Source: RUTGERS, THE STATE UNIVERSITY OF NEW JERSEY submitted to
DETECTION OF FUNGAL DISEASE AND PLANT STRESS IN A MODEL PERENNIAL CROP SYSTEM USING REMOTE SENSING AND GIS
Sponsoring Institution
National Institute of Food and Agriculture
Project Status
TERMINATED
Funding Source
HATCH
Reporting Frequency
Annual
Accession No.
0184498
Grant No.
(N/A)
Project No.
NJ12101
Proposal No.
(N/A)
Multistate No.
(N/A)
Program Code
(N/A)
Project Start Date
Jan 1, 2000
Project End Date
Sep 30, 2005
Grant Year
(N/A)
Project Director
Oudemans, P. V.
Recipient Organization
RUTGERS, THE STATE UNIVERSITY OF NEW JERSEY
3 RUTGERS PLZA
NEW BRUNSWICK,NJ 08901-8559
Performing Department
PLANT BIOLOGY & PATHOLOGY
Non Technical Summary
Current agricultural methodology is aimed at maximizing productivity while minimizing the area of cultivated land. Development of remote sensing methods fit well with future cranberry farming methods. This research will provide some basic methodologies for other high intensity high value crops. Measurement of yield loss due to symptomless or low grade infections is a difficult parameter to quantify. Proposed research will develop a much better understanding of this important issue.
Animal Health Component
(N/A)
Research Effort Categories
Basic
70%
Applied
20%
Developmental
10%
Classification

Knowledge Area (KA)Subject of Investigation (SOI)Field of Science (FOS)Percent
2031121116050%
2141121116050%
Knowledge Area
203 - Plant Biological Efficiency and Abiotic Stresses Affecting Plants; 214 - Vertebrates, Mollusks, and Other Pests Affecting Plants;

Subject Of Investigation
1121 - Cranberry;

Field Of Science
1160 - Pathology;
Goals / Objectives
To characterize field conditions conducive to Phytophthora root rot. To evaluate remote sensing for disease detection. To identify the areas displaying chronic infection.
Project Methods
Field data will be used to ground truth color infrared aerial photography. Photogrammetric methods will be used to classify photographs and model disease development and crop yield variation. Remote sensing data will be combined with field data in a GIS to predict occurence of diseases.

Progress 01/01/00 to 09/30/05

Outputs
Imagery and data has been collected for 6 years to evaluate the utility of remote sensing technology for cranberry culture. Several important findings were made including methods for early detection of Phytophthora root rot and detection of crop limiting factors such as soil conditions and hydrologic features. Interpretation and analysis of satellite imagery required significant training and expertise. Thus it is unlikely that this technology will be directly transferred to commercial growers. However, if delivery of an analyzed product were achieved the grower could easily utilize the product as either printed maps or as georeferenced images that could be used for scouting purposes. The most significant result of this study was the ability to quantify the magnitude of loss due to specific factors and to rank the impact of diseases and edaphic factors on cranberry yield.

Impacts
Use of satellite imagery for cranberry growers includes the detection of crop losses and monitoring of progress towards resolving crop loss issues. Research has targeted two major diseases, Phytophthora Root Rot and Fairy Ring both diseases were easily detected and progress monitored. Use of this technology will provide a very useful tool towards disease and crop management.

Publications

  • Oudemans, P.V., J.J. Polashock and B. Vinyard (2007) Fairy Ring Disease of Cranberry; Assessment of Crop Losses and Impact on Cultivar Genotype (accepted)


Progress 01/01/04 to 12/31/04

Outputs
Understanding of cranberry crop loss has progressed along several avenues. Remote sensing has provided significant information regarding crop loss that is the result of repeated effects such as soil type, drainage patterns, applicator patterns. The effects on yield are quantifiable and therefore cost effective recommendations to remediate these problems can be developed. Use of GIS for investigation of crop yield and interaction with edaphic characteristics is more complex. Generally speaking, soil type influences disease development and as soil complexity (number of soil types per field)increases so does the liklihood of disease and crop loss. The greatest opportunity for crop yield improvement are in the development and management of soil within a single field and all efforts must be placed at the time of field preparation before planting.

