Examinando por Autor "Guarino, Luigi"

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Adapting agriculture to climate change: A synopsis of coordinated national crop wild relative seed collecting programs across five continents
(MDPI, 2022-07-13) Eastwood, Ruth J.; Tambam, Beri B.; Aboagye, Lawrence Misa; Akparov, Zeynal I.; Aladele, Sunday E.; Allen, Richard; Amri, Ahmed; Anglin, Noelle L.; Araya, Rodolfo; Arrieta-Espinoza, Griselda; Asgerov, Aydin; Awang, Khadijah; Awas, Tesfaye; Barata, Ana Maria; Kwasi Boateng, Samuel; Magos Brehm, Joana; Breidy, Joelle; Breman, Elinor; Brenes Angulo, Arturo; Burle, Marília L.; Castañeda-Álvarez, Nora P.; Casimiro, Pedro; Chaves, Néstor F.; Clemente, Adelaide S.; Cockel, Christopher P.; Davey, Alexandra; De la Rosa, Lucía; Debouck, Daniel G.; Dempewolf, Hannes; Dokmak, Hiba; Ellis, David; Faruk, Aisyah; Freitas, Cátia; Galstyan, Sona; García, Rosa M.; Ghimire, Krishna H.; Guarino, Luigi; Harker, Ruth; Hope, Roberta; Humphries, Alan W.; Jamora, Nelissa; Ahmad Jatoi, Shakeel; Khutsishvili, Manana; Kikodze, David; Kyratzis, Angelos C.; León-Lobos, Pedro; Liu, Udayangani; Mainali, Ram P.; Mammadov, Afig T.; Manrique-Carpintero, Norma C.; Manzella, Daniele; Mohd Shukri, Mat Ali; Medeiros, Marcelo B.; Mérida Guzmán, María A.; Mikatadze-Pantsulaia, Tsira; Ibrahim Mohamed, El Tahir; Monteros-Altamirano, Álvaro; Morales, Aura; Müller, Jonas V.; Mulumba, John W.; Nersesyan, Anush; Nóbrega, Humberto; Nyamongo, Desterio O.; Obreza, Matija; Okere, Anthony U.; Orsenigo, Simone; Ortega-Klose, Fernando; Papikyan, Astghik; Pearce, Timothy R.; Pinheiro de Carvalho, Miguel A. A.; Prohens, Jaime; Rossi, Graziano; Salas, Alberto; Singh Shrestha, Deepa; Uddin Siddiqui, Sadar; Smith, Paul P.; Sotomayor Melo, Diego Alejandro; Tacán, Marcelo; Tapia, César; Toledo, Álvaro; Toll, Jane; Vu, Dang Toan; Tuong, Dang Vu; Way, Michael J.; Yazbek, Mariana; Zorrilla Cisneros, Cinthya; Kilian, Benjamin
The Adapting Agriculture to Climate Change Project set out to improve the diversity, quantity, and accessibility of germplasm collections of crop wild relatives (CWR). Between 2013 and 2018, partners in 25 countries, heirs to the globetrotting legacy of Nikolai Vavilov, undertook seed collecting expeditions targeting CWR of 28 crops of global significance for agriculture. Here, we describe the implementation of the 25 national collecting programs and present the key results. A total of 4587 unique seed samples from at least 355 CWR taxa were collected, conserved ex situ, safety duplicated in national and international genebanks, and made available through the Multilateral System (MLS) of the International Treaty on Plant Genetic Resources for Food and Agriculture (Plant Treaty). Collections of CWR were made for all 28 targeted crops. Potato and eggplant were the most collected genepools, although the greatest number of primary genepool collections were made for rice. Overall, alfalfa, Bambara groundnut, grass pea and wheat were the genepools for which targets were best achieved. Several of the newly collected samples have already been used in pre-breeding programs to adapt crops to future challenges.
Spatial patterns of diversity and genetic erosion of traditional cassava (Manihot esculenta Crantz) in the Peruvian Amazon: An evaluation of socio-economic and environmental indicators
(Springer Nature, 2007-02-23) Willemen, Louise; Scheldeman, Xavier; Soto Cabellos, Víctor; Rafael Salazar, Simón; Guarino, Luigi
This study evaluates quantitatively the suitability of the use of site-specific socio-economic and environmental data as indicators to rapidly assess patterns of diversity and genetic erosion risk in cassava. Socio-economic data as well as farmers’ estimation of genetic erosion were collected in the study area, the Ucayali region of the Peruvian Amazon, through interviews with 285 cassava farmers in 50 communities, while diversity was assessed based on agromorphological characterization of 295 cassava accessions. Using multivariate regression analyses, 50 and 45% of the variation in respectively diversity and genetic erosion estimation could be explained by a selected set of socio-economic and environmental indicators. In both regression models four out of the total of 38 variables proved to contribute significantly (at p < 0.10 level). Additionally, the study revealed that farmers are a good direct source of information on the diversity present at community level, which can contribute to the development of methodologies to assess diversity more rapidly. The results of this study are valuable for the development of models to rapidly assess diversity dynamics in large areas.