42 research outputs found

    Mapping a candidate gene (MdMYB10) for red flesh and foliage colour in apple

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    <p>Abstract</p> <p>Background</p> <p>Integrating plant genomics and classical breeding is a challenge for both plant breeders and molecular biologists. Marker-assisted selection (MAS) is a tool that can be used to accelerate the development of novel apple varieties such as cultivars that have fruit with anthocyanin through to the core. In addition, determining the inheritance of novel alleles, such as the one responsible for red flesh, adds to our understanding of allelic variation. Our goal was to map candidate anthocyanin biosynthetic and regulatory genes in a population segregating for the red flesh phenotypes.</p> <p>Results</p> <p>We have identified the <it>Rni </it>locus, a major genetic determinant of the red foliage and red colour in the core of apple fruit. In a population segregating for the red flesh and foliage phenotype we have determined the inheritance of the <it>Rni </it>locus and DNA polymorphisms of candidate anthocyanin biosynthetic and regulatory genes. Simple Sequence Repeats (SSRs) and Single Nucleotide Polymorphisms (SNPs) in the candidate genes were also located on an apple genetic map. We have shown that the MdMYB10 gene co-segregates with the <it>Rni </it>locus and is on Linkage Group (LG) 09 of the apple genome.</p> <p>Conclusion</p> <p>We have performed candidate gene mapping in a fruit tree crop and have provided genetic evidence that red colouration in the fruit core as well as red foliage are both controlled by a single locus named <it>Rni</it>. We have shown that the transcription factor MdMYB10 may be the gene underlying <it>Rni </it>as there were no recombinants between the marker for this gene and the red phenotype in a population of 516 individuals. Associating markers derived from candidate genes with a desirable phenotypic trait has demonstrated the application of genomic tools in a breeding programme of a horticultural crop species.</p

