Southern Australian Wheat Research Articles

Assessment of crop traits retrieved from airborne hyperspectral and thermal remote sensing imagery to predict wheat grain protein content

Wheat (Triticum spp.) is among the world’s most widely grown crops and receives large quantities of nitrogen (N) fertiliser. Grain protein content (GPC) is influenced by genetic, agronomic and weather conditions affecting crops’ physiological status and stress levels; accurate GPC prediction has potential to reduce N losses and improve profit. Success in GPC estimation from remotely sensed plant traits has been limited. For progress to be made, it is necessary to robustly identify imaging spectroscopy-based physiological traits most closely associated with GPC in both experimental and commercial contexts. We present results from piloted hyperspectral flights and ground campaigns at two dryland field experiments with divergent water supply and wide-ranging N treatments, and from two years’ flights over 17 commercial fields planted to either bread (T. aestivum) or durum (T. durum) wheat, in the southern Australian wheat belt. Imagery was acquired with airborne hyperspectral and thermal sensors, with spatial resolutions of approx. 0.3 m and 0.5 m for experimental plots and 1 m/1.7 m in commercial fields. Leaf clip measurements, leaf and grain samples were collected and, in commercial fields, ∼40,000 records obtained from harvester-mounted protein monitors. Crop Water Stress Index (CWSI), solar-induced fluorescence (SIF), reflectance indices and PRO4SAIL radiative transfer model inverted parameters were retrieved for each plot and GPC record location. The photochemical reflectance index (PRI) related to xanthophyll pigments was consistently associated with GPC at both leaf and canopy scale in the plots and transect. In the commercial crops, a gradient boosted machine learning algorithm (GBM) ranked CWSI as the strongest indicator of GPC under severe water stress, while SIF, PRI and inverted biochemical constituents anthocyanins and carotenoids were consistently important under more benign conditions. Structural parameters inverted from the hyperspectral reflectance imagery were not prominent except under severe drought. We attained statistically significant results estimating GPC in unseen samples, with best relationships between predicted and observed GPC of r2 = 0.80 in a model built with thermal and physiological traits obtained from the hyperspectral and thermal imagery.

Ppd-B1 and Ppd-D1 and their effects in southern Australian wheat

Photoperiod and vernalisation genes are important for the adaptation of wheat to variable environments. Previously, using diagnostic markers and a large, unbalanced dataset from southern Australia, we estimated the effects on days to heading of frequent alleles of Vrn-A1, Vrn-B1, and Vrn-D1, and also two allelic classes of Ppd-D1. These genes accounted for ~45% of the genotypic variance for that trait. We now extend these analyses to further alleles of Ppd-D1, and four alleles of Ppd-B1 associated with copy number. Variation in copy number of Ppd-B1 occurred in our population, with one to four linked copies present. Additionally, in rare instances, the Ppd-B1 gene was absent (a null allele). The one-copy allele, which we labelled Ppd-B1b, and the three-copy allele, which we labelled Ppd-B1a, occurred through a century of wheat breeding, and are still frequent. With several distinct progenitors, the one-copy allele might not be homogenous. The two-copy allele, which we labelled Ppd-B1d, was generally introduced from WW15 (syn. Anza), and the four-copy allele, which we labelled Ppd-B1c, came from Chinese Spring. In paired comparisons, Ppd-B1a and Ppd-B1c reduced days to heading, but Ppd-B1d increased days to heading. Ppd-D1a, with a promoter deletion, Ppd-D1d, with a deletion in Exon 7, and Ppd-D1b, the intact allele, were frequent in modern Australian germplasm. Differences between Ppd-D1a and Ppd-D1d for days to heading under our field conditions depended on alleles of the vernalisation genes, confirming our previous report of large epistatic interactions between these classes of genes. The Ppd-D1b allele conferred a photoperiod response that might be useful for developing cultivars with closer to optimal heading dates from variable sowing dates. Inclusion of Ppd-B1 genotypes, and more precise resolution of Ppd-D1, increased the proportion of the genotypic variance attributed to these vernalisation and photoperiod genes to ~53%.

