Machine vision smart sprayer for spot-application of agrochemical in wild blueberry fields

An essential part of the wild blueberry cropping system is the proper management of agrochemical inputs including herbicides, fungicides and insecticides. A machine vision system was developed and mounted on the rear sprayer boom 0.18 m in front of the sprayer nozzles capable of targeting the agrochemical application on an as-needed basis. The three-point hitch mounted sprayer featured 27 nozzles over a 13.7 m boom width and a storage tank capacity of 1135 l. Nine digital color cameras continually take images in real-time while computer software processes the images in 0.15 s to determine the target locations where the nozzles open and spray at speeds up to 1.77 m s^?1. Two wild blueberry fields in central Nova Scotia were selected for smart sprayer performance testing with spot-application (SA) of agrochemical as compared to control and uniform application techniques. Chateau^® herbicide was applied in a field with an infestation of hair cap moss. Spray droplet comparison showed moss patches were properly targeted using the smart sprayer. SA provided the same coverage performance as compared to uniform on the moss targets with herbicide application savings of 78.5% using the smart sprayer. Harvestable yield results were similar for all application tracks. TruPhos Magnesium and ZincMax foliar fertilizers were tank mixed with Bravo^® and Proline^® fungicides and applied to compare the difference of SA, control and uniform application. Results showed SA of foliar fertilizer and fungicide led to less premature leaf drop and increased the blueberry stem height, number of branches, stem diameter and fruit buds. SA of foliar fertilizer and fungicide also increased the percent of healthy wild blueberry plants by 57.8% and the harvestable yield by 137.8%. Fungicide application savings using the smart sprayer for SA were 11.6%.     

Variable rate spraying application on cotton using an electronic flow controller

Vegetation indices (VI) obtained by optical sensors have a positive correlation with various attributes of cotton plant growth. This work is aimed at evaluating the variable rate application of plant growth regulator (PGR) and fruit ripener on zones defined by VI and penological measurements using a sprayer equipped with a relatively low cost electronic flow controller on the height, percentage of open fruits, yield and net income. The work was done in a 92 ha field during crop seasons 2012/2013 and 2013/2014, and in a 202 ha field, during the crop season 2014/2015. Two spray applications were made using variable rate technology (VRT) of the PGR and one fruit ripener, in both harvest seasons, according to three VI classes formed by a previous mapping. The uniformity of the cotton height and opened fruits contribute to a similar yield across zones. Uniform plant height facilitates cotton harvest. The ripener helps to ensure all the cotton is ready to be harvested at the same time. In this trial, use of VRT technique to manage the PGR and fruit ripener application increased net income by US$152.28 ha^?1, but this estimate is based on yields that are not statistically significantly different from the control. This research confirms that PGR and fruit ripener can be sufficiently managed with an electronic flow controller to result in more uniform cotton plant height and yields within fields, but it leaves open the question of whether VRT PGR is profitable even with the lower cost electronic flow controller.     

Simulating field-scale variability and precision management with a 3D hydrologic cropping systems model

Effective variable-rate nitrogen (N) management requires an understanding of temporal variability and field-scale spatial interactions (e.g. lateral redistribution of nutrients). Modeling studies, in conjunction with field data, can improve process understanding of agricultural management. CropSyst-Microbasin (CS-MB) is a fully distributed, 3-dimensional hydrologic cropping systems model that simulates small (10 s of hectares) heterogeneous agricultural watersheds with complex terrain. This study used a highly instrumented 10.9 ha watershed in the Inland Pacific Northwest, USA, to: (1) assess the accuracy of CS-MB simulations of field-scale variability in water transport and crop yield in comparison to observed field data, and (2) quantify differences in simulated yield and farm profitability between variable-rate and uniform fertilizer applications in low, average and high precipitation treatments. During water years 2012 and 2013 (a “water year” refers to October 1st through the following September 30th, where a given water year is named for the calendar year on September 30th), the model simulated surface runoff with a Nash–Sutcliffe efficiency (NSE) of 0.7, periodic soil water content (comparison to seasonal soil core measurements) with a root mean square error (RMSE) ≤0.05 m³ m^?3, and continuous soil water content (comparison to in situ soil sensors) at 15 of 20 microsites with NSE ≥0.4. The model predicted 2013 field variability in winter wheat yield with RMSE of 1100 kg ha^?1. Simulated uniform N management resulted in 0–35 kg ha^?1 greater field average yield in comparison to variable-rate management. The savings in fertilizer costs under variable-rate N management resulted in $23–$32 ha^?1 greater field average returns to risk. This study demonstrated the capacity of CS-MB to further understanding of simulated and observed field-scale spatial variability and simulated crop response to low, medium and high annual precipitation.     

