26 research outputs found
Responsive in-season nitrogen management for cereals
Current nitrogen (N) management strategies for worldwide cereal production systems are characterized by low N use efficiency (NUE), environmental contamination, and considerable ongoing debate regarding what can be done to improve N fertilizer management. Development of innovative strategies that improve NUE and minimize off-field losses is crucial to sustaining cereal-based farming. In this paper, we review the major managerial causes for low NUE, including (1) poor synchrony between fertilizer N and crop demand, (2) uniform field applications to spatially variable landscapes that commonly vary in crop N need, and (3) failure to account for temporally variable influences on crop N needs. Poor synchronization is mainly due to large pre-plant applications of fertilizer N, resulting in high levels of inorganic soil N long before rapid crop uptake occurs. Uniform applications within fields discount the fact that N supplies from the soil, crop N uptake, and crop response are spatially variable. Current N management decisions also overlook year-to-year weather variations and sometimes fail to account for soil N mineralized in warm, wet years, ignoring indigenous N supply. The key to optimizing tradeoffs amongst yield, profit, and environmental protection is to achieve synchrony between N supply and crop demand, while accounting for spatial and temporal variability in soil N. While some have advocated a soil-based management zones (MZ) approach as a means to direct variable N applications and improve NUE, this method disregards yearly variation in weather. Thus, it seems unlikely that the soil-based MZ concept alone will be adequate for variable application of crop N inputs. Alternatively, we propose utilizing emerging computer and electronic technologies that focus on the plant to assess N status and direct in-season spatially variable N applications. Several of these technologies are reviewed and discussed. One technology showing promise is ground-based active-light reflectance measurements converted to NDVI or other similar indices. Preliminary research shows this approach addresses the issue of spatial variability and is accomplished at a time within the growing season so that N inputs are synchronized to match crop N uptake. We suggest this approach may be improved by first delineating a field into MZ using soil or other field properties to modify the decision associated with ground-based reflectance sensing. While additional adaptive research is needed to refine these newer technologies and subsequent N management decisions, preliminary results are encouraging.We expect N use efficiency can be greatly enhanced using this plant-based responsive strategy for N management in cereals
Recommended from our members
Track A Basic Science
Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/138319/1/jia218438.pd
Mapeamento da condutividade elétrica e relação com a argila de Latossolo sob plantio direto
Variação espacial da resposta do milho à adubação nitrogenada de cobertura em lavoura no cerrado
Reflectance spectroscopy detects management and landscape differences in soil carbon and nitrogen.
Not AvailableMany studies have calibrated visible and near-infrared (VNIR) diffuse reflectance spectroscopy (DRS) to various soil properties; however, few studies have used VNIR DRS to detect treatment differences in controlled experiments. Therefore, our objective was to investigate the ability of VNIR DRS to detect treatment differences in topsoil organic C (SOC) and total N (TN) compared with standard dry combustion analysis. A long-term (since 1991) experiment in central Missouri, where cropping systems were replicated across a typical claypan soil landscape was studied. Soil samples from two depths (0â5 and 5â15 cm) were obtained in 2008 at summit, backslope, and footslope positions for three grain cropping systems. Estimates of SOC by VNIR DRS using
oven-dried soil samples and an independent calibration set were very good, with R2 = 0.87 and RMSE = 2.4 g kgâ1. Estimates of TN were somewhat less accurate (R2 = 0.79, RMSE = 0.24 g kgâ1). Field-moist VNIR DRS results were also good, but with 13 to 17% higher RMSE. Trends in differences among treatment means were very similar for dry combustion, oven-dry soil VNIR, and field-moist VNIR. Dry combustion was best at separating treatment means, followed by dry soil VNIR and fi eld-moist VNIR. Differences among methods were relatively minor for 0- to 5-cm depth samples but more pronounced for 5- to 15-cm samples. Efficiency of the VNIR method, particularly when applied ton field-moist soil, suggests that it deserves consideration as a tool for determining near-surface SOC and TN differences in field experiments.Not Availabl