Metabolomics of Red Wines Aged Traditionally, with Chips or Staves.

Traditionally and alternatively aged wines' odour activity values (OAVs) are investigated to differentiate and highlight the differences between the selected methods. An analysis of the volatile aroma compounds of wines derived from ageing in barrels, oak chips, and staves was performed using stir bar sorptive extraction chromatography-mass spectroscopy (SBSE-GC-MS). The results showed that alcohols, esters, and oak compounds were the main contributors to aroma, and their OAVs were higher in the stave samples after 3 months than in the samples from the other two systems of ageing. Furthermore, wines aged with staves have stronger fruity, spiced, and woody aromas, while samples aged in barrels present more chemistry-driven, floral, caramelly, and creamy aromas. The staves-medium plus toast (SMPT at 3 months > 225) and chips-medium plus toast (CMPT at 3 months > 170) showed the highest levels of aromatic series, suggesting that alternative systems provided more powerful aromas than traditional systems, such as barrels-medium plus toast (BMPT at 3 months > 150). A principal component analysis (PCA), orthogonal partial least squares (OPLS) analysis, and cluster analysis allowed for a clear differentiation to be made between red wines according to ageing systems and ageing times. The odour activity values fingerprint in winemaking is a feasible approach to characterise and distinguish wines. Moreover, OAVs provide important information on the effects of production methods on wine quality and aroma profile.

A First Report of Sclerotinia sclerotiorum Causing Forsythia Twig Blight in Romania.

Sclerotinia sclerotiorum (Lib.) de Bary (1884) is a fungal plant pathogen with worldwide distribution and a varying host range from different botanical families. It can cause damage to a large variety of crops such as sunflower, soybean, dry bean, canola, some vegetables, and ornamental plants. This article reports the occurrence of twig blight on the forsythia plant from the NE region of Romania. The disease was observed on Forsythia × intermedia Zab. plants from the Arboretum Park of the Iasi University of Life Sciences (IULS), located in Iasi City, Romania. Infected tissue was investigated through morphological characteristics using Sanger sequencing. Genomic DNA was extracted from the isolate obtained from naturally infected plants, and the ribosomal internal transcribed spacer region was amplified using the ITS1, ITS2, and LSU D1 and D2. Based on the results of this study, molecular and morphological data suggest that Forsythia twig blight can be caused by S. sclerotiorum. Constant monitoring of Sclerotinia sclerotiorum across multiple hosts and time intervals will reduce potential spread and future economic losses in cultivated species.

Investigating Six Common Pesticides Residues and Dietary Risk Assessment of Romanian Wine Varieties.

The food and environmental safety debate extends to the use of pesticides in agriculture including the wine sector, which is one of the most intensive pesticide users across the agricultural sector. Pesticide utilisation is a common agricultural practice to protect fruits and plants from pathogens and insects while maintaining high production levels. Grapevine is generally a crop that is subject to intensive phytosanitary treatments, and therefore, it can be assumed that pesticide residues will accumulate in the vine-shoots and, later on, end up in the grapes and wines. The aim of this study was to determine the pesticide content in red, rosé, and white wines after phytosanitary treatments applied in the vineyard and their impact on long-term dietary risks. The following six pesticides were analysed: oxathiapiprolin, myclobutanil, iprovalicarb, tebuconazole, chlorantraniliprole, and acetamiprid. Samples were extracted using the QuEChERS (quick, easy, cheap, effective, rugged, and safe) method and analysed for the residues of pesticides by liquid chromatography-tandem mass spectrometry. Results indicated that the observed pesticides in the wine samples ranged between 0.05 and 0.75 ng/g. Dietary risks due to pesticide residues for women and men were evaluated using the estimated daily intake (EDI), hazard quotient (HQ), and hazard index (HI) of wines. The HQs and HIs did not surpass the 1 value (HQ, HI < 1) for both women and men, denoting that the concentrations of pesticide residues in these wine samples do not pose any immediate risk to consumers. Moreover, a pesticide residue intake model (PRIMo) model analysis was conducted, and the results suggest that European adult consumers have a low pesticide residue intake due to moderate wine consumption. However, pesticide residue intakes have been associated with several human health problems and high toxicity levels, therefore reliable analytical methods to monitor their presence in horticultural crops is crucial for clean and safe food products and healthy consumers.

Machine Learning Applied to the Search for Nonlinear Features in Breeding Populations.

