A multisite managed environment facility for targeted trait and germplasm phenotyping

Field evaluation of germplasm for performance under water and heat stress is challenging. Field environments are variable and unpredictable, and genotype x environment interactions are difficult to interpret if environments are not well characterised. Numerous traits, genes and quantitative trait loci have been proposed for improving performance but few have been used in variety development. This reflects the limited capacity of commercial breeding companies to screen for these traits and the absence of validation in field environments relevant to breeding companies, and because little is known about the economic benefit of selecting one particular trait over another. The value of the proposed traits or genes is commonly not demonstrated in genetic backgrounds of value to breeding companies. To overcome this disconnection between physiological trait breeding and uptake by breeding companies, three field sites representing the main environment types encountered across the Australian wheatbelt were selected to form a set of managed environment facilities (MEFs). Each MEF manages soil moisture stress through irrigation, and the effects of heat stress through variable sowing dates. Field trials are monitored continuously for weather variables and changes in soil water and canopy temperature in selected probe genotypes, which aids in decisions guiding irrigation scheduling and sampling times. Protocols have been standardised for an essential core set of measurements so that phenotyping yield and other traits are consistent across sites and seasons. MEFs enable assessment of a large number of traits across multiple genetic backgrounds in relevant environments, determine relative trait value, and facilitate delivery of promising germplasm and high value traits into commercial breeding programs.

Rapid phenotyping for adult-plant resistance to stripe rust in wheat

Stripe or yellow rust (YR) is a significant problem in wheat crops worldwide. The deployment of adult-plant resistance (APR) genes in wheat cultivars is considered a sustainable management strategy, as these genes confer partial resistance that is usually non-race specific. Screening for APR typically involves assessment of adult plants in the field, where expression may be influenced by environmental factors. We report a high-throughput screening method for YR APR that can be used to assess fixed lines or segregating populations grown under controlled environmental conditions (CEC). Inoculation of 3-week-old wheat plants from lines with known APR responses to YR, when grown under constant light and temperature, provided disease responses typical of adult plants. Two F-2 populations ('H45' x 'ST93' and 'Wyalkatchem' x 'ST93') segregating for APR were assessed under both CEC and field conditions. These populations showed similar variation in disease response and lines assessed in both environments attained similar rankings. Phenotypic screening using CEC and continuous light provides an opportunity to accelerate the development of new wheat cultivars with durable resistance.

Plot size matters: interference from intergenotypic competition in plant phenotyping studies

Genetic and physiological studies often comprise genotypes diverse in vigour, size and flowering time. This can make the phenotyping of complex traits challenging, particularly those associated with canopy development, biomass and yield, as the environment of one genotype can be influenced by a neighbouring genotype. Limited seed and space may encourage field assessment in single, spaced rows or in small, unbordered plots, whereas the convenience of a controlled environment or greenhouse makes pot studies tempting. However, the relevance of such growing conditions to commercial field-grown crops is unclear and often doubtful. Competition for water, light and nutrients necessary for canopy growth will be variable where immediate neighbours are genetically different, particularly under stress conditions, where competition for resources and influence on productivity is greatest. Small hills and rod-rows maximise the potential for intergenotypic competition that is not relevant to a crop’s performance in monocultures. Response to resource availability will typically vary among diverse genotypes to alter genotype ranking and reduce heritability for all growth-related traits, with the possible exception of harvest index. Validation of pot experiments to performance in canopies in the field is essential, whereas the planting of multirow plots and the simple exclusion of plot borders at harvest will increase experimental precision and confidence in genotype performance in target environments.

Phenotyping novel stay-green traits to capture genetic variation in senescence dynamics

Stay-green plants retain green leaves longer after anthesis and can have improved yield, particularly under water limitation. As senescence is a dynamic process, genotypes with different senescence patterns may exhibit similar final normalised difference vegetative index (NDVI). By monitoring NDVI from as early as awn emergence to maturity, we demonstrate that analysing senescence dynamics improves insight into genotypic stay-green variation. A senescence evaluation tool was developed to fit a logistic function to NDVI data and used to analyse data from three environments for a wheat (Triticum aestivum L.) population whose lines contrast for stay-green. Key stay-green traits were estimated including, maximum NDVI, senescence rate and a trait integrating NDVI variation after anthesis, as well as the timing from anthesis to onset, midpoint and conclusion of senescence. The integrative trait and the timing to onset and mid-senescence exhibited high positive correlations with yield and a high heritability in the three studied environments. Senescence rate was correlated with yield in some environments, whereas maximum NDVI was associated with yield in a drought-stressed environment. Where resources preclude frequent measurements, we found that NDVI measurements may be restricted to the period of rapid senescence, but caution is required when dealing with lines of different phenology. In contrast, regular monitoring during the whole period after flowering allows the estimation of senescence dynamics traits that may be reliably compared across genotypes and environments. We anticipate that selection for stay-green traits will enhance genetic progress towards high-yielding, stay-green germplasm.

