Finger Millet (Eleucine coracana) Yield Estimation: Integrating Remote Sensing and Farm Management Practices in Busia-Kenya

R. M. Kweyu


Early crop yield prediction is important for planning and taking various decisions by the farmer. Conventional techniques of data collection for crop monitoring and yield estimation rely on ground-based visits and reports. These methods are subjective, very costly and time consuming. With the launching of satellites, remotely sensed data is being used for crop monitoring and yield prediction. This study applied space-borne satellite based NDVI to predict crop yield at field level. It was carried out in Kenya’s Busia County. The purpose of the study was to investigate the relationship between space-borne Satellite based NDVI and Finger millet (Eleucine coracana) yield and combining NDVI with farmer’s indigenous knowledge (IK) and practices for yield prediction at field level. A survey was carried out to investigate management and land factors in Finger millet growing area during the long rains growing season, January- June 2014. This was followed by satellite image analysis of farms during different stages of Finger millet growth. Data collected was correlated against Finger millet yield in order to analyse the relationships among Remote sensed data, indigenous practices and crop yield. The results showed that there is significant correlation between remotely sensed NDVI and field level finger millet yield (r = 0.19, p =0.040, N = 57). The most yielding farms were those with mixed variety of seed (i.e local and improved u15 variety) and broadcasting as a planting technique. The study also showed that not all the factors affecting yield also affect NDVI. This paper concludes that remote sensing can be used as a tool for monitoring crop growth and vigor based on different farm management practices. The paper further suggests that the integration of farmer IK in the management of finger millet crop and use of mixed variety of seed is likely to improve yield.


Eleucine coracana, Remote Sensing, Indigenous Knowledge

Full Text:



De Wit, A. J. W. and Boogaard, H. L. (2004). Monitoring of crop development and crop model optimisation using NOAA - AVHRR : towards an integrated satellite and model - based crop monitoring system. Delft: Beleids Commissie Remote Sensing (BCR)

Doorenbos, J. and Pruitt, W. O. (1977). Crop water requirements, FAO Irrigation and Drainage Paper, 24, Rome

Fetene, M., Okoro, P., Gudu, S., Mneney, E. and Tesfaye, K. (2011). ‘Delivering new sorghum and Finger millet innovations for food security and improving livelihoods in East Africa’. Nairobi, Kenya

FAO, FAOSTAT (2008). "Food and agriculture organisation of the United Nations." Retrieved on 15 February (2008).

Food and Agriculture Organization of the United Nations (2008). The state of Food Insecurity in the World 2008: High Food Prices and Food Security –Threats and opportunities. FAO. Rome

Fratkin, E. and Mearns, R. (2003). Sustainability and Pastoral Livelihoods: Lessons from East African Maasai and Mongolia, Human Organization, Vol. 62, No. 2, 2003

Janssen, L. L. F. and Huurneman, G. C. (Eds.). (2001). ''Principles of remote sensing'' : an introductory textbook (2 ed.). Enschede: ITC

Jätzold, R. and Schmidt, H. (1982). Farm management handbook of Kenya, Vol. II, Part A, Rossdorf/Nairobi

Lawler, A. (2009). ‘Bridging East and West: Millet on the move’. Science, 942-943.

Mather, P. (2004). 'Computer Processing of Remotely-Sensed Images: An Introduction John Wiley

Ministry of Agriculture (1995). Guidelines for agricultural production, Government printer, Nairobi

Mukarumbwa, P. And Mushunje A. (2011). Potential of Soghurm and Finger Millet to enhance household food security in Zimbabwe semi arid regions. Department of Agricultural Econoomics and Extension. University of Fort Hare, Republic of South Africa.

Pringle, R.M. (2005). The origins of the Nile perch in Lake Victoria. In BioScience 55:780-787

Schuler, R. T. (2002). Remote Sensing Experiences in Production Fields. Date accessed: 20-12-2013

Singh, R., Semwali, D. P., Rai, A. and Chhikara, R. S. (2002). Small area estimation of crop yield using remote sensing satellite data. In International Journal of Remote Sensing, 23(1) (2002): 49-56.


  • There are currently no refbacks.

© 2015 School of Environmental Studies all rights reserved. Permission should be sought from the publishers before any of this work or part of it is reproduced, transmitted in any form or by any means, electronic or mechanical, microfilming and recording, or by any information storage and retrieval system.