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of Florida

C CI uAND EDUCATION
f FOOD AND AGRICULTURAL iE
UNIVERSITY OF FLORIDA
NATIVEE EXTENSION SERVICE

BELIE GLADE, FLORIDA
MAY 13, 1993

3~k~
lo^- 3

THE UNIVERSITY OF FLORIDA
INSTITUTE OF FOOD AND AGRICULTURAL SCIENCES
EVERGLADES RESEARCH AND EDUCATION CENTER, BELLE GLADE
P.O. BOX 8003 / BELLE GLADE, FLORIDA 33430-8003 / TEL. 407/996-3062 / FAX 407/996-0339
1993 SUGARCANE GROWER'S SEMINAR

MAY 13, 1993

F. J. Coale and T. J. Schueneman, Editors
T. J. Sahueneman, Moderator PA]

CANAL POINT VARIETY UPDATES CP85-1308 AND CP85-1382 1
Glaz, B.

SUGARCANE INTERSPECIFIC HYBRIDS FOR BIOMASS ENERGY SOURCES 7
Deren, C. W., G. H. Snyder, and P. Y. Tai.

WATER AND NITROGEN MANAGEMENT OF SAND LAND SUGARCANE 12
Obreza, T. A. and D. L. Anderson.

PRELIMINARY FINDINGS AND POTENTIAL IMPLICATIONS OF A NEGATIVE 22
RELATION-SHIP BETWEEN SUCROSE AND TONNAGE
Alvarez, J., C. W. Deren, and B. Glaz.

SUPPLY RESPONSE OF THE FLORIDA CANE SUGAR INDUSTRY 29
Advincula, C., L. C. Polopolus, R. W. Ward, and
J. Alvarez

SUGARCANE RESPONSE TO LIMESTONE AND GYPSUM APPLICATION ON 40
ACIDIC FLORIDA SPODOSOLS
Coale, F. J. and T. J. Schueneman.

**********BREAK**********

CORRELATION BETWEEN FIBER CONTENT AND JUICE QUALITY OF 55
SOME CP SUGARCANE VARIETIES
Tai, P. Y.

NEW SUGARCANE DISEASES IDENTIFIED IN FLORIDA; DRY TOP ROT 61
AND PURPLE SPOT (RED LEAF SPOT)
Comstock, J. C., J. D. Miller, D. F. Farr, and
J. M. Shine, Jr.

REDUCED SOIL INSECTICIDE USE IN SUGARCANE PLANTED AFTER RICE 62
Cherry, R. H., Powell, G., and M. Ulloa.

AVAILABLE CHEMICAL AIDS FOR SUGARCANE PRODUCTION IN FLORIDA, 67
1993
Schueneman, T. J.

THE INFLUENCE OF SHORT-TERM FLOODING FOLLOWING PLANTING ON 70
INITIAL STAND ESTABLISHMENT AND YIELD OF SUGARCANE
Raid, R. N. and C. W. Deren.

The Institute of Food and Agricultural Sciences is an Equal Employment Opportunity Affirmative Action Employer authorized to provide research,
educational information and other services only to individuals and institutions that function without regard to race, color, sex, age, handicap or national origin.

SFLORIDA COOPERATIVE EXTENSION SERVICE
THE UNIVERSITY OF FLORIDA
INSTITUTE OF FOOD AND AGRICULTURAL SCIENCES

WELCOME

On behalf of the University of Florida Everglades Research and Education
Center, and the Cooperative Extension Service, I would like to welcome you
to the 1993 Sugarcane Growers Seminar. It has been two years since the last
seminar and lot has been happening. There are 12 papers to be presented
today covering varieties, water management, pest management, nutrition, and
economics.

We are in a time of transition. Probably the most important change is the
industry move toward total mechanization. Another factor of great importance
is the public scrutiny of the stewardship we give our farmland and other
natural resources. Research will continue to play a major role in providing
solutions to world hunger and insure the sustainability of our food production
system.

The support you continue to give to sugarcane research programs at the
EREC, the USDA Canal Point Sugarcane Research Station, and in your own
companies is greatly appreciated. By working together to identify problem
areas, determining the best solutions, and then implementing these solutions,
we will insure a long life for the sugarcane industry in the EAA.

Acknowledgements

Dr. Frank Coale and I wish to express our appreciation to Isabel Coonfare,
senior word processor, for typing and printing this publication, to EREC staff
for its assembly, and to Nancy Renz of the Palm Beach County Cooperative
Extension staff for printing the cover of this publication and for printing the
accompanying handout "Available Chemical Aids For Sugarcane".

Thomas J. Schueneman, PhD May 13, 1993
University of Florida
Extension Agent HI

The Institute of Food and Agricultural Sciences is an Equal Employment Opportunity Affirmative Action Employer authorized to provide research, educational
information and other services only to Individuals and Institutions that function without regard to race, color, sex, age, handicap or rational origin.
COOPERATIVE EXTENSION WORK IN AGRICULTURE AND HOME ECONOMICS, 81TTE OF FLORIDA, IFAS, UNIVERSITY OF FLORIDA,
U.S. DEPARTMENT OF AGRICULTURE, AND BOARDS OF COUNTY COMMISSIONERS COOPERATING.

CANAL POINT VARIETY UPDATE (1993)

CP 85-1308 and CP 85-1382

Barry Glaz, Agronomist

Canal Point scientists examine many crosses each year from a

diverse group of sugarcane varieties. Each seed born from these

crosses can grow into a unique sugarcane variety. About 100,000

true seeds, or varieties, are planted annually in the Canal Point

Seedling Stage. It takes a minimum of 8 years to release a variety

after planting it as a seedling. If a seedling planted this year

proves worthy of release, we will not release it before 2001.

During this 8-year period, USDA, University of Florida, and
Florida Sugar Cane League geneticists, agronomists, pathologists,

and entomologists evaluate these varieties. By visually evaluating

the varieties during the first two years, we reduce the number of

varieties from the original 100,000 to about 1,000. These 1,000

varieties are planted in Stage II at Canal Point. Stage II is the

first stage in which we quantify cane production, sugar tonnage,

and sugar concentration yields for new CP varieties.

Primarily using the yield data from Stage II, but still

incorporating visual impressions, Canal Point scientists recommend

from 125-140 varieties for continued evaluation in Stage III.

Evaluations become more rigorous in Stage III. Before Stage III,

we plant experiments at Canal Point and only evaluate plant cane.

We plant Stage III in commercial fields at four locations and

evaluate it through first ratoon. Each Stage III experiment

contains two replications. Since these experiments are planted at

Page 1

four locations, we have eight replications per variety each year.

Earlier stages have only one observation per variety.

The 11 most promising varieties from Stage III tests are

advance to Stage IV. We plant Stage IV at nine locations, in four

large plots at each location, and evaluate them through their

second-ratoon harvests. When a cycle finishes, we have 36 yield

observations for each variety each year for 3 years, or 108 total

replications. Such intense evaluations improve our chances of

correctly predicting the performance of a new commercial sugarcane

variety.

After successfully completing Stage IV, varieties often need

1 or 2 additional years before release. During this time, the

Florida Sugar Cane League increases seed cane of new varieties to

meet initial grower requests. Throughout the evaluation process,

screening for disease resistance occurs. By the end of the

process, varieties are tested for their reactions to rust, smut,

leaf scald, eye spot, and ratoon stunting disease.

The two varieties upon which this report concentrates, CP 85-

1308 and CP 85-1382, are currently in the seed-cane increase phase.

The Committee that decides their fate does not meet until June

1993. Depending on how much seed cane is available, the Committee

may vote for release of one or both varieties for this year or next

year.

Leaf scald infections on CP 85-1308 and CP 85-1382 caused the

Committee to delay their seed-cane expansion in 1990. Since then

we have learned that their levels of leaf scald were not unusually

high compared to other commercial varieties. Still, growers should

Page 2

remain cautious of leaf scald on both varieties. Sugarcane rust

has also caused minor infections on these varieties. As with leaf

scald, growers should remain cautious about sugarcane rust on CP

85-1308 and CP 85-1382.

The plant-crop Stage IV harvest for these varieties occurred

in the 1989-90 harvest season (Glaz et al. 1991a). Before we

harvested any of the nine experiments containing these varieties,

a severe freeze occurred. Temperatures ranged from 21-280 F,

depending on location. In the subsequent harvests, CP 85-1382 had

excellent cold tolerance. It had sugar concentration yields often

higher, and always at least equal to those of CP 72-1210 at all

nine locations. CP 85-1308 had poor cold tolerance but high cane

tonnage yields.

In the first-ratoon crop, both CP 85-1308 and CP 85-1382 had

cane tonnage yields higher than those of CP 70-1133 (Glaz et al.

1991b). No freeze occurred before this harvest. Under these

conditions, both varieties had outstanding sugar concentration

yields. Both varieties also maintained high cane tonnage and sugar

concentration yields in the second-ratoon harvest (Glaz et al.

1992).

Both varieties have other characteristics making them

distinctive. Each variety grew in two Stage IV experiments planted

on sandy soils. Both did well in these tests. CP 85-1308 did

particularly well. Although growers should plan to reap higher

profits from CP 85-1308 on muck soils, they should take special

note of its excellent potential on sandy soils.

We did not test either of these new varieties under mechanical

Page 3

harvesting conditions, but CP 85-1382 meets many criteria that

mechanical harvester operators prefer. Although it produces a lot

of sugar per acre, it does so with moderate or moderately high cane

tonnages and high sugar concentrations. In addition, it often

remains erect after burning, although probably not as consistently

as does CP 72-1210. CP 85-1308 does not have an outstanding growth

habit for mechanical harvesting.

Tables with much of the Stage IV data for these two varieties

follow.

Page 4

Tons Cane per Acre
Muck

Variety

CP 70-1133
CP 72-1210
CP 85-1308
CP 85-1382

Plant
Cane

68.28
49.50
68.06
59.51

First Second
ratoon ratoon

60.25
48.34
65.51
65.41

50.30
38.89
51.09
50.55

Pounds Sugar per Ton of Cane
Muck

Variety

CP 70-1133
CP 72-1210
CP 85-1308
CP 85-1382

Pounds Sugar per Acre
Muck

Variety

CP 70-1133
CP 72-1210
CP 85-1308
CP 85-1382

Plant
Cane

11,686
9,821
11,689
12,784

First Second
ratoon ratoon

12,493
10,344
14,844
15,116

11,162
8,720
12,019
12,127

Tons Cane per Acre
Sand

Variety

CP 70-1133
CP 72-1210
CP 85-1308
CP 85-1382

Plant
cane

47.53
41.80
51.37
43.18

First Second
ratoon ratoon

42.40
36.89
43.78
44.21

44.40
37.55
49.29
50.64

Page 5

Mean

59.61
45.58
61.55
58.49

Plant
Cane

171.2
198.4
171.8
214.8

First
ratoon

207.4
214.0
226.6
231.1

Second
ratoon

221.9
224.2
235.3
239.9

Mean

200.15
212.21
211.20
228.59

Mean

11,781
9,629
12,851
13,342

Mean

44.78
38.75
48.15
46.01

Pounds Sugar per Ton of Cane
Sand

Plant First Second
Variety cane ratoon ratoon Mean

CP 70-1133 234.5 248.7 232.9 238.69
CP 72-1210 235.3 253.9 235.1 241.45
CP 85-1308 226.7 273.6 243.7 247.97
CP 85-1382 239.5 259.0 248.0 248.82

Pounds Sugar per Acre
Sand

Plant First Second
Variety cane ratoon ratoon Mean

CP 70-1133 11,148 10,544 10,340 10,677
CP 72-1210 9,838 9,368 8,828 9,345
CP 85-1308 11,644 11,978 12,010 11,877
CP 85-1382 10,339 11,449 12,560 11,450

REFERENCES

Glaz, B., J.M. Shine, Jr., C.W. Deren, P.Y.P. Tai, J.D. Miller,
O. Sosa, Jr., and J. Comstock. 1991a. Evaluation of new
Canal Point sugarcane clones, 1989-90 harvest season. U.S.
Department of Agriculture, Agricultural Research Service.

Glaz, B., J.M. Shine, Jr., P.Y.P. Tai, J.D. Miller, C.W. Deren,
J. Comstock, and 0. Sosa, Jr. 1991b. Evaluation of New
Canal Point sugarcane clones, 1990-91 harvest season. U.S.
Department of Agriculture, Agricultural Research Service.

Glaz, B., J.M. Shine, Jr., J.D. Miller, C.W. Deren, P.Y.P. Tai,
J.C. Comstock, and 0. Sosa, Jr. 1992. Evaluation of New
Canal Point sugarcane clones, 1991-92 harvest season. U.S.
Department of Agriculture, Agricultural Research Service.

