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VII. Nitrogen Recycling via Leaf and Excreta

VII. Nitrogen Recycling via Leaf and Excreta

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FORAGE TREE LEGUMES IN TROPICAL ENVIRONMENTS



47



Blair (1990a),901 kg N ha-' year-' was removed in leaf and stem material

of L . leucocephala, C. calothyrsus, G . sepium, and S . grandijlora when

grown as a monoculture. No difference in grass N yield was recorded

between the grass in monoculture and where it was planted under the tree

legume (Table VII).

In a subsequent glasshouse experiment using a split-root technique with

"N, Catchpoole and Blair (1990b)found that the direct transfer of N from

L . leucocephala and G . sepium was only 9% of the total harvested N yield.

Most workers in the field of nitrogen cycling believe that transfer of

biologically fixed nitrogen from legume to soil predominantly occurs as a

result of leaf fall and subsequent decomposition, or via passage through

grazing animals (Vallis, 1978, 1979).

Substantial leaf fall has been shown to occur in a Leucaena-Gliricidia

plantation by Sajise et al., cited by Van den Beldt (1983),who recorded an

annual litter fall of 1 1.3t DM ha-'. Van den Beldt (1983)found leaf fall in a

"Hawaiian Giant" Leucaena plantation to be 8.5 t DM ha-' year-', with

an average nitrogen content of 1.2%.

The relatively low N content of leaf litter compared to leaf on the plant is

due to mobilization of nitrogen from leaf before abscission occurs. Thus

the nitrogen contribution from tree legumes as shade trees might not be as

high as in an alley cropping situation. There is a strong correlation between

rate of decomposition and the nitrogen content of organic matter (Stevenson, 1986). Consequently, leaf cut from hedgerows with a low C/N ratio

will break down and release N more quickly than abscised leaves with a

high C/N ratio. In addition, it is possible that there will be a greater input of



Table VII

Nitrogen Yields (kg ha-') over a 14-Month Period of Tree/Grass Mixtures

and Monocultures at Gowa, South Sulawesi, Indonesia"



Leaf N yield

Stern N yield

Total legume N yield

Grass (%N)

Grass N Yield

Total edible N Yield

Total N yield

~~



~~



a



Tree

monoculture



Treelgrass

mixture



Grass

monoculture



751 ab

150 a

901 a

752 a

901 a



669 b

132 b

801 b

1.3 a

100 a

769 a

901 a



0.9 b

103 a

103 b

103 b



~



From Catchpole and Blair (1990a).

Means with the same letter are not significantly different ( p < .05).



48



GRAEME BLAIR ET AL.



nitrogen from nitrogen fixation into an alley cropping system because,

according to one theory of symbiotic nitrogen fixation (Bethlenfalvay and

Phillips, 1977; Bethlenfalvay et al., 1978), removal of large quantities of

nitrogen from the legume will increase the demand of the plant for available nitrogen, thus stimulating the rate of N2 fixation.

In addition to increasing the total level of soil nitrogen, leguminous trees

also can increase the availability of nitrogen and other nutrients for uptake

by the companion crop. Tiedemann and Klemmedson (1973) found the

relative yield of grass grown in soil taken from under mesquite (Prosopis

glandulensis) to be 15 times that of intratree soil, whereas the soils differed

in total N by a factor of only 3. Tree legumes are known to have deep

rooting systems, up to 50 m in some instances (Phillips, 1963), thus nutrients in low concentration throughout the soil profile can be taken up by the

tree roots and become concentrated near the soil surface from litter fall and

decomposition (Virginia, 1986). This redistribution of nutrients from deep

soil to the surface increases the supply of nutrients to a shallow-rooted

companion crop but, unlike nitrogen, the total quantity of the nutrient in

the system does not increase.

Tree roots can result in a loosening of the soil and improvement in

porosity, and wind-blown soil particles can be intercepted by the tree

canopy and washed to the ground beneath (Sanchez et al., 1985). Shade

and the protection of the litter layer result in a moderation of soil temperature and dampening of temperature fluctuations, which can lead to more

favorable conditions for microbiological breakdown and release of nutrients from organic matter (Virginia, 1986).