    Effects of Microwave Heating on Sensory Characteristics of Kiwifruit Puree

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    The effect of microwave processing on the characteristics of kiwifruit puree was evaluated by applying various gentle treatments. Different combinations of microwave power/processing time were applied, with power among 200-1,000 W and time among 60-340 s, and various sensory and instrumental measurements were performed with the aim of establishing correlations and determining which instrumental parameters were the most appropriate to control the quality of kiwi puree. The water and soluble solids of the product, 83 and 14/100 g sample, respectively, did not change due to treatments. For sensory assessment, an expert panel was previously trained to describe the product. Fourteen descriptors were defined, but only the descriptors 'typical kiwifruit colour', 'tone', 'lightness', 'visual consistency' and 'typical taste' were significant to distinguish between kiwifruit puree samples. The instrumental analysis of samples consisted in measuring consistency, viscosity, colour and physicochemical characteristics of the treated and fresh puree. Applying intense treatments (600 W-340 s, 900 W-300 s and 1,000 W-200 s) through high power or long treatment periods or a combination of these factors, mainly affects the consistency (flow distance decreased from 5. 9 to 3. 4 mm/g sample), viscosity (increased from 1. 6 to 2. 5 Pa/s), colour (maximun ¿E was 6 U) and taste of the product. As a result, samples were thicker and with an atypical flavour and kiwifruit colour due to increased clarity (L* increased from 38 to 43) and slight changes in the yellow-green hue (h* decreased from 95 to 94). For the instrumental determinations of colour and visual perception of consistency, the most suitable parameters for quality control are the colour coordinates L*, a*, h*, whiteness index and flow distance measured with a Bostwick consistometer. © 2011 Springer Science+Business Media, LLC.The authors thank the Ministerio de Educacion y Ciencia for the financial support given throughout the Project AGL 2010-22176. The authors are indebted to the Generalitat Valenciana (Valencia, Spain) for the Grant awarded to the author Maria Benlloch. The translation of this paper was funded by the Universidad Politecnica de Valencia, Spain.Benlloch Tinoco, M.; Varela Tomasco, PA.; Salvador Alcaraz, A.; Martínez Navarrete, N. (2012). Effects of Microwave Heating on Sensory Characteristics of Kiwifruit Puree. Food and Bioprocess Technology. 5(8):3021-3031. https://doi.org/10.1007/s11947-011-0652-1S3021303158Albert, A., Varela, P., Salvador, A., & Fiszman, S. M. (2009). Improvement of crunchiness of battered fish nuggets. European Food Research and Technology, 228, 923–930.Alegria, P., Pinheiro, J., Gonçalves, E. M., Fernandes, I., Moldao, M., & Abreu, M. (2010). Evaluation of a pre-cut heat treatment as an alternative to chlorine in minimally processed shredded carrot. Innovative Food Science and Emerging Technologies, 11, 155–161.AOAC. (2000). Official Methods of Analysis of AOAC International. Gaithersburg: AOAC.Barboni, T., Cannac, M., & Chiaramonti, N. (2010). Effect of cold storage and ozone treatment on physicochemical parameters, soluble sugars and organic acids in Actinidia deliciosa. Food Chemistry, 121, 946–951.Beirão-da-Costa, S., Steiner, A., Correia, L., Empis, J., & Moldão-Martins, M. (2006). Effects of maturity stage and mild heat treatments on quality of minimally processed kiwifruitfruit. Journal of Food Engineering, 76, 616–625.Bodart, M., de Peñaranda, R., Deneyer, A., & Flamant, G. (2008). Photometry and colorimetry characterisation of materials in daylighting evaluation tools. Building and Environment, 43, 2046–2058.Bourne, M. C. (1982). Food texture and viscosity-concept and measurement. New York: Academic.Cano, M. P., Hernández, A., & de Ancos, B. (1997). High pressure and temperature effects on enzyme inactivation in strawberry and orange products. Journal of Food Science, 62(1), 85–88.Chiralt, A., Martínez-Navarrete, N., Camacho, M. M., & González, C. (1998). Experimentos de fisicoquímica de alimentos. Valencia: Editorial Universidad Politécnica de Valencia (Chapter 3).Chiralt, A., Martínez-Navarrete, N., González, C., Talens, P., & Moraga, G. (2007). Propiedades físicas de los alimentos. Valencia: Editorial Universidad Politécnica de Valencia (Chapter 16).Contreras, C., Martín, M. E., Martínez-Navarrete, N., & Chiralt, A. (2005). Effect of vacuum impregnation and microwave application on structural changes occurred during air drying of apple. Food Science and Technology/LWT, 38(5), 471–477.Contreras, C., Martín-Esparza, M. E., Martínez-Navarrete, N., & Chiralt, A. (2007). Influence of osmotic pre-treatment and microwave application on properties of air dried strawberry related to structural changes. European Food Research and Technology, 224, 499–504.de