Non-foliar photosynthesis and nitrogen assimilation influence grain yield in durum wheat regardless of water conditions.

There is a need to generate improved crop varieties adapted to the ongoing changes in the climate. We studied durum wheat canopy and central metabolism of six different photosynthetic organs in two yield-contrasting varieties. The aim was to understand the mechanisms associated with the water stress response and yield performance. Water stress strongly reduced grain yield, plant biomass, and leaf photosynthesis, and down-regulated C/N-metabolism genes and key protein levels, which occurred mainly in leaf blades. By contrast, higher yield was associated with high ear dry weight and lower biomass and ears per area, highlighting the advantage of reduced tillering and the consequent improvement in sink strength, which promoted C/N metabolism at the whole plant level. An improved C metabolism in blades and ear bracts and N assimilation in all photosynthetic organs facilitated C/N remobilization to the grain and promoted yield. Therefore, we propose that further yield gains in Mediterranean conditions could be achieved by considering the source-sink dynamics and the contribution of non-foliar organs, and particularly N assimilation and remobilization during the late growth stages. We highlight the power of linking phenotyping with plant metabolism to identify novel traits at the whole plant level to support breeding programmes.

Field Plant Monitoring from Macro to Micro Scale: Feasibility and Validation of Combined Field Monitoring Approaches from Remote to in Vivo to Cope with Drought Stress in Tomato.

Monitoring plant growth and development during cultivation to optimize resource use efficiency is crucial to achieve an increased sustainability of agriculture systems and ensure food security. In this study, we compared field monitoring approaches from the macro to micro scale with the aim of developing novel in vivo tools for field phenotyping and advancing the efficiency of drought stress detection at the field level. To this end, we tested different methodologies in the monitoring of tomato growth under different water regimes: (i) micro-scale (inserted in the plant stem) real-time monitoring with an organic electrochemical transistor (OECT)-based sensor, namely a bioristor, that enables continuous monitoring of the plant; (ii) medium-scale (<1 m from the canopy) monitoring through red-green-blue (RGB) low-cost imaging; (iii) macro-scale multispectral and thermal monitoring using an unmanned aerial vehicle (UAV). High correlations between aerial and proximal remote sensing were found with chlorophyll-related indices, although at specific time points (NDVI and NDRE with GGA and SPAD). The ion concentration and allocation monitored by the index R of the bioristor during the drought defense response were highly correlated with the water use indices (Crop Water Stress Index (CSWI), relative water content (RWC), vapor pressure deficit (VPD)). A high negative correlation was observed with the CWSI and, in turn, with the RWC. Although proximal remote sensing measurements correlated well with water stress indices, vegetation indices provide information about the crop's status at a specific moment. Meanwhile, the bioristor continuously monitors the ion movements and the correlated water use during plant growth and development, making this tool a promising device for field monitoring.

The effects of microbial fertilizers application on growth, yield and some biochemical changes in the leaves and seeds of guar (Cyamopsis tetragonoloba L.).

Guar (Cyamopsis tetragonoloba L.) is a summer legume that is becoming a crucial industrial crop because of its high gum and protein content. Thus far, the combined effects of arbuscular mycorrhizal fungi (AMF) and Bradyrhizobium on the yield and chemical composition of guar plants are not well studied. Therefore, the current investigation was designed to estimate the individual as well as the combined effects of AMF and Bradyrhizobium on plant growth, yield and nutritional quality of seeds and leaves of guar. AMF and/or Bradyrhizobium inoculation improved chemical composition of guar seeds and its morpho-physiological (plant height, fresh weight, dry weight, and yield production) traits. In addition to increased guar growth and yield production, the inoculation of AMF and/or Bradyrhizobium increased guar leaf and seed minerals, fiber, lipids, crude protein and ash contents. At primary metabolites, there were increases in sugar levels including raffinose stachyose, verbascose and galactomannan. These increases in sugar provided a route for organic acids, amino acids and fatty acids production. Interestingly, there was an increase in essential amino acids and unsaturated fatty acids. At the bioactive secondary metabolite levels, biofertilizers improved phenols and flavonoids levels and anthocyanin and polyamines biosynthesis. In line with these increases, precursors of anthocyanin (phenylalanine, p-coumaric acid, and cinnamic acid) and the levels of polyamines (diaminopropane, putrescine, cadaverine, spermidine, spermine, and agmatine) were increased. Overall, for the first time, our study shed the light on how AMF and Bradyrhizobium improved guar yield and metabolism. Our findings suggested that the combined inoculation of AMF and Bradyrhizobium is an innovative approach to improve guar growth, yield production and yield quality.

