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Wheat (Triticum aestivum L.) is known to be negatively affected by heat stress, and its production is threatened by global warming, particularly in arid regions. Thus, efforts to better understand the molecular responses of wheat to heat stress are required. In the present study, Fourier transform infrared (FTIR) spectroscopy, coupled with chemometrics, was applied to develop a protocol that monitors chemical changes in common wheat under heat stress. Wheat plants at the three-leaf stage were subjected to heat stress at a 42 °C daily maximum temperature for 3 days, and this led to delayed growth in comparison to that of the control. Measurement of FTIR spectra and their principal component analysis showed partially overlapping features between heat-stressed and control leaves. In contrast, supervised machine learning through linear discriminant analysis (LDA) of the spectra demonstrated clear discrimination of heat-stressed leaves from the controls. Analysis of LDA loading suggested that several wavenumbers in the fingerprinting region (400–1800 cm−1) contributed significantly to their discrimination. Novel spectrum-based biomarkers were developed using these discriminative wavenumbers that enabled the successful diagnosis of heat-stressed leaves. Overall, these observations demonstrate the versatility of FTIR-based chemical fingerprints for use in heat-stress profiling in wheat. [ABSTRACT FROM AUTHOR]

Abstract: Drought and salinity are the primary factors limiting wheat production worldwide. It has been shown that a rice stress-responsive transcription factor encoded by the rice NAC1 gene (SNAC1) plays an important role in drought stress tolerance. Therefore, we introduced the SNAC1 gene under the control of a maize ubiquitin promoter into an elite Chinese wheat variety Yangmai12. Plants expressing SNAC1 displayed significantly enhanced tolerance to drought and salinity in multiple generations, and contained higher levels of water and chlorophyll in their leaves, as compared to wild type. In addition, the fresh and dry weights of the roots of these plants were also increased, and the plants had increased sensitivities to abscisic acid (ABA), which inhibited root and shoot growth. Furthermore, quantitative real-time polymerase chain reactions revealed that the expressions of genes involved in abiotic stress/ABA signaling, such as wheat 1-phosphatidylinositol-3-phosphate-5-kinase, sucrose phosphate synthase, type 2C protein phosphatases and regulatory components of ABA receptor, were effectively regulated by the alien SNAC1 gene. These results indicated high and functional expression of the rice SNAC1 gene in wheat. And our study provided a promising approach to improve the tolerances of wheat cultivars to drought and salinity through genetic engineering. [Copyright &y& Elsevier]

Developing climate-resilient crop varieties with better performance under variable environments is essential to ensure food security in a changing climate. This process is significantly influenced, among other factors, by genotype × environment (G × E) interactions. With the objective of identifying high-yielding and stable genotypes, 20 elite durum wheat lines were evaluated in 24 environments (location–season combination) during 5 crop seasons (2010/11–2014/15). The REML (residual maximum likelihood)-predicted means of grain yield of 16 genotypes that were common across all environments ranged from 3522 kg/ha in G201 to 4132 kg/ha in G217. Results of additive main effect and multiplicative interaction (AMMI) analysis showed that genotypes (G), environments (E), and genotype × environment interaction (GEI) significantly affected grain yield. From the total sum of squares due to treatments (G + E + GEI), E attributed the highest proportion of the variation (90.0%), followed by GEI (8.7%) and G (1.3%). Based on the first four AMMI selections for grain yield in the 24 environments, genotypes G217, G219, G211, and G213 were selected in 23, 12, 11, and 9 environments, respectively. The genotype and genotype × environment biplot (GGE) biplot polygon view showed that the environments were separated into three mega-environments. The winning genotypes in these mega-environments were G217, G214, and G204. Genotypes G212, G220, G217, G215, and G213 showed low AMMI stability values (ASV), whereas genotypes G217, G220, G212, G211, and G219 showed low genotype selection index (GSI), indicating their better stability and adaptability to the test environments. The results indicated that genotypes G217, G219, G211, G213, and G220 combined both high grain yield and stability/adaptability under dry but irrigated and heat-prone environments. An in-depth analysis of the superior genotypes could help better understand the stress-adaptive traits that could be targeted to further increase durum wheat yield and stability under the changing climate. [ABSTRACT FROM AUTHOR]