Page 6

SUGARCANE INTERSPECIFIC HYBRIDS FOR

BIOMA88 ENERGY SOURCES

C. W. Deren, G. H. Snyder, and P. Y. P. Tai

ABSTRACT

Biomass can be an economical source of energy. Currently,

sugarcane mills burn bagasse to generate power during the milling

season. For expanded power generation capability, there will be a

need for additional biomass sources. One possible source is

sugarcane-related grasses which are very productive and may be

adaptable to adverse sites. This experiment investigated nine

clones of the Saccharum taxonomic complex for biomass production

and methane conversion after being flooded for six months in each

of two crop years. Ratoon yields for biomass were greater than

plant-cane yields for all clones. Plant-cane yields ranged from

0.47 to 20.28 Mg ha"1 and ratoon yields ranged from 4.57 to 60.1 Mg

ha'1. Hybrids which had a commercial sugarcane parent appeared to

be more flood-tolerant than clones of Erianthus spp.

INTRODUCTION

Year-round power generation form biomass-fueled power plants

will require a steady, plentiful supply of fuel to supplement

bagasse. This fuel should be grown on sites which are not already

in crop production, such as wet, shallow soils or other adverse

locations. Grasses related to sugarcane have been shown to be

extremely productive in biomass (Misleavy et al., 1987; Phillips,

1987) and adaptable to sites ranging from flooded to nutrient-poor

Page 7

sands. The purpose of this experiment was to evaluate nine clones

of giant grasses for biomass production under periodic'flooding.

MATERIALS AND METHODS

Nine clones (Table 1) were planted at the EREC in 1988 in a

randomized complete block design with three replications. Plots

were 3m square with seed pieces planted 0.5m apart, equidistantly

within the plot. Each plot had 49 seedpieces in a 7 x 7

configuration. Plots were planted in February and flooded

(approximately 20 cm deep) from June through November. After

draining, plots were harvested by hand, weighed and a sample was

taken for digestion to estimate methane conversion. The ratoon

crop was managed similarly.

RESULTS AND DISCUSSION

The following results were observed:

1. All clones were relatively slow to establish compared to

sugarcane. Ratoon growth was better than plant cane.

2. All clones had relatively thin stalks, but some were very

prolific in tillering and were quite resistent to lodging,

even in flooded soil.

3. Biomass production varied greatly among clones (Table 2).

Dry matter yield in plant cane was as low as 0.5 Mg ha'1 and

as great as 20.2 Mg ha'1. Two-year means ranged from 2.9 to

40.1 Mg ha'1.

4. Test clones had greater dry matter percent (range 33-52%)

compared to sugarcane (25%). This would mean less water to

Page 8

transport or vaporize during burning.

5. Methane production varied similarly to biomass production.

6. Several test clones had biomass production comparable to other

sources grown under normal, drained conditions.

It can be concluded that these giant grasses have potential

for considerable biomass production, even under adverse conditions.

With selective breeding, it should be feasible to create genotypes

which have long-lasting stands and are adapted to local cultural

conditions.

REFERENCES

Deren, C. W., G. H. Snyder, P. Y. P. Tai, C. E. Turick and D. P.
Chynoweth. 1991. Biomass production and biochemical methane
potential of seasonally flooded inter-generic and inter-
specific Saccharum hybrids. Bioresource Technology 36:179-
184.

Misleavy, P., J. P. Gilbreath, G. M. Prine and L. S. Dunavin.
1987. Alternative production systems: non-conventional
herbaceous species. In Methane from Biomass, ed. W. H. Smith
and J. H. Frank. Elsevier, New York, pp. 261-276.

Phillips, A. 1987. Harvest and preparation technology for
biofuels. In Cane Energy Symposium Report form the Second
Pacific Basin Biofuels Workshop, ed. M. Wood, Kuai, Hawaii,
USA, 2:1-11.

Page 9

Table 1. Nine grass clones evaluated for biomass production under
flood.

Entry

Origin

R 22-19

Erianthus A

Erianthus B

US 72-1288

US 84-1008

US 84-1009

US 79-1010

US 84-1018

Erianthus C

(S. officinarum x S. spontaneum) x S. robustum

E. arundinaceus

E. arundinaceus

Commercial x S. spontaneum

Commercial x E. arundinaceus

Commercial x E. arundinaceus

Commercial x S. spontaneum

Commercial x E. arundinaceus

E. arundinaceus

Page 10

Table 2. Mean yield of dry matter for plant-cane and ratoon crops.

Crop Year

Plant Crop Ratoon Two-Year Mean

Clone Mean Yield Mean Yield Mean Yield
g/1ha MK /ha g[bh-.

R 22-19 2.6 28.2 15.4

Erianthus A 0.5 4.6 2.9

Erianthus B 2.4 23.3 12.8

US 72-1288 20.2 60.1 40.1

US 84-1008 7.9 39.4 23.7

US 84-1009 11.3 59.4 35.4

US 79-1010 6.8 41.5 24.2

US 84-1018 7.4 36.5 22.0

Erianthus C 1.2 8.7 4.6

LSD a =.01 4.9 22.4 11.6

Page 11

WATER AND NITROGEN MANAGEMENT EFFECTS ON

SUGARCANE GROWN ON SANDY SOIL

T. A. Obreza
University of Florida, IFAS
Southwest Florida Research and Education Center
Immokalee, Florida 33934

and

D. L. Anderson
University of Florida, IFAS
Everglades Research and Education Center
Belle Glade, Florida 33430

INTRODUCTION

Sandy soils have become important for Florida sugarcane

production due to subsidence of organic soils, related

environmental concerns, and urban encroachment. In recent years,

expansion of sugarcane acreage has increased on the sandy soils

adjacent to the Everglades Agricultural Area (EAA).

Management of the water table for sugarcane production is

similar throughout southern Florida, regardless of soil type.

Water table control irrigation is used on both organic and

inorganic soils, with the water level maintained close to the soil

surface. This practice has been used on organic soils primarily to

reduce the soil subsidence rate (Snyder et al., 1978). A high

water level for irrigation purposes on organic soils is not as

critical due to their high water-holding capacity. In contrast,

sandy soils have low water-holding capacity, and the water table

must be in close proximity to the root zone to provide the

necessary upward flux for irrigation.

An 18-inch deep water table is commonly used to irrigate

sugarcane on sandy soils (Shih, 1988). However, a deeper water

Page 12

table would allow for greater effectiveness of rainfall, defined as

rainfall that is stored in the root zone and is available to the

plant to meet evapotranspiration requirements. It appears that a

30-inch water table level is too deep for irrigation of sugarcane

on sand (Pitts et al., 1991). However, it still may be possible to

maintain a water table between 18 and 30 inches for sugarcane

without decreasing yield, while increasing the effectiveness of

rainfall.

Nitrogen fertilizer is applied to sandy soils at rates up to

300 lbs N/acre by growers (Anderson, 1990). The maximum

recommended rate is 200 lbs N/acre. Split applications are

recommended because of the high leaching potential of N in Florida

sands. Generally, the total amount of N applied is split into

three to six applications from planting to the middle of the July

through August grand growth period (Anderson, 1990).

Water and fertilizer management are directly related in sandy
soil. Water table management practices that increase the

effectiveness of rainfall will decrease off-site flow and reduce

the loss of soil-mobile nutrients. The relationship between water

table depth and N fertilizer application frequency has not been

investigated for sugarcane grown on sandy soil. The objective of

this study was to evaluate the combined effects of N fertilizer

application schedule and water table level on sugarcane grown on

sandy soil.

Page 13

MATERIALS AND METHODS
Sugarcane (Saccharum spp., cv. CP 72-1210) was planted in
September 1990 in a 90-acre field in western Hendry county, FL.

This field had been in continuous sugarcane production for the

previous 20 yr. Row spacing was 5 ft. The soil was primarily

Basinger sand, with smaller areas of Wabasso fine sand, limestone

substratum, and Margate fine sand.

The experiment was a randomized complete block factorial
design involving two levels each of water table depth, nitrogen

fertilization frequency, and Mg fertilizer rate. Whole plots

consisted of target water table levels 18 inches deep (high) and 24

inches deep (low), designated HWT and LWT, respectively. Split

whole plots consisted of N fertilizer applied as ammonium nitrate

at a total rate of 200 lbs/acre in either five or three

applications during the 1991 growing season, and four or two

applications during the 1992 growing season. For the high
frequency treatment (HF) in the first year, N was applied at 40

lbs/acre in September 1990 and in February, April, May, and July

1991. The low frequency treatment (LF) was fertilized with 40 lbs

N/acre in September 1990 and 80 lbs N/acre in February and May

1991. For the first ratoon crop, the HF treatment was fertilized
with 50, 60, 45, and 45 lbs N/acre in April, May, June, and August

1992, respectively. For the LF treatment, N was applied at 90

Ibs/acre in April and 110 Ibs/acre in May, 1992. Split-split whole

plots consisted of Mg fertilizer rates of 0 or 67 kg Mg ha"'. The

Mg treatments will not be discussed in this paper. There were four

replications of each water table level by N fertilization frequency

Page 14

by Mg fertilizer rate combination.

Additional fertilizer applied to the sugarcane included 35

lbs/acre of P distributed in two equal applications each year, and

250 and 200 lbs/acre (1991 and 1992) of K distributed in three

applications. These rates were based on a predictive soil test

taken prior to planting.

Water table depths were controlled by regulating the water

depth in major canals bordering the east and west sides of the

field. Water in the west canal was kept at a high level and was

connected to perpendicular field ditches that bordered the HWT

plots. A drainage pump was installed in the east canal to keep

water at a lower level. This canal was connected to the field

ditches that bordered the LWT plots. Buffer plots in the field

were those which were bordered by high water on one side and low

water on the other.

A water table level recorder, a neutron probe access tube, and

tensiometers with sensing cups placed 4, 8, and 12-inches deep in

the soil were installed near the center of each main water level

plot. These plots were divided into four quadrants; the north and

south halves received the N fertilization frequency treatments,

whereas the east and west halves received the Mg fertilizer

treatments. Rainfall was measured at the study site using an

electronic data collection system.

Sugarcane plant tiller population was determined for each

treatment in November 1991 and 1992. Following field burning,

sugarcane was mechanically harvested in March 1992 and February

1993. Sugarcane within the north and south halves of each main

Page 15

water table level plot was separately harvested and weighed.

Normal juice sucrose concentration was measured on a subsample from

each harvested half-plot at a commercial sugar mill. Thus,

sugarcane and sugar yields were measured within each water table

level-N fertilization frequency combination plot on a commercial

scale.

RESULTS AND DISCUSSION

Rainfall during the growing season totaled 57.4 inches in 1991

and 38.5 inches in 1992. The spring and fall of 1991 were

considerably wetter than in 1992 (Table 1). Differences in root

zone soil moisture which might have occurred due to differential

upward flux from the water table level treatments were potentially

less in 1991 because of the wet year.

Mean water table depth for the HWT treatment averaged about 19

inches over the 2 years (Table 1). The LWT treatment had a

shallower average water table depth in 1992 (about 22 inches) than

in 1991 (about 25 inches) because of problems with operation of the

drainage pump. However, a difference in water table as little as

4 inches can still result in a wide difference in upward flux into

the root zone of a sandy soil. A difference of 1 inch of water

table level represents about 0.1 inches of free water.

Soil water contents at the 0 to 6-inch and 6 to 12-inch depths

in the HWT treatment were considerably higher than in the LWT

treatment (Table 1), despite the relatively small difference in

water table level. Water content at the 12 to 18-inch depth was

similar between the treatments. The HWT treatment also showed

Page 16

lower average tensiometer readings at the 4, 8, and 12-inch depths

than the LWT treatment. Overall water content was higher in 1991

than 1992, most likely due to higher rainfall.

There was no difference in tiller population, sugarcane yield,
or sugar yield with respect to the water table level or

fertilization frequency treatments in 1991 (Table 2). There was a

slightly higher sucrose concentration with in the HWT treatment.

The average plant cane yield (over 40 tons/acre) for the entire

field was considered good for sandy soil sugarcane production.

However, production decreased substantially for the first ratoon

crop, averaging about 27 tons/acre. Sucrose concentration also

decreased from 19% in 1991 to 12% in 1992. There was again no

response to irrigation treatment in 1992, but tiller population,

sugarcane yield, and sugar yields were significantly higher where

fertilizer was applied at higher frequency (4 applications) than at

lower frequency (2 applications). There was no interaction between

water table level and fertilization frequency treatments.