High-throughput Phenotyping of Wheat Seminal Root Traits in a Breeding Context

Water availability is a major limiting factor for wheat (Triticum aestivum L.) in rain-fed agricultural systems worldwide. Root architecture has important functional implications for the timing and extent of soil water extraction, yet selection for root traits in wheat breeding programs has been largely limited due to the lack of suitable phenotyping methods. The aim of this research was to develop a low-cost high-throughput phenotyping method to facilitate selection for desirable root traits. We developed a method to assess ‘seminal root angle’ and ‘seminal root number’ in seedlings – two proxy traits associated to root architecture of mature wheat plants (1). The method involves measuring the angle between the first pair of seminal roots and the number of roots of wheat seedlings grown in transparent pots (Figure 1). Images captured at 5 to 10 days after sowing are analyzed to calculate seminal root angle and number. Performing this technique under “speed breeding” conditions (plants grown at a density of 600 plants / m2, under controlled temperature and constant light) allows the selection based on the desired root traits of up to 5 consecutive generations within 12 months. Alternatively, when focusing only on germplasm screening, up to 52 successive phenotypic assays can be conducted within 12 months. This approach has been shown to be highly reproducible, it requires little resource (time, space, and labour) and can be used to rapidly enrich breeding populations with desirable alleles for narrow root angle and a high number of seminal roots to indirectly target the selection of deeper root system with higher branching at depth. Such root characteristics are highly desirable in wheat to cope with the climate model projections, especially in summer rainfall dominant regions including some Australian, Indian, South American and African cropping regions, where winter crops mainly rely on deep stored water.

Integrating Rapid Phenotyping and Speed Breeding to Improve Stay-Green and Root Adaptation of Wheat in Changing, Water-Limited, Australian Environments

Temperatures have increased and in-crop rainfall decreased over recent decades in many parts of the Australian wheat cropping region. With these trends set to continue or intensify, improving crop adaptation in the face of climate change is particularly urgent in this, already drought-prone, cropping region. Importantly, improved performance under water-limitation must be achieved while retaining yield potential during more favourable seasons. A multi-trait-based approach to improve wheat yield and yield stability in the face of water-limitation and heat has been instigated in northern Australia using novel phenotyping techniques and a nested association mapping (NAM) approach. An innovative laboratory technique allows rapid root trait screening of hundreds of lines. Using soil grown seedlings, the method offers significant advantages over many other lab-based techniques. Another recently developed method allows novel stay-green traits to be quantified objectively for hundreds of genotypes in standard field trial plots. Field trials in multiple locations and seasons allow evaluation of targeted trait values and identification of superior germplasm. Traits, including yield and yield components are measured for hundreds of NAM lines in rain fed environments under various levels of water-limitation. To rapidly generate lines of interest, the University of Queensland “speed breeding” method is being employed, allowing up to 7 plant generations per annum. A NAM population of over 1000 wheat recombinant inbred lines has been progressed to the F5 generation within 18 months. Genotyping the NAM lines with the genome-wide DArTseq molecular marker system provides up to 40,000 markers. They are now being used for association mapping to validate QTL previously identified in bi-parental populations and to identify novel QTL for stay-green and root traits. We believe that combining the latest techniques in physiology, phenotyping, genetics and breeding will increase genetic progress toward improved adaptation to water-limited environments.

Relative contributions of light interception and radiation use efficiency to the reduction of maize productivity under cold temperatures

Maize (Zea mays L.) is a chill-susceptible crop cultivated in northern latitude environments. The detrimental effects of cold on growth and photosynthetic activity have long been established. However, a general overview of how important these processes are with respect to the reduction of productivity reported in the field is still lacking. In this study, a model-assisted approach was used to dissect variations in productivity under suboptimal temperatures and quantify the relative contributions of light interception (PARc) and radiation use efficiency (RUE) from emergence to flowering. A combination of architectural and light transfer models was used to calculate light interception in three field experiments with two cold-tolerant lines and at two sowing dates. Model assessment confirmed that the approach was suitable to infer light interception. Biomass production was strongly affected by early sowings. RUE was identified as the main cause of biomass reduction during cold events. Furthermore, PARc explained most of the variability observed at flowering, its relative contributions being more or less important according to the climate experienced. Cold temperatures resulted in lower PARc, mainly because final leaf length and width were significantly reduced for all leaves emerging after the first cold occurrence. These results confirm that virtual plants can be useful as fine phenotyping tools. A scheme of action of cold on leaf expansion, light interception and radiation use efficiency is discussed with a view towards helping breeders define relevant selection criteria. This paper originates from a presentation at the 5th International Workshop on Functional–Structural Plant Models, Napier, New Zealand, November 2007.

