A superior gene allele involved in abscisic acid signaling enhances drought tolerance and yield in chickpea

Identifying potential molecular tags for drought tolerance is essential for achieving higher crop productivity under drought stress. We employed an integrated genomics-assisted breeding and functional genomics strategy involving association mapping, fine mapping, map-based cloning, molecular haplotyping and transcript profiling in the introgression lines (ILs)- and near isogenic lines (NILs)-based association panel and mapping population of chickpea (Cicer arietinum). This combinatorial approach delineated a bHLH (basic helix-loop-helix) transcription factor, CabHLH10 (Cicer arietinum bHLH10) underlying a major QTL, along with its derived natural alleles/haplotypes governing yield traits under drought stress in chickpea. CabHLH10 binds to a cis-regulatory G-box promoter element to modulate the expression of RD22 (responsive to desiccation 22), a drought/abscisic acid (ABA)-responsive gene (via a trans-expression QTL), and two strong yield-enhancement photosynthetic efficiency (PE) genes. This, in turn, upregulates other downstream drought-responsive and ABA signaling genes, as well as yield-enhancing PE genes, thus increasing plant adaptation to drought with reduced yield penalty. We showed that a superior allele of CabHLH10 introgressed into the NILs improved root and shoot biomass and PE, thereby enhancing yield and productivity during drought without compromising agronomic performance. Furthermore, overexpression of CabHLH10 in chickpea and Arabidopsis (Arabidopsis thaliana) conferred enhanced drought tolerance by improving root and shoot agro-morphological traits. These findings facilitate translational genomics for crop improvement and the development of genetically tailored, climate-resilient, high-yielding chickpea cultivars.

A comparative study on comprehensive nutritional profiling of indigenous non-bio-fortified and bio-fortified varieties and bio-fortified hybrids of pearl millets

Seven indigenous pearl millet varieties, including non-bio-fortified (HC-10 & HC-20) and bio-fortified (Dhanashakti) and bio-fortified hybrids, viz., AHB-1200, HHB-299, HHB-311, and RHB-233, were studied in the present work. There was not any significant difference observed in the crucial anti-nutrients content, i.e., phytate (24.88-32.56 mg/g), tannin (3.07-4.35 mg/g), and oxalate (0.33-0.43 mg/g). Phytochemical content and antioxidant activity showed significantly high (p < 0.05) TPC and FRAP, TFC, and DPPH radical scavenging activity in the HHB 299 and Dhanashakti, respectively. Quantitative analysis of polyphenols by HPLC (first report on these varieties) revealed that HHB-299 has the highest amount of gallic acid. Fatty acid profiling by GC-FID showed that Dhanashakti, AHB-1200, and HHB-299 have rich monounsaturated fatty acid (MUFA) and polyunsaturated fatty acids (PUFA). Mineral analysis by ICP-OES showed high iron (87.79 and 84.26 mg/kg) and zinc (55.05 and 52.43 mg/kg) content in the HHB-311 and Dhanashakti, respectively. Results of the present study would help facilitate the formulation of various processed functional food products (RTC/RTE) that are currently not reported/unavailable.

Supplementary Information

The online version contains supplementary material available at 10.1007/s13197-022-05452-x.

CRISPR/Cas9 editing of wheat Ppd-1 gene homoeologs alters spike architecture and grain morphometric traits

Mutations in Photoperiod-1 (Ppd-1) gene are known to modify flowering time and yield in wheat. We cloned TaPpd-1 from wheat and found high similarity among the three homoeologs of TaPpd-1. To clarify the characteristics of TaPpd-1 homoeologs in different photoperiod conditions for inflorescence architecture and yield, we used CRISPR/Cas9 system to generate Tappd-1 mutant plants by simultaneous modification of the three homoeologs of wheat Ppd-1. Tappd-1 mutant plants showed no off-target mutations. Four T₀-edited lines under short-day length and three lines under long-day length conditions with the mutation frequency of 25% and 21%, respectively. These putative transgenic plants of all the lines were self-fertilized and generated T₁ and T₂ progenies and were evaluated by phenotypic and expression analysis. Results demonstrated that simultaneously edited TaPpd-1- A1, B1, and D1 homoeologs gene copies in T2_SDL-8-4, T2_SDL-4-5, T2_SDL-3-9, and T2_{_}LDL-10-9 showed similar spike inflorescence, flowering time, and significantly increase in 1000-grain weight, grain area, grain width, grain length, plant height, and spikelets per spike due to mutation in both alleles of Ppd-B1 and Ppd-D1 homoeologs but only spike length was decreased in T2_SDL-8-4, T2_SDL-4-5, and T2_{_}LDL-13-3 mutant lines due to mutation in both alleles of Ppd-A1 homoeolog under both conditions. Our results indicate that all TaPpd1 gene homoeologs influence wheat spike development by affecting both late flowering and earlier flowering but single mutant TaPpd-A1 homoeolog affect lowest as compared to the combination with double mutants of TaPpd-B1 and TaPpd-D1, TaPpd-A1 and TaPpd-B1, and TaPpd-A1 and TaPpd-D1 homoeologs for yield enhancement. Our findings further raised the idea that the relative expression of the various genomic copies of TaPpd-1 homoeologs may have an impact on the spike inflorescence architecture and grain morphometric features in wheat cultivars.

Evaluation of chlorophyll content and membrane stability under oxidative stress induced by glyphosate herbicide as indicators of drought tolerance in some advanced durum wheat (Triticum durum L.) lines: in vitro study

Oxidative stress caused by glyphosate is a complex chemical and physiological phenomenon and develops as a result of overproduction and accumulation of reactive oxygen species (ROS). This study was carried out in vitro at the National Institute of Agronomic Research of Algeria (INRAA) Setif, to select the most susceptible durum wheat (Triticum durum L.) under oxidative stress induced by glyphosate herbicide by evaluating chlorophyll content degradation and cell membrane leakage. Genotypes showed significant variations in almost all the studied traits. The chlorophyll loss ratio ranged from 26.42 % for the genotype G5 to 48.75 % for the local variety Boutaleb, glyphosate sensitivity index values were found to be between 0.65-1.2, the advanced line G5 was found to be the most tolerant under oxidative stress with the lowest chlorophyll loss ratio and lowest Glyphosate sensitivity index. Furthermore, the advanced line G4 recorded the highest electrolyte leakage (80.16 %) while G6 showed the lowest estimate (50.77 %). Therefore, advanced lines G5 and G6 appear the most suitable for the growing conditions.

