Resultados de búsqueda - Hearne, Sarah

Optimal units of selection – how many plants are representative of diversity in collections of cowpea landrace accessions? por Hearne, Sarah Jane, Franco, J., Magembe, E.

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Exploring the potential of genebank collections to address food system challenges por McCouch, Susan, Hearne, Sarah Jane, Wenzl, Peter

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Maize Landraces and Adaptation to Climate Change in Mexico por Hellin, Jonathan, Bellon, M.R., Hearne, Sarah Jane

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DNA fingerprinting for crop varietal identification: Fit-for-purpose protocols, their costs and analytical implications por Poets, Ana, Silverstein, Kevin, Pardey, Philip G., Hearne, Sarah, Stevenson, James R.

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CRISPR-mediated genome editing of wheat for enhancing disease resistance por Waites, Joshua O., Achary, Mohan Murali, David, Easter S., Hearne, Sarah, Bandyopadhyay, Anindya

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DNNGP, a deep neural network-based method for genomic prediction using multi-omics data in plants por Wang, Kelin, Abid, Muhammad Ali, Awais Rasheed, Crossa, José, Hearne, Sarah Jane, Huihui Li

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Introducing the non-rancidity trait into pearl millet seed : scenarios for achieving future impact in Kenya por Muindi, Pauline, Khaemba, Colleta, Rutsaert, Pieter, Donovan, Jason A., Bandyopadhyay, Anindya, Hearne, Sarah Jane

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Fast-forwarding plant breeding with deep learning-based genomic prediction por Gao, Shang, Yu, Tingxi, Rasheed, Awais, Wang, Jiankang, Crossa, Jose, Hearne, Sarah, Li, Huihui

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Editorial: Genomic selection: Lessons learned and perspectives por Martini, Johannes W. R., Hearne, Sarah Jane, Gardunia, Brian W., Wimmer, Valentin, Toledo, Fernando H.

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Artificial intelligence in plant breeding por Farooq, Muhammad Amjad, Shang Gao, Hassan, Muhammad Adeel, Zhangping Huang, Awais Rasheed, Hearne, Sarah, Prasanna, Boddupalli M., Xinhai Li, Huihui Li

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Using an indicator framework to assess organizational change in CGIAR breeding programs resulting from Accelerated Breeding 2022–2024 interventions por Quinn, Michael, De Col, Valentina, Coaldrake, Peter, Hearne, Sarah, Mbanjo, Gaby, Biswanath, Das, Ferguson, Morag E., Gemenet, Dorcus, Jacob, Neena, Bänziger, Marianne

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EXGEP: a framework for predicting genotype-by-environment interactions using ensembles of explainable machine-learning models por Yu, Tingxi, Zhang, Hao, Chen, Shoukun, Gao, Shang, Liu, Ze, Wang, Jiankang, Crossa, Jose, Montesinos-Lopez, Osval Antonio, Hearne, Sarah, Li, Huihui

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Maize Lethal Necrosis disease: review of molecular and genetic resistance mechanisms, socio-economic impacts, and mitigation strategies in sub-Saharan Africa por Biswal, Akshaya Kumar, Alakonya, Amos, Mottaleb, Khondoker Abdul, Hearne, Sarah Jane, Sonder, Kai, Molnar, Terence Luke, Jones, Alan M., Pixley, Kevin Vail, Boddupalli, P.M.

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Mining alleles for tar spot complex resistance from CIMMYT's maize Germplasm Bank por Willcox, Martha, Burgueño, Juan, Jeffers, Daniel, Rodríguez Chanona, Enrique, Guadarrama, Armando, Kehel, Zakaria, Chepetla, Daniel, Shrestha, Rosemary, Swarts, Kelly, Buckler, Edward S., Hearne, Sarah Jane, Chen, Charles

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Leveraging automated machine learning for environmental data-driven genetic analysis and genomic prediction in maize hybrids por He, Kunhui, Yu, Tingxi, Gao, Shang, Chen, Shoukun, Li, Liang, Zhang, Xuecai, Huang, Changling, Xu, Yunbi, Wang, Jiankang, Boddupalli, Prasanna, Hearne, Sarah, Li, Xinhai, Li, Huihui

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Identification, validation and high-throughput genotyping of transcribed gene SNPs in cassava por Ferguson, Morag E., Hearne, Sarah Jane, Close, T.J., Wanamaker, S., Moskal, W.A., Town, C.D., Young, J. de, Marri, P.R., Rabbi, Ismail Y., Villiers, Etienne P. de

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Environmental data provide marginal benefit for predicting climate adaptation por Li, Forrest, Gates, Daniel J., Buckler, Edward, Hufford, Matthew, Janzen, Garrett, Rellán-Álvarez, Rubén, Rodríguez-Zapata, Fausto, Romero Navarro, J. Alberto, Sawers, Ruairidh, Snodgrass, Samantha, Sonder, Kai, Willcox, Martha, Hearne, Sarah, Ross-Ibarra, Jeffrey, Runcie, Daniel

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The role of transposon inverted repeats in balancing drought tolerance and yield-related traits in maize por Sun, Xiaopeng, Xiang, Yanli, Dou, Nannan, Zhang, Hui, Pei, Surui, Valdés Franco, J. Arcadio, Menon, Mitra, Monier, Brandon, Ferebee, Taylor, Liu, Tao, Liu, Sanyang, Gao, Yuchi, Wang, Jubin, Terzaghi, William, Jianbing Yan, Hearne, Sarah Jane, Lin Li, Feng Li, Dai, Mingqiu

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Redesigning crop varieties to win the race between climate change and food security por Pixley, Kevin V., Cairns, Jill E., López Ridaura, Santiago, Ojiewo, Christopher Ochieng, Abba Dawud, Maryam, Drabo, Inoussa, Mindaye, Taye, Nebie, Baloua, Asea, Godfrey, Das, Biswanath, Daudi, Happy, Desmae, Haile, Batieno, Benoit Joseph, Boukar, Ousmane, Mukankusi, Clare T.M., Nkalubo, Stanley T., Hearne, Sarah Jane, Dhugga, Kanwarpal S., Gandhi, Harish, Snapp, Sieglinde, Zepeda Villarreal, Ernesto Adair

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Technical assistance to strengthen national agricultural research organizations’ capacity to use digital sequence information. A submission from CGIAR por López Noriega, Isabel, Rouard, Mathieu, Halewood, Michael, Sackville-Hamilton, N. Ruaraidh, Bhattacharjee, Ranjana, Carvajal Yepes, Monica, Domelevo Entfellner, Jean-Baka, Hearne, Sarah Jane, Hendre, Prasad, Kehel, Zakaria, Kreuze, Jan F., Kuldeep, Singh, Manish, Pandey, Muchugi, Alice, Ndjiondjop, Marie-Noelle, Ng, Eng Hwa, Odeny, Damaris Achieng, Sansaloni, Carolina Paola, Mayes, Sean, Wricha, Tyag, Ziyomo, Cathrine

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