Powers et al.
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They observed several common factors from a number of research projects: 1 continuous maize was not an environmentally acceptable practice in tile-drained soils because of the large losses of nitrate into the drainage flow; 2 reduced tillage or no-till systems provided a better synchronization of soil N mineralization with N uptake requirement; 3 improving water management practices in irrigated systems improved environmental quality; 4 maize-soybean rotations may not produce improved environmental quality if proper accounting for the soil N contributions from the soybean crop; 5 a good soil testing program is needed to implement the best fertilizer N rate for crops; 6 new technologies to assess N requirements of the crop and to address the problem of weather and soil variability; and 7 present practices in the Midwest may produce little environmental impact through nitrate loss; however, these systems may fail under conditions of abnormal weather variability.
One of the emerging technologies is the observation of the plant for N status in combination with soil testing. The premise is that the plant may be a better indicator of actual N status than inference from soil test. Blackmer and Schepers showed that leaf chlorophyll measurements provided a useful method for measuring N status of the leaves and the results compared favorably with the leaf N concentrations.
They found that reflectance near 0.
Improving Water and Nutrient‐Use Efficiency in Food Production Systems | Wiley Online Books
Blackmer et al. This approach was refined by Bausch and Duke with the development of a nitrogen reflectance index for a field that was based on comparing the reflectance across the field with an area in which N was assumed to be non-limiting. Diker and Bausch further refined to show that this index can be used to assess within-field variation of maize yield. Osborne et al. These methods have been extended to wheat Triticum aestivum L. Scharf et al. The current research on reflectance to assess and predict N requirements for maize and wheat may provide management practices that improve environmental quality.
Improvements in water quality are considered as potential outcomes from improvements in the efficiency of nitrogen use by crops.
Increasing agricultural water use efficiency to meet future food production.
Nitrogen use efficiency for grain crops are generally computed based on the grain yield relative to the amount of N fertilizer applied. Cassman et al. Interest in NUE has occurred because of the linkage between N leaching and fertilizer application, although the direct evidence between N rate and leaching has not been found. Nissen and Wander studied NUE in relation to particulate organic matter and aggregate dry mean weight diameter in a greenhouse study on maize and found NUE declined with increasing N application rates.
They concluded that soil management practices that increase particulate organic matter would be a substitute for fertilizer N additions with the added benefit of improving long-term soil productivity. Strategies to improve NUE in wheat have been studied by Blankenau et al. They found NUE could be improved if N availability to the crop could be increased at critical growth stages. In wheat, this could be accomplished by modifying N application systems to lower N application at tillering with higher N rates during later growth stages. These studies demonstrate that NUE can be changed by N management but is further complicated by genetic differences.
Assessment of NUE has generally been completed in laboratory or small plot studies with little attempt to evaluate the change in NUE across fields in which spatial or temporal variability in yield has been observed. Assessment of N across fields provides a measure of feedback about the efficiency of N management decisions. Eghball et al. They found that spatial variability in maize yield was less than the spatial variability in soil NO 3 -N and concluded that using soil NO 3 -N measurements may be ineffective for N management decisions.
Balkcom et al.
Their observations showed it may be possible to reduce NO 3 -N levels in surface waters by delaying N applications to more closely match plant N needs and the combined approach of soil and plant tests could help improve efficiency of N use by producers. Development of management systems that demonstrate increased NUE and decreased environmental impact are needed in the areas in which there is significant NO 3 -N loss to surface waters. Observations of spatial variation of maize yield across fields are not directly related to N management decisions and many studies on NUE and N rates have been confined to a single soil type.
The response of a crop to N availability within the soil profile has shown to affect NUE in wheat Blankenau et al. The observation of greater spatial variation in maize yields among fields in dry compared to wet years suggest that soil water availability and timing of precipitation events may be an underlying factor affecting NUE in maize.
There are challenges in studying N response of crops and environmental quality at the field scale; however, these relationships must be understood if science is to increase production and protect the environment simultaneously. We have been conducting studies across central Iowa fields to evaluate the interactions among crop water use, N management, and crop yield in order to develop an understanding of NUE and water use efficiency WUE in Midwestern cropping systems. The objective of this paper is to present the results of these studies and to propose how this framework can be used to increase our understanding of improving crop production efficiency and environmental quality.
Nitrogen fertilizer data throughout the world shows that annual use rate is increasing. Nitrogen fertilizer use data and the crop production data in the FAO database shows that NUE decreases exponentially in all countries except Western Europe and the United States with increasing amount of N fertilizer applied Fig.
Rationale and definition:
Grain production was computed as the sum of all cereal crops and maize production. During this time period, grain production has increased linearly in the United States and Western Europe Fig. These changes in grain production have caused a slight increase in NUE in the last decade.
Figure 2. Nitrogen use efficiency for grain production relative to N fertilizer use for for selected regions in the world. Figure 3. Grain production cereal and maize for selected regions of the world for the period. There is a linear increase in grain yield with increasing N fertilizer use Fig.
There are; however, differences among the regions in response to N application with the higher N rates. The linear relationship for China and South America shows little deviation from the line while Australia shows years when there is extremely low production compared to the N applied.
This is due to widespread drought across the continent and water becomes a limited factor in production. The expanses of the growing regions in China and South America for grain production provide a buffer against drought on a large scale. Observations for the United States and Western Europe data not shown show increasing variation in grain yield at the higher N application amounts.
These variations would be attributed to other factors, e. It is important to note that the N application amounts are vastly different among these regions Fig. There is not a simple strategy for increasing NUE and Zhu and Chen suggest for China that emphasis be placed on optimization of N application rates, deep placement of N, matching N application with crop demands, balanced fertilizer application, and use of controlled release N fertilizer of nitrification inhibitors.
Figure 4. Nitrogen management strategies to improve NUE have been limited and observations from several production areas throughout the world demonstrate the importance of soil water availability on grain production. An illustration of the field-scale N response is provided in this case study from the Midwestern United States based on observations from production fields. Details of this experiment are provided in Hatfield and Prueger Crop water use patterns showed large differences between soil types within N treatments.
An example for is shown in Fig. These data are typical of what we observed through the five years of the study. Differences were greater among soil types than among N rates for a given year.
Differences among N rates were less than 30 mm of evapotranspiration ET while differences among soils were as large as mm. Differences among years can be attributed to the early precipitation patterns and the frequency of soil wetting that contributed to soil water evaporation when the crops did not cover the soil. This leads to a large portion of the water use by evaporation rather than transpiration Ritchie and Burnett, Early in the season there was no difference among soils and the greatest separation occurred later in the season when the precipitation amounts began to decrease and ET increased because of the greater plant size Fig.
Water use patterns across fields separate more than expected throughout the season but is reasonable given the differences in soil water holding capacity across the landscape.
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These differences between soils would explain why there is increased spatial variability in yields in dry years compared to wet years as observed by Katsvario et al. Precipitation patterns over the five years of this study have ranged from above normal in to below normal amounts in the growing season during , , and Studies that examine the spatial variability of yield need to consider the temporal dynamic of precipitation during the growing season as part of the discussion rather than characterize the years as either wet or dry. Seasonal water use patterns were adjusted for soil water evaporation to compute the transpiration rate in order to compute WUE for each soil-N rate combination.
Although there have not been any direct measurements of WUE in the Midwest and particularly under different N management systems, the expectation was for a common relationship to encompass all of the observations. Actual observations showed a large variation in WUE across the observations Fig.