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.

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).

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.

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.

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.

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.

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 (H ² > 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.

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.

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.

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).

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.

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.

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.

Transient Waterlogging Events Impair Shoot and Root Physiology and Reduce Grain Yield of Durum Wheat Cultivars

Durum wheat (Triticum turgidum L. subsp. durum (Desf.) Husn) is a staple crop of the Mediterranean countries, where more frequent waterlogging events are predicted due to climate change. However, few investigations have been conducted on the physiological and agronomic responses of this crop to waterlogging. The present study provides a comprehensive evaluation of the effects of two waterlogging durations (i.e., 14 and 35 days) on two durum wheat cultivars (i.e., Svevo and Emilio Lepido). An integrated analysis of an array of physiological, biochemical, biometric, and yield parameters was performed at the end of the waterlogging events, during recovery, and at physiological maturity. Results established that effects on durum wheat varied depending on waterlogging duration. This stress imposed at tillering impaired photosynthetic activity of leaves and determined oxidative injury of the roots. The physiological damages could not be fully recovered, subsequently slowing down tiller formation and crop growth, and depressing the final grain yield. Furthermore, differences in waterlogging tolerance between cultivars were discovered. Our results demonstrate that in durum wheat, the energy maintenance, the cytosolic ion homeostasis, and the ROS control and detoxification can be useful physiological and biochemical parameters to consider for the waterlogging tolerance of genotypes, with regard to sustaining biomass production and grain yield.

Morpho-Physiological Classification of Italian Tomato Cultivars (Solanum lycopersicum L.) According to Drought Tolerance during Vegetative and Reproductive Growth

Irrigation is fundamental for agriculture but, as climate change becomes more persistent, there is a need to conserve water and use it more efficiently. It is therefore crucial to identify cultivars that can tolerate drought. For economically relevant crops, such as tomatoes, this purpose takes on an even more incisive role and local agrobiodiversity is a large genetic reservoir of promising cultivars. In this study, nine local Italian cultivars of tomatoes plus four widely used commercial cultivars were considered. These experienced about 20 d of drought, either at vegetative or reproductive phase. Various physio-morphological parameters were monitored, such as stomatal conductance (gs), photosynthesis (A), water use efficiency (WUE), growth (GI) and soil water content (SWC). The different responses and behaviors allowed to divide the cultivars into three groups: tolerant, susceptible, and intermediate. The classification was also confirmed by a principal component analysis (PCA). The study, in addition to deepening the knowledge of local Italian tomato cultivars, reveals how some cultivars perform better under stress condition than commercial ones. Moreover, the different behavior depends on the genotype and on the growth phase of plants. In fact, the Perina cultivar is the most tolerant during vegetative growth while the Quarantino cultivar is mostly tolerant at reproductive stage. The results suggest that selection of cultivars could lead to a more sustainable agriculture and less wasteful irrigation plans.

Genetic control of Fusarium head blight resistance in two Yangmai 158-derived recombinant inbred line populations

Stably expressed type I and type II resistance QTL were identified using two Yangmai 158-derived RIL populations, and plant-height and flowering-time QTL intervals detected did not contribute to the FHB resistance variations. Yangmai 158 (Y158) is an elite wheat cultivar widely grown in China with stable Fusarium head blight (FHB) resistance. To enrich the genetic basis underlying FHB resistance, QTL mapping was conducted using two recombinant inbred line (RIL) populations derived from crosses of Y158 with susceptible lines Annong 8455 and Veery. Survey with makers linked to Fhb1, Fhb2, Fhb4 and Fhb5 in resistance cultivar Wangshuibai indicated that both Y158 and the susceptible lines do not contain these QTL. The RIL populations were surveyed with 65 PCR markers and 55 K chip, which generated 23,159 valid marker data, to produce genetic maps for whole genome scanning of quantitative trait loci (QTL). A total of six QTL, all with the Y158 alleles for better resistance and including one stably expressed QTL for type I resistance (Qfhi.nau-2D) and one stably expressed QTL for type II resistance (Qfhs.nau-2A), were identified. Moreover, taking advantage of the great genetic variations in plant height and flowering time, QTL conditioning these two traits were determined. Of six plant-height QTL and three flowering-time QTL intervals detected, none were associated with FHB resistance. The FHB resistance QTL in Y158 were shown to be useful alternatives in FHB resistance breeding programs. The SNP markers flanking Qfhs.nau-2A and Qfhi.nau-2D have been converted to breeder-friendly PCR-based markers to facilitate their applications.

