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The study was conducted to identify novel simple sequence repeat (SSR) markers associated with resistance to corn aphid (CLA), Rhopalosiphum maidis L. in 48 selected bread wheat (Triticum aestivum L.) and wild wheat (Aegilops spp. & T. dicoccoides) genotypes during two consecutive cropping seasons (2018–19 and 2019–20). A total of 51 polymorphic markers containing 143 alleles were used for the analysis. The frequency of the major allele ranged from 0.552 (Xgwm113) to 0.938 (Xcfd45, Xgwm194 and Xgwm526), with a mean of 0.731. Gene diversity ranged from 0.116 (Xgwm526) to 0.489 (Xgwm113), with a mean of 0.354. The polymorphic information content (PIC) value for the SSR markers ranged from 0.107 (Xgwm526) to 0.370 (Xgwm113) with a mean of 0.282. The results of the STRUCTURE analysis revealed the presence of four main subgroups in the populations. Analysis of molecular variance (AMOVA) showed that the between-group difference was around 37 per cent of the total variation contributed to the diversity by the whole germplasm, while 63 per cent of the variation was attributed between individuals within the group. A general linear model (GLM) was used to identify marker-trait associations, which detected a total of 23 and 27 significant new marker-trait associations (MTAs) at the p < 0.01 significance level during the 2018–19 and 2019–20 crop seasons, respectively. The findings of this study have important implications for the identification of molecular markers associated with CLA resistance. These markers can increase the accuracy and efficiency of aphid-resistant germplasm selection, ultimately facilitating the transfer of resistance traits to desirable wheat genotypes. [ABSTRACT FROM AUTHOR]

This study aimed to survey the long-term effects of fertilization practices on the functional diversity of the soil microbiota. A 60-year fertilization experiment with mineral fertilizers, farmyard manure and combined treatments was sampled in two consecutive years in maize (Zea mays L.) and wheat (Triticum aestivum L.). Soil chemical properties, plant growth and physiological parameters were measured. The MicroRespTM method was applied to assess the community level physiological profiles (CLPPs) of the rhizosphere soil, and the arbuscular mycorrhizal fungal (AMF) colonization of the roots was determined. Samples were taken in the early vegetative stages, at flowering, and at harvest in both years. The measured parameters were analysed using multifactorial ANOVA to determine treatment effects, crop-dependent differences, and seasonality. PCA analysis was performed on the data matrix to reveal more complex correspondences, and Pearson's product-moment correlation was used to confirm relationships between some of the measured soil and plant parameters. Fertilization treatments caused long-term changes in some biological parameters such as: MicroRespTM parameters, citrate utilization, total substrate-induced respiration value, and the ratio of utilization of amino acids and sugars. The rate of AMF colonization responded mainly to the plant nutrition status and the plant requirements, suggesting a plant-mediated effect in the case of mycorrhiza. Mineral nitrogen fertilization and soil acidification were found to be the main factors affecting the catabolic activity of soil microbiota, while AMF colonization responded to the balance of plant nutrition. [ABSTRACT FROM AUTHOR]

Ethiopia's economy is dominated by agriculture which is mainly rain-fed and subsistence. Climate change is expected to have an adverse impact particularly on crop production. Previous studies have shown large discrepancies in the magnitude and sometimes in the direction of the impact on crop production. We assessed the impact of climate change on growth and yield of maize and wheat in Ethiopia using a multi-crop model ensemble. The multi-model ensemble (n = 48) was set up using the agroecosystem modelling framework Expert-N. The framework is modular which facilitates combining different submodels for plant growth and soil processes. The multi-model ensemble was driven by climate change projections representing the mid of the century (2021–2050) from ten contrasting climate models downscaled to finer resolution. The contributions of different sources of uncertainty in crop yield prediction were quantified. The sensitivity of crop yield to elevated CO2, increased temperature, changes in precipitations and N fertilizer were also assessed. Our results indicate that grain yields were very sensitive to changes in [CO2], temperature and N fertilizer amounts where the responses were higher for wheat than maize. The response to change in precipitation was weak, which we attribute to the high water holding capacity of the soils due to high organic carbon contents at the study sites. This may provide the sufficient buffering capacity for extended time periods with low amounts of precipitation. Under the changing climate, wheat productivity will be a major challenge with a 36 to 40% reduction in grain yield by 2050 while the impact on maize was modest. A major part of the uncertainty in the projected impact could be attributed to differences in the crop growth models. A considerable fraction of the uncertainty could also be traced back to different soil water dynamics modeling approaches in the model ensemble, which is often ignored. Uncertainties varied among the studied crop species and cultivars as well. The study highlights significant impacts of climate change on wheat yield in Ethiopia whereby differences in crop growth models causes the large part of the uncertainties. [ABSTRACT FROM AUTHOR]

Transcription factors are regulatory proteins known to modulate gene expression. These are the critical component of signaling pathways and help in mitigating various developmental and stress responses. Among them, bZIP, BBR, and BZR transcription factor families are well known to play a crucial role in regulating growth, development, and defense responses. However, limited data is available on these transcription factors in Triticum aestivum. In this study, bZIP, BBR, and BZR sequences from Brachypodium distachyon, Oryza sativa, Oryza barthii, Oryza brachyantha, T. aestivum, Triticum urartu, Sorghum bicolor, Zea mays were retrieved, and dendrograms were constructed to analyze the evolutionary relatedness among them. The sequences clustered into one group indicated a degree of evolutionary correlation highlighting the common lineage of cereal grains. This analysis also exhibited that these genes were highly conserved among studied monocots emphasizing their common ancestry. Furthermore, these transcription factor genes were evaluated for envisaging conserved motifs, gene structure, and subcellular localization in T. aestivum. This comprehensive computational analysis has provided an insight into transcription factor evolution that can also be useful in developing approaches for future functional characterization of these genes in T. aestivum. Furthermore, the data generated can be beneficial in future for genetic manipulation of economically important plants. [ABSTRACT FROM AUTHOR]