6.4 Remote Sensing of Pasture Mass and Quality
Principal
Investigators
Michael
Collins, Professor, Agronomy
Tom Mueller, Assistant Professor, Agronomy
David Ditsch, Associate Extension Professor, Agronomy
C.T. Dougherty, Professor, Agronomy
Cooperators
J.W.
Wyles, Management Operations, Eden Shale Farm
Charles May, County Agent for Agriculture, Perry County
Larry Clay, Herdsman, D&D Ranch, Chavies, Kentucky
Introduction
Forage crops occupy approximately 60% of the 13 million acres of land
used in agriculture in Kentucky. Optimum use of these areas for forage
production is dictated by slope, soil drainage characteristics, soil pH,
fertility, and numerous other factors. Cash receipts to Kentucky producers from
livestock and livestock products in 1997 totaled $2 billion. In 1997 Kentucky
ranked 8th nationally in total cattle numbers. Dairy production is
declining rapidly in Kentucky, in large part due to chronically low milk prices.
Increased efficiency of pasture use in dairy systems would reduce the cost of
milk production and help to reverse this disturbing trend.
Pressures
of input costs and variable livestock and milk prices require producers to
constantly search for improvements in productivity and/or efficiency of
production to remain competitive. Forages, especially grazed forages, provide
the lowest-cost source of nutrients for beef and dairy cattle in Kentucky. Much
of this potential gain in efficiency of production is lost if too much of the
forage produced on a pasture goes unutilized. It has been estimated that only
about one-third of the forage produced on Kentucky pastures is actually
utilized, the remainder becomes senescent and low in quality. A major
contributor to poor utilization of pastures is a lack of accurate information on
the amount and quality of forage available at any given time.
Remote sensing and terrain attribute information could provide us with
new opportunities to better understand the factors that contribute to variable
forage production and utilization and could form the basis for development of
new management strategies that reduce waste and convert more of the forage
produced into livestock products.
The objectives of this project are:
1)
To use soil:plant spatial relationships to develop more efficient forage
management systems for Kentucky grasslands; and
2)
To improve forage utilization by using remotely sensed spectral data to
provide livestock producers with accurate, timely information on forage
availability and quality.
Background
The basic concepts of precision agriculture for row crops include grid
mapping of soil characteristics in the field using Differential Global
Positioning System (DGPS) combined with grain yield monitoring during harvest
(Shearer et al., 1999). By overlaying soil and grain yield maps, producers can
identify areas of reduced yield that may indicate nutrient deficiencies for land
units much smaller than the whole field, thereby more precisely meeting the
unique management needs of each area.
These site specific management concepts of precision agriculture might
apply to high value forages, such as alfalfa for cash hay but, due to the soil
limitations and lower productivity per acre inherent to most pastures, intensive
and frequent soil or pest sampling may never be economically feasible in most
situations. However, the great economic importance of livestock products
produced from Kentucky grasslands warrants full consideration of the possible
roles these technological advances could play in pasture and hayland management.
Even in the event that detailed remote sensing or other site specific
information is not economical for forage managers due to cost, the information
that could be gained by improving our understanding of relationships between
forage yield, botanical composition, forage quality and soil factors could form
the basic for improved extension recommendations to Kentucky producers.
For example, DGPS and spatial analysis applied to typical Kentucky
forage situations could provide important new information for development of
superior extension recommendations on pasture management. Past research has
failed to consider the high degree of variation in slope, aspect, drainage
characteristics, as well as pH and nutrient levels in developing recommendations
for pasture management. Newly available technologies for viewing and analyzing
spatial variation in terrain characteristics and soil properties should allow
great advances in our knowledge base for optimum grassland management.
Technological advances have made obtaining high quality, multi-spectral
remote sensed imagery practical, straight forward, and affordable for
agricultural producers. Satellite images (e.g. Agri ImaGIS, Spot Image Corp) and
aerial images (e.g. Mercator, Emerge) are available at a variety of resolutions
in digital formats. Figure 1 gives an example of
remote sensed imagery of the type that could be obtained for application in
grassland management.
Among the parameters successfully determined by remote sensing is plant
nitrogen status. Blackmer et al. (1996a) found at the R5 growth stage that crop
reflectance at 536 nm (with filtered black and white photography) predicted
yield response to N very well (r2= 0.93). They also found that the ratio of light reflectance between
550 and 600 nm to light reflectance between 800 and 900 nm provided a sensitive
indicator of N stress (Blackmer et al., 1996b). Schepers (1998) found that red and near infrared reflectance
data could be used to provide reasonable estimates of crop stress. Accurate
information on plant N status would be doubly useful in forage management since,
in addition to being a frequently limiting plant nutrient, low N concentrations
can also limit livestock productivity.
The spectral range of information available by remote sensing includes visible as well as near infrared (NIR) and shortwave infrared (Figure 2). Routine forage analysis for N, fiber, digestible energy and other important forage constituents, utilize NIR spectroscopy of finely ground forage tissue (Collins and McCoy, 1997). It may be possible to gain useful estimates of several forage quality parameters using this remotely sensed spectral information.
Research Approach
Two sites will be utilized in this project, a site in Perry County, in
southeastern Kentucky located on reclaimed surface mined pastureland and a site
on the Eden Shale Farm in Owen County in north central Kentucky.
