Metabolic profiling of pea (Pisum sativum) cultivars in changing environments: Implications for nutritional quality in animal feed.

Field pea seeds have long been recognized as valuable feed ingredients for animal diets, due to their high-quality protein and starch digestibility. However, the chemical composition of pea cultivars can vary across different growing locations, consequently impacting their nutrient profiles. This study employs untargeted metabolomics in conjunction with the quantification of fatty acids and amino acids to explore the influence of three different growing locations in Spain (namely Andalusia, Aragon and Asturias), on the nutritional characteristics of seeds of various pea cultivars. Significant interactions between cultivar and environment were observed, with 121 metabolites distinguishing pea profiles. Lipids, lipid-like molecules, phenylpropanoids, polyketides, carbohydrates, and amino acids were the most affected metabolites. Fatty acid profiles varied across locations, with higher C16:0, C18:0, and 18:1 n-9 concentration in Aragón, while C18:2 n-6 predominated in Asturias and C18:3 n-3 in Andalusia. Amino acid content was also location-dependent, with higher levels in Asturias. These findings underscore the impact of environmental factors on pea metabolite profiles and emphasize the importance of selecting pea cultivars based on specific locations and animal requirements. Enhanced collaboration between research and industry is crucial for optimizing pea cultivation for animal feed production.

Identification of Sources of Resistance to Aphanomyces Root Rot in Pisum.

Aphanomyces root rot (ARR), caused by Aphanomyces euteiches, is one of the most devastating diseases that affect the production of peas. Several control strategies such as crop rotation, biocontrol, and fungicides have been proposed, but none provides a complete solution. Therefore, the deployment of resistant cultivars is fundamental. ARR resistance breeding is hampered by the moderate levels of resistance identified so far. The available screening protocols require post-inoculation root assessment, which is destructive, time-consuming, and tedious. In an attempt to address these limitations, we developed a non-destructive screening protocol based on foliar symptoms and used it to identify new sources of resistance in a Pisum spp. germplasm collection. Accessions were root inoculated separately with two A. euteiches isolates, and leaf symptoms were assessed at 5, 10, 14, 17, and 20 days after inoculation (DAI). Although the majority of accessions exhibited high levels of susceptibility, thirty of them exhibited moderate resistance. These thirty accessions were selected for a second experiment, in which they were inoculated with both A. euteiches isolates at two inoculum doses. The objective of this second trial was to confirm the resistance of these accessions by evaluating root and biomass loss, as well as foliar symptoms, and to compare root and foliar evaluations. As a result, a high correlation (R2 = 0.75) between foliar and root evaluations was observed, validating the foliar evaluation method. Notably, accessions from P.s. subsp. humile exhibited the lowest symptomatology across all evaluation methods, representing valuable genetic resources for breeding programs aimed at developing pea varieties resistant to ARR.

Genomic prediction for rust resistance in pea.

Genomic selection (GS) has become an indispensable tool in modern plant breeding, particularly for complex traits. This study aimed to assess the efficacy of GS in predicting rust (Uromyces pisi) resistance in pea (Pisum sativum), using a panel of 320 pea accessions and a set of 26,045 Silico-Diversity Arrays Technology (Silico-DArT) markers. We compared the prediction abilities of different GS models and explored the impact of incorporating marker × environment (M×E) interaction as a covariate in the GBLUP (genomic best linear unbiased prediction) model. The analysis included phenotyping data from both field and controlled conditions. We assessed the predictive accuracies of different cross-validation strategies and compared the efficiency of using single traits versus a multi-trait index, based on factor analysis and ideotype-design (FAI-BLUP), which combines traits from controlled conditions. The GBLUP model, particularly when modified to include M×E interactions, consistently outperformed other models, demonstrating its suitability for traits affected by complex genotype-environment interactions (GEI). The best predictive ability (0.635) was achieved using the FAI-BLUP approach within the Bayesian Lasso (BL) model. The inclusion of M×E interactions significantly enhanced prediction accuracy across diverse environments in GBLUP models, although it did not markedly improve predictions for non-phenotyped lines. These findings underscore the variability of predictive abilities due to GEI and the effectiveness of multi-trait approaches in addressing complex traits. Overall, our study illustrates the potential of GS, especially when employing a multi-trait index like FAI-BLUP and accounting for M×E interactions, in pea breeding programs focused on rust resistance.