Impact of biostimulant and saline water on cape gooseberry (Physalis peruviana L.) in Brazil

Production of Physalis peruviana L. has gained prominence in Northeastern Brazil. However, salinity limits the crop development in the Brazilian semiarid. Thus, this research aimed to evaluate the application of Acadian® biostimulant as mitigant of the deleterious effects of salinity on growth and gas exchange of P. peruviana plants. The experiment was combining different electrical conductivity of irrigation water (0.50, 1.23, 3.00, 4.44, and 5.50 dS m^-1) and biostimulant doses (0.00, 1.45, 5.00, 8.55, and 10.00 mL L^-1). The main variables evaluated were plant height, stem diameter, number of leaves, root length, leaf area, specific leaf area, leaf area ratio, absolute and relative growth rate for plant height, and gas exchange. Experimental results showed that an increase in electrical conductivity of irrigation water had negatively affected the growth components and gas exchange in P. peruviana. Also, the application of seaweed-based biostimulant improves the photosynthetic capacity (43.3%), reduces transpiration rate (26.5%) and water loss by this process, further it attenuated the deleterious effects of salinity on specific leaf area, leaf area ratio, and stomatal conductance. To further elucidate the effectiveness of biostimulant application as a mitigant of salt stress, research aimed at the biochemical and enzyme activities of the plant's antioxidant system should be conducted to better understand this process.

Wheat Yield Prediction Based on Unmanned Aerial Vehicles-Collected Red–Green–Blue Imagery

Unmanned aerial vehicles-collected (UAVs) digital red–green–blue (RGB) images provided a cost-effective method for precision agriculture applications regarding yield prediction. This study aims to fully explore the potential of UAV-collected RGB images in yield prediction of winter wheat by comparing it to multi-source observations, including thermal, structure, volumetric metrics, and ground-observed leaf area index (LAI) and chlorophyll content under the same level or across different levels of nitrogen fertilization. Color indices are vegetation indices calculated by the vegetation reflectance at visible bands (i.e., red, green, and blue) derived from RGB images. The results showed that some of the color indices collected at the jointing, flowering, and early maturity stages had high correlation (R2 = 0.76–0.93) with wheat grain yield. They gave the highest prediction power (R2 = 0.92–0.93) under four levels of nitrogen fertilization at the flowering stage. In contrast, the other measurements including canopy temperature, volumetric metrics, and ground-observed chlorophyll content showed lower correlation (R2 = 0.52–0.85) to grain yield. In addition, thermal information as well as volumetric metrics generally had little contribution to the improvement of grain yield prediction when combining them with color indices derived from digital images. Especially, LAI had inferior performance to color indices in grain yield prediction within the same level of nitrogen fertilization at the flowering stage (R2 = 0.00–0.40 and R2 = 0.55–0.68), and color indices provided slightly better prediction of yield than LAI at the flowering stage (R2 = 0.93, RMSE = 32.18 g/m2 and R2 = 0.89, RMSE = 39.82 g/m2) under all levels of nitrogen fertilization. This study highlights the capabilities of color indices in wheat yield prediction across genotypes, which also indicates the potential of precision agriculture application using many other flexible, affordable, and easy-to-handle devices such as mobile phones and near surface digital cameras in the future.

Genome wide association study of agronomic and seed traits in a world collection of proso millet (Panicum miliaceum L.)

BACKGROUND

The climate crisis threatens sustainability of crop production worldwide. Crop diversification may enhance food security while reducing the negative impacts of climate change. Proso millet (Panicum milaceum L.) is a minor cereal crop which holds potential for diversification and adaptation to different environmental conditions. In this study, we assembled a world collection of proso millet consisting of 88 varieties and landraces to investigate its genomic and phenotypic diversity for seed traits, and to identify marker-trait associations (MTA).

RESULTS

Sequencing of restriction-site associated DNA fragments yielded 494 million reads and 2,412 high quality single nucleotide polymorphisms (SNPs). SNPs were used to study the diversity in the collection and perform a genome wide association study (GWAS). A genotypic diversity analysis separated accessions originating in Western Europe, Eastern Asia and Americas from accessions sampled in Southern Asia, Western Asia, and Africa. A Bayesian structure analysis reported four cryptic genetic groups, showing that landraces accessions had a significant level of admixture and that most of the improved proso millet materials clustered separately from landraces. The collection was highly diverse for seed traits, with color varying from white to dark brown and width spanning from 1.8 to 2.6 mm. A GWAS study for seed morphology traits identified 10 MTAs. In addition, we identified three MTAs for agronomic traits that were previously measured on the collection.

