Genome-wide association of volatiles reveals candidate loci for blueberry flavor

Association mapping analysis (AMA) for morpho-agronomic traits and leaf aromatic compounds using SSR markers in three types of Perilla crop collected from South Korea

BACKGROUND

Perilla is a representative leafy vegetable in South Korea. As K-Food (Korean food) is in the spotlight around the world, there is also increasing interest in Western countries in Perilla crop, an annual plant belonging to the Lamiaceae family.

OBJECTIVE

To discover comprehensive information, including genetic and phylogenetic relationships among the 80 native Perilla accessions, using three types of data: simple sequence repeat (SSR) marker data, volatiles profile data, and morpho-agronomic data.

METHODS

This study conducted genotypic and phenotypic analyses on 80 Perilla accessions of three types (cultivated var. frutescens, weedy var. frutescens, weedy var. crispa) from South Korea. Five groups (G1-G5) of the 80 Perilla accessions of the three types were differentiated into two different clusters [genotype-based clustering (GTC) and phenotype-based clustering (PTC)] based on an aroma sensory phenotypic test.

RESULTS

A total of 314 alleles were confirmed using 55 Perilla SSR primer sets, and genetic variation in the 80 Perilla accessions was evaluated. Among the three statistical analysis methods, principal coordinate analysis (PCoA) and GTC using data of the 55 Perilla SSR markers revealed perfectly consistent results, whereas PTC produced a total of six clusters. The 10 Perilla SSR markers associated with and significantly correlated with both biochemical and morphological characteristics were selected.

CONCLUSIONS

These findings are expected to provide valuable information for developing global South Korean Perilla cultivars for further studies in Perilla crop breeding programs.

Genomic selection optimization in blueberry: Data-driven methods for marker and training population design

Genomic prediction is a modern approach that uses genome-wide markers to predict the genetic merit of unphenotyped individuals. With the potential to reduce the breeding cycles and increase the selection accuracy, this tool has been designed to rank genotypes and maximize genetic gains. Despite this importance, its practical implementation in breeding programs requires critical allocation of resources for its application in a predictive framework. In this study, we integrated genetic and data-driven methods to allocate resources for phenotyping and genotyping tailored to genomic prediction. To this end, we used a historical blueberry (Vaccinium corymbosun L.) breeding dataset containing more than 3000 individuals, genotyped using probe-based target sequencing and phenotyped for three fruit quality traits over several years. Our contribution in this study is threefold: (i) for the genotyping resource allocation, the use of genetic data-driven methods to select an optimal set of markers slightly improved prediction results for all the traits; (ii) for the long-term implication, we carried out a simulation study and emphasized that data-driven method results in a slight improvement in genetic gain over 30 cycles than random marker sampling; and (iii) for the phenotyping resource allocation, we compared different optimization algorithms to select training population, showing that it can be leveraged to increase predictive performances. Altogether, we provided a data-oriented decision-making approach for breeders by demonstrating that critical breeding decisions associated with resource allocation for genomic prediction can be tackled through a combination of statistics and genetic methods.

Genetic and epigenetic signatures for improved breeding of cultivated blueberry

Blueberry belongs to the Vaccinium genus and is a highly popular fruit crop with significant economic importance. It was not until the early twentieth century that they began to be domesticated through extensive interspecific hybridization. Here, we collected 220 Vaccinium accessions from various geographical locations, including 154 from the United States, 14 from China, eight from Australia, and 29 from Europe and other countries, comprising 164 Vaccinium corymbosum, 15 Vaccinium ashei, 10 lowbush blueberries, seven half-high blueberries, and others. We present the whole-genome variation map of 220 accessions and reconstructed the hundred-year molecular history of interspecific hybridization of blueberry. We focused on the two major blueberry subgroups, the northern highbush blueberry (NHB) and southern highbush blueberry (SHB) and identified candidate genes that contribute to their distinct traits in climate adaptability and fruit quality. Our analysis unveiled the role of gene introgression from Vaccinium darrowii and V. ashei into SHB in driving the differentiation between SHB and NHB, potentially facilitating SHB's adaptation to subtropical environments. Assisted by genome-wide association studies, our analysis suggested VcTBL44 as a pivotal gene regulator governing fruit firmness in SHB. Additionally, we conducted whole-genome bisulfite sequencing on nine NHB and 12 SHB cultivars, and characterized regions that are differentially methylated between the two subgroups. In particular, we discovered that the β-alanine metabolic pathway genes were enriched for DNA methylation changes. Our study provides high-quality genetic and epigenetic variation maps for blueberry, which offer valuable insights and resources for future blueberry breeding.

Metabolite-based genome-wide association studies enable the dissection of the genetic bases of flavonoids, betaine and spermidine in wolfberry (Lycium)

Wolfberry is a plant with medicinal and food values. However, its bioactive ingredients and the corresponding genetic bases have not been determined. Here, we de novo generated a chromosome-level genome assembly for wolfberry, yielding a genome sequence of ~1.77 Gb with contig N50 of 50.55 Mb and 39 224 predicted gene models. A variation map, using 307 re-sequenced accessions, was called based on this genome assembly. Furthermore, the fruit metabolome of these accessions was profiled using 563 annotated metabolites, which separated Lycium barbarum L. and non-L. barbarum L. The flavonoids, coumarins, alkaloids and nicotinic acid contents were higher in the former than in the latter. A metabolite-based genome-wide association study mapped 156 164 significant single nucleotide polymorphisms corresponding to 340 metabolites. This included 19 219 unique lead single nucleotide polymorphisms in 1517 significant association loci, of which three metabolites, flavonoids, betaine and spermidine, were highlighted. Two candidate genes, LbUGT (evm.TU.chr07.2692) and LbCHS (evm.TU.chr07.2738), with non-synonymous mutations, were associated with the flavonoids content. LbCHS is a structural gene that interacts with a nearby MYB transcription factor (evm.TU.chr07.2726) both in L. barbarum and L. ruthenicum. Thus, these three genes might be involved in the biosynthesis/metabolism of flavonoids. LbSSADH (evm.TU.chr09.627) was identified as possibly participating in betaine biosynthesis/metabolism. Four lycibarbarspermidines (E-G and O) were identified, and only the lycibarbarspermidines O content was higher in L. barbarum varieties than in non-L. barbarum varieties. The evm.TU.chr07.2680 gene associated with lycibarbarspermidines O was annotated as an acetyl-CoA-benzylalcohol acetyltransferase, suggesting that it is a candidate gene for spermidine biosynthesis. These results provide novel insights into the specific metabolite profile of non-L. barbarum L. and the genetic bases of flavonoids, betaine and spermidine biosynthesis/metabolism.

