diversity of the major sugar beet growing areas. 
The predictive value of the model is rather poor 
considering the fact that pluviometric data till 
October 31st are to be included. In the model the 
leaf yellowing percentage is the only non- 
meteorological factor and has to be estimated 
visually at the end of August. Leaf chlorosis can be 
detected successfully by multispectral remote sensing 
(Andrieu 1977, Boehnel et al 1983, Reichert 1983). 
In practice the Royal Belgian Institute for Sugar 
Beet Amelioration relies on biweekly sampling in 
the major sugar beet growing areas to assess biomass 
and formulate trends. 
3 MATERIALS AND METHODS 
3.1. Collection of agronomic data 
The experimental results reported herein were 
obtained in 1984 and 1985 from test fields located 
in Sint-Laureins, in the north-west of Flanders. Soil 
type can be characterized as an aquic udifluvent. 
The area constitutes one of the richest agricul 
tural regions featuring crops as winter wheat, winter 
barley, sugar beets and potatoes. 
Sugar beets cv "Allyx" were sown on 23.04.1984 and on 
22.04.1985 respectively. Emergence was recorded on 
14.04.1984 and on 05.05,1985. Application of 
fertilizer and herbicides was similar during both 
seasons and is not further discussed here. Traces of 
fungicide sulphur spray could be detected on leaves 
on 21.08.1984. The use of insecticides on other dates 
did not leave visible traces on the canopy. 
Originally a 10 day interval sampling scheme was 
envisaged. Experiments were to be conducted only when 
a direct solar path free of clouds was available. 
Adverse weather conditions occurred frequently during 
both growing seasons. This resulted in 10 sampling 
dates in 1984 and 9 sampling dates in 1985. 
On each sampling date 3 plots were located by 
throwing a 80cm by 80cm frame onto the canopy from 
randomly defined coordinates in the test field. All 
plants inside the frame were extracted. Green leaves 
were separated from the roots, spread out on a matt- 
black painted surface and recorded on black-and-white 
film. All roots (with heads cut off) were weighed 
immediately to determine fresh weight. Three randomly 
selected roots per plot were retained for sugar 
content determination and deep-frozen to avoid sugar 
loss awaiting analysis. 
Besides root fresh weight and sugar content (%) green 
leaf area index (GLAI) was determined. The latter was 
accomplished by placing a transparent dot grid (4mm 
spacings) on top of 18cm x 24cm sized photographic 
paper during enlargement. By counting the dots on the 
leaves GLAI could be computed as dimensions of black 
background and sample plot were known. This method 
proved to be much faster than the use of a polar 
planimeter. Parallel measurements using both methods 
on randomly selected samples did not reveal 
significant differences (Student's T test). 
3.2. Extraction of multispectral data 
Simultaneous recording of the test plots on CIR film 
assured direct relationship of biomass to 
multispectral parameters to be extracted from the 
images. A MIRANDA SENSOREX EE (*) camera fitted with 
standard 50 mm optics was mounted on a light weight 
metal boom supported by a ZEISS tripod. The camera 
shutter could be triggered using an air release.A B&W 
No Y3 filter, bearing close resemblance to the widely 
used VRATTEN 12 filter, was used throughout the 
(*) This and other trademarks are mentioned for 
information only. No endorsement by the authors is 
implied. 
experiments. The selected emulsion was a 35mm KODAK 
EKTACHROME 2236 film. 
Pictures were taken at solar noon plus or minus 2 
hours to avoid influences by changing solar zenith 
angle. The plane of the film was kept parallel to the 
plane of the canopy. Camera distance to ground level 
was fixed at 2.30 metres. An area of lm by 1.5m 
filled the 24 x 36 mm frame. A KODAK grey card with 
known reflectance characteristics was included in 
every picture. A second reference panel was judged 
unnecessary as the amount of airlight between camera 
and target was considered negligible in relation to 
total reflected energy. Conventional light meters do 
not indicate proper diaphragm/shutter speed 
combinations for infrared-sensitive emulsions. Hence 
series of 4 slightly different combinations were made 
using an approximate meter setting for 50 ASA, It was 
experienced that at least one slide was suitable for 
subsequent processing. 
Exposed emulsions were developed according to NASA 
standards. From each development batch a strip of 
film was exposed through a step wedge in a 
sensitometer. The step wedge image was used for 
preparation of characteristic curves. 
On each slide 50 randomly located points were 
measured using a MACBETH TD 504 transmission densito 
meter. The filter assembly consisted of VRATTEN No 94 
(blue), No 93 (green) and No 92 (red) filters 
allowing measurements of integral densities relating 
to green, red and infrared reflectance respectively. 
A .5 mm aperture was used. Three measurements were 
made on the reference panel. Integral densities were 
converted to analytical densities using unit spectral 
dye density data for the CIR emulsion. Green, red and 
infrared reflectance, as well as a number of 
vegetation indices and transformations were 
calculated for each slide. 
Brightness, Greenness and Yellowness were determined 
using the method outlined by Jackson (1982). 
Following linear combinations similar to Tasseled Cap 
transformations for Landsat data were obtained: 
Brightness= .603*G + .489*R + .629*IR 
Greenness =-.292tG - .598*R + .746*IR 
Yellowness=-.794*G + .634*R + .217*IR 
Eventually only Greenness was retained for further 
analysis due to its proven relationship to green 
biomass. In addition to the IR/R ratio (Vegetation 
Index or VI) and Normalized Difference or ND 
(SQRT((IR-R)/(IR+R) + .5)), the Perpendicular 
Vegetation Index (PVI) as the distance to the Soil 
Line in IR/R space (Richardson and Viegand 1977) was 
calculated. Figure 1 shows the soil lines for the 
test fields.Full details on methodology, applied 
software and hardware configuration used for 
extraction of reflectance from CIR slides can be 
found in De Vulf and Goossens (under review). 
Cover percentage could be calculated by placing a dot 
grid on projected slides and counting the amount of 
points falling on vegetation. 
Figure 1. Soil line for an aquic udifluvent. 
4 RESULTS 
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