Effect of Heat Processing of Rubber Seed Kernel on In Vitro Rumen Biohydrogenation of Fatty Acids and Fermentation

The aim of this study was to assess the effect of rubber seed kernel heat processing on in vitro rumen biohydrogenation of fatty acids and fermentation. The experiment was conducted with a completely randomized design (CRD). The inclusion of RSK at 0% (CON) and 20% with different processing methods as follows: Raw rubber seed kernel (RAWR), roasted rubber seed kernel (ROR), microwave irradiated rubber seed kernel (MIR), and rubber seed kernel were heated in a hot air oven (RHO) in total mixed ration (TMR) diets. The hydrogen cyanide (HCN) was reduced using RSK heat methods. The heat processing of RSK had no effect on cumulative gas production at 96 h, the gas production from the insoluble fraction (b), or degradability (p > 0.05), whereas it reduced the gas production from the immediately soluble fraction (a) and constant rate of gas production for the insoluble fraction (c) (p < 0.01). The RSK processing methods did not influence ruminal pH, total volatile fatty acid (VFA), or VFA proportions (p > 0.05). RSK heat processing reduced ammonia-nitrogen (NH3-N) (p < 0.04) while increasing the bacterial population (p < 0.02). Heat treatment had no effect on linoleic acid (C18:2 cis-9,12 + tran-9,12) (p > 0.05). The RHO increases oleic acid (C18:1 cis-9 + tran-9) and linolenic acid (C18:3 cis-9,12,15) concentrations (p < 0.01). In conclusion, RHO reduced rumen biohydrogenation of unsaturated fatty acids (UFA), especially C18:3 and C18:1.

Marker-trait association analyses revealed major novel QTLs for grain yield and related traits in durum wheat

The growing global demand for wheat for food is rising due to the influence of population growth and climate change. The dissection of complex traits by employing a genome-wide association study (GWAS) allows the identification of DNA markers associated with complex traits to improve the productivity of crops. We used GWAS with 10,045 single nucleotide polymorphism (SNP) markers to search for genomic regions associated with grain yield and related traits based on diverse panels of Ethiopian durum wheat. In Ethiopia, multi-environment trials of the genotypes were carried out at five locations. The genotyping was conducted using the 25k Illumina Wheat SNP array to explore population structure, linkage disequilibrium (LD), and marker-trait associations (MTAs). For GWAS, the multi-locus Fixed and Random Model Circulating Probability Unification (FarmCPU) model was applied. Broad-sense heritability estimates were high, ranging from 0.63 (for grain yield) to 0.97 (for thousand-kernel weight). The population structure based on principal component analysis, and model-based cluster analysis revealed two genetically distinct clusters with limited admixtures. The LD among SNPs declined within the range of 2.02-10.04 Mbp with an average of 4.28 Mbp. The GWAS scan based on the mean performance of the genotypes across the environments identified 44 significant MTAs across the chromosomes. Twenty-six of these MTAs are novel, whereas the remaining 18 were previously reported and confirmed in this study. We also identified candidate genes for the novel loci potentially regulating the traits. Hence, this study highlights the significance of the Ethiopian durum wheat gene pool for improving durum wheat globally. Furthermore, a breeding strategy focusing on accumulating favorable alleles at these loci could improve durum wheat production in the East African highlands and elsewhere.

Health-Promoting Potential of Millet: A Review

Being a key source of animal food, millet production has been sharply increasing over the last few years in order to cope with the dietary requirements of the ever-increasing world population. It is a splendid source of essential nutrients such as protein, carbohydrates, fat, minerals, vitamins, and also some other bioactive compounds that eventually help through multiple biological activities, including antioxidant, anti-hyperglycemic, anti-cholesterol, anti-hypertensive, anthropometric effects and regulation of gut microbiota composition. These bioactive compounds, nutrients, and functions of cereal grains can be affected by processing techniques such as decortication, soaking, malting, milling, fermentation, etc. This study discusses the nutritional and functional properties of millet-incorporated foods and their impact on health, based on around 150 articles between 2015 and 2022 from the Web of Science, Google Scholar, Food and Agriculture Organization of the United Nations (FAO), Breeding Bid Survey (BBS), and FoodData Central (USDA) databases. Analyzing literature reviews, it is evident that the incorporation of millet and its constituents into foodstuffs could be useful against undernourishment and several other health diseases. Additionally, this review provides crucial information about the beneficial features of millet, which can serve as a benchmark of guidelines for industry, consumers, researchers, and nutritionists.

QTL Mapping for Root Traits and Their Effects on Nutrient Uptake and Yield Performance in Common Wheat (Triticum aestivum L.)

Wheat is one of the most important crops in the world. Mapping QTLs for root traits is essential for the selection of wheat roots desirable for the efficient acquisition of nutrients. Here, a QTL analysis for wheat root traits was performed using 142 recombinant inbred lines derived from two wheat varieties Xiaoyan 54 and Jing 411 in a soil column culture trial. The genetic map used in this study contained 470 SSR markers and covered 3438.4 cM of wheat genome. A total of 25 QTLs for root and shoot traits were detected, located at 16 marker intervals of 13 chromosomes. The percentage of phenotypic variation explained by individual QTLs varied from 6.1% to 22.0%. The QTLs regulating RDW and root distribution on chromosomes 1A, 3A, 4A, and 5B are important for root growth in both the top- and subsoils. For qRDW-1A, qRDW-3A, and qRDW-5B, the nearest markers to the QTLs were much closer than that of qRDW-4A, with the genetic distances ranging from 0.01 to 1.18 cM. Combining these three QTLs not only increased RDW and nutrient uptake, but also increased GW, SDW, and BDW under low nitrogen conditions in the field trial. Therefore, these QTLs are valuable for marker-assisted selection of wheat root traits.

Diversity matters in wheat mixtures: A genomic survey of the impact of genetic diversity on the performance of 12 way durum wheat mixtures grown in two contrasted and controlled environments

In ecology, an increase in genetic diversity within a community in natural ecosystems increases its productivity, while in evolutionary biology, kinship selection predicts that relatedness on social traits improves fitness. Varietal mixtures, where different genotypes are grown together, show contrasting results, especially for grain yield where both positive and negative effects of mixtures have been reported. To understand the effect of diversity on field performance, we grew 96 independent mixtures each composed with 12 durum wheat (Triticum turgidum ssp. durum Thell.) inbred lines, under two contrasting environmental conditions for water availability. Using dense genotyping, we imputed allelic frequencies and a genetic diversity index on more than 96000 loci for each mixture. We then analyzed the effect of genetic diversity on agronomic performance using a genome-wide approach. We explored the stress gradient hypothesis, which proposes that the greater the unfavourable conditions, the more beneficial the effect of diversity on mixture performance. We found that diversity on average had a negative effect on yield and its components while it was beneficial on grain weight. There was little support for the stress gradient theory. We discuss how to use genomic data to improve the assembly of varietal mixtures.

QTRAP LC/MS/MS of Garlic Nanoparticles and Improving Sunflower Oil Stabilization during Accelerated Shelf Life Storage

The purpose of this research was to assess and utilize the bioactive compounds of garlic nanoparticles (Ga-NPs) as a natural antioxidant in sunflower oil (SFO) stored at 65 ± 1 °C for 24 days. The garlic nanoparticles (Ga-NPs) from the Balady cultivar were prepared, characterized, and added to SFO at three concentrations: 200, 600, and 1000 ppm (w/v), and they were compared with 600 ppm garlic lyophilized powder extract (Ga-LPE), 200 ppm BHT, 200 ppm α-tocopherol, and SFO without Ga-NPs (control). The QTRAP LC/MS/MS profile of Ga-NPs revealed the presence of four organosulfur compounds. Ga-NPs exhibited the highest capacity for phenolic, flavonoid, and antioxidant compounds. In Ga-NP SFO samples, the values of peroxide, p-anisidine, totox, conjugated dienes, and conjugated trienes were significantly lower than the control. The antioxidant indices of SFO samples containing Ga-NPs were higher than the control. The Ga-NPs enhanced the sensory acceptability of SFO treatments up to day 24 of storage. The shelf life of SFO treated with Ga-NPs was substantially increased (presuming a Q₁₀ amount). The results show that Ga-NPs are a powerful antioxidant that improves SFO stability and extends the shelf life (~384 days at 25 °C).