Genomic-assisted breeding for climate-smart coffee

Coffee is a universal beverage that drives a multi-industry market on a global basis. Today, the sustainability of coffee production is threatened by accelerated climate changes. In this work, we propose the implementation of genomic-assisted breeding for climate-smart coffee in Coffea canephora. This species is adapted to higher temperatures and is more resilient to biotic and abiotic stresses. After evaluating two populations, over multiple harvests, and under severe drought weather condition, we dissected the genetic architecture of yield, disease resistance, and quality-related traits. By integrating genome-wide association studies and diallel analyses, our contribution is four-fold: (i) we identified a set of molecular markers with major effects associated with disease resistance and post-harvest traits, while yield and plant architecture presented a polygenic background; (ii) we demonstrated the relevance of nonadditive gene actions and projected hybrid vigor when genotypes from different geographically botanical groups are crossed; (iii) we computed medium-to-large heritability values for most of the traits, representing potential for fast genetic progress; and (iv) we provided a first step toward implementing molecular breeding to accelerate improvements in C. canephora. Altogether, this work is a blueprint for how quantitative genetics and genomics can assist coffee breeding and support the supply chain in the face of the current global changes.

Sensory Perception and Consumer Acceptance of Carrot Cultivars Are Influenced by Their Metabolic Profiles for Volatile and Non-Volatile Organic Compounds

Sensory parameters as well as the volatile and non-volatile compound profiles of sixteen carrot cultivars were recorded to obtain insight into consumer preference decisions. The sensory test was carried out with a consumer panel of 88 untrained testers allowing a clear acceptance-based differentiation of the cultivars. Five individual sensory characters (sweetness, overall aroma, bitterness, astringency and off-flavor) supported this discrimination. Chemical analyses of volatile organic compounds, polyacetylenes, phenylpropanoids and sugars enabled us to correlate the influence of these ingredients on sensory perception. Higher concentrations of α-pinene, hexanal, styrene and acetophenone correlated with a better acceptance, as well as sweetness and overall aroma perception. In contrast, a low acceptance as well as a stronger perception of bitterness, astringency and off-flavor correlated with enhanced concentrations of camphene, bornylacetate, borneol, myristicine, falcarindiol, falcarindiol-3-acetate, laserin and epilaserin. The present study should support the development of new breeding strategies for carrot cultivars that better satisfy consumer demands.

Adapting enzymes to improve their functionality in plants: why and how

Synthetic biology creates new metabolic processes and improves existing ones using engineered or natural enzymes. These enzymes are often sourced from cells that differ from those in the target plant organ with respect to, e.g. redox potential, effector levels, or proteostasis machinery. Non-native enzymes may thus need to be adapted to work well in their new plant context ('plantized') even if their specificity and kinetics in vitro are adequate. Hence there are two distinct ways in which an enzyme destined for use in plants can require improvement: In catalytic properties such as substrate and product specificity, kcat, and KM; and in general compatibility with the milieu of cells that express the enzyme. Continuous directed evolution systems can deliver both types of improvement and are so far the most broadly effective way to deliver the second type. Accordingly, in this review we provide a short account of continuous evolution methods, emphasizing the yeast OrthoRep system because of its suitability for plant applications. We then cover the down-to-earth and increasingly urgent issues of which enzymes and enzyme properties can - or cannot - be improved in theory, and which in practice are the best to target for crop improvement, i.e. those that are realistically improvable and important enough to warrant deploying continuous directed evolution. We take horticultural crops as examples because of the opportunities they present and to sharpen the focus.

Fruit Quality and Metabolomic Analyses of Fresh Food Accessions Provide Insights into the Key Carbohydrate Metabolism in Blueberry

Blueberry is a nutrient-rich berry, and its taste and flavor directly determine the consumer preference. Until now, few studies have focused on the comparison of fresh food quality and the key metabolites in superior fresh-eating blueberry cultivars. Herein, fruit quality indicators of 10 highbush blueberry cultivars were evaluated using 'Bluerain' as the control. Appearance quality analysis of fruits showed that 'Brigitta' had a larger fruit size and 'Anna' was the smallest. 'Anna' fruits, followed by 'O'Neal', had the highest ratio of soluble solids to acidity because of their lowest titratable acidity content. Despite the high soluble sugar content, the antioxidants in 'Anna' fruits such as total flavonoids, anthocyanins and vitamin C were lowest among all cultivars, while 'Duke' seemed to have opposite patterns. Furthermore, a total of 553 and 557 metabolites were identified by non-targeted metabolomics liquid chromatography-tandem mass spectrometry (LC-MS/MS) in positive and negative ion mode, respectively. Particularly, the numbers of differentially accumulated metabolites (DAMs) were the most between the 'O'Neal' vs. 'Bluerain' group. The DAMs involved in the metabolic pathways, sesquiterpenoid and triterpenoid biosynthesis, monoterpenoid biosynthesis, galactose metabolism, starch and sucrose metabolism, may be mainly related to the synthesis of flavor and carbohydrate substances. Moreover, the expression patterns of genes involved in sugar metabolism were verified by quantitative real-time PCR (qRT-PCR) analysis in different cultivars. Therefore, the systematical comparison of the quality characteristics, metabolites and expression profiles of related genes in highbush blueberries with good flavor could provide some basis for further research on fresh fruit breeding of blueberries.

Plant genome resequencing and population genomics: Current status and future prospects

Advances in DNA sequencing technology have sparked a genomics revolution, driving breakthroughs in plant genetics and crop breeding. Recently, the focus has shifted from cataloging genetic diversity in plants to exploring their functional significance and delivering beneficial alleles for crop improvement. This transformation has been facilitated by the increasing adoption of whole-genome resequencing. In this review, we summarize the current progress of population-based genome resequencing studies and how these studies affect crop breeding. A total of 187 land plants from 163 countries have been resequenced, comprising 54 413 accessions. As part of resequencing efforts 367 traits have been surveyed and 86 genome-wide association studies have been conducted. Economically important crops, particularly cereals, vegetables, and legumes, have dominated the resequencing efforts, leaving a gap in 49 orders, including Lycopodiales, Liliales, Acorales, Austrobaileyales, and Commelinales. The resequenced germplasm is distributed across diverse geographic locations, providing a global perspective on plant genomics. We highlight genes that have been selected during domestication, or associated with agronomic traits, and form a repository of candidate genes for future research and application. Despite the opportunities for cross-species comparative genomics, many population genomic datasets are not accessible, impeding secondary analyses. We call for a more open and collaborative approach to population genomics that promotes data sharing and encourages contribution-based credit policy. The number of plant genome resequencing studies will continue to rise with the decreasing DNA sequencing costs, coupled with advances in analysis and computational technologies. This expansion, in terms of both scale and quality, holds promise for deeper insights into plant trait genetics and breeding design.

Expression of terpene synthase-related genes in parents and offspring of Flammulina filiformis based on differences in volatile aroma components

Flammulina filiformis (F. filiformis) is one of the four major edible types of fungus in the world and has been cultivated in China since 800 CE (Anno Domini). Some of the most essential criteria for evaluating the quality of F. filiformis are the types and contents of volatile components present. A focused study on screened the terpene synthase genes involved in the aroma of offspring and compared key terpenoids between parents and offspring, which is helpful for the development and application of F. filiformis. Firstly, the volatile aroma components of parent and offspring F. filiformis were extracted using two pretreatment procedures, and then were semi-quantified by an internal standard. Forty-eight, fifty-eight, and forty-eight volatile compounds were identified in parents and offspring of three different strains, and 15, 22, and 12 aroma compounds (OAVs ≥ 1) were further screened out via calculating their odor activity values (OAVs). Terpenoids, in particular linalool and eucalyptol, which contribute more to the aroma, result in the unique green and grassy aroma of the offspring. At last, the F. filiformis genome was resequenced and the coordinates of genes related to terpenoid synthase were determined. The results showed that Scaffolds, including scaffold3.t874 and scaffold9.t157 were connected to terpenoid synthesis of offspring (No. 61523). The variant genes g269 and g61 were related to terpenoid synthase sequences. This study provides a theoretical foundation for the cultivation of more diverse and unique varieties of F. filiformis.

