|Tapela, Mataba - BOTSWANA COLLEGE OF AGRIC|
Submitted to: International Conference on Precision Agriculture Abstracts & Proceedings
Publication Type: Proceedings
Publication Acceptance Date: July 17, 2002
Publication Date: July 17, 2002
Citation: TAPELA, M., COLVIN, T.S., KARLEN, D.L. SPATIAL AND TEMPORAL VARIABILITY IN CORN YIELD GROWN UNDER DIFFERENT TILLAGE SYSTEMS. INTERNATIONAL CONFERENCE ON PRECISION AGRICULTURE ABSTRACTS & PROCEEDINGS. 2002. CD-ROM. MADISON, WI. Technical Abstract: Multiple years of yield data from the same field usually exhibits both spatial and temporal variability in yield. This study was conducted to determine if yield maps, in combination with soil information, would explain the annual variation in corn (Zea mays L.) yield. The data were from a field study conducted on Typic Hapludolls and Typic Haplaquolls soils between 1998 and 2000. Yield from five tillage treatments (moldboard, chisel, till-plant, slot-plant, spring disk), each with four replications, was compared using randomized complete block design. Analysis of variance showed no significant differences in mean yield among the tillage treatments in 1998 (p=0.275) and 2000 (p=0.150). Significant yield differences were observed in 1999 (p<0.0001). Corn yield under moldboard tillage was highest at 9.96 Mg ha**-1 and lowest under slot-planting with a yield of 7.75 Mg ha**-1. A paired t-test showed no significant differences in mean yield between soil types in 1998 (p=0.106) and 1999 (p=0.257). However, significant differences in yield due to soil type were found in 2000 (p=0.0001). Visual interpretation of yield maps with soil map unit overlays supported both statistical analyses. Season had a significant effect on yield; interaction between season and tillage was present. Significant differences in bulk density and penetration resistance influenced the mean yield for each treatment. Soil moisture levels in all treatments for 1998 and 1999 were not significantly different, but in 2000 there were significant differences (p=0.0185). This study shows that soils and yield maps can be used to better understand results obtained by statistical methods.