CONCLUSION

Using genomics and automated seed phenotyping, we elucidated phylogenetic relationships and seed diversity in a global millet collection. Overall, we identified 13 MTAs for key agronomic and seed traits indicating the presence of alleles with potential for application in proso breeding programs.

A Novel Route of Mixed Catalysis for Production of Fatty Acid Methyl Esters from Potential Seed Oil Sources

Depleting petroleum resources coupled with the environmental consequences of fossil fuel combustion have led to the search for renewable alternatives, such as biodiesel. In this study, sunflower (Helianthus annus), mustard (Brassica compestres) and pearl millet (Pennisetum americanum) seed oils were converted into biodiesel (fatty acid methyl esters) by acid-, base- and lipase-catalyzed transesterification, and the resultant fuel properties were determined. The methyl esters displayed superior iodine values (102–139), low densities, and a high cetane number (CN). The highest yield of biodiesel was obtained from mustard seed oil, which provided cloud (CP) and pour (PP) points of −3.5 and 5 °C, respectively, and a CN of 53. The sunflower seed oil methyl esters had a density of 0.81–0.86 kg/L at 16 °C, CP of 2 °C, PP of −8 °C, and a CN of 47. The pearl millet seed oil methyl esters yielded a density 0.87–0.89 kg/L, CP and PP of 4 °C and −5 °C, respectively, and a CN of 46. The major fatty acids identified in the sunflower, mustard, and pearl millet seed oils were linolenic (49.2%), oleic acid (82.2%), and linoleic acid (73.9%), respectively. The present study reports biodiesel with ideal values of CP and PP, to extend the use of biodiesel at the commercial level.

QTL mapping for grain yield and three yield components in a population derived from two high-yielding spring wheat cultivars

Four genomic regions on chromosomes 4A, 6A, 7B, and 7D were discovered, each with multiple tightly linked QTL (QTL clusters) associated with two to three yield components. The 7D QTL cluster was associated with grain yield, fertile spikelet number per spike, thousand kernel weight, and heading date. It was located in the flanking region of FT-D1, a homolog gene of Arabidopsis FLOWERING LOCUS T, a major gene that regulates wheat flowering. Genetic manipulation of yield components is an important approach to increase grain yield in wheat (Triticum aestivum). The present study used a mapping population comprised of 181 doubled haploid lines derived from two high-yielding spring wheat cultivars, UI Platinum and LCS Star. The two cultivars and the derived population were assessed for six traits in eight field trials primarily in Idaho in the USA. The six traits were grain yield, fertile spikelet number per spike, productive tiller number per unit area, thousand kernel weight, heading date, and plant height. Quantitative Trait Locus (QTL) analysis of the six traits was conducted using 14,236 single-nucleotide polymorphism (SNP) markers generated from the wheat 90 K SNP and the exome and promoter capture arrays. Of the 19 QTL detected, 14 were clustered in four chromosomal regions on 4A, 6A, 7B and 7D. Each of the four QTL clusters was associated with multiple yield component traits, and these traits were often negatively correlated with one another. As a result, additional QTL dissection studies are needed to optimize trade-offs among yield component traits for specific production environments. Kompetitive allele-specific PCR markers for the four QTL clusters were developed and assessed in an elite spring wheat panel of 170 lines, and eight of the 14 QTL were validated. The two parents contain complementary alleles for the four QTL clusters, suggesting the possibility of improving grain yield via genetic recombination of yield component loci.

Peanut Leaf Wilting Estimation From RGB Color Indices and Logistic Models

Peanut (Arachis hypogaea L.) is an important crop for United States agriculture and worldwide. Low soil moisture is a major constraint for production in all peanut growing regions with negative effects on yield quantity and quality. Leaf wilting is a visual symptom of low moisture stress used in breeding to improve stress tolerance, but visual rating is slow when thousands of breeding lines are evaluated and can be subject to personnel scoring bias. Photogrammetry might be used instead. The objective of this article is to determine if color space indices derived from red-green-blue (RGB) images can accurately estimate leaf wilting for breeding selection and irrigation triggering in peanut production. RGB images were collected with a digital camera proximally and aerially by a unmanned aerial vehicle during 2018 and 2019. Visual rating was performed on the same days as image collection. Vegetation indices were intensity, hue, saturation, lightness, a^∗, b^∗, u^∗, v^∗, green area (GA), greener area (GGA), and crop senescence index (CSI). In particular, hue, a^∗, u^∗, GA, GGA, and CSI were significantly (p ≤ 0.0001) associated with leaf wilting. These indices were further used to train an ordinal logistic regression model for wilting estimation. This model had 90% accuracy when images were taken aerially and 99% when images were taken proximally. This article reports on a simple yet key aspect of peanut screening for tolerance to low soil moisture stress and uses novel, fast, cost-effective, and accurate RGB-derived models to estimate leaf wilting.