Site Mapping - Reclaimed Mineland Pastures: Initial mapping, completed on the Perry County site as part
of an earlier project, has revealed large variation in most soil parameters,
including pH, available P, exchangeable K, and others (eg. pH map, Figure
3). The main objective of the earlier project was to determine optimum beef
cow/calf stocking density for mined land pastures in the Appalachian region of
Kentucky (Teutsch et al., 1998). Approximately 320 points were permanently
placed at a density of 1 point per acre over pasture treatments that include
pasture allowances of 3, 6 and 9 acres per cow/calf unit for mature Angus brood
cows and their calves. Trimble GPS equipment was used to locate each permanent
sample point and an additional 11,000 points were collected to accurately locate
slopes, benches, drains and other features that make up the site. (Trimble,
1996; ArcView, 1996). Each pasture treatment is replicated twice and adjacent
ungrazed areas are included as controls.
Funding for the
stocking rate study, supported by the Robinson Trust, is expected to cease at
the end of the current fiscal year. However, the pastures remain available for
this proposed work and as do the 80 bred cows that graze the site. These
pastures, with the wide range in biomass density created by the three-fold range
in stocking rates, should provide an ideal situation for assessing the potential
for remote sensing information.
Soil
samples will be collected annually in spring, by compositing several cores taken
within a 5-meter radius of each permanent sample point. Each sample will be
analyzed for pH, potential acidity, P, K, Ca, and Mg. These maps will also be
used to describe and present information on soil types, soil fertility, slope,
herbage mass, cover, botanical composition, waterways, erodibility, etc., as
described recently by Teutsch et al.
(1998). Biomass from two randomly selected 1 ft2 areas within a 5-m
radius of each sample point will be collected three times each season; spring,
summer and fall (May 15, July 15, September 15) in order to represent the full
range in forage yield, species contribution to the sward, plant maturity, plant
moisture status and other important variables.
Site Mapping - Permanent Grassland Pasture Site:
Eight 1-ha tall fescue pastures at the Eden Shale farm in Owen County, which
were established 30 years ago, severely infected with Acremonium
coenophialum, will be used as the
second site. We
also expect to encounter large variation in soil and plant
characteristics on the permanent pasture site on undisturbed soil because
grasslands are generally relegated to the most variable fields on a farm that
are not suited to row crop production. Because of the smaller total area in the
second site, two hundred fixed sample sites will be located with GPS at 25 m
intervals (25 per hectare) (Goovaerts, 1999) (excluding fence lines).
Comprehensive management, climate, and production records are available for the
Eden Shale farm over the past 30 years. This information should prove useful in
interpreting spatial variation in soil parameters and in pasture responses.
Calibrated non-destructive procedures (sward surface height, rising
plate, and electronic pasture probe) will be used to estimate herbage mass,
cover, and botanical composition (Dougherty, 1999) at each sample point three
times each season as previously described. Vegetation will be sampled in spring,
summer and fall (May 15; July 15; and September 15). As for site one, remote
sensing spectral data will be obtained in conjunction with each field sampling.
Remote Sensing Data
Ortho corrected 1-m resolution remote
sensed imagery will be purchased from Mercator GIS and Environmental Corporation
in Houston, TX. Each image has four bands. The wavelengths of the bands can be
user-specified. In addition, aerial photos will be collected near the time of
each sampling event. These photos will be scanned, digitized and geo-referenced.
At each location where we have ground information, remote sensing software will
spear through each of the images and determine the number of counts associated
with each band. The SPOT (Satellite 20-m) system provides visible (green, red)
and NIR spectral ranges, and the spot 4 system provides mid IR data. The
Mercator (3-m aerial) system provides visible (red, green, blue) and NIR data.
Forage Quality Analysis
Forage samples will be dried at 65º C and ground to 1 mm size prior to
composition analysis. Laboratory analysis of forage samples will include
moisture (100º C), total nitrogen by the Kjeldahl procedure (Bradstreet, 1965),
neutral detergent fiber, acid detergent fiber, acid detergent lignin, cellulose
and hemicellulose using the detergent system (Goering and Van Soest, 1970;
Robertson and Van Soest, 1980. In vitro dry matter disappearance will be
determined as a estimate of in vivo digestibility of forages (Tilley and Terry,
1963; Marten and Barnes, 1980). Typical coefficients of variation for repeated
NDF and ADF analyses on forage samples are 2 to 4. In vitro determinations are
inherently more variable due to the use of rumen inoculum. Near infrared
reflectance spectra will be collected for each ground forage sample (1100 to
2500 nm). Calibration software will be used to select a portion of the total for
calibration analysis using the methods described above. Calibration equations
for prediction of forage quality constituents will be conducted using equations
developed from laboratory analysis for N, NDF, ADF, ADL, Cellulose,
Hemicellulose, and IVDMD.
Expected Benefits
Information gained in this research will be summarized and disseminated
to producers through field days, winter meetings, and extension publications.
Grazing schools are held annually at several locations in the state where
producers and county agents gather to learn up-to-date information on pasture
management. We will incorporate information learned through the proposed
research into these training sessions.
The potential impact of this work on livestock production is large. If
even a 10% improvement over current estimates of forage utilization in the state
resulted from adoption of recommendations resulting from this work, the impact
on farm receipts would exceed $200 million annually. Significant findings such
as those that could result from the proposed work are also very valuable when
competing for future federal grant funds.
Deliverables
Deliverables would occur primarily in the second year of the project,
since data can be unreliable. These would include anticipated use of the
information at 3-5 field days; 3 grazing schools, and 3 winter meetings.
Publications resulting from the work will include extension publications written
to provide information directly usable by Kentucky livestock producers.