ABSTRACTand Ͼ10% in corn (Hilton et al., 1994). Fertilizer N losses due to surface runoff range between 1 and 13%In 2001, N fertilizer prices nearly doubled as a result of increased (Blevins et al., 1996; Chichester and Richardson, 1992 23% of the total N applied (Drury et al., 1996). In
Nitrogen (N) fertilization for cereal crop production does not follow any kind of generalized methodology that guarantees maximum nitrogen use efficiency (NUE). The objective of this work was to amalgamate some of the current concepts for N management in cereal production into an applied algorithm. This work at Oklahoma State University from 1992 to present has focused primarily on the use of optical sensors in red and near infrared bands for predicting yield, and using that information in an algorithm to estimate fertilizer requirements. The current algorithm, "WheatN.1.0," may be separated into several discreet components: 1) mid-season prediction of grain yield, determined by dividing the normalized difference vegetative index (NDVI) by the number of days from planting to sensing (estimate of biomass produced per day on the specific date when sensor readings are collected); 2) estimating temporally dependent responsiveness to applied N by placing non-N-limiting strips in production fields each year, and comparing these to the farmer practice (response index); and 3) determining the spatial variability within each 0.4 m 2 area using the coefficient of variation (CV) from NDVI readings. These components are then integrated into a functional algorithm to estimate application rate whereby N removal is estimated based on the predicted yield potential for each 0.4 m 2 area and adjusted for the seasonally dependent responsiveness to applied N. This work shows that yield potential prediction equations for winter wheat can be reliably established with only 2 years of field data. Furthermore, basing mid-season N fertilizer rates 2759 on predicted yield potential and a response index can increase NUE by over 15% in winter wheat when compared to conventional methods. Using our optical sensorbased algorithm that employs yield prediction and N responsiveness by location (0.4 m 2 resolution) can increase yields and decrease environmental contamination due to excessive N fertilization.
ABSTRACTand Ͼ10% in corn (Hilton et al., 1994). Fertilizer N losses due to surface runoff range between 1 and 13%In 2001, N fertilizer prices nearly doubled as a result of increased (Blevins et al., 1996; Chichester and Richardson, 1992 23% of the total N applied (Drury et al., 1996). In
Soil properties and weather conditions are known to affect soil N availability and plant N uptake; however, studies examining N response as affected by soil and weather sometimes give conflicting results. Meta‐analysis is a statistical method for estimating treatment effects in a series of experiments to explain the sources of heterogeneity. In this study, the technique was used to examine the influence of soil and weather parameters on N response of corn (Zea mays L.) across 51 studies involving the same N rate treatments that were performed in a diversity of North American locations between 2006 and 2009. Results showed that corn response to added N was significantly greater in fine‐textured soils than in medium‐textured soils. Abundant and well‐distributed rainfall and, to a lesser extent, accumulated corn heat units enhanced N response. Corn yields increased by a factor of 1.6 (over the unfertilized control) in medium‐textured soils and 2.7 in fine‐textured soils at high N rates. Subgroup analyses were performed on the fine‐textured soil class based on weather parameters. Rainfall patterns had an important effect on N response in this soil texture class, with yields being increased 4.5‐fold by in‐season N fertilization under conditions of “abundant and well‐distributed rainfall.” These findings could be useful for developing N fertilization algorithms that would prescribe N application at optimal rates taking into account rainfall pattern and soil texture, which would lead to improved crop profitability and reduced environmental impacts.
season, while potentially costly, could significantly increase NUE. Current nitrogen use efficiency (NUE) of cereal crop productionRecently, methods for estimating winter wheat N reis estimated to be near 33%, indicating that much of the applied quirements based on early season estimates of N uptake fertilizer N is not utilized by the plant and is susceptible to loss from and potential yield were developed (Lukina et al., 2001; the soil-plant system. Supplying fertilizer N only when a crop response is expected may improve use efficiency and profitability. A response Raun et al., 2002). Remote sensing collected by a modiindex using harvest data was recently proposed that indicates the fied daytime-lighting reflectance-sensor was used to esactual crop response to additional N within a given year. This response timate early season plant N uptake. The estimate was index, RI Harvest , is calculated by dividing the average grain yield of the based on a relationship between NDVI and plant N uphighest yielding treatment receiving N by the average yield of a check take between Feekes physiological stage 4 (leaf sheaths treatment (0 N). Although theoretically useful, RI Harvest does not allow lengthen) and 6 (first node of stem visible) (Large, 1954; for in-season adjustment of N application. The objective of this work Stone et al., 1996; Solie et al., 1996). The NDVI was was to determine the relationship between RI Harvest and the response calculated using the following equation:index measured in-season (RI NDVI ) using the normalized difference vegetative index (NDVI). Research was conducted in 23 existing field NDVI ϭ [(NIR ref /NIR inc ) experiments in Oklahoma. Each field experiment evaluated crop re-Ϫ (Red ref /Red inc )]/[(NIR ref /NIR inc )sponse to varying levels of preplant N. At Feekes growth stages 5, 9, and 10.5, RI Harvest was accurately predicted using RI NDVI (r 2 Ͼ 0.56).
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