Genome-Wide Association Studies on Resistance to Pea Weevil: Identification of Novel Sources of Resistance and Associated Markers.

Little resistance to the pea weevil insect pest (Bruchus pisorum) is available in pea (Pisum sativum) cultivars, highlighting the need to search for sources of resistance in Pisum germplasm and to decipher the genetic basis of resistance. To address this need, we screened the response to pea weevil in a Pisum germplasm collection (324 accession, previously genotyped) under field conditions over four environments. Significant variation for weevil seed infestation (SI) was identified, with resistance being frequent in P. fulvum, followed by P. sativum ssp. elatius, P. abyssinicum, and P. sativum ssp. humile. SI tended to be higher in accessions with lighter seed color. SI was also affected by environmental factors, being favored by high humidity during flowering and hampered by warm winter temperatures and high evapotranspiration during and after flowering. Merging the phenotypic and genotypic data allowed genome-wide association studies (GWAS) yielding 73 markers significantly associated with SI. Through the GWAS models, 23 candidate genes were found associated with weevil resistance, highlighting the interest of five genes located on chromosome 6. These included gene 127136761 encoding squalene epoxidase; gene 127091639 encoding a transcription factor MYB SRM1; gene 127097033 encoding a 60S ribosomal protein L14; gene 127092211, encoding a BolA-like family protein, which, interestingly, was located within QTL BpLD.I, earlier described as conferring resistance to weevil in pea; and gene 127096593 encoding a methyltransferase. These associated genes offer valuable potential for developing pea varieties resistant to Bruchus spp. and efficient utilization of genomic resources through marker-assisted selection (MAS).

Identification of novel genes associated with herbicide tolerance in Lentil (Lens culinaris ssp. culinaris Medik.).

Weeds pose a major constraint in lentil cultivation, leading to decrease farmers' revenues by reducing the yield and increasing the management costs. The development of herbicide tolerant cultivars is essential to increase lentil yield. Even though herbicide tolerant lines have been identified in lentils, breeding efforts are still limited and lack proper validation. Marker assisted selection (MAS) can increase selection accuracy at early generations. Total 292 lentil accessions were evaluated under different dosages of two herbicides, metribuzin and imazethapyr, during two seasons at Marchouch, Morocco and Terbol, Lebanon. Highly significant differences among accessions were observed for days to flowering (DF) and maturity (DM), plant height (PH), biological yield (BY), seed yield (SY), number of pods per plant (NP), as well as the reduction indices (RI) for PH, BY, SY and NP. A total of 10,271 SNPs markers uniformly distributed along the lentil genome were assayed using Multispecies Pulse SNP chip developed at Agriculture Victoria, Melbourne. Meta-GWAS analysis was used to detect marker-trait associations, which detected 125 SNPs markers associated with different traits and clustered in 85 unique quantitative trait loci. These findings provide valuable insights for initiating MAS programs aiming to enhance herbicide tolerance in lentil crop.

Improvement of cool-season food legumes for adaptation to intercropping systems: breeding faba bean for intercropping with durum wheat as a case study.

Although the transition toward a more sustainable agricultural system is sparking the interest of scientists and farmers around the globe, breeding programs are still focusing on optimizing cultivars intended for the monoculture system, and most cultivars available on the market are not suitable for intercropping. The incorporation of versatile cool-season food legumes (CSFLs) in the intercropping system is a promising way toward more diversified and sustainable cropping systems. However, as the selection of good-performing cultivars under sole cropping does not always lead to a good performance in intercropping, the development of an alternative breeding scheme for intercropping is now a necessity. The case study of faba bean-wheat intercropping was used to select for traits associated with better performance of faba bean, resulting in identifying the combined grain yield, 100-seed weight, number of pods per plant, and canopy height as key traits for faba bean-wheat intercropping suitability. Incorporating these traits in the breeding programs would be the cornerstone of the prospective transition.

