Analysis of volatile organic compounds in Korean-bred strawberries: insights for improving fruit flavor.

Introduction: The strawberry industry in South Korea has witnessed a significant 65% growth over the past decade, surpassing other fruits and vegetables in production value. While sweetness and acidity are well-recognized flavor determinants, the role of volatile organic compounds (VOCs) in defining the desirable flavor profiles of strawberries is also crucial. However, existing research has predominantly concentrated on a limited range of commercial cultivars, neglecting the broader spectrum of strawberry varieties. Methods: This study embarked on developing a comprehensive VOC database for a diverse array of strawberry cultivars sourced both domestically and internationally. A total of 61 different strawberry cultivars from Korea (45), the USA (7), Japan (8), and France (1) were analyzed for their VOC content using Tenax TA Thermo Desorption tubes and Gas Chromatography-Mass Spectrometry (GC-MS). In addition to VOC profiling, heritability was assessed using one-way ANOVA to compare means among multiple groups, providing insights into the genetic basis of flavor differences. Results and discussion: The analysis identified 122 compounds categorized into esters, alcohols, terpenes, and lactones, with esters constituting the majority (46.5%) of total VOCs in Korean cultivars. 'Arihyang', 'Sunnyberry', and 'Kingsberry' exhibited the highest diversity of VOCs detected (97 types), whereas 'Seolhong' showed the highest overall concentration (57.5mg·kg-1 FW). Compared to the USA cultivars, which were abundant in γ-decalactone (a peach-like fruity aroma), most domestic cultivars lacked this compound. Notably, 'Misohyang' displayed a high γ-decalactone content, highlighting its potential as breeding germplasm to improve flavor in Korean strawberries. The findings underscore the importance of a comprehensive VOC analysis across different strawberry cultivars to understand flavor composition. The significant variation in VOC content among the cultivars examined opens avenues for targeted breeding strategies. By leveraging the distinct VOC profiles, particularly the presence of γ-decalactone, breeders can develop new strawberry varieties with enhanced flavor profiles, catering to consumer preferences for both domestic and international markets.

Turning glucosinolate into allelopathic fate: investigating allyl isothiocyanate variability and nitrile formation in eco-friendly Brassica juncea from South Korea.

Leaf mustard (Brassica juncea L.) is explored for its biofumigant properties, derived from its secondary metabolites, particularly allyl isothiocyanate (AITC), produced during the enzymatic breakdown of glucosinolates like sinigrin. The research examines eight leaf mustard cultivars developed in Yeosu city, South Korea, focusing on their genetic characteristics, AITC concentration and nitriles formation rates from glucosinolates. Results indicate that the allelopathic effects, largely dependent on AITC concentration and enzymatic activity, vary across cultivar. Sinigrin and AITC constitute 79% and 36%, respectively, of glucosinolate and its hydrolysis products. The cultivar 'Nuttongii' demonstrates significant potential for inhibiting weeds, exhibiting the highest AITC concentration at 27.47 ± 6.46 µmole g-1 These outcomes highlight the importance of selecting mustard cultivars for biofumigation based on their glucosinolate profiles and hydrolysis product yields. The study also identifies a significant genetic influence on AITC and nitrile formation, suggesting that epithiospecifier protein modulation could enhance both allelopathic and other beneficial effects. Collectively, the research underscores the promise of mustard as a sustainable, environmentally friendly alternative to traditional herbicides.

Internal quality prediction technology for 'Sulhyang' strawberry fruit using organic analysis and hyperspectral imaging.

In recent years, hyperspectral imaging combined with machine learning techniques has garnered significant attention for its potential in assessing fruit maturity. This study proposes a method for predicting strawberry fruit maturity based on the harvest time. The main features of this study are as follows. 1) Selection of wavelength band associated with strawberry growth season; 2) Extraction of efficient parameters to predict strawberry maturity 3) Prediction of internal quality attributes of strawberries using extracted parameters. In this study, experts cultivated strawberries in a controlled environment and performed hyperspectral measurements and organic analyses on the fruit with minimal time delay to facilitate accurate modeling. Data augmentation techniques through cross-validation and interpolation were effective in improving model performance. The four parameters included in the model and the cumulative value of the model were available for quality prediction as additional parameters. Among these five parameter candidates, two parameters with linearity were finally identified. The predictive outcomes for firmness, soluble solids content, acidity, and anthocyanin levels in strawberry fruit, based on the two identified parameters, are as follows: The first parameter, ps, demonstrated RMSE performances of 1.0 N, 2.3 %, 0.1 %, and 2.0 mg per 100 g fresh fruit for firmness, soluble solids content, acidity, and anthocyanin, respectively. The second parameter, p3, showed RMSE performances of 0.6 N, 1.2 %, 0.1 %, and 1.8 mg per 100 g fresh fruit, respectively. The proposed non-destructive analysis method shows the potential to overcome the challenges associated with destructive testing methods for assessing certain internal qualities of strawberry fruit.