Ancos, B., Cano, M. P., Hernández, A., & Monreal, M. (1999). Effects of microwave heating on pigment composition and color of fruit purees. Journal of the Science of Food and Agriculture, 79, 663–670.Dubost, N. J., Shewfelt, R. L., & Eitenmiller, R. R. (2003). Consumer acceptability, sensory and instrumental analysis of peanut soy spreads. Journal of Food Quality, 26, 27–42.Escribano, S., Sánchez, F. J., & Lázaro, A. (2010). Establishment of a sensory characterization protocol for melon (Cucumis melo L.) and its correlation with physical-chemical attributes: indications for future genetics improvements. European Food Research and Technology, 231, 611–621.Fang, L., Jiang, B., & Zhang, T. (2008). Effect of combined high pressure and thermal treatment in kiwifruit peroxidase. Food Chemistry, 109, 802–807.Fisk, C. L., McDaniel, M. R., Strick, B. C., & Zhao, Y. (2006). Physicochemical, sensory, and nutritive qualities of hardy kiwifruit (Actinidia arguta ‘Ananasnaya’) as affected by harvest maturity and storage. Sensory and Nutritive Qualities of Food, 71(3), 204–210.Fúster, C., Préstamo, G., & Cano, M. P. (1994). Drip loss, peroxidase and sensory changes in kiwi fruit slices during frozen storage. Journal of the Science of Food and Agriculture, 64, 23–29.Guldas, M. (2003). Peeling and the physical and chemical properties of kiwi fruit. Journal of Food Processing Preservation, 27, 271–284.Igual, M., Contreras, C., & Martínez-Navarrete, N. (2010). Non-conventional techniques to obtain grapefruit jam. Innovative Food Science and Emerging Technologies, 11, 335–341.Igual, M., García-Martínez, E., Camacho, M. M., & Martínez-Navarrete, N. (2010). Effect of thermal treatment and storage on the stability of organic acids and the functional value of grapefruit juice. Food Chemistry, 118, 291–299.Jaeger, S. R., Rossiter, K. L., Wismer, W. V., & Harker, F. R. (2003). Consumer-driven product development in the kiwifruit industry. Food Quality and Preference, 14, 187–198.Lawless, H., & Heymann, H. (1998). Sensory evaluation of food: Principles and practices. New York: Chapman & Hall.MAPA (2010). Plataforma de conocimiento para el medio rural y pesquero. National Agricultural Statistics Database, Spain, Available at: www.mapa.es . Accessed 05 October 2010.Maskan, M. (2001). Kinetics of colour change of kiwifruits during hot air and microwave drying. Journal of Food Engineering, 48, 169–175.Mohammadi, A., Rafiee, S., Emam-Djomeh, Z., & Keyhani, A. (2008). Kinetic models for colour change in kiwifruit slices during Hoy Air drying. World Journal of Agricultural Sciences, 4(3), 376–383.Moretti, C. L., Mattos, L. M., Machado, C. M. M., & Kluge, R. A. (2007). Physiological and quality attributes associated with different centrifugation times of baby carrots. Horticultura Brasileira, 25, 557–561.Nielsen, S. S. (2010). Food analysis laboratory manual. New York: Springer.Oraguzie, N., Alspach, P., Volz, R., Whitworz, C., Ranatunga, C., Weskett, R., et al. (2009). Postharvest assessment of fruit quality parameters in apple using both instrument and an expert panel. Posthaverst Biology and Technology., 52, 279–287.Pagliarini, E., Laureati, M., & Lavelli, V. (2010). Sensory evaluation of gluten-free breads assessed by a trained panel of celiac assessors. European Food Research and Technology, 231, 37–46.Park, E. Y., & Luh, B. S. (1985). Polyphenol oxidase of kiwifruit. Journal of Food Science, 50, 678–684.Schubert, H., & Regier, M. (2010). The microwave processing of foods. London: Woodhead.Segnini, S., Dejmek, P., & Öste, R. (1999). Relationship between instrumental and sensory analysis of texture and colour of potato chips. Journal of Texture Studies, 30, 677–690.Sinija, V. R., & Mishra, H. N. (2011). Fuzzy analysis of sensory data for quality evaluation and ranking of instant green Tea powder and granules. Food Bioprocess Technology, 4, 408–416.Soufleros, E. H., Pissa, I., Petridis, D., Lygerakis, M., Mermelas, K., Boukouvalas, G., et al. (2001). Instrumental analysis of volatile and other compounds of Greek kiwi wine; sensory evaluation and optimization of its composition. Analytical, Nutritional and Clinical Methods Section, 75, 487–500.Vadivambal, R., & Jayas, D. S. (2007). Changes in quality of microwave-treated agricultural products-a review. Biosystems Engineering, 98, 1–16.Worch, T., Lê, S., & Punter, P. (2010). How reliable are the consumers? Comparison of sensory profiles from consumers and experts. Food Quality and Preference, 21, 309–318.Zanoni, B., Lavelli, V., Ambrosoli, R., Garavaglia, L., Minati, J., & Pagliarini, E. (2007). A model to predict shelf-life in air and darkness of cut, ready-to-use, fresh carrots under both isothermal and non-isothermal conditions. Journal of Food Engineering, 79, 586–591.Zolfaghari, M., Sahari, M. A., Barzegar, M., & Samadloiy, H. (2010). Physicochemical and enzymatic properties of five kiwifruit cultivars during cold storage. Food Bioprocess Technology, 3, 239–246

