Assessing yield gap in high productive countries by designing wheat ideotypes

Reproductive resilience of growth and nitrogen uptake underpins yield improvement in winter wheat with forced delay of sowing

Winter wheat production is influenced by climate extremes worldwide. Heavy precipitation induced delay of sowing generates limited photothermal resources for wheat early growth. However, how wheat build resilience from stunted seedling growth has not been fully explored. Here, a twelve-year farmers' survey of wheat yield was recorded and four-year field experiments of wheat grown in normal and late-sowing were performed under zero nitrogen (N0) and optimum nitrogen (Opt.N) supply. Wheat growth and N uptake were measured at both vegetative and reproductive stages alongside photothermal resource-use efficiency. Farmers' survey showed 10.4 % yield losses due to delayed sowing compared to the normal. However, four-year field trials revealed that the combination of increasing seeding rates and Opt.N application recovered grain yield of sowing-delayed wheat and even increased by 13.2 % compared to plants in the normal seasons. Although delayed sowing substantially suppressed seedling growth and tillering before winter dormancy, the Opt.N application increased spring tillers by 2.4-fold which were productive at maturity. Further, plant growth and N uptake from jointing to anthesis of sowing-delayed wheat were accelerated by Opt.N, but not by N0 treatment. Delayed sowing significantly shortened the duration of lag phase of grain filling by 3.5 days and by 183 growing degree days compared with the normal, which initiated the linear and fast filling earlier. Increased leaf photosynthesis by 27.4 % during grain filling further supported the fast recovery of grain filling in the sowing-delayed wheat. Concomitantly, the physiological N-use efficiency increased by 46.7 % during grain filling and by 41.5 % at maturity by enhancing N availability and seeding rates, and photothermal resource-use efficiency increased by 1.3- to 1.7-fold for wheat with delayed vs. normal sowing. Overall, these findings highlight the integrated management of nutrient and cultivation to mitigate the impacts of climate extremes on crop productivity through building plant reproductive resilience.

Defining durum wheat ideotypes adapted to Mediterranean environments through remote sensing traits

An acceleration of the genetic advances of durum wheat, as a major crop for the Mediterranean region, is required, but phenotyping still represents a bottleneck for breeding. This study aims to define durum wheat ideotypes under Mediterranean conditions by selecting the most suitable phenotypic remote sensing traits among different ones informing on characteristics related with leaf pigments/photosynthetic status, crop water status, and crop growth/green biomass. A set of 24 post-green revolution durum wheat cultivars were assessed in a wide set of 19 environments, accounted as the specific combinations of a range of latitudes in Spain, under different management conditions (water regimes and planting dates), through 3 consecutive years. Thus, red-green-blue and multispectral derived vegetation indices and canopy temperature were evaluated at anthesis and grain filling. The potential of the assessed remote sensing parameters alone and all combined as grain yield (GY) predictors was evaluated through random forest regression models performed for each environment and phenological stage. Biomass and plot greenness indicators consistently proved to be reliable GY predictors in all of the environments tested for both phenological stages. For the lowest-yielding environment, the contribution of water status measurements was higher during anthesis, whereas, for the highest-yielding environments, better predictions were reported during grain filling. Remote sensing traits measured during the grain filling and informing on pigment content and photosynthetic capacity were highlighted under the environments with warmer conditions, as the late-planting treatments. Overall, canopy greenness indicators were reported as the highest correlated traits for most of the environments and regardless of the phenological moment assessed. The addition of carbon isotope composition of mature kernels was attempted to increase the accuracies, but only a few were slightly benefited, as differences in water status among cultivars were already accounted by the measurement of canopy temperature.

