Wheat occupies a special role in global food security since, in addition to providing 20% of our carbohydrates and protein, almost 25% of the global production is traded internationally. The importance of wheat for food security was recognised by the Chief Agricultural Scientists of the G20 group of countries when they endorsed the establishment of the Wheat Initiative in 2011. The Wheat Initiative was tasked with supporting the wheat research community by facilitating collaboration, information and resource sharing and helping to build the capacity to address challenges facing production in an increasingly variable environment. Many countries invest in wheat research. Innovations in wheat breeding and agronomy have delivered enormous gains over the past few decades, with the average global yield increasing from just over 1 tonne per hectare in the early 1960s to around 3.5 tonnes in the past decade. These gains are threatened by climate change, the rapidly rising financial and environmental costs of fertilizer, and pesticides, combined with declines in water availability for irrigation in many regions. The international wheat research community has worked to identify major opportunities to help ensure that global wheat production can meet demand. The outcomes of these discussions are presented in this paper.

Nitrogen (N) is one of the primary macronutrients required for crop growth and yield. This nutrient is especially limiting wheat yields in the dry and low fertile agro-ecologies having low N in the root zone soil strata. Moreover, majority of farmers in India and South Asia are small to marginal with meagre capacity to invest in costly nitrogen fertilizers. Therefore, there is an immense need to identify lines that use nitrogen efficiently. A set of 50 diverse wheat genotypes consisting of indigenous germplasm lines (05), cultivars released for commercial cultivation (23) and selected elite lines from CIMMYT nurseries (22) were evaluated in an alpha-lattice design with two replications, a six-rowed plot of 2.5m length for 24 agro morphological, physiological and NUE related traits during two consecutive crop seasons in an N-depleted precision field under two different N levels of 50%-N50 (T1) and 100%-N100 (T2) of recommended N, i.e., 100 kg/ha. Analysis of variance revealed significant genetic variation among genotypes for all the traits studied. About 11.36% yield reduction was observed at reduced N levels. Significant correlations among NUE traits and yield component traits were observed which indicated pivotal role of N remobilization to the grain in enhancing yield levels. Among N-insensitive genotypes identified based on their yielding ability at low N levels, UASBW13356, UASBW13358, UASBW13354, UASBW13357 and KRL1-4 showed their inherent genotypic plasticity toward N application. The genotypes with more yield and high to moderate NUtE can be used as parents for the breeding of N efficient genotypes for marginal agro-ecologies. Low N tolerant genotypes identified from the current investigation may be further utilized in the identification of genomic regions responsible for NUE and its deployment in wheat breeding programs. The comprehensive data of 24 traits under different nitrogen levels for diverse genotypes from India and global sources (mainly CIMMYT) should be useful for supporting breeding for NUE and thus will be of great help for small and marginal farmers in India and South Asia.

Bipolaris sorokiniana is a fungal pathogen that infects wheat, barley, and other crops, causing spot blotch disease. The disease is most common in humid, warm, wheat-growing regions, with South Asia’s Eastern Gangetic Plains serving as a hotspot. There is very little information known about its genetic variability, demography, and divergence period. The current work is the first to study the phylogeographic patterns of B. sorokiniana isolates obtained from various wheat and barley-growing regions throughout the world, with the goal of elucidating the demographic history and estimating divergence times. In this study, 162 ITS sequences, 18 GAPDH sequences, and 74 TEF-1α sequences from B. sorokiniana obtained from the GenBank, including 21 ITS sequences produced in this study, were used to analyse the phylogeographic pattern of distribution and evolution of B. sorokiniana infecting wheat and barley. The degrees of differentiation among B. sorokiniana sequences from eighteen countries imply the presence of a broad and geographically undifferentiated global population. The study provided forty haplotypes. The H_1 haplotype was identified to be the ancestral haplotype, followed by H_29 and H_27, with H_1 occupying a central position in the median-joining network and being shared by several populations from different continents. The phylogeographic patterns of species based on multi-gene analysis, as well as the predominance of a single haplotype, suggested that human-mediated dispersal may have played a significant role in shaping this pathogen’s population. According to divergence time analysis, haplogroups began at the Plio/Pleistocene boundary.

Genetic variability in rice breeding programs plays a very crucial role. It provides an outstanding pool of superior alleles governing better agronomic and quality characters through association mapping. For a greater understanding of population structure, the genetic relationship among different rice lines is indispensable prior to the setting of a correlation among dynamic alleles and traits. In the present investigation, the genetic diversity and population structure of 116 rice accessions were studied to understand genetic relatedness and diversity among them using 64 polymorphic SSR markers. A genotyping assessment based on SSR markers revealed a total of 225 alleles, with an average PIC value of 0.755. The germplasm lines were classified into three distinct subgroups through population structure analysis, utilizing both model- and distance-based approaches. AMOVA analysis showed that 11% of the total variation could be attributed to differences between groups, while the remaining 89% was likely due to differences within groups. This study suggested that population structure and genetic relatedness should be considered to establish marker–trait associations for association mapping when working with the core collection of germplasm lines.