Project description:Descriptive analysis via trained sensory panels has great power to facilitate flavor improvement in fresh fruits and vegetables. When paired with an understanding of fruit volatile organic compounds, descriptive analysis can help uncover the chemical drivers of sensory attributes. In the present study, 213 strawberry samples representing 56 cultivars and advanced selections were sampled over seven seasons and subjected to both sensory descriptive and chemical analyses. Principal component analysis and K-cluster analyses of sensory data highlighted three groups of strawberry samples, with one classified as superior with high sweetness and strawberry flavor and low sourness and green flavor. Partial least square models revealed 20 sweetness-enhancing volatile organic compounds and two sweetness-reducing volatiles, many of which overlap with previous consumer sensory studies. Volatiles modulating green, sour, astringent, overripe, woody, and strawberry flavors were also identified. The relationship between soluble solids content (SSC) and sweetness was modeled with Bayesian regression, generating probabilities for sweetness levels from varying levels of soluble solids. A hierarchical Bayesian model with month effects indicated that SSC is most correlated to sweetness toward the end of the fruiting season, making this the best period to make phenotypic selections for soluble solids. Comparing effects from genotypes, harvest months, and their interactions on sensory attributes revealed that sweetness, sourness, and firmness were largely controlled by genetics. These findings help formulate a paradigm for improvement of eating quality in which sensory analyses drive the targeting of chemicals important to consumer-desired attributes, which further drive the development of genetic tools for improvement of flavor.
Project description:Maturity degree and quality evaluation are important for strawberry harvest, trade, and consumption. Deep learning has been an efficient artificial intelligence tool for food and agro-products. Hyperspectral imaging coupled with deep learning was applied to determine the maturity degree and soluble solids content (SSC) of strawberries with four maturity degrees. Hyperspectral image of each strawberry was obtained and preprocessed, and the spectra were extracted from the images. One-dimension residual neural network (1D ResNet) and three-dimension (3D) ResNet were built using 1D spectra and 3D hyperspectral image as inputs for maturity degree evaluation. Good performances were obtained for maturity identification, with the classification accuracy over 84% for both 1D ResNet and 3D ResNet. The corresponding saliency maps showed that the pigments related wavelengths and image regions contributed more to the maturity identification. For SSC determination, 1D ResNet model was also built, with the determination of coefficient (R 2) over 0.55 of the training, validation, and testing sets. The saliency maps of 1D ResNet for the SSC determination were also explored. The overall results showed that deep learning could be used to identify strawberry maturity degree and determine SSC. More efforts were needed to explore the use of 3D deep learning methods for the SSC determination. The close results of 1D ResNet and 3D ResNet for classification indicated that more samples might be used to improve the performances of 3D ResNet. The results in this study would help to develop 1D and 3D deep learning models for fruit quality inspection and other researches using hyperspectral imaging, providing efficient analysis approaches of fruit quality inspection using hyperspectral imaging.
Project description:Oilseed-vegetable-dual-purpose (OVDP) rapeseed can effectively alleviate the land contradiction between crops and it supplements vegetable supplies in winter or spring. The soluble solids content (SSC) is an important index that is used to evaluate the quality and sugar content of fruits and vegetables. However, the genetic architecture underlying the SSC in Brassica napus shoots is still unclear. Here, quantitative trait loci (QTLs) for the SSC in B. napus shoots were investigated by performing linkage mapping using a recombinant inbred line population containing 189 lines. A germplasm set comprising 302 accessions was also used to conduct a genome-wide association study (GWAS). The QTL mapping revealed six QTLs located on chromosomes A01, A04, A08, and A09 in two experiments. Among them, two major QTLs, qSSC/21GY.A04-1 and qSSC/21NJ.A08-1, accounted for 12.92% and 10.18% of the phenotypic variance, respectively. In addition, eight single-nucleotide polymorphisms with phenotypic variances between 5.62% and 10.18% were identified by the GWAS method. However, no locus was simultaneously identified by QTL mapping and GWAS. We identified AH174 (7.55 °Brix and 7.9 °Brix), L166 (8.9 °Brix and 8.38 °Brix), and L380 (8.9 °Brix and 7.74 °Brix) accessions can be used as superior parents. These results provide valuable information that increases our understanding of the genetic control of SSC and will facilitate the breeding of high-SSC B. napus shoots.