The Role of Alternative Crops in an Upcoming Global Food Crisis: A Concise Review

Achieving Food Security (FS) is perhaps our most challenging aspiration. Despite our best efforts, millions of people around the globe are malnourished or live with hunger. The state of the geo-political scene, as well as the COVID-19 pandemic, have recently brought forth fears of a Global Food Crisis (GFC). Here, we present the factors that threaten FS and could trigger a GFC, examine the potential of alternative crops (ACs) as a measure against an upcoming GFC, and highlight the key aspects of the ACs introduction process in new regions. ACs could enhance FS, yet their success is premised on the adoption of sustainable practices and the implementation of food strategies that aim to promote healthy consumer behaviours.

Unlocking the molecular basis of wheat straw composition and morphological traits through multi-locus GWAS

Background

Rapid reductions in emissions from fossil fuel burning are needed to curb global climate change. Biofuel production from crop residues can contribute to reducing the energy crisis and environmental deterioration. Wheat is a renewable source for biofuels owing to the low cost and high availability of its residues. Thus, identifying candidate genes controlling these traits is pivotal for efficient biofuel production. Here, six multi-locus genome-wide association (ML-GWAS) models were applied using 185 tetraploid wheat accessions to detect quantitative trait nucleotides (QTNs) for fifteen traits associated with biomass composition.

Results

Among the 470 QTNs, only 72 identified by at least two models were considered as reliable. Among these latter, 16 also showed a significant effect on the corresponding trait (p.value < 0.05). Candidate genes survey carried out within 4 Mb flanking the QTNs, revealed putative biological functions associated with lipid transfer and metabolism, cell wall modifications, cell cycle, and photosynthesis. Four genes encoded as Cellulose Synthase (CeSa), Anaphase promoting complex (APC/C), Glucoronoxylan 4-O Methyltransferase (GXM) and HYPONASTIC LEAVES1 (HYL1) might be responsible for an increase in cellulose, and natural and acid detergent fiber (NDF and ADF) content in tetraploid wheat. In addition, the SNP marker RFL_Contig3228_2154 associated with the variation in stem solidness (Q.Scsb-3B) was validated through two molecular methods (High resolution melting; HRM and RNase H²-dependent PCR; rhAMP).

Conclusions

The study provides new insights into the genetic basis of biomass composition traits on tetraploid wheat. The application of six ML-GWAS models on a panel of diverse wheat genotypes represents an efficient approach to dissect complex traits with low heritability such as wheat straw composition. The discovery of genes/genomic regions associated with biomass production and straw quality parameters is expected to accelerate the development of high-yielding wheat varieties useful for biofuel production.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12870-022-03900-6.

High-Throughput Plant Phenotyping (HTPP) in Resource-Constrained Research Programs: A Working Example in Ghana

In this paper, we present a procedure for implementing field-based high-throughput plant phenotyping (HTPP) that can be used in resource-constrained research programs. The procedure relies on opensource tools with the only expensive item being one-off purchase of a drone. It includes acquiring images of the field of interest, stitching the images to get the entire field in one image, calculating and extracting the vegetation indices of the individual plots, and analyzing the extracted indices according to the experimental design. Two populations of groundnut genotypes with different maturities were evaluated for their reaction to early and late leaf spot (ELS, LLS) diseases under field conditions in 2020 and 2021. Each population was made up of 12 genotypes in 2020 and 18 genotypes in 2021. Evaluation of the genotypes was done in four locations in each year. We observed a strong correlation between the vegetation indices and the area under the disease progress curve (AUDPC) for ELS and LLS. However, the strength and direction of the correlation depended upon the time of disease onset, level of tolerance among the genotypes and the physiological traits the vegetation indices were associated with. In 2020, when the disease was observed to have set in late in medium duration population, at the beginning of the seed stage (R5), normalized green-red difference index (NGRDI) and variable atmospheric resistance index (VARI) derived at the beginning pod stage (R3) had a positive relationship with the AUDPC for ELS, and LLS. On the other hand, NGRDI and VARI derived from images taken at R5, and physiological maturity (R7) had negative relationships with AUDPC for ELS, and LLS. In 2021, when the disease was observed to have set in early (at R3) also in medium duration population, a negative relationship was observed between NGRDI and VARI and AUDPC for ELS and LLS, respectively. We found consistently negative relationships of NGRDI and VARI with AUDPC for ELS and LLS, respectively, within the short duration population in both years. Canopy cover (CaC), green area (GA), and greener area (GGA) only showed negative relationships with AUDPC for ELS and LLS when the disease caused yellowing and defoliation. The rankings of some genotypes changed for NGRDI, VARI, CaC, GA, GGA, and crop senescence index (CSI) when lesions caused by the infections of ELS and LLS became severe, although that did not affect groupings of genotypes when analyzed with principal component analysis. Notwithstanding, genotypes that consistently performed well across various reproductive stages with respect to the vegetation indices constituted the top performers when ELS, LLS, haulm, and pod yields were jointly considered.

Growth responses and genetic variation among highly ecologically diverse spring wheat genotypes grown under seawater stress

Most of the freshwaters worldwide are used for agriculture. Freshwater sources are expected to decline and will not suffice to support the food production needed for the growing population. Therefore, growing crops with seawater might constitute a solution. However, very little work has been done on the effect of seawater stress on wheat, an important cereal crop. The present study aimed to determine whether particular wheat genotypes provided better resistance to seawater stress. A set of 80 highly diverse spring wheat genotypes collected from different countries in Europe, Asia, Africa, North and South America was exposed to 50% seawater stress at the early growth stage. Four seeding shoot and root traits were scored for all genotypes. High genetic variations were found among all genotypes for the epicotyl length (EL), hypocotyl length (HL), number of radicles (NOR), and fresh weight (FW). Eight genotypes with high-performance scores of seedling traits were selected. The correlation analyses revealed highly significant correlations among all traits scored in this study. The strongest correlation was found between the NOR and the other seeding traits. Thus, the NOR might be an important adaptive trait for seawater tolerance. The genetic diversity among all genotypes was investigated based on genetic distance. A wide range of genetic distances among all genotypes was found. There was also a great genetic distance among the eight selected genotypes. In particular, the genetic distance between ATRI 5310 (France) and the other seven genotypes was the greatest. Such high genetic diversity might be utilized to select highly divergent genotypes for crossing in a future breeding program. The present study provides very useful information on the presence of different genetic resources in wheat for seawater tolerance.