Photoperiod and vernalization gene effects in southern Australian wheat

Photoperiod and vernalization genes are important for the optimal adaptation of wheat to different environments. Diagnostic markers are now available for Vrn-A1, Vrn-B1, Vrn-D1 and Ppd-D1, with all four genes variable in southern Australian wheat-breeding programs. To estimate the effects of these genes on days to heading we used data from 128 field experiments spanning 24 years. From an analysis of 1085 homozygous cultivars and breeding lines, allelic variation for these four genes accounted for ~45% of the genotypic variance for days to heading. In the presence of the photoperiod-insensitive allele of Ppd-D1, differences between the winter genotype and genotypes with a spring allele at one of the genes ranged from 3.5 days for Vrn-B1 to 4.9 days for Vrn-D1. Smaller differences occurred between genotypes with a spring allele at one of the Vrn genes and those with spring alleles at two of the three genes. The shortest time to heading occurred for genotypes with spring alleles at both Vrn-A1 and Vrn-D1. Differences between the photoperiod-sensitive and insensitive alleles of Ppd-D1 depended on the genotype of the vernalization genes, being greatest when three spring alleles were present (11.8 days) and least when the only spring allele was at Vrn-B1 (3.7 days). Because of these epistatic interactions, for the practical purposes of using these genes for cross prediction and marker-assisted selection we concluded that using combinations of alleles of genes simultaneously would be preferable to summing effects of individual genes. The spring alleles of the vernalization genes responded differently to the accumulation of vernalizing temperatures, with the common spring allele of Vrn-A1 showing the least response, and the spring allele of Vrn-D1 showing a response that was similar to, but less than, a winter genotype.

The effects on grain quality traits of a grain serpin protein and the VPM1 segment in southern Australian wheat breeding

Production of wheat of sufficient quality to meet market demands is an ongoing agricultural challenge. Identification and evaluation of alleles of genes affecting quality parameters enables breeders to improve their germplasm by active selection towards specific allele combinations. Using a large dataset obtained from southern Australian wheat breeding programs, and including a relationship matrix in the analysis to minimise bias, we re-evaluated the effects of high- and low-molecular-weight glutenin alleles and puroindoline alleles on the grain quality parameters Rmax, dough extensibility, dough development time, flour water absorption, and milling yield and found that estimated effects were in close agreement with those from earlier analyses without a relationship matrix. We also evaluated, for the first time, the effects on the same quality parameters of 2 alleles (wild-type and null) of a defence grain protein, a serpin located on chromosome 5B. In addition, we assessed the effect of the VPM1 alien segment. The serpin null allele significantly reduced milling yield by ~0.4 g of flour per 100 g of grain milled across different germplasm sources and flour protein levels. In Australian germplasm, the origin of this allele was traced to a 19th Century introduction from India by William Farrer; however other sources, of significance in international breeding programs, were also identified. Our analysis of the effect of the VPM1 segment on quality traits revealed no detrimental effects of its presence on the traits we measured.