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.

Analysis of durum wheat photosynthetic organs during grain filling reveals the ear as a water stress-tolerant organ and the peduncle as the largest pool of primary metabolites.

MAIN CONCLUSION: The pool of carbon- and nitrogen-rich metabolites is quantitatively relevant in non-foliar photosynthetic organs during grain filling, which have a better response to water limitation than flag leaves. The response of durum wheat to contrasting water regimes has been extensively studied at leaf and agronomic level in previous studies, but the water stress effects on source-sink dynamics, particularly non-foliar photosynthetic organs, is more limited. Our study aims to investigate the response of different photosynthetic organs to water stress and to quantify the pool of carbon and nitrogen metabolites available for grain filling. Five durum wheat varieties were grown in field trials in the Spanish region of Castile and León under irrigated and rainfed conditions. Water stress led to a significant decrease in yield, biomass, and carbon and nitrogen assimilation, improved water use efficiency, and modified grain quality traits in the five varieties. The pool of carbon (glucose, glucose-6-phosphate, fructose, sucrose, starch, and malate) and nitrogen (glutamate, amino acids, proteins and chlorophylls) metabolites in leaf blades and sheaths, peduncles, awns, glumes and lemmas were also analysed. The results showed that the metabolism of the blades and peduncles was the most susceptible to water stress, while ear metabolism showed higher stability, particularly at mid-grain filling. Interestingly, the total metabolite content per organ highlighted that a large source of nutrients, which may be directly involved in grain filling, are found outside the blades, with the peduncles being quantitatively the most relevant. We conclude that yield improvements in our Mediterranean agro-ecosystem are highly linked to the success of shoots in producing ears and a higher number of grains, while grain filling is highly dependent on the capacity of non-foliar organs to fix CO2 and N. The ear organs show higher stress resilience than other organs, which deserves our attention in future breeding programmes.

Source-Sink Dynamics in Field-Grown Durum Wheat Under Contrasting Nitrogen Supplies: Key Role of Non-Foliar Organs During Grain Filling.

The integration of high-throughput phenotyping and metabolic approaches is a suitable strategy to study the genotype-by-environment interaction and identify novel traits for crop improvement from canopy to an organ level. Our aims were to study the phenotypic and metabolic traits that are related to grain yield and quality at canopy and organ levels, with a special focus on source-sink coordination under contrasting N supplies. Four modern durum wheat varieties with contrasting grain yield were grown in field conditions under two N fertilization levels in north-eastern Spain. We evaluated canopy vegetation indices taken throughout the growing season, physiological and metabolic traits in different photosynthetic organs (flag leaf blade, sheath, peduncle, awn, glume, and lemma) at anthesis and mid-grain filling stages, and agronomic and grain quality traits at harvest. Low N supply triggered an imbalance of C and N coordination at the whole plant level, leading to a reduction of grain yield and nutrient composition. The activities of key enzymes in C and N metabolism as well as the levels of photoassimilates showed that each organ plays an important role during grain filling, some with a higher photosynthetic capacity, others for nutrient storage for later stages of grain filling, or N assimilation and recycling. Interestingly, the enzyme activities and sucrose content of the ear organs were positively associated with grain yield and quality, suggesting, together with the regression models using isotope signatures, the potential contribution of these organs during grain filling. This study highlights the use of holistic approaches to the identification of novel targets to improve grain yield and quality in C3 cereals and the key role of non-foliar organs at late-growth stages.

Estimating peanut and soybean photosynthetic traits using leaf spectral reflectance and advance regression models.

