Tolerance of Combined Drought and Heat Stress Is Associated With Transpiration Maintenance and Water Soluble Carbohydrates in Wheat Grains.

Wheat (Triticum aestivum L.) production is increasingly challenged by simultaneous drought and heatwaves. We assessed the effect of both stresses combined on whole plant water use and carbohydrate partitioning in eight bread wheat genotypes that showed contrasting tolerance. Plant water use was monitored throughout growth, and water-soluble carbohydrates (WSC) and starch were measured following a 3-day heat treatment during drought. Final grain yield was increasingly associated with aboveground biomass and total water use with increasing stress intensity. Combined drought and heat stress immediately reduced daily water use in some genotypes and altered transpiration response to vapor pressure deficit during grain filling, compared to drought only. In grains, glucose and fructose concentrations measured 12 days after anthesis explained 43 and 40% of variation in final grain weight in the main spike, respectively. Starch concentrations in grains offset the reduction in WSC following drought or combined drought and heat stress in some genotypes, while in other genotypes both stresses altered the balance between WSC and starch concentrations. WSC were predominantly allocated to the spike in modern Australian varieties (28-50% of total WSC in the main stem), whereas the stem contained most WSC in older genotypes (67-87%). Drought and combined drought and heat stress increased WSC partitioning to the spike in older genotypes but not in the modern varieties. Ability to maintain transpiration, especially following combined drought and heat stress, appears essential for maintaining wheat productivity.

Transcripts of wheat at a target locus on chromosome 6B associated with increased yield, leaf mass and chlorophyll index under combined drought and heat stress.

Drought and heat stress constrain wheat (Triticum aestivum L.) yields globally. To identify putative mechanisms and candidate genes associated with combined drought and heat stress tolerance, we developed bread wheat near-isogenic lines (NILs) targeting a quantitative trait locus (QTL) on chromosome 6B which was previously associated with combined drought and heat stress tolerance in a diverse panel of wheats. Genotyping-by-sequencing was used to identify additional regions that segregated in allelic pairs between the recurrent and the introduced exotic parent, genome-wide. NILs were phenotyped in a gravimetric platform with precision irrigation and exposed to either drought or to combined drought and heat stress from three days after anthesis. An increase in grain weight in NILs carrying the exotic allele at 6B locus was associated with thicker, greener leaves, higher photosynthetic capacity and increased water use index after re-watering. RNA sequencing of developing grains at early and later stages of treatment revealed 75 genes that were differentially expressed between NILs across both treatments and timepoints. Differentially expressed genes coincided with the targeted QTL on chromosome 6B and regions of genetic segregation on chromosomes 1B and 7A. Pathway enrichment analysis showed the involvement of these genes in cell and gene regulation, metabolism of amino acids and transport of carbohydrates. The majority of these genes have not been characterized previously under drought or heat stress and they might serve as candidate genes for improved abiotic stress tolerance.

The Performances of Hyperspectral Sensors for Proximal Sensing of Nitrogen Levels in Wheat.

The accurate and high throughput quantification of nitrogen (N) content in wheat using non-destructive methods is an important step towards identifying wheat lines with high nitrogen use efficiency and informing agronomic management practices. Among various plant phenotyping methods, hyperspectral sensing has shown promise in providing accurate measurements in a fast and non-destructive manner. Past applications have utilised non-imaging instruments, such as spectrometers, while more recent approaches have expanded to hyperspectral cameras operating in different wavelength ranges and at various spectral resolutions. However, despite the success of previous hyperspectral applications, some important research questions regarding hyperspectral sensors with different wavelength centres and bandwidths remain unanswered, limiting wide application of this technology. This study evaluated the capability of hyperspectral imaging and non-imaging sensors to estimate N content in wheat leaves by comparing three hyperspectral cameras and a non-imaging spectrometer. This study answered the following questions: (1) How do hyperspectral sensors with different system setups perform when conducting proximal sensing of N in wheat leaves and what aspects have to be considered for optimal results? (2) What types of photonic detectors are most sensitive to N in wheat leaves? (3) How do the spectral resolutions of different instruments affect N measurement in wheat leaves? (4) What are the key-wavelengths with the highest correlation to N in wheat? Our study demonstrated that hyperspectral imaging systems with satisfactory system setups can be used to conduct proximal sensing of N content in wheat with sufficient accuracy. The proposed approach could reduce the need for chemical analysis of leaf tissue and lead to high-throughput estimation of N in wheat. The methodologies here could also be validated on other plants with different characteristics. The results can provide a reference for users wishing to measure N content at either plant- or leaf-scales using hyperspectral sensors.

