Awned versus awnless wheat spikes: does it matter?

Awnless and awned wheat is found across the globe. Archeological and historical records show that the wheat spike was predominantly awned across the many millennia following domestication. Thus, ancient farmers did not select against awns at least until the last millennium. Here, we describe the evolution and domestication of wheat awns, quantifying their role in spike photosynthesis and yield under contrasting environments. Awns increase grain weight directly (increasing the size of all grains) or indirectly (increasing the failure of distal grains), but not as a consequence of additional spike photosynthesis. However, a trade-off is produced through decreasing grain number. Thus, favorable effects of awns on yield are not consistently found across environments.

Ear photosynthesis in C3 cereals and its contribution to grain yield: methodologies, controversies, and perspectives.

In C3 cereals such as wheat and barley, grain filling was traditionally explained as being sustained by assimilates from concurrent leaf photosynthesis and remobilization from the stem. In recent decades, a role for ear photosynthesis as a contributor to grain filling has emerged. This review analyzes several aspects of this topic: (i) methodological approaches for estimation of ear photosynthetic contribution to grain filling; (ii) the existence of genetic variability in the contribution of the ear, and evidence of genetic gains in the past; (iii) the controversy of the existence of C4 metabolism in the ear; (iv) the response of ear photosynthesis to water deficit; and (v) morphological and physiological traits possibly related to ear temperature and thermal balance of the ear. The main conclusions are: (i) there are a number of methodologies to quantify ear photosynthetic activity (e.g. gas exchange and chlorophyll fluorescence) and the contribution of the ear to grain filling (individual ear shading, ear emergence in shaded canopies, and isotope composition); (ii) the contribution of ear photosynthesis seems to have increased in modern wheat germplasm; (iii) the contribution of the ear to grain filling increases under resource-limitation (water deficit, defoliation, or pathogen infection); (iv) there is genetic variability in the contribution of the ear in wheat, opening up the possibility to use this trait to ameliorate grain yield; (v) current evidence supports the existence of C3 metabolism rather than C4 metabolism; (vi) the ear is a 'dehydration avoider organ' under drought; and (vii) thermal balance in the ear is a relevant issue to explore, and more research is needed to clarify the underlying morphological and physiological traits.

Improving crop yield and resilience through optimization of photosynthesis: panacea or pipe dream?

Increasing the speed of breeding to enhance crop productivity and adaptation to abiotic stresses is urgently needed. The perception that a second Green Revolution should be implemented is widely established within the scientific community and among stakeholders. In recent decades, different alternatives have been proposed for increasing crop yield through manipulation of leaf photosynthetic efficiency. However, none of these has delivered practical or relevant outputs. Indeed, the actual increases in photosynthetic rates are not expected to translate into yield increases beyond 10-15%. Furthermore, instantaneous rates of leaf photosynthesis are not necessarily the reference target for research. Yield is the result of canopy photosynthesis, understood as the contribution of laminar and non-laminar organs over time, within which concepts such as canopy architecture, stay-green, or non-laminar photosynthesis need to be taken into account. Moreover, retrospective studies show that photosynthetic improvements have been more common at the canopy level. Nevertheless, it is crucial to place canopy photosynthesis in the context of whole-plant functioning, which includes sink-source balance and transport of photoassimilates, and the availability and uptake of nutrients, such as nitrogen in particular. Overcoming this challenge will only be feasible if a multiscale crop focus combined with a multidisciplinary scientific approach is adopted.

Effect of irrigation salinity and ecotype on the growth, physiological indicators and seed yield and quality of Salicornia europaea.

