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

Variation in Chemical, Textural and Sensorial Traits Among Remontant Red Raspberry (Rubus idaeus L.) Cultivars Maintained in a Double-Cropping System

Remontant raspberry cultivars originally produce fruit in the upper part of primocanes in the fall, but if retained over winter, they can produce a second crop in the lower part of the floricanes the following spring. Maintaining remontant cultivars to yield twice during the cane's growth cycle corresponds to a double-cropping system, which enables an increase in the total yield and the extension of the fruiting season. To date, there is little information on changes in fruit quality between primocane and floricane crops. The aim of this study was, therefore, to investigate variations in the content of sugars and organic acids, fruit weight, color and textural and sensorial attributes among five newly introduced remontant raspberry cultivars ('Dafne', 'Kokanee', 'Paris', 'Versailles' and 'Primalba') and the control cultivar 'Enrosadira'. The specific aim was to evaluate how a double-cropping system in each cultivar may affect the variability in quality traits between primocane and floricane crops. The results showed a significant increase in fruit weight and individual and total sugar content in primocane crops, while significantly brighter red-colored and firmer fruits were observed in floricane crops. Cultivars did not differ from the control regarding total sugar content and sweetness index, while the content of individual sugars caused greater variations. The highest content of citric, malic and total acid (9.74, 1.42 and 11.25 mg 100 g-1 FW, respectively) were recorded in 'Paris', by which this cultivar was the only one distinguished from the control. 'Dafne' and 'Versailles' exhibited better internal and external fruit quality on primocanes, having significantly larger fruits (6.83 g and 6.37 g, respectively) and twice the increased sugar content. The lowest fruit weight was observed in 'Kokanee' for both primocane (4.63 g) and floricane (3.65 g) crops. 'Kokanee' and 'Primalba' also performed worse than the control for most sensory attributes in both seasons. Based on the analysis of the overall fruit quality linked to the appearance-, texture- and taste-related attributes that affect consumer preference, cultivars 'Enrosadira', 'Versailles' and 'Dafne' stood out, while 'Paris' showed high uniformity in fruit quality between crops, but scored the worst according to the total quality index.

Differences in primary metabolism related to quality of raspberry (Rubus idaeus L.) fruit under open field and protected soilless culture growing conditions

Introduction

The raspberry (Rubus idaeus) fruit is characterized by good taste and high acceptability by consumers. Thus, the impact on the quality attributes and metabolites related to raspberry taste should be evaluated in crop alternatives such as the protected soilless culture. This study aimed to evaluate the metabolic changes during fruit development and postharvest of raspberry grown in open field and protected soilless culture and their relationship with quality parameters and sensory perception.

Methods

In this study, the quality parameters and polar metabolites -sugar and amino acids- content were evaluated during raspberry ripening. In addition, ripe fruit was stored at 1 °C for five days, followed by one day of shelf life at 20 °C.

Results

The physiological and quality parameters showed typical changes during ripening in both growing conditions: a constant production of CO2, a drastic loss of firmness, an increase in weight and soluble solids content, loss of acidity, and a turning to red color from the green to fully ripe fruit stages in both growing conditions. Fruit from the protected soilless culture had significantly higher weight but a lower soluble solids content. The metabolic analysis showed differences in primary metabolites content during ripening and storage at 1 °C between both growing conditions. The raspberries grown in the open field showed higher contents of sugars such as D-glucose and D-fructose. On the contrary, the fruit from the protected soilless culture showed higher contents of some amino acids such as L-alanine, L-serine and L-valine, among others. The sensorial panel showed significant differences in the perception of the sweetness, acidity, color and firmness of ripe fruit from both growing conditions.

Discussion

The present study provides interesting and useful results with direct commercial application for this alternative growing system, mainly in areas where soil and water scarcity are a reality.

Nutritionally Important Pro-Health Active Ingredients and Antioxidant Properties of Fruits and Fruit Juice of Selected Biennial Fruiting Rubus idaeus L. Cultivars

Raspberry fruits are an important source of many biologically active chemical compounds exerting nutritional and pro-health effects. The study presents a comparative analysis of nutritionally important bioactive chemical compounds-polyphenols; flavonoids, including anthocyanins; vitamin C; amino acids; fatty acids; and primary metabolites-contained in the fruits of three biennial fruiting cultivars, R. idaeus 'Glen Ample', 'Laszka', and 'Radziejowa', i.e., common cultivars in Poland and Europe. The antioxidant activity of fresh fruits and juice was determined with five methods. The analyses revealed the strong free radical scavenging potential of the fruits and juice, confirmed by the high concentration of nutrients, e.g., polyphenols, anthocyanins, vitamin C, amino acids, and fatty acids. The antioxidant activity of the juice determined with the ferric reducing antioxidant power (FRAP) and OH radical methods was from 2.5 to 4.0 times higher than that of the fruits. The following orders of total polyphenol contents were established in the analyzed cultivars: 'Glen Ample' < 'Laszka' < 'Radziejowa' in the fruits and 'Glen Ample' < 'Radziejowa' < 'Laszka' in the juice. The highest antioxidant activity was exhibited by the 'Radziejowa' fruits. Given their high content of dietary fiber, the fruits of the analyzed raspberry cultivars can be consumed by dieting subjects. The concentrations of vitamin C (28-34 mg/100 g) and anthocyanins (20-34 mg/100 g) indicate the biological and pharmacological activity of these fruits. The main unsaturated fatty acids in the fruits were gamma-linoleic acid (C18:2n6c) and alpha-linolenic acid (C18:3n3), which neutralize excess free radicals. The amino acids nutritionally essential to humans were dominated by leucine, arginine, and phenylalanine. This is the first comparative analysis of the antioxidant activity of fruits and juice and the contents of selected active compounds in the fruits of biennial fruiting cultivars of R. idaeus, i.e., a highly commercialized crop in Europe.