Genome-wide association identifies key loci controlling blackberry postharvest quality

Introduction

Blackberry (Rubus subgenus Rubus) is a soft-fruited specialty crop that often suffers economic losses due to degradation in the shipping process. During transportation, fresh-market blackberries commonly leak, decay, deform, or become discolored through a disorder known as red drupelet reversion (RDR). Over the past 50 years, breeding programs have achieved better fruit firmness and postharvest quality through traditional selection methods, but the underlying genetic variation is poorly understood.

Methods

We conducted a genome-wide association of fruit firmness and RDR measured in 300 tetraploid fresh-market blackberry genotypes from 2019-2021 with 65,995 SNPs concentrated in genic regions of the R. argutus reference genome.

Results

Fruit firmness and RDR had entry-mean broad sense heritabilities of 68% and 34%, respectively. Three variants on homologs of polygalacturonase (PG), pectin methylesterase (PME), and glucan endo-1,3-β-glucosidase explained 27% of variance in fruit firmness and were located on chromosomes Ra06, Ra01, and Ra02, respectively. Another PG homolog variant on chromosome Ra02 explained 8% of variance in RDR, but it was in strong linkage disequilibrium with 212 other RDR-associated SNPs across a 23 Mb region. A large cluster of six PME and PME inhibitor homologs was located near the fruit firmness quantitative trait locus (QTL) identified on Ra01. RDR and fruit firmness shared a significant negative correlation (r = -0.28) and overlapping QTL regions on Ra02 in this study.

Discussion

Our work demonstrates the complex nature of postharvest quality traits in blackberry, which are likely controlled by many small-effect QTLs. This study is the first large-scale effort to map the genetic control of quantitative traits in blackberry and provides a strong framework for future GWAS. Phenotypic and genotypic datasets may be used to train genomic selection models that target the improvement of postharvest quality.

Aroma Components in Horticultural Crops: Chemical Diversity and Usage of Metabolic Engineering for Industrial Applications

Plants produce an incredible variety of volatile organic compounds (VOCs) that assist the interactions with their environment, such as attracting pollinating insects and seed dispersers and defense against herbivores, pathogens, and parasites. Furthermore, VOCs have a significant economic impact on crop quality, as well as the beverage, food, perfume, cosmetics and pharmaceuticals industries. These VOCs are mainly classified as terpenoids, benzenoids/phenylpropanes, and fatty acid derivates. Fruits and vegetables are rich in minerals, vitamins, antioxidants, and dietary fiber, while aroma compounds play a major role in flavor and quality management of these horticultural commodities. Subtle shifts in aroma compounds can dramatically alter the flavor and texture of fruits and vegetables, altering their consumer appeal. Rapid innovations in -omics techniques have led to the isolation of genes encoding enzymes involved in the biosynthesis of several volatiles, which has aided to our comprehension of the regulatory molecular pathways involved in VOC production. The present review focuses on the significance of aroma volatiles to the flavor and aroma profile of horticultural crops and addresses the industrial applications of plant-derived volatile terpenoids, particularly in food and beverages, pharmaceuticals, cosmetics, and biofuel industries. Additionally, the methodological constraints and complexities that limit the transition from gene selection to host organisms and from laboratories to practical implementation are discussed, along with metabolic engineering's potential for enhancing terpenoids volatile production at the industrial level.

Multi-omics integration to explore the molecular insight into the volatile organic compounds in watermelon

A range of volatile organic compounds played an important role in the formation of watermelon fruit aroma, while due to the low content and difficulty in detection, it is often neglected in watermelon breeding programs, resulting in a decline in fruit flavor. VOCs in the flesh of 194 watermelon accessions and seven cultivars at four developmental stages were determined by SPME-GC-MS. Ten metabolites with significant differences in the natural population and positive accumulation during fruit development are considered to be the key metabolite related to watermelon fruit aroma. And the link between metabolite and, flesh color and sugar content by correlation analysis was established. The results of the genome-wide association study showed that (5E)-6,10-dimethylundeca-5,9-dien-2-one, and 1-(4-methylphenyl) ethanone were colocalized with watermelon flesh color on chromosome 4, which may be regulated by LCYB and CCD. (E)-4-(2,6,6-trimethylcyclohexen-1-yl)but-3-en-2-one is the VOC produced by the cleavage of carotenoids, which has a positive correlation with the sugar content of the fruit, and the candidate gene Cla97C05G092490 on chromosome 5 may interact with PSY to influence the accumulation of this metabolite. In addition, Cla97C02G049790 (enol reductase), Cla97C03G051490 (omega-3 fatty acid desaturase gene), LOX, and ADH may play important roles in the synthesis of fatty acids and their derived VOCs. Taken together, our findings provide molecular insights into the accumulation and natural variation of VOCs in watermelon, and give data support for breeding watermelon cultivars with better flavor.

A multi-omics framework reveals strawberry flavor genes and their regulatory elements

Flavor is essential to consumer preference of foods and is an increasing focus of plant breeding programs. In fruit crops, identifying genes underlying volatile organic compounds has great promise to accelerate flavor improvement, but polyploidy and heterozygosity in many species have slowed progress. Here we use octoploid cultivated strawberry to demonstrate how genomic heterozygosity, transcriptomic intricacy and fruit metabolomic diversity can be treated as strengths and leveraged to uncover fruit flavor genes and their regulatory elements. Multi-omics datasets were generated including an expression quantitative trait loci map with 196 diverse breeding lines, haplotype-phased genomes of a highly-flavored breeding selection, a genome-wide structural variant map using five haplotypes, and volatile genome-wide association study (GWAS) with > 300 individuals. Overlaying regulatory elements, structural variants and GWAS-linked allele-specific expression of numerous genes to variation in volatile compounds important to flavor. In one example, the functional role of anthranilate synthase alpha subunit 1 in methyl anthranilate biosynthesis was supported via fruit transient gene expression assays. These results demonstrate a framework for flavor gene discovery in fruit crops and a pathway to molecular breeding of cultivars with complex and desirable flavor.

