|Egli, Dennis -|
Submitted to: Agronomy Journal
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: October 25, 2013
Publication Date: March 6, 2014
Repository URL: http://handle.nal.usda.gov/10113/58646
Citation: Egli, D.B., Hatfield, J.L. 2014. Yield gaps and yield relationships in US soybean production systems. Agronomy Journal. 106(2):560-566. Interpretive Summary: There is a demand for increasing production from agricultural lands in order to meet the increasing demand for food, feed, and fiber; however, we don’t always consider the limitations to yield and the reasons for the yield variation. A study was conducted to evaluate different methods of evaluating the yield gap as defined as the difference between the potential yield and the actual yield. We used an analysis of the county level yields for soybean from Iowa, Kentucky, and Nebraska (irrigated lands only) to define the attainable potential yield and found the yield gap varied across years and the yield gap decreased as the county level yields increased. The ability to attain the yield potential was related to the quality of the soil as defined by a productivity index which is used by the Natural Resource Conservation Service (NRCS) to evaluate different soils. Results from Iowa and Kentucky showed a strong relationship to soil quality; however, this was not true in Nebraska because the addition of irrigation water overcame the impact of the natural soil conditions on soybean yield. This research will be of interest to researchers, consultants, and producers as they strive to increase crop yields.
Technical Abstract: The magnitude of yield gaps (YG) (potential yield – farmer yield) provides some indication of the prospects for increasing crop yield to meet the food demands of future populations. Quantile regression analysis was applied to county soybean [Glycine max (L.) Merrill] yields (1971 – 2011) from Kentucky, Iowa, and Nebraska (irrigated only) to estimate the attainable potential yield (APY) (yield in the most favorable environments in the 40-yr record). The YG for each year in each county was the difference between the APY and the county yield. There was substantial variation in the 40-yr mean county yields (186 to 335 g m-2) within and among states. The mean county APY within each state increased linearly (significant at p < 0.0001) in conjunction with mean county yields. The mean YGs varied from 9 to 24% of APY and were largest in the lowest yielding counties and they decreased linearly (p< 0.0001) as the mean county yield increased for each state. The large YGs in some counties were partially related to very low yields that occurred in some years during the 40-yr period. These YGs may partially reflect the ability of the soil to supply water to the crop. The difference between the maximum APY in each state and each county APY defined a second YG. The largest values ranged from 12 to 19% of the maximum APY. Irrigation should partially eliminate the first YG, but the second may be more intractable to the degree it is related to soil characteristics. These results suggest that soil conditions may play an important role in determining the size of YGs.