Large plant breeding populations are traditionally a source of novel allelic diversity and are at the core of selection efforts for elite material. Finding rare diversity requires a deep understanding of biological interactions between the genetic makeup of one genotype and its environmental conditions. Most modern breeding programs still rely on linear regression models to solve this problem, generalizing the complex genotype by phenotype interactions through manually constructed linear features. However, the identification of positive alleles vs. background can be addressed using deep learning approaches that have the capacity to learn complex nonlinear functions for the inputs. Machine learning (ML) is an artificial intelligence (AI) approach involving a range of algorithms to learn from input data sets and predict outcomes in other related samples. This paper describes a variety of techniques that include supervised and unsupervised ML algorithms to improve our understanding of nonlinear interactions from plant breeding data sets. Feature selection (FS) methods are combined with linear and nonlinear predictors and compared to traditional prediction methods used in plant breeding. Recent advances in ML allowed the construction of complex models that have the capacity to better differentiate between positive alleles and the genetic background. Using real plant breeding program data, we show that ML methods have the ability to outperform current approaches, increase prediction accuracies, decrease the computing time drastically, and improve the detection of important alleles involved in qualitative or quantitative traits.

Dissection of Quantitative Blackleg Resistance Reveals Novel Variants of Resistance Gene Rlm9 in Elite Brassica napus.

Blackleg is one of the major fungal diseases in oilseed rape/canola worldwide. Most commercial cultivars carry R gene-mediated qualitative resistances that confer a high level of race-specific protection against Leptosphaeria maculans, the causal fungus of blackleg disease. However, monogenic resistances of this kind can potentially be rapidly overcome by mutations in the pathogen's avirulence genes. To counteract pathogen adaptation in this evolutionary arms race, there is a tremendous demand for quantitative background resistance to enhance durability and efficacy of blackleg resistance in oilseed rape. In this study, we characterized genomic regions contributing to quantitative L. maculans resistance by genome-wide association studies in a multiparental mapping population derived from six parental elite varieties exhibiting quantitative resistance, which were all crossed to one common susceptible parental elite variety. Resistance was screened using a fungal isolate with no corresponding avirulence (AvrLm) to major R genes present in the parents of the mapping population. Genome-wide association studies revealed eight significantly associated quantitative trait loci (QTL) on chromosomes A07 and A09, with small effects explaining 3-6% of the phenotypic variance. Unexpectedly, the qualitative blackleg resistance gene Rlm9 was found to be located within a resistance-associated haploblock on chromosome A07. Furthermore, long-range sequence data spanning this haploblock revealed high levels of single-nucleotide and structural variants within the Rlm9 coding sequence among the parents of the mapping population. The results suggest that novel variants of Rlm9 could play a previously unknown role in expression of quantitative disease resistance in oilseed rape.

A novel deletion in FLOWERING LOCUS T modulates flowering time in winter oilseed rape.

KEY MESSAGE: A novel structural variant was discovered in the FLOWERING LOCUS T orthologue BnaFT.A02 by long-read sequencing. Nested association mapping in an elite winter oilseed rape population revealed that this 288 bp deletion associates with early flowering, putatively by modification of binding-sites for important flowering regulation genes. Perfect timing of flowering is crucial for optimal pollination and high seed yield. Extensive previous studies of flowering behavior in Brassica napus (canola, rapeseed) identified mutations in key flowering regulators which differentiate winter, semi-winter and spring ecotypes. However, because these are generally fixed in locally adapted genotypes, they have only limited relevance for fine adjustment of flowering time in elite cultivar gene pools. In crosses between ecotypes, the ecotype-specific major-effect mutations mask minor-effect loci of interest for breeding. Here, we investigated flowering time in a multiparental mapping population derived from seven elite winter oilseed rape cultivars which are fixed for major-effect mutations separating winter-type rapeseed from other ecotypes. Association mapping revealed eight genomic regions on chromosomes A02, C02 and C03 associating with fine modulation of flowering time. Long-read genomic resequencing of the seven parental lines identified seven structural variants coinciding with candidate genes for flowering time within chromosome regions associated with flowering time. Segregation patterns for these variants in the elite multiparental population and a diversity set of winter types using locus-specific assays revealed significant associations with flowering time for three deletions on chromosome A02. One of these was a previously undescribed 288 bp deletion within the second intron of FLOWERING LOCUS T on chromosome A02, emphasizing the advantage of long-read sequencing for detection of structural variants in this size range. Detailed analysis revealed the impact of this specific deletion on flowering-time modulation under extreme environments and varying day lengths in elite, winter-type oilseed rape.

