Patrick F. Byrne

Root traits contributing to plant productivity under drought.

Geneticists and breeders are positioned to breed plants with root traits that improve productivity under drought. However, a better understanding of root functional traits and how traits are related to whole plant strategies to increase crop productivity under different drought conditions is needed. Root traits associated with maintaining plant productivity under drought include small fine root diameters, long specific root length, and considerable root length density, especially at depths in soil with available water. In environments with late season water deficits, small xylem diameters in targeted seminal roots save soil water deep in the soil profile for use during crop maturation and result in improved yields. Capacity for deep root growth and large xylem diameters in deep roots may also improve root acquisition of water when ample water at depth is available. Xylem pit anatomy that makes xylem less “leaky” and prone to cavitation warrants further exploration holding promise that such traits may improve plant productivity in water-limited environments without negatively impacting yield under adequate water conditions. Rapid resumption of root growth following soil rewetting may improve plant productivity under episodic drought. Genetic control of many of these traits through breeding appears feasible. Several recent reviews have covered methods for screening root traits but an appreciation for the complexity of root systems (e.g., functional differences between fine and coarse roots) needs to be paired with these methods to successfully identify relevant traits for crop improvement. Screening of root traits at early stages in plant development can proxy traits at mature stages but verification is needed on a case by case basis that traits are linked to increased crop productivity under drought. Examples in lesquerella (Physaria) and rice (Oryza) show approaches to phenotyping of root traits and current understanding of root trait genetics for breeding.

A shifted multiplicative model cluster analysis for grouping environments without genotypic rank change

SummaryThe shifted multiplicative model (SHMM) is used with a cluster method to identify subsets of sites in an international maize (Zea mays L.) trial without genotypic rank-change. For cluster analysis, distance between two sites is defined as the residual sum of squares after fitting SHMM with one multiplicative term (SHMM1) if SHMM1 does not show genotypic rank-change. However, if SHMM1 does show genotypic rank-change, the distance between two sites is defined as the smaller of the sums of squares owing to genotypes within each of the two sites. Calculation of distance between two sites is facilitated by using the site regression model with one multiplicative term (SREG1), which can be reparameterized as SHMM1 when only two sites are considered. The dichotomous splitting procedure, used on the dendrogram obtained from cluster analysis, will first perform SHMM analyses on each of the last two cluster groups to join (end of the dendrogram). If SHMM1 does not give an adequate fit, the next step is to move down the branches of the tree until groups of sites (clusters) are found to which SHMM1 provides an adequate fit and primary effects of sites are all of the same sign. Five final groups of sites to which SHMM1 provides an adequate fit and primary effects of sites are all of the same sign were obtained. The procedure appears to be useful in identifying subsets of sites in which genotypic rank-change interactions are negligible.

Association mapping and nucleotide sequence variation in five drought tolerance candidate genes in spring wheat

Functional markers are needed for key genes involved in drought tolerance to improve selection for crop yield under moisture stress conditions. The objectives of this study were to (i) characterize five drought tolerance candidate genes, namely dehydration responsive element binding 1A (DREB1A), enhanced response to abscisic acid (ERA1‐B and ERA1‐D), and fructan 1‐exohydrolase (1‐FEH‐A and 1‐FEH‐B), in wheat (Triticum aestivum L.) for nucleotide and haplotype diversity, Tajimas D value, and linkage disequilibrium (LD) and (ii) associate within‐gene single nucleotide polymorphisms (SNPs) with phenotypic traits in a spring wheat association mapping panel (n = 126). Field trials were grown under contrasting moisture regimes in Greeley, CO, and Melkassa, Ethiopia, in 2010 and 2011. Genome‐specific amplification and DNA sequence analysis of the genes identified SNPs and revealed differences in nucleotide and haplotype diversity, Tajimas D, and patterns of LD. DREB1A showed associations (false discovery rate adjusted probability value = 0.1) with normalized difference vegetation index, heading date, biomass, and spikelet number. Both ERA1‐A and ERA1‐B were associated with harvest index, flag leaf width, and leaf senescence. 1‐FEH‐A was associated with grain yield, and 1‐FEH‐B was associated with thousand kernel weight and test weight. If validated in relevant genetic backgrounds, the identified marker–trait associations may be applied to functional marker‐assisted selection.