An Exploration of Pepino (Solanum muricatum) Flavor Compounds Using Machine Learning Combined with Metabolomics and Sensory Evaluation

Flavor is one of the most important characteristics that directly determines the popularity of a food. Moreover, the flavor of fruits is determined by the interaction of multiple metabolic components. Pepino, an emerging horticultural crop, is popular for its unique melon-like flavor. We analyzed metabolomics data from three different pepino growing regions in Haidong, Wuwei, and Jiuquan and counted the status of sweetness, acidity, flavor, and overall liking ratings of pepino fruit in these three regions by sensory panels. The metabolomics and flavor ratings were also integrated and analyzed using statistical and machine learning models, which in turn predicted the sensory panel ratings of consumers based on the chemical composition of the fruit. The results showed that pepino fruit produced in the Jiuquan region received the highest ratings in sweetness, flavor intensity, and liking, and the results with the highest contribution based on sensory evaluation showed that nucleotides and derivatives, phenolic acids, amino acids and derivatives, saccharides, and alcohols were rated in sweetness (74.40%), acidity (51.57%), flavor (56.41%), and likability (33.73%) dominated. We employed 14 machine learning strategies trained on the discovery samples to accurately predict the outcome of sweetness, sourness, flavor, and liking in the replication samples. The Radial Sigma SVM model predicted with better accuracy than the other machine learning models. Then we used the machine learning models to determine which metabolites influenced both pepino flavor and consumer preference. A total of 27 metabolites most important for pepino flavor attributes to distinguish pepino originating from three regions were screened. Substances such as N-acetylhistamine, arginine, and caffeic acid can enhance pepino‘s flavor intensity, and metabolites such as glycerol 3-phosphate, aconitic acid, and sucrose all acted as important variables in explaining the liking preference. While glycolic acid and orthophosphate inhibit sweetness and enhance sourness, sucrose has the opposite effect. Machine learning can identify the types of metabolites that influence fruit flavor by linking metabolomics of fruit with sensory evaluation among consumers, which conduces breeders to incorporate fruit flavor as a trait earlier in the breeding process, making it possible to select and release fruit with more flavor.

High-density linkage map construction in an autotetraploid blueberry population and detection of quantitative trait loci for anthocyanin content

Highbush blueberry (Vaccinium corymbosum, 2n = 4x = 48) is the most cultivated type of blueberry, both in New Zealand and overseas. Its perceived nutritional value is conferred by phytonutrients, particularly anthocyanins. Identifying the genetic mechanisms that control the biosynthesis of these metabolites would enable faster development of cultivars with improved fruit qualities. Here, we used recently released tools for genetic mapping in autotetraploids to build a high-density linkage map in highbush blueberry and to detect quantitative trait loci (QTLs) for fruit anthocyanin content. Genotyping was performed by target sequencing, with ∼18,000 single nucleotide polymorphism (SNP) markers being mapped into 12 phased linkage groups (LGs). Fruits were harvested when ripe for two seasons and analyzed with high-performance liquid chromatography-mass spectrometry (HPLC-MS): 25 different anthocyanin compounds were identified and quantified. Two major QTLs that were stable across years were discovered, one on LG2 and one on LG4, and the underlying candidate genes were identified. Interestingly, the presence of anthocyanins containing acylated sugars appeared to be under strong genetic control. Information gained in this study will enable the design of molecular markers for marker-assisted selection and will help build a better understanding of the genetic control of anthocyanin biosynthesis in this crop.

Towards smart and sustainable development of modern berry cultivars in Europe

Fresh berries are a popular and important component of the human diet. The demand for high-quality berries and sustainable production methods is increasing globally, challenging breeders to develop modern berry cultivars that fulfill all desired characteristics. Since 1994, research projects have characterized genetic resources, developed modern tools for high-throughput screening, and published data in publicly available repositories. However, the key findings of different disciplines are rarely linked together, and only a limited range of traits and genotypes has been investigated. The Horizon2020 project BreedingValue will address these challenges by studying a broader panel of strawberry, raspberry and blueberry genotypes in detail, in order to recover the lost genetic diversity that has limited the aroma and flavor intensity of recent cultivars. We will combine metabolic analysis with sensory panel tests and surveys to identify the key components of taste, flavor and aroma in berries across Europe, leading to a high-resolution map of quality requirements for future berry cultivars. Traits linked to berry yields and the effect of environmental stress will be investigated using modern image analysis methods and modeling. We will also use genetic analysis to determine the genetic basis of complex traits for the development and optimization of modern breeding technologies, such as molecular marker arrays, genomic selection and genome-wide association studies. Finally, the results, raw data and metadata will be made publicly available on the open platform Germinate in order to meet FAIR data principles and provide the basis for sustainable research in the future.

Fatty acid metabolism-related genes are associated with flavor-presenting aldehydes in Chinese local chicken

Aldehydes are primary volatile organic compounds (VOCs) in local Chinese chicken meat and contribute green grass, fatty, citrus, and bitter almond aromas to chicken meat. To understand the genetic basis of these aldehyde VOC aromas, we used approximately 500 Chinese Jingxing Yellow (JXY) chickens to conduct genome-wide association studies (GWAS) on the flavor traits with the data of single nucleotide polymorphisms (SNPs) and insertions and deletions (INDELs). In total, 501 association variants (253 SNPs and 248 INDELs) were found to be suggestively (SNPs: p-value < 2.77e-06 and INDELs: p-value < 3.78e-05) associated with total aldehydes (the sum of nine aldehydes), hexanal, heptanal, benzaldehyde, (E,E)-2,4-nonadienal, octanal, (E)-2-decenal, nonanal, decanal, and octadecanal. Of them, six SNPs and 23 INDELs reached a genome-wide significance level (SNPs: p-value < 1.38e-07 and INDELs: p-value < 1.89e-06). Potential candidate aldehyde genes were functionally annotated for lipid metabolism, especially fatty acid-related pathways and phospholipid-related gene ontology (GO) terms. Moreover, the GWAS analysis of total aldehydes, hexanal, and nonanal generated the most significant signals, and phenotypic content differed between different genotypes at candidate gene-related loci. For total aldehydes and hexanal traits, candidate genes were annotated based on the significant and suggestive variants on chromosomes 3 and 8 with highly polymorphic linkage blocks. The following candidate genes were also identified: GALM, MAP4K3, GPCPD1, RPS6KA2, CRLS1, ASAP1, TRMT6, SDC1, PUM2, ALDH9A1, MGST3, GMEB1, MECR, LDLRAP1, GPAM and ACSL5. We also found that polyunsaturated fatty acids (PUFAs) (C18:2n6c linoleic acid and C18:3n3 linolenic acid) were significantly correlated with total aldehydes and hexanal contents. PUFAs are important aldehyde precursors, and consistently, our results suggested that candidate genes involved in fatty acid pathways and phospholipid GO terms were identified in association loci. This work provides an understanding of the genetic basis of aldehyde formation, which is a key flavor-forming compound.

Biochemical, Sensory, and Molecular Evaluation of Flavour and Consumer Acceptability in Australian Papaya (Carica papaya L.) Varieties

Inconsistency in flavour is one of the major challenges to the Australian papaya industry. However, objectively measurable standards of the compound profiles that provide preferable taste and aroma, together with consumer acceptability, have not been set. In this study, three red-flesh papayas (i.e., ‘RB1’, ‘RB4’, and ‘Skybury’) and two yellow-flesh papayas (i.e., ‘1B’ and ‘H13’) were presented to a trained sensory panel and a consumer panel to assess sensory profiles and liking. The papaya samples were also examined for sugar components, total soluble solids, and 14 selected volatile compounds. Additionally, the expression patterns of 10 genes related to sweetness and volatile metabolism were assessed. In general, red papaya varieties had higher sugar content and tasted sweeter than yellow varieties, while yellow varieties had higher concentrations of citrus floral aroma volatiles and higher aroma intensity. Higher concentrations of glucose, linalool oxide, and terpinolene were significantly associated with decreased consumer liking. Significant differences were observed in the expression profiles of all the genes assessed among the selected papaya varieties. Of these, cpGPT2 and cpBGLU31 were positively correlated to glucose production and were expressed significantly higher in ‘1B’ than in ‘RB1’ or ‘Skybury’. These findings will assist in the strategic selective breeding for papaya to better match consumer and, hence, market demand.