More than 1000 genotypes are required to derive robust relationships between yield, yield stability and physiological parameters: a computational study on wheat crop

Using in silico experiment in crop model, we identified different physiological regulations of yield and yield stability, as well as quantify the genotype and environment numbers required for analysing yield stability convincingly. Identifying target traits for breeding stable and high-yielded cultivars simultaneously is difficult due to limited knowledge of physiological mechanisms behind yield stability. Besides, there is no consensus about the adequacy of a stability index (SI) and the minimal number of environments and genotypes required for evaluating yield stability. We studied this question using the crop model APSIM-Wheat to simulate 9100 virtual genotypes grown under 9000 environments. By analysing the simulated data, we showed that the shape of phenotype distributions affected the correlation between SI and mean yield and the genotypic superiority measure (P_i) was least affected among 11 SI. P_i was used as index to demonstrate that more than 150 environments were required to estimate yield stability of a genotype convincingly and more than 1000 genotypes were necessary to evaluate the contribution of a physiological parameter to yield stability. Network analyses suggested that a physiological parameter contributed preferentially to yield or P_i. For example, soil water absorption efficiency and potential grain filling rate explained better the variations in yield than in P_i; while light extinction coefficient and radiation use efficiency were more correlated with P_i than with yield. The high number of genotypes and environments required for studying P_i highlight the necessity and potential of in silico experiments to better understand the mechanisms behind yield stability.

Identification of agro-physiological traits of lentil that reduce risks of drought

Ideotype breeding is an essential approach for selection of desired combination of plant traits for testing in crop growth model for potential yield gain in specific environments and management practices. Here we parameterized plant traits for untested lentil cultivars for the APSIM-lentil model in phenology, biomass, and seed yield. We then tested these against independent data and applied the model in an extrapolated analysis (i) to assess the impact of drought on productivity across different rainfall environments; (ii) to identify impactful plant traits and (iii) to design new lentil ideotypes with a combination of desirable traits that mitigate the impact of drought, in the context of various agronomic practices across a wide range of production environments. Desirable phenological and physiological traits related to yield were identified with RUE having the greatest effect on yield followed by HI rate. Leaf size significantly affected seed yield (p< 0.05) more than phenological phases. The physiological traits were integrated into four ideotype designs applied to two baseline cultivars (PBA Hallmark XT and PBA Jumbo2) providing eight ideotypes. We identified a combination of genetic traits that promises a yield advantage of around 10% against our current cultivars PBA Hallmark XT and PBA Jumbo2. Under drought conditions, our ideotypes achieved 5 to 25% yield advantages without stubble and 20 to 40% yield advantages with stubble residues. This shows the importance of genetic screening under realistic production conditions (e.g., stubble retention in particular environments). Such screening is aided by the employment of biophysical models that incorporate both genetic and agronomic variables that focus on successful traits in combination, to reduce the impact of drought in the development of new cultivars for various environments. Stubble retention was found to be a major agronomic contributor to high yield in water-limiting environments and this contribution declined with increasing growing season rainfall. In mid- and high-rainfall environments, the key drivers of yield were time of sowing, physiological traits and soil type. Overall, the agronomic practices, namely, early sowing, residue retention and narrow row spacing deceased the impact of drought when combined with improved physiological traits of the ideotypes based on long term climate data.

Dehydration Stress Memory Genes in Triticum turgidum L. ssp. durum (Desf.)

Exposure to successive stress cycles can result in a variety of memory response patterns in several plant species. We have investigated a group of these patterns at both the transcriptional and physiological memory levels in durum wheat. The data revealed huge discrepancies between investigated durum wheat cultivars, which presumably are all drought tolerant. It was possible to generate a consensus memory response pattern for each cultivar, where Hourani 27 was the most tolerant followed by Balikh 2 and then Omrabi 5. When durum wheat homologs from rice and maize were compared, only 18% gave similar memory response patterns. The data would indicate the presence of potentially divergent memory mechanisms in different plant species and genotypes. Ultimately, a thorough examination is required for each genotype before giving solid memory-based conclusions that can be applied in plant breeding and agricultural management practices.

Global wheat production could benefit from closing the genetic yield gap

Global food security requires food production to be increased in the coming decades. The closure of any existing genetic yield gap (Y_ig) by genetic improvement could increase crop yield potential and global production. Here we estimated present global wheat Y_ig, covering all wheat-growing environments and major producers, by optimizing local wheat cultivars using the wheat model Sirius. The estimated mean global Y_ig was 51%, implying that global wheat production could benefit greatly from exploiting the untapped global Y_ig through the use of optimal cultivar designs, utilization of the vast variation available in wheat genetic resources, application of modern advanced breeding tools, and continuous improvements of crop and soil management.

