Abstract
Soil test-based fertilizer recommendations traditionally serve to predict average nutrient needs across fields, but their effectiveness for precision agriculture remains uncertain. Our objectives were to evaluate whether soil phosphorus (P) concentrations predicted corn (Zea mays,r L.) yield response to P at the sub-field level, and to determine if soil test critical levels varied within field boundaries. We conducted research over seven growing seasons at two Kentucky sites collecting spatially dense yield response data from over 150 paired plots per field. Mehlich 3 extractable phosphorus (M3P) soil ranged from 0.8 to 63 mg kg−1, with 96% of sample points falling below the University of Kentucky's fertilizer cutoff of 30 mg kg−1 M3P for corn. Each plot (10−2 ha) received 0 or 29.5 kg ha−1 P. While M3P effectively predicted average field-level response, with yield increases in five of seven site-years, it failed to predict subfield responses, where only 51% of plots showed positive yield response to P application. Linear plateau models revealed that conventional statistical treatments of soil test correlation data mask important subfield variability. The poor relationship between soil test P and yield response at the subfield scale suggests that variable rate P management requires incorporating additional factors beyond soil P concentration or moving away from such deterministic models toward probabilistic models. Our findings demonstrate that while current soil test recommendations provide accurate field-scale guidance, they lack the precision required for variable rate application.
Original language | English (US) |
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Article number | e270028 |
Journal | Agronomy Journal |
Volume | 117 |
Issue number | 1 |
DOIs | |
State | Published - Jan 1 2025 |
All Science Journal Classification (ASJC) codes
- Agronomy and Crop Science