Optimization of inoculum production of Stemphylium botryosum for large-scale resistance screening of lentils.

BACKGROUND: Stemphylium blight incited by Stemphylium botryosum poses a significant threat to lentil crops worldwide, inducing severe defoliation and causing substantial yield losses in susceptible varieties under favorable conditions. While some moderate levels of resistance have been identified within lentil germplasm, a low number of resistant cultivars are available to farmers. Adding to the common constraints of resistance breeding, a notable challenge is generating a sufficient number of spores for large-scale screenings, which are essential for pinpointing additional sources of resistance for integration into breeding programs. Therefore, there is a pressing need to improve existing screening methods and tailor them for large-scale material selection. In pursuit of this objective, a protocol for the efficient production of fungal material has been adapted. RESULTS: Optimization of fungal material production was successfully achieved by comparing the use of fungal mycelia and spores. Spore production was found to be optimal when produced on solid V8-PDA(hi) medium, while liquid Richard's medium was identified as superior for mycelium yield. Furthermore, a refined screening method was developed by evaluating the resistance of six lentil accessions to stemphylium blight. This assessment included the use of either fungal mycelia (at densities ranging from 1 to 5 g L- 1) or spores (with densities ranging from 5 × 104 to 2 × 105 conidia mL- 1) under three different relative humidity levels (from 50 to 100%). Both humidity levels and inoculum dose significantly influenced the final disease rating (DR) and the relative Area Under the Disease Progress Curve (rAUDPC). Differences among genotypes in final symptom severity (DR) became more pronounced after inoculation with inoculum densities of 5 g L- 1 of mycelium or of 105 and 2 × 105 conidia mL- 1 of spore under 100% relative humidity. Given the challenges associated with the large-scale production of S. botryosum spores, inoculations with 5 g L- 1 of mycelium is highly recommended as a practical alternative for conducting mass-scale screenings. CONCLUSIONS: The findings from this study underscore the critical importance of maintaining high level of humidity during inoculation and disease progression development for accurately assessing resistance to stemphylium blight. The optimization of mycelial production for suspension inoculation emerges as a more reliable and efficient approach for conducting large-scale screening to assess germplasm resistance against stemphylium blight in lentil crops.

Identification of novel sources of partial and incomplete hypersensitive resistance to rust and associated genomic regions in common bean.

Common bean (Phaseolus vulgaris) is one of the legume crops most consumed worldwide and bean rust is one of the most severe foliar biotrophic fungal diseases impacting its production. In this work, we searched for new sources of rust resistance (Uromyces appendiculatus) in a representative collection of the Portuguese germplasm, known to have accessions with an admixed genetic background between Mesoamerican and Andean gene pools. We identified six accessions with incomplete hypersensitive resistance and 20 partially resistant accessions of Andean, Mesoamerican, and admixed origin. We detected 11 disease severity-associated single-nucleotide polymorphisms (SNPs) using a genome-wide association approach. Six of the associations were related to partial (incomplete non-hypersensitive) resistance and five to incomplete hypersensitive resistance, and the proportion of variance explained by each association varied from 4.7 to 25.2%. Bean rust severity values ranged from 0.2 to 49.1% and all the infection types were identified, reflecting the diversity of resistance mechanisms deployed by the Portuguese germplasm.The associations with U. appendiculatus partial resistance were located in chromosome Pv08, and with incomplete hypersensitive resistance in chromosomes Pv06, Pv07, and Pv08, suggesting an oligogenic inheritance of both types of resistance. A resolution to the gene level was achieved for eight of the associations. The candidate genes proposed included several resistance-associated enzymes, namely ß-amylase 7, acyl-CoA thioesterase, protein kinase, and aspartyl protease. Both SNPs and candidate genes here identified constitute promising genomics targets to develop functional molecular tools to support bean rust resistance precision breeding.

Comparative Analysis of Secondary Metabolites Produced by Ascochyta fabae under In Vitro Conditions and Their Phytotoxicity on the Primary Host, Vicia faba, and Related Legume Crops.