Identification of Main-Effect and Environmental Interaction QTL and Their Candidate Genes for Drought Tolerance in a Wheat RIL Population Between Two Elite Spring Cultivars

Understanding the genetics of drought tolerance can expedite the development of drought-tolerant cultivars in wheat. In this study, we dissected the genetics of drought tolerance in spring wheat using a recombinant inbred line (RIL) population derived from a cross between a drought-tolerant cultivar, ‘Reeder’ (PI613586), and a high-yielding but drought-susceptible cultivar, ‘Albany.’ The RIL population was evaluated for grain yield (YLD), grain volume weight (GVW), thousand kernel weight (TKW), plant height (PH), and days to heading (DH) at nine different environments. The Infinium 90 k-based high-density genetic map was generated using 10,657 polymorphic SNP markers representing 2,057 unique loci. Quantitative trait loci (QTL) analysis detected a total of 11 consistent QTL for drought tolerance-related traits. Of these, six QTL were exclusively identified in drought-prone environments, and five were constitutive QTL (identified under both drought and normal conditions). One major QTL on chromosome 7B was identified exclusively under drought environments and explained 13.6% of the phenotypic variation (PV) for YLD. Two other major QTL were detected, one each on chromosomes 7B and 2B under drought-prone environments, and explained 14.86 and 13.94% of phenotypic variation for GVW and YLD, respectively. One novel QTL for drought tolerance was identified on chromosome 2D. In silico expression analysis of candidate genes underlaying the exclusive QTLs associated with drought stress identified the enrichment of ribosomal and chloroplast photosynthesis-associated proteins showing the most expression variability, thus possibly contributing to stress response by modulating the glycosyltransferase (TraesCS6A01G116400) and hexosyltransferase (TraesCS7B01G013300) unique genes present in QTL 21 and 24, respectively. While both parents contributed favorable alleles to these QTL, unexpectedly, the high-yielding and less drought-tolerant parent contributed desirable alleles for drought tolerance at four out of six loci. Regardless of the origin, all QTL with significant drought tolerance could assist significantly in the development of drought-tolerant wheat cultivars, using genomics-assisted breeding approaches.

Scrutinizing the impact of water deficit in plants: Transcriptional regulation, signaling, photosynthetic efficacy, and management

Suboptimal availability of water limits plant growth, development, and performance. Drought is one of the leading factors responsible for worldwide crop yield reduction. In the future, owing to climate changes, more agricultural land will be affected by prolonged periods of water deficit. Thus, understanding the fundamental mechanism of drought response is a major scientific concern for improvement of crop production. To combat drought stress, plants deploy varied mechanistic strategies and alter their morphological, physiochemical, and molecular attributes. This helps plant to enhance water uptake and storage, reduce water loss and avoid wilting. Induction of several transcription factors and drought responsive genes leads to synthesis of stress proteins, regulation of water channels i.e. aquaporins and production of osmolytes that are essential for maintenance of osmotic balance at the cellular level. Self- and hormone-regulated signaling pathways are often stimulated by plants after receiving drought stress signals via secondary messengers, mitogen-activated protein kinases, and stress hormones. These signaling cascades often leads to stomatal closure and reduction in transpiration rates. Reduced carbon dioxide diffusion in chloroplast, lowered efficacy of photosystems, and other metabolic constraints limits the key regulatory photosynthetic process during water deficit. The impact of these stomatal and nonstomatal limitations varies with stress intensity, superimposed stresses and plant species. A clear understanding of the drought resistance process is thus important before adopting strategies for imparting drought tolerance in plants. These management practices at present include exogenous hormone application, breeding, and genetic engineering techniques for combating the water deficit issues.

