Increased plant nitrogen loss with increasing nitrogen applied in winter wheat observed with 15nitrogen

Nitrogen (N) fertilizer is generally the most costly input for winter wheat (Triticum aestivum L.) production. Therefore, it was important to maximize fertilizer use efficiency and minimize N losses to the environment. One of the mechanisms responsible for decreased N use efficiency (NUE) was plant N loss. The objectives of this experiment were to determine fertilizer N recovery in winter wheat when produced for forage and grain, and to quantify potential plant N losses from flowering to maturity in winter wheat. Two long‐term (>25 years) winter wheat (Triticum aestivum L.) N rate fertility experiments (Experiment 222 and Experiment 502) were selected to evaluate ¹⁵N fertilizer recovery. Percent ¹⁵N recovery was determined from all microplots in plant tissue at flowering, in the grain, and straw at harvest and in the soil. Fertilizer N(¹⁵NH₄ ¹⁵NO₃) was applied atratesof 0, 45, 90, and 135kg N ha^‐1 in Experiment 222, and 0, 22, 45, 67, 90, and 112 kg N ha^‐1 in Experiment 502. The ratio ofNO₃ ^‐to NH₄ ⁺ in wheat forage at flowering was positively correlated with estimated plant N loss. Estimated plant N loss (total N uptake in wheat at flowering minus N uptake in the grain and straw at maturity) ranged from a net gain of 12 kg N ha^‐1 to a loss of 42 kg N ha^‐1, and losses increased with increasing N applied.     

Forage and Grain Yield Response to Applied Sulfur in Winter Wheat as Influenced by Source and Rate

ABSTRACT

Recently, environmental quality issues related to sulfur (S) have made it necessary to reduce its release into the atmosphere in wet or dry forms, which in turn might influence the S requirement of crops. It is anticipated that by 2020, S deposition will decrease by up to 30% in eastern portions of Oklahoma and by 15% throughout the remainder of the state. This change calls for frequent monitoring and evaluation of S nutrition in wheat and other crops. Experiments were conducted at Hennessey and Perkins research stations for a period of seven years starting in the fall of 1996, with the objective of assessing the effect of different levels of elemental and sulfate-S fertilizers on the grain and forage yields of winter wheat in Oklahoma. The experimental design was a randomized complete block with three replications. Four S rates, 0, 56, 112, and 224 kg S ha^{? 1}, were applied to the plots from 1996 to 2002 as CaSO₄. Another two rates, 56 and 112 kg S ha^{? 1}, were included in the trials beginning in 1998 using 92% elemental S. Gypsum, as a source of S for winter wheat, resulted in a greater yield than did elemental S in cases where S fertilizer sources were deemed significant. In six of 14 trials from 1996 to 2002, applied S as CaSO4 significantly increased wheat-grain yields. Observing significant grain and forage yield increases due to applied S was important, but the response was sporadic and unpredictable from one year to the next.     

Effect of dual applied phosphorus and gypsum on wheat forage and grain yield

Winter wheat (Triticum aestivum L.) production on acid soils can be greatly affected by reduced phosphorus (P) availability. At low pH (below 5.5), iron (Fe) and aluminum (Al) react with P to form highly insoluble compounds that severely reduce the amount of plant available P. Previous research suggested that supersaturating localized P fertilizer bands with respect to Ca²⁺ could induce precipitation of applied P as dicalcium phosphate (DCP) or dicalcium phosphate dihydrate (DCPD) which would slowly become plant available with time. The objective of this study was to determine the effect of dual‐band applications of P and gypsum on winter wheat forage and grain yield. Methods of application included P and gypsum banded with the seed, P and gypsum broadcast, and P banded and gypsum broadcast at rates of 29 and 58 kg P ha^‐1 and 22 and 44 kg S as gypsum ha^‐1. Sources of P included diammonium phosphate (DAP; 18–20–0) and triple superphosphate (TSP; 0–20–0). Grain and forage yields increased when P was applied. Dual‐band applications of P and gypsum increased wheat grain and forage yields compared to P banded without gypsum, and P banded and gypsum broadcast. When DAP was the P source, the N‐P band reduced yields compared to P banded alone or the N‐P‐gypsum band. This suggests that gypsum should be included in the band for maximum benefit. Precipitation of DCPD and DCP may have taken place within the dual P‐gypsum band, reducing fertilizer P fixed as Fe or Al hydroxides thus increasing long‐term P availability for winter wheat forage and grain production on acid soils.     