Ascochyta blight, caused by Ascochyta fabae, poses a significant threat to faba bean and other legumes worldwide. Necrotic lesions on stems, leaves, and pods characterize the disease. Given the economic impact of this pathogen and the potential involvement of secondary metabolites in symptom development, a study was conducted to investigate the fungus's ability to produce bioactive metabolites that might contribute to its pathogenicity. For this investigation, the fungus was cultured in three substrates (Czapek-Dox, PDB, and rice). The produced metabolites were analyzed by NMR and LC-HRMS methods, resulting in the dereplication of seven metabolites, which varied with the cultural substrates. Ascochlorin, ascofuranol, and (R)-mevalonolactone were isolated from the Czapek-Dox extract; ascosalipyrone, benzoic acid, and tyrosol from the PDB extract; and ascosalitoxin and ascosalipyrone from the rice extract. The phytotoxicity of the pure metabolites was assessed at different concentrations on their primary hosts and related legumes. The fungal exudates displayed varying degrees of phytotoxicity, with the Czapek-Dox medium's exudate exhibiting the highest activity across almost all legumes tested. The species belonging to the genus Vicia spp. were the most susceptible, with faba bean being susceptible to all metabolites, at least at the highest concentration tested, as expected. In particular, ascosalitoxin and benzoic acid were the most phytotoxic in the tested condition and, as a consequence, expected to play an important role on necrosis's appearance.

Variability of Fatty Acid Composition and Lignan Content in Sesame Germplasm, and Effect of Roasting.

Sesame (Sesamum indicum) seeds are highly valued for their culinary applications and for producing a premium-quality oil. This study investigated the polyphenol content and fatty acid composition of a set of sesame accessions and examined their association with seed colors. Among the different colors, black-seeded accessions exhibited the highest total lignan content, while white-seeded accessions had average lower levels. Brown-seeded accessions showed relatively lower concentrations of sesamol and intermediate levels of sesamolin and sesamin than other colors. The oil derived from these seeds contained unsaturated fatty acids (UFAs) and saturated fatty acids (SFAs), nutritionally crucial for human consumption. Brown varieties exhibited higher concentrations of these fatty acids. Roasting black and white sesame seeds at increasing temperatures (180 and 250 °C) significantly affected lignan and UFAs concentrations. Higher temperatures resulted in elevated levels of detrimental t-oleic and t-linoleic acids. Furthermore, sesamolin content notably decreased at 180 °C and became undetectable at 250 °C. The temperature also caused a marked increase in sesamol, regardless of seed color. PCA analysis highlighted clusters between white and black varieties according to roasting temperature, displaying the potential application of chemometrics to assess processing effects and ensure sesame quality and safety. This research provides valuable insights for exploiting sesame within agrosystems in Mediterranean climates.

RGB image-based method for phenotyping rust disease progress in pea leaves using R.

BACKGROUND: Rust is a damaging disease affecting vital crops, including pea, and identifying highly resistant genotypes remains a challenge. Accurate measurement of infection levels in large germplasm collections is crucial for finding new resistance sources. Current evaluation methods rely on visual estimation of disease severity and infection type under field or controlled conditions. While they identify some resistance sources, they are error-prone and time-consuming. An image analysis system proves useful, providing an easy-to-use and affordable way to quickly count and measure rust-induced pustules on pea samples. This study aimed to develop an automated image analysis pipeline for accurately calculating rust disease progression parameters under controlled conditions, ensuring reliable data collection. RESULTS: A highly efficient and automatic image-based method for assessing rust disease in pea leaves was developed using R. The method's optimization and validation involved testing different segmentation indices and image resolutions on 600 pea leaflets with rust symptoms. The approach allows automatic estimation of parameters like pustule number, pustule size, leaf area, and percentage of pustule coverage. It reconstructs time series data for each leaf and integrates daily estimates into disease progression parameters, including latency period and area under the disease progression curve. Significant variation in disease responses was observed between genotypes using both visual ratings and image-based analysis. Among assessed segmentation indices, the Normalized Green Red Difference Index (NGRDI) proved fastest, analysing 600 leaflets at 60% resolution in 62 s with parallel processing. Lin's concordance correlation coefficient between image-based and visual pustule counting showed over 0.98 accuracy at full resolution. While lower resolution slightly reduced accuracy, differences were statistically insignificant for most disease progression parameters, significantly reducing processing time and storage space. NGRDI was optimal at all time points, providing highly accurate estimations with minimal accumulated error. CONCLUSIONS: A new image-based method for monitoring pea rust disease in detached leaves, using RGB spectral indices segmentation and pixel value thresholding, improves resolution and precision. It rapidly analyses hundreds of images with accuracy comparable to visual methods and higher than other image-based approaches. This method evaluates rust progression in pea, eliminating rater-induced errors from traditional methods. Implementing this approach to evaluate large germplasm collections will improve our understanding of plant-pathogen interactions and aid future breeding for novel pea cultivars with increased rust resistance.

