5 Works

Profitability Analysis of Traditional African Vegetable Seeds Production in Kenya

Henry Myungi, Alaik Laizer, Philipo J. Lukumay, Justus Ochieng, Godfrey Ngoteya, Fekadu Dinssa, James E. Simon, Ramu Govindasamy, Christine Ndinya & Martins Odendo

Assessment of Seed Quality of Selected African Leafy Vegetables Produced in Western Kenya using informal and semi-formal seed systems

Christine Ndinya, Fekadu Dinssa, James E. Simon, Naman Nyabinda, Norah Maiyo, Stephen Weller, Martins Odendo, Eunice Onyango, Michael Mwangi & Noel Makete

Improving Income and Nutrition of Smallholder Farmers in Eastern Africa using a Market-First Science-Driven Approach to Enhance Value Chain Production of African Indigenous Vegetables

James E. Simon, Stephen Weller, Daniel Hoffman, Ramu Govindasamy, Xenia Morin, Emily V. Merchant, Fekadu F. Dinssa, Emil Van Wyk, David Byrnes, Martins Odendo, Christine Ndinya, Henry H.A. Mvungi, Justus Ochieng, Norah Maiyo, Mebelo Mataa, John Shindano, Himoonga Bernard Moonga, J. Steve Yaninek, Qingli Wu, Naman Nyabinda & Victor Afari-Sefa

Participatory Farmer Evaluation of Selected African Indigenous Vegetables for Enhanced Food and Nutrition Security in Western Kenya

Francis Wayua, Christine Ndinya, Noel Makete, Martins Odendo, Eunice Onyango, Maurice Mudeheri, Elias Thuranira, Ludovicus Okitoi, Samuel Akolo & Suleiman Kweyu

A machine learning approach to integrating genetic and ecological data in tsetse flies (Glossina pallidipes) for spatially explicit vector control planning

Anusha Bishop, Giuseppe Amatulli, Chaz Hyseni, Evlyn Pless, Rosemary Bateta, Winnie Okeyo, Paul Mireji, Sylvance Okoth, Imna Malele, Grace Murilla, Serap Aksoy & Norah Saarman
Introduction - Control of vector populations is an effective strategy for addressing vector-borne disease transmission. Effective vector control requires knowledge of habitat use and connectivity. Our goal was to improve this knowledge for the tsetse species Glossina pallidipes, a vector of animal African trypanosomiasis, which is a wasting disease in livestock and represents a serious socioeconomic burden across sub-Saharan Africa. Methods and Results - We used random forest regression to: (i) Build and integrate models...

Registration Year

  • 2021

Resource Types

  • Text
  • Dataset


  • Kenya Agricultural and Livestock Research Organization
  • World Vegetable Center
  • Rutgers, The State University of New Jersey
  • Purdue University System
  • Utah State University
  • Vector & Vector-Borne Diseases Research Institute
  • University of California, Berkeley
  • Maseno University
  • University of Zambia
  • Yale University