The euhalophyte species Salicornia europaea is cultivated for oilseed and as a fodder crop in various parts of the world. In saline coastal environments it possesses great potential for the subsistence of the most disadvantaged farmers. We investigated the effect of salinity levels in irrigation water on the germination capacity, shoot biomass and seed productivity as well as diverse quality traits (nitrogen content in shoots and seeds and fatty acids, in seeds) and physiological traits (stable carbon and nitrogen isotopes and ion content) of two accessions collected in the United Arab Emirates (UAE). The three salinity levels tested were irrigation with fresh water (0.3 dS m-1), brackish water (25 dS m-1) and sea water (40 dS m-1). In addition, a hypersaline condition (80 dS m-1) was also tested for germination. The best germination rates were achieved with seeds exposed to fresh and brackish water, while imbibition with sea water decreased germination by half and hypersaline water inhibited it almost totally. However, the best irrigation regime in terms of biomass and seed yield involved brackish water. Moreover, rising salinity in the irrigation increased the stable isotope composition of carbon (δ13C) and nitrogen (δ15N), together with the Na+ and K+ of shoots and seeds, and the lipid levels of seeds, while the total nitrogen content and the profile of major fatty acids of seeds did not change. Differences between the two ecotypes existed for growth and seed yield with the best ecotype exhibiting lower δ13C and higher K+ in both shoots and seeds, lower Na+ and higher δ15N in shoots, and lower N in seeds, together with differences in major fatty acids. Physiological mechanisms behind the response to irrigation salinity and the ecotypic differences are discussed in terms of photosynthetic carbon and nitrogen metabolism.

Assessing the evolution of wheat grain traits during the last 166 years using archived samples.

The current study focuses on yield and nutritional quality changes of wheat grain over the last 166 years. It is based on wheat grain quality analyses carried out on samples collected between 1850 and 2016. Samples were obtained from the Broadbalk Continuous Wheat Experiment (UK) and from herbaria from 16 different countries around the world. Our study showed that, together with an increase in carbohydrate content, an impoverishment of mineral composition and protein content occurred. The imbalance in carbohydrate/protein content was specially marked after the 1960's, coinciding with strong increases in ambient [CO2] and temperature and the introduction of progressively shorter straw varieties. The implications of altered crop physiology are discussed.

Leaf versus whole-canopy remote sensing methodologies for crop monitoring under conservation agriculture: a case of study with maize in Zimbabwe.

Enhancing nitrogen fertilization efficiency for improving yield is a major challenge for smallholder farming systems. Rapid and cost-effective methodologies with the capability to assess the effects of fertilization are required to facilitate smallholder farm management. This study compares maize leaf and canopy-based approaches for assessing N fertilization performance under different tillage, residue coverage and top-dressing conditions in Zimbabwe. Among the measurements made on individual leaves, chlorophyll readings were the best indicators for both N content in leaves (R < 0.700) and grain yield (GY) (R < 0.800). Canopy indices reported even higher correlation coefficients when assessing GY, especially those based on the measurements of the vegetation density as the green area indices (R < 0.850). Canopy measurements from both ground and aerial platforms performed very similar, but indices assessed from the UAV performed best in capturing the most relevant information from the whole plot and correlations with GY and leaf N content were slightly higher. Leaf-based measurements demonstrated utility in monitoring N leaf content, though canopy measurements outperformed the leaf readings in assessing GY parameters, while providing the additional value derived from the affordability and easiness of using a pheno-pole system or the high-throughput capacities of the UAVs.

Agronomical and analytical trait data assessed in a set of quinoa genotypes growing in the UAE under different irrigation salinity conditions.

The importance of quinoa has been emphasized considerably in the recent decades, as a highly nutritional crop seed that is tolerant to salinity and amenable to arid agronomical conditions. The focus of this paper is to provide raw and a supplemental data of the research article entitled "Agronomic performance of irrigated quinoa in desert areas: comparing different approaches for early assessment of salinity stress" [1], aiming to compare different approaches for early detection, at the genotypic and crop levels, of the effect of salinity caused by irrigation on the agronomic performance of this crop. A set of 20 genotypes was grown under drip irrigation in sandy soil, amended with manure, at the International Center for Biosaline Agriculture (UAE) for two weeks, after which half of the trial was submitted to irrigation with saline water and this was continued until crop maturity. After eight weeks of applying the two irrigation regimes, pigment contents were evaluated in fully expanded leaves. The same leaves were then harvested, dried and the stable carbon and nitrogen isotope compositions (δ13C and δ15N) and the total nitrogen and carbon contents of the dry matter analyzed, together with ion concentrations. At maturity yield components were assessed and yield harvested. Data analysis demonstrated significant differences in genotypes response under each treatment, within all assessed parameters. The significant level was provided using the Tukey-b test on independent samples. The present dataset highlights the potential use of different approaches to crop phenotyping and monitoring decision making.