Nutritional and health-promoting attributes of millet: current and future perspectives

Millet is consumed as a staple food, particularly in developing countries, is part of the traditional diet in a number of relatively affluent countries, and is gaining popularity throughout the world. It is a valuable dietary energy source. In addition to high caloric value, several health-promoting attributes have been reported for millet seeds. This review describes many nutritional characteristics of millet seeds and their derivatives that are important to human health: antioxidant, antihypertensive, immunomodulatory or anti-inflammatory, antibacterial or antimicrobial, hypocholesterolemic, hypoglycemic, and anti-carcinogenic potential, and their role as modulators of gut health. There are several varieties, but the main focus of this review is on pearl millet (Cenchrus americanus [synonym Pennisetum glaucum]), one of the most widely eaten millet crops grown in India, though other millet types are also covered. In this article, the health-promoting properties of the natural components (ie, proteins, peptides, polyphenols, polysaccharides, oil, isoflavones, etc.) present in millet seeds are discussed. Although many of these health benefits have been demonstrated using animal models in vitro studies, human intervention-feeding trials are required to confirm several of the potential health benefits of millet seeds. Based on the nutritional and health-promoting attributes known for pearl millet (discussed in this review), finger millet and foxtail millet are suggested as good candidates for use in future nutritional interventions for improved human health.

Regional Monitoring of Fall Armyworm (FAW) Using Early Warning Systems

The second United Nations Sustainable Development Goal (SDG2), zero hunger, aims to improve the productivity, food security, nutrition, and sustainability of small-scale farmers. The fall armyworm (FAW, Spodoptera frugiperda) has been devasting to smallholder farmer food security since it spread to sub-Saharan Africa in 2016, who have suffered massive crop losses, particularly maize, an important staple for basic sustenance. Since the FAW mainly devours green leaf biomass during the maize vegetative growth stage, the implementation of remote sensing technologies offers opportunities for monitoring the FAW. Here, we developed and tested a Sentinel 2 a+b satellite-based monitoring algorithm based on optimized first-derivative NDVI time series analysis using Google Earth Engine. For validation, we first employed the FAO Fall Armyworm Monitoring and Early Warning System (FAMEWS) mobile app data from Kenya, and then subsequently conducted field validation campaigns in Zimbabwe, Kenya, and Tanzania. Additionally, we directly observed loss of green biomass during maize vegetative growth stages caused by the FAW, confirming the observed signals of loss of the leaf area index (LAI) and the total green biomass (via the NDVI). Preliminary analyses suggested that satellite monitoring of small-scale farmer fields at the regional level may be possible with an NDVI first-derivative time series anomaly analysis using ESA Sentinel 2 a+b (R2 = 0.81). Commercial nanosatellite constellations, such as PlanetScope, were also explored, which may offer benefits from greater spatial resolution and return interval frequency. Due to other confounding factors, such as clouds, intercropping, weeds, abiotic stresses, or even other biotic pests (e.g., locusts), validation results were mixed. Still, maize biomass anomaly detection for monitoring the FAW using satellite data could help confirm the presence of the FAW with the help of expanded field-based monitoring through the FAO FAMEWS app.

Mapping of Two Major QTLs Controlling Flowering Time in Brassica napus Using a High-Density Genetic Map

Research on the flowering habit of rapeseed is important for the selection of varieties adapted to specific ecological environments. Here, quantitative trait loci (QTL) for the days-to-flowering trait were identified using a doubled haploid population of 178 lines derived from a cross between the winter type SGDH284 and the semi-winter type 158A. A linkage map encompassing 3268.01 cM was constructed using 2777 bin markers obtained from next-generation sequencing. The preliminary mapping results revealed 56 QTLs for the days to flowering in the six replicates in the three environments. Twelve consensus QTLs were identified by a QTL meta-analysis, two of which (cqDTF-C02 and cqDTF-C06) were designated as major QTLs. Based on the micro-collinearity of the target regions between B. napus and Arabidopsis, four genes possibly related to flowering time were identified in the cqDTF-C02 interval, and only one gene possibly related to flowering time was identified in the cqDTF-C06 interval. A tightly linked insertion-deletion marker for the cqFT-C02 locus was developed. These findings will aid the breeding of early maturing B. napus varieties.

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.

Evaluation of the U.S. Peanut Germplasm Mini-Core Collection in the Virginia-Carolina Region Using Traditional and New High-Throughput Methods

Peanut (Arachis hypogaea L.) is an important food crop for the U.S. and the world. The Virginia-Carolina (VC) region (Virginia, North Carolina, and South Carolina) is an important peanut-growing region of the U.S and is affected by numerous biotic and abiotic stresses. Identification of stress-resistant germplasm, along with improved phenotyping methods, are important steps toward developing improved cultivars. Our objective in 2017 and 2018 was to assess the U.S. mini-core collection for desirable traits, a valuable source for resistant germplasm under limited water conditions. Accessions were evaluated using traditional and high-throughput phenotyping (HTP) techniques, and the suitability of HTP methods as indirect selection tools was assessed. Traditional phenotyping methods included stand count, plant height, lateral branch growth, normalized difference vegetation index (NDVI), canopy temperature depression (CTD), leaf wilting, fungal and viral disease, thrips rating, post-digging in-shell sprouting, and pod yield. The HTP method included 48 aerial vegetation indices (VIs), which were derived using red, blue, green, and near-infrared reflectance; color space indices were collected using an octocopter drone at the same time, with traditional phenotyping. Both phenotypings were done 10 times between 4 and 16 weeks after planting. Accessions had yields comparable to high yielding checks. Correlation coefficients up to 0.8 were identified for several Vis, with yield indicating their suitability for indirect phenotyping. Broad-sense heritability (H2) was further calculated to assess the suitability of particular VIs to enable genetic gains. VIs could be used successfully as surrogates for the physiological and agronomic trait selection in peanuts. Further, this study indicates that UAV-based sensors have potential for measuring physiologic and agronomic characteristics measured for peanut breeding, variable rate input application, real time decision making, and precision agriculture applications.

SSR-based genome-wide association study in turkish durum wheat germplasms revealed novel QTL of accumulated platinum

BACKGROUND

Durum wheat has a genetic capacity to accumulate toxic metals that can exceed the safety limit of the international standards, which may seriously affect human health. Identifying germplasms with low, nontoxic accumulated metal contents is important to select and develop new varieties. Thus, the objective of this study is to identify the levels of accumulated platinum in durum wheat and detect novel QTL.

METHODS AND RESULTS

Platinum contents were determined using 130 durum genotypes. Results generally showed low values of accumulated Pt and significantly less than the maximum grain's Pt content determined by international standards. Pt contents among genotypes varied from ≤ 0.001 to 0.72 µg/kg with an average of 0.02. Landraces showed the lowest average accumulated Pt. GWAS was then performed with 780 SSR markers. Five QTL were detected and explained 14.4-23.1% of the total phenotypic variation. Chromosomes 3 A, 3B, and 5B appear to be hotspots and may play a crucial role in accumulated Pt and were harbored in 1, 3, and 1 QTL, respectively.