A simulation-based assessment of the efficiency of QTL mapping under environment and genotype x environment interaction effects

The objective of this simulation-based study was to assess how genes, environments, and genotype x environment (GxE) interaction affect the quantitative trait loci (QTL) mapping efficiency. The simulation software performed 50 samplings of 300 recombinant inbred lines (RILs) from a F2, which were assessed in six environments. The RILs were genotyped for 977 single nucleotide polymorphisms (SNP) and phenotyped for grain yield. The average SNP density was 2 cM. We defined six QTLs and 190 minor genes. The trait heritability ranged from 30 to 80%. We fitted the single QTL model and the multiple QTL model on multiple phenotypes. The environment and complex GxE interaction effects led to a low correlation between the QTL heritability and power. The single- and across-environment analyses allowed all QTLs be declared, with an average power of 28 to 100%. In the across-environment analysis, five QTLs showed average power in the range 46 to 82%. Both models provided a good control of the false positive rate (6%, on average) and a precise localization of the QTLs (bias of 2 cM, on average). The QTL power in each environment has a high positive correlation with the range between QTL genotypes for the sum of the additive, environment, and GxE interaction effects (0.76 to 0.96). The uncertainty about the magnitude and sign of the environment and GxE interaction effects makes QTL mapping in multi-environment trials unpredictable. Unfortunately, this uncertainty has no solution because the geneticist has no control over the magnitude and sign of the environment and GxE interaction effects. However, the single- and across-environment analyses are efficient even under a low correlation between QTL heritability and power.

Volatilomics of raspberry fruit germplasm by combining chromatographic and direct-injection mass spectrometric techniques

The application of direct-injection mass spectrometric (DI-MS) techniques, like Proton Transfer Reaction Time of Flight Mass Spectrometry (PTR-ToF-MS) has been suggested as a reliable phenotyping tool for fruit volatilome assessment in both genetic and quality-related studies. In this study the complexity of raspberry aroma was investigated by a comprehensive untargeted VOC analysis, done by combining SPME-GC-MS and PTR-ToF-MS assessments with multi-block discriminant analysis using the DIABLO mixOmics framework. The aim was to acquire an exhaustive characterization of the raspberry volatilome according to different fruit ripening stages (pink, ripe, and overripe) and genetic variances (50 accessions), as well as to investigate the potential of PTR-ToF-MS as a rapid and high throughput VOC phenotyping tool to address issues related to raspberry fruit quality. Results of this study demonstrated the complementarity between SPME-GC-MS and PTR-ToF-MS techniques to evaluate the raspberry aroma composition. PTR-ToF-MS generates reliable raspberry VOC fingerprints mainly due to a reduced compound fragmentation and precise content estimation. In addition, the high collinearity between isomers of monoterpenes and norisoprenoids, discovered by GC analysis, reduces the main analytic limitation of PTR-ToF-MS of not being able to separate isomeric molecules. The high similarity between the VOC matrices obtained by applying PTR-ToF-MS and SPME-GC-MS confirmed the possibility of using PTR-ToF-MS as a reliable high throughput phenotyping tool for raspberry volatiolome assessment. In addition, results provided by the germplasm collection investigation enabled to distinguish the best performing accessions, based on VOCs composition, to be used as superior parental lines for future breeding programs.

Analysis of fruit ripening in Theobroma cacao pod husk based on untargeted metabolomics

The pod husk of Theobroma cacao (CPH) plays an important agronomical role, as its appearance is used as indicator of ripening, guiding the farmers in the harvest process. Cacao harvesting is not a standardized practice because farmers harvest between six up to eight months from flowering, guided by pod's color and shape. The mixture of cacao beans from different ripening stages (RS), negatively affecting the quality and price of grain. A way to help the farmers in the harvest standardization could be through the use of chemical markers and visual indicators of CPH ripening. This study analyses CPH's metabolic distribution of two cacao clones, ICS95 and CCN51 at six, seven, and eight months of ripening. Untargeted metabolomics was done using HPLC-MS/MS for biomarker discovery and association to cacao ripening. The results indicated a strong metabolic differentiation of the sixth month with the rest of the months independent of the variety. Also, metabolic differences were found between cacao clones for the seventh and eighth month. We annotated five potential biochemical markers including 3-caffeoylpelargodinin 5-glucoside, indoleacetaldehyde, procyanidin A dimer, procyanidin C1, and kaempferol. We further looked for correlation between patterns of progression of our markers against quantitative indicators of CPH appearance and texture, at the same ripening stages. We also performed a functional analysis and three possible metabolic pathways: flavone and flavonol biosynthesis, flavonoid biosynthesis, and tryptophan metabolism were identified associated with stress sensing, plant development and defense respectively. We found significant and positive correlations between green color density and all metabolites. For texture, the correlations were significantly negative with all metabolites. Our results suggest that about the sixth month is appropriate for harvesting cacao in the region of Caldas, Colombia in order to avoid all the metabolic variations occurring at later stages of ripening which impact the cacao bean quality. Therefore, studying the cacao ripening process can help in the estimation of the best harvest time and contribute to the standardization of harvest practices.

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.

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.