Month: March 2012

Bianca Moebius-Clune, Harold van Es, and Jeff Melkonian, Department of Crop and Soil Sciences, Cornell University

Research has demonstrated (summarized by van Es et al., 2007) that soil and crop management practices, combined with weather conditions during the early growing season, greatly affect N losses and are therefore critical factors in determining optimum N rates.  The difference in fertilizer N needs from one year to the next could easily be 100 lb N, and generalized N recommendations are inherently imprecise. In a recent case study, we highlighted the impact of early- vs. late planting on recommended N rates (What’s Cropping Up?, Vol. 21, No 4).

It is not possible to accurately determine at the beginning of the growing season how much N fertilizer will be needed for that year’s crop, because some critical processes that affect N losses have not yet passed.  Most growers fertilize for a worst-case scenario and apply “insurance fertilizer” – they put on in excess of what is needed in most years. This reduces farm profits and causes high environmental losses.  Seasonal corn N needs can be estimated much better in the late spring to guide sidedress applications.  Adapt-N is an online decision support tool (http://adapt-n.cals.cornell.edu) designed to help farmers precisely manage nitrogen (N) inputs for grain, silage, and sweet corn. It uses a well-calibrated computer model, and combines user information on soil and crop management with high resolution weather information, to provide N sidedress recommendations and other simulation results on nitrogen gains and losses. We have completed the first year of beta-testing through on-farm strip trials in New York, which are presented in this article.

Methods
We completed 18 replicated strip trials on commercial and research farms throughout New York during the 2011 growing season. They involved grain and silage corn, with and without manure application, and different rotations (corn after corn, corn after soybean, and corn after a clover cover crop; Table 1). Treatments involved two rates of nitrogen, a conventional “Gower-N” rate based on current grower practice and an “Adapt-N” recommended rate.  A simulation was run for each field prior to sidedressing to determine the Adapt-N rate. In 2011, due to seasonal weather conditions, all Adapt-N rates were lower than conventional N rates (by 15 to 140 lbs/ac; Table 1).  Growers then implemented field-scale strips with 3 or 4 replications for each treatment (except NY8 and NY9, where only single yield strips were implemented due to time and equipment constraints).

Yields were measured by weigh wagon, yield monitor, or in a few cases by representative sampling (two 20 ft x 2 row sections per strip). Partial profit differences between the Adapt-N recommended and Grower-N management practices were estimated through a per-acre partial profit calculation:

Profit = [Adapt-N yield – Grower-N yield] * crop price – [Adapt-N  N use – Grower N use] * price of N

Yields were used as measured, regardless of statistical significance, since the statistical power to detect treatment effects is inherently low for two-treatment strip trials. For corn, a grain price of $5.50/bu was assumed ($6.50/bu minus $1.00/bu for drying, storing and trucking from PA Custom Rates; USDA, 2011). For silage, $50/T was assumed based on reported NY silage prices of $25-75/T. The price of N fertilizer was assumed at $0.60/lb N (prices ranged from $0.49 – $0.75/lb N in NY). Total N losses to the environment (atmosphere and water) and N leaching losses were estimated for each treatment by running model simulations with all N inputs through the end of the growing season (30 October). Agronomic, economic and environmental outcomes of these trials were then used to assess Adapt-N performance.

Results
Errors were made in model and/or trial implementation in a few cases (labeled with * in Table 1):  A clover cover crop was improperly simulated as an incorporated sod, resulting in a low Adapt-N recommendation and substantial yield losses. In other cases, Adapt-N fertilizer and manure inputs did not reflect real field applications, or N applications were made too late in the season.  The lesson here is that correct input information is, of course, needed for Adapt-N to provide an accurate recommendation.  The resulting yields and simulations from the above four trials were not representative of 2011 Adapt-N performance, and these trials were therefore removed from further analysis.

Agronomic, economic and environmental comparisons between Grower-N and Adapt-N treatments for each trial are provided in Figure 1, and as averages in Table 2. A comparison of grain and silage harvest data (Fig. 1a & 1b) shows that differences in yields were negligible and statistically not significant for almost every trial, despite substantially reduced N rates applied for the Adapt-N treatment (Tables 1 and 2).  A case study describing one of these trials, conducted at Donald & Sons Farm, in Moravia, NY, where 140 lb of N were saved without yield loss, is described in a companion article in the current issue of What’s Cropping Up?.

When the previous crop was soybean (3 trials), yield losses were found in every case (Fig. 1a), although the grower N rates were well above economic optimum N rates. We determined that Adapt-N overestimated the soybean N contribution, and thus provided low N recommendations in these three cases. The 2011 version of Adapt-N used a flat 30 lb soybean N credit, but also simulated immobilization of N in stover in corn-after-corn rotations, effectively almost doubling the N credit for corn following soybean.  We believe that part or all of the soybean ‘N credit’ should mostly be regarded as an absence of an immobilization penalty for corn-corn rotations. Changes will be made to the Adapt-N tool to reflect these findings for the 2012 growing season.