CONCLUSIONS

This assessment of accumulated Pt within a unique panel included accessions mostly from Turkish regions, and GWAS used is the first study regarding accumulated Pt indices to reveal novel QTL. It will allow breeders to accelerate their selection of proper genotypes according to desired alleles and offer an opportunity to apply MAS to minimize Pt toxicity in durum wheat. Results indicated that the significance of genome (B) regions are likely related to the inheritance control of Pt content and may play a pivotal role regarding durum wheat's Pt contents. Nonetheless, these novel QTL should be validated in independent populations in numerous environments.

Exploration of Alternative Approaches to Phenotyping of Late Leaf Spot and Groundnut Rosette Virus Disease for Groundnut Breeding

Late leaf spot (LLS), caused by Nothopassalora personata (Berk. & M.A Curt.), and groundnut rosette disease (GRD), [caused by groundnut rosette virus (GRV)], represent the most important biotic constraints to groundnut production in Uganda. Application of visual scores in selection for disease resistance presents a challenge especially when breeding experiments are large because it is resource-intensive, subjective, and error-prone. High-throughput phenotyping (HTP) can alleviate these constraints. The objective of this study is to determine if HTP derived indices can replace visual scores in a groundnut breeding program in Uganda. Fifty genotypes were planted under rain-fed conditions at two locations, Nakabango (GRD hotspot) and NaSARRI (LLS hotspot). Three handheld sensors (RGB camera, GreenSeeker, and Thermal camera) were used to collect HTP data on the dates visual scores were taken. Pearson correlation was made between the indices and visual scores, and logistic models for predicting visual scores were developed. Normalized difference vegetation index (NDVI) (r = –0.89) and red-green-blue (RGB) color space indices CSI (r = 0.76), v* (r = –0.80), and b* (r = –0.75) were highly correlated with LLS visual scores. NDVI (r = –0.72), v* (r = –0.71), b* (r = –0.64), and GA (r = –0.67) were best related to the GRD visual symptoms. Heritability estimates indicated NDVI, green area (GA), greener area (GGA), a*, and hue angle having the highest heritability (H² > 0.75). Logistic models developed using these indices were 68% accurate for LLS and 45% accurate for GRD. The accuracy of the models improved to 91 and 84% when the nearest score method was used for LLS and GRD, respectively. Results presented in this study indicated that use of handheld remote sensing tools can improve screening for GRD and LLS resistance, and the best associated indices can be used for indirect selection for resistance and improve genetic gain in groundnut breeding.

Proximal and remote sensing in plant phenomics: 20 years of progress, challenges, and perspectives

Plant phenomics (PP) has been recognized as a bottleneck in studying the interactions of genomics and environment on plants, limiting the progress of smart breeding and precise cultivation. High-throughput plant phenotyping is challenging owing to the spatio-temporal dynamics of traits. Proximal and remote sensing (PRS) techniques are increasingly used for plant phenotyping because of their advantages in multi-dimensional data acquisition and analysis. Substantial progress of PRS applications in PP has been observed over the last two decades and is analyzed here from an interdisciplinary perspective based on 2972 publications. This progress covers most aspects of PRS application in PP, including patterns of global spatial distribution and temporal dynamics, specific PRS technologies, phenotypic research fields, working environments, species, and traits. Subsequently, we demonstrate how to link PRS to multi-omics studies, including how to achieve multi-dimensional PRS data acquisition and processing, how to systematically integrate all kinds of phenotypic information and derive phenotypic knowledge with biological significance, and how to link PP to multi-omics association analysis. Finally, we identify three future perspectives for PRS-based PP: (1) strengthening the spatial and temporal consistency of PRS data, (2) exploring novel phenotypic traits, and (3) facilitating multi-omics communication.

Comparison of Proximal Remote Sensing Devices of Vegetable Crops to Determine the Role of Grafting in Plant Resistance to Meloidogyne incognita

Proximal remote sensing devices are novel tools that enable the study of plant health status through the measurement of specific characteristics, including the color or spectrum of light reflected or transmitted by the leaves or the canopy. The aim of this study is to compare the RGB and multispectral data collected during five years (2016–2020) of four fruiting vegetables (melon, tomato, eggplant, and peppers) with trial treatments of non-grafted and grafted onto resistant rootstocks cultivated in a Meloidogyne incognita (a root-knot nematode) infested soil in a greenhouse. The proximal remote sensing of plant health status data collected was divided into three levels. Firstly, leaf level pigments were measured using two different handheld sensors (SPAD and Dualex). Secondly, canopy vigor and biomass were assessed using vegetation indices derived from RGB images and the Normalized Difference Vegetation Index (NDVI) measured with a portable spectroradiometer (Greenseeker). Third, we assessed plant level water stress, as a consequence of the root damage by nematodes, using stomatal conductance measured with a porometer and indirectly using plant temperature with an infrared thermometer, and also the stable carbon isotope composition of leaf dry matter.. It was found that the interaction between treatments and crops (ANOVA) was statistically different for only four of seventeen parameters: flavonoid (p < 0.05), NBI (p < 0.05), NDVI (p < 0.05) and the RGB CSI (Crop Senescence Index) (p < 0.05). Concerning the effect of treatments across all crops, differences existed only in two parameters, which were flavonoid (p < 0.05) and CSI (p < 0.001). Grafted plants contained fewer flavonoids (x¯ = 1.37) and showed lower CSI (x¯ = 11.65) than non-grafted plants (x¯ = 1.98 and x¯ = 17.28, respectively, p < 0.05 and p < 0.05) when combining all five years and four crops. We conclude that the grafted plants were less stressed and more protected against nematode attack. Leaf flavonoids content and the CSI index were robust indicators of root-knot nematode impacts across multiple crop types.

Genetic Mapping and Candidate Gene Prediction of a QTL Related to Early Heading on Wild Emmer Chromosome 7BS in the Genetic Background of Common Wheat

Heading date (HD) is an essential agronomic objective in wheat conventional breeding. Field experiments from several years and locations indicated that the chromosome arm substitution line (CASL) of wild emmer chromosome 7BS in the genetic background of common wheat var. Chinese Spring (CS) always showed a substantially earlier HD than CS planted in different seasons; usually about 8 d earlier than CS grown under a normal autumn sowing season. CASL7BS consistently showed a much earlier HD than CS when treated for vernalization under a long or short photoperiod and then grown under a short or long photoperiod in the growth room. CASL7BS showed faster spike development than CS at the stages before the glume stage when grown under long days, and depicted relatively rapid growth at all stages when grown under short days. To map the early gene in CASL7BS, F2 plants from the cross of CASL7BS and CS were planted in the field and growth room, forming two mapping populations (P1 and P2, respectively). According to the HD distribution of P1, the HD was most likely regulated by a dominant gene. A QTL was detected consistently in the distal region of about 8.94 cM flanked by C268 and C309 with LOD scores of 5–8, explaining 9.14 and 12.35% of the phenotypic variation in the two mapping populations. The QTL was further narrowed down to an interval between ZAFU058724 and ZAFU061354 of 58–61 Mb based on the HD and genotype of F3 and F4 families. A total of 41 genes were located in this region, and eleven of them were thought to be the candidate genes based on the gene functions. According to the HD and mapping location, the QTL identified in this study was a new gene associated with flowering, which will be helpful in understanding the mechanism of wheat flowering and for breeding an early wheat variety.

