Assessment of Yield and Nutritional Qualities of Local and Improved Maize Varieties Cultivated in Wukari and Environement of the Nigerian Guinea Savanna Agro-Ecology






1998 ◽  
Vol 34 (4) ◽  
pp. 407-422 ◽  
Author(s):  
R. J. CARSKY ◽  
S. NOKOE ◽  
S. T. O. LAGOKE ◽  
S. K. KIM

Farmer-managed tests of Striga hermonthica-resistant maize varieties were conducted in 1994 in a moderately intensified zone in the northern Guinea savanna of Nigeria. Field history, soil properties, current season fertility management, and crop management observations were recorded for 37 farmer-managed trials. Site averages for maize grain yield varied from 300 to 4000 kg grain ha−1. In spite of the tremendous variability observed, the grain yield was significantly higher for the striga-resistant hybrid 8321-18 compared with an improved open-pollinated variety, STR Syn-W, and the farmers' current variety. Correlation analysis and stepwise regression analysis of grain yield on measured variables suggested that maize yield was a function of plant density for all three varieties. The rate of nitrogen fertilizer application was an important variable only for the hybrid, while the day of first weeding was most important for the improved varieties. The yield of the local varieties and STR Syn-W was related to the number of emerged striga at harvest in the stepwise regression, and the yield of the local varieties was highly correlated with the striga-damage score on maize. The striga-damage score was significantly lower on 8321-18 than on the other varieties, suggesting some degree of resistance in the hybrid. The number of emerged striga was lower for the hybrid but not significantly different. Farmers were almost unanimous in ranking the hybrid as least damaged by striga and highest yielding. Besides being related to maize variety, striga-damage score was lower if crop residue was observed on the field at the time of site confirmation. Highest yields (approximately 4 t ha−1) were recorded on fields near the homestead (compound fields) where soil organic carbon values were 2.0–2.5%. Realization of maize yield potential in the absence of manure or fertilizer will only be possible on long-term compound fields. Striga-resistant maize can maintain high yields under S. hermonthica infestation.



2012 ◽  
Vol 2 (2) ◽  
pp. 14-21 ◽  
Author(s):  
Bello O. B. ◽  
Abdulmaliq S. Y. ◽  
Ige S. A. ◽  
Mahamood J. ◽  
Oluleye F. ◽  
...  


2003 ◽  
Vol 22 (3) ◽  
pp. 533-538 ◽  
Author(s):  
N.C Kuchinda ◽  
I Kureh ◽  
B.D Tarfa ◽  
C Shinggu ◽  
R Omolehin


Agronomy ◽  
2020 ◽  
Vol 10 (6) ◽  
pp. 871 ◽  
Author(s):  
Abdullahi I. Tofa ◽  
Uche F. Chiezey ◽  
Bashir A. Babaji ◽  
Alpha Y. Kamara ◽  
Adnan A. Adnan ◽  
...  

The Crop Environment Resource Synthesis (CERES)-Maize model in Decision Support System for Agricultural Technology Transfer (DSSAT) was calibrated and evaluated with experimental data for simulation of response of two intermediate-maturing maize varieties to different sowing dates in the Nigerian savannas. The calibration experiments involved 14 consecutive field trials conducted in the rainy and dry seasons in Bayero University Kano (BUK), Dambatta, and Zaria between 2014–2019. Two sets of field experiments were conducted simultaneously for model evaluation in Iburu in the southern Guinea savanna zone and Zaria in the northern Guinea savanna zone during 2015 and 2016 cropping seasons. The experiments for calibration had two maize (SAMMAZ-15 and SAMMAZ-16) varieties planted under optimum conditions with no water and nutrients stresses. The trials for model evaluation were conducted using the same varieties under four different nitrogen (N) rates (0, 60, 120 and 180 kg N ha−1). A 30-year (1985–2014) term simulation was performed to determine effect of varying sowing dates on yields of two maize varieties (SAMMAZ-15 and SAMMAZ-16) in the Sudan savanna (SS), northern Guinea savanna (NGS), and southern Guinea savanna (SGS) zones. The calibration results showed that the cultivar coefficients of the two maize varieties resulted in simulated growth and development parameters that were in good agreement with observed parameters. Model evaluation showed a good agreement between simulated and observed data for phenology and growth of maize. This demonstrated the potential of the CERES-Maize model to simulate growth and yield of maize in the Nigeria savannas. Results of 30-year sensitivity analysis with 9 different sowing windows showed that in SS, sowing the intermediate maize varieties from early to mid-June produced the highest grain yields. In NGS, the optimum sowing windows were found between late June and late July for the both varieties. In SGS, the optimum sowing window is from early June to late July for SAMMAZ-15 and mid-June to late July for SAMMAZ-16. These planting windows gave the highest long-term average yields for each variety. The variety SAMMAZ-15 was found to be best performing across the three agro-ecologies. Maize performance was generally higher in NGS than in SGS. SS in the Sudan savanna recorded the lowest yield compared with other locations.



2013 ◽  
Vol 33 (2) ◽  
pp. 12 ◽  
Author(s):  
SSJ Buah ◽  
JM Kombiok ◽  
RAL Kanton ◽  
NN Denwar ◽  
A Haruna ◽  
...  


2004 ◽  
Vol 52 (2) ◽  
pp. 157-163
Author(s):  
C. U. Egbo ◽  
M. A. Adagba ◽  
D. K. Adedzwa

Field trials were conducted in the wet seasons of 1997 and 1998 at Makurdi, Otukpo and Yandev in the Southern Guinea Savanna ecological zone of Nigeria to study the responses of ten soybean genotypes to intercropping. The experiment was laid out in a randomised complete block design. The genotypes TGX 1807-19F, NCRI-Soy2, Cameroon Late and TGX 1485-1D had the highest grain yield. All the Land Equivalent Ratio (LER) values were higher than unity, indicating that there is great advantage in intercropping maize with soybean. The yield of soybean was positively correlated with the days to 50% flowering, days to maturity, plant height, pods/plant and leaf area, indicating that an improvement in any of these traits will be reflected in an increase in seed yield. There was a significant genotype × yield × location interaction for all traits. This suggests that none of these factors acted independently. Similarly, the genotype × location interaction was more important than the genotype × year interaction for seed yield, indicating that the yield response of the ten soybean genotypes varied across locations rather than across years. Therefore, using more testing sites for evaluation may be more important than the number of years.



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