    Genetic diversity in cultivated carioca common beans based on molecular marker analysis

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    A wide array of molecular markers has been used to investigate the genetic diversity among common bean species. However, the best combination of markers for studying such diversity among common bean cultivars has yet to be determined. Few reports have examined the genetic diversity of the carioca bean, commercially one of the most important common beans in Brazil. In this study, we examined the usefulness of two molecular marker systems (simple sequence repeats – SSRs and amplified fragment length polymorphisms – AFLPs) for assessing the genetic diversity of carioca beans. The amount of information provided by Roger’s modified genetic distance was used to analyze SSR data and Jaccards similarity coefficient was used for AFLP data. Seventy SSRs were polymorphic and 20 AFLP primer combinations produced 635 polymorphic bands. Molecular analysis showed that carioca genotypes were quite diverse. AFLPs revealed greater genetic differentiation and variation within the carioca genotypes (Gst = 98% and Fst = 0.83, respectively) than SSRs and provided better resolution for clustering the carioca genotypes. SSRs and AFLPs were both suitable for assessing the genetic diversity of Brazilian carioca genotypes since the number of markers used in each system provided a low coefficient of variation. However, fingerprint profiles were generated faster with AFLPs, making them a better choice for assessing genetic diversity in the carioca germplasm

    Genome-wide association study reveals a set of genes associated with resistance to the Mediterranean corn borer (Sesamia nonagrioides L.) in a maize diversity panel

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    Applying genetic markers for self-compatibility in the WSU sweet cherry breeding program

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    Sweet cherry (Prunus avium) is a member of the Rosaceae family, with a gametophytic self-incompatibility system that strongly affects pollination and fruit set. Alleles at the S-locus control this system, and fertilization does not occur if the Sallele of a haploid pollen gamete matches either S-allele of the diploid maternal pistil. To produce fruit, self-incompatible cherry trees require nearby crosscompatible trees with synchronous flowering. In cherry orchards, two or more cross-compatible pollinizer cultivars are therefore usually inter-planted with the main cultivar. Fortunately, self-compatibility exists, the result of a mutation of one of the alleles at the S-locus, permitting the breeding of self-compatible cultivars that do not require pollinizer trees. The Washington State University (WSU) sweet cherry breeding program seeks to produce self-compatible cultivars (in addition to superior fruit quality and other trait improvements) and desires an early detection system for self-compatible seedlings. PCR-based S-genotyping that included primers for detecting self-compatibility was conducted for 243 seedlings from crosses made in 2004 that initiated this modern breeding program. While self-compatible seedlings were identified, a large proportion of seedlings resulted from unintended parentage, with implications for future breeding strategies

    Meta-QTL for resistance to white mold in common bean

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    <div><p>White mold, caused by the fungus <i>Sclerotinia sclerotiorum</i> (Lib.) de Bary, is a major disease that limits common bean production and quality worldwide. The host-pathogen interaction is complex, with partial resistance in the host inherited as a quantitative trait with low to moderate heritability. Our objective was to identify meta-QTL conditioning partial resistance to white mold from individual QTL identified across multiple populations and environments. The physical positions for 37 individual QTL were identified across 14 recombinant inbred bi-parental populations (six new, three re-genotyped, and five from the literature). A meta-QTL analysis of the 37 QTL was conducted using the genetic linkage map of Stampede x Red Hawk population as the reference. The 37 QTL condensed into 17 named loci (12 previously named and five new) of which nine were defined as meta-QTL WM1.1, WM2.2, WM3.1, WM5.4, WM6.2, WM7.1, WM7.4, WM7.5, and WM8.3. The nine meta-QTL had confidence intervals ranging from 0.65 to 9.41 Mb. Candidate genes shown to express under <i>S</i>. <i>sclerotiorum</i> infection in other studies, including cell wall receptor kinase, <i>COI1</i>, ethylene responsive transcription factor, peroxidase, and MYB transcription factor, were found within the confidence interval for five of the meta-QTL. The nine meta-QTL are recommended as potential targets for MAS for partial resistance to white mold in common bean.</p></div
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