Soil and plant tissue nutrient content is being investigated
as possible causal agents for the yield decline observed. This

experiment is continuing for a third year, with identical water

level and fertilization frequency treatments as in 1992. The
drainage pump has been repaired, thus the water table levels should

be able to be maintained at least 6 inches apart.

Page 17

REFERENCES

Anderson, D. L. 1990. A review: soils, nutrition, and fertility
practices of the Florida sugarcane industry. Soil Crop Sci.
Soc. Fla. Proc. 49:78-87.

Pitts, D. J., D. L. Myhre, Y. J. Tsai, and S. F. Shih. 1991.
Effects of water-table depth on water relations and yield for
sugarcane grown on sand. J. Amer. Soc. Sugar Cane Technol.
11:29-37.

Shih, S. F. 1988. Sugarcane yield, biomass, and water-use
efficiency. Trans. ASAE 31(1):142-148.

Snyder, G. H., H. W. Burdine, J. R. Crockett, G. J. Gascho, D. S.
Harrison, G. Kidder, J. W. Mishoe, D. L. Myhre, F. M. Pate,
and S. F. Shih. 1978. Water table management for organic
soil conservation and crop production in the Florida
Everglades. Fla. Agr. Exp. Stn. Bull. 801.

Page 18

Table 1. Average water table depths, soil water contents, and tensiometer readings for 1991 (plant cane) and 1992 (first ratoon).

Mean water Mean volumetric soil water content Mean tensiometer readings
table depth High water table Low water table High water table Low water table

Depth in soil Depth in soil Depth in soil Depth in soil
Rain HWT LWT 0-6' 6-12' 12-18" 0-6 6-12" 12-18" 4' 8" 12" 4" 8" 12"

Inches inches percent by volume centibars of soil suction
1991

Spring 12.4 19 25 15.0 24.5 26.9 8.5 17.9 25.6 4.8 5.1 6.0 5.9 6.3 7.4

Summer 18.3 20 24 14.5 22.4 26.1 8.4 17.4 25.1 6.6 4.9 5.9 4.2 5.5 6.8

Fall 26.7 20 25 14.7 23.0 26.3 8.0 16.4 25.6 4.4 5.4 6.0 5.2 5.8 7.1

1992

Spring 5.4 18 22 13.5 18.7 21.8 8.2 14.2 23.6 3.3 5.1 6.2 6.7 6.6 6.1

Summer 27.0 19 21 13.2 17.1 22.2 8.4 15.5 22.8 6.7 4.4 5.0 5.3 6.1 6.0

Fall 6.1 18 23 14.8 21.2 25.2 8.2 14.0 23.2 3.6 4.4 5.9 7.8 6.2 7.1

Spring Interval: Feb 27-May 24,1991 and Apr 2-Jun 12, 1992
Summer interval: May 25-Aug 20, 1991 and Jun 13-Aug 29, 1992
Fall interval: Aug 21-Dec 31, 1991 and Aug 30-Dec 31, 1992.

Table 2.

Sugarcane and sucrose yields with respect to main effect treatments for plant
cane (1991) and first ratoon (1992) crops. HWT and LWT designate high and
low water table treatments; HF and LF designate high and low fertilization
frequency treatments.

Main Sucrose
effect Tillers Sugarcane concentration Sugar

No./acre tons/acre % tons/acre
1991

HWT 28,700 40.5 19.1 5.4
LWT 30,000 43.6 18.5 5.5
NS NS NS

HF 29,600 43.4 18.8 5.6
LF 29,100 40.8 18.8 5.3
NS NS NS NS

1992

HWT 31,400 25.7 12.0 3.1
LWT 32,100 28.3 12.3 3.5
NS NS NS NS

HF 34,300 29.6 12.1 3.6
LF 29,300 24.4 12.2 3.0
NS *

*Main effect means significantly different at the 0.05 level.
NS=Main effect means not significantly different.

Page 20

Weather information collected from Water Table Fertility Experiment (J.M. Hillard Bros.).

Rainfall Radiation Temp., C Wind ETw
1991 Daily Monthy Yearly LPM LPD Tavg Tmax Tmin kmld mm/day

January 0.18 5.64 5.64 0.21 299 20.5 25.0 16.0 91.0 2.63
Febraury 0.06 1.71 7.35 0.27 386 18.6 24.6 12.6 75.3 3.40
March 0.05 1.68 9.03 0.31 447 21.4 27.2 15.6 103.7 4.32
April 0.25 7.46 16.49 0.36 514 24.6 29.2 20.0 85.4 5.50
May 0.16 4.88 21.37 0.35 510 27.4 34.5 22.6 126.4 6.05
June 0.19 5.82 28.09 0.34 484 29.1 40.0 23.1 132.0 6.27
July 0.23 7.21 35.30 0.32 465 29.7 40.1 24.3 118.1 6.04
August 0.27 7.87 43.57 0.35 511 27.6 33.4 22.7 44.2 5.76
September 0.28 8.52 52.09 0.33 472 26.7 31.0 22.3 54.2 5.16
October 0.30 10.00 62.09 0.34 491 24.1 27.9 20.4 48.0 4.53
November 0.12 3.66 65.75 0.42 611 17.7 26.1 11.6 96.4 3.64
December 0.01 0.44 66.19 0.25 362 20.4 26.5 14.3 86.4 2.67

Rainfall Radiation Temp., C Wind ETw
1992 Daily Monthy Yearly LPM LPD Tavg Tmax Tmin km/d mm/day

January 0.04 1.09 1.09 0.20 291 16.8 24.9 9.8 163.8 2.69
Febraury 0.13 3.69 4.78 0.25 366 18.0 25.1 12.2 173.3 3.62
March 0.43 13.21 17.99 0.29 414 19.6 28.7 13.4 189.0 4.29
April 0.53 15.85 33.84 0.34 492 21.1 29.1 14.6 249.5 5.58
May 0.37 11.75 45.59 0.41 597 23.9 34.1 15.7 176.2 6.60
June 0.52 15.73 61.32 0.32 463 23.8 33.0 18.0 165.9 5.53
July 0.09 2.86 64.18 0.37 527 25.6 36.1 18.2 106.5 6.02
August 0.48 14.73 78.91 0.32 463 23.8 34.3 18.0 118.3 5.10
September 0.11 3.18 82.09 0.29 425 23.7 32.0 18.8 111.7 4.61
October 0.01 0.45 82.54 0.28 405 23.9 30.1 17.8 183.0 4.44
November 0.06 1.79 84.33 0.22 315 22.9 28.2 17.9 114.9 3.22
December 0.02 0.76 85.08 0.19 276 18.3 26.0 12.1 109.0 2.44

Rainfall Radiation Temp., C Wind ETw
1993 Daily Monthy Yearly LPM LPD Tavg Tmax Tmin km/d mm/day

January 0.19 5.87 5.87 0.20 287 20.5 26.2 16.0 280.8 3.82
Febraury 0.07 1.97 7.84 0.26 372 17.6 25.3 10.8 147.1 3.63
March 0.08 2.43 10.27 0.30 435 19.1 27.0 12.7 279.8 4.70
April 0.08 2.34 12.61 0.37 536 21.5 30.4 13.4 188.5 4.03

Table 3.

PRELIMINARY FINDINGS AND POTENTIAL IMPLICATIONS OF A

NEGATIVE RELATIONSHIP BETWEEN SUCROSE AND TONNAGE

J. Alvarez, Agricultural Economist
C.W. Deren, Plant Breeder
UF, Belle Glade, FL
and
B. Glaz, Agronomist
USDA-ARS Sugarcane Field Station
Canal Point, FL

INTRODUCTION

Energy captured during photosynthesis is stored in plants as

carbon compounds. In sugarcane, these can be structural compounds,

such as cellulose, which makes up most of the "fiber" of a stalk.

The other alternative is for the plant to produce sucrose.

Intuitively, it seems that if a plant fixed a certain amount of

carbon, it could be allocated to stalks (cellulose for fiber) and

sucrose in varying proportions. At a certain point, however, the

increase in one must come at the expense of sacrificing the other;

hence, there is the potential for a negative relationship between

the amount of fiber in each individual stalk and its sucrose

content.

This presentation describes the on-going research intended to

elucidate this issue given its potential implications for a

breeding program.

THE FIRST STEP: TESTING THE BIOLOGICAL RELATIONSHIP

A direct test of a negative relationship between sucrose and

Stonnage was unsuccessful. The three year crop cycle of 164 clones

in Stage IV of the Canal Point breeding program in the last 10

Page 22

years provided 492 observations. The resulting scatter diagram did

Snot yield any visual evidence, which was also absent in the results

of the correlation analyses. The correlation coefficients lacked

statistical significance for all clones and years combined and for

some sub-sets of the data, while it was statistically significant

for others.

THE SECOND STEP: DEVELOPING AN ECONOMIC INDEX

Selection of clones in a sugarcane breeding program is based

upon numerous attributes, but the amount of sugar produced per unit

of land (sugar per acre, SA) is of primary importance. However, in

some circumstances, selection based on SA may be misleading,

particularly if the clone has a relatively low sugar concentration

but high tonnage of stalks (tons of cane per acre, TCA). Such

clones incur greater costs for the cutting, hauling and processing

necessary to achieve estimated sugar yields.

For that reason, a project to develop a method for selecting

clones based upon an economic evaluation that considers production

costs was undertaken. Relevant data and preliminary results were

extended at the 1991 Sugarcane Growers Seminar (Deren, et al.,

1991)'. The project was completed and the results presented at the

last meeting of the International Society of Sugar Cane

S Technologists (Deren, et al., 1992).
-4*
SThe following equation was modified to reflect conditions for

independent producers.

Page 23

A profit equation for administration cane was developed:

3
I = z ((P,*SPTIJ*NTj) -PHC- (HLH*NTIJ)- (M*NTI))* (+r) -n
i=1

where:

I = economic index (net returns, $/acre);

P, = price of sugar ($/lb);

SPT = sugar yield (Ib/net ton of cane);

NT = biomass yield (net tons/acre);

PHC = preharvest costs ($/acre);

HLH = harvesting, loading, and hauling costs ($/net ton);

M = milling costs ($/net ton);

i = the ith crop (1=plant cane; 2=first ratoon; and 3=second

ratoon);

j = the jth cultivar; and

(l+r)'" = present value formula, where r=interest rate, and n = 1.5,

2.5 and 3.5 years for plant cane, first ratoon, and second ratoon,

respectively.

The resulting economic index allowed the ranking of cultivars

based on their relative profitability. The use of the economic

index has resulted in an improved process of cultivar selection in

Florida.

THE THIRD STEP: USING THE ECONOMIC INDEX
TO TEST THE INVERSE RELATIONSHIP

The economic index, and the corresponding economic ranking of

cultivars, seemed an appropriate means to test the existence of a

negative relationship between sucrose and tonnage. Data used

included the three year average TCA and sugar per ton of cane (ST)

Page 24

of the 164 clones previously mentioned.

To test the potential relationship among the different

parameters measuring tonnage and sugar yields in the economic

ranking, the first 15 CP cultivars were analyzed (Table 1). The

results seemed to indicate that the economic ranking is independent

of any particular parameter included in the formula: economic value

(EV), tons of cane per acre (TCA), sugar per ton (ST), and sugar

per acre (SA). For example, when looking at the first and last

rankings in the four groups, the closer association is found in CP

78-1247, which is EVl, TA7, ST2, and SA1. However, CP 78-1599 is

EV6, TA15, ST1, and SA15; while CP 65-357 is EV7, TA1, ST15, and

SA3.

All 164 cultivars ranked by economic value were then plotted

with sugar per ton in the vertical axis and total cane per acre in

the horizontal axis (Figure 1). The first obvious result showed the

cultivars in descending order from the upper right to the bottom

left of the graph. That is, the cultivars with the highest economic

ranking fell on the upper right while those with the lowest

appeared on the bottom left.

The second not so obvious result was that, after close

scrutiny and as a result of the previous finding, the cultivars

appeared to be clustered in three different groups. The first

cluster (upper right) could include EV1 through EV31; the second

cluster (middle) EV32 through EV135; and the third cluster (bottom

left) EV136 through EV164.

Preliminary statistical analyses were conducted with these

three clusters. A consistent negative sign for the three

Page 25

correlation coefficients seemed to indicate the existence of the

negative relationship. Highly statistical significance seemed to

corroborate that fact. However, the selection of the clusters was

somehow arbitrary and a more refined statistical analysis is

required before proceeding any further with this project.