Jointed Goatgrass (Aegilops Cylindrica) by Imidazolinone-Resistant Wheat Hybridization under Field Conditions

Abstract Gene flow between jointed goatgrass and winter wheat is a concern because transfer of herbicide-resistance genes from imidazolinone-resistant (IR) winter wheat cultivars to jointed goatgrass could restrict weed-management options for this serious weed of winter wheat cropping systems. The objectives of this study were (1) to investigate the frequency of interspecific hybridization between IR wheat and jointed goatgrass in eastern Colorado, and (2) to determine the gene action of the IR acetolactate synthase (ALS) allele in IR wheat by jointed goatgrass and in IR wheat by imidazolinone-susceptible (IS) wheat backgrounds. Jointed goatgrass was sampled side-by-side with IR wheat and at distances up to 53 m away in both experimental plots and at commercial field study sites in 2003, 2004, and 2005. A greenhouse-screening method was used to identify IR hybrids in collected jointed goatgrass seed. The average percentage of hybridization across sites and years when IR wheat and jointed goatgrass were grown side-by-side was 0.1%, and the maximum was 1.6%. The greatest distance over which hybridization was documented was 16 m. The IR ALS allele contributed 25% of untreated ALS activity in jointed goatgrass by IR wheat F1 plants, as measured by an in vitro ALS assay. The hybridization rate between wheat and jointed goatgrass and the expression of the IR wheat ALS allele in hybrid plants will both influence trait introgression into jointed goatgrass. Nomenclature: Jointed goatgrass, Aegilops cylindrica Host AEGCY; hard red winter wheat, Triticum aestivum L. ‘Above’, ‘Bond’, ‘Prairie Red’, ‘Halt’.

GPFARM plant model parameters: Complications of varieties and the genotype x environment interaction in wheat

The USDA–ARS Great Plains Framework for Agricultural Resource Management (GPFARM) decision support system was developed to assist Great Plains producers in making economically viable and environmentally sound strategic plans for whole farm and ranch systems. A major user requirement for GPFARM is to supply the default plant parameters required to simulate crop growth. Developing this plant parameter database is difficult because varietal differences, caused by a genotype by environment (G . E) interaction, increases parameter uncertainty and variability. This article examines species–based plant parameter sets for simulating winter wheat (Triticum aestivum L.) yield responses, explores the significance of the G . E interaction on simulating varietal grain yield, and investigates whether simple adjustments to a species–based plant parameter database can improve simulation of varietal differences across environments. Three plant parameter sets were evaluated against observed yield data for six locations in eastern Colorado: (1) the Default parameter set used best estimates from EPIC–based plant parameter databases, (2) the Dryland Agroecosystems Project (DAP) parameter set further calibrated the default plant parameters against observed yield data for Colorado, and (3) the Theory parameter set modified DAP parameters based on whether irrigated or dryland conditions were simulated. The Theory parameter set simulated yield the best when pooling varieties over environments and locations. However, no parameter set could simulate all the different varietal yield responses to environmental conditions (irrigated or dryland) due to the diverse G . E interactions. The Theory parameter set best simulated the wheat variety TAM 107 across diverse locations, with little bias for either irrigated or dryland conditions. Simple adjustments to a few plant parameters based on whether dryland or irrigated conditions were simulated improved the species–based plant parameter approach used in GPFARM. However, until a better mechanistic representation of the G . E interaction is incorporated into existing plant growth models, opportunities for improving yield response to environmental conditions and management will be limited.

Metabolite Profiling of a Diverse Collection of Wheat Lines Using Ultraperformance Liquid Chromatography Coupled with Time-of-Flight Mass Spectrometry

Genetic differences among major types of wheat are well characterized; however, little is known about how these distinctions affect the small molecule profile of the wheat seed. Ethanol/water (65% v/v) extracts of seed from 45 wheat lines representing 3 genetically distinct classes, tetraploid durum (Triticum turgidum subspecies durum) (DW) and hexaploid hard and soft bread wheat (T. aestivum subspecies aestivum) (BW) were subjected to ultraperformance liquid chromatography coupled with time-of-flight mass spectrometry (UPLC-TOF-MS). Discriminant analyses distinguished DW from BW with 100% accuracy due to differences in expression of nonpolar and polar ions, with differences attributed to sterol lipids/fatty acids and phospholipids/glycerolipids, respectively. Hard versus soft BW was distinguished with 100% accuracy by polar ions, with differences attributed to heterocyclic amines and polyketides versus phospholipid ions, respectively. This work provides a foundation for identification of metabolite profiles associated with desirable agronomic and human health traits and for assessing how environmental factors impact these characteristics.

