294-2 Meta-Analysis As a Tool to Study Crop Productivity Response to Poultry Litter Application.
Poster Number 224
See more from this Division: ASA Section: Biometry and Statistical Computing
See more from this Session: Biometry and Statistical Computing: II
Tuesday, November 17, 2015
Minneapolis Convention Center, Exhibit Hall BC
Abstract:
Extensive research on the use of poultry litter (PL) under different agricultural practices in the USA has shown both negative and positive effects on crop productivity (either yield or aboveground biomass). However, these experimental results are substantially dependent on the experimental set-up, soil properties, and management systems, which determines the need for a comprehensive quantitative review. The objective of this study was to use meta-analytic methods to summarize and quantitatively describe the effect of PL on crop yield based on peer-reviewed published and unpublished research. Eighty studies, totaling 842 data sets were included in this analysis representing different region of the world, primarily the USA under different agricultural practices (i.e., crop species, tillage, application method, and application time, etc.). A separate analysis was conducted to study the effect of soil type, tillage method, poultry litter application rate, or crop in addition to the effect of poultry litter on crop yield. In loam soil, poultry litter had a significant positive effect whereas the effect in clay and sandy soils were negative; no significance was observed in silt soils. Under conventional tillage, mineral fertilizer had a positive effect on crop yield, albeit not significantly so, whereas poultry litter had a significant positive effect in strip-till or no-till situations. Poultry litter and mineral fertilizer application were matched for total applied N. The magnitude of the positive poultry litter effect was linked to rate. Among the agronomic crop in these studies, poultry litter had a positive effect on corn, cotton, soybean, and peanuts, but a negative effect on yield in barley and wheat.
See more from this Division: ASA Section: Biometry and Statistical Computing
See more from this Session: Biometry and Statistical Computing: II