Dissecting maize productivity: ideotypes associated with grain yield under drought stress and well-watered conditions

Unveiling Drought-Resilient Latin American Popcorn Lines through Agronomic and Physiological Evaluation

Water stress can lead to physiological and morphological damage, affecting the growth and development of popcorn. The objective of this study was to identify the yield potential of 43 popcorn lines derived from a Latin American germplasm collection, based on agronomic and physiological traits, under full irrigation (WW) and water deficit conditions (WS), aiming to select superior germplasm. The evaluated agronomic traits included the ear length and diameter, number of grains per row (NGR) and rows per ear (NRE), grain yield (GY), popping expansion (EC), volume of expanded popcorn per hectare (VP), grain length (GL), width, and thickness. The physiological traits included the chlorophyll, anthocyanin, and flavonoid content in the leaves. The genetic variability and distinct behavior among the lines for all the agronomic traits under WW and WS conditions were observed. When comparing the water conditions, line L292 had the highest mean for the GY, and line L688 had the highest mean for the EC, highlighting them as the most drought-tolerant lines. A water deficit reduced the leaf greenness but increased the anthocyanin content as an adaptive response. The GY trait showed positive correlations with the VP, NGR, and GL under both water conditions, making the latter useful for indirect selection and thus of great interest for plant breeding targeting the simultaneous improvement of these traits.

Genetic trends in the Zimbabwe's national maize breeding program over two decades

Monitoring genetic gains within breeding programs is a critical component for continuous improvement. While several national breeding programs in Africa have assessed genetic gain using era studies, this study is the first to use two decades of historical data to estimate genetic trends within a national breeding program. The objective of this study was to assess genetic trends within the final two stages of Zimbabwe's Department of Research & Specialist Services maize breeding pipeline between 2002 and 2021. Data from 107 intermediate and 162 advanced variety trials, comprising of 716 and 398 entries, respectively, was analyzed. Trials were conducted under optimal, managed drought stress, low nitrogen stress, low pH, random stress, and disease pressure (maize streak virus (MSV), grey leaf spot (GLS), and turcicum leaf blight under artificial inoculation. There were positive and significant genetic gains for grain yield across management conditions (28-35 kg ha-1 yr-1), under high-yield potential environments (17-61 kg ha-1 yr-1), and under low-yield potential environments (0-16 kg ha-1 yr-1). No significant changes were observed in plant and ear height over the study period. Stalk and root lodging, as well as susceptibility to MSV and GLS, significantly decreased over the study period. New breeding technologies need to be incorporated into the program to further increase the rate of genetic gain in the maize breeding programs and to effectively meet future needs.

Maize green leaf area index dynamics: genetic basis of a new secondary trait for grain yield in optimal and drought conditions

KEY MESSAGE

Green Leaf Area Index dynamics is a promising secondary trait for grain yield and drought tolerance. Multivariate GWAS is particularly well suited to identify the genetic determinants of the green leaf area index dynamics. Improvement of maize grain yield is impeded by important genotype-environment interactions, especially under drought conditions. The use of secondary traits, that are correlated with yield, more heritable and less prone to genotype-environment interactions, can increase breeding efficiency. Here, we studied the genetic basis of a new secondary trait: the green leaf area index (GLAI) dynamics over the maize life cycle. For this, we used an unmanned aerial vehicle to characterize the GLAI dynamics of a diverse panel in well-watered and water-deficient trials in two years. From the dynamics, we derived 24 traits (slopes, durations, areas under the curve), and showed that six of them were heritable traits representative of the panel diversity. To identify the genetic determinants of GLAI, we compared two genome-wide association approaches: a univariate (single-trait) method and a multivariate (multi-trait) method combining GLAI traits, grain yield, and precocity. The explicit modeling of correlation structure between secondary traits and grain yield in the multivariate mixed model led to 2.5 times more associations detected. A total of 475 quantitative trait loci (QTLs) were detected. The genetic architecture of GLAI traits appears less complex than that of yield with stronger-effect QTLs that are more stable between environments. We also showed that a subset of GLAI QTLs explains nearly one fifth of yield variability across a larger environmental network of 11 water-deficient trials. GLAI dynamics is a promising grain yield secondary trait in optimal and drought conditions, and the detected QTLs could help to increase breeding efficiency through a marker-assisted approach.

Effect of Zinc Foliar Fertilization Alone and Combined with Trehalose on Maize (Zea mays L.) Growth under the Drought

Maize (Zea mays L.) is one of the most widely grown cereals in the world. Its cultivation is affected by abiotic stress caused by climate change, in particular, drought. Zinc (Zn) supplied by foliar nutrition can increase plant resistance to water stress by enhancing physiological and enzymatic antioxidant defence mechanisms. One of the possibilities to reduce the effect of drought on plant production is also the utilization of trehalose. In order to confirm the effect of the foliar application of selected forms of Zn (0.1% w/v solution)-zinc oxide micro- (ZnO) and nanoparticles (ZnO^NP), zinc sulphate (ZnSO₄) and zinc chelate (ZnEDTA)-a pot experiment in controlled conditions was conducted in combination with trehalose (1% w/v solution) on selected growth parameters of maize exposed to the drought stress. A significant effect of coapplication of Zn and trehalose on chlorophyll content, chlorophyll fluorescence parameters, root electrical capacity, weight of maize aboveground biomass (AGB) and Zn content in AGB was found. At the same time, the hypothesis of a positive effect of carbohydrates on increasing the uptake of foliar-applied Zn was confirmed, especially for the ZnEDTA and ZnSO₄. This paper presents the first empirical evidence of the trehalose addition to sprays for zinc foliar fertilization of maize proving to be an effective way of increasing the resistance of maize grown under drought stress conditions.

Recurrent Interpopulation Selection in Popcorn: From Heterosis to Genetic Gains

In view of the need to develop new popcorn cultivars and considering the uncertainties in choosing the most appropriate breeding methods to ensure consistent genetic progress, simultaneously for both popping expansion and grain yield, this study addressed the efficiency of interpopulation recurrent selection regarding genetic gains, the study of the response in genetic parameters as well as heterotic effects on the control of the main agronomic traits of popcorn. Two populations were established, Pop₁ and Pop₂. A total of 324 treatments were evaluated, which consisted of 200 half-sib families (100 from Pop₁ and 100 from Pop₂), 100 full-sib families from the two populations and 24 controls. The field experiment was arranged in a lattice design with three replications in two environments, in the north and northwest regions of the State of Rio de Janeiro, Brazil. The genotype × environment interaction was partitioned and the genetic parameters, heterosis and predicted gains were estimated by the Mulamba and Mock index, based on selection results in both environments. The genetic parameters detected variability that can be explored in successive interpopulation recurrent selection cycles. Exploring heterosis for GY, PE and yield components is a promising option to increase grain yield and quality. The Mulamba and Mock index was efficient in predicting the genetic gains in GY and PE. Interpopulation recurrent selection proved effective to provide genetic gains for traits with predominantly additive and dominance inheritance.