MAIN CONCLUSION: By combining hyperspectral signatures of peanut and soybean, we predicted Vcmax and Jmax with 70 and 50% accuracy. The PLS was the model that better predicted these photosynthetic parameters. One proposed key strategy for increasing potential crop stability and yield centers on exploitation of genotypic variability in photosynthetic capacity through precise high-throughput phenotyping techniques. Photosynthetic parameters, such as the maximum rate of Rubisco catalyzed carboxylation (Vc,max) and maximum electron transport rate supporting RuBP regeneration (Jmax), have been identified as key targets for improvement. The primary techniques for measuring these physiological parameters are very time-consuming. However, these parameters could be estimated using rapid and non-destructive leaf spectroscopy techniques. This study compared four different advanced regression models (PLS, BR, ARDR, and LASSO) to estimate Vc,max and Jmax based on leaf reflectance spectra measured with an ASD FieldSpec4. Two leguminous species were tested under different controlled environmental conditions: (1) peanut under different water regimes at normal atmospheric conditions and (2) soybean under high [CO2] and high night temperature. Model sensitivities were assessed for each crop and treatment separately and in combination to identify strengths and weaknesses of each modeling approach. Regardless of regression model, robust predictions were achieved for Vc,max (R2 = 0.70) and Jmax (R2 = 0.50). Field spectroscopy shows promising results for estimating spatial and temporal variations in photosynthetic capacity based on leaf and canopy spectral properties.

Dataset of above and below ground traits assessed in Durum wheat cultivars grown under Mediterranean environments differing in water and temperature conditions.

Ideotypic characteristics of durum wheat associated with higher yield under different water and temperature regimes were studied under Mediterranean conditions. The focus of this paper is to provide raw and supplemental data from the research article entitled "Durum wheat ideotypes in Mediterranean environments differing in water and temperature conditions" [1], which aims to define specific durum wheat ideotypes according to their responses to different agronomic conditions. In this context, six modern (i.e. post green revolution) genotypes with contrasting yield performance (i.e. high vs low yield) were grown during two consecutive years under different treatments: (i) winter planting under support-irrigation conditions, (ii) winter planting under rainfed conditions, (iii) late planting under support-irrigation. Trials were conducted at the INIA station of Colmenar de Oreja (Madrid). Different traits were assessed to inform about water status (canopy temperature at anthesis and stable carbon isotope composition (δ13C) of the flag leaf and mature grains), root performance (root traits and the oxygen isotope composition (δ18O) in the stem base water), phenology (days from sowing to heading), nitrogen status/photosynthetic capacity (nitrogen content and stable isotope composition (δ15N) of the flag leaf and mature grain together with the pigment contents and the nitrogen balance index (NBI) of the flag leaf), crop growth (plant height (PH) and the normalized difference vegetation index (NDVI) at anthesis), grain yield and agronomic yield components. For most of the parameters assessed, data analysis demonstrated significant differences among genotypes within each treatment. The level of significance was determined using the Tukey-b test on independent samples, and ideotypes were modelled from the results of principle component analysis. The present data shed light on traits that help to define specific ideotype characteristics that confer genotypic adaptation to a wide range of agronomic conditions produced by variations in planting date, water conditions and season.

Crop phenotyping in a context of global change: What to measure and how to do it.

High-throughput crop phenotyping, particularly under field conditions, is nowadays perceived as a key factor limiting crop genetic advance. Phenotyping not only facilitates conventional breeding, but it is necessary to fully exploit the capabilities of molecular breeding, and it can be exploited to predict breeding targets for the years ahead at the regional level through more advanced simulation models and decision support systems. In terms of phenotyping, it is necessary to determined which selection traits are relevant in each situation, and which phenotyping tools/methods are available to assess such traits. Remote sensing methodologies are currently the most popular approaches, even when lab-based analyses are still relevant in many circumstances. On top of that, data processing and automation, together with machine learning/deep learning are contributing to the wide range of applications for phenotyping. This review addresses spectral and red-green-blue sensing as the most popular remote sensing approaches, alongside stable isotope composition as an example of a lab-based tool, and root phenotyping, which represents one of the frontiers for field phenotyping. Further, we consider the two most promising forms of aerial platforms (unmanned aerial vehicle and satellites) and some of the emerging data-processing techniques. The review includes three Boxes that examine specific case studies.

Preharvest phenotypic prediction of grain quality and yield of durum wheat using multispectral imaging.