Nitrate reductase is required for salicylic acid-induced water stress tolerance of pepper by upraising the AsA-GSH pathway and glyoxalase system

A trial was conducted to evaluate whether nitrate reductase (NR) participates in salicylic acid (SA)-improved water stress (WS) tolerance in pepper (Capsicum annuum L.) plants. Before starting WS treatment, 0.5 mM SA was applied to half of the well-watered (WW) plants as well as to WS-plants as a foliar spray once a day for a week. The soil water holding capacity was maintained at 40 and 80% of the full water storing capacity for WS and and well-watered (WW) plants, respectively. Water stress caused substantial decreases in total plant dry weight, F_v /F_m , chlorophyll a and b, relative water content, leaf water potential (ΨI) by 53, 37, 49, 21, 36 and 33%, respectively relative to control, but significant increases in malondialdehyde (MDA), hydrogen peroxide (H₂ O₂ ), electrolyte leakage (EL), methylglyoxal (MG), proline, key antioxidant enzymes' activities, NO and NR activity. The SA reduced oxidative stress, but improved antioxidant defence system, ascorbate-glutathione (AsA-GSH) cycle enzymes, glyoxalase system-related enzymes, glyoxalase I (Gly I) and glyoxalase II (Gly II), plant growth, photosynthetic traits, NO, NR and proline. SA-induced WS tolerance was further improved by supplementation of sodium nitroprusside (SNP), a donor of NO. NR inhibitor, sodium tungstate (ST) was applied in conjunction with SA and SA + SNP to the WW and WS-plants to assess whether NR contributes to SA-improved WS tolerance. ST abolished the beneficial effects of SA by reducing NO and NR activity in WS-pepper, but the application of SNP along with SA + ST reversed negative effects of ST, showing that NO and NR are jointly needed for SA-induced WS tolerance of pepper plants.

Important Physiological Changes Due to Drought Stress on Oat

As temperatures rise and water availability decreases, the water decit is gaining attention regarding future agricultural production. Drought stress is a global issue and adversely affects the productivity of different crops. In this study, drought-tolerant varieties of oats were screened to determine drought-tolerant varieties that may be employed in drought-prone areas to achieve sustainable development and mitigate the impact of climate change. To do so, the growth and stress adaptive mechanism of 15 domestic and overseas oat cultivars at the seedling stage were analyzed. Water stress was simulated using 20% polyethylene glycol (PEG-6000). The results showed that the soluble protein content and superoxide dismutase activity of variety DY2 significantly increased under drought stress, whereas the photochemical efficiency and relative water content decreased slightly. The relative electrical conductivity (REC) and drought damage index of the QH444 and DY2 varieties increased the least. The peroxidase content of Q1 and DY2 significantly increased, and the catalase activity of Q1, QH444, and DY2 also substantially increased. Principal component analysis revealed that nine physiological and biochemical parameters were transformed into three independent comprehensive indexes. The comprehensive evaluation results showed that DY2, LN, and Q1 exhibited a strong drought resistance capacity and could be used as a reference material for a drought-resistant oat breeding program. The gray correlation analysis also indicated that Fv/Fm, chlorophyll, REC, and malondialdehyde could be used as key indexes for evaluating the drought resistance of oat.

Impact of Varying Light and Dew on Ground Cover Estimates from Active NDVI, RGB, and LiDAR

Canopy ground cover (GC) is an important agronomic measure for evaluating crop establishment and early growth. This study evaluates the reliability of GC estimates, in the presence of varying light and dew on leaves, from three different ground-based sensors: (1) normalized difference vegetation index (NDVI) from the commercially available GreenSeeker®; (2) RGB images from a digital camera, where GC was determined as the portion of pixels from each image meeting a greenness criterion (i.e., (Green - Red)/(Green + Red) > 0); and (3) LiDAR using two separate approaches: (a) GC from LiDAR red reflectance (whereby red reflectance less than five was classified as vegetation) and (b) GC from LiDAR height (whereby height greater than 10 cm was classified as vegetation). Hourly measurements were made early in the season at two different growth stages (tillering and stem elongation), among wheat genotypes highly diverse for canopy characteristics. The active NDVI showed the least variation through time and was particularly stable, regardless of the available light or the presence of dew. In addition, between-sample-time Pearson correlations for NDVI were consistently high and significant (P < 0.0001), ranging from 0.89 to 0.98. In comparison, GC from LiDAR and RGB showed greater variation across sampling times, and LiDAR red reflectance was strongly influenced by the presence of dew. Excluding times when the light was exceedingly low, correlations between GC from RGB and NDVI were consistently high (ranging from 0.79 to 0.92). The high reliability of the active NDVI sensor potentially affords a high degree of flexibility for users by enabling sampling across a broad range of acceptable light conditions.