Genetic Yield Gains and Changes in Morphophysiological-Related Traits of Winter Wheat in Southern Chilean High-Yielding Environments

Both the temperate-humid zone and the southern part of the Mediterranean climate region of Chile are characterized by high wheat productivity. Study objectives were to analyze the yield potential, yield progress, and genetic progress of the winter bread wheat (Triticum aestivum L.) cultivars and changes in agronomic and morphophysiological traits during the past 60 years. Thus, two field experiments: (a) yield potential and (b) yield genetic progress trials were conducted in high-yielding environments of central-southern Chile during the 2018/2019 and 2019/2020 seasons. In addition, yield progress was analyzed using yield historical data of a high-yielding environment from 1957 to 2017. Potential yield trials showed that, at the most favorable sites, grain yield reached ∼20.46 Mg ha-1. The prolonged growing and grain filling period, mild temperatures in December-January, ample water availability, and favorable soil conditions explain this high-potential yield. Yield progress analysis indicated that average grain yield increased from 2.70 Mg ha-1 in 1959 to 12.90 Mg ha-1 in 2017, with a 128.8 kg ha-1 per-year increase due to favorable soil and climatic conditions. For genetic progress trials, genetic gain in grain yield from 1965 to 2019 was 70.20 kg ha-1 (0.49%) per year, representing around 55% of the yield progress. Results revealed that the genetic gains in grain yield were related to increases in biomass partitioning toward reproductive organs, without significant increases in Shoot DW production. In addition, reducing trends in the NDVI, the fraction of intercepted PAR, the intercepted PAR (form emergence to heading), and the RGB-derived vegetation indices with the year of cultivar release were detected. These decreases could be due to the erectophile leaf habit, which enhanced photosynthetic activity, and thus grain yield increased. Also, senescence of bottom canopy leaves (starting from booting) could be involved by decreasing the ability of spectral and RGB-derived vegetation indices to capture the characteristics of green biomass after the booting stage. Contrary, a positive correlation was detected for intercepted PAR from heading to maturity, which could be due to a stay-green mechanism, supported by the trend of positive correlations of Chlorophyll content with the year of cultivar release.

Local impacts of climate change on winter wheat in Great Britain

Under future CMIP5 climate change scenarios for 2050, an increase in wheat yield of about 10% is predicted in Great Britain (GB) as a result of the combined effect of CO2 fertilization and a shift in phenology. Compared to the present day, crops escape increases in the climate impacts of drought and heat stresses on grain yield by developing before these stresses can occur. In the future, yield losses from water stress over a growing season will remain about the same across Great Britain with losses reaching around 20% of potential yield, while losses from drought around flowering will decrease and account for about 9% of water limited yield. Yield losses from heat stress around flowering will remain negligible in the future. These conclusions are drawn from a modelling study based on the response of the Sirius wheat simulation model to local-scale 2050-climate scenarios derived from 19 Global Climate Models from the CMIP5 ensemble at 25 locations representing current or potential wheat-growing areas in GB. However, depending on susceptibility to water stress, substantial interannual yield variation between locations is predicted, in some cases suggesting low wheat yield stability. For this reason, local-scale studies should be performed to evaluate uncertainties in yield prediction related to future weather patterns.