A comprehensive meta-QTL analysis for yield-related traits of durum wheat (Triticum turgidum L. var. durum) grown under different water regimes

Abiotic stress strongly affects yield-related traits in durum wheat, in particular drought is one of the main environmental factors that have effect on grain yield and plant architecture. In order to obtain new genotypes well adapted to stress conditions, the highest number of desirable traits needs to be combined in the same genotype. In this context, hundreds of quantitative trait loci (QTL) have been identified for yield-related traits in different genetic backgrounds and environments. Meta-QTL (MQTL) analysis is a useful approach to combine data sets and for creating consensus positions for the QTL detected in independent studies for the reliability of their location and effects. MQTL analysis is a useful method to dissect the genetic architecture of complex traits, which provide an extensive allelic coverage, a higher mapping resolution and allow the identification of putative molecular markers useful for marker-assisted selection (MAS). In the present study, a complete and comprehensive MQTL analysis was carried out to identify genomic regions associated with grain-yield related traits in durum wheat under different water regimes. A total of 724 QTL on all 14 chromosomes (genomes A and B) were collected for the 19 yield-related traits selected, of which 468 were reported under rainfed conditions, and 256 under irrigated conditions. Out of the 590 QTL projected on the consensus map, 421 were grouped into 76 MQTL associated with yield components under both irrigated and rainfed conditions, 12 genomic regions containing stable MQTL on all chromosomes except 1A, 4A, 5A, and 6B. Candidate genes associated to MQTL were identified and an in-silico expression analysis was carried out for 15 genes selected among those that were differentially expressed under drought. These results can be used to increase durum wheat grain yields under different water regimes and to obtain new genotypes adapted to climate change.

All Are in a Drought, but Some Stand Out: Multivariate Analysis in the Selection of Agronomic Efficient Popcorn Genotypes

The search for productive germplasm adapted to adverse conditions is an important action to mitigate the harmful effects of climate change. The aim was to identify the yield potential of 50 popcorn inbred lines grown in field conditions, in two crop seasons (CS), and under contrasting water conditions (WC). Morphoagronomic, physiological, and root system traits were evaluated. Joint and individual analyses of variance were performed, in addition to the multivariate GT bip-lot analysis. Expressive reductions between WC were observed in 100-grain weight (100 GW), popping expansion (PE), grain yield (GY), expanded popcorn volume per ha (EPV), row number per ear (RNE), plant height (PH), relative chlorophyll content (SPAD), and nitrogen balance index (NBI). It was found that the SPAD, 100 GW, GY, PE, and grain number per ear (GNE) traits had the most significant impact on the selection of genotypes. Regardless of WC and CS, the ideal lines were L294 and L688 for PE; L691 and L480 for GY; and L291 and L292 for both traits. SPAD, 100 GW, and GNE can contribute to the indirect selection. Our work contributes to understanding the damage caused by drought and the integration of traits for the indirect selection of drought-tolerant popcorn genotypes.

Driving Sustainable Popcorn Breeding for Drought Tolerance in Brazil

Drought currently affects several regions worldwide and tends to be more frequent due to climate change. It might compromise food security and the economic structure related to agribusiness. Popcorn has a crucial role in the Brazilian economy, but the cultivars that adapt to water stress, the most prejudicial abiotic stress for crop productivity, are unknown to date. This deficit of popcorn varieties adapted to heat and drought stresses will become more limiting with climate change. Given this scenario, knowing the genetic basis of agronomic traits under stress conditions is essential in promoting crop productivity and plant adaptation to abiotic stresses. Under two contrasting water conditions (WC) and different crop seasons (CS), we aimed to generate information about the combining ability of 10 popcorn progenitors and 15 hybrids through a partial diallel-mating design. The water stress was initiated at the male pre-anthesis stage. Significant genotype*crop seasons (G*CS), genotype*water condition (G*WC), and genotype*crop seasons*water condition (G*CS*WC) interactions were present. Regardless of CS and WC, non-additive effects controlled grain yield (GY), grain number per row (GN), ear length and diameter (ED), and 100-grain weight, while additive effects were present for popping expansion (PE). For each CS, regardless of WC, the cause-effect of GN (2018) and ED (2020) on GY seems to be an opportunity for indirect selection. Utilizing genetically broad-based hybrids is also a good opportunity for obtaining superior genotypes for GY and PE as it is possible to select inbred lines for both of these traits. We recommend the L76 × L61 hybrid for the Brazilian agribusiness context due to its greater productivity and dominance deviations.

Supporting Physiological Trait for Indirect Selection for Grain Yield in Drought-Stressed Popcorn

The identification of traits associated with drought tolerance in popcorn is a contribution to support selection of superior plants under soil water deficit. The objective of this study was to choose morphological traits and the leaf greenness index, measured on different dates, to estimate grain yield (GY) and popping expansion (PE), evaluated in a set of 20 popcorn lines with different genealogies, estimated by multiple regression models. The variables were divided into three groups: morpho-agronomic traits-100-grain weight (GW), prolificacy (PR), tassel length (TL), number of tassel branches, anthesis-silking interval, leaf angle (FA) and leaf rolling (FB); variables related to the intensity of leaf greenness during the grain-filling period, at the leaf level, measured by a portable chlorophyll meter (SPAD) and at the canopy level, calculated as the normalized difference vegetation index (NDVI). The inbred lines were cultivated under two water conditions: well-watered (WW), maintained at field capacity, and water stress (WS), for which irrigation was stopped before male flowering. The traits GY (55%) and PE (28%) were most affected by water restriction. Among the morpho-agronomic traits, GW and PR were markedly reduced (>10%). Under dry conditions, the FA in relation to the plant stalk tended to be wider, the FB curvature greater and leaf senescence accelerated (>15% at 22 days after male flowering). The use of multiple regression for the selection of predictive traits proved to be a useful tool for the identification of groups of adequate traits to efficiently predict the economically most important features of popcorn (GY and PE). The SPAD index measured 17 days after male flowering proved useful to select indirectly for GY, while, among the morphological traits, TL stood out for the same purpose. Of all traits, PR was most strongly related with PE under WS, indicating its use in breeding programs. The exploitation of these traits by indirect selection is expected to induce increments in GY and PE.

