Nitrogen [N] fertilizer and irrigation management practices are both critical factors for determining agronomic and environmental outcomes for potato production. This dissertation was comprised of two overall objectives.
First, a small-plot experiment evaluating the effects of six N rate, source, and timing treatments and two irrigation rate treatments on tuber yield, quality, net profitability, nitrate leaching, residual soil nitrate, plant N uptake, N nutrition index [NNI], N uptake efficiency, N utilization efficiency [NUtE], N use efficiency [NUE], biomass, harvest index, biomass, and potential N losses for potato [Solanum tuberosum (L.) ‘Russet Burbank’] were investigated in 2016 and 2017 at Becker, MN, on a Hubbard loamy sand. Convention N fertilizer best management practices [BMPs] were compared to reduced N rate, control N rate, and a variable rate [VR] N treatment based on the N sufficiency index [NSI] approach using remote sensing. Irrigation treatments included a conventional rate (100%) based on the “checkbook” method and a reduced rate (85%). The VR treatment reduced N applied relative to the recommended rate by 22 and 44 kg N ha−1 in 2016 and 2017, respectively. Irrigation rate was reduced by 29 and 33 mm in 2016 and 2017, respectively. From an agronomic perspective, neither VR N nor reduced irrigation produced significant differences in tuber yield or net return compared to full rate treatments. From an environmental perspective, nitrate leaching losses varied between 2016 and 2017 with flow-weighted mean nitrate N concentrations of 5.6 and 12.8 mg N L−1, respectively, and increased from 7.1 to 10.4 mg N L−1 as N rate increased from 45 to 270 kg N ha−1. Despite reductions in N rate for the VR N treatment, there was no significant difference in nitrate leaching compared with the existing N best management practices (BMPs). However, reducing irrigation rate by 15% decreased nitrate leaching load by 17% through a reduction in percolation.
Second, an evaluation of the relationship between NUE, NNI, and their variation across genotype [G] x environment [E] effects was conducted. A novel theoretical relationship between NNI and NUtE was derived: at a constant NNI value, NUtE values increased non-linearly as biomass increased, and at an NNI value of 1.0 this relationship defines the critical N utilization efficiency curve [CNUtEC]. Subsequently, an evaluation of the variation in critical N concentration [%Nc] was conducted using a hierarchical Bayesian framework to infer the critical N dilution curve [CNDC] across G x E effects observed from multiple experimental trials. This statistical method was able to quantify the uncertainty in %Nc, which was used to directly compare CNDCs. Critical N concentration was found to significantly vary across the effect of E, and in some cases for G within E. Therefore, consideration of both NNI and NUE require explicit consideration of the uncertainty in and variation due to G x E effects for %Nc.