3.8 Article

LIQUID SWINE MANURE APPLICATION VARIABILITY: CHALLENGES AND OPPORTUNITIES

期刊

JOURNAL OF THE ASABE
卷 65, 期 4, 页码 715-722

出版社

AMER SOC AGRICULTURAL & BIOLOGICAL ENGINEERS
DOI: 10.13031/ja.14674

关键词

Manure application; Manure management; Manure nutrient content; Manure nutrient sensing; Manure rate calibration

资金

  1. Leopold Center for Sustainable Agriculture
  2. Iowa Nutrient Research Center

向作者/读者索取更多资源

Liquid livestock manure application presents challenges in achieving target nitrogen application rate due to variability in nutrient content, equipment adjustments, and field conditions. Using average of previous years' manure samples improved accuracy for phosphorus, but no significant difference was found for nitrogen. This study highlights the need for real-time manure nutrient sensing and on-the-go rate adjustment.
Liquid livestock manure application presents both opportunities for replacing commercial fertilizer and challenges to doing so accurately. This study demonstrated the challenges in achieving a target N application rate using liquid swine manure on eighteen 0.4 ha research plots at the Northeast Research and Demonstration Farm (NERF) near Nashua, Iowa. Differences between the nufrient analyses of manure from a pre-application sample and samples taken on the day of application, equipment adjustments, field conditions, and changing manure nutrient content during pit pumping contributed to variability in the actual N rate applied. The coefficient of variability (CV) of manure N during manure pumping ranged from 2.7 to 13.6, with an 8-year average of 6.5. A weighted-average CV for applied manure volume ranged from 1.5 to 4.7, with an 8-year average CV of 3.2, suggesting that plot-to-plot variability in manure volume was less of an issue for achieving the target N rate than was the variability of manure Non the day of application. A separate analysis of manure from six Iowa swine farms showed that using the average of the previous years' manure samples improved accuracy for phosphorus at Farm 2, whereas using a single sample from the application year improved accuracy for potassium at Farm 5. Averaged across the six farms, using the average of the previous years' manure samples resulted in less error for phosphorus than using a single sample from the application year. For nitrogen, there was no significant difference between the two approaches within or across farms (p < 0.1). The average economic loss from missing the target N rate in the NERF study was $34.27 +/- $32.49 ha(-1) year(-1) ($13.87 +/- $13.15 ac(-1) year(-1)). The estimated economic value from using real-time nutrient sensing to improve N rate accuracy ranged from $7.56 to $32.03 ha(-1) ($3.06 to $12.96 ac(-1)) in a corn-soybean rotation and from $10.38 to $44.41 ha(-1) ($4.20 to $17.97 ac(-1)) in continuous corn. This study illustrates the need for new technologies for real-time manure nutrient sensing and on-the-go rate adjustment. The economic analysis can serve as a guide for manure applicators when evaluating the feasibility of manure nutrient-sensing systems.

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