CONCLUSION AND IMPLICATION

Although not in a unequivocal manner, the results of this

study seem to indicate the existence of a negative relationship

between ST and TCA in sugarcane. Even in the absence of a negative

biological relationship, the one shown by the economic ranking

portrays a penalty for biomass and a reward for sucrose content;

i.e., sucrose is sacrificed in order to achieve a higher tonnage.

The potential implication, pending on the final results of

this project, is obvious. Even if there is no negative biological

relationship, the economic ranking indicates that breeders should

make selections based on that ranking and resulting clustering of

clones to maximize growers' returns.

REFERENCES

Deren, C.W., J. Alvarez and B. Glaz. "En Economic Index for
Selection of Sugarcane Clones," Belle Glade EREC Research
Report EV-1991-3, 1991 Sugarcane Growers Seminar, EREC-IFAS
and Florida Cooperative Extension Service, Belle Glade, FL,
May 15, 1991, pp. 20-22.

Deren, C.W., J. Alvarez and B. Glaz. "Use of Economic Criteria for
Selecting Clones in a Sugarcane Breeding Program," Paper
presented at the meetings of the International Society of
Sugar Cane Technologists, Bangkok, Thailand, March 10, 1992.

Page 26

39
73 47

58 49
83
66 3542
55

101

121

15

16
17 5
23 10
20 1912

4
118
nla

85 7 5
85 7P 18 1
ldc# 757,0 62 3
57 ^ ^ 24
116 100 95
111 6An ~ 5524587
114 59 56 si0
112108 95 544
24 132 120 105
6 87 84
f--PlK4 99 88 68
6 1441 13 2813115102
144 80
3 1 13 109 09
154 150 140 1 25 1 106
11722

1559
163 155

14
I

4132
44

127107 9

-l11 I I ----

60
Tonnage yield (ton/acre)

Negative relationship between sugar and tonnage of 164 cultivars ranked by the economic

index and potential clustering.

-Y

250 -

240 -

230 -

220 -

210 -

200 -

190 -

ISU

Figure 1.

Table 1.

Comparison between ranking by economic value of the first fifteen CP cultivars and
different measures of tonnage and sugar yields.

Ec. value Tons/acre Sugar/ton Sugar/acre
Cultivar $/ac. Rank Mean Rank Mean Rank Tons Rank

78-1247
78-1628
82-1172
68-1067
78-1156
78-1599
65-357
78-1610
0 82-1592
82-2043
78-2114
78-1263
68-1026
78-1140
81-1254

2,618
2,422
2,327
2,255
2,214
2,212
2,204
2,178
2,161
2,159
2,150
2,142
2,136
2,131
2,122

52.2
51.4
56.0
52.2
48.8
43.5
57.2
52.3
53.0
49.3
51.7
49.9
52.4
53.9
52.0

248.5
243.1
232.7
234.5
240.6
253.7
223.9
232.5
230.9
238.3
231.8
234.7
230.2
227.1
230.2

19.42
18.69
19.26
18.30
17.50
16.50
19.14
18.14
18.26
17.47
17.88
17.50
17.97
18.28
17.89

1
4
2
5
12
15
3
8
7
14
11
13
9
6
10

SUPPLY RESPONSE OF THE FLORIDA
CANE SUGAR INDUSTRY

Carolyn A. Advinoula, Leo C. Polopolus, Ronald W. Ward
Agricultural Economists, UF, Gainesville, FL
Jose Alvarez
Agricultural Economist, UF, Belle Glade, FL

INTRODUCTION
Supply elasticity is a measure of the responsiveness of supply
to changes in price and is calculated by dividing the percentage

change in quantity supplied by the percentage change in price. The

elasticity of supply can be elastic (e > 1), inelastic (e < 1) or

unitary (e = 1).

A supply elasticity for sugarcane production in Florida was

estimated by Gemmill in 1976 to be 4.23. Elasticities for other

cane producing regions in the United States were 0.00 for Puerto

Rico, 0.75 for Louisiana, and 0.99 for Hawaii. Except for Florida,

Gemmill's supply elasticities were estimated to be in the inelastic

range (Gemmill, 1976).

If the sugarcane supply elasticity is as elastic (4.23) as
estimated by Gemmill, a 10 percent increase in sugarcane prices

would result in a 42.3 percent increase in the tonnage of Florida

sugarcane supplied. Such a large expansion in cane acreage and

production would place severe strains on the fragile ecosystem in

the Everglades.

This study hypothesizes that the supply elasticity of

sugarcane in Florida is considerably less than what was previously

estimated. Supply elasticities for sugarcane and any major

agricultural commodity are normally in the inelastic range (less

than 1). The lower supply elasticity is also believed to be due to

Page 29

U.S. sugar policy changes and the land constraint on sugarcane

production. A more up-to-date estimate is needed to determine an

accurate appraisal of the probable impact of future changes in

sugar price policy or industry output.

EMPIRICAL RESULTS

Expectational Supply Model1

A representative sample of Florida sugarcane production on

muck and sandy soil was included in the survey. Data were collected

from three respondents representing approximately 78 percent of the

1990-91 sugarcane production in Florida (Advincula, et al., Table

15, p. 24). Expectational supply responses were obtained for

production under both muck and sandy soil conditions.

By aggregating the individual supply schedules, the combined

supply elasticities at 22 cents per pound of sugar were estimated

to be:

Muck land: e = 0.45

Sand land: e = 0.82

Combined muck and sand land: e = 0.51

These results show inelastic supply elasticities for Florida.

The relatively less inelastic (closer to 1) supply elasticity on

sand land is consistent with expected results. Sand land growers

are not facing a land constraint and can consider such crops as

oranges and grapefruit when sugar prices drop.

Figure 1 graphs the elasticity of supply on muck, on sand, and

on both muck and sand over a range of prices from 18 to 29 cents

'Readers interested in the specific information related to
producers' responses, their supply schedules, and the regression
results are referred to Advincula, et al., (pp. 23-27).

Page 30

0.9

0.8

S0.7

0. -
0.5 -

0.4

0.3
18

Fig re
Figure I

20 22 24 26 Poud)
Raw Sugar Price
Estimated Supply Elasticities For Florida Sugarcane in 1990 on
Muck, on Sand, and on Both Muck and Sandy Soil Over Price Range
18 Cents to 29 Cents per Pound Using the Expectational Supply
Model.

Table 4 Error Sum of Squares(ESS) and Parameter Estimates of Variables.

Number of Lags Weights ESS Last Period Kalman Filter
Parameters

One 0.01 608.545 1,696.67 .563.599
(2.11517) (-1.60778)
Two 0.01 608,546 1,231.79 -438.043
(1.64905) (-1.10419)
Three 1.00 605,385 -1,574.38 659.244
(-2.40263) (3.02374)
Four 0.01 608,546 725.971 -232.477
(1.10392) (-.485042)
Five 1.00 607,907 7,749.68 -2,447.56
(9.75462) (-9.24233)
Six 1.00 606.165 8,890.40 -2,821.99
(10.9024) (-10.4033)
Note: Figures in parenthesis indicate the statistics for both parameters.

Page 3U

___

per pound of sugar. The elasticity ranges between 0.37 and 0.59 on

muck soil, between 0.67 and 1.08 on sandy soil, and between 0.42

and 0.67 on both muck and sandy soil over the relevant price range.

Distributed Lag Model
A regression was run between the difference of the current and

previous year's raw sugar production (dependent variable) and the

weighted moving average of the NY spot raw sugar price (independent

variable) expressed as the logarithm of the moving average price

Mapkt. Time series data used were from 1960 to 1990.

The models with Mapkt lagged one, two, three, four, five, and

six years and each weighted, were run. As a result of the variable

Mapkt, beginning with the 1966 raw sugar price for all the six
equations, the degrees of freedom (df) and total sum of squares

(TSS) remain the same.

Obtained from the ordinary least squares regression, the

results where the error sum of squares (ESS) were least for each of

the models are presented in Table 1. Among the six different

models, the ESS is least at 605,385 where raw sugar prices are

lagged for three years and are weighted equally. The results

indicate that lagged prices have equal effect on production

decisions. The significance of the three year lag is attributed to

the ratoons that are harvested after the new plantings occur.

Using the Kalman filter estimation technique, the parameter
estimate citfor the model lagged three years with equal weights

yielded the appropriate sign for the coefficient of the logarithm

of Mapkt, which is positive. The variance/covariance matrix of the

model with prices lagged three years was used to estimate the

Page 32

parameters. The results indicated significant t-statistics for both

parameters oc, and oct. A sensitivity analysis performed on the

variance-covariance matrix did not show significant deviations from

the estimated parameter, lending considerable credibility to the

Kalman filter results.

Through the Kalman filter estimation technique, parameter

estimates were calculated for each of the years beginning in 1966.

Figures 2 and 3 depict the estimated cot and oct parameters,

respectively. The octparameter shows an upward trend while the aei

parameter starts off high then stabilizes.

From Table 1 the final sugar supply model was determined where

a three year moving average price proved to be the best

specification. From this model the parameters ocg and oci were

estimated giving the values -1,574.38 and 659.244, respectively.

The production response was based on a differential model where Qt

- Qt.1 was the left hand side variable to be explained; i.e., Qt -

Qt-1 = o'+ c11log(MAP). These two coefficients represent the supply
adjustment as illustrated with Figure 4. Moving average sugar

prices are on the bottom axis and the predicted change in sugar

production on the left axis and the supply response denoted with

the dotted curve in the figure. The slope of the supply response is

determined using o 1.The larger this value, the steeper the dotted

curve in this figure and the greater the supply response. Whereas,

the coefficient basically determines where the supply response

crosses the zero change axis. Note in this figure that the supply

response crosses the zero axis where the moving average sugar price

is 10.89 cents. Larger values of oc0would shift this curve to the

Page 33

-1.7

S-1.9
. -.9 -

(4 -2

-2.1 -
1966

Figure 2

1978 1990
Year
Kalman Filter Parameter (Xo(Intercept) From 1966 through 1990.

Year

Figure 3

Kalman Filter Parameter

a, From 1966 through 1990.

Page 34.

I

II I I _

Figure 4 Relationship between changes in sugar production and the 3 year moving average price
(see model in Table 1 where dQ=-1574.38+659.244 log(MAP))

Change in Production (Pxroi -Prod(t-1))
1,000-

Negative Production __ Positive Production
Changes Chages
500

-500

-1,000

-1,500

-2,000

1 3 5 7 9 11 13 15 17 19 21 23 25 27 29 31 33 35 37 39 41 43

Moving Average gaPrice (3 yearmoving average wih prices = cens per pound)

right and smaller values would shift the supply response to the

left. Thus both ocand determine the coordinates as illustrated

in this figure.

Clearly, the supply response is positive as evident with the

upward sloping path in Figure 4. However, supply changes can be

positive or negative even though the amount of change is positively

related to rising prices. For example, if sugar prices were

depressed producing levels below 10.89 cents per pound, supplies

would always decline over time but the amount of decline depends on

how low actual prices are. This suggests a consistent exiting from

the industry during severally depressed prices. In contrast, with

sugar prices above 10.89 cents per pound, the response is always

positive as seen with the plotted points to the right of this

threshold price level. One can view the estimated coefficients to

show the response rate but also to derive this threshold price

level.

Using the parameter estimates of 1966, 1978, and 1990, supply

curves were simulated accordingly (Figure 5). The shifts to the
right of the supply curves for the 12-year intervals beginning in

1966 reflect the changing nature of the sugarcane industry. The

nature of the Kalman filter estimation technique allows it to

capture the changes in U.S. sugar policy and other factors from

year to year as reflected in the production responses of the

sugarcane industry. For example, the shift from 1966 to 1978 is

likely the result of the lifting of acreage and marketing

allotments in 1974 and 1975. The prevailing prices in the world

market were high enough then that a U.S. sugar program was deemed

Page 36

E
'U

g.

E.

'A

Figure 5

3.4
3.2
3.0
28-
2.6
2.4
2.2
2.0
1.8 -
1.6
1.4-
1.2
1.0
0.8 -
0.6
0.4
0.2

Figure 6

S36-
S34-
32 RSSupply in
32" 1966
S30 -
SRS Supply in
u- 28 1978
26
24
22
20
18
16
14
12
10 ........i-
0.2 0.4 0.6 0.8 I 1.2 .4 1.6
Raw Sugar Production

Estimated Supply Curves of the Distributed Lag Model Using
the Kalman Filter Method for Years 1966, 1978, and 1990.

14 II 22 26 30 34
Simulated Moving Average Price (Map) (C...tPuer n

Estimated Supply Elasticities for Florida Sugarcane in 1966,
1978, and 1990 over Price Range 11 Cents to 35 Cents per
Pound Using the Distributed Lag Model.