Importance of New Edible Oil Extracted from Seeds of Seven Cereals Species

Cereals constitute a major source of human and animal nutrition. In spite of the extensive production of numerous cereal species, some information is unavailable in terms of lipid composition. Due to the oil increasing demand by the overgrowth of the world population, oleaginous species have encountered problems in recent years. In order to find new sources of edible oil, the aim of this study was to describe the importance of seventeen varieties oil of seven cereal species. Oils were extracted by the Soxhlet method, and fatty acids were measured by gas chromatography. The present study demonstrated that the lipid content of cereal seeds ranged from 1.42% to 5.97%. In average, oat, millet, and maize had significantly higher lipid content, respectively, 5.97%, 5.06%, and 4.71%. The main fatty acid recorded in the studied cereal species, except oat, was linoleic acid C18 : 2 (ω6). Regarding the essential fatty acids linoleic acid C18 : 2 and linolenic acid C18 : 3 (ω3), the oil of all studied species, except oat, was rich in ω6 fatty acids (47.50 to 60.13%) and poor in ω3 (0.45% to 5.33%). The content of unsaturated fatty acids in all studied species ranged from 77.22 to 81.89%. Cereal oil was considered as highly unsaturated oil with the presence of the essential fatty acids necessary for human health. Therefore, cereal oils could be commercialized in small quantities in pharmacies or parapharmacies.

Importance of New Edible Oil Extracted from Seeds of Seven Cereals Species

Cereals constitute a major source of human and animal nutrition. In spite of the extensive production of numerous cereal species, some information is unavailable in terms of lipid composition. Due to the oil increasing demand by the overgrowth of the world population, oleaginous species have encountered problems in recent years. In order to find new sources of edible oil, the aim of this study was to describe the importance of seventeen varieties oil of seven cereal species. Oils were extracted by the Soxhlet method, and fatty acids were measured by gas chromatography. The present study demonstrated that the lipid content of cereal seeds ranged from 1.42% to 5.97%. In average, oat, millet, and maize had significantly higher lipid content, respectively, 5.97%, 5.06%, and 4.71%. The main fatty acid recorded in the studied cereal species, except oat, was linoleic acid C18 : 2 (ω6). Regarding the essential fatty acids linoleic acid C18 : 2 and linolenic acid C18 : 3 (ω3), the oil of all studied species, except oat, was rich in ω6 fatty acids (47.50 to 60.13%) and poor in ω3 (0.45% to 5.33%). The content of unsaturated fatty acids in all studied species ranged from 77.22 to 81.89%. Cereal oil was considered as highly unsaturated oil with the presence of the essential fatty acids necessary for human health. Therefore, cereal oils could be commercialized in small quantities in pharmacies or parapharmacies.

Starch molecular configuration and starch-sugar homeostasis: Key determinants of sweet sensory perception and starch hydrolysis in pearl millet (Pennisetum glaucum)

Starch-sugar homeostasis and starch molecular configuration regulates the dynamics of starch digestibility which result in sweet sensory perception and eliciting glycemic response, which has been measured in vitro as inherent glycemic potential (IGP). The objective of the research was to understand the key determinants of IGP as well as sweetness in different Pearl millet (PM) genotypes. To understand the intricate balance between starch and sugar, total starch content (TSC) and total soluble sugars (TSS) were evaluated. Higher concentrations of TSC (67.8%), TSS (2.75%), glucose (0.78%) and sucrose (1.68%) were found in Jafarabadi Bajra. Considering the role of compact molecular configuration of starch towards digestibility, X-ray powder diffraction (XRD) analysis was performed. A-type crystallinity with crystallinity degree (CD %) ranged from 53.53-62.63% among different genotypes, where the least CD% (53.53%) was found in Jafarabadi Bajra. In vitro starch hydrolyzation kinetics carried out to determine IGP, revealed a maximum of 77.05% IGP with minimum 1.42% resistant starch (RS) in Jafarabadi Bajra. Overall our results suggest higher sweet sensory perception of Jafarabadi Bajra which is contributed by the matrix composition with least molecular compactness of starch. Also, the interdependence among starch quality parameters; CD%, IGP, RS and amylose has also been discussed.