Estimated leaching losses (Fig. 1c & d), as well as total N losses (Table 2) decreased as a result of reduced N application rates for the Adapt-N treatment. On average, leaching losses decreased by 38 lb N/ac in grain trials, and by 11lb/ac in silage trials. There was less room for improvement in silage trials because lower fertilizer rates were used after manure applications.

Most trials resulted in profit gains from the use of Adapt-N, ranging from $1 – $80/acre, (Fig. 1e & f). Average profit gains were $35/acre for corn after corn and $39/acre for silage corn (Table 2). Corn after soybean trials registered an average loss of $11/acre due to one trial with high yield loss (NY3). This was the only trial out of 14 (7%) where profit loss was significant.  Fig. 2 indicates the low risk of profit loss (<14% overall before the correction of the soybean N credit), and high probability of improved profits (86%) of using Adapt-N in 2011.

Our data suggest that after minor adjustments of the Adapt-N tool, it will be even better equipped to give accurate recommendations.  Growers who tend to use high amounts of nitrogen will realize large savings. In a much wetter year, increased profitability would come from appropriately applying more N at sidedress time in order to prevent yield reductions from N losses.  In the long term we expect that environmental losses will decrease in both dry and wet years, because this tool provides strong incentives to shift  N applications to sidedress time.

Conclusions
From beta-testing on commercial farms throughout NY State in 2011, we determined that the value of the Adapt-N tool was substantial. The tool was quite successful in adjusting for the effects of seasonal conditions to accurately recommend N fertilizer needs.  Also,
• N application rates were significantly reduced (15         to 140 lb/acre).
• Grower profits increased on average by $35/acre, except in corn after soybean (due to model inaccuracies that are being corrected for the 2012 growing season).
• N losses to the environment were decreased substantially (5 to 120 lb/acre).

Adjustments to the Adapt-N tool will improve ease of use and accuracy for the 2012 growing season. The Adapt-N tool and information about it is accessible to stakeholders through any device with internet access (desktop, laptop, smartphone, and tablet) at http://adapt-n.cals.cornell.edu/, where information on account setup is also available.

Acknowledgments
This work was supported by grants from the NY Farm Viability Institute and the USDA-NRCS Conservation Innovation Program.  We are grateful for the cooperation in field activities from Bob Schindelbeck, Keith Severson, Kevin Ganoe, Sandra Menasha, and Anita Deming of Cornell Cooperative Extension, from Dave DeGolyer, Dave Shearing and Jason Post at the Western NY Crop Management Association, and from Eric Bever and Mike Contessa at Champlain Valley Agronomics. We also are thankful for the cooperation of the many farmers who implemented these trials.

References
van Es, H.M., B.D. Kay, J.J. Melkonian, and J.M. Sogbedji. 2007. Nitrogen Management Under Maize in Humid Regions: Case for a Dynamic Approach.  In: T. Bruulsema (ed.) Managing Crop Nutrition for Weather. Intern. Plant Nutrition Institute Publ. pp. 6-13. http://adapt-n.cals.cornell.edu/pubs/pdfs/vanEs_2007_Managing N for Weather_Ch2.pdf. [URL verified 2/22/12].

EPA, 2010. Inventory of U.S. Greenhouse Gas Emissions and Sinks (1990-2008). U.S. Environmental Protection Agency, Washington, DC.

Marlene van Es (1), Bianca Moebius-Clune (1), Harold van Es(1), Jeff Melkonian(1), and Keith Severson (2), (1) Department of Crop and Soil Sciences, Cornell University and (2) Cornell Cooperative Extension Cayuga County

Growers across the country have used a wide range of methods to decide on nitrogen (N) application rates for corn, from mass balances to a variety of soil and plant tissue tests, to maximum return to nitrogen curves, to… simply… rules of thumb. But most are frustrated by the lack of accuracy of these methods.  Early-season weather can greatly impact how much N fertilizer is needed year to year, and this variability has been difficult to manage. The amount of N fertilizer required could easily differ by 100 lbs from one year to the next. This variability results in average N recommendations that are higher than needed in many years, leading to profit loss for growers and environmental damage through N losses to water as nitrate and to the air as nitrous oxide, a potent greenhouse gas.

The web-based Adapt-N tool has the potential to change the way N management is done. Soil data, along with crop and soil management information are supplied by the grower. The Adapt-N tool uses these data in combination with newly available high-resolution climate data to simulate N availability and losses due to weather, and thus provide more accurate sidedress N recommendations. The tool is undergoing beta-testing in on-farm strip trials across New York and Iowa in the 2011 and 2012 growing seasons. Once fully validated, Adapt-N will, over the long term, help reduce N losses to the environment that contribute to air and water pollution, while saving farmers money through the optimization of fertilizer purchases and application rates.