Automatic wheat ear counting using machine learning based on RGB UAV imagery.

In wheat (Triticum aestivum L) and other cereals, the number of ears per unit area is one of the main yield-determining components. An automatic evaluation of this parameter may contribute to the advance of wheat phenotyping and monitoring. There is no standard protocol for wheat ear counting in the field, and moreover it is time consuming. An automatic ear-counting system is proposed using machine learning techniques based on RGB (red, green, blue) images acquired from an unmanned aerial vehicle (UAV). Evaluation was performed on a set of 12 winter wheat cultivars with three nitrogen treatments during the 2017-2018 crop season. The automatic system uses a frequency filter, segmentation and feature extraction, with different classification techniques, to discriminate wheat ears in micro-plot images. The relationship between the image-based manual counting and the algorithm counting exhibited high levels of accuracy and efficiency. In addition, manual ear counting was conducted in the field for secondary validation. The correlations between the automatic and the manual in-situ ear counting with grain yield were also compared. Correlations between the automatic ear counting and grain yield were stronger than those between manual in-situ counting and GY, particularly for the lower nitrogen treatment. Methodological requirements and limitations are discussed.

Breeding to adapt agriculture to climate change: affordable phenotyping solutions.

Breeding is one of the central pillars of adaptation of crops to climate change. However, phenotyping is a key bottleneck that is limiting breeding efficiency. The awareness of phenotyping as a breeding limitation is not only sustained by the lack of adequate approaches, but also by the perception that phenotyping is an expensive activity. Phenotyping is not just dependent on the choice of appropriate traits and tools (e.g. sensors) but relies on how these tools are deployed on their carrying platforms, the speed and volume of data extraction and analysis (throughput), the handling of spatial variability and characterization of environmental conditions, and finally how all the information is integrated and processed. Affordable high throughput phenotyping aims to achieve reasonably priced solutions for all the components comprising the phenotyping pipeline. This mini-review will cover current and imminent solutions for all these components, from the increasing use of conventional digital RGB cameras, within the category of sensors, to open-access cloud-structured data processing and the use of smartphones. Emphasis will be placed on field phenotyping, which is really the main application for day-to-day phenotyping.

Phenotyping Conservation Agriculture Management Effects on Ground and Aerial Remote Sensing Assessments of Maize Hybrids Performance in Zimbabwe.

In the coming decades, Sub-Saharan Africa (SSA) faces challenges to sustainably increase food production while keeping pace with continued population growth. Conservation agriculture (CA) has been proposed to enhance soil health and productivity to respond to this situation. Maize is the main staple food in SSA. To increase maize yields, the selection of suitable genotypes and management practices for CA conditions has been explored using remote sensing tools. They may play a fundamental role towards overcoming the traditional limitations of data collection and processing in large scale phenotyping studies. We present the result of a study in which Red-Green-Blue (RGB) and multispectral indexes were evaluated for assessing maize performance under conventional ploughing (CP) and CA practices. Eight hybrids under different planting densities and tillage practices were tested. The measurements were conducted on seedlings at ground level (0.8 m) and from an unmanned aerial vehicle (UAV) platform (30 m), causing a platform proximity effect on the images resolution that did not have any negative impact on the performance of the indexes. Most of the calculated indexes (Green Area (GA) and Normalized Difference Vegetation Index (NDVI)) were significantly affected by tillage conditions increasing their values from CP to CA. Indexes derived from the RGB-images related to canopy greenness performed better at assessing yield differences, potentially due to the greater resolution of the RGB compared with the multispectral data, although this performance was more precise for CP than CA. The correlations of the multispectral indexes with yield were improved by applying a soil-mask derived from a NDVI threshold with the aim of corresponding pixels with vegetation. The results of this study highlight the applicability of remote sensing approaches based on RGB images to the assessment of crop performance and hybrid choice.

Comparative Performance of Ground vs. Aerially Assessed RGB and Multispectral Indices for Early-Growth Evaluation of Maize Performance under Phosphorus Fertilization.