Construction of a high density genetic map for hexaploid kiwifruit (Actinidia chinensis var. deliciosa) using genotyping by sequencing

Commercially grown kiwifruit (genus Actinidia) are generally of two sub-species which have a base haploid genome of 29 chromosomes. The yellow-fleshed Actinidia chinensis var. chinensis, is either diploid (2n = 2x = 58) or tetraploid (2n = 4x = 116) and the green-fleshed cultivar A. chinensis var. deliciosa “Hayward,” is hexaploid (2n = 6x = 174). Advances in breeding green kiwifruit could be greatly sped up by the use of molecular resources for more efficient and faster selection, for example using marker-assisted selection (MAS). The key genetic marker that has been implemented for MAS in hexaploid kiwifruit is for gender testing. The limited marker-trait association has been reported for other polyploid kiwifruit for fruit and production traits. We have constructed a high-density linkage map for hexaploid green kiwifruit using genotyping-by-sequence (GBS). The linkage map obtained consists of 3686 and 3940 markers organized in 183 and 176 linkage groups for the female and male parents, respectively. Both parental linkage maps are co-linear with the A. chinensis “Red5” reference genome of kiwifruit. The linkage map was then used for quantitative trait locus (QTL) mapping, and successfully identified QTLs for king flower number, fruit number and weight, dry matter accumulation, and storage firmness. These are the first QTLs to be reported and discovered for complex traits in hexaploid kiwifruit.

Combining Thermal and RGB Imaging Indices with Multivariate and Data-Driven Modeling to Estimate the Growth, Water Status, and Yield of Potato under Different Drip Irrigation Regimes

Advances in proximal hyperspectral sensing tools, chemometric techniques, and data-driven modeling have enhanced precision irrigation management by facilitating the monitoring of several plant traits. This study investigated the performance of remote sensing indices derived from thermal and red-green-blue (RGB) images combined with stepwise multiple linear regression (SMLR) and an integrated adaptive neuro-fuzzy inference system with a genetic algorithm (ANFIS-GA) for monitoring the biomass fresh weight (BFW), biomass dry weight (BDW), biomass water content (BWC), and total tuber yield (TTY) of two potato varieties under 100%, 75%, and 50% of the estimated crop evapotranspiration (ETc). Results showed that the plant traits and indices varied significantly between the three irrigation regimes. Furthermore, all of the indices exhibited strong relationships with BFW, CWC, and TTY (R2 = 0.80–0.92) and moderate to weak relationships with BDW (R2 = 0.25–0.65) when considered for each variety across the irrigation regimes, for each season across the varieties and irrigation regimes, and across all data combined, but none of the indices successfully assessed any of the plant traits when considered for each irrigation regime across the two varieties. The SMLR and ANFIS-GA models gave the best predictions for the four plant traits in the calibration and testing stages, with the exception of the SMLR testing model for BDW. Thus, the use of thermal and RGB imaging indices with ANFIS-GA models could be a practical tool for managing the growth and production of potato crops under deficit irrigation regimes.

Genome-wide association study of multiple traits linked to heat tolerance in emmer-derived hexaploid wheat genotypes

Heat stress tolerance in plants is a complex trait controlled by multiple genes of minor effect which are influenced by the environment and this makes breeding and selection complicated. Emmer wheat (Triticum dicoccon Schrank) carries valuable diversity that can be used to improve the heat tolerance of modern bread wheat. A diverse set of emmer-based genotypes was developed by crossing emmer wheat with hexaploid wheat. These materials, along with their hexaploid recurrent parents and commercial cultivars, were evaluated at optimum (E1) and heat stressed (E2) sowing times in the field for three consecutive years (2014-2016). The material was genotyped using the Infinium iSelect SNP 90K SNP Assay. The phenotypic data were combined across years within each sowing time and best linear unbiased estimators calculated for each genotype in each environment. These estimates were used for GWAS analysis. Significant phenotypic and genotypic variation was observed for all traits. A total of 125 and 142 marker-trait associations (MTAs) were identified in E1 and E2, respectively. The highest number of MTAs were observed on the A genome (106), followed by the B (105) and D (56) genomes. MTAs with pleiotropic effects within and across the environments were observed. Many of the MTAs found were reported previously for various traits, and a few significant MTAs under heat stress were new and linked to emmer genome. Genomic regions identified on chromosomes 2B and 3A had a significant positive impact on grain yield under stress with a 7% allelic effect. Genomic regions on chromosomes 1A and 4B contributed 11% and 9% of the variation for thousand kernel weight (TKW) under heat stress respectively. Following fine mapping, these regions could be used for marker-assisted selection to improve heat tolerance in wheat.

