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.

Quinoa panicles contribute to carbon assimilation and are more tolerant to salt stress than leaves.

Contribution of inflorescences to seed filling have attracted great attention given the resilience of this photosynthetic organ to stressful conditions. However, studies have been almost exclusively focused to small grain cereals. In this study, we aimed to explore these responses in quinoa, as a climate resilient seed crop of elevated economic and nutritious potential.

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.

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.

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.

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.

Comparison of Selection Traits for Effective Popcorn ( L. var. Everta) Breeding Under Water Limiting Conditions.

Climate change is expected to intensify water restriction to crops, impacting on the yield potential of crops such as popcorn. This work aimed to evaluate the performance of 10 field cultivated popcorn inbred lines during two growing seasons, under well-watered (WW) and water stressed (WS) (ψ≥ -1.5 MPa) conditions.

Application of Trichoderma asperellum T34 on maize (Zea mays) seeds protects against drought stress.

Coating maize seeds with the microbial plant protection product Trichoderma asperellum strain T34 is an effective form of inoculation that enhances plant performance when faced with drought stress, and it improves nutrient and kernel parameters differently in drought and non-stressed conditions. Drought is currently one of the biggest threats to maize production. Trichoderma spp.

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.

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.

Identification of traits associated with barley yield performance using contrasting nitrogen fertilizations and genotypes.

Much attention has been paid to understanding the traits associated with crop performance and the associated underlying physiological mechanisms, with less effort done towards combining different plant scales, levels of observation, or including hybrids of autogamous species. We aim to identify mechanisms at canopy, leaf and transcript levels contributing to crop performance under contrasting nitrogen supplies in three barley genotypes, two hybrids and one commercial line. High nitrogen fertilization did not affect photosynthetic capacity on a leaf area basis and lowered nitrogen partial factor productivity past a certain point, but increased leaf area and biomass accumulation, parameters that were closely tracked using various different high throughput remote sensing based phenotyping techniques.

Evaluating Maize Genotype Performance under Low Nitrogen Conditions Using RGB UAV Phenotyping Techniques.

Maize is the most cultivated cereal in Africa in terms of land area and production, but low soil nitrogen availability often constrains yields. Developing new maize varieties with high and reliable yields using traditional crop breeding techniques in field conditions can be slow and costly. Remote sensing has become an important tool in the modernization of field-based high-throughput plant phenotyping (HTPP), providing faster gains towards the improvement of yield potential and adaptation to abiotic and biotic limiting conditions.

Cereal Crop Ear Counting in Field Conditions Using Zenithal RGB Images.

Ear density, or the number of ears per square meter (ears/m), is a central focus in many cereal crop breeding programs, such as wheat and barley, representing an important agronomic yield component for estimating grain yield. Therefore, a quick, efficient, and standardized technique for assessing ear density would aid in improving agricultural management, providing improvements in preharvest yield predictions, or could even be used as a tool for crop breeding when it has been defined as a trait of importance. Not only are the current techniques for manual ear density assessments laborious and time-consuming, but they are also without any official standardized protocol, whether by linear meter, area quadrant, or an extrapolation based on plant ear density and plant counts postharvest.

The Plant-Transpiration Response to Vapor Pressure Deficit (VPD) in Durum Wheat Is Associated With Differential Yield Performance and Specific Expression of Genes Involved in Primary Metabolism and Water Transport.

The regulation of plant transpiration was proposed as a key factor affecting transpiration efficiency and agronomical adaptation of wheat to water-limited Mediterranean environments. However, to date no studies have related this trait to crop performance in the field. In this study, the transpiration response to increasing (VPD) of modern Spanish semi-dwarf durum wheat lines was evaluated under controlled conditions at vegetative stage, and the agronomical performance of the same set of lines was assessed at grain filling as well as grain yield at maturity, in Mediterranean environments ranging from water stressed to good agronomical conditions.

Leaf dorsoventrality as a paramount factor determining spectral performance in field-grown wheat under contrasting water regimes.

The effects of leaf dorsoventrality and its interaction with environmentally induced changes in the leaf spectral response are still poorly understood, particularly for isobilateral leaves. We investigated the spectral performance of 24 genotypes of field-grown durum wheat at two locations under both rainfed and irrigated conditions. Flag leaf reflectance spectra in the VIS-NIR-SWIR (visible-near-infrared-short-wave infrared) regions were recorded in the adaxial and abaxial leaf sides and at the canopy level, while traits providing information on water status and grain yield were evaluated.

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.

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.

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.

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.