Strawberry fruit shape: quantification by image analysis and QTL detection by genome-wide association analysis

Multi-objective RGB-D fusion network for non-destructive strawberry trait assessment

Growing consumer demand for high-quality strawberries has highlighted the need for accurate, efficient, and non-destructive methods to assess key postharvest quality traits, such as weight, size uniformity, and quantity. This study proposes a multi-objective learning algorithm that leverages RGB-D multimodal information to estimate these quality metrics. The algorithm develops a fusion expert network architecture that maximizes the use of multimodal features while preserving the distinct details of each modality. Additionally, a novel Heritable Loss function is implemented to reduce redundancy and enhance model performance. Experimental results show that the coefficient of determination (R²) values ​​for weight, size uniformity and number are 0.94, 0.90 and 0.95 respectively. Ablation studies demonstrate the advantage of the architecture in multimodal, multi-task prediction accuracy. Compared to single-modality models, non-fusion branch networks, and attention-enhanced fusion models, our approach achieves enhanced performance across multi-task learning scenarios, providing more precise data for trait assessment and precision strawberry applications.

Comprehensive insights on association mapping in perennial fruit crops breeding - Its implications, current status and future perspectives

In order to provide food and nutritional security for the world's rapidly expanding population, fruit crop researchers have identified two critical priorities: increasing production and preserving fruit quality during the pre- and post-harvest periods. The genetic basis of these complex, commercially important fruit traits which are uniquely regulated by polygenes or multi-allelic genes that interact with one another and the environment can be analyzed with the aid of trait mapping tools. The most interesting trait mapping approach that offers the genetic level investigation for marker-trait associations (MTAs) for these complex fruit traits, without the development of mapping population, is association mapping. This approach was used during the genetic improvement program, emphasizing the obstacles (breeding strategies adopted, generation interval, and their genomic status) pertaining to perennial fruit crops. This method of studying population diversity and linkage disequilibrium in perennial fruit crops has been made possible by recent developments in genotyping, phenotyping, and statistical analysis. Thus, the purpose of this review is to provide an overview of different trait mapping techniques, with a focus on association mapping (method, essential components, viability, constraints, and future perspective) and its advantages, disadvantages, and possibilities for breeding perennial fruit crops.

BerryPortraits: Phenotyping Of Ripening Traits cranberry (Vaccinium macrocarpon Ait.) with YOLOv8

BerryPortraits (Phenotyping of Ripening Traits) is open source Python-based image-analysis software that rapidly detects and segments berries and extracts morphometric data on fruit quality traits such as berry color, size, shape, and uniformity. Utilizing the YOLOv8 framework and community-developed, actively-maintained Python libraries such as OpenCV, BerryPortraits software was trained on 512 postharvest images (taken under controlled lighting conditions) of phenotypically diverse cranberry populations (Vaccinium macrocarpon Ait.) from the two largest public cranberry breeding programs in the U.S. The implementation of CIELAB, an intuitive and perceptually uniform color space, enables differentiation between berry color and berry brightness, which are confounded in classic RGB color channel measurements. Furthermore, computer vision enables precise and quantifiable color phenotyping, thus facilitating inclusion of researchers and data analysts with color vision deficiency. BerryPortraits is a phenotyping tool for researchers in plant breeding, plant genetics, horticulture, food science, plant physiology, plant pathology, and related fields. BerryPortraits has strong potential applications for other specialty crops such as blueberry, lingonberry, caneberry, grape, and more. As an open source phenotyping tool based on widely-used python libraries, BerryPortraits allows anyone to use, fork, modify, optimize, and embed this software into other tools or pipelines.

Exploration of a European-centered strawberry diversity panel provides markers and candidate genes for the control of fruit quality traits

Fruit quality traits are major breeding targets in cultivated strawberry (Fragaria × ananassa). Taking into account the requirements of both growers and consumers when selecting high-quality cultivars is a real challenge. Here, we used a diversity panel enriched with unique European accessions and the 50 K FanaSNP array to highlight the evolution of strawberry diversity over the past 160 years, investigate the molecular basis of 12 major fruit quality traits by genome-wide association studies (GWAS), and provide genetic markers for breeding. Results show that considerable improvements of key breeding targets including fruit weight, firmness, composition, and appearance occurred simultaneously in European and American cultivars. Despite the high genetic diversity of our panel, we observed a drop in nucleotide diversity in certain chromosomal regions, revealing the impact of selection. GWAS identified 71 associations with 11 quality traits and, while validating known associations (firmness, sugar), highlighted the predominance of new quantitative trait locus (QTL), demonstrating the value of using untapped genetic resources. Three of the six selective sweeps detected are related to glossiness or skin resistance, two little-studied traits important for fruit attractiveness and, potentially, postharvest shelf life. Moreover, major QTL for firmness, glossiness, skin resistance, and susceptibility to bruising are found within a low diversity region of chromosome 3D. Stringent search for candidate genes underlying QTL uncovered strong candidates for fruit color, firmness, sugar and acid composition, glossiness, and skin resistance. Overall, our study provides a potential avenue for extending shelf life without compromising flavor and color as well as the genetic markers needed to achieve this goal.

