of eight amphidiploids, averaged across sites and years, varied from 36 to 43 mg kg−1. Some amphidiploids derived from T. bessarabicum showed greater GYD and grain Zn concentration under saline soils (Hisar) than normal soils (Karnal). These might be potential new sources for the development of salt-tolerant wheat varieties with increased grain Zn concentration under salt-affected soils

Identification of wheat cultivars for low nitrogen tolerance using multivariable screening approaches

© 2020 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/). A set of thirty-six wheat cultivars were grown for two consecutive years under low and high nitrogen conditions. The interactions of cultivars with different environmental factors were shown to be highly significant for most of the studied traits, suggesting the presence of wider genetic variability which may be utilized for the genetic improvement of desired trait(s). Three cultivars, i.e., RAJ 4037, DBW 39 and GW 322, were selected based on three selection indices, i.e., tolerance index (TOL), stress susceptibility index (SSI), and yield stability index (YSI), while two cultivars, HD 2967 and MACS 6478, were selected based on all four selection indices which were common in both of the study years. According to Kendall’s concordance coefficient, the consistency of geometric mean productivity (GMP) was found to be highest (0.778), followed by YSI (0.556), SSI (0.472), and TOL (0.200). Due to the high consistency of GMP followed by YSI and SSI, the three selection indices could be utilized as a selection tool in the identification of high-yielding genotypes under low nitrogen conditions. The GMP and YSI selection indices had a positive and significant correlation with grain yield, whereas TOL and SSI exhibited a significant but negative correlation with grain yield under both high and low nitrogen conditions in both years. The common tolerant genotypes identified through different selection indices could be utilized as potential donors in active breeding programs to incorporate the low nitrogen tolerant genes to develop high-yielding wheat varieties for low nitrogen conditions. The study also helps in understanding the physiological basis of tolerance in high-yielding wheat genotypes under low nitrogen conditions

Variation in grain Zn concentration, and the grain ionome, in field-grown Indian wheat

Wheat is an important dietary source of zinc (Zn) and other mineral elements in many countries. Dietary Zn deficiency is widespread, especially in developing countries, and breeding (genetic biofortification) through the HarvestPlus programme has recently started to deliver new wheat varieties to help alleviate this problem in South Asia. To better understand the potential of wheat to alleviate dietary Zn deficiency, this study aimed to characterise the baseline effects of genotype (G), site (E), and genotype by site interactions (GxE) on grain Zn concentration under a wide range of soil conditions in India. Field experiments were conducted on a diverse panel of 36 Indian-adapted wheat genotypes, grown on a range of soil types (pH range 4.5–9.5), in 2013–14 (five sites) and 2014–15 (six sites). Grain samples were analysed using inductively coupled plasma-mass spectrometry (ICP-MS). The mean grain Zn concentration of the genotypes ranged from 24.9–34.8 mg kg-1, averaged across site and year. Genotype and site effects were associated with 10% and 6% of the overall variation in grain Zn concentration, respectively. Whilst G x E interaction effects were evident across the panel, some genotypes had consistent rankings between sites and years. Grain Zn concentration correlated positively with grain concentrations of iron (Fe), sulphur (S), and eight other elements, but did not correlate negatively with grain yield, i.e. no yield dilution was observed. Despite a relatively small contribution of genotype to the overall variation in grain Zn concentration, due to experiments being conducted across many contrasting sites and two years, our data are consistent with reports that biofortifying wheat through breeding is likely to be effective at scale given that some genotypes performed consistently across diverse soil types. Notably, all soils in this study were probably Zn deficient and interactions between wheat genotypes and soil Zn availability/management (e.g. the use of Zn-containing fertilisers) need to be better-understood to improve Zn supply in food systems

Assessment of terminal heat tolerance based on agro-morphological and stress selection indices in wheat