Detection and use of QTL for complex traits in multiple environments.

QTL mapping methods for complex traits are challenged by new developments in marker technology, phenotyping platforms, and breeding methods. In meeting these challenges, QTL mapping approaches will need to also acknowledge the central roles of QTL by environment interactions (QEI) and QTL by trait interactions in the expression of complex traits like yield. This paper presents an overview of mixed model QTL methodology that is suitable for many types of populations and that allows predictive modeling of QEI, both for environmental and developmental gradients. Attention is also given to multi-trait QTL models which are essential to interpret the genetic basis of trait correlations. Biophysical (crop growth) model simulations are proposed as a complement to statistical QTL mapping for the interpretation of the nature of QEI and to investigate better methods for the dissection of complex traits into component traits and their genetic controls.

DNA markers linked to the R(2) rust resistance gene in sunflower (Helianthus annuus L.) facilitate anticipatory breeding for this disease variant.

Pre-emptive breeding for host disease resistance is an effective strategy for combating and managing devastating incursions of plant pathogens. Comprehensive, long-term studies have revealed that virulence to the R (2) sunflower (Helianthus annuus L.) rust resistance gene in the line MC29 does not exist in the Australian rust (Puccinia helianthi) population. We report in this study the identification of molecular markers linked to this gene. The three simple sequence repeat (SSR) markers ORS795, ORS882, and ORS938 were linked in coupling to the gene, while the SSR marker ORS333 was linked in repulsion. Reliable selection for homozygous-resistant individuals was efficient when the three markers, ORS795, ORS882, and ORS333, were used in combination. Phenotyping for this resistance gene is not possible in Australia without introducing a quarantinable race of the pathogen. Therefore, the availability of reliable and heritable DNA-based markers will enable the efficient deployment of this gene, permitting a more effective strategy for generating sustainable commercial cultivars containing this rust resistance gene.

QTL for nodal root angle in sorghum (Sorghum bicolor L. Moench) co-locate with QTL for traits associated with drought adaptation.

Nodal root angle in sorghum influences vertical and horizontal root distribution in the soil profile and is thus relevant to drought adaptation. In this study, we report for the first time on the mapping of four QTL for nodal root angle (qRA) in sorghum, in addition to three QTL for root dry weight, two for shoot dry weight, and three for plant leaf area. Phenotyping was done at the six leaf stage for a mapping population (n = 141) developed by crossing two inbred sorghum lines with contrasting root angle. Nodal root angle QTL explained 58.2% of the phenotypic variance and were validated across a range of diverse inbred lines. Three of the four nodal root angle QTL showed homology to previously identified root angle QTL in rice and maize, whereas all four QTL co-located with previously identified QTL for stay-green in sorghum. A putative association between nodal root angle QTL and grain yield was identified through single marker analysis on field testing data from a subset of the mapping population grown in hybrid combination with three different tester lines. Furthermore, a putative association between nodal root angle QTL and stay-green was identified using data sets from selected sorghum nested association mapping populations segregating for root angle. The identification of nodal root angle QTL presents new opportunities for improving drought adaptation mechanisms via molecular breeding to manipulate a trait for which selection has previously been very difficult.

Resistance gene analogues in sugarcane and sorghum and their association with quantitative trait loci for rust resistance

Fifty-four different sugarcane resistance gene analogue (RGA) sequences were isolated, characterized, and used to identify molecular markers linked to major disease-resistance loci in sugarcane. Ten RGAs were identified from a sugarcane stem expressed sequence tag (EST) library; the remaining 44 were isolated from sugarcane stem, leaf, and root tissue using primers designed to conserved RGA motifs. The map location of 31 of the RGAs was determined in sugarcane and compared with the location of quantitative trait loci (QTL) for brown rust resistance. After 2 years of phenotyping, 3 RGAs were shown to generate markers that were significantly associated with resistance to this disease. To assist in the understanding of the complex genetic structure of sugarcane, 17 of the 31 RGAs were also mapped in sorghum. Comparative mapping between sugarcane and sorghum revealed syntenic localization of several RGA clusters. The 3 brown rust associated RGAs were shown to map to the same linkage group (LG) in sorghum with 2 mapping to one region and the third to a region previously shown to contain a major rust-resistance QTL in sorghum. These results illustrate the value of using RGAs for the identification of markers linked to disease resistance loci and the value of simultaneous mapping in sugarcane and sorghum.