Genetic dissection of grain yield in bread wheat. I. QTL analysis

Grain yield forms one of the key economic drivers behind a successful wheat (Triticum aestivum L.) cropping enterprise and is consequently a major target for wheat breeding programmes. However, due to its complex nature, little is known regarding the genetic control of grain yield. A doubled-haploid population, comprising 182 individuals, produced from a cross between two cultivars 'Trident' and 'Molineux', was used to construct a linkage map based largely on microsatellite molecular makers. 'Trident' represents a lineage of wheat varieties from southern Australia that has achieved consistently high relative grain yield across a range of environments. In comparison, 'Molineux' would be rated as a variety with low to moderate grain yield. The doubled-haploid population was grown from 2002 to 2005 in replicated field experiments at a range of environments across the southern Australian wheat belt. In total, grain yield data were recorded for the population at 18 site-year combinations. Grain yield components were also measured at three of these environments. Many loci previously found to be involved in the control of plant height, rust resistance and ear-emergence were found to influence grain yield and grain yield components in this population. An additional nine QTL, apparently unrelated to these traits, were also associated with grain yield. A QTL associated with grain yield on chromosome 1B, with no significant relationship with plant height, ear-emergence or rust resistance, was detected (LOD > or =2) at eight of the 18 environments. The mean yield, across 18 environments, of individuals carrying the 'Molineux' allele at the 1B locus was 4.8% higher than the mean grain yield of those lines carrying the 'Trident' allele at this locus. Another QTL identified on chromosome 4D was also associated with overall gain yield at six of the 18 environments. Of the nine grain yield QTL not shown to be associated with plant height, phenology or rust resistance, two were located near QTL associated with grain yield components. A third QTL, associated with grain yield components at each of the environments used for testing, was located on chromosome 7D. However, this QTL was not associated with grain yield at any of the environments. The implications of these findings on marker-assisted selection for grain yield are discussed.

Contributions of glutenin and puroindoline genes to grain quality traits in southern Australian wheat breeding programs

Glutenin genes were known to influence maximum dough resistance (Rmax), dough extensibility (extensibility), and dough development time, whereas puroindoline genes were known to influence grain hardness, flour water absorption (water absorption), and milling yield. These are important determinants of grain quality of wheat in Australia. This study was conducted to investigate the combined effect of these genes on Rmax, extensibility, dough development time, water absorption, and milling yield in a large dataset assembled from the breeding programs based at Horsham, Victoria; Roseworthy, South Australia; and Wagga Wagga, New South Wales; for at least 10 seasons. The effect of the glutenin genes on Rmax, extensibility, and dough development time was confirmed, as was the effect of the puroindoline genes on water absorption and milling yield. In addition, puroindoline genes were shown to significantly affect extensibility and dough development time. The Pina-D1a/Pinb-D1b genotype increased extensibility, dough development time, and milling yield relative to the Pina-D1b/Pinb-D1a genotype. Both of these genotypes are present in cultivars classified as hard-grained in southern Australia. Therefore, the allelic composition of both glutenin and puroindoline genes is required to predict the grain quality of hard wheat in southern Australian breeding programs. The glutenin and puroindoline genes in combination accounted for more than 50% of the genotypic variance for these traits, except for milling yield, but a substantial proportion of the genotypic variation could not be attributed to these genes, indicating that other genes affecting the traits were present in the populations of these wheat-breeding programs.

Capture of agricultural surplus water determines the productivity and scale of new low-rainfall woody crop industries

This paper presents a conceptual model for estimating the maximum scale of biomass processing industry that may be supported by woody crops grown in the medium and low rainfall agricultural regions of southern Australia. The model integrates paddock scale economics, water capture by woody crops, conversion of water to woody biomass, and estimation of suitable area. It enables estimates to be made of the maximum scale of implementation of commercial woody crops in various climatic regions, and the maximum amount of woody biomass that could be produced commercially within an economic transport distance of a processing facility. To demonstrate the utility of the model, potential biomass supply is estimated for 2 Western Australian wheatbelt towns, Merredin and Narrogin. These estimates are compared with the feedstock requirements of a range of different processing industries. This paper demonstrates that the rate of converting water to biomass and water capture biomass price are key determinants of the potential scale of biomass crops and processing industries in the southern Australian wheat and wool belts and hence the potential contribution of woody crops to dryland salinity management.

Revision of the estimates of glutenin gene effects at the Glu-B1 locus from southern Australian wheat breeding programs

Glutenins are the major determinant of dough characteristics in wheat. These proteins are determined by genes at 6 loci, with multiple alleles present in southern Australian breeding programs. Previously, we estimated the effects of these genes on maximum dough resistance (Rmax), dough extensibility and dough development time. Subsequently, the allele previously classified as Glu-B1b was found to consist of 2 alleles, with one, now considered to be Glu-B1al, producing an overexpression of the Bx7 glutenin subunit. Therefore, there is a potential bias in our previous estimates. An extended dataset was analysed with the 2 alleles now separated. These analyses identified negligible biases in our previous estimates, probably due to a low frequency of Glu-B1al before 1999. However, Glu-B1al produced significantly higher Rmax, dough extensibility, and dough development time values than all other alleles at the Glu-B1 locus. Therefore, at intermediate allele frequencies, substantial bias in estimates of the effects of the Glu-B1 alleles can be expected without correct identification of Glu-B1al.