The profitability of precision spraying on specialty crops: a technical–economic analysis of protection equipment at increasing technological levels

A technical–economic analysis was conducted on three different technological levels of spraying equipment for specialty crops, based on the results on precision spraying technologies reported in scientific literature. The application scenarios referred to general protection protocols against fungal diseases adopted in vineyards and apple orchards in Central-Southern Europe. The analysis evaluated the total costs of protection treatments (equipment + pesticide costs), comparing the use of conventional air-blast sprayers (referred to as L0), of on–off switching sprayers (L1), and of canopy-optimised distribution sprayers (L2). Pesticide savings from 10 to 35% were associated with equipment L1 and L2, as compared to L0. Within the assumptions made, on grapevines, the conventional sprayer L0 resulted in the most profitable option for vineyard areas smaller than 10 ha; from 10 ha to approximately 100 ha, L1 was the best option, while above 100 ha, the more advanced equipment L2 resulted in the best choice. On apple orchards, L0 was the best option for areas smaller than 17 ha. Above this value, L1 was more profitable, while L2 never proved advantageous. Finally, in a speculation on possible prospectives of precision spraying on specialty crops, the introduction of an autonomous robotic platform able to selectively target the pesticide on diseased areas was hypothesised. The analysis indicated that the purchase price that would make the robotic platform profitable, thanks to the assumed pesticide and labour savings over conventional sprayers, was unrealistically lower than current industrial cost. This study showed that, in current conditions, profitability cannot be the only driver for possible adoption of intelligent robotic platforms for precision spraying on specialty crops, while on–off and canopy-optimised technologies can be profitable over conventional spraying in specific conditions.     

Sensing and control system for spot-application of granular fertilizer in wild blueberry field

An automated sensing and control system (hardware and software) was developed for real-time spot-application of granular fertilizer in mowed wild blueberry fields. The custom hardware system was incorporated into a commercial pneumatic granular fertilizer spreader. Custom software for the sensing and control system was developed by combining color co-occurrence matrix based texture analysis and g-ratio algorithms in C++ to acquire and process images in real-time to differentiate mowed wild blueberry plants from bare spots and weeds. The performance accuracy of the spot-applicable fertilizer spreader was evaluated both in laboratory simulation and real-time field tests. Simulation results reported that the accuracy of the developed system was 94.9 %. Real-time field tests reported that the system produced acceptable results at ground speeds of 1.6 and 3.2 km h^?1 for the spot-application of fertilizer at target areas (in plant areas only) within the field. Results also indicated that the ground speed of 4.8 km h^?1 was unacceptable, which could be due to blurred images at high speed and surface unevenness of the wild blueberry field. Spot-application of fertilizer using the modified fertilizer spreader could save fertilizer for the wild blueberry producers.     

Spot-application of fungicide for wild blueberry using an automated prototype variable rate sprayer

Wild blueberry producers apply fungicide uniformly without considering significant bare spots in the field. The wrong or over use of fungicide in bare spots results in an increased cost of production and threatens the environment. An automated prototype variable rate (VR) sprayer was used for spot-application (SA) of Chlorothalonil (Bravo^®) fungicide in a wild blueberry field. Eighteen 6.1 m wide test tracks were selected in the field and bare spots were mapped using a real-time kinematics-global positioning system (RTK-GPS). Six plots were selected randomly for three different application rates. Water sensitive papers (WSP) were placed in foliage and bare spots in SA and uniform-application (UA) tracks. The percent area coverage (PAC) of WSP with both SA and UA in foliage and bare spot areas were calculated. Plant growth parameters were measured from all 108 randomly selected plots in SA, UA and control (CN) tracks for comparison. Plant images were taken over six selected plots in each of the 18 tracks. Images were analyzed using custom developed software to calculate the percentage of green pixels (PGP) for determining the effect of Bravo^® on plant health. Fruit yield parameters were also measured from selected plots for comparison. Non-significance of the t test for SA versus UA plant targets’ PAC indicated that there was no significant bias in the SA with saving (9.90–51.22 %) and SA was accurate. Bravo^® did not show any significant difference on plant growth parameters among SA, UA and CN. However, PGP, floral bud and harvestable yield of SA and UA were significantly increased over CN. Therefore, a VR sprayer could be used for SA of fungicides in wild blueberry cropping system to reduce chemical usage and maintain crop productivity.     