Low soil fertility is one of the factors most limiting agricultural production, with phosphorus deficiency being among the main factors, particularly in developing countries. To deal with such environmental constraints, remote sensing measurements can be used to rapidly assess crop performance and to phenotype a large number of plots in a rapid and cost-effective way. We evaluated the performance of a set of remote sensing indices derived from Red-Green-Blue (RGB) images and multispectral (visible and infrared) data as phenotypic traits and crop monitoring tools for early assessment of maize performance under phosphorus fertilization. Thus, a set of 26 maize hybrids grown under field conditions in Zimbabwe was assayed under contrasting phosphorus fertilization conditions. Remote sensing measurements were conducted in seedlings at two different levels: at the ground and from an aerial platform. Within a particular phosphorus level, some of the RGB indices strongly correlated with grain yield. In general, RGB indices assessed at both ground and aerial levels correlated in a comparable way with grain yield except for indices a* and u*, which correlated better when assessed at the aerial level than at ground level and Greener Area (GGA) which had the opposite correlation. The Normalized Difference Vegetation Index (NDVI) evaluated at ground level with an active sensor also correlated better with grain yield than the NDVI derived from the multispectral camera mounted in the aerial platform. Other multispectral indices like the Soil Adjusted Vegetation Index (SAVI) performed very similarly to NDVI assessed at the aerial level but overall, they correlated in a weaker manner with grain yield than the best RGB indices. This study clearly illustrates the advantage of RGB-derived indices over the more costly and time-consuming multispectral indices. Moreover, the indices best correlated with GY were in general those best correlated with leaf phosphorous content. However, these correlations were clearly weaker than against grain yield and only under low phosphorous conditions. This work reinforces the effectiveness of canopy remote sensing for plant phenotyping and crop management of maize under different phosphorus nutrient conditions and suggests that the RGB indices are the best option.

Comparative UAV and Field Phenotyping to Assess Yield and Nitrogen Use Efficiency in Hybrid and Conventional Barley.

With the commercialization and increasing availability of Unmanned Aerial Vehicles (UAVs) multiple rotor copters have expanded rapidly in plant phenotyping studies with their ability to provide clear, high resolution images. As such, the traditional bottleneck of plant phenotyping has shifted from data collection to data processing. Fortunately, the necessarily controlled and repetitive design of plant phenotyping allows for the development of semi-automatic computer processing tools that may sufficiently reduce the time spent in data extraction. Here we present a comparison of UAV and field based high throughput plant phenotyping (HTPP) using the free, open-source image analysis software FIJI (Fiji is just ImageJ) using RGB (conventional digital cameras), multispectral and thermal aerial imagery in combination with a matching suite of ground sensors in a study of two hybrids and one conventional barely variety with ten different nitrogen treatments, combining different fertilization levels and application schedules. A detailed correlation network for physiological traits and exploration of the data comparing between treatments and varieties provided insights into crop performance under different management scenarios. Multivariate regression models explained 77.8, 71.6, and 82.7% of the variance in yield from aerial, ground, and combined data sets, respectively.

Interactive Effects of CO2 Concentration and Water Regime on Stable Isotope Signatures, Nitrogen Assimilation and Growth in Sweet Pepper.

Sweet pepper is among the most widely cultivated horticultural crops in the Mediterranean basin, being frequently grown hydroponically under cover in combination with CO2 fertilization and water conditions ranging from optimal to suboptimal. The aim of this study is to develop a simple model, based on the analysis of plant stable isotopes in their natural abundance, gas exchange traits and N concentration, to assess sweet pepper growth. Plants were grown in a growth chamber for near 6 weeks. Two [CO2] (400 and 800 µmol mol-1), three water regimes (control and mild and moderate water stress) and four genotypes were assayed. For each combination of genotype, [CO2] and water regime five plants were evaluated. Water stress applied caused significant decreases in water potential, net assimilation, stomatal conductance, intercellular to atmospheric [CO2], and significant increases in water use efficiency, leaf chlorophyll content and carbon isotope composition, while the relative water content, the osmotic potential and the content of anthocyanins did change not under stress compared to control conditions support this statement. Nevertheless, water regime affects plant growth via nitrogen assimilation, which is associated with the transpiration stream, particularly at high [CO2], while the lower N concentration caused by rising [CO2] is not associated with stomatal closure. The stable isotope composition of carbon, oxygen, and nitrogen (δ13C, δ18O, and δ15N) in plant matter are affected not only by water regime but also by rising [CO2]. Thus, δ18O increased probably as response to decreases in transpiration, while the increase in δ15N may reflect not only a lower stomatal conductance but a higher nitrogen demand in leaves or shifts in nitrogen metabolism associated with decreases in photorespiration. The way that δ13C explains differences in plant growth across water regimes within a given [CO2], seems to be mediated through its direct relationship with N accumulation in leaves. The changes in the profile and amount of amino acids caused by water stress and high [CO2] support this conclusion. However, the results do not support the use of δ18O as an indicator of the effect of water regime on plant growth.