Puroindoline genes and their effects on grain quality traits in southern Australian wheat cultivars

Grain hardness is a major determinant of the classification and end-use of wheat. Two genes, Pina-D1 and Pinb-D1, have a major effect on this trait, so for wheat breeding programs it is important to identify the alleles of these genes present in elite germplasm. This study was conducted to identify the alleles present in southern Australian germplasm, and to determine if they affected quality characteristics other than grain hardness.Only 3 genotypes were identified. These were Pina-D1a/Pinb-D1a producing soft grain, Pina-D1a/Pinb-D1b producing moderately hard grain, and Pina-D1b/Pinb-D1a producing very hard grain. WW15 was the probable source of Pina-D1a/Pinb-D1b in most cultivars; however, Halberd represented another source. An important source of Pina-D1b/Pinb-D1a was the CIMMYT line Pavon, with sources from the old Australian cultivars Gabo and Falcon probably still present in modern germplasm.In an analysis of grain quality data from the Victorian Institute for Dryland Agriculture breeding program, the Pina-D1b/Pinb-D1a genotype had a significantly higher water absorption and significantly lower milling yield than the Pina-D1a/Pinb-D1b genotype, which indicates that these genes will impede the development of hard-grained cultivars that combine high water absorption and high milling yield.

Genetic and environmental variation for grain quality traits routinely evaluated in southern Australian wheat breeding programs

Milling yield, maximum dough resistance (Rmax), dough extensibility, flour protein concentration (flour protein), particle size index (PSI), water absorption, and dough development time are important determinants of grain quality and are routinely evaluated in Australian wheat breeding programs. Information on allelic variation at the 6 loci determining glutenin proteins is also regularly obtained and used to predict Rmax and extensibility. For each character, except dough development time, 4029 observations on 2377 lines and 94 environments were analysed to estimate genotypic and environmental variances, heritabilities, genotypic and environmental correlations, and the effects of glutenin genes. A subset was analysed for dough development time. Milling yield, Rmax, extensibility, PSI, water absorption, and dough development time had intra-class correlation coefficients, or broad-sense heritabilities, between 0.66 and 0.76, and extensibility had a value of 0.52, with flour protein at 0.36. Genotypic and environmental correlations between extensibility and flour protein were high at +0.78 and +0.85, respectively. Rmax had a genotypic correlation with dough development time of +0.67, which was substantially due to pleiotropic effects of glutenin genes. Rmax, extensibility, PSI, and dough development time were influenced by glutenin genes. For Rmax about 50% of the genotypic variance could be explained by glutenin genes. For extensibility about 50% could be explained by flour protein, with 50% of the remainder by the inclusion of glutenin genes. For dough development time about 15% could be explained by flour protein, with a further 30% by glutenin genes. For PSI, about 40% of the genotypic variation could be accounted for by glutenin genes after the removal of the effects of flour protein and milling yield. We concluded that dough development time could be added to Rmax and extensibility as a trait that can be usefully predicted by the glutenin genes, but more work is required for PSI.