Field application uniformity and accuracy of two rate control systems with automatic section capabilities on agricultural sprayers

The adoption of automatic section control (ASC) on agricultural sprayers remains popular since it reduces overlap and application in unwanted areas leading to input savings and improved environmental stewardship. Most spray controllers attempt to maintain the desired target rate during ASC actuation (ON and OFF of control sections which change the width of boom-section actually spraying) but limited knowledge exists regarding controller response and nozzle discharge variation during field operation. Therefore, field experiments were conducted using two common self-propelled sprayers equipped with commercially available control systems with ASC capabilities. Pressure transducers were mounted across the spray booms to record real-time nozzle pressure with data tagged with GPS location and time. Nozzle flow was obtained from nozzle pressure to compute nozzle flow uniformity or coefficient of variations (CVs) across the ON boom, off-rate errors (percent difference between actual and target nozzle flow rate) and settling times. Results indicated that nozzle CVs were >10 % for both auto-boom and auto-nozzle control systems, when each of the auto-boom and auto-nozzle sections were turned back ON for 0.5 and 0.2 s, respectively. Further, nozzle off-rate errors exceeding ±10 % occurred in both rectangular and irregular shaped fields. These off-rate errors primarily occurred during ASC actuation while at the same time the sprayer was being accelerated or decelerated. The extended nozzle flow settling times of up to 20 s (delayed response) indicated that the rate controller may require intelligent and enhanced control algorithms to minimize nozzle flow stabilization and thereby a reduction in sprayer off-rate errors during field operation.     

烟田中使用不同喷雾器的农药沉积分布研究

[目的]比较不同喷雾器以及喷头对农药有效利用率和施药效率的影响。[方法]采用诱惑红作为农药喷雾的示踪剂,分析了4种喷雾器及喷头在田间喷雾下的雾滴大小、施药效率、叶片农药的沉积回收率和雾滴田间分布均匀性。[结果]农药的有效利用率方面表现为电动喷雾器>机动喷雾器>手动喷雾器>手动弥雾器;施药效率方面表现为机动喷雾器>电动喷雾器>手动弥雾器>手动喷雾器;农药雾滴田间分布均匀性方面表现为电动喷雾器最好,其余都较差。[结论]为新型植保器械的推广应用提供了理论依据。     

Whole farm analysis of automatic section control for agricultural machinery

Automatic section control was analyzed in a whole farm decision-making framework when implemented on an agricultural sprayer and/or planter. In addition, various field types and navigational scenarios were examined to determine their impact on profitability. It was determined that automatic section control increased net returns under all scenarios; up to $36/ha. This investigation highlighted the importance of considering field size in addition to field shape as well as initial navigational scenarios when determining the profitability of automatic section control.     

Uniformity of wheat yield and quality using sensor assisted application of nitrogen

Proximal sensing, or obtaining information from close range, is a potentially useful tool for measuring the crop nitrogen status in real-time The objective of this study was to use proximal sensing of crop canopy spectral reflectance to evaluate variable-rate application of nitrogen in terms of its effect on yield and grain quality of winter wheat (Triticum aestivum L.). The sensor used was the Hydro-Precise N-Sensor System. Yield and grain quality maps were used as a basis for full-scale field trials with winter wheat growing under four nitrogen application treatments: a large (274 kg ha^?1), recommended (167 kg ha^?1) and two sensor-assisted (167 kg ha^?1) rates. The recommended rate of 167 kg N ha^?1 was given in a three-split application that meets the present Danish regulations to reduce nitrogen leaching. These require arable farmers to decrease nitrogen fertilizer application to 90% of the economically optimal level. Each farm’s baseline is calculated to take into account land quality, land allocated to each crop, and crop rotation. In the two sensor-assisted applications the Hydro-Precise N-Sensor System directs the last two of the three-split N application. Grain samples were collected directly from the grain flow of a combine harvester and analysed for protein, water and starch content. Grain data were related to and compared with combine yield meter registrations. Within the field, the variances of protein yield (698–1208 kg ha^?1) and grain protein (9.5–13.4%) were large. The nitrogen application treatments affected the average protein content (10.5–12.3%) and grain yield (9.87–10.42 t ha^?1) strongly. The grain starch content was largest in the uniform and sensor applied systems and smallest in the high nitrogen application treatment. Applying nitrogen according to the Hydro-Precise N-Sensor System did not increase grain yield or the protein and starch contents. Minor differences only were observed in both protein content and yield between uniform-rate N application and sensor-based variable-rate N application.     