Uncovering Phytotoxic Compounds Produced by Colletotrichum spp. Involved in Legume Diseases Using an OSMAC-Metabolomics Approach.

Different fungal species belonging to the Colletotrichum genus cause anthracnose disease in a range of major crops, resulting in huge economic losses worldwide. Typical symptoms include dark, sunken lesions on leaves, stems, or fruits. Colletotrichum spp. have synthesized, in vitro, a number of biologically active and structurally unusual metabolites that are involved in their host's infection process. In this study, we applied a one strain many compounds (OSMAC) approach, integrated with targeted and non-targeted metabolomics profiling, to shed light on the secondary phytotoxic metabolite panels produced by pathogenic isolates of Colletotrichum truncatum and Colletotrichum trifolii. The phytotoxicity of the fungal crude extracts was also assessed on their primary hosts and related legumes, and the results correlated with the metabolite profile that arose from the different cultural conditions. To the best of our knowledge, this is the first time that the OSMAC strategy integrated with metabolomics approaches has been applied to Colletotrichum species involved in legume diseases.

Lathyrus sativus Resistance Against the Existing and Emerging Pathogens Erysiphe pisi and E. trifolii: A Case of Commonalities or Total Discrepancy?

Powdery mildew on Lathyrus sativus (grass pea) is commonly caused by Erysiphe pisi, the causal agent of pea powdery mildew. E. trifolii could also pose an additional threat to grass pea, as it does to pea (Pisum sativum). In order to understand the potential threat and the availability of resistance sources, the response to both pathogens was analyzed on a worldwide germplasm collection of 189 grass pea accessions. Infection type and disease severity (DS) of grass pea accessions, independently inoculated with E. pisi and E. trifolii, were evaluated under controlled conditions. A wide range of responses were detected, with the previously uncharacterized partial resistance to E. trifolii in grass pea detected less frequently and uncorrelated with partial resistance against E. pisi. To test for the lack of correlation at the genetic level, an exploratory association mapping study was undertaken by statistically combining grass pea collection DS scores against both pathogens, with 5,651 previously screened genotype-by-sequencing-based single nucleotide polymorphisms (SNP). Mostly different genetic regions in grass pea were identified as being associated with the response to E. trifolii and E. pisi, anticipating an independent genetic basis that requires further validation in larger germplasm collections, with higher SNP densities. This study proposes common and unique partial resistance components against two different powdery mildews, implying the need for complementary approaches to introduce resistance to both pathogens into new grass pea varieties. The identified sources of resistance and predicted genomic targets will assist in breeding for resistance to multiple powdery mildews.

Oligogenic Control of Quantitative Resistance Against Powdery Mildew Revealed in Portuguese Common Bean Germplasm.