Genomic regions influencing seminal root traits in barley

Water availability is a major limiting factor for crop production, making drought adaptation and its many component traits a desirable attribute of plant cultivars. Previous studies in cereal crops indicate that root traits expressed at early plant developmental stages, such as seminal root angle and root number, are associated with water extraction at different depths. Here, we conducted the first study to map seminal root traits in barley (Hordeum vulgare L.). Using a recently developed high-throughput phenotyping method, a panel of 30 barley genotypes and a doubled-haploid (DH) population (ND24260 × 'Flagship') comprising 330 lines genotyped with diversity array technology (DArT) markers were evaluated for seminal root angle (deviation from vertical) and root number under controlled environmental conditions. A high degree of phenotypic variation was observed in the panel of 30 genotypes: 13.5 to 82.2 and 3.6 to 6.9° for root angle and root number, respectively. A similar range was observed in the DH population: 16.4 to 70.5 and 3.6 to 6.5° for root angle and number, respectively. Seven quantitative trait loci (QTL) for seminal root traits (root angle, two QTL; root number, five QTL) were detected in the DH population. A major QTL influencing both root angle and root number (RAQ2/RNQ4) was positioned on chromosome 5HL. Across-species analysis identified 10 common genes underlying root trait QTL in barley, wheat (Triticum aestivum L.), and sorghum [Sorghum bicolor (L.) Moench]. Here, we provide insight into seminal root phenotypes and provide a first look at the genetics controlling these traits in barley.

Molecular Breeding for Complex Adaptive Traits: How Integrating Crop Ecophysiology and Modelling Can Enhance Efficiency

Progress in crop improvement is limited by the ability to identify favourable combinations of genotypes (G) and management practices (M) in relevant target environments (E) given the resources available to search among the myriad of possible combinations. To underpin yield advance we require prediction of phenotype based on genotype. In plant breeding, traditional phenotypic selection methods have involved measuring phenotypic performance of large segregating populations in multi-environment trials and applying rigorous statistical procedures based on quantitative genetic theory to identify superior individuals. Recent developments in the ability to inexpensively and densely map/sequence genomes have facilitated a shift from the level of the individual (genotype) to the level of the genomic region. Molecular breeding strategies using genome wide prediction and genomic selection approaches have developed rapidly. However, their applicability to complex traits remains constrained by gene-gene and gene-environment interactions, which restrict the predictive power of associations of genomic regions with phenotypic responses. Here it is argued that crop ecophysiology and functional whole plant modelling can provide an effective link between molecular and organism scales and enhance molecular breeding by adding value to genetic prediction approaches. A physiological framework that facilitates dissection and modelling of complex traits can inform phenotyping methods for marker/gene detection and underpin prediction of likely phenotypic consequences of trait and genetic variation in target environments. This approach holds considerable promise for more effectively linking genotype to phenotype for complex adaptive traits. Specific examples focused on drought adaptation are presented to highlight the concepts.

Wheats developed for high yield on stored soil moisture have deep vigorous root systems

Many rainfed wheat production systems are reliant on stored soil water for some or all of their water inputs. Selection and breeding for root traits could result in a yield benefit; however, breeding for root traits has traditionally been avoided due to the difficulty of phenotyping mature root systems, limited understanding of root system development and function, and the strong influence of environmental conditions on the phenotype of the mature root system. This paper outlines an international field selection program for beneficial root traits at maturity using soil coring in India and Australia. In the rainfed areas of India, wheat is sown at the end of the monsoon into hot soils with a quickly receding soil water profile; in season water inputs are minimal. We hypothesised that wheat selected and bred for high yield under these conditions would have deep, vigorous root systems, allowing them to access and utilise the stored soil water at depth around anthesis and grain-filling when surface layers were dry. The Indian trials resulted in 49 lines being sent to Australia for phenotyping. These lines were ranked against 41 high yielding Australian lines. Variation was observed for deep root traits e.g. in eastern Australia in 2012, maximum depth ranged from 118.8 to 146.3 cm. There was significant variation for root traits between sites and years, however, several Indian genotypes were identified that consistently ranked highly across sites and years for deep rooting traits.