Advances in genomics and genome editing for improving strawberry (Fragaria ×ananassa)

The cultivated strawberry, Fragaria ×ananassa, is a recently domesticated fruit species of economic interest worldwide. As such, there is significant interest in continuous varietal improvement. Genomics-assisted improvement, including the use of DNA markers and genomic selection have facilitated significant improvements of numerous key traits during strawberry breeding. CRISPR/Cas-mediated genome editing allows targeted mutations and precision nucleotide substitutions in the target genome, revolutionizing functional genomics and crop improvement. Genome editing is beginning to gain traction in the more challenging polyploid crops, including allo-octoploid strawberry. The release of high-quality reference genomes and comprehensive subgenome-specific genotyping and gene expression profiling data in octoploid strawberry will lead to a surge in trait discovery and modification by using CRISPR/Cas. Genome editing has already been successfully applied for modification of several strawberry genes, including anthocyanin content, fruit firmness and tolerance to post-harvest disease. However, reports on many other important breeding characteristics associated with fruit quality and production are still lacking, indicating a need for streamlined genome editing approaches and tools in Fragaria ×ananassa. In this review, we present an overview of the latest advancements in knowledge and breeding efforts involving CRISPR/Cas genome editing for the enhancement of strawberry varieties. Furthermore, we explore potential applications of this technology for improving other Rosaceous plant species.

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.

Form and contour: breeding and genetics of organ shape from wild relatives to modern vegetable crops

Shape is a primary determinant of consumer preference for many horticultural crops and it is also associated with many aspects of marketing, harvest mechanics, and postharvest handling. Perceptions of quality and preference often map to specific shapes of fruits, tubers, leaves, flowers, roots, and other plant organs. As a result, humans have greatly expanded the palette of shapes available for horticultural crops, in many cases creating a series of market classes where particular shapes predominate. Crop wild relatives possess organs shaped by natural selection, while domesticated species possess organs shaped by human desires. Selection for visually-pleasing shapes in vegetable crops resulted from a number of opportunistic factors, including modification of supernumerary cambia, allelic variation at loci that control fundamental processes such as cell division, cell elongation, transposon-mediated variation, and partitioning of photosynthate. Genes that control cell division patterning may be universal shape regulators in horticultural crops, influencing the form of fruits, tubers, and grains in disparate species. Crop wild relatives are often considered less relevant for modern breeding efforts when it comes to characteristics such as shape, however this view may be unnecessarily limiting. Useful allelic variation in wild species may not have been examined or exploited with respect to shape modifications, and newly emergent information on key genes and proteins may provide additional opportunities to regulate the form and contour of vegetable crops.

Image-Based High-Throughput Phenotyping in Horticultural Crops

Plant phenotyping is the primary task of any plant breeding program, and accurate measurement of plant traits is essential to select genotypes with better quality, high yield, and climate resilience. The majority of currently used phenotyping techniques are destructive and time-consuming. Recently, the development of various sensors and imaging platforms for rapid and efficient quantitative measurement of plant traits has become the mainstream approach in plant phenotyping studies. Here, we reviewed the trends of image-based high-throughput phenotyping methods applied to horticultural crops. High-throughput phenotyping is carried out using various types of imaging platforms developed for indoor or field conditions. We highlighted the applications of different imaging platforms in the horticulture sector with their advantages and limitations. Furthermore, the principles and applications of commonly used imaging techniques, visible light (RGB) imaging, thermal imaging, chlorophyll fluorescence, hyperspectral imaging, and tomographic imaging for high-throughput plant phenotyping, are discussed. High-throughput phenotyping has been widely used for phenotyping various horticultural traits, which can be morphological, physiological, biochemical, yield, biotic, and abiotic stress responses. Moreover, the ability of high-throughput phenotyping with the help of various optical sensors will lead to the discovery of new phenotypic traits which need to be explored in the future. We summarized the applications of image analysis for the quantitative evaluation of various traits with several examples of horticultural crops in the literature. Finally, we summarized the current trend of high-throughput phenotyping in horticultural crops and highlighted future perspectives.

The Effect of Climatic Parameters on Strawberry Production in a Small Walk-In Greenhouse

The purpose of this study was to evaluate the impact of different environmental factors such as temperature, solar radiation, and relative humidity on the quality of strawberries in terms of their shape, size, and sugar accumulation. The experiment was carried out in a small walk-in greenhouse in Matsusaka city, Japan. Harunoka strawberries (Fragaria × ananassa Duch.) were cultivated from September to May of the following year. Production was evaluated on 20 February 2021 (peak season) and 5 April 2021 (end season). To evaluate the influence of environmental factors on strawberry fruit quality, the weight, shape, and soluble sugar content were recorded and compared to each other. According to the environmental data, the average temperature between day and night at peak harvest was around 12 °C, which was suitable for high-quality strawberry cultivation. However, the average temperature difference between day and night was approximately 4 °C at the end of the season. In addition, there were no significant differences in solar radiation and relative humidity between both seasons. Increasing temperatures led to the decline in the soluble sugar content at the end season. Thus, it can be concluded that the temperature difference between day and night is a major factor affecting strawberry production. The assessment of the impact of environmental conditions on strawberry quality can be used as a guideline not only in temperate climates, but also in other climates, such as in tropical countries.