Smoothing and extraction of traits in the growth analysis of noninvasive phenotypic data.

BACKGROUND: Non-destructive high-throughput plant phenotyping is becoming increasingly used and various methods for growth analysis have been proposed. Traditional longitudinal or repeated measures analyses that model growth using statistical models are common. However, often the variation in the data is inappropriately modelled, in part because the required models are complicated and difficult to fit. We provide a novel, computationally efficient technique that is based on smoothing and extraction of traits (SET), which we compare with the alternative traditional longitudinal analysis methods. RESULTS: The SET-based and longitudinal analyses were applied to a tomato experiment to investigate the effects on plant growth of zinc (Zn) addition and growing plants in soil inoculated with arbuscular mycorrhizal fungi (AMF). Conclusions from the SET-based and longitudinal analyses are similar, although the former analysis results in more significant differences. They showed that added Zn had little effect on plants grown in inoculated soils, but that growth depended on the amount of added Zn for plants grown in uninoculated soils. The longitudinal analysis of the unsmoothed data fitted a mixed model that involved both fixed and random regression modelling with splines, as well as allowing for unequal variances and autocorrelation between time points. CONCLUSIONS: A SET-based analysis can be used in any situation in which a traditional longitudinal analysis might be applied, especially when there are many observed time points. Two reasons for deploying the SET-based method are (i) biologically relevant growth parameters are required that parsimoniously describe growth, usually focussing on a small number of intervals, and/or (ii) a computationally efficient method is required for which a valid analysis is easier to achieve, while still capturing the essential features of the exhibited growth dynamics. Also discussed are the statistical models that need to be considered for traditional longitudinal analyses and it is demonstrated that the oft-omitted unequal variances and autocorrelation may be required for a valid longitudinal analysis. With respect to the separate issue of the subjective choice of mathematical growth functions or splines to characterize growth, it is recommended that, for both SET-based and longitudinal analyses, an evidence-based procedure is adopted.

Drought and heat stress tolerance screening in wheat using computed tomography.

BACKGROUND: Improving abiotic stress tolerance in wheat requires large scale screening of yield components such as seed weight, seed number and single seed weight, all of which is very laborious, and a detailed analysis of seed morphology is time-consuming and visually often impossible. Computed tomography offers the opportunity for much faster and more accurate assessment of yield components. RESULTS: An X-ray computed tomographic analysis was carried out on 203 very diverse wheat accessions which have been exposed to either drought or combined drought and heat stress. Results demonstrated that our computed tomography pipeline was capable of evaluating grain set with an accuracy of 95-99%. Most accessions exposed to combined drought and heat stress developed smaller, shrivelled seeds with an increased seed surface. As expected, seed weight and seed number per ear as well as single seed size were significantly reduced under combined drought and heat compared to drought alone. Seed weight along the ear was significantly reduced at the top and bottom of the wheat spike. CONCLUSIONS: We were able to establish a pipeline with a higher throughput with scanning times of 7 min per ear and accuracy than previous pipelines predicting a set of agronomical important seed traits and to visualize even more complex traits such as seed deformations. The pipeline presented here could be scaled up to use for high throughput, high resolution phenotyping of tens of thousands of heads, greatly accelerating breeding efforts to improve abiotic stress tolerance.

Variable water cycles have a greater impact on wheat growth and soil nitrogen response than constant watering.

