Development of a Knowledge Base for Site-Specific Application of Crop Nutrients

1998 Annual Report for LNE98-110

Project Type: Research and Education
Funds awarded in 1998: $109,968.00
Projected End Date: 12/31/2002
Region: Northeast
State: New York
Project Leader:
Harold Van Es
Cornell University, Dept of Soils and Crops

Development of a Knowledge Base for Site-Specific Application of Crop Nutrients


This project focuses on the use of precision agriculture technologies to improve the efficiency and reduce the environmental impact of nutrient management on New York farms. Tools such as intensive soil sampling, split-planter hybrid and fertilizer strip trials, remote sensing, yield monitoring and geographical information systems are used to evaluate the potential for precision management of crop inputs. Results show good potential for use of such technologies, including site-specific application of lime, P and K fertilizer. N fertilizer is better adjusted annually based on early-season weather. Educational activities included a grower meetings and field day, in-service training, certified Crop Advisor Training, and a two-day workshop.

This project evaluates the use of precision agriculture technologies for the purpose of increasing the efficiency and reducing the environmental impact of nutrient management on New York farms, and to develop guidelines and education on the implementation of these technologies.

In 1999, field trials were initiated on five fields associated with three farms in central New York: Elmer Richards and Sons Farms near Skaneateles, and Split Pine Farms and Freier Farms, both near Geneva. The former is a dairy operation, while the other two are primarily cash crop farms. The fields range from 10 to 25 acres. Two of them regularly receive manure, and all were planted into maize in 1999, 2000 and 2001. Input was sought in February of1999 during a meeting of the New York Precision Agriculture Alliance (growers, ag business, researchers, educators, and agency staff) to refine the experimental procedures for this project.

For each of the growing seasons 1999 and 2000, soil samples were collected on a non-aligned grid for each half acre. This oversampling allows for a spatial analysis of nutrient distribution and the determination of optimal sample spacing. Soil samples were submitted to the Cornell Nutrient Analysis Laboratory for standard soil test analysis. Soil samples were also collected for nitrate analysis at the same grid points in mid-June (for PSNT analysis), and at the end of the growing season (for residual nitrate analysis). For each year, two corn hybrids (Pioneer 3752 and 37M81) were planted using a split-planter approach with strips along the length of each field. P and K fertilizer were applied according to Cornell recommendations. Starter fertilizer N was applied uniformly in each field at rates ranging from 25 to 60 lbs/ac. Supplemental sidedress N was applied in field-scale strips using two rates: 25 lbs/acre above and below the Cornell-recommended rate. This allowed for an annual and field-scale evaluation of maize response to N fertilizer, and the need for upward or downward adjustment of those rates. For the year 2000, field-scale measurements were made of maize growth, soil water content, soil strength and N content in the lower stalk.

For each field, digital georeferenced multi-spectral, color-infrared images were acquired from aerial overflights either three (1999) or two (2000) times during the growing season. The first set of images for each growing season were obtained for evaluation of field variability under bare soil conditions, while the mid-season images were collected to assess crop health. The images were acquired through a collaborative effort with Emerge-mPower3, and were processed to derive the SoilView and Vegetation Index (NDVI) products that aim at providing interpretive information on soil variability and crop health, respectively.

Yield data was collected using weigh wagons and digital georeferenced yield monitors. The yield monitors provide a spatial distribution of yield on the fields. Weigh wagons provided strip-average yields, which were used for calibration and validation of the yield monitors. The AgLinkTM software (courtesy of Agris) was used to analyze the strip trial data and evaluate the spatial distribution of hybrid and N fertilizer response. ArcViewTM (ESRI) and Vesper (Australian Center for Precision Agriculture) software were used for spatial analysis and presentation of the data.

Preliminary data analysis provided the following results:

Soil nutrient and pH variability on typical New York farms shows structured variability. This is especially the case for the manured fields in this study. The potential for the use of site-specific application is therefore high, especially for lime; pH variability on several fields was such that field-composited samples would have resulted in a biased estimate, and the use of uniform lime rates would have resulted in considerable overapplication in certain parts of the field. P levels on the manured fields showed clear field trends which were agronomically and environmentally significant. We determined that optimum sampling schemes for central New York fields are based on a composited sample for every three to five acres.

PSNT results showed structured field-scale variability, suggesting the need for sampling of all parts of a field to obtain representative distributions, and a potential for the use of variable-rate N application. However, the yield data from the N-rate strips did not support this, i.e., N response did not vary over the field. Based on concurrent research at the Musgrave Research Farm, we have concluded that precision management of N in the Northeast should focus on annual adjustment of N rates based on early-season weather conditions. We are working on developing a new recommendation system using real-time, site-specific weather data and simulation models.

Yield monitors can be very useful for on-farm research. Besides fine-tuning N response, we determined this technology to be very useful for split-planter trials. On the manured fields, hybrid 37M81 outperformed 3752 by 7 bu/ac in 1999 and by 19 bu/ac in 2000. On the grain farms, little difference was observed in hybrid response, suggesting that the varieties interact strongly with locations, presumably soil quality and nutrient status. This indicates that on-farm research is useful and yield monitors readily provide a return on investment. A partial-budget spreadsheet was developed to analyze this for various-size farms. The yield monitor also quantifies yield losses in low-productive areas of the field, thereby providing information on the potential for remedial action.

Remotely sensed images can provide useful information for field management, and show considerable discrimination in field-scale soil variability and crop growth. Bare soil and crop images were well correlated with yield potential, although they generally did not predict field-scale nutrient variability.

Impact and Potential Contributions
This project is providing information that is essential to the use of the next-generation crop management tools. Guidelines on soil sampling, improved N management, on-farm research, and the use of new technologies provide new insights into improved agronomic and environmental management of croplands.

Reported December 2000


Wayne Knoblauch

Professor, Dept. of Applied and Economics and Mana
Cornell University
Tim Taylor

Mapshots, Inc
Doug Freier

Freier Farms
Geneva, NY
Dill Otis

Research Support Specialist
Cornell University
Jason Kahabka

Extension Support Specialist
Cornell University
Kevin Swartley

Split Pine Farms
Geneva, NY
William Cox

Professor, Dept. of Crop and Soil Sciences
Cornell University
Tawainga Katsvairo

Postdoctoral Associate, Dept. of Crop and Soil Sci
Cornell University
Michael Glos

Research Support Specialist
Cornell University
Craig Richards

Elmer Richards and Sons Farms
Skaneateles, NY
Antoni Magri

M.S. candidate, Dept. of Crop and Soil Sciences
Cornell University