Alteration of Metabolites Accumulation in Maize Inbreds Leaf Tissue under Long-Term Water Deficit

Simple Summary

As sessile organisms, plants are constantly exposed to diverse environmental stresses of which water deficit is the most significant because it limits plant growth, development, and productivity. In this work, we showed the influence of non-irrigation treatment on changes in maize leaf metabolite content. We argued that the different susceptibility of maize inbred lines to long-term water deficit will result in different patterns of change in metabolite accumulation. We emphasized the need for the careful interpretation of the level and type of accumulated metabolites in order to assess the drought tolerance status of maize inbred lines in terms of improved grain yield exhibited under severe water deficit conditions. Leaf metabolites that have contributed to higher grain yield under the condition of long-term water deficit could be considered as biochemical markers useful in breeding drought-tolerant maize.

Abstract

Plants reconfigure their metabolic pathways to cope with water deficit. The aim of this study was to determine the status of the physiological parameters and the content of phenolic acids in the upper most ear leaf of maize inbred lines contrasting in drought tolerance in terms of improved plant productivity e.g., increased grain yield. The experiment was conducted under irrigation and rain-fed conditions. In drought-tolerant lines, the effect of water deficit was reflected through a chlorophyll and nitrogen balance index increase followed by a flavonols index decrease. The opposite trend was noticed in drought susceptible inbreds, with the exception of the anthocyanins index. Moreover, in comparison to irrigation treatment, opposite trends in the correlations between grain yield and physiological parameters found under water deficit conditions indicated the activation of different metabolic pathways in defense against water deficit stress. Concerning phenolic acid content, water deficit caused the reduction of protocatechuic, caffeic, and sinapic acid in all inbreds evaluated. However, the highly pronounced increase of ferulic and especially cinnamic acid content under water deficit conditions indicated possible crucial role of these secondary metabolites in preventing the harmful effects of water deficit stress, which, in turn, might be useful in maize breeding selection for drought tolerance.

Bottlenecks and opportunities in field-based high-throughput phenotyping for heat and drought stress

Flowering and grain-filling stages are highly sensitive to heat and drought stress exposure, leading to significant loss in crop yields. Therefore, phenotyping to enhance resilience to these abiotic stresses is critical for sustaining genetic gains in crop improvement programs. However, traditional methods for screening traits related to these stresses are slow, laborious, and often expensive. Remote sensing provides opportunities to introduce low-cost, less biased, high-throughput phenotyping methods to capture large genetic diversity to facilitate enhancement of stress resilience in crops. This review focuses on four key physiological traits and processes that are critical in understanding crop responses to drought and heat stress during reproductive and grain-filling periods. Specifically, these traits include: (i) time of day of flowering, to escape these stresses during flowering; (ii) optimizing photosynthetic efficiency; (iii) storage and translocation of water-soluble carbohydrates; and (iv) yield and yield components to provide in-season yield estimates. Moreover, we provide an overview of current advances in remote sensing in capturing these traits, and discuss the limitations with existing technology as well as future direction of research to develop high-throughput phenotyping approaches. In the future, phenotyping these complex traits will require sensor advancement, high-quality imagery combined with machine learning methods, and efforts in transdisciplinary science to foster integration across disciplines.

Phenotyping Latin American Open-Pollinated Varieties of Popcorn for Environments with Low Water Availability

Drought is a common abiotic stress in tropical and subtropical regions that limits the growth and development of agricultural crops, mainly impacting grain yield. Acting through plant breeding is the most viable alternative for obtaining genotypes more tolerant of environments with stress. This work aims to select popcorn genotypes for environments with drought and to identify discriminating traits for the evaluation of drought tolerance in popcorn germplasm. Fifteen Latin American populations of popcorn were evaluated in water stress (WS) and well-watered (WW) conditions. The evaluated traits were based in morpho-agronomic, physiological and radicular descriptors. Data were submitted to individual and joint ANOVA and GT Biplot analysis. Variability was detected between populations for all traits in both conditions. The drought caused a reduction of 30.61% and 3.5% in grain yield and popping expansion, respectively. Based in GT biplot analysis, 880POP was the most stable in WS and WW, being indicated as a promising population for cultivation in environments with water limitation. This study is going to allow the establishment of a collection of great importance to maize germplasm and to provide information to facilitate the process of selection in breeding programs focused on drought tolerance.

Effects of 24-epibrassinolide on plant growth, antioxidants defense system, and endogenous hormones in two wheat varieties under drought stress

Drought stress is a major limitation in enhancing agricultural productivity to fulfill the food demand for the world's population. Fertigation of plants with a variety of biochemicals is being used to create drought resistance in wheat; however, the previous work has been limited in addressing these issues in plants at different growth stages. Therefore, a greenhouse study was conducted to ameliorate the drought stress in two wheat varieties (Chakwal-50 and Faisalabad-2008) by foliar application of 24-epibrassinolide (EBL). It was evident that drought stress had a negative effect on the growth, photosynthesis, and yield of wheat plants. EBL significantly enhanced the plant growth both under optimal and drought conditions. EBL improved the plant height, spike length, and the dry weights of roots, shoots, and grains as compared to control. Furthermore, the foliar application of EBL positively enhanced the osmolyte accumulation, increased the amounts of photosynthetic pigments, and improved the gas exchange parameters. The EBL minimized the oxidative stress by reducing electrolyte leakage, malondialdehyde, and hydrogen peroxide contents whereas it enhanced the activities of antioxidant enzymes, such as catalase, superoxide dismutase, and peroxidase under drought stress. The EBL significantly improved the level of stress hormones, such as abscisic acid, indol acetic acid, and cytokinin under drought stress. The growth response of Chakwal-50 was higher than that of Faisalabad-2008 when exposed to EBL under drought stress. Overall, the EBL plays a major role in the enhancement of growth, biomass, yield, and decrease in oxidative damage in wheat under drought conditions, however; field investigations with different doses of EBL are needed before any further recommendation.

Dynamics of Maize Vegetative Growth and Drought Adaptability Using Image-Based Phenotyping Under Controlled Conditions

Changes in climate are likely to have a negative impact on water availability and soil fertility in many maize-growing agricultural areas. The development of high-throughput phenotyping platforms provides a new prospect for dissecting the dynamic complex plant traits such as abiotic stress tolerance into simple components. The growth phenotypes of 20 maize (Zea mays L.) inbred lines were monitored in a non-invasive way under control, nitrogen, and water limitation as well as under combined nitrogen and water stress using an automated phenotyping system in greenhouse conditions. Thirteen biomass-related and morphophysiological traits were extracted from RGB images acquired at 33 time points covering developmental stages from leaf count 5 at the first imaging date to leaf count 10-13 at the final harvest. For these traits, genetic differences were identified and dynamic developmental trends during different maize growth stages were analyzed. The difference between control and water stress was detectable 3-10 days after the beginning of stress depending on the genotype, while the effect of limited nitrogen supply only induced subtle phenotypic effects. Phenotypic traits showed different response dynamics as well as multiple and changing interaction patterns with stress progression. The estimated biovolume, leaf area index, and color ratios were found to be stress-responsive at different stages of drought stress progression and thereby represent valuable reference indicators in the selection of drought-adaptive genotypes. Furthermore, genotypes could be grouped according to two typical growth dynamic patterns in water stress treatments by c-means clustering analysis. Inbred lines with high drought adaptability across time and development were identified and could serve as a basis for designing novel genotypes with desired, stage-specific growth phenotypes under water stress through pyramiding. Drought recovery potential may play an equal role as drought tolerance in plant drought adaptation.