One of the New York agricultural enterprises collaborating with the Adapt-N team is Donald and Sons Farm located in Moravia, NY. The farm has been in the family for several generations and currently encompasses 1500 acres of land. In 2011, 1050 acres were in corn and 250 in soybeans.

The Donald brothers, Robert and Rodney, are no strangers to on-farm research and have collaborated with Cornell University and private companies many times over the years.  When asked why they keep getting involved in research Rodney replied, “Money! Some [projects] take you down a dead end street, but if we see, for example, that we can save putting 100 lbs [of N] on, that’s a lot of money.” So, although the on-farm research can be time consuming for Robert and Rodney, they see the value in the important benefits it can generate.

The Donald brothers’ acreage varies greatly in soil type, and organic matter contents range from about 1 to 5%. The farm currently bases its N application rates on recommendations from A&L Great Lakes Laboratories, generated based on soil tests by management unit. Robert and Rodney practice variable rate application, taking advantage of their RTK-GPS system for soil sampling, input application and yield monitoring. The bulk of their fertilizer N application occurs at sidedress time, as they have found that early season applications run the risk of losses during wet springs. They experimented for a few years with putting anhydrous ammonia on at preplant, and considered slow-release and inhibitor technology, but decided to return to sidedressing. The amount the Donalds spend on N fertilizer has nearly quadrupled since 2000, and in 2011 they spent $107,000 – a strong incentive for them to seek new tools to help optimize application rates. As Rodney puts it, “money talks … and with what we are getting in corn for what we are putting on in ammonia, we’re not gaining.”

This past spring, Robert and Rodney identified 10 acres of a 100-acre field to implement a replicated strip trial to test the Adapt-N tool. The field was planted with corn on May 21st with 22lbs of N from monoammonium phosphate starter. In early June, Keith Severson of Cayuga Cooperative Extension used Adapt-N, inputting the Donald brothers’ field information, such as organic matter content, expected yield, tillage, fertilizer inputs, etc., to generate an N sidedress recommendation of 80 lb N/acre.

When asked what he thought when he heard of the 80 lb recommendation, Rodney said, “it was hard for me to chew on 80. … It was a little hard for me to chew on!” On June 19th, two sidedress treatments were applied in eight, 16-row-wide strips. Four of the strips received the standard N rate based on the recommendation from A&L labs, which was 220 lbs, and the remaining 4 strips received the Adapt-N rate of 80 lbs. Throughout the growing season, the brothers still felt very unsure about the low Adapt-N rate compared to their usual practice. They kept their eyes on the field after sidedressing, taking note that the Adapt-N strips appeared to be a lighter shade of green. “We thought, uh oh, this is going to be a blow, here we go.”

However, as the season came to a close the results indicated otherwise. There was no loss in yield despite the 140 lb application rate difference. The Donald’s yield monitor data showed spot-yields between about 120 and 230 bu/ac. The average yields for the conventional plots were 174.1 bu/ac, while Adapt-N average yield was 173.6 bu/ac. Robert and Rodney were shocked by the results stating, “it wasn’t until we were combining that we realized the yield wasn’t really different even though there was a 140 lb N difference [in sidedress rate]”.

The results show great promise for the Adapt-N tool and for the Donald brothers’ ability to save on N fertilizer. Assuming that the trial field was fairly representative of the rest of the farm, the Donalds would have saved approximately $70,000 in fertilizer in 2011.  A post-season Adapt-N simulation estimated that they had also reduced their N leaching losses in 2011 by about 77%, from 142 to 32 lbs/ac.

Robert and Rodney intend to collaborate on more extensive testing of the Adapt-N tool next year and see whether different weather conditions affect the recommendations. In addition to another fully replicated strip trial, they may use variable-rate recommendations provided by Adapt-N in strips next to those provided by A&L Laboratories on multiple fields. When discussing variable rate application with the brothers, using rates with drastically higher N amounts than needed by the crop was likened to “aiming for the bull’s eye in the opposite direction of the target,” to which Rodney laughingly replied, “I’ve been doing that all my life.” Variable rate application using Adapt-N should allow for a more accurate AND precise accounting of the effects of organic matter-derived N and texture in interaction with that year’s weather on overall N availability.

Overall the trial suggests that more accurate N recommendations based on weather impacts, in addition to soil and management information, could lead to substantially higher profits for farmers, while reducing environmental losses in most years. This creates a win-win situation as farmers face higher costs for fertilizer and we search for feasible and effective ways to reduce detrimental losses to the environment.

Acknowledgments
This work was supported by grants from the NY Farm Viability Institute and the USDA-NRCS. Thank you to Robert and Rodney Donald for their cooperation in diligently implementing this trial, and taking the time to share their thoughts.  For more information about the Adapt-N tool, visit http://adapt-n.cals.cornell.edu/.