Allelic Variation in Developmental Genes and Effects on Winter Wheat Heading Date in the U.S. Great Plains

Heading date in wheat (Triticum aestivum L.) and other small grain cereals is affected by the vernalization and photoperiod pathways. The reduced-height loci also have an effect on growth and development. Heading date, which occurs just prior to anthesis, was evaluated in a population of 299 hard winter wheat entries representative of the U.S. Great Plains region, grown in nine environments during 2011–2012 and 2012–2013. The germplasm was evaluated for candidate genes at vernalization (Vrn-A1, Vrn-B1, and Vrn-D1), photoperiod (Ppd-A1, Ppd-B1 and Ppd-D1), and reduced-height (Rht-B1 and Rht-D1) loci using polymerase chain reaction (PCR) and Kompetitive Allele Specific PCR (KASP) assays. Our objectives were to determine allelic variants known to affect flowering time, assess the effect of allelic variants on heading date, and investigate changes in the geographic and temporal distribution of alleles and haplotypes. Our analyses enhanced understanding of the roles developmental genes have on the timing of heading date in wheat under varying environmental conditions, which could be used by breeding programs to improve breeding strategies under current and future climate scenarios. The significant main effects and two-way interactions between the candidate genes explained an average of 44% of variability in heading date at each environment. Among the loci we evaluated, most of the variation in heading date was explained by Ppd-D1, Ppd-B1, and their interaction. The prevalence of the photoperiod sensitive alleles Ppd-A1b, Ppd-B1b, and Ppd-D1b has gradually decreased in U.S. Great Plains germplasm over the past century. There is also geographic variation for photoperiod sensitive and reduced-height alleles, with germplasm from breeding programs in the northern Great Plains having greater incidences of the photoperiod sensitive alleles and lower incidence of the semi-dwarf alleles than germplasm from breeding programs in the central or southern plains.

Comparing test cultivars using reliability functions of test-check differences from on-farm trials

An approach to selection is proposed that is based on the probabilities that a test cultivar outperforms a check by more than an amount d in a future environment. The function that gives these probabilities for all possible values of d is called the reliability function. When d=0, the value of the reliability function is the probability that the test cultivar outperforms the check. The method is illustrated using data from on-farm maize (Zea mays L.) strip test trials grown cooperatively by Pioneer Hi-bred International and farmers. Results indicate that reliability functions are useful for evaluating how test cultivars perform relative to a check across a range of environments since the location, slope and shape of the reliability function may be used to describe a test cultivars performance, similarity to the check and stability, and identify environments where the test cultivar has performance problems.

Increasing public understanding of transgenic crops through the World Wide Web

Transgenic crops are among the most controversial “science and society” issues or recent years. Because of the complex techniques involved in creating these crops and the polarized debate over their risks and benefits, a critical need has arisen for accessible and balanced information on this technology. World Wide Web sites offer several advantages for disseminating information on a fast-changing technical topic, including their global accessibility; and their ability to update information frequently, incorporate multimedia formats, and link to networks of other sites. An alliance between two complementary web sites at Colorado State University and the University of Nebraska-Lincoln takes advantage of the web environment to help fill the need for public information on crop genetic engineering. This article describes the objectives and features of each site. Viewership data and other feedback have shown these web sites to be effective means of reaching public audiences on a complex scientific topic.

Selection of stable varieties by minimizing the probability of disaster

Abstract Many plant breeders use estimates of stability parameters to aid them with making selections in the presence of cultivar × environment interaction. To make selections, the breeder must weight the importance of yield to stability. On the assumption that the plant breeder prefers varieties which minimize the probability of disastrously low yields, a general index is proposed which explicitly shows how the plant breeder weighs the importance of mean yield to stability. This index was applied to six internationamaize (Zea mays L.) yield trials using various stability models. Results indicated that the choice of a stability model can have a substantial effect on the desirability of a variety, and that inclusion of a measure of stability in the index may significantly alter the ranking of varieties compared with considering only the mean yield. The proposed index approach can be a practical way of making selectionsin the presence of cultivar × environment interaction when stability is a major concern.