Unraveling candidate genomic regions responsible for delayed leaf senescence in rice

Photosynthates generated after heading contributes to 60% - 80% of grain yield in rice. Delay in leaf senescence can contribute to a long grain-filling period and thereby increased yield. The objective of this study was to identify genomic region(s) responsible for delayed leaf senescence (DLS) and validate the role of underlying candidate genes in controlling target traits. 302 BC₂F₄ backcross-derived lines (BILs) developed from a cross between Swarna and Moroberekan were phenotyped for two seasons (DS2016 and WS2017) for chlorophyll content and yield parameters. KASPar-SNP assays based genotyping data with 193 SNPs of mapping population was used to identify the targeted genomic region(s). Significant positive correlation was observed between the two most important determinants of DLS traits viz., RDCF (reduced decline degree of chlorophyll content of flag leaf) and RDCS (reduced decline degree of chlorophyll content of second leaf) with plant height (PH), grain number per panicle (GPN), panicle length (PL), number of tiller (NT) and grain yield (GY). A total of 41 and 29 QTLs with phenotypic variance (PVE) ranging from 8.2 to 25.1% were detected for six DLS traits during DS2016 and WS2017, respectively. Out of these identified QTLs, 19 were considered as stable QTLs detected across seasons. 17 of the identified stable QTLs were found to be novel. In-silico analysis revealed five key genes regulating chlorophyll metabolism. Expression analysis of these genes confirmed their strong association with the senescence pattern in leaf tissue of parents as well as selected phenotypically extreme lines. The identified stable QTLs regulating DLS traits and validation of potential candidate genes provides insight into genetic basis of delayed senescence and is expected to contribute in enhancing grain yield through genomics-assisted breeding (GAB).

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.

Comparison of Selection Traits for Effective Popcorn (Zea mays 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_soil≥ -1.5 MPa) conditions. Water stress was applied by withholding irrigation in the phenological phase of male pre-anthesis. Additionally, two contrasting inbred lines, P7 (superior line) and L75 (low performer) were compared for grain yield (GY) and expanded popcorn volume (EPV), selected from previous studies, were tested under greenhouse conditions. In the field, no genotype x water condition x crop season (G×WC×CS) interaction was observed, whereas GY (-51%), EPV (-55%) and leaf greenness (SPAD index) measured 17 days after anthesis (DAA) (> -10%) were highly affected by water limitation. In general, root traits (angles, number, and density) presented G×WC×CS interaction, which did not support their use as selection parameters. In relation to leaf senescence, for both WS and WW conditions, the superior inbred lines maintained a stay-green condition (higher SPAD index) until physiological maturity, but maximum SPAD index values were observed later in WW (48.7 by 14 DAA) than in WS (43.9 by 7 DAA). Under both water conditions, negative associations were observed between SPAD index values 15 and 8 days before anthesis DBA), and GY and EPV (r ≥ -0.69), as well as between SPAD index 7, 17, and 22 DAA, and angles of brace root (AB), number of crown roots (NC) and crown root density (CD), in WS (r ≥ -0.69), and AB and CD, in WW (r ≥ -0.70). Lower NC and CD values may allow further root deepening in WS conditions. Under WS P7 maintained higher net photosynthesis values, stomatal conductance, and transpiration, than L75. Additionally, L75 exhibited a lower (i.e., more negative) carbon isotope composition value than P7 under WS, confirming a lower stomatal aperture in L75. In summary, besides leaf greenness, traits related to leaf photosynthetic status, and stomatal conductance were shown to be good indicators of the agronomic performance of popcorn under water constraint.

α-Tocopherol Foliar Spray and Translocation Mediates Growth, Photosynthetic Pigments, Nutrient Uptake, and Oxidative Defense in Maize (Zea mays L.) under Drought Stress

A pot experiment was conducted to assess the induction of drought tolerance in maize by foliar-applied α-tocopherol at early growth stage. Experiment was comprised two maize cultivars (Agaiti-2002 and EV-1098), two water stress levels (70% and 100% field capacity), and two α-tocopherol levels (0 mmol and 50 mmol) as foliar spray. Experiment was arranged in a completely randomized design in factorial arrangement with three replications of each treatment. α-tocopherol was applied foliary at the early vegetative stage. Water stress reduced the growth of maize plants with an increase in lipid peroxidation in both maize cultivars. Contents of non-enzymatic antioxidants and activities of antioxidant enzymes increased in studied plant parts under drought, while the nutrient uptake was decreased. Foliary-applied α-tocopherol improved the growth of both maize cultivars, associated with improvements in photosynthetic pigment, water relations, antioxidative mechanism, and better nutrient acquisition in root and shoot along with tocopherol contents and a decrease in lipid peroxidation. Furthermore, the increase of tocopherol levels in roots after α-Toc foliar application confers its basipetal translocation. In conclusion, the findings confer the role of foliar-applied α-tocopherol in the induction of drought tolerance of maize associated with tissue specific improvements in antioxidative defense mechanism through its translocation.

Automatic kernel counting on maize ear using RGB images

BACKGROUND

The number of kernels per ear is one of the major agronomic yield indicators for maize. Manual assessment of kernel traits can be time consuming and laborious. Moreover, manually acquired data can be influenced by subjective bias of the observer. Existing methods for counting of kernel number are often unstable and costly. Machine vision technology allows objective extraction of features from image sensor data, offering high-throughput and low-cost advantages.

RESULTS

Here, we propose an automatic kernel recognition method which has been applied to count the kernel number based on digital colour photos of the maize ears. Images were acquired under both LED diffuse (indoors) and natural light (outdoor) conditions. Field trials were carried out at two sites in China using 8 maize varieties. This method comprises five steps: (1) a Gaussian Pyramid for image compression to improve the processing efficiency, (2) separating the maize fruit from the background by Mean Shift Filtering algorithm, (3) a Colour Deconvolution (CD) algorithm to enhance the kernel edges, (4) segmentation of kernel zones using a local adaptive threshold, (5) an improved Find-Local-Maxima to recognize the local grayscale peaks and determine the maize kernel number within the image. The results showed good agreement (> 93%) in terms of accuracy and precision between ground truth (manual counting) and the image-based counting.