Impacts
Growers will utilize the tools under development for improved farm management.

Publications

  • Pozdnyakova, Larisa, Daniel Gimenez, and Peter V. Oudemans (2005) Spatial Analysis of Cranberry Yield at Three Scales. Agron. J. 97:49-57


Progress 01/01/03 to 12/31/03

Outputs
Precision agriculture is a technology-based approach to farming. From a broad perspective it is rooted in information management. Through use of a geographic information system (GIS) data is projected using geographic coordinates and the output is in the form of maps. Data of different types can be layered in a GIS database and analyses between layers can provide meaningful results that may ultimately help growers make decisions. Using these tools we have investigated methods for yield mapping and assessing disease impacts, utilizing aerial and satellite based imagery and mobile GIS. Methods for detection and quantification of yield loss using remote sensing are the most the primary objectives. In 2003 imagery from the QuickBird Satellite from July and August were used for yield/loss mapping. Validation tests were conducted for 2003. Developed an ArcPad mobile GIS application for growers to develop an on farm GIS. The software is designed to simplify data entry in the field. Pesticide and fertilizer applications are used to populate the databases. Yield data is entered at the seasons end. Applets for crop statistics and field history provide growers the opportunity of reviewing field histories (current and past year) on the fly.

Impacts
Growers will utilize the tools under development for improved farm management.

Publications

  • No publications reported this period


Progress 01/01/02 to 12/31/02

Outputs
Research targeting Phytophthora root rot has demonstrated that mapping requires samples to be taken on a relatively fine scale. By utilizing a GIS approach for analysis relationships with vine density, yield, soil water content, elevation, soil bulk density and electrical resistivity have provided the elements for developing a descriptive model showing interactions of factors affecting and resulting from Phytophthora infection.

Impacts
Development of yield, plant vigor, pathogen, drainage and soils maps will provide field professionals with information to design cultural methods for disease management.

Publications

  • Pozdnyakova,L. P.V. Oudemans, M.G. Hughes and D. Gimenez (2002) Spatial detection and quantification of Phytophthora root rot effects on cranberry yield. Computers and Electronic in Agriculture 37: 57-70.


Progress 01/01/01 to 12/31/01

Outputs
In 2000-2001 several types of imagery were collected. These imagery types included hyperspectral, multispectral, and scanned CIR. Imagery was georeferenced and calibrated (in the case of hyperspectral) using a ground based spectral radiometer. The data was analyzed to examine the relationship of spectral response with crop yield. In an unsupervised classification 20 classes were created and between twelve and nineteen of the classes were significantly correlated with yield, depending on the cultivar. Of these, between four and six classes were positively correlated with yield and between eight and thirteen were negatively correlated with yield. The results were entered into a GIS with a coverage including 310ha of cranberry beds with three predominant cultivars. Results were ground truthed and findings indicate crop losses detected via this approach included Phytophthora root rot, poor drainage, injury due to early harvest (previous year) as well as instances of unknown cause. Results were presented to growers within the study area for evaluation. In cases of Phytophthora root rot and poor drainage growers designed remediation tactics within the GIS.

Impacts
Early detection and quantification of crop loss can allow growers to take preventive action(s). At the forefront of the tools available are cultural mathods aimed at increasing bed uniformity. The tools being developed under this proposal are expected to provide growers with valuable information that can be used to manage the crop growing environment (soils, and water) to aid in reducing inputs while maximising productivity.