There and back again; historical perspective and future directions for Vaccinium breeding and research studies

The genus Vaccinium L. (Ericaceae) contains a wide diversity of culturally and economically important berry crop species. Consumer demand and scientific research in blueberry (Vaccinium spp.) and cranberry (Vaccinium macrocarpon) have increased worldwide over the crops' relatively short domestication history (~100 years). Other species, including bilberry (Vaccinium myrtillus), lingonberry (Vaccinium vitis-idaea), and ohelo berry (Vaccinium reticulatum) are largely still harvested from the wild but with crop improvement efforts underway. Here, we present a review article on these Vaccinium berry crops on topics that span taxonomy to genetics and genomics to breeding. We highlight the accomplishments made thus far for each of these crops, along their journey from the wild, and propose research areas and questions that will require investments by the community over the coming decades to guide future crop improvement efforts. New tools and resources are needed to underpin the development of superior cultivars that are not only more resilient to various environmental stresses and higher yielding, but also produce fruit that continue to meet a variety of consumer preferences, including fruit quality and health related traits.

Applications of Genomic Tools in Plant Breeding: Crop Biofortification

Crop breeding has mainly been focused on increasing productivity, either directly or by decreasing the losses caused by biotic and abiotic stresses (that is, incorporating resistance to diseases and enhancing tolerance to adverse conditions, respectively). Quite the opposite, little attention has been paid to improve the nutritional value of crops. It has not been until recently that crop biofortification has become an objective within breeding programs, through either conventional methods or genetic engineering. There are many steps along this long path, from the initial evaluation of germplasm for the content of nutrients and health-promoting compounds to the development of biofortified varieties, with the available and future genomic tools assisting scientists and breeders in reaching their objectives as well as speeding up the process. This review offers a compendium of the genomic technologies used to explore and create biodiversity, to associate the traits of interest to the genome, and to transfer the genomic regions responsible for the desirable characteristics into potential new varieties. Finally, a glimpse of future perspectives and challenges in this emerging area is offered by taking the present scenario and the slow progress of the regulatory framework as the starting point.

Metabolomic selection for enhanced fruit flavor

Consumers often regard heirloom fruit varieties grown in the garden as more flavorful than commercial varieties purchased at the grocery store. While plant breeders have historically focused on improving producer-orientated traits such as yield, consumer-oriented traits such as flavor have regularly been neglected. This is, in part, due to the difficulty associated with measuring the sensory perceptions of flavor. Here, we combine fruit chemical and consumer sensory panel information to train machine learning models that can predict how flavorful a fruit will be from its chemistry. By increasing the throughput of flavor evaluations, these models will help plant breeders to integrate flavor earlier in the breeding pipeline and aid in the design of varieties with exceptional flavor profiles.

Although they are staple foods in cuisines globally, many commercial fruit varieties have become progressively less flavorful over time. Due to the cost and difficulty associated with flavor phenotyping, breeding programs have long been challenged in selecting for this complex trait. To address this issue, we leveraged targeted metabolomics of diverse tomato and blueberry accessions and their corresponding consumer panel ratings to create statistical and machine learning models that can predict sensory perceptions of fruit flavor. Using these models, a breeding program can assess flavor ratings for a large number of genotypes, previously limited by the low throughput of consumer sensory panels. The ability to predict consumer ratings of liking, sweet, sour, umami, and flavor intensity was evaluated by a 10-fold cross-validation, and the accuracies of 18 different models were assessed. The prediction accuracies were high for most attributes and ranged from 0.87 for sourness intensity in blueberry using XGBoost to 0.46 for overall liking in tomato using linear regression. Further, the best-performing models were used to infer the flavor compounds (sugars, acids, and volatiles) that contribute most to each flavor attribute. We found that the variance decomposition of overall liking score estimates that 42% and 56% of the variance was explained by volatile organic compounds in tomato and blueberry, respectively. We expect that these models will enable an earlier incorporation of flavor as breeding targets and encourage selection and release of more flavorful fruit varieties.

A High-Density Genetic Map Enables Genome Synteny and QTL Mapping of Vegetative Growth and Leaf Traits in Gardenia

The gardenia is a traditional medicinal horticultural plant in China, but its molecular genetic research has been largely hysteretic. Here, we constructed an F₁ population with 200 true hybrid individuals. Using the genotyping-by-sequencing method, a high-density sex-average genetic map was generated that contained 4,249 SNPs with a total length of 1956.28 cM and an average genetic distance of 0.46 cM. We developed 17 SNP-based Kompetitive Allele-Specific PCR markers and found that 15 SNPs were successfully genotyped, of which 13 single-nucleotide polymorphism genotypings of 96 F₁ individuals showed genotypes consistent with GBS-mined genotypes. A genomic collinearity analysis between gardenia and the Rubiaceae species Coffea arabica, Coffea canephora and Ophiorrhiza pumila showed the relativity strong conservation of LG11 with NC_039,919.1, HG974438.1 and Bliw01000011.1, respectively. Lastly, a quantitative trait loci analysis at three phenotyping time points (2019, 2020, and 2021) yielded 18 QTLs for growth-related traits and 31 QTLs for leaf-related traits, of which qBSBN7-1, qCD8 and qLNP2-1 could be repeatably detected. Five QTL regions (qCD8 and qSBD8, qBSBN7 and qSI7, qCD4-1 and qLLLS4, qLNP10 and qSLWS10-2, qSBD10 and qLLLS10) with potential pleiotropic effects were also observed. This study provides novel insight into molecular genetic research and could be helpful for further gene cloning and marker-assisted selection for early growth and development traits in the gardenia.

A Semi-Automated SNP-Based Approach for Contaminant Identification in Biparental Polyploid Populations of Tropical Forage Grasses

Artificial hybridization plays a fundamental role in plant breeding programs since it generates new genotypic combinations that can result in desirable phenotypes. Depending on the species and mode of reproduction, controlled crosses may be challenging, and contaminating individuals can be introduced accidentally. In this context, the identification of such contaminants is important to avoid compromising further selection cycles, as well as genetic and genomic studies. The main objective of this work was to propose an automated multivariate methodology for the detection and classification of putative contaminants, including apomictic clones (ACs), self-fertilized individuals, half-siblings (HSs), and full contaminants (FCs), in biparental polyploid progenies of tropical forage grasses. We established a pipeline to identify contaminants in genotyping-by-sequencing (GBS) data encoded as allele dosages of single nucleotide polymorphism (SNP) markers by integrating principal component analysis (PCA), genotypic analysis (GA) measures based on Mendelian segregation, and clustering analysis (CA). The combination of these methods allowed for the correct identification of all contaminants in all simulated progenies and the detection of putative contaminants in three real progenies of tropical forage grasses, providing an easy and promising methodology for the identification of contaminants in biparental progenies of tetraploid and hexaploid species. The proposed pipeline was made available through the polyCID Shiny app and can be easily coupled with traditional genetic approaches, such as linkage map construction, thereby increasing the efficiency of breeding programs.

