Dreisigacker, Susanne, 2019, "Multiplication trial of the 49TH IBWSN – Gene-based marker data for marker-assisted selection", https://hdl.handle.net/11529/10548171, CIMMYT Research Data & Software Repository Network, V3, UNF:6:+9rN5vb/ENHOa2kb9GmZwg== [fileUNF]
Centro Internacional de Mejoramiento de Maíz y Trigo (CIMMYT), 'Report of an ARPT/CIMMYT networkshops on the role of rural sociology and anthropology in farming systems research and extension', iii, 116 pages, CIMMYT Eastern and Southern Africa Economics Programme, 1985
De Almeida, G. D., Nair, S. K., Borém, A., Cairns, J. E., Trachsel, S., Ribaut, J., Bänziger, M., Prasanna, B. M., Crossa, J., & Babu, R. (2014). Molecular mapping across three populations reveals a QTL hotspot region on chromosome 3 for secondary traits associated with drought tolerance in tropical maize. *Molecular Breeding*, 34(2), 701-715. https://doi.org/10.1007/s11032-014-0068-5
Wichern, J., Van Wijk, M. T., Descheemaeker, K., Frelat, R., Van Asten, P. J. A., & Giller, K. E. (2017). Food availability and livelihood strategies among rural households across Uganda. *Food Security*, 9(6), 1385-1403. https://doi.org/10.1007/s12571-017-0732-9
Archana, K. A., Kuchanur, P. H., Zaidi, P. H., Mandal, S. S., Arunkumar, B., Patil, A., Seetharam, K., & Vinayan, M. T. (2018). Stability for grain yield and other traits in tropical maize (Zea mays L.) under heat stress and optimal conditions. *International Journal of Current Microbiology and Applied Sciences*, 7(11), 815-823. https://doi.org/10.20546/ijcmas.2018.711.096
Dracatos, P. M., Haghdoust, R., Singh, R. P., Huera Espino, J., Barnes, C. W., Forrest, K., Hayden, M., Niks, R. E., Park, R., & Singh, D. (2019). High-density mapping of triple rust resistance in barley using DArT-Seq markers. *Frontiers in Plant Science*, 10, 467. https://doi.org/10.3389/fpls.2019.00467
Chipindu, L., Mupangwa, W., Mtsilizah, J., Nyagumbo, I., & Zaman‐Allah, M. (2020). Maize kernel abortion recognition and classification using binary classification machine learning algorithms and deep convolutional neural networks. *AI*, 1(3), 361-375. https://doi.org/10.3390/ai1030024
Labudda, M., Tokarz, K., Tokarz, B., Muszyńska, E., Gietler, M., Górecka, M., Różańska, E., Rybarczyk-Płońska, A., Fidler, J., Prabucka, B., Dababat, A. A., & Lewandowski, M. (2020). Reactive oxygen species metabolism and photosynthetic performance in leaves of Hordeum vulgare plants co-infested with Heterodera filipjevi and Aceria tosichella. *Plant Cell Reports*, 39(12), 1719-1741. https://doi.org/10.1007/s00299-020-02600-5
Abay, K. A., Asnake, W., Ayalew, H., Chamberlin, J., & Sumberg, J. (2021). Landscapes of opportunity: patterns of young people’s engagement with the rural economy in sub-Saharan Africa. *Journal of Development Studies*, 57(4), 594–613. https://doi.org/10.1080/00220388.2020.1808195
Sajji, S.; Nagaraji, S., 'Stakeholder consultation workshop on "Co-Lab: the virtual collaboration platform for Digital Agri-food Systems" in Pune, India', 16 pages, CGIAR, IFPRI, 2023
Yahaya, M. A., Shimelis, H., Nebie, B., Ojiewo, C. O., Rathore, A., & Das, R. R. (2023). Genetic diversity and population structure of African sorghum (sorghum bicolor L. moench) accessions assessed through single nucleotide polymorphisms markers. *Genes*, 14(7), 1480. https://doi.org/10.3390/genes14071480
Ndlovu, N., Kachapur, R. M., Beyene, Y., Das, B., Ogugo, V., Makumbi, D., Spillane, C., McKeown, P. C., Prasanna, B. M., & Gowda, M. (2024). Linkage mapping and genomic prediction of grain quality traits in tropical maize (Zea mays L.). *Frontiers In Genetics*, 15, 1353289. https://doi.org/10.3389/fgene.2024.1353289