Optimization of corn plant population according to management zones in Southern Brazil

Precision agriculture relies on site-specific interventions determined by the spatial variability of factors driving plant growth. The main objective of this study was to assess the efficiency of variable-rate seeding of corn (Zea mays L.) with delineated management zones. This study involved two experiments carried out in Não-Me-Toque, Rio Grande do Sul, Brazil. For the first experiment, carried out in 2009/2010, management zones were delineated by the farmer’s knowledge of the crop field. The field was split into low (LZ), medium (MZ) and high (HZ) crop performance zones. In the second experiment, carried out in 2010/2011, management zones were delineated by overlaying standardized yield data from nine crop seasons (seven of soybean and two of corn). The experiment was carried out with a randomized block design with three management zones and five corn seeding rates ranging from 50 000 to 90 000 seeds per ha^?1. The soil was a Rhodic Hapludox with a subtropical climate. Optimization of the corn plant population within the field increased grain yield compared to the reference plant population (70 000 plants ha^?1). Yield increases in the LZ, due to corn plant population reduction in relation to the target population, were 1.20 and 1.90 Mg ha^?1 for first and second experiments, respectively. This resulted in economic gains of 19.8 and 28.7 %, respectively. Yield increases in the HZ were 0.89 and 0.94 Mg ha^?1, respectively, and were due to an increase in plant population in relation to the target population. This resulted in economic gains of 5.6 and 6.6 % for the first and second experiments, respectively. In the MZ, the adjustment of the target plant population was not necessary. Optimizing corn population according to management zones is a promising tool for precision agriculture in Southern Brazil.     

Sensing soil and foliar phosphorus fluorescence in <Emphasis Type="Italic">Zea mays</Emphasis> in response to large phosphorus additions

Additions of large loads of phosphorus (P) enriched animal manure to soils and the persistence of their environmental impact have been associated with continued water quality impairment in regions of high density of confined animal feeding operations. Foliar P in corn (Zea mays L.) and changes in labile P in Aquic Hapludults were determined following P application of 0–560 kg P ha^?1 as KH₂PO₄ and an application of Fe³⁺ (150 mg Fe³⁺ kg^?1) in field mini-lysimeters to develop calibrations of soil and plant nutritional responses. X-ray fluorescence (XRF) scanning of uppermost leaves of plants at the V2, V5, and V8 stages showed that foliar P proportionally increased with addition rates. Exchangeable and enzyme-labile P forms were effective indicators of foliar XRFS-P for up to 30 days after emergence. Phosphorus calibration curves developed for flag leaves showed that spatial distribution of foliar P (3.6, 4.2, and 5.3 g kg^?1) corresponded to field zones treated with 0, 15, and 30 kg P ha^?1 as dairy manure P for the past 18 years. Up-to-date crop uptake and availability of P in these Hapludults were best described by a square root function of soil XRFS-P and total exchangeable inorganic P (r² = 0.4; RMSE = 419 and 422 g ha^?1, respectively). Therefore, a timely knowledge of canopy P status and its linkage to actual soil P status supports in situ element-specific sensing and precision nutrient management in order to manage the declining use-efficiency in crops and reduce potential loss to the environment.     

A new integrated CFD modelling approach towards air-assisted orchard spraying—Part II: Validation for different sprayer types

A computational fluid dynamics (CFD) model to simulate airflow from air-assisted orchard sprayers through pear canopies was validated for three different sprayers; single-fan (Condor V), two-fan (Duoprop) and four-fan sprayers (AirJet Quatt). The first two sprayers are widely used in Belgium and the latter one is a new design. Validation experiments were carried out in an experimental orchard (pcfruit, Velm, Belgium) in spring 2008. Ultrasonic anemometers were used to measure the time-averaged velocity components at different vertical positions before the tree and after the tree when the sprayers were driven through the orchard. The model was able to predict accurately the peak jet velocity, U_m from all the sprayers considered at all distances from the sprayer centre and vertical positions. More than 95% of the local relative errors of U_m were below 20%. Average relative errors, E, and root mean square errors, E_RMS, were all less than 11.04% and 1.68 m s⁻¹, respectively. The regions of high- (up to 18.0 m s⁻¹ upstream) and low (down to 2.8 m s⁻¹ downstream)-air velocity zones for all the sprayers were accurately predicted. The simulation results showed that the Condor V sprayer had a highly disturbed vertical jet velocity profile, especially at higher heights. The Duoprop sprayer had high jet velocities at the two-fan positions and lower jet velocity in between the two fans. Within the canopy height the AirJet Quatt sprayer showed a more uniform distribution of air than the other two sprayers except the minor peaks at the fan positions. These situations were all confirmed by the measurements.     