Exploring Genotype-by-Environment Interactions of Chemical Composition of Raspberry by Using a Metabolomics Approach

Promoting the consumption of fruits is a key objective of nutrition policy campaigns due to their associated health benefits. Raspberries are well appreciated for their remarkable flavor and nutritional value attributable to their antioxidant properties. Consequently, one of the objectives of present-day raspberry breeding programs is to improve the fruit’s sensory and nutritive characteristics. However, developing new genotypes with enhanced quality traits is a complex task due to the intricate impacts genetic and environmental factors have on these attributes, and the difficulty to phenotype them. We used a multi-platform metabolomic approach to compare flavor- and nutritional-related metabolite profiles of four raspberry cultivars (‘Glen Ample’, ‘Schönemann’, ‘Tulameen’ and ‘Veten’) grown in different European climates. Although the cultivars appear to be better adapted to high latitudes, for their content in soluble solids and acidity, multivariate statistical analyses allowed us to underscore important genotypic differences based on the profiles of important metabolites. ‘Schönemann’ and ‘Veten’ were characterized by high levels of anthocyanins and ellagitannins, respectively, ‘Tulameen’ by its acidity, and ‘Glen Ample’ for its content of sucrose and β-ionone, two main flavor contributors. Our results confirmed the value of metabolomic-driven approaches, which may foster the development of cultivars with enhanced health properties and flavor.

Exploring the genic resources underlying metabolites through mGWAS and mQTL in wheat: From large-scale gene identification and pathway elucidation to crop improvement

Common wheat (Triticum aestivum L.) is a leading cereal crop, but has lagged behind with respect to the interpretation of the molecular mechanisms of phenotypes compared with other major cereal crops such as rice and maize. The recently available genome sequence of wheat affords the pre-requisite information for efficiently exploiting the potential molecular resources for decoding the genetic architecture of complex traits and identifying valuable breeding targets. Meanwhile, the successful application of metabolomics as an emergent large-scale profiling methodology in several species has demonstrated this approach to be accessible for reaching the above goals. One such productive avenue is combining metabolomics approaches with genetic designs. However, this trial is not as widespread as that for sequencing technologies, especially when the acquisition, understanding, and application of metabolic approaches in wheat populations remain more difficult and even arguably underutilized. In this review, we briefly introduce the techniques used in the acquisition of metabolomics data and their utility in large-scale identification of functional candidate genes. Considerable progress has been made in delivering improved varieties, suggesting that the inclusion of information concerning these metabolites and genes and metabolic pathways enables a more explicit understanding of phenotypic traits and, as such, this procedure could serve as an -omics-informed roadmap for executing similar improvement strategies in wheat and other species.

Combining biotechnology and evolution for understanding the mechanisms of pollinator attraction

Many flowering plants rely on pollinators for their reproductive success. Plant-pollinator interactions usually depend on a complex combination of traits based on a fine-tuned biosynthetic machinery, with many structural and regulatory genes involved. Yet, the physiological mechanisms in plants are the product of evolutionary processes. While evolution has been modifying flowers through millions of years, it is also a rapid process that can change plant traits within few generations. Here we discuss both mechanistic and evolutionary aspects of pollinator attraction. We also propose how latest advances in biotechnology and evolutionary studies, and their combination, will improve the elucidation of molecular mechanisms and evolutionary dynamics of pollinator attraction in changing environments.

Genomic Selection in an Outcrossing Autotetraploid Fruit Crop: Lessons From Blueberry Breeding

Blueberry (Vaccinium corymbosum and hybrids) is a specialty crop with expanding production and consumption worldwide. The blueberry breeding program at the University of Florida (UF) has greatly contributed to expanding production areas by developing low-chilling cultivars better adapted to subtropical and Mediterranean climates of the globe. The breeding program has historically focused on recurrent phenotypic selection. As an autopolyploid, outcrossing, perennial, long juvenile phase crop, blueberry breeding cycles are costly and time consuming, which results in low genetic gains per unit of time. Motivated by applying molecular markers for a more accurate selection in the early stages of breeding, we performed pioneering genomic selection studies and optimization for its implementation in the blueberry breeding program. We have also addressed some complexities of sequence-based genotyping and model parametrization for an autopolyploid crop, providing empirical contributions that can be extended to other polyploid species. We herein revisited some of our previous genomic selection studies and showed for the first time its application in an independent validation set. In this paper, our contribution is three-fold: (i) summarize previous results on the relevance of model parametrizations, such as diploid or polyploid methods, and inclusion of dominance effects; (ii) assess the importance of sequence depth of coverage and genotype dosage calling steps; (iii) demonstrate the real impact of genomic selection on leveraging breeding decisions by using an independent validation set. Altogether, we propose a strategy for using genomic selection in blueberry, with the potential to be applied to other polyploid species of a similar background.

Understanding Omics Driven Plant Improvement and de novo Crop Domestication: Some Examples

In the current era, one of biggest challenges is to shorten the breeding cycle for rapid generation of a new crop variety having high yield capacity, disease resistance, high nutrient content, etc. Advances in the "-omics" technology have revolutionized the discovery of genes and bio-molecules with remarkable precision, resulting in significant development of plant-focused metabolic databases and resources. Metabolomics has been widely used in several model plants and crop species to examine metabolic drift and changes in metabolic composition during various developmental stages and in response to stimuli. Over the last few decades, these efforts have resulted in a significantly improved understanding of the metabolic pathways of plants through identification of several unknown intermediates. This has assisted in developing several new metabolically engineered important crops with desirable agronomic traits, and has facilitated the de novo domestication of new crops for sustainable agriculture and food security. In this review, we discuss how "omics" technologies, particularly metabolomics, has enhanced our understanding of important traits and allowed speedy domestication of novel crop plants.

Strawberry sweetness and consumer preference are enhanced by specific volatile compounds

Breeding crops for improved flavor is challenging due to the high cost of sensory evaluation and the difficulty of connecting sensory experience to chemical composition. The main goal of this study was to identify the chemical drivers of sweetness and consumer liking for fresh strawberries (Fragaria × ananassa). Fruit of 148 strawberry samples from cultivars and breeding selections were grown and harvested over seven years and were subjected to both sensory and chemical analyses. Each panel consisted of at least 100 consumers, resulting in more than 15,000 sensory data points per descriptor. Three sugars, two acids and 113 volatile compounds were quantified. Consumer liking was highly associated with sweetness intensity, texture liking, and flavor intensity, but not sourness intensity. Partial least square analyses revealed 20 volatile compounds that increased sweetness perception independently of sugars; 18 volatiles that increased liking independently of sugars; and 15 volatile compounds that had positive effects on both. Machine learning-based predictive models including sugars, acids, and volatiles explained at least 25% more variation in sweetness and liking than models accounting for sugars and acids only. Volatile compounds such as γ-dodecalactone; 5-hepten-2-one, 6-methyl; and multiple medium-chain fatty acid esters may serve as targets for breeding or quality control attributes for strawberry products. A genetic association study identified two loci controlling ester production, both on linkage group 6 A. Co-segregating makers in these regions can be used for increasing multiple esters simultaneously. This study demonstrates a paradigm for improvement of fruit sweetness and flavor in which consumers drive the identification of the most important chemical targets, which in turn drives the discovery of genetic targets for marker-assisted breeding.