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

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

QTL Mapping of Leaf Area Index and Chlorophyll Content Based on UAV Remote Sensing in Wheat

High-throughput phenotypic identification is a prerequisite for large-scale identification and gene mining of important traits. However, existing work has rarely leveraged high-throughput phenotypic identification into quantitative trait locus (QTL) acquisition in wheat crops. Clarifying the feasibility and effectiveness of high-throughput phenotypic data obtained from UAV multispectral images in gene mining of important traits is an urgent problem to be solved in wheat. In this paper, 309 lines of the spring wheat Worrakatta × Berkut recombinant inbred line (RIL) were taken as materials. First, we obtained the leaf area index (LAI) including flowering, filling, and mature stages, as well as the flag leaf chlorophyll content (CC) including heading, flowering, and filling stages, from multispectral images under normal irrigation and drought stress, respectively. Then, on the basis of the normalized difference vegetation index (NDVI) and green normalized difference vegetation index (GNDVI), which were determined by multispectral imagery, the LAI and CC were comprehensively estimated through the classification and regression tree (CART) and cross-validation algorithms. Finally, we identified the QTLs by analyzing the predicted and measured values. The results show that the predicted values of determination coefficient (R2) ranged from 0.79 to 0.93, the root-mean-square error (RMSE) ranged from 0.30 to 1.05, and the relative error (RE) ranged from 0.01 to 0.18. Furthermore, the correlation coefficients of predicted and measured values ranged from 0.93 to 0.94 for CC and from 0.80 to 0.92 for LAI at different wheat growth stages under normal irrigation and drought stress. Additionally, a linkage map of this RIL population was constructed by 11,375 SNPs; eight QTLs were detected for LAI on wheat chromosomes 1BL, 2BL (four QTLs), 3BL, 5BS, and 5DL, and three QTLs were detected for CC on chromosomes 1DS (two QTLs) and 3AL. The closely linked QTLs formed two regions on chromosome 2BL (from 54 to 56 cM and from 96 to 101 cM, respectively) and one region on 1DS (from 26 to 27 cM). Each QTL explained phenotypic variation for LAI from 2.5% to 13.8% and for CC from 2.5% to 5.8%. For LAI, two QTLs were identified at the flowering stage, two QTLs were identified at the filling stage, and three QTLs were identified at the maturity stage, among which QLAI.xjau-5DL-pre was detected at both filling and maturity stages. For CC, two QTLs were detected at the heading stage and one QTL was identified at the flowering stage, among which QCC.xjau-1DS was detected at both stages. Three QTLs (QLAI.xjau-2BL-pre.2, QLAI.xjau-2BL.2, and QLAI.xjau-3BL-pre) for LAI were identified under drought stress conditions. Five QTLs for LAI and two QTLs for CC were detected by imagery-predicted values, while four QTLs for LAI and two QTLs for CC were identified by manual measurement values. Lastly, investigations of these QTLs on the wheat reference genome identified 10 candidate genes associated with LAI and three genes associated with CC, belonging to F-box family proteins, peroxidase, GATA transcription factor, C2H2 zinc finger structural protein, etc., which are involved in the regulation of crop growth and development, signal transduction, and response to drought stress. These findings reveal that UAV sensing technology has relatively high reliability for phenotyping wheat LAI and CC, which can play an important role in crop genetic improvement.

New alternatives from sustainable sources to wheat in bakery foods: Science, technology, and challenges

Ongoing research in the food industry is striving to replace wheat flour with new alternatives from sustainable sources to overcome the disease burden in the existing population. Celiac disease, wheat allergy, gluten sensitivity, or non-celiac gluten sensitivity are some common disorders associated with gluten present in wheat. These scientific findings are crucial to finding appropriate alternatives in introducing new ingredients supporting the consumer's requirements. Among the alternatives, amaranth, barley, coconut, chestnut, maize, millet, teff, oat, rye, sorghum, soy, rice flour, and legumes could be considered appropriate due to their chemical composition, bioactive profile, and alternatives utilization in the baking industry. Furthermore, the enrichment of these alternatives with proper ingredients is considered effective. Literature demonstrated that the flours from these alternative sources significantly enhanced the physicochemical, pasting, and rheological properties of the doughs. These flours boost a significant reduction in gluten proteins associated with food intolerance, in comparison with wheat highlighting a visible market opportunity with nutritional and organoleptic benefits for food producers. PRACTICAL APPLICATIONS: New alternatives from sustainable sources to wheat in bakery foods as an approach that affects human health. Alternatives from sustainable sources are important source of nutrients and bioactive compounds. Alternatives from sustainable sources are rising due to nutritional and consumer demand in bakery industry. New alternatives from sustainable sources improve physicochemical, pasting, and rheological properties of dough. Non-wheat-based foods from non-traditional grains have a potential to increase consumer market acceptance.

Progenitor species hold untapped diversity for potential climate-responsive traits for use in wheat breeding and crop improvement

Climate change will have numerous impacts on crop production worldwide necessitating a broadening of the germplasm base required to source and incorporate novel traits. Major variation exists in crop progenitor species for seasonal adaptation, photosynthetic characteristics, and root system architecture. Wheat is crucial for securing future food and nutrition security and its evolutionary history and progenitor diversity offer opportunities to mine favourable functional variation in the primary gene pool. Here we provide a review of the status of characterisation of wheat progenitor variation and the potential to use this knowledge to inform the use of variation in other cereal crops. Although significant knowledge of progenitor variation has been generated, we make recommendations for further work required to systematically characterise underlying genetics and physiological mechanisms and propose steps for effective use in breeding. This will enable targeted exploitation of useful variation, supported by the growing portfolio of genomics and accelerated breeding approaches. The knowledge and approaches generated are also likely to be useful across wider crop improvement.

Drought-Tolerance QTLs Associated with Grain Yield and Related Traits in Spring Bread Wheat

The present research aims to identify the efficient combination of drought-tolerance selection criteria and associated quantitative trait loci. A panel of 197 bread wheat genotypes was evaluated for yield- and drought-tolerance-related traits in two environments (favorable and semiarid) for 2 years (2015–2016). Grain number, biomass, number of fertile spikes per plant and ground cover exhibited a significant correlation with grain yield and constitute potential secondary selection criteria for yield under drought conditions. About 73 significant marker–trait associations were detected along various chromosomal positions. The markers “wsnp_Ex_Rep_c67786_66472676” and “ExcalibuR_c24593_1217” exhibited important genetic gains associated with yield increase under drought (11 and 7%, respectively). The markers “KukRi_c94792_127” and “wsnp_Ex_c298_580660” showed a significant correlation with grain yield, biomass and grain number and were associated with a significant increase in yield performance at the semiarid site (+6 and +7%, respectively). The ground cover was found associated with grain yield and biomass through the markers “wsnp_Ex_Rep_c67786_66472676” (+11%) and “KukRi_c49927_151” (+10%). One marker “TduRuM_contig25432_1377” on chromosome 5B at 20 cM was consistently correlated with the number of fertile spikes across both environments. Further research should be considered to validate the efficiency of these markers to undertake selection for drought tolerance under various environments and genetic backgrounds.