Current climate change models project that water availability will become more erratic in the future. With soil nitrogen (N) supply coupled to water availability, it is important to understand the combined effects of variable water and N supply on food crop plants (above- and below-ground). Here we present a study that precisely controls soil moisture and compares stable soil moisture contents with a controlled wetting-drying cycle. Our aim was to identify how changes in soil moisture and N concentration affect shoot-root biomass, N acquisition in wheat, and soil N cycling. Using a novel gravimetric platform allowing fine-scale control of soil moisture dynamics, a 3 × 3 factorial experiment was conducted on wheat plants subjected to three rates of N application (0, 25 and 75 mg N/kg soil) and three soil moisture regimes (two uniform treatments: 23.5 and 13% gravimetric moisture content (herein referred to as Well-watered and Reduced water, respectively), and a Variable treatment which cycled between the two). Plant biomass, soil N and microbial biomass carbon were measured at three developmental stages: tillering (Harvest 1), flowering (Harvest 2), and early grain milk development (Harvest 3). Reduced water supply encouraged root growth when combined with medium and high N. Plant growth was more responsive to N than the water treatments imposed, with a 15-fold increase in biomass between the high and no added N treatment plants. Both uniform soil water treatments resulted in similar plant biomass, while the Variable water treatment resulted in less biomass overall, suggesting wheat prefers consistency whether at a Well-watered or Reduced water level. Plants did not respond well to variable soil moisture, highlighting the need to understand plant adaptation and biomass allocation with resource limitation. This is particularly relevant to developing irrigation practices, but also in the design of water availability experiments.

The Interplay Between Water Limitation, Dhurrin, and Nitrate in the Low-Cyanogenic Sorghum Mutant adult cyanide deficient class 1.

Sorghum bicolor (L.) Moench produces the nitrogen-containing natural product dhurrin that provides chemical defense against herbivores and pathogens via the release of toxic hydrogen cyanide gas. Drought can increase dhurrin in shoot tissues to concentrations toxic to livestock. As dhurrin is also a remobilizable store of reduced nitrogen and plays a role in stress mitigation, reductions in dhurrin may come at a cost to plant growth and stress tolerance. Here, we investigated the response to an extended period of water limitation in a unique EMS-mutant adult cyanide deficient class 1 (acdc1) that has a low dhurrin content in the leaves of mature plants. A mutant sibling line was included to assess the impact of unknown background mutations. Plants were grown under three watering regimes using a gravimetric platform, with growth parameters and dhurrin and nitrate concentrations assessed over four successive harvests. Tissue type was an important determinant of dhurrin and nitrate concentrations, with the response to water limitation differing between above and below ground tissues. Water limitation increased dhurrin concentration in the acdc1 shoots to the same extent as in wild-type plants and no growth advantage or disadvantage between the lines was observed. Lower dhurrin concentrations in the acdc1 leaf tissue when fully watered correlated with an increase in nitrate content in the shoot and roots of the mutant. In targeted breeding efforts to down-regulate dhurrin concentration, parallel effects on the level of stored nitrates should be considered in all vegetative tissues of this important forage crop to avoid potential toxic effects.

The Development of Hyperspectral Distribution Maps to Predict the Content and Distribution of Nitrogen and Water in Wheat (Triticum aestivum).

Quantifying plant water content and nitrogen levels and determining water and nitrogen phenotypes is important for crop management and achieving optimal yield and quality. Hyperspectral methods have the potential to advance high throughput phenotyping efforts by providing a rapid, accurate, and nondestructive alternative for estimating biochemical and physiological plant traits. Our study (i) acquired hyperspectral images of wheat plants using a high throughput phenotyping system, (ii) developed regression models capable of predicting water and nitrogen levels of wheat plants, and (iii) applied the regression coefficients from the best-performing models to hyperspectral images in order to develop prediction maps to visualize nitrogen and water distribution within plants. Hyperspectral images were collected of four wheat (Triticum aestivum) genotypes grown in nine soil nutrient conditions and under two water treatments. Five multivariate regression methods in combination with 10 spectral preprocessing techniques were employed to find a model with strong predictive performance. Visible and near infrared wavelengths (VNIR: 400-1,000nm) alone were not sufficient to accurately predict water and nitrogen content (validation R2 = 0.56 and R2 = 0.59, respectively) but model accuracy was improved when shortwave-infrared wavelengths (SWIR: 1,000-2,500nm) were incorporated (validation R2 = 0.63 and R2 = 0.66, respectively). Wavelength reduction produced equivalent model accuracies while reducing model size and complexity (validation R2 = 0.69 and R2 = 0.66 for water and nitrogen, respectively). Developed distribution maps provided a visual representation of the concentration and distribution of water within plants while nitrogen maps seemed to suffer from noise. The findings and methods from this study demonstrate the high potential of high-throughput hyperspectral imagery for estimating and visualizing the distribution of plant chemical properties.