Long-read sequencing reveals widespread intragenic structural variants in a recent allopolyploid crop plant.

Genome structural variation (SV) contributes strongly to trait variation in eukaryotic species and may have an even higher functional significance than single-nucleotide polymorphism (SNP). In recent years, there have been a number of studies associating large chromosomal scale SV ranging from hundreds of kilobases all the way up to a few megabases to key agronomic traits in plant genomes. However, there have been little or no efforts towards cataloguing small- (30-10 000 bp) to mid-scale (10 000-30 000 bp) SV and their impact on evolution and adaptation-related traits in plants. This might be attributed to complex and highly duplicated nature of plant genomes, which makes them difficult to assess using high-throughput genome screening methods. Here, we describe how long-read sequencing technologies can overcome this problem, revealing a surprisingly high level of widespread, small- to mid-scale SV in a major allopolyploid crop species, Brassica napus. We found that up to 10% of all genes were affected by small- to mid-scale SV events. Nearly half of these SV events ranged between 100 bp and 1000 bp, which makes them challenging to detect using short-read Illumina sequencing. Examples demonstrating the contribution of such SV towards eco-geographical adaptation and disease resistance in oilseed rape suggest that revisiting complex plant genomes using medium-coverage long-read sequencing might reveal unexpected levels of functional gene variation, with major implications for trait regulation and crop improvement.

Gene presence-absence variation associates with quantitative Verticillium longisporum disease resistance in Brassica napus.

Although copy number variation (CNV) and presence-absence variation (PAV) have been discovered in selected gene families in most crop species, the global prevalence of these polymorphisms in most complex genomes is still unclear and their influence on quantitatively inherited agronomic traits is still largely unknown. Here we analyze the association of gene PAV with resistance of oilseed rape (Brassica napus) against the important fungal pathogen Verticillium longisporum, as an example for a complex, quantitative disease resistance in the strongly rearranged genome of a recent allopolyploid crop species. Using Single Nucleotide absence Polymorphism (SNaP) markers to efficiently trace PAV in breeding populations, we significantly increased the resolution of loci influencing V. longisporum resistance in biparental and multi-parental mapping populations. Gene PAV, assayed by resequencing mapping parents, was observed in 23-51% of the genes within confidence intervals of quantitative trait loci (QTL) for V. longisporum resistance, and high-priority candidate genes identified within QTL were all affected by PAV. The results demonstrate the prominent role of gene PAV in determining agronomic traits, suggesting that this important class of polymorphism should be exploited more systematically in future plant breeding.

Endophytic bacterial communities of oilseed rape associate with genotype-specific resistance against Verticillium longisporum.

Associations of endophytic bacterial community composition of oilseed rape (Brassica napus L.) with quantitative resistance against the soil-borne fungal pathogen Verticillium longisporum was assessed by 16S rRNA gene amplicon sequencing in roots and hypocotyls of four plant lines with contrasting genetic composition in regard to quantitative resistance reactions. The plant compartment was found to be the dominating driving factor for the specificity of bacterial communities in healthy plants. Furthermore, V. longisporum infection triggered a stabilization of phylogenetic group abundance in replicated samples suggesting a host genotype-specific selection. Genotype-specific associations with bacterial phylogenetic group abundance were identified by comparison of plant genotype groups (resistant versus susceptible) and treatment groups (healthy versus V. longisporum-infected) allowing dissection into constitutive and induced directional association patterns. Relative abundance of Flavobacteria, Pseudomonas, Rhizobium and Cellvibrio was associated with resistance/susceptibility. Relative abundance of Flavobacteria and Cellvibrio was increased in resistant genotypes according to their known ecological functions. In contrast, a higher relative abundance of Pseudomonas and Rhizobium, which are known to harbor many species with antagonistic properties to fungal pathogens, was found to be associated with susceptibility, indicating that these groups do not play a major role in genetically controlled resistance of oilseed rape against V. longisporum.

Evaluation of Aroma Compounds in the Process of Wine Ageing with Oak Chips.

