Performance assessment of wheat genotypes based on the superiority index using additive main and multiplicative interaction effects and BLUP analysis

The simultaneous use of additive main and multiplicative interaction effects (AMMI) and best linear unbiased predictors (BLUP) has been reflected in the multi-location evaluation of trials for number of crops. The additional advantages of both these approaches would be combined in superiority index (SI) to have an edge over the commonly used approaches. The promising wheat genotypes had been considered under multi location trails in Peninsular zone of India during the cropping seasons of 2018-2019 and 2019-2020. The highly significant environmental effects contributed 44.1% & 35.3% of total sum of squares in the AMMI analysis, 20.6% & 26.2% were augmented by G × E interaction, while 10.8% & 7.5% were contributed by the genotypes.Wheat genotypes of UAS3001, MACS6222, GW322, and DDW48 expressed their superiority in BLUP values. Superiority indexes and adaptability measures had identified WHD964 and DDW48 genotypes for the second year of study. More than 75% variations among the considered measures were due to the first two interaction principal components (IPCA’s) under Biplot analysis. Number of superiority index measures were clustered with adaptability measures in the same quadrant. Superiority index, the weighted measure of yield and consistent performance of genotypes would be more appropriate for stability and adaptabilities studies

Wheat Production in India: Trends and Prospects

Trends in Indian wheat production before and after the inception of the All India Coordinated Research Project (AICRP) on wheat have been analyzed to show its significant progress over the years. A brief intercountry comparison of productivity, production and area coupled with regional comparison within India has been attempted to give an idea about the contribution of country and regions, respectively, for global and national food security. The milestones in Indian wheat programme and research outcomes were highlighted post-AICRP along with the vision and strategies set for 2050 against diverse production challenges. Regional disparities, zone-wise production constraints and research programmes for achieving the set production target were briefed. The chapter concludes with possible interventions in strengthening the complete wheat value chain for ensuring food security for the future generation

Evaluation of biofortified spring wheat genotypes for yield and micronutrients

Advanced wheat genotypes were tested for agronomic as well as grain iron and zinc content traits. The analysis of variance indicated variation for all traits except iron (Fe) and zinc (Zn). The grain Fe content ranged from 39-58 mg/kg whereas grain Zn ranged from 32-47 mg/kg among the tested lines. A significant positive correlation (0.45) was observed between grain Fe and Zn content. There was no association between yield and grain Fe and Zn content indicating that improvement in these micronutrients will not have any undesirable affect on yield. The data was further analysed for principal component analysis and genotype by trait association. The first five principal components viz., PC1 (0.3149), PC2 (0.2198), PC3 (0.1461), PC4 (0.10) and PC5 (0.0923) accounted for 0.87 of the total variation. The major traits contributing to the PC1 are days to heading, days to maturity, grain iron content and yield. The cluster analysis revealed significant variation among the tested germplasm thus providing opportunities for increasing the micronutrient content along with yield through hybridization with high micronutrient content lines

Parametric and Non Parametric measures to compare Fixed and random effects of malt barley genotypes

AMMI analysis of 21 malt barley genotypes evaluated at nine locations of north western plains zone revealed highly significant variation due to environments (61.8%), G x E interactions (19.5%) and genotypes (8.2%). Further, interaction effects were partitioned into seven interactions principal components. AMMI stability Value measures (ASV1 and ASV) had considered first two interaction principal components and based on 54.1% of total interaction variations had recommended (PL926, PL931, RD2849) and (BH1036, PL931, RD2849) malt barley genotypes respectively. Modified AMMI Stability Values measures (MASV1 and MASV) had exploited nearly 97.6% of total interaction variations, based on which BH1036, DWRB219, RD2849 and BH1036, DWRB219, PL926 malt barley genotypes were identified for stable yield performance. Geometric Mean (GM) based on BLUP effects of genotypes yield was in favour of DWRB219, BH1036 and DWRB221 while corresponding to Harmonic Mean of yield values, DWRB219, BH1036, DWRB221 genotypes would be of choice. Relative Performance of Genotypic Values (RPGV) favored DWRB219, BH1036 , DWRB221 barley genotypes and Harmonic Mean of Relative Performance of Genotypic Value (HMRPGV) measure favoured DWRB219, BH1036, DWRB220 malt genotypes. Non parametric composite measure, NPi (1) , suggested that UPB1097, RD3029, DWRB218 were suitable, whereas DWRB219, RD3029, G4 genotypes would be preferable as per values NPi (2) while NPi (3) identified DWRB219, BH1036, DWRB160. The composite measure NPi (4) found DWRB219, BH1036, DWRB160 as genotypes of choice for this zone. Measures MASV, MASV1, Si 1, Si 3, Si 4, Si 5,Si 6 ,Si 7, Si 2, NPi (1), ASV and ASV1 accounted more in first principal component, whereas NPi (2), NPi (3), NPi (4), Average, GM, HM, Mean, PRVG, HMPRVG were major contributors for second principal component. Small cluster of standard deviation (Stdev) with CV, IPC4 and IPC7 were placed in second quadrant. Smallest cluster of IPC1 and IPC6 was also observed in this quadrant. Large cluster comprised of NPi (1), Si 2 ,Si 5 Si 2 ,Si 5 ,Si 6 with ASV and ASV1. Measures GM, HM, PRVG and HMPRVG considered random effects of genotypes grouped with average and placed in last quadrant while adjacent cluster of NPi (2), NPi (3), and NPi (4) observed in same quadrant. Close association among the AMMI analysis based measures had been observed with adaptability measures based on BLUP effects of malt barley genotypes in the present study based on the Biplot analysis while considering first two principal components