EFFICIENCY OF PRE-PLANT,TOPDRESS, AND VARIABLE RATE APPLICATION OF NITROGEN IN WINTER WHEAT

Past research about the efficiency of nitrogen application in winter wheat (Triticum aestivum L.) based on source and timing has produced inconsistent results. The majority of the literature used data from few locations over short time periods. This study used a unique data set of yields and nitrogen quantities from 2002–2009 at ten different locations in Oklahoma, USA. The objective of this research was to determine wheat yield response for granular pre-plant, uniform foliar topdress, and variable rate foliar topdress. Topdress liquid nitrogen had a 19% higher NUE than pre-plant urea, and was the most profitable source of nitrogen.     

Advances in biosecurity to 2010 and beyond: Towards integrated detection,analysis and response to exotic pest invasions

In order to limit the number and impact of exotic pest invasions, leading-edge technologies must be embraced and embedded within integrated national and international biosecurity systems. Outlined here are recent advances in the detection of exotic pests, and prospects for the early recognition of disease. Applications of new tools are described, using our understanding of the genomes of pathogens and vectors. In addition, the role of mathematical and simulation models to aid both biosecurity planning, and decision making in the face of an epidemic, are discussed, and recent attempts to unify epidemiology and evolutionary dynamics are outlined. Given the importance of emerging diseases and zoonoses, the need to align human and veterinary surveillance within fully integrated systems is underlined.     

Purification of secretory immunoglobulin A from milk of the brushtail possum (Trichosurus vulpecula)

AIM: To identify and purify secretory immunoglobulin A (sIgA), a key effecter molecule in mucosal immune responses, from milk of the brushtail possum (Trichosurus vulpecula).

METHODS: Milk samples were collected from female possums with pouch young, and clarified by centrifugation and precipitation methods. The clarified fraction was purified by gel filtration and affinity chromatography to yield sIgA. Sodium dodecyl sulphate-polyacrylamide gel electrophoresis (SDS-PAGE) and immunoblotting techniques were used to assess the purity of the final product, and to identify the heavy (H) chain, light (L) chain and secretory component (SC) of possum sIgA.

RESULTS: Immunoblotting, using antibodies raised against cloned possum sIgA SC and H-chain, and a synthetic peptide fragment of the H-chain, confirmed the identity of the purified protein. The N-terminal amino acid sequence of purified possum sIgA showed strong homology to reported sequences of H-chain variable regions of marsupial immunoglobulins.

CONCLUSIONS: Milk was shown to be a convenient source of mucosal secretion containing sIgA, and a process involving 2 precipitation and 2 chromatography steps produced purified sIgA. This IgA preparation will prove useful for the generation of sIgA-specific immunological reagents for measurement of immune responses in the development of mucosal-based vaccines for biological control of possums.     

Is data needed from every field to determine in-season precision nitrogen recommendations in winter wheat?

The research reported here seeks to determine whether it is necessary to obtain optical reflectance measurements with a GreenSeeker^® handheld sensor from each field to make accurate in-season nitrogen application recommendations for winter wheat, and how much precision—and profit—would be lost by moving from site-specific (or field-specific) optical reflectance sampling to region-level sampling. The approach used was to estimate a separate linear response-plateau regression every year using yield and optical reflectance data from randomized complete block experiments. Profits from region-level sampling and field-level sampling were statistically indistinguishable, but this result was mostly due to both being imprecise. Furthermore, the region- and field-based sampling systems were no better than break-even with the historical extension advice to apply preplant anhydrous ammonia at 90 kg ha^?1. The approach of estimating a new regression every year is too imprecise, whether at the field or region level. This research goes beyond past research by accounting for the uncertainty in the estimated relationships. The poor performance of the systems is directly related to the imprecise relationship between yield and optical reflectance responses to nitrogen.     