Durum wheat is an important cereal that is widely grown in the Mediterranean basin. In addition to high yield, grain quality traits are of high importance for farmers. The strong influence of climatic conditions makes the improvement of grain quality traits, like protein content, vitreousness, and test weight, a challenging task. Evaluation of quality traits post-harvest is time- and labor-intensive and requires expensive equipment, such as near-infrared spectroscopes or hyperspectral imagers. Predicting not only yield but also important quality traits in the field before harvest is of high value for breeders aiming to optimize resource allocation. Implementation of efficient approaches for trait prediction, such as the use of high-resolution spectral data acquired by a multispectral camera mounted on unmanned aerial vehicles (UAVs), needs to be explored. In this study, we have acquired multispectral image data with an 11-band multispectral camera mounted on a UAV and analyzed the data with machine learning (ML) models to predict grain yield and important quality traits in breeding micro-plots. Combining 11-band multispectral data for 34 cultivars and 16 environments allowed to develop ML models with good prediction capability. Applying the trained models to test sets explained a considerable degree of phenotypic variance with good accuracy showing r squared values of 0.84, 0.69, 0.64, and 0.61 and normalized root mean squared errors of 0.17, 0.07, 0.14, and 0.03 for grain yield, protein content, vitreousness, and test weight, respectively.

Exploring plant responses to abiotic stress by contrasting spectral signature changes.

In this study, daily changes over a short period and diurnal progression of spectral reflectance at the leaf level were used to identify spring wheat genotypes (Triticum aestivum L.) susceptible to adverse conditions. Four genotypes were grown in pots experiments under semi-controlled conditions in Chile and Spain. Three treatments were applied: i) control (C), ii) water stress (WS), and iii) combined water and heat shock (WS+T). Spectral reflectance, gas exchange and chlorophyll fluorescence measurements were performed on flag leaves for three consecutive days at anthesis. High canopy temperature ( H CT ) genotypes showed less variability in their mean spectral reflectance signature and chlorophyll fluorescence, which was related to weaker responses to environmental fluctuations. While low canopy temperature ( L CT ) genotypes showed greater variability. The genotypes spectral signature changes, in accordance with environmental fluctuation, were associated with variations in their stomatal conductance under both stress conditions (WS and WS+T); L CT genotypes showed an anisohydric response compared that of H CT , which was isohydric. This approach could be used in breeding programs for screening a large number of genotypes through proximal or remote sensing tools and be a novel but simple way to identify groups of genotypes with contrasting performances.

Comparative Performances of Beneficial Microorganisms on the Induction of Durum Wheat Tolerance to Fusarium Head Blight.

Durum wheat production is seriously threatened by Fusarium head blight (FHB) attacks in Tunisia, and the seed coating by bio-agents is a great alternative for chemical disease control. This study focuses on evaluating, under field conditions, the effect of seed coating with Trichoderma harzianum, Meyerozyma guilliermondii and their combination on (i) FHB severity, durum wheat grain yield and TKW in three crop seasons, and (ii) on physiological parameters and the carbon and nitrogen content and isotope composition in leaves and grains of durum wheat. The results indicated that the treatments were effective in reducing FHB severity by 30 to 70% and increasing grain yield with an increased rate ranging from 25 to 68%, compared to the inoculated control. The impact of treatments on grain yield improvement was associated with higher NDVI and chlorophyll content and lower canopy temperature. Furthermore, the treatments mitigated the FHB adverse effects on N and C metabolism by resulting in a higher δ13Cgrain (13C/12Cgrain) and δ15Ngrain (15N/14Ngrain). Overall, the combination outperformed the other seed treatments by producing the highest grain yield and TKW. The high potency of seed coating with the combination suggests that the two microorganisms have synergetic or complementary impacts on wheat.

Comparative Performance of High-Yielding European Wheat Cultivars Under Contrasting Mediterranean Conditions.

Understanding the interaction between genotype performance and the target environment is the key to improving genetic gain, particularly in the context of climate change. Wheat production is seriously compromised in agricultural regions affected by water and heat stress, such as the Mediterranean basin. Moreover, wheat production may be also limited by the nitrogen availability in the soil. We have sought to dissect the agronomic and physiological traits related to the performance of 12 high-yield European bread wheat varieties under Mediterranean rainfed conditions and different levels of N fertilization during two contrasting crop seasons. Grain yield was more than two times higher in the first season than the second season and was associated with much greater rainfall and lower temperatures. However, the nitrogen effect was rather minor. Genotypic effects existed for the two seasons. While several of the varieties from central/northern Europe yielded more than those from southern Europe during the optimal season, the opposite trend occurred in the dry season. The varieties from central/northern Europe were associated with delayed phenology and a longer crop cycle, while the varieties from southern Europe were characterized by a shorter crop cycle but comparatively higher duration of the reproductive period, associated with an earlier beginning of stem elongation and a greater number of ears per area. However, some of the cultivars from northern Europe maintained a relatively high yield capacity in both seasons. Thus, KWS Siskin from the UK exhibited intermediate phenology, resulting in a relatively long reproductive period, together with a high green area throughout the crop cycle.