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

Ensuring nutritional security in India through wheat biofortification: A review

Undernourishment of nutrients, also known as hidden hunger, affects over 2 billion populace globally. Even though stunting among children below five years of age has decreased in India in the last ten years, India is home to roughly thirty percent of the world's population of stunted pre-schoolers. A significant improvement has been witnessed in the targeted development and deployment of biofortified crops; approximately 20 million farm households from developing counties benefit from cultivating and consuming biofortified crops. There is ample scope for including biofortified varieties in the seed chain, ensuring nutritional security. Wheat is a dietary staple in India, typically consumed as wholemeal flour in the form of flatbreads such as chapatti and roti. Wheat contributes to nearly one fifth of global energy requirements and can also provide better amounts of iron (Fe) and zinc (Zn). As a result, biofortified wheat can serve as a medium for delivery of essential micronutrients such as Fe and Zn to end users. This review discusses wheat biofortification components such as Fe and Zn dynamics, its uptake and movement in plants, the genetics of their buildup, and the inclusion of biofortified wheat varieties in the seed multiplication chain concerning India

Phylogeography and Population Structure Analysis Reveal Diversity by Gene Flow and Mutation in Ustilago segetum (Pers.) Roussel tritici Causing Loose Smut of Wheat

Ustilago segetum (Pers.) Roussel tritici (UST) causes loose smut of wheat account for considerable grain yield losses globally. For effective management, knowledge of its genetic variability and population structure is a prerequisite. In this study, UST isolates sampled from four different wheat growing zones of India were analyzed using the second largest subunit of the RNA polymerase II (RPB2) and a set of sixteen neutral simple sequence repeats (SSRs) markers. Among the 112 UST isolates genotyped, 98 haplotypes were identified. All the isolates were categorized into two groups (K = 2), each consisting of isolates from different sampling sites, on the basis of unweighted paired-grouping method with arithmetic averages (UPGMA) and the Bayesian analysis of population structure. The positive and significant index of association (IA = 1.169) and standardized index of association (rBarD = 0.075) indicate population is of non-random mating type. Analysis of molecular variance showed that the highest variance component is among isolates (91%), with significantly low genetic differentiation variation among regions (8%) (Fst = 0.012). Recombination (Rm = 0) was not detected. The results showed that UST isolates have a clonal genetic structure with limited genetic differentiation and human arbitrated gene flow and mutations are the prime evolutionary processes determining its genetic structure. These findings will be helpful in devising management strategy especially for selection and breeding of resistant wheat cultivars

Genetic diversity and population structure analyses in barley (Hordeum vulgare) against corn-leaf aphid, Rhopalosiphum maidis (Fitch)