Evaluation of mid-season sensor based nitrogen fertilizer recommendations for winter wheat using different estimates of yield potential

Optical sensors, coupled with mathematical algorithms, have proven effective at determining more accurate mid-season nitrogen (N) fertilizer recommendations in winter wheat. One parameter required in making these recommendations is in-season grain yield potential at the time of sensing. Four algorithms, with different methods for determining grain yield potential, were evaluated for effectiveness to predict final grain yield and the agronomic optimum N rate (AONR) at 34 site-years. The current N fertilizer optimization algorithm (CNFOA) outperformed the other three algorithms at predicting yield potential with no added N and yield potential with added N (R² = 0.46 and 0.25, respectively). However, no differences were observed in the amount of variability accounted for among all four algorithms in regards to predicting the AONR. Differences were observed in that the CNFOA and proposed N fertilizer optimization algorithm (PNFOA), under predicted the AONR at approximately 75 % of the site-years; whereas, the generalized algorithm (GA) and modified generalized algorithm (MGA) recommended N rates under the AONR at about 50 % of the site-years. The PNFOA was able to determine N rate recommendations within 20 kg N ha^?1 of the AONR for half of the site-years; whereas, the other three algorithms were only able recommend within 20 kg N ha^?1 of the AONR for about 40 % of the site-years. Lastly, all four algorithms reported more accurate N rate recommendations compared to non-sensor based methodologies and can more precisely account for the year to year variability in grain yields due to environment.     

Development of an in-season estimate of yield potential utilizing optical crop sensors and soil moisture data for winter wheat

When utilizing optical sensors to make in-season agronomic recommendations in winter wheat, one parameter often required is the in-season grain yield potential at the time of sensing. Current estimates use an estimate of biomass, such as normalized difference vegetation index (NDVI), and growing degree days (GDDs) from planting to NDVI data collection. The objective of this study was to incorporate soil moisture data to improve the ability to predict final grain yield in-season. Crop NDVI, GDDs that were adjusted based upon if there was adequate water for crop growth, and the amount of soil profile (0–0.80 m) water were incorporated into a multiple linear regression model to predict final grain yield. Twenty-two site-years of N fertility trials with in-season grain yield predictions for growth stages ranging from Feekes 3 to 10 were utilized to calibrate the model. Three models were developed: one for all soil types, one for loamy soil textured sites, and one for coarse soil textured sites. The models were validated with 11 independent site-years of NDVI and weather data. The results indicated there was no added benefit to having separate models based upon soil types. Typically, the models that included soil moisture, more accurately predicted final grain yield. Across all site years and growth stages, yield prediction estimates that included soil moisture had an R² = 0.49, while the current model without a soil moisture adjustment had an R² = 0.40.     

Independence of yield potential and crop nitrogen response

Crop yield level and nitrogen (N) responsiveness influence the demand for fertilizer. If they were found to be unrelated, this would justify using a combination of both for determining fertilizer N requirements. Failure to understand the independence of crop response to N and yield level has led to confusion as to what theory is appropriate for making N fertilizer rate recommendations. The sufficiency approach applies a fixed rate of N at a computed sufficiency level, regardless of yield potential. Alternatively, mid-season optical sensor estimates of yield potential and crop response to additional N provide a physiological basis to estimate N removal and a biologically based N application rate. This study investigated the relationship between grain yield and response to N in long-term wheat and corn experiments. No relationship between response to N and grain yield was found. There was also no relationship between yield and year at two of three sites. Finally, there was no relationship between response to N and year at any site. Because yield and response to N were consistently independent of one another, and as both affect the demand for fertilizer N, estimates of both should be combined to calculate realistic in-season N rates.