Resource allocation to growth or luxury consumption drives mycorrhizal responses.

Highly variable phenotypic responses in mycorrhizal plants challenge our functional understanding of plant-fungal mutualisms. Using non-invasive high-throughput phenotyping, we observed that arbuscular mycorrhizal (AM) fungi relieved phosphorus (P) limitation and enhanced growth of Brachypodium distachyon under P-limited conditions, while photosynthetic limitation under low nitrogen (N) was exacerbated by the fungus. However, these responses were strongly dependent on host genotype: only the faster growing genotype (Bd3-1) utilised P transferred from the fungus to achieve improved growth under P-limited conditions. Under low N, the slower growing genotype (Bd21) had a carbon and N surplus that was linked to a less negative growth response compared with the faster growing genotype. These responses were linked to the regulation of N : P stoichiometry, couples resource allocation to growth or luxury consumption in diverse plant lineages. Our results attest strongly to a mechanism in plants by which plant genotype-specific resource economics drive phenotypic outcomes during AM symbioses.

Estimation of vegetation indices for high-throughput phenotyping of wheat using aerial imaging.

BACKGROUND: Unmanned aerial vehicles offer the opportunity for precision agriculture to efficiently monitor agricultural land. A vegetation index (VI) derived from an aerially observed multispectral image (MSI) can quantify crop health, moisture and nutrient content. However, due to the high cost of multispectral sensors, alternate, low-cost solutions have lately received great interest. We present a novel method for model-based estimation of a VI using RGB color images. The non-linear spatio-spectral relationship between the RGB image of vegetation and the index computed by its corresponding MSI is learned through deep neural networks. The learned models can be used to estimate VI of a crop segment. RESULTS: Analysis of images obtained in wheat breeding trials show that the aerially observed VI was highly correlated with ground-measured VI. In addition, VI estimates based on RGB images were highly correlated with VI deduced from MSIs. Spatial, spectral and temporal information of images contributed to estimation of VI. Both intra-variety and inter-variety differences were preserved by estimated VI. However, VI estimates were reliable until just before significant appearance of senescence. CONCLUSION: The proposed approach validates that it is reasonable to accurately estimate VI using deep neural networks. The results prove that RGB images contain sufficient information for VI estimation. It demonstrates that low-cost VI measurement is possible with standard RGB cameras.

Integrated genomics, physiology and breeding approaches for improving nitrogen use efficiency in potato: translating knowledge from other crops.

Potato plays a key role in global food and nutritional security. Potato is an N fertiliser-responsive crop, producing high tuber yields. However, excessive use of N can result in environmental damage and high production costs, hence improving nitrogen use efficiency (NUE) of potato plants is one of the sustainable options to address these issues and increase yield. Advanced efforts have been undertaken to improve NUE in other plants like Arabidopsis, rice, wheat and maize through molecular and physiological approaches. Conversely, in potato, NUE studies have predominantly focussed on agronomy or soil management, except for a few researchers who have measured gene expression and proteins relevant to N uptake or metabolism. The focus of this review is to adapt knowledge gained from other plants to inform investigation of N metabolism and associated traits in potato with the aim of improving potato NUE using integrated genomics, physiology and breeding methods.

Nitrate uptake and its regulation in relation to improving nitrogen use efficiency in cereals.

On average less than half of the applied N is captured by crops, thus there is scope and need to improve N uptake in cereals. With nitrate (NO3-) being the main form of N available to cereal crops there has been a significant global research effort to understand plant NO3- uptake. Despite this, our knowledge of the NO3- uptake system is not sufficient to easily target ways to improve NO3- uptake. Based on this there is an identified need to better understand the NO3- uptake system and the signalling molecules that modulate it. With strong transcriptional control governing the NO3- uptake system, we also need new leads for modulating transcription of NO3- transporter genes.

Transition from a maternal to external nitrogen source in maize seedlings.