Physiological Traits Associated with Wheat Yield Potential and Performance under Water-Stress in a Mediterranean Environment.

Different physiological traits have been proposed as key traits associated with yield potential as well as performance under water stress. The aim of this paper is to examine the genotypic variability of leaf chlorophyll, stem water-soluble carbohydrate content and carbon isotope discrimination (Δ(13)C), and their relationship with grain yield (GY) and other agronomical traits, under contrasting water conditions in a Mediterranean environment. The study was performed on a large collection of 384 wheat genotypes grown under water stress (WS, rainfed), mild water stress (MWS, deficit irrigation), and full irrigation (FI). The average GY of two growing seasons was 2.4, 4.8, and 8.9 Mg ha(-1) under WS, MWS, and FI, respectively. Chlorophyll content at anthesis was positively correlated with GY (except under FI in 2011) and the agronomical components kernels per spike (KS) and thousand kernel weight (TKW). The WSC content at anthesis (WSCCa) was negatively correlated with spikes per square meter (SM2), but positively correlated with KS and TKW under WS and FI conditions. As a consequence, the relationships between WSCCa with GY were low or not significant. Therefore, selecting for high stem WSC would not necessary lead to genotypes of GY potential. The relationship between Δ(13)C and GY was positive under FI and MWS but negative under severe WS (in 2011), indicating higher water use under yield potential and MWS conditions.

A Novel Remote Sensing Approach for Prediction of Maize Yield Under Different Conditions of Nitrogen Fertilization.

Maize crop production is constrained worldwide by nitrogen (N) availability and particularly in poor tropical and subtropical soils. The development of affordable high-throughput crop monitoring and phenotyping techniques is key to improving maize cultivation under low-N fertilization. In this study several vegetation indices (VIs) derived from Red-Green-Blue (RGB) digital images at the leaf and canopy levels are proposed as low-cost tools for plant breeding and fertilization management. They were compared with the performance of the normalized difference vegetation index (NDVI) measured at ground level and from an aerial platform, as well as with leaf chlorophyll content (LCC) and other leaf composition and structural parameters at flowering stage. A set of 10 hybrids grown under five different nitrogen regimes and adequate water conditions were tested at the CIMMYT station of Harare (Zimbabwe). Grain yield and leaf N concentration across N fertilization levels were strongly predicted by most of these RGB indices (with R (2)~ 0.7), outperforming the prediction power of the NDVI and LCC. RGB indices also outperformed the NDVI when assessing genotypic differences in grain yield and leaf N concentration within a given level of N fertilization. The best predictor of leaf N concentration across the five N regimes was LCC but its performance within N treatments was inefficient. The leaf traits evaluated also seemed inefficient as phenotyping parameters. It is concluded that the adoption of RGB-based phenotyping techniques may significantly contribute to the progress of plant breeding and the appropriate management of fertilization.

The Nitrogen Contribution of Different Plant Parts to Wheat Grains: Exploring Genotype, Water, and Nitrogen Effects.