Supplementary Information

The online version contains supplementary material available at 10.1007/s11032-021-01222-3.

High-Throughput Phenotyping: A Platform to Accelerate Crop Improvement

Development of high-throughput phenotyping technologies has progressed considerably in the last 10 years. These technologies provide precise measurements of desired traits among thousands of field-grown plants under diversified environments; this is a critical step towards selection of better performing lines as to yield, disease resistance, and stress tolerance to accelerate crop improvement programs. High-throughput phenotyping techniques and platforms help unraveling the genetic basis of complex traits associated with plant growth and development and targeted traits. This review focuses on the advancements in technologies involved in high-throughput, field-based, aerial, and unmanned platforms. Development of user-friendly data management tools and softwares to better understand phenotyping will increase the use of field-based high-throughput techniques, which have potential to revolutionize breeding strategies and meet the future needs of stakeholders.

Identification of Candidate Genes for Root Traits Using Genotype-Phenotype Association Analysis of Near-Isogenic Lines in Hexaploid Wheat (Triticum aestivum L.)

Global wheat (Triticum aestivum L.) production is constrained by different biotic and abiotic stresses, which are increasing with climate change. An improved root system is essential for adaptability and sustainable wheat production. In this study, 10 pairs of near-isogenic lines (NILs)-targeting four genomic regions (GRs) on chromosome arms 4BS, 4BL, 4AS, and 7AL of hexaploid wheat-were used to phenotype root traits in a semi-hydroponic system. Seven of the 10 NIL pairs significantly differed between their isolines for 11 root traits. The NIL pairs targeting qDSI.4B.1 GR varied the most, followed by the NIL pair targeting qDT.4A.1 and QHtscc.ksu-7A GRs. For pairs 5-7 targeting qDT.4A.1 GR, pair 6 significantly differed in the most root traits. Of the 4 NIL pairs targeting qDSI.4B.1 GR, pairs 2 and 4 significantly differed in 3 and 4 root traits, respectively. Pairs 9 and 10 targeting QHtscc.ksu-7A GR significantly differed in 1 and 4 root traits, respectively. Using the wheat 90K Illumina iSelect array, we identified 15 putative candidate genes associated with different root traits in the contrasting isolines, in which two UDP-glycosyltransferase (UGT)-encoding genes, TraesCS4A02G185300 and TraesCS4A02G442700, and a leucine-rich repeat receptor-like protein kinase (LRR-RLK)-encoding gene, TraesCS4A02G330900, also showed important functions for root trait control in other crops. This study characterized, for the first time, that these GRs control root traits in wheat, and identified candidate genes, although the candidate genes will need further confirmation and validation for marker-assisted wheat breeding.

Using Unmanned Aerial Vehicle and Ground-Based RGB Indices to Assess Agronomic Performance of Wheat Landraces and Cultivars in a Mediterranean-Type Environment

The adaptability and stability of new bread wheat cultivars that can be successfully grown in rainfed conditions are of paramount importance. Plant improvement can be boosted using effective high-throughput phenotyping tools in dry areas of the Mediterranean basin, where drought and heat stress are expected to increase yield instability. Remote sensing has been of growing interest in breeding programs since it is a cost-effective technology useful for assessing the canopy structure as well as the physiological traits of large genotype collections. The purpose of this study was to evaluate the use of a 4-band multispectral camera on-board an unmanned aerial vehicle (UAV) and ground-based RGB imagery to predict agronomic traits as well as quantify the best estimation of leaf area index (LAI) in rainfed conditions. A collection of 365 bread wheat genotypes, including 181 Mediterranean landraces and 184 modern cultivars, was evaluated during two consecutive growing seasons. Several vegetation indices (VI) derived from multispectral UAV and ground-based RGB images were calculated at different image acquisition dates of the crop cycle. The modified triangular vegetation index (MTVI2) proved to have a good accuracy to estimate LAI (R2 = 0.61). Although the stepwise multiple regression analysis showed that grain yield and number of grains per square meter (NGm2) were the agronomic traits most suitable to be predicted, the R2 were low due to field trials were conducted under rainfed conditions. Moreover, the prediction of agronomic traits was slightly better with ground-based RGB VI rather than with UAV multispectral VIs. NDVI and GNDVI, from multispectral images, were present in most of the prediction equations. Repeated measurements confirmed that the ability of VIs to predict yield depends on the range of phenotypic data. The current study highlights the potential use of VI and RGB images as an efficient tool for high-throughput phenotyping under rainfed Mediterranean conditions.