Maximizing NO3- uptake during seedling development is important as it has a major influence on plant growth and yield. However, little is known about the processes leading to, and involved in, the initiation of root NO3- uptake capacity in developing seedlings. This study examines the physiological processes involved in root NO3- uptake and metabolism, to gain an understanding of how the NO3- uptake system responds to meet demand as maize seedlings transition from seed N use to external N capture. The concentrations of seed-derived free amino acids within root and shoot tissues are initially high, but decrease rapidly until stabilizing eight days after imbibition (DAI). Similarly, shoot N% decreases, but does not stabilize until 12-13 DAI. Following the decrease in free amino acid concentrations, root NO3- uptake capacity increases until shoot N% stabilizes. The increase in root NO3- uptake capacity corresponds with a rapid rise in transcript levels of putative NO3- transporters, ZmNRT2.1 and ZmNRT2.2. The processes underlying the increase in root NO3- uptake capacity to meet N demand provide an insight into the processes controlling N uptake.

Nitrogen assimilation system in maize is regulated by developmental and tissue-specific mechanisms.

KEY MESSAGE: We found metabolites, enzyme activities and enzyme transcript abundances vary significantly across the maize lifecycle, but weak correlation exists between the three groups. We identified putative genes regulating nitrate assimilation. Progress in improving nitrogen (N) use efficiency (NUE) of crop plants has been hampered by the complexity of the N uptake and utilisation systems. To understand this complexity we measured the activities of seven enzymes and ten metabolites related to N metabolism in the leaf and root tissues of Gaspe Flint maize plants grown in 0.5 or 2.5 mM NO3 (-) throughout the lifecycle. The amino acids had remarkably similar profiles across the lifecycle except for transient responses, which only appeared in the leaves for aspartate or in the roots for asparagine, serine and glycine. The activities of the enzymes for N assimilation were also coordinated to a certain degree, most noticeably with a peak in root activity late in the lifecycle, but with wide variation in the activity levels over the course of development. We analysed the transcriptional data for gene sets encoding the measured enzymes and found that, unlike the enzyme activities, transcript levels of the corresponding genes did not exhibit the same coordination across the lifecycle and were only weakly correlated with the levels of various amino acids or individual enzyme activities. We identified gene sets which were correlated with the enzyme activity profiles, including seven genes located within previously known quantitative trait loci for enzyme activities and hypothesise that these genes are important for the regulation of enzyme activities. This work provides insights into the complexity of the N assimilation system throughout development and identifies candidate regulatory genes, which warrant further investigation in efforts to improve NUE in crop plants.

Maize maintains growth in response to decreased nitrate supply through a highly dynamic and developmental stage-specific transcriptional response.

Elucidation of the gene networks underlying the response to N supply and demand will facilitate the improvement of the N uptake efficiency of plants. We undertook a transcriptomic analysis of maize to identify genes responding to both a non-growth-limiting decrease in NO3- provision and to development-based N demand changes at seven representative points across the life cycle. Gene co-expression networks were derived by cluster analysis of the transcript profiles. The majority of NO3--responsive transcription occurred at 11 (D11), 18 (D18) and 29 (D29) days after emergence, with differential expression predominating in the root at D11 and D29 and in the leaf at D18. A cluster of 98 probe sets was identified, the expression pattern of which is similar to that of the high-affinity NO3- transporter (NRT2) genes across the life cycle. The cluster is enriched with genes encoding enzymes and proteins of lipid metabolism and transport, respectively. These are candidate genes for the response of maize to N supply and demand. Only a few patterns of differential gene expression were observed over the entire life cycle; however, the composition of the classes of the genes differentially regulated at individual time points was unique, suggesting tightly controlled regulation of NO3--responsive gene expression.

Variation for N Uptake System in Maize: Genotypic Response to N Supply.

An understanding of the adaptations made by plants in their nitrogen (N) uptake systems in response to reduced N supply is important to the development of cereals with enhanced N uptake efficiency (NUpE). Twenty seven diverse genotypes of maize (Zea mays, L.) were grown in hydroponics for 3 weeks with limiting or adequate N supply. Genotypic response to N was assessed on the basis of biomass characteristics and the activities of the nitrate ([Formula: see text]) and ammonium ([Formula: see text]) high-affinity transport systems. Genotypes differed greatly for the ability to maintain biomass with reduced N. Although, the N response in underlying biomass and N transport related characteristics was less than that for biomass, there were clear relationships, most importantly, lines that maintained biomass at reduced N maintained net N uptake with no change in size of the root relative to the shoot. The root uptake capacity for both [Formula: see text] and [Formula: see text] increased with reduced N. Transcript levels of putative [Formula: see text] and [Formula: see text] transporter genes in the root tissue of a subset of the genotypes revealed that predominately ZmNRT2 transcript levels responded to N treatments. The correlation between the ratio of transcripts of ZmNRT2.2 between the two N levels and a genotype's ability to maintain biomass with reduced N suggests a role for these transporters in enhancing NUpE. The observed variation in the ability to capture N at low N provides scope for both improving NUpE in maize and also to better understand the N uptake system in cereals.