Many modern alcoholic beverages are subjected to ageing processes during which compounds extracted from wood contribute decisively to the overall beverage character. Wines represent a perfect example of beverage in which ageing is a crucial technological manufacturing step. During winemaking, producers accelerate chemical changes in wine composition by traditional and alternative methods, such as the use of oak wood barrels and/or oak wood chips. Our research aimed to investigate the overall volatile composition and sensory quality of red wines aged for two timeframes, namely, 1.5 and 3 months, and with two technological variants, i.e., American and French oak wood chips. Red grapes from the Feteasca neagra (Vitis vinifera) variety were harvested from a vineyard in the North-East region of Romania. Stir bar sorptive extraction and gas chromatography coupled with mass spectrometry (SBSE-GC-MS) was used to extract minor aromas present in wine samples. The results showed clear differences between wines treated with American and French oak chips. Furthermore, ageing for 3 months increased the concentration of cis-whiskey lactone and guaiacol in American oak-treated wine samples. For wines aged with French oak chips, we observed higher concentrations of furfural, 5-methylfurfural, 4-vinylguaiacol, and trans-whiskey lactone. The increased presence of chemical compounds in wine aged with French oak chips generated prominent smoky, licorice, and toasty aromas, whereas in wines aged with American oak chips, notes of vanilla, toasty, and cacao aromas were noticed. Moreover, red wines aged with American and French oak chips were discriminated by chemometric analysis, which confirmed the evolution of aroma compounds.

Connecting genome structural variation with complex traits in crop plants.

KEY MESSAGE: Structural genome variation is a major determinant of useful trait diversity. We describe how genome analysis methods are enabling discovery of trait-associated structural variants and their potential impact on breeding. As our understanding of complex crop genomes continues to grow, there is growing evidence that structural genome variation plays a major role in determining traits important for breeding and agriculture. Identifying the extent and impact of structural variants in crop genomes is becoming increasingly feasible with ongoing advances in the sophistication of genome sequencing technologies, particularly as it becomes easier to generate accurate long sequence reads on a genome-wide scale. In this article, we discuss the origins of structural genome variation in crops from ancient and recent genome duplication and polyploidization events and review high-throughput methods to assay such variants in crop populations in order to find associations with phenotypic traits. There is increasing evidence from such studies that gene presence-absence and copy number variation resulting from segmental chromosome exchanges may be at the heart of adaptive variation of crops to counter abiotic and biotic stress factors. We present examples from major crops that demonstrate the potential of pangenomic diversity as a key resource for future plant breeding for resilience and sustainability.

Genetic insights into underground responses to Fusarium graminearum infection in wheat.

The ongoing global intensification of wheat production will likely be accompanied by a rising pressure of Fusarium diseases. While utmost attention was given to Fusarium head blight (FHB) belowground plant infections of the pathogen have largely been ignored. The current knowledge about the impact of soil borne Fusarium infection on plant performance and the underlying genetic mechanisms for resistance remain very limited. Here, we present the first large-scale investigation of Fusarium root rot (FRR) resistance using a diverse panel of 215 international wheat lines. We obtained data for a total of 21 resistance-related traits, including large-scale Real-time PCR experiments to quantify fungal spread. Association mapping and subsequent haplotype analyses discovered a number of highly conserved genomic regions associated with resistance, and revealed a significant effect of allele stacking on the stembase discoloration. Resistance alleles were accumulated in European winter wheat germplasm, implying indirect prior selection for improved FRR resistance in elite breeding programs. Our results give first insights into the genetic basis of FRR resistance in wheat and demonstrate how molecular parameters can successfully be explored in genomic prediction. Ongoing work will help to further improve our understanding of the complex interactions of genetic factors influencing FRR resistance.

Finding invisible quantitative trait loci with missing data.

Evolutionary processes during plant polyploidization and speciation have led to extensive presence-absence variation (PAV) in crop genomes, and there is increasing evidence that PAV associates with important traits. Today, high-resolution genetic analysis in major crops frequently implements simple, cost-effective, high-throughput genotyping from single nucleotide polymorphism (SNP) hybridization arrays; however, these are normally not designed to distinguish PAV from failed SNP calls caused by hybridization artefacts. Here, we describe a strategy to recover valuable information from single nucleotide absence polymorphisms (SNaPs) by population-based quality filtering of SNP hybridization data to distinguish patterns associated with genuine deletions from those caused by technical failures. We reveal that including SNaPs in genetic analyses elucidate segregation of small to large-scale structural variants in nested association mapping populations of oilseed rape (Brassica napus), a recent polyploid crop with widespread structural variation. Including SNaP markers in genomewide association studies identified numerous quantitative trait loci, invisible using SNP markers alone, for resistance to two major fungal diseases of oilseed rape, Sclerotinia stem rot and blackleg disease. Our results indicate that PAV has a strong influence on quantitative disease resistance in B. napus and that SNaP analysis using cost-effective SNP array data can provide extensive added value from 'missing data'. This strategy might also be applicable for improving the precision of genetic mapping in many important crop species.