Estimation and utilisation of glutenin gene effects from the analysis of unbalanced data from wheat breeding programs

Glutenins are a major determinant of dough characteristics in wheat. These proteins are determined by genes at 6 loci (Glu genes), with multiple alleles present in most breeding programs. This study was conducted to determine whether estimates of allele effects for the important dough rheological characters, maximum dough resistance (Rmax) and dough extensibility, could be determined from aggregated data from southern Australian wheat breeding programs using statistical techniques appropriate for unbalanced data. From a 2-stage analysis of 3226 samples of 1926 cultivars and breeding lines, estimates of Rmax and extensibility effects were obtained, first for the lines, and then for 31 glutenin alleles. Glutenin genes did not determine flour protein concentration, and this character was used as a covariate. Rankings of the estimates of Rmax for the alleles were similar to the relative scores for dough strength reported from previous studies, providing strong evidence that the analysis of a large, unbalanced data set from applied wheat breeding programs can provide reliable estimates. All 2-way interactions between loci were present for 18 of the alleles. Analyses including interactions showed that epistasis was important for both Rmax and extensibility, especially between the Glu-B1 locus coding for high molecular weight glutenins and the Glu-A3 and Glu-B3 loci coding for low molecular weight glutenins. Because of the complexity of these interactions, similar values of Rmax and extensibility were predicted for diverse combinations of alleles. This implied that the practical application of glutenin genes in applied wheat breeding would be greatly enhanced by computer software which can predict dough rheology characteristics from glutenin allele classifications.

Utilization by wheat crops of nitrogen from legume residues decomposing in soils in the field

Ground 15N-labelled legume material ( Medicago littoralis) was mixed with topsoils in confined microplots in the field, and allowed to decompose for 7 and 5 months in successive years (1979, 1980) before sowing wheat. The soil cropped in 1979 (and containing 15N-labelled wheat roots and legume residues) was cropped again in 1980. The results support evidence that ungrazed legume residues, incorporated in amounts commonly found in southern Australian wheat growing regions, contribute only a little to soil available N and to crop N uptake, even in the first year of their decomposition. Thus mature first crops of wheat, although varying greatly in dry matter yield (2.9-fold) and total N uptake (2.4-fold), took up only 27.8 and 20.2% of the legume N applied at 48.4 kg ha −1, these corresponding to 6.1 and 10.8% of the N of the wheat crops. The availability of N from medic residues to a second wheat crop declines to <5% of input. For both first and second wheat crops, uptake of N from legume residues was approximately proportional to legume N input over the range 24.2 to 96.8 kg ha −1. The proportional contributions of medic N to soil inorganic N, N released in mineralization tests, and to wheat crop N, differed between seasons and soils, but for a given crop did not significantly differ between tillering, flowering and maturity. In both years, grain accounted for 52–65% of the total 15N of first crops, roots for < 5–6%. In neither year did the amounts of N or 15N in the tops change significantly between flowering and maturity, despite a gain in tops dry matter in 1979; by contrast N and 15N of roots decreased significantly during ripening in both years. Wheat plants at tillering contained about 75% of the N and 15N taken up at flowering. The amounts of legume-derived 15N in mature first wheat crops were equivalent to 82–88% of the amounts of inorganic 15N in the soil profiles at sowing. Wheat straw added at the rate of 2.5 t ha −1, 2 months before sowing, decreased the uptake of N (15%) and 15N (18%) by wheat in a nitrogen responsive season.

The role of bacteria in the biological control of Gaeumannomyces graminis by suppressive soils

The suppression of Gaeumannomyces graminis var. tritici by certain soils or following certain soil treatments is considered to be an expression of either specific or general antagonism sensu Gerlagh (1968). Specific antagonism is effective in dilutions as high as 1 in 1,000, can be transferred from soil to soil, operates near or on wheat roots, is destroyed by 60°C moist heat for 30 min. or desiccation, is fostered by wheat monoculture but may be lost from a soil by fallow or rotation with certain crops, especially legume hay or pasture crops. Strains of Pseudomonas fluorescens may be involved. General antagonism is a soil property which cannot be transferred and is resistant to 80°C moist heat for 30 min, to methyl bromide and chloropicrin, but not to autoclaving. Take-all control by organic amendments, minimum tillage, or a soil temperature of 28°C may be expressions of increased general antagonism. In much of the southern Australian wheat belt, where take-all can cause heavy crop losses, some general but rarely specific antagonism is apparently operative. Both types of antagonism are probably operative in long-term wheat growing areas of the Pacific Northwest U.S.A. where take-all is virtually nonexistent.