Project description:Genomic regions associated with ripening time (RPT) and soluble solids concentration (SSC) were mapped using a pedigreed population including multiple F1 and F2 families from the Clemson University peach breeding program (CUPBP). RPT and SSC QTLs were consistently identified in two seasons (2011 and 2012) and the average datasets (average of two seasons). A target region spanning 10,981,971-11,298,736 bp on chromosome 4 of peach reference genome used for haplotype analysis revealed four haplotypes with significant differences in trait values among different diplotype combinations. Favorable alleles at the target region for both RPT and SSC were determined and a DNA test for predicting RPT and SSC was developed. Two Kompetitive Allele Specific PCR (KASP) assays were validated on 84 peach cultivars and 163 seedlings from the CUPBP, with only one assay (Ppe.RPT/SSC-1) needed to predict between early and late-season ripening cultivars and low and high SSC. These results advance our understanding of the genetic basis of RPT and SSC and facilitate selection of new peach cultivars with the desired RPT and SSC.
Project description:Melon (Cucumis melo L.) is an economically important Cucurbitaceae crop grown around the globe. The sweetness of melon is a significant factor in fruit quality and consumer appeal, and the soluble solids content (SSC) is a key index of melon sweetness. In this study, 146 recombinant inbred lines (RILs) derived from two oriental melon materials with different levels of sweetness containing 1427 bin markers, and 213 melon accessions containing 1,681,775 single nucleotide polymorphism (SNP) markers were used to identify genomic regions influencing SSC. Linkage mapping detected 10 quantitative trait loci (QTLs) distributed on six chromosomes, seven of which were overlapped with the reported QTLs. A total of 211 significant SNPs were identified by genome-wide association study (GWAS), 138 of which overlapped with the reported QTLs. Two new stable, co-localized regions on chromosome 3 were identified by QTL mapping and GWAS across multiple environments, which explained large phenotypic variance. Five candidate genes related to SSC were identified by QTL mapping, GWAS, and qRT-PCR, two of which were involved in hydrolysis of raffinose and sucrose located in the new stable loci. The other three candidate genes were involved in raffinose synthesis, sugar transport, and production of substrate for sugar synthesis. The genomic regions and candidate genes will be helpful for molecular breeding programs and elucidating the mechanisms of sugar accumulation.
Project description:Key Message Powdery mildew resistance in two strawberry mapping populations is controlled by both stable and transient novel QTL of moderate effect. Some low transferability of QTL across wider germplasm was observed. The obligate biotrophic fungus Podosphaera aphanis is the causative agent of powdery mildew on cultivated strawberry (Fragaria × ananassa). Genotypes from two bi-parental mapping populations 'Emily' × 'Fenella' and 'Redgauntlet' × 'Hapil' were phenotyped for powdery mildew disease severity in a series of field trials. Here, we report multiple QTL associated with resistance to powdery mildew, identified in ten phenotyping events conducted across different years and locations. Six QTL show a level of stable resistance across multiple phenotyping events; however, many other QTL were represented in a single phenotyping event and therefore must be considered transient. Subsequent screening of identified QTL across a validation set determined whether identified QTL remained closely linked to the associated resistance gene in the wider germplasm. Furthermore, a preliminary association analysis identified a novel conserved locus for further investigation. Our data suggest that resistance is highly complex and that multiple, primarily additive, sources of quantitative resistance to powdery mildew exist across strawberry germplasm. Utilisation of the reported markers in marker-assisted breeding or genomic selection would lead to improved powdery mildew-resistant strawberry cultivars, particularly where the studied parents, progeny and close pedigree material are included in breeding germplasm.