Assessing Phytosanitary Application Efficiency of a Boom Sprayer Machine Using RGB Sensor in Grassy Fields

The systematic use of plant protection products is now being called into question with the growing awareness of the risks they can represent for the environment and human health. The application of precision agriculture technologies helps to improve agricultural production but also to rationalize input costs and improve ecological footprints. Here we present a study on fungicide application efficiency and its impact on the grass quality of a golf course green using the free open-source image analysis software FIJI (Image J) to analyze ground RGB (high-resolution digital cameras) and multispectral aerial imagery in combination with experimental data of spray pressure and hydraulic slot nozzle size of a boom sprayer machine. The multivariate regression model best explained variance in the normalized green-red difference index (NGRDI) as a relevant indicator of healthy turfgrass fields from the aerial, ground, and machine data set.

Arbuscular Mycorrhizal Symbiosis Differentially Affects the Nutritional Status of Two Durum Wheat Genotypes under Drought Conditions

Durum wheat is one of the most important agricultural crops, currently providing 18% of the daily intake of calories and 20% of daily protein intake for humans. However, being wheat that is cultivated in arid and semiarid areas, its productivity is threatened by drought stress, which is being exacerbated by climate change. Therefore, the identification of drought tolerant wheat genotypes is critical for increasing grain yield and also improving the capability of crops to uptake and assimilate nutrients, which are seriously affected by drought. This work aimed to determine the effect of arbuscular mycorrhizal fungi (AMF) on plant growth under normal and limited water availability in two durum wheat genotypes (Svevo and Etrusco). Furthermore, we investigated how the plant nutritional status responds to drought stress. We found that the response of Svevo and Etrusco to drought stress was differentially affected by AMF. Interestingly, we revealed that AMF positively affected sulfur homeostasis under drought conditions, mainly in the Svevo cultivar. The results provide a valuable indication that the identification of drought tolerant plants cannot ignore their nutrient use efficiency or the impact of other biotic soil components (i.e., AMF).

ColorBayes: Improved color correction of high-throughput plant phenotyping images to account for local illumination differences.. [DOI: 10.1101/2022.03.01.482532] [Cited by in Crossref: 0] [Impact Index Per Article: 0] BackgroundColor distortion is an inherent problem in image-based phenotyping systems that are illuminated by artificial light. This distortion is problematic when examining plants because it can cause data to be incorrectly interpreted. One of the leading causes of color distortion is the non-uniform spectral and spatial distribution of artificial light. However, color correction algorithms currently used in plant phenotyping assume that a single and uniform illuminant causes color distortion. These algorithms are consequently inadequate to correct the local color distortion caused by multiple illuminants common in plant phenotyping systems, such as fluorescent tubes and LED light arrays. We describe here a color constancy algorithm, ColorBayes, based on Bayesian inference that corrects local color distortions. The algorithm estimates the local illuminants using the Bayes’ rule, the maximum a posteriori, the observed image data, and prior illuminant information. The prior is obtained from light measurements and Macbeth ColorChecker charts located on the scene.ResultsThe ColorBayes algorithm improved the accuracy of plant color on images taken by an indoor plant phenotyping system. Compared with existing approaches, it gave the most accurate metric results when correcting images from a dataset of Arabidopsis thaliana images.The software is available at https://github.com/diloc/Color_correction.git

Background

Color distortion is an inherent problem in image-based phenotyping systems that are illuminated by artificial light. This distortion is problematic when examining plants because it can cause data to be incorrectly interpreted. One of the leading causes of color distortion is the non-uniform spectral and spatial distribution of artificial light. However, color correction algorithms currently used in plant phenotyping assume that a single and uniform illuminant causes color distortion. These algorithms are consequently inadequate to correct the local color distortion caused by multiple illuminants common in plant phenotyping systems, such as fluorescent tubes and LED light arrays. We describe here a color constancy algorithm, ColorBayes, based on Bayesian inference that corrects local color distortions. The algorithm estimates the local illuminants using the Bayes’ rule, the maximum a posteriori, the observed image data, and prior illuminant information. The prior is obtained from light measurements and Macbeth ColorChecker charts located on the scene.

Results

The ColorBayes algorithm improved the accuracy of plant color on images taken by an indoor plant phenotyping system. Compared with existing approaches, it gave the most accurate metric results when correcting images from a dataset of Arabidopsis thaliana images.

The software is available at https://github.com/diloc/Color_correction.git.

Phenotypic Traits Extraction and Genetic Characteristics Assessment of Eucalyptus Trials Based on UAV-Borne LiDAR and RGB Images

Phenotype describes the physical, physiological and biochemical characteristics of organisms that are determined or influenced by genes and environment. Accurate extraction of phenotypic data is a prerequisite for comprehensive forest phenotyping in order to improve the growth and development of forest plantations. Combined with the assessments of genetic characteristics, forest phenotyping will help to accelerate the breeding process, improve stress resistance and enhance the quality of the planted forest. In this study, we disposed our study in Eucalyptus trials within the Gaofeng forest farm (a typical Eucalyptus plantation site in southern China) for a high-throughput phenotypic traits extraction and genetic characteristics analysis based on high-density point clouds (acquired by a UAV-borne LiDAR sensor) and high-resolution RGB images (acquired by a UAV-borne camera), aiming at developing a high-resolution and high-throughput UAV-based phenotyping approach for tree breeding. First, we compared the effect of CHM-based Marker-Controlled Watershed Segmentation (MWS) and Point Cloud-based Cluster Segmentation (PCS) for extracting individual trees; Then, the phenotypic traits (i.e., tree height, diameter at breast height, crown width), the structural metrics (n = 19) and spectral indices (n = 9) of individual trees were extracted and assessed; Finally, a genetic characteristics analysis was carried out based on the above results, and we compared the differences between high-throughput phenotyping by UAV-based data and on manual measurements. Results showed that: in the relatively low stem density site of the trial (760 n/ha), the overall accuracy of MWS and PCS was similar, while in the higher stem density sites (982 n/ha, 1239 n/ha), the overall accuracy of MWS (F(2) = 0.93, F(3) = 0.86) was higher than PCS (F(2) = 0.84, F(3) = 0.74); With the increase of stem density, the difference between the overall accuracy of MWS and PCS gradually expanded. Both UAV–LiDAR extracted phenotypic traits and manual measurements were significantly different across the Eucalyptus clones (P < 0.05), as were most of the structural metrics (47/57) and spectral indices (26/27), revealing the genetic divergence between the clones. The rank of clones demonstrated that the pure clones (of E. urophylla), the hybrid clones (of E. urophylla as the female parent) and the hybrid clones (of E. wetarensis and E. grandis) have a higher fineness of growth. This study proved that UAV-based fine-resolution remote sensing could be an efficient, accurate and precise technology in phenotyping (used in genetic analysis) for tree breeding.