Page 37

1.8 2 2.2
(Millions)

1966
,/

1978

1990

111 II I -~

-I ~I' e 1 I I Is

unnecessary. Technological improvements in cane variety development

and in the harvesting as well as milling operations have allowed

the sugarcane industry to become more efficient in its production

through the 1980s.

Figure 6 depicts the elasticity of supply in the years 1966,

1978, and 1980 over a range of 11 cents to 35 cents per pound of

sugar in 1982 real prices. Elasticity falls between 3.23 and 0.68

in 1966, between 1.21 and 0.50 in 1978, and between 0.47 and 0.30

in 1990. The decreasing responsiveness of Florida sugarcane growers

over the years may be attributed to factors such as land

availability, land prices, presence of competing crops,

environmental regulations, declining "real" support prices, and

substitutability of high fructose corn syrup and noncaloric

sweeteners for sugar.

SUMMARY AND CONCLUSIONS

Both methodologies --the expectational supply model and the

distributed lag model using the Kalman filter estimation technique-

- confirm sugarcane supply response in Florida to be inelastic, at

least under current conditions. These findings validate our

hypothesis that the Florida supply elasticity is much lower than

the one estimated by Gemmill in 1976.

With producer responsiveness in the inelastic range, it is

unlikely that price increases from federal policies or market

forces will cause large increases in Florida's sugarcane acreage or

raw sugar output. Because of this, it is unlikely that the Florida

sugarcane industry will be causing adverse environmental problems

to the south Florida region from increased output. Instead, the

Page 38

focus of the Florida sugar industry will likely be on cost

reductions and improved efficiency from a relatively stable

sugarcane acreage base. These findings provide some assurances of

the maintenance of a stable and viable Florida sugar industry.

REFERENCES

Advincula, Carolyn A., Leo C. Polopolus, Ronald W. Ward and Jose
Alvarez. Supply Response of the Florida Cane Sugar Industry
and Related Policy Implications, Staff Paper Series SP 92-26,
Food and Resource Economics Department, Institute of Food and
Agricultural Sciences, University of Florida, Gainesville,
Florida, November 1992.

Gemmill, Gordon. "The World Sugar Economy: An Econometric Analysis
of Production and Policies," Ph.D. Dissertation, Michigan
State University, East Lansing, 1976.

Page 39

SUGARCANE RESPONSE TO LIMESTONE AND GYPSUM

APPLICATION ON ACIDIC FLORIDA SPODOSOLS

Frank J. Coale
Associate Professor
Everglades Research & Education Center
Belle Glade, Florida

and

Thomas J. Schueneman
Agricultural Extension Agent
Palm Beach County Extension Service
Belle Glade, Florida

For the 1992-93 harvest, 87% of Florida's sugarcane was grown

on Histosols in the Everglades Agricultural Area (EAA), while the

remaining 13% was grown on adjacent sandy mineral soils (Coale and

Glaz, 1992). Nearly all of the Histosols in the EAA potentially

available for agricultural production are currently under

cultivation. Hence, expansion of the sugarcane industry will

necessitate increased production on the sandy mineral soils

adjacent to the EAA.

The mineral soils adjacent to the EAA are predominantly

classified as Entisols, Mollisols, and Spodosols. Spodosols,

primarily of the aquod suborder, are the dominant soils used for

sugarcane production (Anderson, 1990). Many of these soils have

surface soil pH below that required for optimum sugarcane

productivity and liming for pH adjustment is a common practice.

Current liming recommendations were developed by Gascho and Kidder

(1975) who recommended that lime, usually dolomite, be applied at

3.3 t ha"I on sands with pH less than 5.0. Presumably, this

recommendation was developed from field observations, growers'

experiences, and adaptation of research results from other regions

Page 40

because, substantiating research literature specific to the acidic

mineral soils of central southern Florida does not exist.

The sandy mineral soils available for sugarcane production in

Florida typically have low exchangeable Al contents (USDA, 1990),

thus, liming these soils is not directed towards ameliorating Al

toxicity. These soils typically have low clay content (1 to 5 %),

low organic matter content (1 to 2 %), and a low CEC (1 to 5 cmol,

kg'1) with variable (30 to 80%) base saturation (USDA, 1990). The

chemical reaction of these soils with liming amendments will be

quite different than the liming reaction observed with highly

weathered tropical clay soils or with medium textured soils that

have higher clay or organic matter contents. The objective of our

research was to evaluate sugarcane yield response to soil

amendments applied for increasing the soil pH of acidic sandy

Spodosols. The goal of liming is to neutralize soil acidity but

liming amendments also provide Ca and sometimes Mg for plant

nutrition. The soil amendments studied in our research were

selected in order to gain insight into the individual benefits to

sugarcane productivity of neutralizing soil acidity, supplying

nutrient Ca, and supplying nutrient Mg.

MATERIALS AND METHODS
Experiments were conducted at two locations in Hendry County,
Florida. The soil at location 1 was a Myakka sand (Sandy,

siliceous, hyperthermic Aeric Haplaquods) which is characterized by

clay and organic matter contents both less than 2%. The spodic

horizon was approximately 50 cm below the soil surface. The

Page 41

initial surface soil (0 to 15 cm) pH was 4.5. The soil at location

2 was an Immokalee sand (Sandy, siliceous, hyperthermic Arenic

Haplaquods) which is also characterized by low clay and organic

matter contents. The spodic horizon was approximately 90 cm below

the soil surface. The initial surface soil (0 to 15 cm) pH was

5.6.

At both locations, the experiment design was a randomized

complete block with four replications. Each replication was a

factorial of three soil amendments and four application rates. The

soil amendments were commercial agricultural calcite (CaCO3),

dolomite (CaMgCO3), and gypsum (CaS04"H20) (Table 1).

The calcite and dolomite amendments had similar total percent

carbonates and, thus, similar acid neutralizing capacities. Both

liming materials were applied at rates of 0, 1.1, 2.2, and 4.4 t

ha"'. Gypsum was applied at 0, 1.9, 3.8, and 7.6 t ha"'. Gypsum

amendment rates were selected in order to apply an approximately

equivalent quantity of amendment Ca as was applied by the limestone

amendment. All amendments were surface broadcast over the entire

plot area and incorporated by roto-tiller to approximately 20 cm

depth two days prior to sugarcane planting. Each plot area was 72

m2 (12 m long, 6 m wide) and included four rows of sugarcane

planted on 1.5 m row widths.

Sugarcane yield data were collected for the plant-cane crops

at both locations, the first-ratoon crop at location 2, and the

second-ratoon crop at location 1. Yield data were not collected

for the first-ratoon crop at location 1. Prior to crop harvest,

millable stalk number per 12 m in the two middle rows of each plot

Page 42

(36 m2) were counted. At harvest, 15 adjacent stalks were sampled

from a random interior section of one of the two middle rows of

each plot. The stalks were cut at the soil surface and topped at

the upper-most hard node.

RESULTS AND DISCUSSION
Soil Response to Amendments

The calcite and dolomite amendments used in our studies had
similar total percent carbonates and, thus, similar acid

neutralizing capacity (Table 1). The reaction rates of calcite and

dolomite amendments were rapid and pH equilibrium was achieved

approximately 2 months after application (location 1 = 53 days

after treatment (DAT); location 2 = 66 DAT) (Fig. 1). The

magnitude of pH elevation in response to amendment application was

similar for both calcite and dolomite amendments. Elevated soil pH

resulting from amendment application was maintained throughout the

course of the experiment at location 1 (922 DAT) and at location 2

(534 DAT) (Fig. 1).

Increasing rates of calcite and dolomite amendments both

resulted in significant increases in soil pH at the 0 to 15 cm

depth. Liming did not alter soil pH at the 15 to 30 cm depth at

location 1 but did significantly increase soil pH at the 15 to 30

cm depth at location 2. Liming did not alter soil pH at the 30 to

45 cm depth at either location (data not shown).

Calcite and dolomite amendments contained 211 and 148 g Ca

kg'-, respectively (Table 1). As a result, acetic acid extractable

Ca was increased in the 0 to 15 cm depth by both amendments at both

Page 43

locations (Table 2). Elevated extractable Ca levels were not

observed at deeper depths except for in the 15 to 30 cm depth at

location 2.

Dolomite contained 76 g Mg kg'1 that was not available from

equivalent rates of calcite (Table 1). Increasing rates of

dolomite resulted in increasing acetic acid extractable Mg levels

in the 0 to 15 and 15 to 30 cm depths at both locations. Magnesium

content of the 30 to 45 cm depth was not changed by dolomite

application (data not shown).

Increased soil pHs in the 0 to 15 and 15 to 30 cm depths due

to calcite and dolomite applications were maintained through

ratoon-crop development (Table 2 and Fig. 1). Liming did not alter

soil pH in the 30 to 45 cm depth.

When location 1 was sampled nearly three years (922 DAT) after

liming, a significant increase in extractable Ca in the 0 to 15 and

15 to 30 cm depths persisted (Table 2). Similar observations were

made for soil samples collected 534 DAT at location 2 (Table 2).

Elevated soil Mg levels in the 0 to 15 and 15 to 30 cm depths

resulting from dolomite application prior to planting were

maintained throughout the course of the experiment at both

locations (Table 2).

Gypsum amendment rates were selected in order to supply an
approximately equivalent quantity of amendment Ca as was available

from the limestone amendments with out neutralizing soil acidity.

Indeed, gypsum application resulted in increased soil Ca similar to

the increase resulting from limestone application (Table 2). As

expected, gypsum amendments did not alter soil pH when samples were

Page 44

collected at mid-season of each crop at location 1 (Table 2).

Water extractable soil P (Pw) determined 922 DAT was not

affected by the amendments (Table 3). Acetic acid extractable soil

P (Pa) in the 0 to 15 cm depth, however, increased with increasing

rates of calcite application (Table 3). Also, in both the 0 to 15

and 15 to 30 cm depths, Pa increased with increasing rates of

dolomite application. Neither calcite nor dolomite amendments

altered Pa at the 30 to 45 cm depth. Gypsum amendments did not

change Pw or Pa at any depth. Calcite and dolomite amendments

appeared to have created a soil reservoir for long-term

accumulation of fertilizer P with limited water solubility. This

P sorption may be detrimental to sugarcane productivity if P

nutrition is limiting crop growth or it may be beneficial if sorbed

P slowly became plant available in what is typically a well leached

root zone. Also, if P fertilizer application exceeded crop P

utilization, P sorption by soil amendments may result in lower P

loading in field drainage water which may be beneficial to adjacent

wetland ecosystems (Izuno et al., 1991). The impact of soil

amendments on soil P dynamics in these soils warrants further

study.

Crop Response to Amendments

The plant-cane crops did not exhibit a significant increase in

sugarcane yield with increased rate of calcite or dolomite

application (Fig. 2). However, the sugarcane yield of subsequent

ratoon crops significantly increased (P < 0.10) with application of

calcite and dolomite prior to planting (Fig. 2). The sugarcane

yield response for both amendments was linear through the highest

Page 45

amendment rate. The rate response was greater for dolomite than for

limestone which suggested an additional benefit of supplying

nutritional Mg in conjunction with neutralizing soil acidity.

Sugarcane yield was not affected by gypsum amendments (data not

shown). Apparently, the supply of nutrient Ca was not a growth

limiting factor for sugarcane production on the these acidic sandy

soils.

Inspection of plant cane yield components revealed that there
were no significant differences (P > 0.10) in stalk length, stalk

weight, millable stalk number, or sugar content among calcite or

dolomite amendments (Table 5). However, for the subsequent ratoon

crops, stalk length and stalk weight significantly increased (P <

0.05) with liming. Millable stalk number was significantly

increased (P < 0.10) by application of dolomite but not by calcite.

Sugar content was not affected by any of the treatments. Hence,

ultimate sugar yield was solely dependent on biomass production

(sugarcane yield) and not biomass quality (sugar content).

Top visible dewlap (TVD) leaf samples were collected at the
beginning of the grand growth period (June or July) of each

harvested crop. There were no significant differences (P > 0.10)

in TVD N, P, K, Ca, or Mg concentrations among the amendment

treatments (data not shown). Apparently, although application of

supplemental Mg through dolomite amendments was beneficial to

sugarcane yield, the Mg deficit was not expressed in TVD leaf Mg

concentrations.