Pairwise linkage disequilibrium estimation for polyploids

Many tasks in statistical genetics involve pairwise estimation of linkage disequilibrium (LD). The study of LD in diploids is mature. However, in polyploids, the field lacks a comprehensive characterization of LD. Polyploids also exhibit greater levels of genotype uncertainty than diploids, yet no methods currently exist to estimate LD in polyploids in the presence of such genotype uncertainty. Furthermore, most LD estimation methods do not quantify the level of uncertainty in their LD estimates. Our study contains three major contributions. (i) We characterize haplotypic and composite measures of LD in polyploids. These composite measures of LD turn out to be functions of common statistical measures of association. (ii) We derive procedures to estimate haplotypic and composite LD in polyploids in the presence of genotype uncertainty. We do this by estimating LD directly from genotype likelihoods, which may be obtained from many genotyping platforms. (iii) We derive standard errors of all LD estimators that we discuss. We validate our methods on both real and simulated data. Our methods are implemented in the R package ldsep, available on the Comprehensive R Archive Network https://cran.r-project.org/package=ldsep.

High-Density Linkage Map Construction and QTL Identification in a Diploid Blueberry Mapping Population

Genotyping by sequencing approaches have been widely applied in major crops and are now being used in horticultural crops like berries and fruit trees. As the original and largest producer of cultivated blueberry, the United States maintains the most diverse blueberry germplasm resources comprised of many species of different ploidy levels. We previously constructed an interspecific mapping population of diploid blueberry by crossing the parent F₁#10 (Vaccinium darrowii Fla4B × diploid V. corymbosum W85-20) with the parent W85-23 (diploid V. corymbosum). Employing the Capture-Seq technology developed by RAPiD Genomics, with an emphasis on probes designed in predicted gene regions, 117 F₁ progeny, the two parents, and two grandparents of this population were sequenced, yielding 131.7 Gbp clean sequenced reads. A total of 160,535 single nucleotide polymorphisms (SNPs), referenced to 4,522 blueberry genome sequence scaffolds, were identified and subjected to a parent-dependent sliding window approach to further genotype the population. Recombination breakpoints were determined and marker bins were deduced to construct a high density linkage map. Twelve blueberry linkage groups (LGs) consisting of 17,486 SNP markers were obtained, spanning a total genetic distance of 1,539.4 cM. Among 18 horticultural traits phenotyped in this population, quantitative trait loci (QTLs) that were significant over at least 2 years were identified for chilling requirement, cold hardiness, and fruit quality traits of color, scar size, and firmness. Interestingly, in 1 year, a QTL associated with timing of early bloom, full bloom, petal fall, and early green fruit was identified in the same region harboring the major QTL for chilling requirement. In summary, we report here the first high density bin map of a diploid blueberry mapping population and the identification of several horticulturally important QTLs.

Can gene editing reduce postharvest waste and loss of fruit, vegetables, and ornamentals?

Postharvest waste and loss of horticultural crops exacerbates the agricultural problems facing humankind and will continue to do so in the next decade. Fruits and vegetables provide us with a vast spectrum of healthful nutrients, and along with ornamentals, enrich our lives with a wide array of pleasant sensory experiences. These commodities are, however, highly perishable. Approximately 33% of the produce that is harvested is never consumed since these products naturally have a short shelf-life, which leads to postharvest loss and waste. This loss, however, could be reduced by breeding new crops that retain desirable traits and accrue less damage over the course of long supply chains. New gene-editing tools promise the rapid and inexpensive production of new varieties of crops with enhanced traits more easily than was previously possible. Our aim in this review is to critically evaluate gene editing as a tool to modify the biological pathways that determine fruit, vegetable, and ornamental quality, especially after storage. We provide brief and accessible overviews of both the CRISPR-Cas9 method and the produce supply chain. Next, we survey the literature of the last 30 years, to catalog genes that control or regulate quality or senescence traits that are "ripe" for gene editing. Finally, we discuss barriers to implementing gene editing for postharvest, from the limitations of experimental methods to international policy. We conclude that in spite of the hurdles that remain, gene editing of produce and ornamentals will likely have a measurable impact on reducing postharvest loss and waste in the next 5-10 years.

Genome-Wide Identification of Loci Associated With Phenology-Related Traits and Their Adaptive Variations in a Highbush Blueberry Collection

Genetic variation in phenological traits is the key in expanding production areas of crops. Southern highbush blueberry (SHB) is a blueberry cultivar group adapted to warmer climates and has been developed by multiple interspecific hybridizations between elite northern highbush blueberry (NHB) (Vaccinium corymbosum L.) and low-chill Vaccinium species native to the southern United States. In this study, we employed a collection of diverse SHB accessions and performed a genome-wide association study (GWAS) for five phenology-related traits [chilling requirement (CR), flowering date, ripening date, fruit development period, and continuous flowering] using polyploid GWAS models. Phenology-related traits showed higher heritability and larger correlation coefficients between year replications, which resulted in the detection of robust phenotype-genotype association peaks. Notably, a single association peak for the CR was detected on Chromosome 4. Comparison of genotypes at the GWAS peaks between NHB and SHB revealed the putative introgression of low-chill and late-flowering alleles into the highbush genetic pool. Our results provide basic insights into the diversity of phenological traits in blueberry and the genetic establishment of current highbush cultivar groups.

The carrot monoterpene synthase gene cluster on chromosome 4 harbours genes encoding flavour-associated sabinene synthases

In plants, low molecular weight terpenes produced by terpene synthases (TPS) contribute to multiple ecologically and economically important traits. The present study investigates a carrot terpene synthase gene cluster on chromosome 4 associated with volatile monoterpene production. Two carrot mutants, yellow and cola, which are contrasting in the content of low molecular weight terpenes, were crossed to develop an F2 mapping population. The mapping analysis revealed overlapping QTLs on chromosome 4 for sabinene, α-thujene, α-terpinene, γ-terpinene, terpinen-4-ol and 4-carene. The genomic region of this locus includes a cluster of five terpene synthase genes (DcTPS04, DcTPS26, DcTPS27, DcTPS54 and DcTPS55). DcTPS04 and DcTPS54 displayed genotype- and tissue-specific variation in gene expression. Based on the QTL mapping results and the gene expression patterns, DcTPS04 and DcTPS54 were selected for functional characterization. In vitro enzyme assays showed that DcTPS54 is a single-product enzyme catalysing the formation of sabinene, whereas DcTPS04 is a multiple-product terpene synthase producing α-terpineol as a major product and four additional products including sabinene, β-limonene, β-pinene and myrcene. Furthermore, we developed a functional molecular marker that could discriminate carrot genotypes with different sabinene content in a set of 85 accessions.