CONCLUSIONS

The proposed algorithm has robust and superior performance in maize ear kernel counting under various illumination conditions. In addition, the approach is highly-efficient and low-cost. The performance of this method makes it applicable and satisfactory for real-world breeding programs.

Stay-Green Trait: A Prospective Approach for Yield Potential, and Drought and Heat Stress Adaptation in Globally Important Cereals

The yield losses in cereal crops because of abiotic stress and the expected huge losses from climate change indicate our urgent need for useful traits to achieve food security. The stay-green (SG) is a secondary trait that enables crop plants to maintain their green leaves and photosynthesis capacity for a longer time after anthesis, especially under drought and heat stress conditions. Thus, SG plants have longer grain-filling period and subsequently higher yield than non-SG. SG trait was recognized as a superior characteristic for commercially bred cereal selection to overcome the current yield stagnation in alliance with yield adaptability and stability. Breeding for functional SG has contributed in improving crop yields, particularly when it is combined with other useful traits. Thus, elucidating the molecular and physiological mechanisms associated with SG trait is maybe the key to defeating the stagnation in productivity associated with adaptation to environmental stress. This review discusses the recent advances in SG as a crucial trait for genetic improvement of the five major cereal crops, sorghum, wheat, rice, maize, and barley with particular emphasis on the physiological consequences of SG trait. Finally, we provided perspectives on future directions for SG research that addresses present and future global challenges.

Alpha-tocopherol fertigation confers growth physio-biochemical and qualitative yield enhancement in field grown water deficit wheat (Triticum aestivum L.)

Water stress is a major problem to fulfill the world food demand and to solve the problem of malnutrition. Different strategies are being used to solve these problems including the fertigation of plants with different biochemical at different growth stages. The present study was conducted for the induction of drought tolerance in field grown wheat for better yield and nutritional quality through foliar spray of α-tocopherol (α-Toc) at start of reproductive stage. Water stress was maintained based on number of irrigation. Three levels of α-Toc 0.001, 0.01 and 0.1 mM were applied as foliar spray. Water stress significantly reduced the biomass production that associated with the decreased photosynthetic pigments, water relation, photosynthetic efficiency, but increased the lipid peroxidation, leaf relative membrane permeability, activities of antioxidant enzymes and the contents of phenolic, flavonoids, α-toc and ASA. Water stress also negatively effected the different yield attributes and seed nutrient quality. Foliar fertigation of wheat plants with α-Toc significantly improved the water stress tolerance of wheat plants in term of improvement in growth and seed yield associated with improved water relations, photosynthetic efficiency, contents of photosynthetic pigments and improvement in antioxidative defence mechanism (enzymatic and non-enzymatic antioxidants). Fertigation of water stressed wheat plants with α-Toc also improved the seed nutritional quality in terms of the contents of seed phenolics, flavonoids, activities of antioxidant enzymes and the content of α-, β- and γ-tocopherols. In conclusion, it was found that fertigation of water stressed wheat plants not only improved the water stress tolerance but also improved the seed yield and nutritional quality that will not only be helpful for the improvement in wheat yield that also be a step to solve the problem of malnutrition through the bio-fertification of α-Toc.

A High-Throughput Model-Assisted Method for Phenotyping Maize Green Leaf Area Index Dynamics Using Unmanned Aerial Vehicle Imagery

The dynamics of the Green Leaf Area Index (GLAI) is of great interest for numerous applications such as yield prediction and plant breeding. We present a high-throughput model-assisted method for characterizing GLAI dynamics in maize (Zea mays subsp. mays) using multispectral imagery acquired from an Unmanned Aerial Vehicle (UAV). Two trials were conducted with a high diversity panel of 400 lines under well-watered and water-deficient treatments in 2016 and 2017. For each UAV flight, we first derived GLAI estimates from empirical relationships between the multispectral reflectance and ground level measurements of GLAI achieved over a small sample of microplots. We then fitted a simple but physiologically sound GLAI dynamics model over the GLAI values estimated previously. Results show that GLAI dynamics was estimated accurately throughout the cycle (R2 > 0.9). Two parameters of the model, biggest leaf area and leaf longevity, were also estimated successfully. We showed that GLAI dynamics and the parameters of the fitted model are highly heritable (0.65 ≤ H2 ≤ 0.98), responsive to environmental conditions, and linked to yield and drought tolerance. This method, combining growth modeling, UAV imagery and simple non-destructive field measurements, provides new high-throughput tools for understanding the adaptation of GLAI dynamics and its interaction with the environment. GLAI dynamics is also a promising trait for crop breeding, and paves the way for future genetic studies.

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. We evaluated the performance of a set of remote sensing indices derived from red-green-blue (RGB) images along with field-based multispectral normalized difference vegetation index (NDVI) and leaf chlorophyll content (SPAD values) as phenotypic traits for assessing maize performance under managed low-nitrogen conditions. HTPP measurements were conducted from the ground and from an unmanned aerial vehicle (UAV). For the ground-level RGB indices, the strongest correlations to yield were observed with hue, greener green area (GGA), and a newly developed RGB HTPP index, NDLab (normalized difference Commission Internationale de I´Edairage (CIE)Lab index), while GGA and crop senescence index (CSI) correlated better with grain yield from the UAV. Regarding ground sensors, SPAD exhibited the closest correlation with grain yield, notably increasing in its correlation when measured in the vegetative stage. Additionally, we evaluated how different HTPP indices contributed to the explanation of yield in combination with agronomic data, such as anthesis silking interval (ASI), anthesis date (AD), and plant height (PH). Multivariate regression models, including RGB indices (R2 > 0.60), outperformed other models using only agronomic parameters or field sensors (R2 > 0.50), reinforcing RGB HTPP's potential to improve yield assessments. Finally, we compared the low-N results to the same panel of 64 maize genotypes grown under optimal conditions, noting that only 11% of the total genotypes appeared in the highest yield producing quartile for both trials. Furthermore, we calculated the grain yield loss index (GYLI) for each genotype, which showed a large range of variability, suggesting that low-N performance is not necessarily exclusive of high productivity in optimal conditions.

Identification of donors for low-nitrogen stress with maize lethal necrosis (MLN) tolerance for maize breeding in sub-Saharan Africa

After drought, a major challenge to smallholder farmers in sub-Saharan Africa is low-fertility soils with poor nitrogen (N)-supplying capacity. Many challenges in this region need to be overcome to create a viable fertilizer market. An intermediate solution is the development of maize varieties with an enhanced ability to take up or utilize N in severely depleted soils, and to more efficiently use the small amounts of N that farmers can supply to their crops. Over 400 elite inbred lines from seven maize breeding programs were screened to identify new sources of tolerance to low-N stress and maize lethal necrosis (MLN) for introgression into Africa-adapted elite germplasm. Lines with high levels of tolerance to both stresses were identified. Lines previously considered to be tolerant to low-N stress ranked in the bottom 10% under low-N confirming the need to replace these lines with new donors identified in this study. The lines that performed best under low-N yielded about 0. 5 Mg ha-1 (20%) more in testcross combinations than some widely used commercial parent lines such as CML442 and CML395. This is the first large scale study to identify maize inbred lines with tolerance to low-N stress and MLN in eastern and southern Africa.