Exploring the Potential of Meyerozyma guilliermondii on Physiological Performances and Defense Response against Fusarium Crown Rot on Durum Wheat.

Coating seeds with bio-control agents is a potentially effective approach to reduce the usage of pesticides and fertilizers applied and protect the natural environment. This study evaluated the effect of seed coating with Meyerozyma guilliermondii, strain INAT (MT731365), on seed germination, plant growth and photosynthesis, and plant resistance against Fusarium culmorum, in durum wheat under controlled conditions. Compared to control plants, seed coating with M. guilliermondii promoted the wheat growth (shoot and roots length and biomass), and photosynthesis and transpiration traits (chlorophyll, ɸPSII, rates of photosynthesis and transpiration, etc.) together with higher nitrogen balance index (NBI) and lower flavonols and anthocyanins. At 21 days post infection with Fusarium, M. guilliermondii was found to reduce the disease incidence and the severity, with reduction rates reaching up to 31.2% and 30.4%, respectively, as well as to alleviate the disease damaging impact on photosynthesis and plant growth. This was associated with lower ABA, flavonols and anthocyanins, compared to infected control. A pivotal function of M. guilliermondii as an antagonist of F. culmorum and a growth promoter is discussed.

Bridging the genotype-phenotype gap for a Mediterranean pine by semi-automatic crown identification and multispectral imagery.

Progress in high-throughput phenotyping and genomics provides the potential to understand the genetic basis of plant functional differentiation. We developed a semi-automatic methodology based on unmanned aerial vehicle (UAV) imagery for deriving tree-level phenotypes followed by genome-wide association study (GWAS). An RGB-based point cloud was used for tree crown identification in a common garden of Pinus halepensis in Spain. Crowns were combined with multispectral and thermal orthomosaics to retrieve growth traits, vegetation indices and canopy temperature. Thereafter, GWAS was performed to analyse the association between phenotypes and genomic variation at 235 single nucleotide polymorphisms (SNPs). Growth traits were associated with 12 SNPs involved in cellulose and carbohydrate metabolism. Indices related to transpiration and leaf water content were associated with six SNPs involved in stomata dynamics. Indices related to leaf pigments and leaf area were associated with 11 SNPs involved in signalling and peroxisome metabolism. About 16-20% of trait variance was explained by combinations of several SNPs, indicating polygenic control of morpho-physiological traits. Despite a limited availability of markers and individuals, this study is provides a successful proof-of-concept for the combination of high-throughput UAV-based phenotyping with cost-effective genotyping to disentangle the genetic architecture of phenotypic variation in a widespread conifer.

Aphid Resistance: An Overlooked Ecological Dimension of Nonstructural Carbohydrates in Cereals.

Nonstructural carbohydrates in cereals have been widely investigated from physiological, genetic, and breeding perspectives. Nonstructural carbohydrates may contribute to grain filling, but correlations with yield are inconsistent and sometimes negative. Here we ask if there are hidden functions of nonstructural carbohydrates, advance an ecological dimension to this question, and speculate that high concentration of nonstructural carbohydrates may challenge the osmotic homeostasis of aphids, thus providing a working hypothesis that connects nonstructural carbohydrates with aphid resistance in cereals. In the light of this proposition, the amount and concentration of nonstructural carbohydrates should be regarded as functionally different traits, with amount relevant to the carbon economy of the crop and concentration playing an osmotic role. We conclude with suggestions for experiments to test our hypothesis.

Remote sensing techniques and stable isotopes as phenotyping tools to assess wheat yield performance: Effects of growing temperature and vernalization.