Changes of the Aroma Composition and Other Quality Traits of Blueberry 'Garden Blue' during the Cold Storage and Subsequent Shelf Life

The changes of volatile composition and other quality traits of blueberry during postharvest storage were investigated. Blueberries were packaged in vented clam-shell containers, and stored at 0 °C for 0, 15 and 60 days, followed by storage at room temperature (25 °C) for up to 8 days for quality evaluation. The firmness, pH, and total soluble solids increased by 8.42%, 8.92% and 42.9%, respectively, after 60 days of storage at 0 °C. Titratable acidity decreased 18.1% after 60 days of storage at 0 °C. The volatile change was monitored using headspace-solid-phase microextraction-gas chromatography-quadrupole time-of-flight-mass spectrometry (HS-SPME-TOF-MS) and off-odor was evaluated by sensory panel. Volatile compounds generally showed a downward trend during cold storage. However, the subsequent shelf life was the most remarkable period of volatile change, and was represented by the strong fluctuation of ethyl acetate and the rapid decrease of terpenoids. Extending storage from 15 to 60 days under cold condition still resulted in an acceptable odor. However, subsequent storage at higher temperature resulted in a quick deterioration in sensory acceptability. The results proved that cold storage was a reliable way to maintain the quality of blueberry, and flavor deterioration during subsequent shelf life was more fatal to the blueberry flavor.

A Review of the Fruit Volatiles Found in Blueberry and Other Vaccinium Species

Variations in volatile organic compound (VOC) type and content can result in noticeable differences in fruit aroma. The genus Vaccinium encompasses over 500 distinct species of berry-producing plants, several of which are important to commercial horticulture. Understanding which VOCs are produced by different members of this genus could greatly aid efforts to improve the aroma of multiple Vaccinium crops by breeding for desirable fruit volatiles. This review summarizes the published research available on this topic, examining prior work done to characterize the volatile profiles of blueberries, cranberries, bilberries, lingonberries, whortleberries, and other Vaccinium berries. In addition, analytical methodologies used to obtain Vaccinium berry volatile profiles are discussed. Possible future directions for Vaccinium berry volatile research are also examined.

Development of a Novel Phenotypic Roadmap to Improve Blueberry Quality and Storability

Improved fruit quality and prolonged storage capability are key breeding traits for blueberry (Vaccinium spp.) fruit. Until now, breeding selection was mostly oriented on the amelioration of agronomic traits, such as flowering time, chilling requirement, or plant structure. Up until now, however, the storage effect on fruit quality has not been extensively studied, mostly because objective and handy phenotyping tools to evaluate quality traits were not available. In this study we are proposing a novel phenotyping protocol to support breeding selection and quality control within the entire blueberry production chain. Volatile organic compounds (VOCs) and texture traits, were measured by Proton Transfer Reaction- Time of Flight- Mass Spectrometry (PTR-ToF-MS) and a texture analyzer respectively, taking into consideration the influence of prolonged storage. The exploitation of the genetic variability existing within the investigated blueberry germplasm collection (including both southern and northern highbush, hybrids, and rabbiteyes) allowed the identification of the best performing cultivars, based on texture and VOCs variability, to be used as superior parental lines for future breeding programs. The comprehensive characterization of blueberry aroma allowed the identification of a wide array of spectrometric features, mostly related to aldehydes, alcohols, terpenoids, and esters, that can be used as putative biomarkers to rapidly evaluate the blueberry aroma variations related to genetic differences and storability. In addition, this study revealed a lack of straightforward relationship between harvest and postharvest quality features, that might be genotype-dependent.

High-Resolution Linkage Map and QTL Analyses of Fruit Firmness in Autotetraploid Blueberry

Blueberry (Vaccinium corymbosum and hybrids) is an autotetraploid crop whose commercial relevance has been growing steadily during the last 20 years. However, the ever-increasing cost of labor for hand-picking blueberry is one main constraint in competitive marketing of the fruit. Machine harvestability is, therefore, a key trait for the blueberry industry. Understanding the genetic architecture of traits related to machine harvestability through Quantitative Trait Loci (QTL) mapping is the first step toward implementation of molecular breeding for faster genetic gains. Despite recent advances in software development for autotetraploid genetic mapping, a high-resolution map is still not available for blueberry. In this study, we crafted a map for autotetraploid low-chill highbush blueberry containing 11,292 SNP markers and a total size of 1,953.97 cM (average density of 5.78 markers/cM). This map was subsequently used to perform QTL analyses in 2-year field trials for a trait crucial to machine harvesting: fruit firmness. Preliminary insights were also sought for single evaluations of firmness retention after cold storage, and fruit detachment force traits. Significant QTL peaks were identified for all the traits and overlapping QTL intervals were detected for firmness across the years. We found low-to-moderate QTL effects explaining the phenotypic variance, which suggest a quantitative nature of these traits. The QTL intervals were further speculated for putative gene repertoire. Altogether, our findings provide the basis for future fine-mapping and molecular breeding efforts for machine harvesting in blueberry.

Comparing the Flavor Characteristics of 71 Tomato (Solanum lycopersicum) Accessions in Central Shaanxi

Flavor is an important quality of mature tomato fruits. Compared with heirloom tomatoes, modern commercial tomato cultivars are considerably less flavorful. This study aimed to compare the flavor of 71 tomato accessions (8 pink cherry, PC; 11 red cherry, RC; 15 pink large-fruited, PL; and 37 red large-fruited, RL) using hedonism scores and odor activity values. Taste compounds were detected using high-performance liquid chromatography. Volatiles were detected using gas chromatography-olfactometry-mass spectrometry. The flavor of tomato accessions can be evaluated using the DTOPSIS analysis method. According to the results of DTOPSIS analysis, 71 tomato accessions can be divided into 4 classes. Tomato accessions PL11, PC4, PC2, PC8, RL35, RC6, and RC10 had better flavor; accessions PC4, PC8, RC10, RL2, and RL35 had better tomato taste; and accessions PL11, PC2, and RC6 had better tomato odor. The concentrations of total soluble solids, fructose, glucose, and citric acid were shown to positively contribute to tomato taste. Tomato odor was mainly derived from 15 volatiles, namely, 1-hexanol, (Z)-3-hexen-1-ol, hexanal, (E)-2-hexenal, (E)-2-heptenal, (E)-2-octenal, (E,E)-2,4-decadienal, (Z)-3,7-dimethyl-2,6-octadieal, 2,6,6-timethyl-1-cyclohexene-1-carboxaldehyde, (2E)-3-(3-pentyl-2-oxiranyl)acrylaldehyde, 6-methyl-5-hepten-2-one, (E)-6,10-dimetyl-5,9-undecadien-2-one, methyl salicylate, 4-allyl-2-methoxyphenol, and 2-isobutylthiazole. Significant positive correlations (P < 0.05) were detected between the compound concentrations and flavor scores. The above-mentioned compounds can be used as parameters for the evaluation of flavor characteristics and as potential targets to improve the flavor quality of tomato varieties.