[01] Samuel Jerry Odindo, Department of Health System Management, Faculty of Community Health and Development, Great Lakes University of Kisumu, Kisumu, Kenya. [02] Aaron Mwayi, Department of Health Promotion, Faculty of Community Health and Development, Great Lakes University of Kisumu, Kisumu, Kenya. [03] Dan Odindo, Department of Health System Management, Faculty of Community Health and Development, Great Lakes University of Kisumu, Kisumu, Kenya. [04] Winnie Otieno, Department of Environmental Health, Faculty of Community Health and Development, Great Lakes University of Kisumu, Kisumu, Kenya. [05] Caro Akinyi, Department of Research and Measurement, Faculty of Community Health and Development, Great Lakes University of Kisumu, Kisumu, Kenya. [06] Jeremy Nzanzu, Department of Research and Measurement, Faculty of Community Health and Development, Great Lakes University of Kisumu, Kisumu, Kenya. [07] Noah Adera, Programming, Data Management and Analysis, Monitoring and Evaluation Food Security Programme, Kisumu, Kenya.

This is a Monitoring and Evaluation research that monitored the same households for the second seasons and displayed the information to the farmers on a noticeboard as a way of sensitizing them on good farm management practices. Key findings were analyzed and used to determine the quarterly Adoption-Trend’s depicted from the harvest quantities, the impact of the noticeboard intervention on the harvest, to compare the Seasonality on Adoption (CAN quantities used) - Dry verse Wet seasons, to evaluate Storage and usage of the harvest in relation to the food security and to compare the effects of intervention in relation to the Kisumu regional harvest. Census was done for the 570 households. Frequency was run using SAS and STATA and Chi square test to determine the associations of farmindicators, such as quantity of fertilizer and seeds application on the production of maize, beans, groundnuts and vegetables. Descriptive analysis was conducted to determine and compare the harvest in the intervention sites to the rest of the place in Kisumu where the intervention was not affected. Logistic regression analysis was used to determine the significant influence of the variables on the production of monitored food crops. Comparative analysis was used to test the null hypothesis on the statistic significant between first season and second season.

Monitoring Food Security, Information Asymmetry, Food Production, Target Plan

[01] Agritourism: Potential Socio-Economic Impacts in Kisumu County. [02] Data from Agricultural Sector Development Support Programme (ASDSP)-Kisumu County. [03] Data from Kenya Agricultural Value Chains Enterprises Project-Kisumu West. [04] ITU-T Technology watch report July 2009, ICTs and Food Security. [05] Kenya National Bureaus of statistics (2008), Food Insecurity Assessment in Kenya based on Kenya Integrated householdbudget surveys (2005/2006). [06] Kisumu County, Kenya. Universal journal of medical Science. [07] National figures on food production. [08] NzanzuJeremie., Dan Kaseje, Rose Olayo and Caro Akinyi (2014). Utilization of Community- based Health Information System in Decision making and Health Action in Nyalenda. [09] African farm radio research initiative 2011, Participatory Radio Campains and Food Security, African farm. [10] Odindo, S, J., Odindo, D, O and Mwayi, A., (2014). The role of information asymmetry in monitoring food security programme in Bar A sub location Kisumu county. [11] Odindo, S, J., Mwayi, A., Odindo, D, O, Otieno, W., Akinyi, C and Nzanzu J.(2014). The role of information asymmetry in monitoring food security programme in Bar A sub location Kisumu county, second season harvest 2014.