Predicting phenological development in winter wheat

Accurate prediction of phenological development is important in the winter wheat Triticum aestivum agroecosystem. From a practical perspective, applications of pesticides and fertilizers are carried out at specific phenological stages. In crop-simulation modeling, the prediction of yield components (kernel number and kernel weight) and wheat-grain yield relies on accurate prediction of phenology. In this study, a nonlinear multiplicative model by Wang & Engel (WE) for predicting phenological development in differing winter wheat cultivars was evaluated using data from a 3 yr field experiment. In the vegetative phase (emergence to anthesis) the daily development rate (r) was simulated based on the product of a maximum development rate (Rmax) in the vegetative phase, a temperature response function [ƒ(T)], a photoperiod response function [ƒ(P)], and a vernalization response function [ƒ(V)]. ƒ(T) was a nonlinear function of the 3 cardinal temperatures for phenological development (minimum, Tmin, optimum, Topt, and maximum, Tmax). ƒ(P) was an exponential function of the actual and critical photoperiods and a sensitivity parameter unique to each cultivar. ƒ(V) was calculated using ƒ(T) based on the cardinal temperatures for vernalization (Tmin,vn, Topt,vn, and Tmax,vn). In the reproductive phase, r was simulated based on the product of Rmax for the reproductive phase and ƒ(T). Predictions from this nonlinear model were compared to predictions from the phenology submodel of CERES-Wheat V3.0 (CW3). The nonlinear model performed very well for predicting phenological development in the 3 winter wheat cultivars, the mean root mean square error (RMSE) ranged from 2.9 to 4.1 d from booting to maturity. For the CW3 model, the mean RMSE ranged from 4.8 to 5.9 d for the same phenological stages. The WE model predicted double ridge with a mean RMSE of 7.3 d. Both models predicted terminal spikelet with a mean RMSE ranging from 6.2 to 7.1 d. The WE model was generally a better predictor of phenology between booting and maturity than the CW3 model

Emerging Trends in Wheat (\u3ci\u3eTriticum\u3c/i\u3e spp.) Breeding: Implications for the Future

Wheat (Triticum spp and, particularly, T. aestivum L.) is an essential cereal with increased human and animal nutritional demand. Therefore, there is a need to enhance wheat yield and genetic gain using modern breeding technologies alongside proven methods to achieve the necessary increases in productivity. These modern technologies will allow breeders to develop improved wheat cultivars more quickly and efficiently. This review aims to highlight the emerging technological trends used worldwide in wheat breeding, with a focus on enhancing wheat yield. The key technologies for introducing variation (hybridization among the species, synthetic wheat, and hybridization; genetically modified wheat; transgenic and gene-edited), inbreeding (double haploid (DH) and speed breeding (SB)), selection and evaluation (marker-assisted selection (MAS), genomic selection (GS), and machine learning (ML)) and hybrid wheat are discussed to highlight the current opportunities in wheat breeding and for the development of future wheat cultivars

SIMULATION AND RESPONSE SURFACE METHODOLOGY TO OPTIMIZE WINTER WHEAT RESPONSE TO GLOBAL CLIMATE CHANGE

Future climate changes can have a major impact on crop production. But, whatever the climatic changes, crop production can be adapted to climate change by implementing alternative management practices and developing new genotypes that will take full advantage of the future climatic conditions. Since the classical agronomic research approach is not possible in identifying these new agronomic technologies for the future climatic conditions, we used response surface methodology (RSM) in connection with the CERES-Wheat crop model and the HADCM2 climate simulation model to identify optimal configuration of plant traits and management practices that maximize yield of winter wheat under high CO2 environments. The simulations were conducted for three Nebraska locations (Havelock, Dickens and Alliance), which were considered representative of winter wheat growing areas in the central Great Plains. At all locations, the identified optimal winter wheat cultivar under high CO2 conditions had a larger number of tillers, larger kernel size, shorter days to flower, grew faster and had more kernels per square meter than the check variety under normal CO2 conditions, while the optimal planting dates were later and planting densities were lower than under normal conditions. We concluded that RSM used in conjunction with crop and climate simulation models was a useful approach to understanding the complex relationship between wheat genotypes, climate and management practices

