Kernel size and shape are important parameters determining the wheat profitability, being main determinants of yield and its technological quality. In this study, a segregating population of 118 recombinant inbred lines, derived from a cross between the Iranian durum landrace accession “Iran_249” and the Iranian durum cultivar “Zardak”, was used to investigate durum wheat kernel morphology factors and their relationships with kernel weight, and to map the corresponding QTLs. A high density genetic map, based on wheat 90k iSelect Infinium SNP assay, comprising 6,195 markers, was developed and used to perform the QTL analysis for kernel length and width, traits related to kernel shape and weight, and heading date, using phenotypic data from three environments. Overall, a total of 31 different QTLs and 9 QTL interactions for kernel size, and 21 different QTLs and 5 QTL interactions for kernel shape were identified. The landrace Iran_249 contributed the allele with positive effect for most of the QTLs related to kernel length and kernel weight suggesting that the landrace might have considerable potential toward enhancing the existing gene pool for grain shape and size traits and for further yield improvement in wheat. The correlation among traits and co-localization of corresponding QTLs permitted to define 11 clusters suggesting causal relationships between simplest kernel size trait, like kernel length and width, and more complex secondary trait, like kernel shape and weight related traits. Lastly, the recent release of the T. durum reference genome sequence allowed to define the physical interval of our QTL/clusters and to hypothesize novel candidate genes inspecting the gene content of the genomic regions associated to target traits.
in agricoltura e l'analisi dell'economia agraria (CREA),
Parole chiave: Condizionalità; sviluppo rurale; Standard 2.1; gestione delle stoppie e dei residui colturali; competitività.Lavoro svolto nell'ambito del Progetto MO.NA.CO. (Rete di monitoraggio nazionale dell'efficacia ambientale della condizionalità e del differenziale di competitività da essa indotto a carico delle imprese agricole) finanziato dal Ministero delle Politiche Agricole, Alimentari e Forestali (MiPAAF) nell'ambito del Programma Rete Rurale Nazionale nel contesto dell'Azione 1.2.2 "Laboratori interregionali per lo sviluppo" del Programma Operativo denominato "Rete Rurale Nazionale 2007 -2013 Coord. Paolo Bazzoffi".Contributi: Domenico Ventrella: capofila Standard 2.1, coordinatore UO CREA-SCA, stesura del testo ed elaborazione dati delle UO, progettazione e allestimento dispositivo sperimentale: Francesco Montemurro:, coordinatore UO CREA-SSC, progettazione e allestimento dispositivo sperimentale, elaborazione dati, stesura del testo. Vittorio Alessandro Vonella: allestimento dispositivo sperimentali, conduzione agronomica, rilievi di campo, campionamenti. Luisa Giglio: rilievi di campo, campionamenti, elaborazione dati. Francesco Fornaro: rilievi di campo, campionamenti, elaborazione e georeferenziazione dati. Mirko Castellini: rilievi di campo, campionamenti, elaborazione dati. Rita Leogrande: rilievi di campo, campionamenti, elaborazione dati. Carolina Vitti: analisi chimiche del suolo (monitoraggio di SCA), elaborazione dati. Angelo Fiore: rilievi di campo, elaborazione dati, stesura del testo. Mariangela Diacono: rilievi di campo, elaborazione dati, stesura del testo. Marcello Mastrangelo: analisi chimiche del suolo (monitoraggio di SCA). Nino Virzì: coordinatore UO CREA-ACM, progettazione dispositivo sperimentale, rilievi di campo, stesura del testo. Francesco Intrigliolo:. già coordinatore UO CREA-ACM, progettazione dispositivo sperimentale. Massimo Palumbo: elaborazione dati e stesura del testo. Michele Cambrea: allestimento dispositivi sperimentali, conduzione agronomica, rilievi di campo, campionamenti. Alfio Platania: allestimento dispositivi sperimentali. Fabiola Sciacca: elaborazione dati. Stefania Licciardello: rilievi di campo, campionamenti, analisi qualitative. Antonio Troccoli: coordinatore UO CREA-CER, progettazione dispositivo sperimentale, rilievi di campo, elaborazione dati, stesura del testo. Mario Russo: rilievi di campo, elaborazione dati, stesura del testo. Rosa Francaviglia: coordinatore UO CREA-RPS, stesura del testo ed elaborazione dati. Ulderico Neri: allestimento delle prove sperimentali, rilievi di campo, rilievi differenziale competitività, stesura del testo ed elaborazione dati. Margherita Falcucci: analisi di laboratorio sui parametri chimici del suolo e dei vegetali. Giampiero Simonetti: allestimento delle prove sperimentali, rilievi differenziale competitività e rilievi di campo. Olimpia Masetti: analisi di laboratorio sui parametri biochimici e biologici del suolo. Gianluca Renzi: analisi di laboratorio sui parametri biochimici e biologici del suolo. Marisanna ...
Within the Project MO.NA.CO was evaluated the Environmental effectiveness of GAEC cross-compliance standard 2.2 “Maintaining the level of soil organic matter through crop rotation” and economic evaluation of the competitiveness gap for farmers who support or not the cross-compliance regime. The monitoring was performed in nine experimental farms of the Council for Agricultural Research and Economics (CREA) distributed throughout Italy and with different soil and climatic conditions. Were also evaluated the soil organic matter and some yield parameters, in a cereal monocropping (treatment counterfactual) and a two-year rotation cereal-legume or forage (treatment factual). The two-years application of the standard “crop rotations” has produced contrasting results with regards to the storage of soil organic matter through crop rotation and these were not sufficient to demonstrate a statistically significant effect of treatment in any of the farms considered in monitoring, only in those farms subjected to more years of monitoring was recorded only a slight effect of the standard as a trend. The variations of organic matter in soils in response to changes in the culture technique or in the management of the soil may have long lag times and two years of time are not sufficient to demonstrate the dynamics of SOM associated with the treatment, also in consideration of the large inter annual variability recorded in different monitored sites.
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