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Assessment of Management Options on Striga Infestation and Maize Grain Yield in Kenya

Published online by Cambridge University Press:  04 April 2018

Fred Kanampiu*
Affiliation:
Senior Scientist, International Institute of Tropical Agriculture, Nairobi, Kenya
Dan Makumbi*
Affiliation:
Senior Scientist, International Maize and Wheat Improvement Center, Nairobi, Kenya
Edna Mageto
Affiliation:
Graduate Student, Department of Agronomy, Iowa State University, Ames, IA 50011, USA
Gospel Omanya
Affiliation:
Senior Project Manager, African Agricultural Technology Foundation, Nairobi, Kenya
Sammy Waruingi
Affiliation:
Managing Director, DUDU East Africa Ltd, Thika, Kenya;
Peter Musyoka
Affiliation:
Project Officer, African Agricultural Technology Foundation, Nairobi, Kenya
Joel Ransom
Affiliation:
Professor and Extension Agronomist, North Dakota State University, Department of Plant Sciences, Fargo, ND 58108, USA
*
Authors for correspondence: Fred Kanampiu, International Institute of Tropical Agriculture, P.O. Box 30772-00100, Nairobi, Kenya. (Email: F.Kanampiu@cgiar.org)
Dan Makumbi, International Maize and Wheat Improvement Center, PO Box 1041-00621, Nairobi, Kenya. (Email: D.Makumbi@cgiar.org).
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Abstract

The parasitic purple witchweed [Striga hermonthica (Del.) Benth.] is a serious constraint to maize production in sub-Saharan Africa, especially in poor soils. Various Striga spp. control measures have been developed, but these have not been assessed in an integrated system. This study was conducted to evaluate a set of promising technologies for S. hermonthica management in western Kenya. We evaluated three maize genotypes either intercropped with peanut (Arachis hypogaea L.), soybean [Glycine max (L.) Merr.], or silverleaf desmodium [Desmodium uncinatum (Jacq.) DC] or as a sole crop at two locations under artificial S. hermonthica infestation and at three locations under natural S. hermonthica infestation between 2011 and 2013. Combined ANOVA showed significant (P<0.05) cropping system and cropping system by environment interactions for most traits measured. Grain yield was highest for maize grown in soybean rotation (3,672 kg ha−1) under artificial infestation and in D. uncinatum and peanut cropping systems (3,203 kg ha−1 and 3,193 kg ha−1) under natural infestation. Grain yield was highest for the Striga spp.-resistant hybrid under both methods of infestation. A lower number of emerged S. hermonthica plants per square meter were recorded at 10 and 12 wk after planting on maize grown under D. uncinatum in the artificial S. hermonthica infestation. A combination of herbicide-resistant maize varieties intercropped with legumes was a more effective method for S. hermonthica control than individual-component technologies. Herbicide-resistant and Striga spp.-resistant maize integrated with legumes would help reduce the Striga spp. seedbank in the soil. Farmers should be encouraged to adopt an integrated approach to control Striga spp. for better maize yields.

Information

Type
Weed Management
Creative Commons
Creative Common License - CCCreative Common License - BY
This is an Open Access article, distributed under the terms of the Creative Commons Attribution licence (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted re-use, distribution, and reproduction in any medium, provided the original work is properly cited.
Copyright
© Weed Science Society of America, 2018
Figure 0

Figure 1 Mean number of emerged S. hermonthica plants at 8, 10, and 12 wk after planting (WAP) for four cropping systems under artificial (A) and natural (B) S. hermonthica infestation for 3 yr (2011–2013). The whiskers represent SEs.

Figure 1

Table 1 Mean squares from combined ANOVA for agronomic traits and S. hermonthica counts under artificial S. hermonthica infestation at two locations (Kibos and Alupe) in Kenya across 3 yr (2011–2013).a

Figure 2

Table 2 Mean squares from combined ANOVA for agronomic traits and S. hermonthica counts under natural S. hermonthica infestation at three locations (Siaya, Teso, and Rachuonyo) in Kenya across 3 yr (2011–2013).a

Figure 3

Table 3 Mean grain yield and other agronomic traits for different treatment combinations under artificial and natural S. hermonthica infestation at five locations in Kenya across 3 yr (2011–2013).

Figure 4

Figure 2 Mean number of emerged S. hermonthica plants at 8, 10, and 12 wk after planting (WAP) for four maize varieties under artificial (A) and natural (B) S. hermonthica infestation for 3 yr (2011–2013). The whiskers represent SEs. IR hybrid, imazapyr-resistant maize hybrid; IR-OPV, imazapyr-resistant maize, open-pollinated variety; Striga hybrid, S. hermonthica-resistant maize hybrid; WH403, commercial maize hybrid.

Figure 5

Table 4 Kendall’s coefficient of concordance (W) for traits of maize varieties evaluated under different management options under artificial and natural S. hermonthica infestation in Kenya.

Figure 6

Figure 3 Mean S. hermonthica emergence at 8, 10, and 12 wk after planting (WAP) for four cropping systems under artificial S. hermonthica infestation at two locations for 3 yr (2011–2013). IR hybrid, imazapyr-resistant maize hybrid; IR-OPV, imazapyr-resistant maize, open-pollinated variety; S. hermonthica hybrid, S. hermonthica-resistant maize hybrid; WH403, commercial maize hybrid. The whiskers represent SEs.

Figure 7

Figure 4 Mean S. hermonthica emergence at 8, 10, and 12 wk after planting (WAP) for four cropping systems under natural S. hermonthica infestation at three locations for 3 yr (2011–2013). IR hybrid, imazapyr-resistant maize hybrid; IR-OPV, imazapyr-resistant maize, open-pollinated variety; Striga hybrid, S. hermonthica-resistant maize hybrid; WH403, commercial maize hybrid. The whiskers represent SEs.

Figure 8

Table 5 Mean grain yield and other agronomic traits for different treatment combinations under artificial and natural S. hermonthica infestation at five locations in Kenya across 3 yr (2011–2013).