Genome-Wide Association Study Reveals Novel Genomic Regions for Grain Yield and Yield-Related Traits in Drought-Stressed Synthetic Hexaploid Wheat

Synthetic hexaploid wheat (SHW; 2n = 6x = 42, AABBDD, Triticum aestivum L.) is produced from an interspecific cross between durum wheat (2n = 4x = 28, AABB, T. turgidum L.) and goat grass (2n = 2x = 14, DD, Aegilops tauschii Coss.) and is reported to have significant novel alleles-controlling biotic and abiotic stresses resistance. A genome-wide association study (GWAS) was conducted to unravel these loci [marker–trait associations (MTAs)] using 35,648 genotyping-by-sequencing-derived single nucleotide polymorphisms in 123 SHWs. We identified 90 novel MTAs (45, 11, and 34 on the A, B, and D genomes, respectively) and haplotype blocks associated with grain yield and yield-related traits including root traits under drought stress. The phenotypic variance explained by the MTAs ranged from 1.1% to 32.3%. Most of the MTAs (120 out of 194) identified were found in genes, and of these 45 MTAs were in genes annotated as having a potential role in drought stress. This result provides further evidence for the reliability of MTAs identified. The large number of MTAs (53) identified especially on the D-genome demonstrate the potential of SHWs for elucidating the genetic architecture of complex traits and provide an opportunity for further improvement of wheat under rapidly changing climatic conditions

EC88-102 Nebraska Spring Small Grain Variety Tests 1988

Extension circular 88-102 is about Nebraska spring small grain variety tests in 1988

Effect of Growth Stage on the Relationship Between Tan Spot and Spot Blotch Severity and Yield in Winter Wheat

Foliar fungal diseases frequently cause significant economic losses in the hard red winter wheat production areas of the Great Plains of the United States. In 2007, field experiments were conducted in four environments in Nebraska, USA to determine the crop growth stage at which severity of tan spot and spot blotch was most strongly related to yield in winter wheat. Secondary objectives were to evaluate the efficacy of fungicides in controlling tan spot and spot blotch and to determine the effect of fun¬gicide application timing on disease intensity and yield. Disease severity assessed at Zadoks growth stage (ZGS) 60 (flower¬ing) had the strongest relationship to yield at all four locations (0.72 ≤ R2 ≤ 0.90, P \u3c 0.0001). Disease severity assessed at ZGS 71 (kernel watery ripe) also was strongly related to yield (0.54 ≤ R2 ≤ 0.87, P ≤ 0.0011), but not as consistently across the four loca¬tions as disease severity assessed at ZGS 60. The relationship between yield and area under the disease progress curve (AUDPC) (0.43 ≤ R2 ≤ 0.80, P ≤ 0.0055) was weaker and less consistent across the four locations than the relationship between yield and dis¬ease severity assessed at ZGS 60 or ZGS 71. Disease progress was faster at Mead (southeast) and Clay Center (south central) than at North Platte (west central) and Sidney (west). The fungicides azoxystrobin, pyraclostrobin, propiconazole, azoxystrobin plus propiconazole, and trifloxystrobin plus propiconazole effectively reduced disease severity and AUDPC. Out of a total of 60 fun¬gicide treatments at four locations, 98%, 100%, and 100% significantly (P = 0.05) reduced disease severity, reduced AUDPC, and increased yield, respectively, compared to the check. Yield losses ranging from 27% to 42% were prevented by fungicide applica¬tions. There was no consistent effect on disease intensity or on yield of timing fungicide applications at ZGS 31 (first node on the stem detectable) versus ZGS 39 (ligule/collar of flag leaf just visible). The results from this study suggest that (i) the best predic¬tor of yield loss caused by tan spot and spot blotch in winter wheat in Nebraska is disease severity assessed at flowering and (ii) fungicides can prevent significant yield losses from tan spot and spot blotch in winter wheat