Publications

  • No publications reported this period


Progress 01/01/00 to 12/31/00

Outputs
In 2000 a GIS was constructed for test beds in New Jersey. The GIS includes a base map of cranberry beds digitized from USGS digital ortho quarter quads, the cultivar grown, and the yields for each bed from 1993 until the present. In addition, 1:12000 color-IR aerial photography was contracted for all cranberry beds under investigation for 1999. Data were collected in three bands, the green (.5-.6), red (.6-.7), and near-IR (.7-2.0). In 1999, color-IR imagery was obtained in May, July, and August to provide a temporal archive of cranberry crop development over a season. The imagery was scanned at 1500dpi giving a ground resolution of 30cm per pixel and georeferenced. The imagery was analysed in the following manner: 1) An unsupervised classification was done on the color-IR photography to map bed features and variability, 2) spectral information was derived from the resulting classification scheme and statistical relationships were developed between the classes and ground-truthed data to map bed yield. The spatial distributions of two cranberry diseases, Phytophthora root rot and fairy ring were examined and the economic impacts determined using the CIR aerial photography, historical records of bed yields, and ground-based yield measurements. Results indicate that root rot occurs over larger areas than fairy ring and causes more significant yield losses. Treatment to reverse the effects of root rot appears to provide long-term control and significant positive economic impact for the grower. Fairy ring appears not to be an economically important disease, and the cost of treatment generally exceeds the impact on crop productivity. Early remote sensing results demonstrate significant correlation of the digital CIR imagery using unsupervised classifications with both yield and early disease detection. We have also found significant correlations of CIR aerial imagery (i.e. reflectance values of a single band (NIR, R, or G) or the ratio, NDVI) with yield, vine density, Phytophthora root rot symptoms, and soil properties, such as soil infiltration rates and elevation. Results, however, were not comparable over large areas or between growing seasons because the available aerial photography was not radiometrically calibrated at the time of flight. This resulted in large variations across the imagery that altered the "color" within the frames. Many of the frames appeared to have "hot spots" areas of sun glare that were difficult to remove. In addition, large variation in color in the imagery from one year to the next causes high variability within the derived classes. For the current growing season we have obtained hyperspectral imagery from an airborne scanner as well as satellite imagery (Ikonos, Space Imaging). This data is being analyzed to determine the optimal parameters (spectral and spatial resolution, band width and spectral wavelengths) for this application in remote sensing.

Impacts
The primary goal of this proposal is to develop the key elements of a precision agriculture program applicable to high value, woody perennial crops, such as cranberries. Perennial crop systems exhibit tremendous variability in crop yields and quality as imposed by variations in soil properties (water availability and nutrient deficiency) leading to crop stress (disease development and weed competition). We are using state of the art methodologies (GIS, GPS, remote sensing, nonintrusive ground sampling) to quantify and map spatial variation of the crop, soils, and diseases. We have developed preliminary yield and pathogen maps based on remote sensing and these will be field tested this summer.

Publications

  • Pozdnyakova,L. P.V. Oudemans, M.G. Hughes and D. Gimenez (2000) Estimation of spatial and spectral properties of Phytophthora root rot and its effects on cranberry yield. COMPAG (in press)
  • Pozdnyakova,L , P.V. Oudemans, M.G. Hughes and D. Gimenez (2000) Spatial detection and quantification of Phytophthora root rot effects on cranberry yield. Proceedings of the Second International Conference on Geospatial Information in Agriculture and Forestry. I: 295-302
  • Oudemans P.V., Hughes M.G., Pozdnyakova,L. (2000) Evaluating commercial cranberry beds for variability and yield using remote sensing techniques. Proceedings of the Second International Conference on Geospatial Information in Agriculture and Forestry. II: 444-448
  • Oudemans, P.V., Hughes M.G., Pozdnyakova, L. (2000) Detection and quantification of diseases using aerial remote sensing methods. Phytopathology 90: 1145 (abstract)
  • Pozdnyakova, L.A., P.V. Oudemans, D. Gimenez, and M.G. Hughes. 2000. Spatial distribution of diseases, yield, and soil physical properties on commercial cranberry beds in New Jersey. Poster presentation and abstract at Annual Meeting of ASA/CSSA/SSSA. 30 October - 3 November. Minneapolis. MN. 248.