This study compares distinct phenotypic approaches to assess wheat performance under different growing temperatures and vernalization needs. A set of 38 (winter and facultative) wheat cultivars were planted in Valladolid (Spain) under irrigation and two contrasting planting dates: normal (late autumn), and late (late winter). The late plating trial exhibited a 1.5 °C increase in average crop temperature. Measurements with different remote sensing techniques were performed at heading and grain filling, as well as carbon isotope composition (δ13C) and nitrogen content analysis. Multispectral and RGB vegetation indices and canopy temperature related better to grain yield (GY) across the whole set of genotypes in the normal compared with the late planting, with indices (such as the RGB indices Hue, a* and the spectral indices NDVI, EVI and CCI) measured at grain filling performing the best. Aerially assessed remote sensing indices only performed better than ground-acquired ones at heading. Nitrogen content and δ13C correlated with GY at both planting dates. Correlations within winter and facultative genotypes were much weaker, particularly in the facultative subset. For both planting dates, the best GY prediction models were achieved when combining remote sensing indices with δ13C and nitrogen of mature grains. Implications for phenotyping in the context of increasing temperatures are further discussed.

Metabolome Profiling Supports the Key Role of the Spike in Wheat Yield Performance.

Although the relevance of spike bracts in stress acclimation and contribution to wheat yield was recently revealed, the metabolome of this organ and its response to water stress is still unknown. The metabolite profiles of flag leaves, glumes and lemmas were characterized under contrasting field water regimes in five durum wheat cultivars. Water conditions during growth were characterized through spectral vegetation indices, canopy temperature and isotope composition. Spike bracts exhibited better coordination of carbon and nitrogen metabolisms than the flag leaves in terms of photorespiration, nitrogen assimilation and respiration paths. This coordination facilitated an accumulation of organic and amino acids in spike bracts, especially under water stress. The metabolomic response to water stress also involved an accumulation of antioxidant and drought tolerance related sugars, particularly in the spikes. Furthermore, certain cell wall, respiratory and protective metabolites were associated with genotypic outperformance and yield stability. In addition, grain yield was strongly predicted by leaf and spike bracts metabolomes independently. This study supports the role of the spike as a key organ during wheat grain filling, particularly under stress conditions and provides relevant information to explore new ways to improve wheat productivity including potential biomarkers for yield prediction.

New avenues for increasing yield and stability in C3 cereals: exploring ear photosynthesis.

Small grain cereals such as wheat, rice and barley are among the most important crops worldwide. Any attempt to increase crop productivity and stability through breeding implies developing new strategies for plant phenotyping, including defining ideotype attributes for selection. Recently, the role of non-foliar photosynthetic organs, particularly the inflorescences, has received increasing attention. For example, ear photosynthesis has been reported to be a major contributor to grain filling in wheat and barley under stress and good agronomic conditions. This review provides an overview of the particular characteristics of the ear that makes this photosynthetic organ better adapted to grain filling than the flag leaf and revises potential metabolic and molecular traits that merit further research as targets for cereal improvement. Currently, the absence of high-throughput phenotyping methods limits the inclusion of ear photosynthesis in the breeding agenda. In this regard, a number of different approaches are presented.

Assessing durum wheat ear and leaf metabolomes in the field through hyperspectral data.

Hyperspectral techniques are currently used to retrieve information concerning plant biophysical traits, predominantly targeting pigments, water, and nitrogen-protein contents, structural elements, and the leaf area index. Even so, hyperspectral data could be more extensively exploited to overcome the breeding challenges being faced under global climate change by advancing high-throughput field phenotyping. In this study, we explore the potential of field spectroscopy to predict the metabolite profiles in flag leaves and ear bracts in durum wheat. The full-range reflectance spectra (visible (VIS)-near-infrared (NIR)-short wave infrared (SWIR)) of flag leaves, ears and canopies were recorded in a collection of contrasting genotypes grown in four environments under different water regimes. GC-MS metabolite profiles were analyzed in the flag leaves, ear bracts, glumes, and lemmas. The results from regression models exceeded 50% of the explained variation (adj-R2 in the validation sets) for at least 15 metabolites in each plant organ, whereas their errors were considerably low. The best regressions were obtained for malate (82%), glycerate and serine (63%) in leaves; myo-inositol (81%) in lemmas; glycolate (80%) in glumes; sucrose in leaves and glumes (68%); γ-aminobutyric acid (GABA) in leaves and glumes (61% and 71%, respectively); proline and glucose in lemmas (74% and 71%, respectively) and glumes (72% and 69%, respectively). The selection of wavebands in the models and the performance of the models based on canopy and VIS organ spectra and yield prediction are discussed. We feel that this technique will likely to be of interest due to its broad applicability in ecophysiology research, plant breeding programmes, and the agri-food industry.