A study was conducted to quantify the effects of terminal heat stress on yield and component traits for two consecutive years under normal and late sown environments. Analysis of variance indicated significant differences among genotypes for most of the studied traits. Tiller/meter (T/M) and grain yield were the most affected traits (>30% reduction), whereas traits like grain filling rate (GFR), grain number per spike (GNPS) and thousand kernel weight (TKW) were less affected (<15%) under heat stress. The traits, viz. GFR, GNPS, TKW, T/M and spike weight, as well as the relative change in these traits exhibited positive and significant correlation with yield and yield stability index (YSI), while negative and significant correlation with heat susceptibility index (HSI) and kernel weight reduction percentage (KWR) under heat stress. Based on HSI, KWR, and YSI indices, genotypes WH 1021, NW 1014 and NW 2036 were identified as the heat tolerant, while HD 3086, HD 2967 and HD 3059 were identified to be highly productive under both normal and heat stress environments based on STI and mean yield across the environments. The above selected genotypes also showed high mean performance for GFR and TKW under heat stress and could be used for breeding wheat genotypes for heat tolerance

High density digital recording

In bread wheat, QTL interval mapping was conducted for nine important drought responsive agronomic traits. For this purpose, a doubled haploid (DH) mapping population derived from Kukri/Excalibur was grown over three years at four separate locations in India, both under irrigated and rain-fed environments. Single locus analysis using composite interval mapping (CIM) allowed detection of 98 QTL, which included 66 QTL for nine individual agronomic traits and 32 QTL, which affected drought sensitivity index (DSI) for the same nine traits. Two-locus analysis allowed detection of 19 main effect QTL (M-QTL) for four traits (days to anthesis, days to maturity, grain filling duration and thousand grain weight) and 19 pairs of epistatic QTL (E-QTL) for two traits (days to anthesis and thousand grain weight). Eight QTL were common in single locus analysis and two locus analysis. These QTL (identified both in single- and two-locus analysis) were distributed on 20 different chromosomes (except 4D). Important genomic regions on chromosomes 5A and 7A were also identified (5A carried QTL for seven traits and 7A carried QTL for six traits). Marker-assisted recurrent selection (MARS) involving pyramiding of important QTL reported in the present study, together with important QTL reported earlier, may be used for improvement of drought tolerance in wheat. In future, more closely linked markers for the QTL reported here may be developed through fine mapping, and the candidate genes may be identified and used for developing a better understanding of the genetic basis of drought tolerance in wheat

Genomics

Not AvailableAn increase in the rate of crop improvement is essential for achieving sustained food production and other needs of ever-increasing population. Genomic selection (GS) is a potential breeding tool that has been successfully employed in animal breeding and is being incorporated into plant breeding. GS promises accelerated breeding cycles through a rapid selection of superior genotypes. Numerous empirical and simulation studies on GS and realized impacts on improvement in the crop yields are recently being reported. For a holistic understanding of the technology, we briefly discuss the concept of genetic gain, GS methodology, its current status, advantages of GS over other breeding methods, prediction models, and the factors controlling prediction accuracy in GS. Also, integration of speed breeding and other novel technologies viz. high throughput genotyping and phenotyping technologies for enhancing the efficiency and pace of GS, followed by its prospective applications in varietal development programs is reviewed

Grain concentrations of Zn and other mineral elements of Indian wheat.

<p>Data are in mg kg^-1, summarised across all plots (n = 719). Grain yield and yield components data are summarised across all plots (n = 864).</p

Plant available soil Zn (Ca(NO₃)₂-extractable) and grain Zn concentration at six sites in 2013–14 and 2014–15.

<p>Soil Zn data are means of three replicate soil samples of each depth at each site. Grain Zn data are mean of two replicate at Karnal, Hisar, Malda and one replicate at Kumarganj-reclaimed and Kumarganj-sodic sites in 2013–14 and two replicates at all six sites in 2014–15.</p

The correlation coefficients in grain ionome of a panel of 36 genotypes between 2013–14 and 2014–15.

<p>Data represent the means of two replicate plots per genotype at Karnal, Hisar and Malda, and one replicate per genotype at Kumarganj-reclaimed and Kumarganj-sodic sites in 2013–14, and the means of two replicate plots of each genotype at all six sites in 2014–15. Colour represents strength of correlation from strongly negative (dark blue) to strongly positive (dark red).</p