For each of the four harvested crops, an "equilibrium pH" for
the 0 to 15 cm depth was identified and was used to characterize

Page 46

the average surface soil pH during the majority of crop

development. Equilibrium pH is the pH measured approximately 2

months after amendment application for plant-cane crops (location

1 = 53 DAT; location 2 = 66 DAT) and mid-season for ratoon crops

(location 1 = 922 DAT; location 2 = 534 DAT). A significant (P <

0.05) quadratic model described the relationship between

equilibrium pH for calcite and dolomite amended plots and relative

sugarcane yield (Fig. 3). Evaluation of the model disclosed that

maximum relative sugarcane yield corresponded to pH = 6.0. This pH

threshold is the same as that defined by Davidson (1967) and

reconfirmed by Golden (1972) for loam soils in Louisiana.

Inspection of the treatment means revealed a slightly lower

practical threshold of approximately pH = 5.5, above which liming

did not improve sugarcane yield.

Since the initial soil pH at location 1 was well below the

newly established threshold, the soil pH response to amendment rate

at location 1 was used to complete the calibration of amendment

rates. The relationship between calcite or dolomite amendment rate

and equilibrium pH was defined by a significant (P < 0.05) linear

model: pH = 4.49 + 0.24 amendment rate (t ha"') (r2 = 0.81). For

each tonne of calcite or dolomite applied, equilibrium pH increased

0.24 units.

CONCLUSIONS
Existing recommendations for growing sugarcane on acidic sandy

soils include application of 3.3 t dolomite ha"' on soils with pH

less than 5.0 (Gascho and Kidder, 1975). Our research confirms

Page 47

that dolomite is the preferred living amendment due to its capacity

to supply nutritional Mg. Nutritional Ca supply from these soils

appeared to be adequate. Our research also defined a practical

threshold of pH = 5.5, above which liming did not improve sugarcane

yield but below which a yield response to liming is expected.

Surface soil pH was increased 0.24 pH units per tonne of limestone

or dolomite applied.

REFERENCES

Anderson, D. L. 1990. A review: soils, nutrition, and fertility
practices of the Florida sugarcane industry. Soil Crop Sci.
Soc. Fla. Proc.49:78-87.

Coale, F. J., and B. Glaz. 1992. Sugar cane variety census:
Florida 1992. Sugar y Azucar 87(11):27-33.

Davidson, L. G. 1967. The effects of lime on yields of sugarcane
and sugar on acid soils of Louisiana. Proc. Inter. Soc. Sugar
Cane Technol. 12:181-187.

Gascho, G. J., and G. Kidder. 1975. Fertilizer recommendations
for sugarcane produced for sugar. Belle Glade AREC Res. Rep.
EV-1975-16. Fla. Agric. Exp. Stn.

Golden, L. E. 1972. The effect of agricultural lime and ground
rock phosphate on yield of sugarcane, soil pH and P and Ca
extractable from Baldwin silty clay loam soil. Proc. Amer.
Soc. Sugar Cane Technol. 2:45-48.

Izuno, F. T., C. A. Sanchez, F. J. Coale, A. B. Bottcher, and D.
B. Jones. 1991. Phosphorus concentrations in drainage water in
the Everglades Agricultural Area. J. Environ. Qual. 20:608-
619.

USDA. 1990. Soil survey of Hendry County, Florida. Soil
Conservation Service, USDA, Washington, DC.

Page 48

Fig. 1. Soil pH (0 to 15 cm depth) as affected by four rates of calcite and dolomite
amendments at location 1 (A and B, respectively) and at location 2 (C and D,
respectively).

0 53 200

0 66 100 200 300 400
Days after treatment (DAT)

500 600

66 100 200 300 400
Days after treatment (DAT)

500 600

5

4.5

Fig. 2. Plant-cane crop and ratoon-cane crop sugarcane yield
response to calcite and dolomite amendments. Sugarcane yields
are the mean of two locations (n=8).

80

7 A ............................A dolomite, plant cane
Y = 54.63 + 3.39X, r2= 0.11, P = 0.38...

0= 60 -

0 *------ calcite, plant cane
s* -Y = 53.72 + 3.40X, r2= 0.21, P = 0.33

rO -
40
3 40 -

A....."" -- 0 calcite, ratoon cane
... Y = 31.05 + 4.18X, r2= 0.19, P = 0.10
30 ...

............................ dolomite, ratoon cane
Y = 25.42 + 6.58X, r = 0.32, P = 0.01
20 I---
0 1 2 3 4 5
Amendment rate (t/ha)

Page 50

Fig. 3. Sugarcane relative yield response to surface soil (0 to
15 cm depth) equilibrium pH. Equilibrium pH is the pH measured
approximately 2 months after treatment for plant-cane crops
(location 1 = 53 DAT; location 2 = 66) and mid-season for ratoon
crops (location 1 = 922 DAT; location 2 = 534 DAT).
i

0.8

S*0

0O 4

0

0.6 h-

0.4

0.2

Y = -3.62 + 1.49*X 0.12*X, R = 0.68
Y maximum at X = 6.0

I I

4.5

5 5.5 6
Equilibrium pH

6.5

Page 51

0*
4)
0)

i
I'*
(3

Table 1. Selected chemical analyses of amendment materials.

Amendment

Carbonates

---- g kg' ---- %
Calcite 211 4.4 90.2 8.85
Dolomite 148 80.1 91.3 8.38
Gypsum 118 0.1 64.3 5.84

t 1:1 amendment:water slurry.

Page 52

pHt

Table 2. Soil pH and extractable Ca and Mg in acidic sandy solts amended with calcite, dolomite, or gypsum.

Calcite

Dolomite

Gypsum

Depth Rate pH Ca Ma Rate p Ca Mg Rate pH Ca Ng
cm t/ha -- ypg/m t/lha "- jpg/ml- t/ha --- g/mt --

Location 1
103 DATt
0 15 0 4.3 165 10.3 0 4.3 165 10.3 0 4.3 165 10.3
1.1 4.9 358 12.4 1.1 4.9 181 20.0 1.9 4.5 172 9.7
2.2 5.2 363 10.9 2.2 5.0 208 36.2 3.8 4.3 220 9.1
4.4 5.6 428 12.6 4.4 5.3 269 58.2 7.6 4.4 288 10.0
** ns ** ** ** ns ** ns

15 30 0 5.1 141 6.5 0 5.1 141 6.5 0 5.1 141 6.5
1.1 5.3 166 7.6 1.1 5.3 143 9.1 1.9 5.1 155 8.5
2.2 5.4 260 8.5 2.2 5.1 131 9.1 3.8 5.0 175 6.8
4.4 5.3 151 7.1 4.4 5.3 164 12.4 7.6 5.1 209 8.5
ns ns ns ns ns ** ns ns

922 DAT
0 15 0 4.5 86 13.5 0 4.5 86 13.5 0 4.5 86 13.5
1.1 4.7 125 19.1 1.1 4.9 125 25.3 1.9 4.4 94 14.7
2.2 5.0 167 14.4 2.2 5.1 166 37.4 3.8 4.4 98 14.7
4.4 5.6 211 13.8 4.4 5.5 247 62.6 7.6 4.6 121 14.4
** ** rn ** ** ** ns ** na

15 30 0 4.2 86 12.9 0 4.2 86 12.9 0 4.2 86 12.9
1.1 4.6 117 15.3 1.1 4.6 99 19.1 1.9 4.3 93 13.5
2.2 4.9 167 14.4 2.2 4.9 111 24.7 3.8 4.3 105 14.4
4.4 5.6 204 13.2 4.4 5.5 167 40.3 7.6 4.3 111 11.2
** ** ns ** ** ** ns ** ns

Location 2
220 DAT
0- 15 0 4.9 64 5.9 0 4.9 64 5.9 0 4.9 64 5.9
1.1 5.7 121 8.8 1.1 5.9 90 22.6 1.9 4.7 92 6.2
2.2 6.1 157 7.6 2.2 6.4 183 61.8 3.8 4.6 145 5.3
4.4 6.7 236 9.4 4.4 6.7 226 92.9 7.6 4.3 264 5.9
** ** ns ** ** ** ** ** ns

15 30 0 4.9 51 5.9 0 4.9 51 5.9 0 4.9 51 5.9
1.1 5.3 76 7.1 1.1 5.4 51 11.5 1.9 4.8 69 5.3
2.2 5.4 79 5.6 2.2 5.8 87 22.4 3.8 4.7 97 4.7
4.4 5.9 99 6.2 4.4 6.0 67 20.9 7.6 4.4 142 4.7
** ** ns ** ns ** ** ns

534 DAT
0 15 0 4.5 64 7.9 0 4.5 64 7.9 0 4.5 64 7.9
1.1 4.9 112 9.1 1.1 5.2 111 30.6 1.9 4.6 85 9.1
2.2 5.2 113 7.4 2.2 5.9 152 36.2 3.8 4.5 83 5.6
4.4 6.0 222 9.4 4.4 6.2 175 77.4 7.6 4.5 119 5.9
** ** ln ** ** ** ns ** ns

15 30 0 4.8 50 6.2 0 4.8 50 6.2 0 4.8 50 6.2
1.1 4.9 70 7.6 1.1 5.0 53 11.8 1.9 4.7 52 6.5
2.2 4.9 64 6.2 2.2 5.3 76 15.9 3.8 4.6 56 5.0
4.4 5.1 78 6.5 4.4 5.8 72 21.5 7.6 4.5 72 5.9
ns ns ns ** ** ns no
**, *, ns Linear regression over amendment rates are significant at P < 0.01, 0.05, and not significant (P > 0.05),
respectively.
t AT = days after treatment.

Page 53

Table 3. Acetic acid extractable P (Pa) and water extractable P (Pw) In an acidic sandy soil (Location 1)
922 days after amendment with calcite, dolomite, or gypsum.

Calcite

Dolomite

Depth Rate Pa Pw Rate Pa Pw Rate Pa Pw
cm t/ha g/ml-- t/ha jg/mt t/ha fg/t---

0 15 0 1.4 1.1 0 1.4 1.1 0 1.4 1.1
1.1 2.4 1.6 1.1 2.4 1.7 1.9 1.0 0.9
2.2 3.5 1.5 2.2 .2.1 1.2 3.8 1.7 1.5
4.4 3.4 1.3 4.4 3.7 1.4 7.6 1.6 1.4
ns ** ns ns
15 30 0 1.4 1.2 0 1.4 1.2 0 1.4 1.2
1.1 1.7 1.3 1.1 2.2 1.4 1.9 1.2 0.9
2.2 3.1 1.4 2.2 2.5 1.5 3.8 1.8 1.5
4.4 2.5 1.2 4.4 3.5 1.4 7.6 1.6 1.2
ns ns ns ns ns
**, *, ns Linear regression over amendment rates are significant at P < 0.01, 0.05, and not significant
(P > 0.05), respectively.

Table 4. Plant cane and ratoon cane yield component responses to rates of soil amendments applied prior to
sugarcane planting. Data shown are means over two locations (n=8).

Plant cane Ratoon cane
Stalk Stalk Mitlable Sugar Stalk Stalk Millable Sugar
Amendment Rate length weight stalks content length weight stalks content

t ha"1 m kg no. hea" kg t1 m kg no. ha1 kg t1

Calcite 0 1.58 0.83 56 610 141 1.14 0.51 46 654 120
1.1 1.72 0.93 57 608 139 1.54 0.71 59 626 127
2.2 1.74 0.94 63 696 141 1.41 0.62 57 350 123
4.4 1.78 0.92 70 592 138 1.58 0.72 65 087 121
Signif.
Linear ns ns ns ns ns ns
quad. ns ns ns ns ns ns ns ns

Dolomite 0 1.58 0.83 56 610 141 1.14 0.51 46 654 120
1.1 1.67 0.94 63 764 140 1.42 0.63 50 735 123
2.2 1.75 0.92 61 824 139 1.39 0.63 55 915 124
4.4 1.86 0.97 67 307 137 1.73 0.85 65 782 126
Signif.
linear ns ns ns ns ** ** t ns
quad. ns ns ns ns ns ns ns ns

ns = not significant (P > 0.10).

Page 54

t, *, ** Regression significant at P < 0.10, 0.05, and 0.01, respectively.

Cypsum

CORRELATION BETWEEN FIBER CONTENT AND JUICE QUALITY

OF SOME CP SUGARCANE VARIETIES

SP. Y. P Tai
USDA-ARS Sugarcane Field Station
Canal Point, Florida

Fiber and sugar are important economic characters of

sugarcane. Information on the relationship between these two

characters would help sugarcane breeders select superior varieties.

Even though the correlation between high sucrose content and high

fiber content is negative in some reports (Brown et al., 1969),

positive correlation between these two characters has been reported

(Hebert, 1972). James and Falgout (1969) also reported that the

S correlation coefficient between fiber and Brix was positive and

significant in progenies of four sugarcane crosses. Information on

the correlation between fiber content and juice quality is still

lacking. The objective of this study was to examine the

correlation between fiber content and juice quality as sugarcane

plants develop toward physiological maturity. Juice quality

includes measurements of Brix, sucrose (%), and purity (%) of

crusher juice.

