Glob Chang Biol
August 2024
The use of plant genetic resources (PGR)-wild relatives, landraces, and isolated breeding gene pools-has had substantial impacts on wheat breeding for resistance to biotic and abiotic stresses, while increasing nutritional value, end-use quality, and grain yield. In the Global South, post-Green Revolution genetic yield gains are generally achieved with minimal additional inputs. As a result, production has increased, and millions of hectares of natural ecosystems have been spared.
View Article and Find Full Text PDFIn this study, we present a modified high throughput phloroglucinol colorimetric assay for the quantification of arabinoxylans (AX) in wheat named PentoQuant. The method was downscaled from a 10 ml glass tube to 2 ml microcentrifuge tube format, resulting in a fivefold increase in throughput while concurrently reducing the overall cost and manual labor required for the analysis. Comparison with established colorimetric assays and gas chromatography validates the modified protocol, demonstrating its superior repeatability, rapidity, and simplicity.
View Article and Find Full Text PDFIntroduction: During the 20th century, the worldwide genetic diversity of wheat was sharply eroded by continual selection for high yields and industry demands for particular standardized qualities. A collection of Israeli and Palestinian landraces (IPLR) was established to represent genetic diversity, accumulated for ten millennia under diverse environments, which was mostly lost in this transition. As our long-term goal is to study this pre- Green Revolution genetic reservoir, herein we focus on its flour and bread quality and sensorial attributes.
View Article and Find Full Text PDFBackground: Durum wheat is key source of calories and nutrients for many regions of the world. Demand for it is predicted to increase. Further efforts are therefore needed to develop new cultivars adapted to different future scenarios.
View Article and Find Full Text PDFBackground: Continuous development of new wheat varieties is necessary to satisfy the demands of farmers, industry, and consumers. The evaluation of candidate genotypes for commercial release under different on-farm conditions is a strategy that has been strongly recommended to assess the performance and stability of new cultivars in heterogeneous environments and under different farming systems. The main objectives of this study were to evaluate the grain yield and quality performance of ten different genotypes across six contrasting farmers' field conditions with different irrigation and nitrogen fertilization levels, and to develop suggestions to aid breeding programs and farmers to use resources more efficiently.
View Article and Find Full Text PDFPhenolics are a class of chemical compounds possessing antioxidant activity, which are mainly located in the wheat (Triticum aestivum) bran. Different approaches have been used in food industry to increase the availability of phenolics. Compared to these methods, however, genetic improvement of the wheat antioxidant potential, is a cost-effective, easier and safer approach.
View Article and Find Full Text PDFBiofortification of cereal grains offers a lasting solution to combat micronutrient deficiency in developing countries where it poses developmental risks to children. Breeding efforts thus far have been directed toward increasing the grain concentrations of iron (Fe) and zinc (Zn) ions. Phytic acid (PA) chelates these metal ions, reducing their bioavailability in the digestive tract.
View Article and Find Full Text PDFCentral to the diversity of wheat products was the origin of hexaploid bread wheat, which added the D-genome of Aegilops tauschii to tetraploid wheat giving rise to superior dough properties in leavened breads. The polyploidization, however, imposed a genetic bottleneck, with only limited diversity introduced in the wheat D-subgenome. To understand genetic variants for quality, we sequenced 273 accessions spanning the known diversity of Ae.
View Article and Find Full Text PDFImplementing genomic-based prediction models in genomic selection requires an understanding of the measures for evaluating prediction accuracy from different models and methods using multi-trait data. In this study, we compared prediction accuracy using six large multi-trait wheat data sets (quality and grain yield). The data were used to predict 1 year (testing) from the previous year (training) to assess prediction accuracy using four different prediction models.
View Article and Find Full Text PDFActive nitrifiers and rapid nitrification are major contributing factors to nitrogen losses in global wheat production. Suppressing nitrifier activity is an effective strategy to limit losses from agriculture. Production and release of nitrification inhibitors from plant roots is termed "biological nitrification inhibition" (BNI).
View Article and Find Full Text PDFWheat quality improvement is an important objective in all wheat breeding programs. However, due to the cost, time and quantity of seed required, wheat quality is typically analyzed only in the last stages of the breeding cycle on a limited number of samples. The use of genomic prediction could greatly help to select for wheat quality more efficiently by reducing the cost and time required for this analysis.
View Article and Find Full Text PDFMicronutrient deficiencies, and especially zinc (Zn) deficiency, pose serious health problems to people who mainly depend on cereal-based diets. Here, we performed a genome-wide association study (GWAS) to detect the genetic basis of the Zn accumulation in wheat ( L.) grains with a diversity panel of 207 bread wheat varieties.
View Article and Find Full Text PDFRecombination at the Glu-3 loci was identified, and strong genetic linkage was observed only between the amplicons representing i-type and s-type genes located, respectively, at the Glu-A3 and Glu-B3 loci. The low-molecular weight glutenin subunits (LMW-GSs) are one of the major components of wheat seed storage proteins and play a critical role in the determination of wheat end-use quality. The genes encoding this class of proteins are located at the orthologous Glu-3 loci (Glu-A3, Glu-B3, and Glu-D3).
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