Integration of multi-omics techniques and physiological phenotyping within a holistic phenomics approach to study senescence in model and crop plants

The study of senescence in plants is complicated by diverse levels of temporal and spatial dynamics as well as the impact of external biotic and abiotic factors and crop plant management. Whereas the molecular mechanisms involved in developmentally regulated leaf senescence are very well understood, in particular in the annual model plant species Arabidopsis, senescence of other organs such as the flower, fruit, and root is much less studied as well as senescence in perennials such as trees. This review addresses the need for the integration of multi-omics techniques and physiological phenotyping into holistic phenomics approaches to dissect the complex phenomenon of senescence. That became feasible through major advances in the establishment of various, complementary 'omics' technologies. Such an interdisciplinary approach will also need to consider knowledge from the animal field, in particular in relation to novel regulators such as small, non-coding RNAs, epigenetic control and telomere length. Such a characterization of phenotypes via the acquisition of high-dimensional datasets within a systems biology approach will allow us to systematically characterize the various programmes governing senescence beyond leaf senescence in Arabidopsis and to elucidate the underlying molecular processes. Such a multi-omics approach is expected to also spur the application of results from model plants to agriculture and their verification for sustainable and environmentally friendly improvement of crop plant stress resilience and productivity and contribute to improvements based on postharvest physiology for the food industry and the benefit of its customers.

High-throughput method for ear phenotyping and kernel weight estimation in maize using ear digital imaging

BACKGROUND

Grain yield, ear and kernel attributes can assist to understand the performance of maize plant under different environmental conditions and can be used in the variety development process to address farmer's preferences. These parameters are however still laborious and expensive to measure.

RESULTS

A low-cost ear digital imaging method was developed that provides estimates of ear and kernel attributes i.e., ear number and size, kernel number and size as well as kernel weight from photos of ears harvested from field trial plots. The image processing method uses a script that runs in a batch mode on ImageJ; an open source software. Kernel weight was estimated using the total kernel number derived from the number of kernels visible on the image and the average kernel size. Data showed a good agreement in terms of accuracy and precision between ground truth measurements and data generated through image processing. Broad-sense heritability of the estimated parameters was in the range or higher than that for measured grain weight. Limitation of the method for kernel weight estimation is discussed.

CONCLUSION

The method developed in this work provides an opportunity to significantly reduce the cost of selection in the breeding process, especially for resource constrained crop improvement programs and can be used to learn more about the genetic bases of grain yield determinants.

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.

Identification of QTL for Early Vigor and Stay-Green Conferring Tolerance to Drought in Two Connected Advanced Backcross Populations in Tropical Maize (Zea mays L.)

We aimed to identify quantitative trait loci (QTL) for secondary traits related to grain yield (GY) in two BC₁F_2:3 backcross populations (LPSpop and DTPpop) under well-watered (4 environments; WW) and drought stressed (6; DS) conditions to facilitate breeding efforts towards drought tolerant maize. GY reached 5.6 and 5.8 t/ha under WW in the LPSpop and the DTPpop, respectively. Under DS, grain yield was reduced by 65% (LPSpop) to 59% (DTPpop) relative to WW. GY was strongly associated with the normalized vegetative index (NDVI; r ranging from 0.61 to 0.96) across environmental conditions and with an early flowering under drought stressed conditions (r ranging from -0.18 to -0.25) indicative of the importance of early vigor and drought escape for GY. Out of the 105 detected QTL, 53 were overdominant indicative of strong heterosis. For 14 out of 18 detected vigor QTL, as well as for eight flowering time QTL the trait increasing allele was derived from CML491. Collocations of early vigor QTL with QTL for stay green (bin 2.02, WW, LPSpop; 2.07, DS, DTPpop), the number of ears per plant (bins 2.02, 2.05, WW, LPSpop; 5.02, DS, LPSpop) and GY (bin 2.07, WW, DTPpop; 5.04, WW, LPSpop), reinforce the importance of the observed correlations. LOD scores for early vigor QTL in these bins ranged from 2.2 to 11.25 explaining 4.6 (additivity: +0.28) to 19.9% (additivity: +0.49) of the observed phenotypic variance. A strong flowering QTL was detected in bin 2.06 across populations and environmental conditions explaining 26–31.3% of the observed phenotypic variation (LOD: 13–17; additivity: 0.1–0.6d). Improving drought tolerance while at the same time maintaining yield potential could be achieved by combining alleles conferring early vigor from the recurrent parent with alleles advancing flowering from the donor. Additionally bin 8.06 (DTPpop) harbored a QTL for GY under WW (additivity: 0.27 t/ha) and DS (additivity: 0.58 t/ha). R² ranged from 0 (DTPpop, WW) to 26.54% (LPSpop, DS) for NDVI, 18.6 (LPSpop, WW) to 42.45% (LPSpop, DS) for anthesis and from 0 (DTPpop, DS) to 24.83% (LPSpop, WW) for GY. Lines out-yielding the best check by 32.5% (DTPpop, WW) to 60% (DTPpop, DS) for all population-by-irrigation treatment combination (except LPSpop, WW) identified are immediately available for the use by breeders.

Staying Alive or Going to Die During Terminal Senescence-An Enigma Surrounding Yield Stability

Breeding programs with the aim to enhance yield productivity under abiotic stress conditions during the reproductive stage of crops is a top priority in the era of climate change. However, the choice of exploring stay-green or senescence phenotypes, which represent an opposing physiological bearing, are explored in cereal breeding programs for enhanced yield stability to a different extent. Thus, the consideration of stay-green or senescence phenotypes is still an ongoing debate and has not been comprehensively addressed. In this review, we provide arguments for designing a target phenotype to mitigate abiotic stresses during pre- and post-anthesis in cereals with a focus on hormonal balances regulating stay-green phenotype versus remobilization. The two major hypothesis for grain yield improvement are (i) the importance of the stay-green trait to elevate grain number under pre-anthesis and anthesis stress and (ii) fine tuning the regulatory and molecular physiological mechanisms to accelerate nutrient remobilization to optimize grain quality and seed weight under post-anthesis stress. We highlight why a cautious balance in the phenotype design is essential. While stay-green phenotypes promise to be ideal for developing stress-tolerant lines during pre-anthesis and fertilization to enhance grain number and yield per se, fine-tuning efficient remobilizing behavior during seed filling might optimize grain weight, grain quality and nutrient efficiency. The proposed model provides novel and focused directions for cereal stress breeding programs to ensure better seed-set and efficient grain-filling in cereals under terminal drought and heat stress exposure.