Common bean (Phaseolus vulgaris L.) is one of the most important food legumes worldwide, and its production is severely affected by fungal diseases such as powdery mildew. Portugal has a diverse germplasm, with accessions of Andean, Mesoamerican, and admixed origin, making it a valuable resource for common bean genetic studies. In this work, we evaluated the response of a Portuguese collection of 146 common bean accessions to Erysiphe diffusa infection, observing a wide range of disease severity and different levels of compatible and incompatible reactions, revealing the presence of different resistance mechanisms. We identified 11 incompletely hypersensitive resistant and 80 partially resistant accessions. We performed a genome-wide association study to clarify its genetic control, resulting in the identification of eight disease severity-associated single-nucleotide polymorphisms, spread across chromosomes Pv03, Pv09, and Pv10. Two of the associations were unique to partial resistance and one to incomplete hypersensitive resistance. The proportion of variance explained by each association varied between 15 and 86%. The absence of a major locus, together with the relatively small number of loci controlling disease severity, suggested an oligogenic inheritance of both types of resistance. Seven candidate genes were proposed, including a disease resistance protein (toll interleukin 1 receptor-nucleotide binding site-leucine-rich repeat class), an NF-Y transcription factor complex component, and an ABC-2 type transporter family protein. This work contributes with new resistance sources and genomic targets valuable to develop selection molecular tools and support powdery mildew resistance precision breeding in common bean.

High Inter- and Intra- Diversity of Amino Acid Content and Protein Digestibility Disclosed in Five Cool Season Legume Species with a Growing Market Demand.

Legumes have been sought as alternative protein sources to ensure food security and environmental sustainability. Characterizing their protein content and quality, including in underutilized grain legumes, e.g., grass pea, gives value to the legumes' underexplored variability. To fill the gap of knowledge in legumes' protein quality, for the first time, five extensive collections of cool season grain legumes were cropped under the same environmental conditions and further analyzed. Multivariate analysis showed the existent intra- and inter-species variability. The legume species with the highest protein content, grass pea, Lathyrus sativus (LS), was not the one with the overall highest individual amino acids content and in vitro protein digestibility. With these last characteristics lentil, Lens culinaris (LC), was highlighted. The highest average values of arginine (Arg), glutamic acid (Glu), and threonine (Thr) were found in LS and Vicia faba (VF). Cicer arietinum (CA) stood out as the species with the highest values of Thr and methionine (Met). Regarding the in vitro protein digestibility (IVPD), LC, followed by Pisum sativum (PS) and LS, were the legume species with the highest values. Ultimately, this study bought to the fore legume species that are not commonly used in western diets but have high adaptability to the European agricultural systems.

Status of Phytotoxins Isolated from Necrotrophic Fungi Causing Diseases on Grain Legumes.

Fungal phytotoxins can be defined as secondary metabolites toxic to host plants and are believed to be involved in the symptoms developed of a number of plant diseases by targeting host cellular machineries or interfering with host immune responses. As any crop, legumes can be affected by a number of fungal diseases, causing severe yield losses worldwide. In this review, we report and discuss the isolation, chemical, and biological characterization of fungal phytotoxins produced by the most important necrotrophic fungi involved in legume diseases. Their possible role in plant-pathogen interaction and structure-toxicity relationship studies have also been reported and discussed. Moreover, multidisciplinary studies on other prominent biological activity conducted on reviewed phytotoxins are described. Finally, we explore the challenges in the identification of new fungal metabolites and their possible applications in future experiments.

Crop Diversification to Control Rust in Faba Bean Caused by Uromyces viciae-fabae.

Uromyces viciae-fabae is a highly specific biotrophic fungus that causes faba bean rust, one of the major diseases affecting this crop. We have assessed the feasibility of using intercropping (faba bean mixed with either pea, wheat or barley) or mixtures of susceptible and resistant cultivars to control rust both under field and controlled conditions. The results of four field intercropping experiments showed a significant reduction in rust severity on faba bean when intercropped with barley (average 22% reduction) but not with the other combinations. This reduction was also confirmed in studies under controlled conditions. The barrier effect of barley appears as the main mechanism explaining rust suppression. Additional experiments under controlled conditions showed that intercropping with barley did not influence the N content of faba bean and that different levels of N nutrition had no impact on rust severity in any case. The cultivar mixture field experiments showed that rust severity in the susceptible cultivar decreased as the proportion of the resistant cultivar in the mixture increased. The importance of the barrier effect of the resistant cultivars was determined in an experiment under controlled conditions. It can be concluded that crop diversification offers great potential to reduce rust in faba bean.