Genetic approaches to enhancing nitrogen-use efficiency (NUE) in cereals: challenges and future directions.

Over 100million tonnes of nitrogen (N) fertiliser are applied globally each year to maintain high yields in agricultural crops. The rising price of N fertilisers has made them a major cost for farmers. Inefficient use of N fertiliser leads to substantial environmental problems through contamination of air and water resources and can be a significant economic cost. Consequently, there is considerable need to improve the way N fertiliser is used in farming systems. The efficiency with which crops use applied N fertiliser - the nitrogen-use efficiency (NUE) - is currently quite low for cereals. This is the case in both high yielding environments and lower yielding environments characteristic of cereal growing regions of Australia. Multiple studies have attempted to identify the genetic basis of NUE, but the utility of the results is limited because of the complex nature of the trait and the magnitude of genotype by environment interaction. Transgenic approaches have been applied to improve plant NUE but with limited success, due, in part, to a combination of the complexity of the trait but also due to lack of accurate phenotyping methods. This review documents these two approaches and suggests future directions in improving cereal NUE with a focus on the Australian cereal industry.

The response of the maize nitrate transport system to nitrogen demand and supply across the lifecycle.

An understanding of nitrate (NO3-) uptake throughout the lifecycle of plants, and how this process responds to nitrogen (N) availability, is an important step towards the development of plants with improved nitrogen use efficiency (NUE). NO3- uptake capacity and transcript levels of putative high- and low-affinity NO3- transporters (NRTs) were profiled across the lifecycle of dwarf maize (Zea mays) plants grown at reduced and adequate NO3-. Plants showed major changes in high-affinity NO3- uptake capacity across the lifecycle, which varied with changing relative growth rates of roots and shoots. Transcript abundances of putative high-affinity NRTs (predominantly ZmNRT2.1 and ZmNRT2.2) were correlated with two distinct peaks in high-affinity root NO3- uptake capacity and also N availability. The reduction in NO3- supply during the lifecycle led to a dramatic increase in NO3- uptake capacity, which preceded changes in transcript levels of NRTs, suggesting a model with short-term post-translational regulation and longer term transcriptional regulation of NO3- uptake capacity. These observations offer new insight into the control of NO3- uptake by both plant developmental processes and N availability, and identify key control points that may be targeted by future plant improvement programmes to enhance N uptake relative to availability and/or demand.

Rice DUR3 mediates high-affinity urea transport and plays an effective role in improvement of urea acquisition and utilization when expressed in Arabidopsis.

• Despite the great agricultural and ecological importance of efficient use of urea-containing nitrogen fertilizers by crops, molecular and physiological identities of urea transport in higher plants have been investigated only in Arabidopsis. • We performed short-time urea-influx assays which have identified a low-affinity and high-affinity (K(m) of 7.55 µM) transport system for urea-uptake by rice roots (Oryza sativa). • A high-affinity urea transporter OsDUR3 from rice was functionally characterized here for the first time among crops. OsDUR3 encodes an integral membrane-protein with 721 amino acid residues and 15 predicted transmembrane domains. Heterologous expression demonstrated that OsDUR3 restored yeast dur3-mutant growth on urea and facilitated urea import with a K(m) of c. 10 µM in Xenopus oocytes. • Quantitative reverse-transcription polymerase chain reaction (qPCR) analysis revealed upregulation of OsDUR3 in rice roots under nitrogen-deficiency and urea-resupply after nitrogen-starvation. Importantly, overexpression of OsDUR3 complemented the Arabidopsis atdur3-1 mutant, improving growth on low urea and increasing root urea-uptake markedly. Together with its plasma membrane localization detected by green fluorescent protein (GFP)-tagging and with findings that disruption of OsDUR3 by T-DNA reduces rice growth on urea and urea uptake, we suggest that OsDUR3 is an active urea transporter that plays a significant role in effective urea acquisition and utilisation in rice.