Gene-ecology of durum wheat HMW glutenin reflects their diffusion from the center of origin

Gliadin and glutenin genomes and their effects on the technological aspect of wheat-based products

Wheat is the most important crops worldwide, providing about one-fifth of the daily protein and calories for human consumption. The quality of cereal-based products is principally governed by the genetic basis of gluten (glutenin and gliadin proteins), which exists in a wide range of variable alleles and is controlled by clusters of genes. There are certain limitations associated with gluten characteristics, which can be genetically manipulated. The present review aimed to investigate the correlation between the genetic characteristics of gluten protein components and wheat-based product's quality. According to various references, Glu-B1d (6 + 8), Glu-B1h (14 + 15) and Glu-B1b (7 + 8) are related to higher gluten strength and pasta quality, while, subunits Dx2 + Dy12 and Dx5 + Dy10, are usually present at the Glu-D1 locus in bread wheat, resulted in lower cooked firmness in pasta. Moreover, introducing Gli-D1/Glu-D3 and Glu-D1 loci into durum wheat genomes, causing to provide the maximum values of gluten index in pasta products. 1Dx5 + 1Dy10 alleles determine the level of increase in dough's consistency, elasticity, viscosity, and extensibility quality of baking and appropriate bread loaf volume, while 1Dx2 + 1Dy12 as the alleles associated with poor baking quality, being more suitable for soft wheat/pastry end uses. Bx7, Bx7OE, 1Bx17 + 1By18, 1Bx13 + 1By16, Bx7 + By9 and 1Bx7 + 1By8 at Glu-B1alleles and 1Ax2* found on Glu-A1, augmented dough strength and has positive effects on consistency, extensibility, viscosity, and elasticity of bread dough. Breeding programs by genome editing have made gluten a promoting component for improving cereal-based products.

Molecular and genetic bases of heat stress responses in crop plants and breeding for increased resilience and productivity

To ensure the food security of future generations and to address the challenge of the 'no hunger zone' proposed by the FAO (Food and Agriculture Organization), crop production must be doubled by 2050, but environmental stresses are counteracting this goal. Heat stress in particular is affecting agricultural crops more frequently and more severely. Since the discovery of the physiological, molecular, and genetic bases of heat stress responses, cultivated plants have become the subject of intense research on how they may avoid or tolerate heat stress by either using natural genetic variation or creating new variation with DNA technologies, mutational breeding, or genome editing. This review reports current understanding of the genetic and molecular bases of heat stress in crops together with recent approaches to creating heat-tolerant varieties. Research is close to a breakthrough of global relevance, breeding plants fitter to face the biggest challenge of our time.

High-Throughput Genotype, Morphology, and Quality Traits Evaluation for the Assessment of Genetic Diversity of Wheat Landraces from Sicily

During the XX Century, the widespread use of modern wheat cultivars drastically reduced the cultivation of ancient landraces, which nowadays are confined to niche cultivation areas. Several durum wheat landraces adapted to the extreme environments of the Mediterranean region, are still being cultivated in Sicily, Italy. Detailed knowledge of the genetic diversity of this germplasm could lay the basis for their efficient management in breeding programs, for a wide-range range of traits. The aim of the present study was to characterize a collection of durum wheat landraces from Sicily, using single nucleotide polymorphisms (SNP) markers, together with agro-morphological, phenological and quality-related traits. Two modern cv. Simeto, Claudio, and the hexaploid landrace, Cuccitta, were used as outgroups. Cluster analysis and Principal Coordinates Analysis (PCoA) allowed us to identify four main clusters across the analyzed germplasm, among which a cluster included only historical and modern varieties. Likewise, structure analysis was able to distinguish the ancient varieties from the others, grouping the entries in seven cryptic genetic clusters. Furthermore, a Principal Component Analysis (PCA) was able to separate the modern testers from the ancient germplasm. This approach was useful to classify and evaluate Sicilian ancient wheat germplasm, supporting their safeguard and providing a genetic fingerprint that is necessary for avoiding commercial frauds to sustaining the economic profits of farmers resorting to landraces cultivation.

Can High Throughput Phenotyping Help Food Security in the Mediterranean Area?

According to the IPCC 2014 report the Mediterranean region will be affected by strong climatic changes, both in terms of average temperature and of precipitations regime. This area hosts some half a billion people and the impact on food production will be severe. To implement a climate smart agriculture paradigm and a sustainable increase of agricultural productivity different approaches can be deployed. Agriculture alone consumes 70% of the entire water available on the planet, thus the observed reduction of useful rainfall and growing costs for irrigation water may severely constrain food security. In our work we focused on two typical Mediterranean crops: durum wheat, a rainfed crop, and tomato, an irrigated one. In wheat we explored the possibility of identifying genotypes resilient to water stress for future breeding aims, while in tomato we explored the possibility of using biostimulants to increase the plant capacity of using water. In order to achieve these targets, we used high throughput phenotyping (HTP). Two traits were considered: digital biovolume, a measure based on imaging techniques in the RGB domain, and Water Use Efficiency index as calculated semi-automatically on the basis of evaporation measurements resulting in a high throughput, non-destructive, non-invasive approach, as opposed to destructive and time consuming traditional methods. Our results clearly indicate that HTP is able to discriminate genotypes and biostimulant treatments that allow plants to use soil water more efficiently. In addition, these methods based on RGB quality images can easily be scaled to field phenotyping structure USVs or UAVs.