Phenotyping for drought resistance in bread wheat using physiological and biochemical traits

Drought is one of the most prominent limiting factors that negatively affect crop productivity by manipulating its physiological pathway. One hundred twenty diverse bread wheat genotypes were used in a pot experiment to explore the relationship among their fifteen physio-biochemical traits (PBT) by using multivariate analysis, heatmapping and stress tolerance index (STI) for grain yield as a marker trait to identify high yielding genotype with maximum stress tolerance capability. Increased proline and sugar accumulation were observed from control to moisture deficient environments by 159% and 122%, respectively. Moreover, leaf membrane stability index (LMSI), leaf relative water content (LRWC), relative dry weight (RDW), chlorophyll content, leaf surface area (LSA), Leaf succulence (LS), canopy temperature depression (CTD), relative excised leaf water loss (RELWL) and leaf osmotic potential (LOP) showed significantly decreasing trend in drought stress treatment as compared to well-watered plants by -21%, -21%, -34%, -22%, -38%, -37%, -46%, -18% and -35% respectively. Additionally, principal component analysis and genotype by trait biplot analysis showed that initial 7 principal components (PC1 to PC7) represented 77.27% and 79.02% of total cumulative variation under control and drought stress respectively. Genotypic-Phenotypic correlation revealed that most of the attributes were higher in case of genotypic correlation component (rg) as compared to the phenotypic correlation component (rp) indicating more genetic association between traits. The darker and lighter colour scale produced by heatmap exhibited contrasting nature of genotypes, as positive side with higher values represented drought resistance while values on the negative side with lower values showed susceptible performance of genotypes. Our results concluded that the studied PBT associated with STI for grain yield are the main factors which may contribute in improved productivity of wheat crop and if these traits show appropriate performance under stress condition the crop will show the more productive returns under changing climate.

Small-Scale Variation in Nitrogen Use Efficiency Parameters in Winter Wheat as Affected by N Fertilization and Tillage Intensity

Limited information exists on how tillage and nitrogen (N) fertilization affects small-scale variation in nitrogen use efficiency (NUE) and crop performance. In a two-year field study under temperate conditions, we investigated how tillage (NT, no-tillage; CT, conventional tillage) and N fertilization affected the small-scale variation in NUE and winter wheat performance (grain yield, Gw; grain protein concentration, GPC). A randomized complete block design with three replications was used. Within each tillage plot (12 × 35 m2), N rates (0, 50, 100, 150, 200, 250 kg N ha−1) were completely randomized within each of four groups of microplots (1.5 × 1.5 m2). Early-season soil mineral N (Nmin) was also monitored in both years. At rates < 150 kg N ha−1, NT was not competitive with CT in terms of Gw and NUE. Gw and aboveground plant N were not correlated with Nmin prior to application of N fertilizer. NT usually led to larger spatial heterogeneity of Nmin, Gw, and NUE. The small-scale variability of Gw, GPC, NUE, and N supply decreased with increasing N fertilization rates under both tillage systems. Significant increases in Gw and GPC were observed with increasing N rates, whereas NUE decreased slightly with increasing N rates in both NT and CT. The overall moderate spatial variation in Nmin, Gw, and NUE did not justify site-specific N fertilization in these small fields, with the exception of the stony within-plot positions, which were not responsive to rates of N > 50 kg N ha−1.

Large genetic yield potential and genetic yield gap estimated for wheat in Europe

Improving yield potential and closing the yield gap are important to achieve global food security. Europe is the largest wheat producer, delivering about 35% of wheat globally, but European wheat's yield potential from genetic improvements is as yet unknown. We estimated wheat 'genetic yield potential', i.e. the yield of optimal or ideal genotypes in a target environment, across major wheat growing regions in Europe by designing in silico ideotypes. These ideotypes were optimised for current climatic conditions and based on optimal physiology, constrained by available genetic variation in target traits. A 'genetic yield gap' in a location was estimated as the difference between the yield potential of the optimal ideotype compared with a current, well-adapted cultivar. A large mean genetic yield potential (11-13 t ha-1) and genetic yield gap (3.5-5.2 t ha-1) were estimated under rainfed conditions in Europe. In other words, despite intensive wheat breeding efforts, current local cultivars were found to be far from their optimum, meaning that a large genetic yield gap still exists in European wheat. Heat and drought tolerance around flowering, optimal canopy structure and phenology, improved root water uptake and reduced leaf senescence under drought were identified as key traits for improvement. Closing this unexploited genetic yield gap in Europe through crop improvements and genetic adaptations could contribute towards global food security.