Delineation of specific management areas for coffee cultivation based on the soil–relief relationship and numerical classification

Predicting and mapping productivity areas allows crop producers to improve their planning of agricultural activities. The primary aims of this work were the identification and mapping of specific management areas allowing coffee bean quality to be predicted from soil attributes and their relationships to relief. The study area was located in the Southeast of the Minas Gerais state, Brazil. A grid containing a total of 145 uniformly spaced nodes 50 m apart was established over an area of 31.7 ha from which samples were collected at depths of 0.00–0.20 m in order to determine physical and chemical attributes of the soil. These data were analysed in conjunction with plant attributes including production, proportion of beans retained by different sieves and drink quality. The results of principal component analysis (PCA) in combination with geostatistical data showed the attributes clay content and available iron to be the best choices for identifying four crop production environments. Environment A, which exhibited high clay and available iron contents, and low pH and base saturation, was that providing the highest yield (30.4l ha^?1) and best coffee beverage quality (61 sacks ha^?1). Based on the results, we believe that multivariate analysis, geostatistics and the soil–relief relationships contained in the digital elevation model (DEM) can be effectively used in combination for the hybrid mapping of areas of varying suitability for coffee production.     

Effects of silicon amendment on the occurrence of rice insect pests and diseases in a field test

Rice is one of the most important staple foods for the world population,but it is attacked by a number of destructive pests.While evidence from greenhouse and laboratory tests has shown that silicon(Si)amendment can confer enhanced resistance to pests in rice,few studies have directly demonstrated the Si-mediated protection from pests in a field situation.In this study,field plots with silicon amendments at 0,75,150 and 300 kg SiO_2 ha~(–1) in early-and late-season rice were employed to evaluate the effects of silicon amendment on the occurrence of major insect pests and diseases and rice yield.Compared with the control plots without silicon amendment,plant damage by stem borer and leaf folder and population size of planthopper were significantly lower in three to five of the seven monitoring observations in each season in the plots amended with 300 kg SiO_2 ha~(–1).The disease index of rice blast in the early-season rice was lower in the plots amended with Si at 300 kg SiO_2 ha~(–1) than in the control plots,while Si protection from rice blast in the late-season rice and from rice sheath blight in the early-season rice were not apparent.An insignificant increase of rice yield by 16.4%(604 kg ha~(–1))was observed in the plots amended with 300 kg SiO_2 ha~(–1) over the control plots.Our results indicate that Si amendment at 300kg SiO_(2 )ha~(–1) can provide substantial protection from some of the rice pests under field conditions.These findings support the recommendation of silicon amendment as a key component of integrated management of rice pests.     

Estimation of bioenergy crop yield and N status by hyperspectral canopy reflectance and partial least square regression

The objective of this study was to compare performance of partial least square regression (PLSR) and best narrowband normalize nitrogen vegetation index (NNVI) linear regression models for predicting N concentration and best narrowband normalize different vegetation index (NDVI) for end of season biomass yield in bioenergy crop production systems. Canopy hyperspectral data was collected using an ASD FieldSpec FR spectroradiometer (350–2500 nm) at monthly intervals in 2012 and 2013. The cropping systems evaluated in the study were perennial grass {mixed grass [50 % switchgrass (Panicum virgatum L.), 25 % Indian grass “Cheyenne” (Sorghastrum nutans (L.) Nash) and 25 % big bluestem “Kaw” (Andropogon gerardii Vitman)] and switchgrass “Alamo”} and high biomass sorghum “Blade 5200” (Sorghum bicolor (L.) Moench) grown under variable N applications rates to estimate biomass yield and quality. The NNVI was computed with the wavebands pair of 400 and 510 nm for the high biomass sorghum and 1500 and 2260 nm for the perennial grass that were strongly correlated to N concentration for both years. Wavebands used in computing best narrowband NDVI were highly variable, but the wavebands from the red edge region (710–740 nm) provided the best correlation. Narrowband NDVI was weakly correlated with final biomass yield of perennial grass (r² = 0.30 and RMSE = 1.6 Mg ha^?1 in 2012 and r² = 0.37 and RMSE = 4.0 Mg ha^?1, but was strongly correlated for the high biomass sorghum in 2013 (r² = 0.72 and RMSE = 4.6 Mg ha^?1). Compared to the best narrowband VI, the RMSE of the PLSR model was 19–41 % lower for estimating N concentration and 4.2–100 % lower for final biomass. These results indicates that PLSR might be best for predicting the final biomass yield using spectral sample obtained in June to July, but narrowband NNVI was more robust and useful in predicting N concentration.     