Multispectral airborne imagery in the field reveals genetic determinisms of morphological and transpiration traits of an apple tree hybrid population in response to water deficit

Genetic studies of response to water deficit in adult trees are limited by low throughput of the usual phenotyping methods in the field. Here, we aimed at overcoming this bottleneck, applying a new methodology using airborne multispectral imagery and in planta measurements to compare a high number of individuals.An apple tree population, grafted on the same rootstock, was submitted to contrasting summer water regimes over two years. Aerial images acquired in visible, near- and thermal-infrared at three dates each year allowed calculation of vegetation and water stress indices. Tree vigour and fruit production were also assessed. Linear mixed models were built accounting for date and year effects on several variables and including the differential response of genotypes between control and drought conditions.Broad-sense heritability of most variables was high and 18 quantitative trait loci (QTLs) independent of the dates were detected on nine linkage groups of the consensus apple genetic map. For vegetation and stress indices, QTLs were related to the means, the intra-crown heterogeneity, and differences induced by water regimes. Most QTLs explained 15-20% of variance.Airborne multispectral imaging proved relevant to acquire simultaneous information on a whole tree population and to decipher genetic determinisms involved in response to water deficit.

Plant phenotyping: from bean weighing to image analysis

Plant phenotyping refers to a quantitative description of the plant's anatomical, ontogenetical, physiological and biochemical properties. Today, rapid developments are taking place in the field of non-destructive, image-analysis -based phenotyping that allow for a characterization of plant traits in high-throughput. During the last decade, 'the field of image-based phenotyping has broadened its focus from the initial characterization of single-plant traits in controlled conditions towards 'real-life' applications of robust field techniques in plant plots and canopies. An important component of successful phenotyping approaches is the holistic characterization of plant performance that can be achieved with several methodologies, ranging from multispectral image analyses via thermographical analyses to growth measurements, also taking root phenotypes into account.

Remote, aerial phenotyping of maize traits with a mobile multi-sensor approach

BACKGROUND

Field-based high throughput phenotyping is a bottleneck for crop breeding research. We present a novel method for repeated remote phenotyping of maize genotypes using the Zeppelin NT aircraft as an experimental sensor platform. The system has the advantage of a low altitude and cruising speed compared to many drones or airplanes, thus enhancing image resolution while reducing blurring effects. Additionally there was no restriction in sensor weight. Using the platform, red, green and blue colour space (RGB), normalized difference vegetation index (NDVI) and thermal images were acquired throughout the growing season and compared with traits measured on the ground. Ground control points were used to co-register the images and to overlay them with a plot map.

RESULTS

NDVI images were better suited than RGB images to segment plants from soil background leading to two separate traits: the canopy cover (CC) and its NDVI value (NDVIPlant). Remotely sensed CC correlated well with plant density, early vigour, leaf size, and radiation interception. NDVIPlant was less well related to ground truth data. However, it related well to the vigour rating, leaf area index (LAI) and leaf biomass around flowering and to very late senescence rating. Unexpectedly, NDVIPlant correlated negatively with chlorophyll meter measurements. This could be explained, at least partially, by methodical differences between the used devices and effects imposed by the population structure. Thermal images revealed information about the combination of radiation interception, early vigour, biomass, plant height and LAI. Based on repeatability values, we consider two row plots as best choice to balance between precision and available field space. However, for thermography, more than two rows improve the precision.

CONCLUSIONS

We made important steps towards automated processing of remotely sensed data, and demonstrated the value of several procedural steps, facilitating the application in plant genetics and breeding. Important developments are: the ability to monitor throughout the season, robust image segmentation and the identification of individual plots in images from different sensor types at different dates. Remaining bottlenecks are: sufficient ground resolution, particularly for thermal imaging, as well as a deeper understanding of the relatedness of remotely sensed data and basic crop characteristics.

Unmanned aerial platform-based multi-spectral imaging for field phenotyping of maize

BACKGROUND

Recent developments in unmanned aerial platforms (UAP) have provided research opportunities in assessing land allocation and crop physiological traits, including response to abiotic and biotic stresses. UAP-based remote sensing can be used to rapidly and cost-effectively phenotype large numbers of plots and field trials in a dynamic way using time series. This is anticipated to have tremendous implications for progress in crop genetic improvement.

RESULTS

We present the use of a UAP equipped with sensors for multispectral imaging in spatial field variability assessment and phenotyping for low-nitrogen (low-N) stress tolerance in maize. Multispectral aerial images were used to (1) characterize experimental fields for spatial soil-nitrogen variability and (2) derive indices for crop performance under low-N stress. Overall, results showed that the aerial platform enables to effectively characterize spatial field variation and assess crop performance under low-N stress. The Normalized Difference Vegetation Index (NDVI) data derived from spectral imaging presented a strong correlation with ground-measured NDVI, crop senescence index and grain yield.

CONCLUSION

This work suggests that the aerial sensing platform designed for phenotyping studies has the potential to effectively assist in crop genetic improvement against abiotic stresses like low-N provided that sensors have enough resolution for plot level data collection. Limitations and future potential uses are also discussed.

Detection and validation of stay-green QTL in post-rainy sorghum involving widely adapted cultivar, M35-1 and a popular stay-green genotype B35

BACKGROUND

Sorghum [Sorghum bicolor (L.) Moench] is an important dry-land cereal of the world providing food, fodder, feed and fuel. Stay-green (delayed-leaf senescence) is a key attribute in sorghum determining its adaptation to terminal drought stress. The objective of this study was to validate sorghum stay-green quantitative trait loci (QTL) identified in the past, and to identify new QTL in the genetic background of a post-rainy adapted genotype M35-1.

RESULTS

A genetic linkage map based on 245 F9 Recombinant Inbred Lines (RILs) derived from a cross between M35-1 (more senescent) and B35 (less senescent) with 237 markers consisting of 174 genomic, 60 genic and 3 morphological markers was used. The phenotypic data collected for three consecutive post-rainy crop seasons on the RIL population (M35-1 × B35) was used for QTL analysis. Sixty-one QTL were identified for various measures of stay-green trait and each trait was controlled by one to ten QTL. The phenotypic variation explained by each QTL ranged from 3.8 to 18.7%. Co-localization of QTL for more than five traits was observed on two linkage groups i.e. on SBI-09-3 flanked by S18 and Xgap206 markers and, on SBI-03 flanked by XnhsbSFCILP67 and Xtxp31. QTL identified in this study were stable across environments and corresponded to sorghum stay-green and grain yield QTL reported previously. Of the 60 genic SSRs mapped, 14 were closely linked with QTL for ten traits. A genic marker, XnhsbSFCILP67 (Sb03g028240) encoding Indole-3-acetic acid-amido synthetase GH3.5, was co-located with QTL for GLB, GLM, PGLM and GLAM on SBI-03. Genes underlying key enzymes of chlorophyll metabolism were also found in the stay-green QTL regions.