The flag leaf has been traditionally considered as the main contributor to grain nitrogen. However, during the reproductive stage, other organs besides the flag leaf may supply nitrogen to developing grains. Therefore, the contribution of the ear and other organs to the nitrogen supplied to the growing grains remains unclear. It is important to develop phenotypic tools to assess the relative contribution of different plant parts to the N accumulated in the grains of wheat which may helps to develop genotypes that use N more efficiently. We studied the effect of growing conditions (different levels of water and nitrogen in the field) on the nitrogen contribution of the spike and different vegetative organs of the plant to the grains. The natural abundance of δ15N and total N content in the flag blade, peduncle, whole spike, glumes and awns were compared to the δ15N and total N in mature grains to trace the origin of nitrogen redistribution to the grains. The δ15N and total N content of the different plant parts correlated positively with the δ15N and total N content of mature grains suggesting that all organs may contribute a portion of their N content to the grains. The potential contribution of the flag blade to grain N increased (by 46%) as the growing conditions improved, whereas the potential contribution of the glumes plus awns and the peduncle increased (46 and 31%, respectively) as water and nitrogen stress increased. In general, potential contribution of the ear providing N to growing grains was similar (42%) than that of the vegetative parts of the plants (30-40%), regardless of the growing conditions. Thus, the potential ear N content could be a positive trait for plant phenotyping, especially under water and nitrogen limiting conditions. In that sense, genotypic variability existed at least between old (tall) and modern (semidwarf) cultivars, with the ear from modern genotypes exhibiting less relative contribution to the total grain N. The combined use of δ15N and N content may be used as an affordable tool to assess the relative contribution of different plant parts to the grain N in wheat.

Differential CO2 effect on primary carbon metabolism of flag leaves in durum wheat (Triticum durum Desf.).

C sink/source balance and N assimilation have been identified as target processes conditioning crop responsiveness to elevated CO2 . However, little is known about phenology-driven modifications of C and N primary metabolism at elevated CO2 in cereals such as wheat. Here, we examined the differential effect of elevated CO2 at two development stages (onset of flowering, onset of grain filling) in durum wheat (Triticum durum, var. Sula) using physiological measurements (photosynthesis, isotopes), metabolomics, proteomics and (15) N labelling. Our results show that growth at elevated CO2 was accompanied by photosynthetic acclimation through a lower internal (mesophyll) conductance but no significant effect on Rubisco content, maximal carboxylation or electron transfer. Growth at elevated CO2 altered photosynthate export and tended to accelerate leaf N remobilization, which was visible for several proteins and amino acids, as well as lysine degradation metabolism. However, grain biomass produced at elevated CO2 was larger and less N rich, suggesting that nitrogen use efficiency rather than photosynthesis is an important target for improvement, even in good CO2 -responsive cultivars.

Systems responses to progressive water stress in durum wheat.

Durum wheat is susceptible to terminal drought which can greatly decrease grain yield. Breeding to improve crop yield is hampered by inadequate knowledge of how the physiological and metabolic changes caused by drought are related to gene expression. To gain better insight into mechanisms defining resistance to water stress we studied the physiological and transcriptome responses of three durum breeding lines varying for yield stability under drought. Parents of a mapping population (Lahn x Cham1) and a recombinant inbred line (RIL2219) showed lowered flag leaf relative water content, water potential and photosynthesis when subjected to controlled water stress time transient experiments over a six-day period. RIL2219 lost less water and showed constitutively higher stomatal conductance, photosynthesis, transpiration, abscisic acid content and enhanced osmotic adjustment at equivalent leaf water compared to parents, thus defining a physiological strategy for high yield stability under water stress. Parallel analysis of the flag leaf transcriptome under stress uncovered global trends of early changes in regulatory pathways, reconfiguration of primary and secondary metabolism and lowered expression of transcripts in photosynthesis in all three lines. Differences in the number of genes, magnitude and profile of their expression response were also established amongst the lines with a high number belonging to regulatory pathways. In addition, we documented a large number of genes showing constitutive differences in leaf transcript expression between the genotypes at control non-stress conditions. Principal Coordinates Analysis uncovered a high level of structure in the transcriptome response to water stress in each wheat line suggesting genome-wide co-ordination of transcription. Utilising a systems-based approach of analysing the integrated wheat's response to water stress, in terms of biological robustness theory, the findings suggest that each durum line transcriptome responded to water stress in a genome-specific manner which contributes to an overall different strategy of resistance to water stress.