Evaluation of agronomic and economic benefits of using RTK-GPS-based auto-steer guidance systems for peanut digging operations

Increasing the peanut (Arachis hypogea L.) digger efficiency by accurate placement over the target rows could minimize damaged pods and yield losses. Producers have traditionally relied solely on tractor operator skills to harvest peanuts. However, as peanut production has shifted to new growing regions in the Southeast US, producers face difficulties digging peanuts under conventional and new management schemes. The present study aimed to: (i) determine the effect of row deviations (RD) of the digger from the target row on peanut yield and quality, and (ii) determine the economic value of using RTK auto-steer guidance systems to avoid tractor deviations during peanut harvest. The study consisted of a randomized complete block design of tillage [conventional (CT) and strip tillage (ST)], row patterns [single (SR) and twin (TWR)] and row deviation (RD_0 mm, RD_90 mm, and RD_180 mm). The RD_90 mm and RD_180 mm treatments exemplify manual driving deviations compared to using an RTK auto-steer guidance system (RD_0 mm). Higher yields and higher net returns resulted from using the RTK auto-steer guidance system. Data showed that for every 20 mm row deviation, an average of 186 kg ha^?1 yield loss can be expected. Overall, yield was higher for the conventional tillage and twin row pattern treatments compared to the other treatments. Yield losses for the SR-CT treatment were higher as the row deviation increased compared with the TWR-CT treatment. In contrast, higher yield losses for TWR-ST compared to SR-ST were observed when deviations of 180 mm occurred instead of digging using the RTK auto-steer guidance system. While a farmer using an RTK auto-steer guidance system with an accuracy within 25 mm (RD_0 mm treatment) could potentially expect additional net returns of between 94 and 404 $ ha^?1 compared to those from row deviations of 90 mm, higher net returns of between 323 and 695 $ ha^?1 could be perceived if the guidance system is used instead of having row deviations of 180 mm. Therefore, the use of RTK auto-steer guidance system will allow growers to capitalize on the increases in yield potential by implementing changes in tillage and row patterns as those evaluated in this study.     

Probability of profitable yield response to nitrification inhibitor used with liquid swine manure on corn

Nitrification inhibitors (NI) can be used with liquid swine manure (LSM) to decrease potential NO₃ losses, but knowledge specifying when and where NI can increase corn (Zea mays L.) yields is limited. Eleven on-farm evaluation trials (OET) were conducted in 2009 and 15 in 2010 to identify site-specific factors for using Instinct (an encapsulated form of nitrapyrin) with LSM in Iowa. Farmers injected LSM in the fall in at least three field-long strips with and without NI. Yield responses (YR) to NI were calculated by dividing yield monitor data into 50-m cells within each field. Hierarchical models were used to estimate predictive probabilities of profitable YR for two categories of monthly average rainfall and soil drainage. On average, NI produced no YR in relatively normal 2009 and a 0.15 Mg ha^?1 YR in extremely wet 2010. The NI did not change late-season corn N status but half of corn stalk nitrate test (CSNT) samples were N deficient in 2009 and about 65 % in 2010. Fields receiving >90 cm March through August rainfall in 2010 were predicted 65 % more likely to have economic YR (>0.13 Mg ha^?1) than fields receiving <90 cm rainfall. Within-field variability in YR was about four times greater than among-field variability, but within field-level factors had no significant effects on YR. The NI effects may not have lasted long enough to increase yields across all OET and predictive probabilities suggest that NI may produce profitable YR only when spring and summer rainfall exceed the long-term averages by more than 40 %.