Identifying Winter Forage Triticale (×\u3ci\u3eTriticosecale\u3c/i\u3e Wittmack) Strains for the Central Great Plains

Triticale (×Triticosecale Wittmack) is mainly used as a forage crop in the central Great Plains. A successful triticale cultivar should have high forage yield with good quality, and also high grain yield so the seed can be economically produced. The purpose of this study was to evaluate existing triticale cultivars and experimental strains for their relative value in the central Great Plains as an annual hay crop primarily for feeding to beef cattle. Two experiments (one for forage yield and one for grain yield) were planted at two locations (one representing the arid Great Plains and the second representing the or higher rainfall central Great Plains) for 2 yr. Twenty-nine triticale cultivars and strains were evaluated for forage yield and quality, and grain yield. In both experiments, year effects were significant (P \u3c 0.05) for all traits except grain yield; location effects were significant for forage yield, neutral detergent fiber (NDF), and acid detergent fiber. There was no location × strain or year × location × strain interaction for all the quality traits indicating that triticale forage quality was stable across environments. Triticale strains differed significantly for forage yield, grain yield, NDF, acid detergent lignin, and relative feed value. However, forage of all strains had good feed quality. Three strains had high grain and forage yield, and very good relative feed value suggesting that triticale improvement for both grain and forage traits is possible

GWAS: Fast-forwarding gene identification and characterization in temperate Cereals: lessons from Barley – A review

Understanding the genetic complexity of traits is an important objective of small grain temperate cereals yield and adaptation improvements. Bi-parental quantitative trait loci (QTL) linkage mapping is a pow- erful method to identify genetic regions that co-segregate in the trait of interest within the research pop- ulation. However, recently, association or linkage disequilibrium (LD) mapping using a genome-wide association study (GWAS) became an approach for unraveling the molecular genetic basis underlying the natural phenotypic variation. Many causative allele(s)/loci have been identified using the power of this approach which had not been detected in QTL mapping populations. In barley (Hordeum vulgare L.), GWAS has been successfully applied to define the causative allele(s)/loci which can be used in the breeding crop for adaptation and yield improvement. This promising approach represents a tremendous step forward in genetic analysis and undoubtedly proved it is a valuable tool in the identification of can- didate genes. In this review, we describe the recently used approach for genetic analyses (linkage map- ping or association mapping), and then provide the basic genetic and statistical concepts of GWAS, and subsequently highlight the genetic discoveries using GWAS. The review explained how the candidate gene(s) can be detected using state-of-art bioinformatic tools

Insights into the Genetic Architecture of Bran Friability and Water Retention Capacity, Two Important Traits for Whole Grain End-Use Quality in Winter Wheat

Bran friability (particle size distribution after milling) and water retention capacity (WRC) impact wheat bran functionality in whole grain milling and baking applications. The goal of this study was to identify genomic regions and underlying genes that may be responsible for these traits. The Hard Winter Wheat Association Mapping Panel, which comprised 299 lines from breeding programs in the Great Plains region of the US, was used in a genome-wide association study. Bran friability ranged from 34.5% to 65.9% (median, 51.1%) and WRC ranged from 159% to 458% (median, 331%). Two single-nucleotide polymorphisms (SNPs) on chromosome 5D were significantly associated with bran friability, accounting for 11–12% of the phenotypic variation. One of these SNPs was located within the Puroindoline-b gene, which is known for influencing endosperm texture. Two SNPs on chromosome 4A were tentatively associated with WRC, accounting for 4.6% and 4.4% of phenotypic variation. The favorable alleles at the SNP sites were present in only 15% (friability) and 34% (WRC) of lines, indicating a need to develop new germplasm for these whole-grain end-use quality traits. Validation of these findings in independent populations will be useful for breeding winter wheat cultivars with improved functionality for whole grain food applications