Data on fiber content and juice quality of 24 clones of the CP

91 series from Stage II of the Canal Point variety development

program were collected in February 1993. Cane stalk samples of

four commercial varieties, CP 65-357, CP 70-1113, CP 70-1527, and

CP 72-1210, which were used as checks for Stage II, were sampled

monthly from October 1992 to February 1993 for the determination of

fiber content and juice quality. The Stage II test was planted in

September 1991.

Page 55

The results obtained from the 24 CP 91 clones indicated that

the correlation coefficients among characters of juice quality

appeared to be very high (Brix vs. sucrose r = 0.91, purity vs.

Brix r = 0.62, and purity vs. sucrose r = 0.88). The correlations

between fiber content and measures of juice quality were low and

not significant (sucrose vs. fiber r = -0.04, Brix vs. fiber r =

0.14, and purity vs. fiber r = -0.22). The low, negative

correlations for sucrose and fiber and for purity and fiber

suggested that these characters were independent or loosely

associated. The CP 89 series also showed similar correlation

between fiber content and sucrose content (Tai, 1991). However,
Brown et al. (1969) reported that the genotypic correlation between

percent sucrose and fiber was highly negative (r = -0.76).

Correlations between two characters may be dependent upon types of

populations and environments of the experiments.

The three measurements of juice quality, Brix, sucrose (%) and
purity (%), of the four CP varieties showed similar trends during

the process of maturation (Fig. 2). All three characters showed

rapid increases up to flowering and then leveled off and finally

started declining.

The trends of fiber content varied among the four commercial
varieties (Fig. 3). The fiber content of CP 70-1133, CP 70-1527

and CP 72-1210 increased markedly during the flowering stage. The

rapid increase of fiber content could be due to the increase of

lignin-like compounds. Cornelison and Cooper (1941) reported with

increase in age there was more and more deposition of lignin-like

compounds in and around fibrovascular tissue up to the time of

Page 56

tasselling. After tasselling, much of the lignin was lost from the

fibrovascular tissue. Among the four varieties examined, the fiber

content of both CP 70-1133 and CP 70-1527 continued to increase

whereas both CP 65-357 and CP 72-1210 declined during or after

flowering. The inconsistent trends of fiber content among

varieties during the maturing stage of sugarcane indicated that

more studies are needed.

ACKNOWLEDGEMENTS

I thank Dr. Raul Perdomo and his staff who assisted me in

collecting the data for this study.

REFERENCES

Brown, A. H. D., J. Daniels, and B. D. H. Latter. 1969.
Quantitative genetics of sugarcane. II. Correlation analysis
of continuous characters in relation to hybrid sugarcane
breeding. Theo. Appl. Genet. 39: 1-10.

Cornelison, A. H., and H. F. Cooper. 1941. Further studies in
nitrogen nutrition. Time-of-application-of-nitrogen test.
Haw. Plant. Rec. 45: 155-178.

Hebert, L. P. 1972. Testing of sugarcane varieties for milling
quality. Proceed., ASSCT, pp. 300-305.

James, N. I., and R. H. Falgout. 1969. Association of five
characters in progenies of four sugarcane crosses. Crop Sci.
9: 88-91.

Tai, P. Y. P. 1991. Sugarcane fiber A renewable resource.
Sugarcane Grower Seminar. Belle Glade EREC Research Report
EV-1991-3, pp. 23-27.

Page 57

SUCROSE VS FIBER

.* 2
+ + +*

+ +++
+ +

SUCROSE

21 +

19 +

23 +

21 +

19 +

17 +

-----------+------- ----* ------------- -.-

13 15 17
SUCROSE

19 21

+ +

+ +

444 4

+ 4

++ +
4

+ +

ra-0.04

--------------------- ---------------------+-
11 23 15 17 19
FIBER

PURITY VS BRIX
PURITY

91 + +
2
+ +

85 + ++
++ + +
++

79 + + +

+ r = 0.62
73 +
-------------+----------------------------+-
16 18 20 22 24
BRIX

PURITY VS SUCROSE

PURITY

BRIX VS FIBER

BRIX

23

21+

19 +

+ +

+ +
2 + +
4 *
2

S 0.1
S T = 0.14

17 +
----+-..... ---------------- .. ----------
11 13 15 17 19
FIBER
PURITY VS FIBER
PURITY

+ + 2
+ +

44 4

4 4

91 +

85 +

79 +

73 +

i+ r O.8
-+--------------+--------------------------
13 15 17 19 21
SUCROSE

4 *+
4 4
* 44

+ + +
+ *

+ r-0.22

-+--------------+------------------ --------4-
11 13 15 17 19
FIBER

Correlation between traits with 24 clones of CP 91
Series of sugarcane selection. Canes were planted
in September 1992 and stalk samples were collected
in February 1993.

Page 58

BRIX

r o0.91

91 +

85

79 +

73

Fig. 1.

BRIX VS SUCROSE

19 --.-CP65-357
---CP70-1133
........ C P 70 -152 7
1 8 -. -- CP72-1210

./ /

1 6 / 1
o II

/

14 /
/
/
13

12 I
10-7-92 11-12-92 12
SAMPLING

S %

FLOWERING

-15-92 1-13-93 2-15-93
DATE

Fig. 2. Trends of sucrose content (%) during
the maturing stage of sugarcane stalks
of four CP varieties.

Page 59

.....CP65-357

Imm

* a ... .

JI

I
I

I
/I

./

FLOWERING

10-7-92 11-12-92 12-
SAMPLING

15-92 1-13-93 2-16-93
DATE

Fig. 3. Trends of fiber content (%) during the
maturing stage of sugarcane stalks of
four CP varieties.

Page 60

NEW SUGARCANE DISEASES IDENTIFIED IN FLORIDA;

DRY TOP ROT AND PURPLE SPOT (RED LEAF SPOT)

J. C. Comstock and J. D. Miller,
USDA-ARS, Sugarcane Field Station
Canal Point, Florida
D. F. Parr,
USDA-ARS, Systematic Botany and Mycology
Beltsville, Maryland
and
J. M. Shine, Jr.
Florida Sugar Cane League
Canal Point, Florida

Dry top rot was first observed at the Sugarcane Field Station

in November, 1991. Symptoms include initial drying of the spindle

leaf tips, subsequent drying out of the entire spindle, and finally

death of individual stalks within a stool. Growth of the upper

internodes of the stalk is reduced and the internodes gradually

taper and desiccate. Eventually the top internodes just below the

spindle leaves shrink and shrivel as if suffering from severe

drought. Vascular bundles located at the base of the plant are

pinkish in infected plants. Microscopic examination reveals large

masses of brownish-orange spores, 17-25 p in diameter, of the

pathogen, Ligniera vasculorum, in the xylem cells. Water flow is

restricted in infected plants.

A second disease, purple spot, which is also called red leaf

spot, was found by Dr. Soto, a visiting plant breeder from

Guatemala, in February, 1993 on several cultivars in Stage II at

the Sugarcane Field Station. This is a minor foliar disease which

is identified by an irregular roundish leaf spot that is a reddish-

purple in color. Pseudothecia of the pathogen, Dimeriella

sacchari, are usually present for microscopic verification.

Variation in cultivar susceptibility to both diseases was noted.
Page 61

REDUCED SOIL INSECTICIDE USE

IN SUGARCANE PLANTED AFTER RICE

Ron Cherry,
Everglades Research and Education Center
Belle Glade, FL

Jerry Powell,
Okeelanta Corporation
South Bay, FL

and

Modesto Ulloa,
New Hope Sugar Cooperative,
Loxahatchee, FL

Soil insect data and yield data were obtained from 10 Florida

sugarcane fields planted after rice production. Soil insecticides

were used at planting for wireworm control except in 12 rows per

field which were planted without insecticides. Within each field,

one pair of plots was sampled for soil insect populations. Each

plot was 20 x 20 meters in size. One plot was selected in an area

of the field with soil insecticide and the other plot in an

adjacent area without soil insecticide.

Yield data were obtained by two methods. First, stalks per

acre were obtained in the summer by counting stalks in six 100 foot

sections of row in each area of insecticide application and each

area of no insecticide application in each field. Second, stalk

weight was obtained in the spring before harvest by weighing four

25 stalk bundles of cane in each area of insecticide application

and each area of no insecticide application in each field.

The following data were obtained from these fields from

November, 1990 to April 1993. Only one wireworm was found in 100

soil samples (50 insecticide and 50 non insecticide) taken when

Page 62

sugarcane fields were planted. Since flooding is known to kill

wireworms, the extremely low wireworm population present at this

time was probably due to the previous flooding of the fields for

rice production. There were no significant differences in wireworm

populations between insecticide applied and insecticide free areas

at 0, 5, 10, or 15 months after planting. Also, there was no

significant difference in stalks per acre, weight per stalk, or

estimated tons of cane per acre between insecticide applied and

insecticide free areas.

During 1992 and 1993, insect data and yield data were also

obtained from 10 additional sugarcane fields planted after rice

production. Five of these fields received soil insecticide

application at planting versus five whole fields which were planted

without soil insecticides. Insect data and yield data showed no

significant differences between fields planted with or without soil

insecticides.

Data for the preceding tests are shown in Table 1 to Table 6.

Additional details may be obtained from the authors.

In summary, both insect data and yield data indicate that in

many cases soil insecticides for wireworm control are not necessary

when planting sugarcane after rice.

This research has been supported by the Florida Sugar Cane

League and Western Palm Beach County Farm Bureau.

Page 63

Table 1. Wireworms in plots in five sugarcane fields planted
November, 1990 after rice production.

Total # Wireworms
After Planting + Insecticide Insecticide

0 months 1 0

5 months 1 1

10 months 8 3

15 months 3 6

Table 2. Yield data from five sugarcane fields planted November,
1990 after rice production.

ftiR TqCA

Field #1
+ Insecticide
- Insecticide

Field #2
+ Insecticide
- Insecticide

Field #3
+ Insecticide
- Insecticide

Field #4
+ Insecticide
- Insecticide

Field #5
+ Insecticide
- Insecticide

33,759
36,227

32,699
33,323

32,699
32,220

30,013
32,292

30,492
29,606

3.773
3.630

3.378
3.368

3.410
3.713

3.478
3.375

3.408
3.380

63.69
65.75

55.23
56.12

55.75
59.82

52.19
54.49

51.96
50.03

Page 64

ry-. Tr

Stalks per Acry

Weight Per Stalk

Table 3. Wireworms in plots in five sugarcane fields planted
January, 1992 after rice production.

After Plantinq

Total # Wireworms
+ Insecticide Insecticide

0 months

5 months

10 months

15 months

May, 1993

Table 4. Yield data from five sugarcane fields planted January,
1992 after rice production.

We~dvwhl Dai, P4-zs11

Field #1
+ Insecticide
- Insecticide

Field #2
+ Insecticide
- Insecticide

Field #3
+ Insecticide
- Insecticide

Field #4
+ Insecticide
- Insecticide

Field #5
+ Insecticide
- Insecticide

28,140
26,397

22,999
23,784

24,742
24,132

21,519
21,940

24,219
22,738

2.980
2.903

2.775
2.825

2.923
2.843

2.980
3.043

2.923
2.920

tB+- mr

41.93
38.91

31.91
33.59

36.16
34.30

32.06
33.38

35.40
33.20

Page 65

Q* Iva V=V- ae-r I- 4 h+ on Q IV r +- WN ~

May, 1993

~~a~t~ D~r ~~r~

Table 5. Wireworms found in ten sugarcane fields planted
November, 1991 after rice production. Five fields
planted entirely either with or without soil
insecticide.

Total # Wireworms
After Planting + Insecticide Insecticide

5 months 2 1

15 months 11 4

Table 6. Yield data in ten sugarcane fields planted November,
1991 after rice production.

Tons of Cane Per Acre
+ Insecticide Insecticide

Fields

1 and 2

3 and 4

5 and 6

7 and 8

9 and 10

65.11

67.47

53.13

72.10

60.06

x = 63.6
se = 3.3

57.94

57.91

56.19

54.52

65.42

58.4
1.9

Page 66

----------- ~----

AVAILABLE CHEMICAL AIDS FOR SUGARCANE 1993

Thomas J. Sohueneman, Extension Agent III
Palm Beach County, Florida

As a separate handout, a 19 page booklet of chemicals that can

be used in Florida sugarcane, other than fertilizer, has been

prepared for producers. The title is the same as this brief

summary. The purpose of this booklet is to combine scattered bits

of information into one source. If a chemical has an application

rate for Florida sugarcane on its label, it is included here. The

efficacy or economics of the product was not questioned. A very

brief summary of each chemical is given, just enough for you to

determine if the chemical may be of use to you.