CONCLUSIONS

We validated important stay-green QTL reported in the past in sorghum and detected new QTL influencing the stay-green related traits consistently. Stg2, Stg3 and StgB were prominent in their expression. Collectively, the QTL/markers identified are likely candidates for subsequent verification for their involvement in stay-green phenotype using NILs and to develop drought tolerant sorghum varieties through marker-assisted breeding for terminal drought tolerance in sorghum.

Influence of the variation of geometrical and topological traits on light interception efficiency of apple trees: sensitivity analysis and metamodelling for ideotype definition

BACKGROUND AND AIMS

The impact of a fruit tree's architecture on its performance is still under debate, especially with regard to the definition of varietal ideotypes and the selection of architectural traits in breeding programmes. This study aimed at providing proof that a modelling approach can contribute to this debate, by using in silico exploration of different combinations of traits and their consequences on light interception, here considered as one of the key parameters to optimize fruit tree production.

METHODS

The variability of organ geometrical traits, previously described in a bi-parental population, was used to simulate 1- to 5-year-old apple trees (Malus × domestica). Branching sequences along trunks observed during the first year of growth of the same hybrid trees were used to initiate the simulations, and hidden semi-Markov chains previously parameterized were used in subsequent years. Tree total leaf area (TLA) and silhouette to total area ratio (STAR) values were estimated, and a sensitivity analysis was performed, based on a metamodelling approach and a generalized additive model (GAM), to analyse the relative impact of organ geometry and lateral shoot types on STAR.

KEY RESULTS

A larger increase over years in TLA mean and variance was generated by varying branching along trunks than by varying organ geometry, whereas the inverse was observed for STAR, where mean values stabilized from year 3 to year 5. The internode length and leaf area had the highest impact on STAR, whereas long sylleptic shoots had a more significant effect than proleptic shoots. Although the GAM did not account for interactions, the additive effects of the geometrical factors explained >90% of STAR variation, but much less in the case of branching factors.

CONCLUSIONS

This study demonstrates that the proposed modelling approach could contribute to screening architectural traits and their relative impact on tree performance, here viewed through light interception. Even though trait combinations and antagonism will need further investigation, the approach opens up new perspectives for breeding and genetic selection to be assisted by varietal ideotype definition.

Field high-throughput phenotyping: the new crop breeding frontier

Constraints in field phenotyping capability limit our ability to dissect the genetics of quantitative traits, particularly those related to yield and stress tolerance (e.g., yield potential as well as increased drought, heat tolerance, and nutrient efficiency, etc.). The development of effective field-based high-throughput phenotyping platforms (HTPPs) remains a bottleneck for future breeding advances. However, progress in sensors, aeronautics, and high-performance computing are paving the way. Here, we review recent advances in field HTPPs, which should combine at an affordable cost, high capacity for data recording, scoring and processing, and non-invasive remote sensing methods, together with automated environmental data collection. Laboratory analyses of key plant parts may complement direct phenotyping under field conditions. Improvements in user-friendly data management together with a more powerful interpretation of results should increase the use of field HTPPs, therefore increasing the efficiency of crop genetic improvement to meet the needs of future generations.

Stay-green trait-antioxidant status interrelationship in durum wheat (Triticum durum) flag leaf during post-flowering

Three independent durum wheat mutant lines that show delayed leaf senescence or stay-green (SG) phenotype, SG196, SG310 and SG504, were compared to the parental genotype, cv. Trinakria, with respect to the photosynthetic parameters and the cellular redox state of the flag leaf in the period from flowering to senescence. The SG mutants maintained their chlorophyll content and net photosynthetic rate for longer than Trinakria, thus revealing a functional SG phenotype. They also showed a better redox state as demonstrated by: (1) a lower rate of superoxide anion production due to generally higher activity of the antioxidant enzymes superoxide dismutase and catalase in all of the SG mutants and also of the total peroxidase in SG196; (2) a higher thiol content that can be ascribed to a higher activity of the NADPH-providing enzyme glucose-6-phosphate dehydrogenase in all of the SG mutants and also of the NADP(+)-dependent malic enzyme in SG196; (3) a lower pro-oxidant activity of lipoxygenase that characterises SG196 and SG504 mutants close to leaf senescence. Overall, these results show a general relationship in durum wheat between the SG phenotype and a better redox state. This relationship differs across the different SG mutants, probably as a consequence of the different set of altered genes underlying the SG trait in these independent mutant lines.

Alleviation of osmotic stress effects by exogenous application of salicylic or abscisic acid on wheat seedlings

The aim of the study was to assess the role of salicylic acid (SA) and abscisic acid (ABA) in osmotic stress tolerance of wheat seedlings. This was accomplished by determining the impact of the acids applied exogenously on seedlings grown under osmotic stress in hydroponics. The investigation was unique in its comprehensiveness, examining changes under osmotic stress and other conditions, and testing a number of parameters simultaneously. In both drought susceptible (SQ1) and drought resistant (CS) wheat cultivars, significant physiological and biochemical changes were observed upon the addition of SA (0.05 mM) or ABA (0.1 μM) to solutions containing half-strength Hoagland medium and PEG 6000 (−0.75 MPa). The most noticeable result of supplementing SA or ABA to the medium (PEG + SA and PEG + ABA) was a decrease in the length of leaves and roots in both cultivars. While PEG treatment reduced gas exchange parameters, chlorophyll content in CS, and osmotic potential, and conversely, increased lipid peroxidation, soluble carbohydrates in SQ1, proline content in both cultivars and total antioxidants activity in SQ1, PEG + SA or PEG + ABA did not change the values of these parameters. Furthermore, PEG caused a two-fold increase of endogenous ABA content in SQ1 and a four-fold increase in CS. PEG + ABA increased endogenous ABA only in SQ1, whereas PEG + SA caused a greater increase of ABA content in both cultivars compared to PEG. In PEG-treated plants growing until the harvest, a greater decrease of yield components was observed in SQ1 than in CS. PEG + SA, and particularly PEG + ABA, caused a greater increase of these yield parameters in CS compared to SQ1. In conclusion, SA and ABA ameliorate, particularly in the tolerant wheat cultivar, the harmful effects and after effects of osmotic stress induced by PEG in hydroponics through better osmotic adjustment achieved by an increase in proline and carbohydrate content as well as by an increase in antioxidant activity.