Corn-leaf aphid (CLA), Rhopalosiphum maidis (Fitch) (Hemiptera: Aphididae) is a serious economic pest of barley worldwide. Breeding for aphid resistance in plants is considered a cost-effective and environmentally safe approach for aphid control, compared to the use of chemical pesticides. One of the challenges in breeding for aphid resistance is the identification of resistant plant genotypes, which can be achieved through the use of molecular markers. In the present study, a set of aphid specific 10 simple-sequence repeats (SSR) markers were used to investigate genetic diversity and population structure analyses in 109 barley genotypes against R. maidis. Three statistical methods viz., multivariate hierarchical clustering based on Jaccard’s similarity coefficient, principal coordinate analysis (PCoA) and the Bayesian approach were utilized to classify the 109 barley genotypes. The analyses revealed four subpopulations i.e., SubPop1, SubPop2, SubPop3 and SubPop4 with 19, 46, 20 and 24 genotypes including admixtures, respectively and represented 17.43%, 42.2%, 18.34% and 22.01% genotypes of the total population size, respectively. The studied SSR markers produced 67 polymorphic bands, with an average of 6.7 and ranging from 3 to 12 bands. Heterozygosity (H) was found to be highest in SSR28 (0.64) and lowest in SSR27 (0.89). The observed genetic diversity index varied from 0.10 to 0.34 (with an average of 0.19). Major allele frequency varied from 74.08% to 94.80%. On an average, 87.52% of the 109 barley genotypes shared a common major allele at any locus. Based on the Aphid Infestation Index (AII), only 2 genotypes were found to be resistant against CLA. SubPop2 also had lowest mean aphid population (28.83), widest genetic similarity index (0.60-1.00) and highest genetic similarity coefficient (0.82), which highlighted its potential for inclusion in future CLA resistance breeding programs

Marker-assisted backcross breeding for heat tolerance in bread wheat (Triticum aestivum L.)

Manipulation of flowering time for adaptation through natural or genetic approaches may combat heat-stress damage that occurs at the reproductive stages in production conditions. HD2733, a popular wheat variety of the eastern plains of India, is largely sensitive to heat stress. Therefore, the current study aims to improve heat tolerance of HD2733 by introgression of QTLs associated with early anthesis and high kernel weight linked to markers Xbarc186 and Xgwm190, respectively, through marker-assisted backcross breeding (MABB) from a tolerant donor, WH730. A total of 124 simple sequence repeat (SSR) markers distributed evenly across the genome were used for the background selection. The alleles of Xbarc186 and Xgwm190 were fixed in BC2F1 and BC1F2 generations by selecting individual plants heterozygous for both marker loci and backcrossed with HD2733 and simultaneously selfed to generate BC2F1 and BC1F2 populations, respectively. Furthermore, the selected BC1F2 were selfed to generate the BC1F4 population. By background screening, a total of 39 BC2F3 and 21 BC1F4 families homozygous for the targeted QTLs with 90.9–97.9% and 86.8–88.3% RPG recoveries were selected. The best performing 17 BC2F3 and 10 BC1F4 lines were evaluated for various morpho-physiological traits. Phenotypic evaluation and multi-location trials of the introgressed lines under late sown conditions led to the selection of three promising lines with early anthesis and higher grain yield. The improved lines will serve as an excellent genetic material for functional genomics and expression studies to understand the molecular mechanisms and pathways underlying the stress tolerance

Conservation agriculture based crop management practices impact diversity and population dynamics of the insect-pests and their natural enemies in agroecosystems

Human efforts to grow abundant food through the persistent use of resource-intensive farming practices have resulted in declining soil health, and deterioration of ecosystem functions and services. Conservation agriculture (CA) has emerged as a practice to minimize the impacts of conventional resource-exhaustive and energy-intensive agriculture. Minimum soil disturbance, permanent soil cover, and diversification are the key components of CA. Tillage through conventional practices on the other hand has detrimental effects on the soil and environment as it requires deep inversion of soil with instruments such as mouldboard plow, disc plow etc. leaving very less organic matter in soil after establishment of crop. Even though, CA advocates many benefits over conventional agriculture in terms of soil and water conservation, the consequent changes in moisture and temperature regimes due to reduced tillage and surface cover would likely going to influence the biological activity, including insect pests and their natural enemies which dwell within these agroecosystems. The changed crop conditions under CA may favor particular insect communities and their ecological niches. The adoption of such practices may lead to decrease in insect pests with major activity on the crop canopy. However, the activity of the insect pests that spend their maximum life span at the soil surface or beneath the soil surface may increase. Recent insect-pest outbreaks in North-Western India and imbalances reported in Indo-Gangetic Plains point to the need for a better understanding of the inter-relationships between tillage intensity, residue retention, and insect pest population dynamics. The current review analyzes the existing state of knowledge of these dynamics and presents the scenarios that may emerge as CA get more acceptance. This review will help to develop countermeasures to improve performance and ecosystem services of Conservation agriculture (CA) based cropping systems