A 'List of Chemicals' table was added to the beginning of the

publication to serve as a quick reference source. Chemical

additions are as follows; hexazinone, pendimethalin, simazine,

trifluralin, Bacillus thuringiensis, and sulfur. Deletions include

all parathion products and Furadan 5G. Notable formulation

additions or changes include Gramoxone, Roundup WSD, Sencor

Solupak, Dyfonate 2G and 4EC, Dyfonate II 15G and 20G, Mocap EC,

and Thimet 15G and 20G Lock and Load. Many new 'Trade' names

appear as a result of reviewing a large number of 'label' books for

any reference to sugarcane. This also includes the 'Spray

Additive' category. Omissions should be brought to my attention

for inclusion in future revisions of this summary.

As a reminder, atrazine and diazinon 14G have become

restricted use pesticides.

Page 67

Examine your pest problem. Review the alternative control

measures available. If chemical control is warranted, check with

your chemical dealer and read the label before deciding to use a

particular chemical aid.

READ THE LABEL.

This summary is only that, a summary. It in no way replaces

reading the label. Since the label is the law, it is a violation

of federal law to use a chemical in a manner contrary to the label.

You may tank-mix two or more chemicals as long as no

restrictions for that particular combination appear on the label.

Always check for compatibility when working with unfamiliar

pesticides, formulations, or adjuvants.

You may apply a chemical at less than the recommended rate.

This practice has shown to be a leading cause of resistance build-

up.

If a chemical can be applied by aircraft, the label will say

so, along with specific directions.

The 'same' chemical under a different company's label may have

different uses listed.

The pesticides presented in this publication were current with

state and federal regulations at the time of publication. The user

is responsible for determining that the intended pesticide use is

consistent with the directions on the label of the product being

used.

Several formulations of popular pesticides have been omitted

because they are no longer being manufactured or the labels have

Page 68

been canceled. In some cases left over inventory can still be used

but the products are no longer commercially available. Some

products are no longer legal to apply. Check with your dealer if

this question arises. Sources of information used in this

publication were the University of Florida spray guides, product

labels, and commercial chemical company representatives.

Suggestions are welcomed.

The use of trade names in this publication is solely for the

purpose of providing specific information. It is not a guarantee

or warranty of the products named, and does not signify they are

approved to the exclusion of others of similar or suitable

composition.

Page 69

INFLUENCE OF SHORT-TERM FLOODING FOLLOWING PLANTING

ON INITIAL STAND ESTABLISHMENT AND YIELD OF SUGARCANE

R. N. Raid & C. W. Deren
University of Florida, IFAS
Everglades Research and Education Center
Belle Glade, Florida 33430

Sugarcane is normally planted during the months of October

through January in the Everglades Agricultural Area (EAA) of

Florida. Although this period coincides with south Florida's dry

season, rainfalls exceeding 5 cm are not uncommon. Due to the

area's decreasing soil depths and imposed drainage restrictions

with regard to water quality, sugarcane fields may remain saturated

for several days to several weeks following such rainfalls.

Flooded field conditions can adversely affect seedpiece germination

and initial stand establishment of sugarcane. Pineapple disease,

caused by the fungus Ceratocystis paradoxa, has been identified as

an important factor associated with poor stands under such

conditions, although there are undoubtedly others. Since cultivars

may vary in their susceptibility to pineapple disease, it was

hypothesized that cultivars may respond differently when exposed to

short-term flooding following planting. The objective of this

experiment was to investigate the influence of short-term flooding

on the initial stand establishment and yield of four different

cultivars when exposed at various stages of germination.

Page 70

MATERIALS AND METHODS

Field experiments were conducted at the Everglades Research

and Education Center in Belle Glade during the 1991/92 and 1992/93

growing seasons. The first experiment had been previously planted

to sweet corn and the second experiment was planted in a field

previously cropped to sugarcane where natural levels of C. paradoxa

inoculum were known to be present. Four commercially important

sugarcane cultivars were planted on three different planting dates,

each separated by approximately 14-day and 18-day intervals during

the first and second experiments, respectively (Table 1). The 2 X

3 X 4 factorial experiments were planted in a split-split plot

design with flooding as the main plot factor, planting date as the

subplot factor, and cultivar as the sub-subplot factor with six

replications of each treatment. Experimental units consisted of

three rows of sugarcane (25-ft and 35-ft in length during 1991 and

1992, respectively) planted on 5-ft centers and separated by 5-ft

alleys within subplots. Subsequent to the last planting, all

treatments were exposed to either flooded or drained field

conditions. A portable field pump was used to maintain a 4-inch

flooded condition for a 7-day period on the flooded half of the

experiment, which was surrounded by a dike. Given the time that it

took to flood and drain the fields, flooded main plots were at or

exceeding field capacity for approximately a 10-day period. With

the exception of the flooding, all plots were treated equally with

respect to fertilization, weed control, and other cultural

practices. Sugarcane yields during the 1992/93 experiment were

estimated by multiplying the total millable stalk count per

Page 71

experimental unit times the average millable stalk weight of ten

stalks randomly selected from the center row of each unit.

RESULTS AND DISCUSSION

Flooded field conditions had an overall negative influence on

sugarcane stands in both experiments. In the first experiment,

sugarcane stands were reduced by an average of 13.6, 48.1, and 34.1

percent in the first, second, and third plantings, respectively

(Table 2). During 1992/93, stalk populations were reduced by an

average of -0.4, 24.5, and 5.6 percent in the first, second, and

third plantings, respectively (Table 3). Significant flooding X

planting date X cultivar interactions were observed during both

experiments, indicating a differential response by cultivars in

various stages of germination to flooded conditions. Although

generalizations regarding cultivar response are difficult to make,

of the cultivars tested both years, CP72-1210 appeared to be the

cultivar least influenced by flooding. However, noticeable

differences in the response of CL73-239 to flooding during the two

years of study suggest that generalizations regarding cultivar

response are probably risky.

In both experiments, overall stands reductions were highest

for the second planting date. It is very possible that buds

actively germinating but not yet emerged may be the most adversely

affected by flooding. This hypothesis requires further testing.

Stand establishment appeared to be more heavily influenced by

flooding in the first experiment than in the second. Overall

reductions were 31.9 and 9.9 percent, respectively. Differences in

Page 72

seed quality may offer some explanation for this. The first

experiment was planted toward the end of the 1991/92 planting

season, and seed quality was noted to be deteriorating with each

planting. This observation was supported by a decline in stand

establishment with planting date in the nonflooded treatments

(Table 2). Seed quality in the second experiment was much more

consistent.

Stalk biomasses are reported for the second experiment only

(Table 4). Overall, it appeared that flooding had little influence

on millable stalk weights, resulting in a reduction of only 1.5

percent when averaged across planting date and cultivar.

Flooding reduced cane yield by 11.0 percent when averaged

across cultivar and planting date (Table 5). As with stalk

populations, the greatest impact was observed for the second

planting date. Yield reductions relative to the nonflooded control

ranged from 2.0 and 2.3 percent for CL73-239 and CP72-1210, to 17.0

and 22.5 percent for CP72-2086 and CP80-1827, respectively.

In summary, flooded field conditions of relatively short

duration (7-10 days) following planting can reduce stand

establishment, and eventually, sugarcane yield. The amount of

stand reduction will most likely depend on the cultivar planted and

the stage of germination at the time of flooding.

Page 73

Table 1.

Planting dates, cultivars, plot sizes, and flooding dates for
the 1991/92 and 1992/93 experiments.

Year Planting Dates Cultivars Flooding Dates Plot Size

91/92 Feb 27, 1991 CP72-1210 Apr 1 Apr 10 3 rows X 25 ft
Mar 11, 1991 CP80-1827
Mar 25, 1991 CL73-239
CL61-620

92/93 Jan 22, 1992 CP72-1210 Mar 3 Mar 13 3 rows X 35 ft
Feb 10, 1992 CP80-1827
Feb 28, 1992 CL73-239
CP72-2086

Table 2.

Influence of short-term flooding, planting date, and
cultivar on stalk populations (stalks/plot) during the
1991-92 season. Percent reductions with respect to the

nonflooded control are indicated in parentheses.

Planting Date
Cultivar
Cultivar Flooding Date 1 Date 2 Date 3 Mean

CP72-1210 Yes 52.8 19.4 20.3
No 68.7 38.6 18.8
(23.1) (49.7) (-8.0) (21.6)

CP80-1827 Yes 67.1 23.2 10.2
No 58.5 38.2 33.5
(-14.7) (39.3) (69.6) (31.4)

CL73-239 Yes 79.2 25.1 14.6
No 87.1 73.8 44.4
( 9.0) (66.0) (67.1) (47.4)
CL61-620 Yes 44.5 26.1 24.7
No 70.5 41.8 26.7
(36.9) (37.6) ( 7.5) (27.3)

Planting
Date Mean

(13.6)

(48.1)

(34.1)

(31.9)

Page 74

Table 3. Influence of short-term flooding, planting date, and
cultivar on millable stalk populations (stalks/acre)
during the 1992-93 season. Percent reductions with
respect to the nonflooded control are indicated in
parentheses.

Planting Date
Cultivar
Cultivar Flooding Date 1 Date 2 Date 3 Mean

CP72-1210 Yes 21,129 22,997 21,849
No 20,964 25,223 21,047
(-0.5) ( 8.8) (-3.8) ( 1.5)

CP80-1827 Yes 15,405 15,598 17,935
No 16,553 23,066 20,023
( 6.9) (32.4) (10.4) (16.6)

CP72-2086 Yes 22,872 17,023 16,124
No 22,001 24,601 20,438
(-4.0) (30.8) (21.1) (16.0)

CL73-239 Yes 27,200 26,896 29,980
No 26,163 36,258 28,500
(-4.0) (25.8) (-5.2) ( 5.5)

Planting
Date Mean

(-0.4)

(24.5)

( 5.6)

( 9.9)

Page 75

Table 4.

Influence of short-term flooding, planting date, and
cultivar on millable stalk biomass (lbs/stalk) during the
1992-93 season. Percent reductions with respect to the
nonflooded control are indicated in parentheses.

Planting Date
Cultivar
Cultivar Flooding Date 1 Date 2 Date 3 Mean

CP72-1210 Yes 2.71 2.90 2.65
No 2.74 2.78 2.80
( 1.1) (-4.3) ( 5.4) ( 0.7)
CP80-1827 Yes 3.76 3.32 2.98
No 3.77 3.37 3.70
( 0.3) ( 1.5) (19.5) ( 7.1)
CP72-2086 Yes 3.30 3.15 2.87
No 3.43 3.05 2.97
( 3.8) (-3.3) ( 3.4) ( 1.3)
CL73-239 Yes 2.56 2.50 2.34
No 2.68 2.34 2.19
( 4.5) (-7.3) (-6.8) (-3.2)

Planting
Date Mean

( 2.4)

(-3.4)

( 5.4)

( 1.5)

Page 76

Table 5.

Influence of short-term flooding, planting date, and
cultivar on cane yield (tons/acre) during the 1992-93
season. Percent reductions with respect to the
nonflooded control are indicated in parentheses.

Planting Date
Cultivar
Cultivar Flooding Date 1 Date 2 Date 3 Mean

CP72-1210 Yes 28.7 33.5 29.6
No 29.0 35.2 29.9
( 1.0) ( 4.8) ( 1.0) ( 2.3)

CP80-1827 Yes 29.3 26.0 27.4
No 31.6 39.9 36.8
( 7.3) (34.8) (25.5) (22.5)

CP72-2086 Yes 37.6 27.1 23.8
No 38.0 37.6 30.5
( 1.0) (27.9) (22.0) (17.0)

CL73-239 Yes 34.9 34.3 35.2
No 34.9 42.3 31.2
( 0.0) (19.0) (-12.8) ( 2.0)

( 2.3)

Planting
Date Mean

(21.6)

( 8.9)

(11.0)

Page 77

	Copyright
	Title Page
	Table of Contents
	Welcome and acknowledgements
	Canal point variety update (1993)...
	Sugarcane interspecific hybrids...
	Water and nitrogen management effects...
	Preliminary findings and potential...
	Supply response of the Florida...
	Sugarcane response to limestone...
	Correlation between fiber content...
	Reduced soil insecticide use in...
	Available chemical aids for sugarcane...
	Influence of short-term flooding...