Genome Wide Association Study Uncovers the QTLome for Osmotic Adjustment and Related Drought Adaptive Traits in Durum Wheat

Osmotic adjustment (OA) is a major component of drought resistance in crops. The genetic basis of OA in wheat and other crops remains largely unknown. In this study, 248 field-grown durum wheat elite accessions grown under well-watered conditions, underwent a progressively severe drought treatment started at heading. Leaf samples were collected at heading and 17 days later. The following traits were considered: flowering time (FT), leaf relative water content (RWC), osmotic potential (ψs), OA, chlorophyll content (SPAD), and leaf rolling (LR). The high variability (3.89-fold) in OA among drought-stressed accessions resulted in high repeatability of the trait (h² = 72.3%). Notably, a high positive correlation (r = 0.78) between OA and RWC was found under severe drought conditions. A genome-wide association study (GWAS) revealed 15 significant QTLs (Quantitative Trait Loci) for OA (global R² = 63.6%), as well as eight major QTL hotspots/clusters on chromosome arms 1BL, 2BL, 4AL, 5AL, 6AL, 6BL, and 7BS, where a higher OA capacity was positively associated with RWC and/or SPAD, and negatively with LR, indicating a beneficial effect of OA on the water status of the plant. The comparative analysis with the results of 15 previous field trials conducted under varying water regimes showed concurrent effects of five OA QTL cluster hotspots on normalized difference vegetation index (NDVI), thousand-kernel weight (TKW), and/or grain yield (GY). Gene content analysis of the cluster regions revealed the presence of several candidate genes, including bidirectional sugar transporter SWEET, rhomboid-like protein, and S-adenosyl-L-methionine-dependent methyltransferases superfamily protein, as well as DREB1. Our results support OA as a valuable proxy for marker-assisted selection (MAS) aimed at enhancing drought resistance in wheat.

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

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

Detection of drought tolerance-related QTL in the Plainsman V./Cappelle Desprez doubled haploid wheat population

Drought stress is one of the major abiotic factors that significantly reduces wheat grain yield. Improving drought tolerance is a challenge that plant breeders are facing nowadays. In this study, our goal was to identify quantitative trait loci (QTL) in the Plainsman V./Cappelle Desprez doubled haploid (DH) population under drought induced as decreased irrigation (ds) and well-watered (ww) conditions in glasshouse. In total, 54 QTL were detected across the three years in two water regimes linked to 10 drought tolerance-related agronomic traits. Out of the detected QTL regions several have been previously reported. The QTL on chromosome 1A (wPt-744613-wPt-8016) related to thousand grain weight was detected in both ds and ww conditions, explaining the 12.7–17.4% of the phenotypic variance. QTL for grain yield was detected on chromosomes 1A, and 6B in the ds treatment. Numerous QTL was identified under both irrigation levels.

Wheat Breeding, Fertilizers, and Pesticides: Do They Contribute to the Increasing Immunogenic Properties of Modern Wheat?

Celiac disease (CD) is a small intestinal inflammatory condition where consumption of gluten induces a T-cell mediated immune response that damages the intestinal mucosa in susceptible individuals. CD affects at least 1% of the world’s population. The increasing prevalence of CD has been reported over the last few decades. However, the reason for this increase is not known so far. Certain factors such as increase in awareness and the development of advanced and highly sensitive diagnostic screening markers are considered significant factors for this increase. Wheat breeding strategies, fertilizers, and pesticides, particularly herbicides, are also thought to have a role in the increasing prevalence. However, less is known about this issue. In this review, we investigated the role of these agronomic practices in depth. Our literature-based results showed that wheat breeding, use of nitrogen-based fertilizers, and herbicides cannot be solely responsible for the increase in celiac prevalence. However, applying nitrogen fertilizers is associated with an increase in gluten in wheat, which increases the risk of developing celiac-specific symptoms in gluten-sensitive individuals. Additionally, clustered regularly interspaced short palindromic repeats (CRISPR) techniques can edit multiple gliadin genes, resulting in a low-immunogenic wheat variety that is safe for such individuals.

Chlorophyll Fluorescence and Drought Tolerance in a Mapping Population of Durum Wheat

This study was conducted to compare and estimate the genetic variability among durum wheat lines in response to drought according to their grain yields and physiological traits. The use of fluorescence parameters as drought selection criteria for durum wheat was investigated in a population of 249 recombinant inbred lines (RILs) derived from a cross between two cultivars of durum wheat: ‘Svevo’ and ‘Kofa’. The durum wheat RILs considered were analyzed to determine the relationship between their grain yields and chlorophyll fluorescence parameters at the grain filling stage under drought stress (rainfed) and supplemental irrigation (irrigated) conditions during the 2004 and 2005 seasons at the ICARDA center. The results obtained show that the durum wheat line performance was influenced by drought stress, indicating significant differences between the grain yields and fluorescence parameters recorded under drought rainfed (RF) and irrigation (IR) conditions. Significant differences between the experimental groups of durum wheat RILs (P<0.05) were only recorded under drought conditions, with the exception of leaf water potential (Lwp). Under such conditions, nearly all the parameters examined were significantly increased in the high-yielding group (with the exception of the Que parameter), thus revealing the genetic variability of the durum wheat lines considered in response to drought stress. The potential quantum efficiency of photosystem II (Fv/Fm) was found to be positively associated with the grain yield parameter. The mean values of Fv/Fm in both the high- and low-yielding groups significantly dropped under drought stress (0.71 and 0.68, respectively) compared to the Fv/Fm values recorded under irrigated conditions (0.80 and 0.81). Under drought conditions, slopes were highly significant (P<0.001) nearly for all the fluorescence parameters examined (with the exception of CHLSPAD) compared to those recorded under irrigation conditions. It was concluded that chlorophyll content (SPAD), F0, Fm, Fv, Fv/Fm, Lwp, and Que could be used as additional indicators in screening wheat germplasm for drought tolerance.

Crop Wild Relatives Crosses: Multi-Location Assessment in Durum Wheat, Barley, and Lentil

Crop wild relatives (CWR) are a good source of useful alleles for climate change adaptation. Here, 19 durum wheat, 24 barley, and 24 lentil elites incorporating CWR in their pedigrees were yield tested against commercial checks across 19 environments located in Morocco, Ethiopia, Lebanon, and Senegal. For each crop, the combined analysis of variance showed that genotype (G), environment (E), and genotype x environment (G×E) effects were significant for most of the traits. A selection index combining yield potential (G) and yield stability (G×E) was used to identify six CWR-derived elites for each crop matching or superior to the best check. A regression analysis using a climate matrix revealed that grain yield was mostly influenced by the maximum daily temperature and soil moisture level during the growing stages. These climatic factors were used to define five clusters (i.e., E1 to E5) of mega-environments. The CWR-derived elites significantly outperformed the checks in E1, E2, and E4 for durum wheat, and in E2 for both barley and lentil. The germplasm was also assessed for several food transformation characteristics. For durum wheat, one accession (Zeina) originating from T. araraticum was significantly superior in mixograph score to the best check, and three accessions originating from T. araraticum and T. urartu were superior for Zn concentration. For barley, 21 accessions originating from H. spontaneum were superior to the checks for protein content, six for Zn content, and eight for β-glucan. For lentil, ten accessions originating from Lens orientalis were superior to the check for protein content, five for Zn, and ten for Fe concentration. Hence, the results presented here strongly support the use of CWR in breeding programs of these three dryland crops, both for adaptation to climatic stresses and for value addition for food transformation.