Project description:Worldwide consumption of oil is increasing with the growing population in need for edible oil and the expansion of industry using biofuels. Then, demand for high yielding varieties of oil crops is always increasing. Brassica napus (rapeseed) is one of the most important oil crop in the world, therefore, increasing rapeseed yield through breeding is inevitable in order to cater for the high demand of vegetable oil and high-quality protein for live stocks. Quantitative trait loci (QTL) analysis is a powerful tool to identify important loci and which is also valuable for molecular marker assisted breeding. Seed-yield (SY) is a complex trait that is controlled by multiple loci and is affected directly by seed weight, seeds per silique and silique number. Some yield-related traits, such as plant height, biomass yield, flowering time, and so on, also affect the SY indirectly. This study reports the assembly of QTLs identified for seed-yield and yield-related traits in rapeseed, in one unique map. A total of 972 QTLs for seed-yield and yield-related were aligned into the physical map of B. napus Darmor-bzh and 92 regions where 198 QTLs overlapped, could be discovered on 16 chromosomes. Also, 147 potential candidate genes were discovered in 65 regions where 131 QTLs overlapped, and might affect nine different traits. At the end, interaction network of candidate genes was studied, and showed nine genes that could highly interact with the other genes, and might have more influence on them. The present results would be helpful to develop molecular markers for yield associated traits and could be used for breeding improvement in B. napus.
Project description:X-ray induced photoemission yield contains structural information complementary to that provided by X-ray Fresnel reflectivity, which presents an advantage to a wide variety of surface studies if this information is made easily accessible. Photoemission in materials research is commonly acknowledged as a method with a probing depth limited by the escape depth of the photoelectrons. Here we show that the integral hard-X-ray-induced photoemission yield is modulated by the Fresnel reflectivity of a multilayer structure and carries structural information that extends well beyond the photoelectron escape depth. A simple electric self-detection of the integral photoemission yield and Fourier data analysis permit extraction of thicknesses of individual layers. The approach does not require detection of the reflected radiation and can be considered as a framework for non-invasive evaluation of buried layers with hard X-rays under grazing incidence.
Project description:K and N are the nutrients with the highest influence on yield and fruit quality. From this perspective, the aim of this study was to determine the effect of N as NO3-, K+ and their interactions on the yield and quality of strawberries grown under soilless conditions. A solution comprised of micronutrients based on an amended Steiner's Universal Nutrient Solution was mixed with 4 levels of K+ (5, 7, 9 and 11 mol m-3) and 3 levels of NO3- (9, 12, and 15 mol m-3) to obtain 12 treatments. The results suggest that 15 mol m-3 of NO3- in the nutrient solution produced the highest yield, but fruit with low nutraceutical quality. On the other hand, 11 mol m-3 of K+ in the nutrient solution produced the highest yield and fruit with the best nutraceutical quality. The ionic concentration of the Universal Steiner's Nutrient Solution proved to be the best nutritional option to maximize the yield and nutraceutical quality of strawberry fruit. The increase in NO3- concentration in the nutrient solution produced a higher yield of strawberries, while a higher concentration of K+ improved fruit quality, thus reaffirming the significance of nutrients within the plant functioning of this crop.
Project description:Improving yield is one of the most important targets of sesame breeding. Identifying quantitative trait loci (QTLs) of yield-related traits is a prerequisite for marker-assisted selection (MAS) and QTL/gene cloning. In this study, a BC1 population was developed and genotyped with the specific-locus amplified fragment (SLAF) sequencing technology, and a high-density genetic map was constructed. The map consisted of 13 linkage groups, contained 3528 SLAF markers, and covered a total of 1312.52 cM genetic distance, with an average distance of 0.37 cM between adjacent markers. Based on the map, 46 significant QTLs were identified for seven yield-related traits across three environments. These QTLs distributed on 11 linkage groups, each explaining 2.34-71.41% of the phenotypic variation. Of the QTLs, 23 were stable QTLs that were detected in more than one environment, and 20 were major QTLs that explained more than 10% of the corresponding phenotypic variation in at least one environment. Favorable alleles of 38 QTLs originated from the locally adapted variety, Yuzhi 4; the exotic germplasm line, BS, contributed favorable alleles to only 8 QTLs. The results should provide useful information for future molecular breeding and functional gene cloning.Supplementary informationThe online version contains supplementary material available at 10.1007/s11032-021-01236-x.