The idea of incorporating tree legumes in fencelines as “living fences”

or on the bunds between rice paddies has won widespread acceptance in

many areas of the tropics. Piggin and Parera (1985) reported that in Timor

large areas of hilly country have been planted to Leucaena leucocephala,

and forage material is cut from these slopes and carried to animals tethered

to horticultural trees (e.g., coffee or coconuts) in backyard gardens. This

has resulted in an apparent improvement in horticultural yields since the

adoption of this practice. It is likely that much of the increased growth is a

result of nitrogen cycled through the animal and returned in feces and urine

to the soil, given the low maintenance requirement of adult ruminants for

nitrogen (Henzell and Ross, 1973). In Java, feces and uneaten leaf falling

through the slatted floors of animal pens is periodically collected and

spread onto neighboring vegetable gardens as fertilizer. Thus, improvement of animal feed quality through the use of tree legumes has ramifications not only for increased animal production, but also for greater crop

yields. However, to date no research to quantify this avenue of nitrogen

contribution from tree legumes in a cut-and-carry management system has

been reported.



FORAGE TREE LEGUMES IN TROPICAL ENVIRONMENTS



49



The use of material cut from tree legumes as fertilizer for nonlegume

crops has long been a practice in many areas of Asia (Brewbaker and

Glover, 1987; Evans and Rotar, 1987a). Traditional “green manuring”

techniques, however, usually involved carrying branches or leaves cut

from trees grown in one area to the intended area for cropping (Bin, 1983),

whereas in an alley cropping system the trimmed foliage does not have to

be camed as far (NAS, 1979).

There has been very little research conducted comparing yields of nonlegume crops within an alley cropping system with yields obtainable from a

monoculture of the crop on a per hectare basis. Hoekstra (1983)conducted

an economic analysis of a simulated alley cropping system in a semiarid

environment based on the assumptions of Torres (1983) that introduction

of Leucaena hedgerows would halve the area available for maize, but at a

rate of increase of 13.5 kg maize ha-’ for every kilogram of organic N

added from Leucaena prunings. Research conducted at the International

Institute of Tropical Agriculture in Nigeria showed that the material cut

from Leucaena hedgerows was able to sustain maize grain yield for two

consecutive years, but with no addition of prunings, maize yield declined

(Kang et al., 1981).



VIII. CONCLUSION

The growing body of literature concerning tree legumes is indicative of

the increasing realization of their potential role in farming systems and

their multiplicity of uses in developing countries. However, much of the

evidence of the high productivity of leguminous trees in the tropics is

indirect and inferential, with a paucity of information from controlled

experimentation and research. There is a need for rigorous information on

management options that can best exploit the potential of various species

of tree legumes. Although much attention has been focused on Leucaena

leucocephala, there has been very little investigative work done on the

potential of other perennial legume species, particularly in areas where soil

and climatic conditions are unsuitable for Leucaena. There are few published reports of long-term comparisons of productivity of several species

at a single site, and virtually no information available on management

strategies for cut-and-carry forage production for genera other than Leucaena. Much of the literature on cutting management of Leucaena for

forage is conflicting, and there are very few reports of the yields of nitrogen

that can be obtained when forage is cut from Leucaena, and little published

information exists on yields of N from other species.

Leguminous trees are already widely used in tropical Third World

countries as sources of timber, fuelwood, forage, and shade for plantation



50



GRAEME BLAIR E T A L .



crops. However, if their role as a source of symbiotically fixed nitrogen is

to be exploited fully, then it is important to have knowledge of their

nitrogen input in the various agricultural systems in which tree legumes are

employed.

Developing countries in the wet and humid tropics have been drawn into

the trap of using a single species of tree legume (Leucaena) by enthusiastic

scientists and agriculturalists. They are now paying the penalty for this as

the psyllid insect devastates large areas. Scientists must show the way

with alternative species and information on their management to obtain

sustainable production.

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ADVANCES IN AGRONOMY, VOL. 44



STATISTICAL ANALYSES OF

MULTI LOCATION TRIALS

Jose Crossa

Biometrics and Statistics Unit

International Maize and Wheat Improvement Center (CIMMYT)

06600 Mexico D. F., Mexico



I. Introduction

11. Conventional Analysis of Variance

A. Limitations

B. Components of Variance

111. Joint Linear Regression

A. Statistical and Biological Limitations

B. Other Measurements of Yield Stability

C. Stability, Risk, and Economic Analysis

IV. Crossover Interactions

V. Multivariate Analyses of Multilocation Trials

A. Principal Components Analysis

B. Principal Coordinates Analysis

C. Factor Analysis

D. Cluster Analysis

VI . AMMI Analysis

A. AMMI Analysis with Predictive Success

VII. Other Methods of Analysis

VIII. General Considerations and Conclusions

References



I. INTRODUCTION

Multilocation trials play an important role in plant breeding and agronomic research. Data from such trials have three main agricultural objectives: ( a )to accurately estimate and predict yield based on limited experimental data; ( b )to determine yield stability and the pattern of response of

genotypes or agronomic treatments across environments; and (c) to provide reliable guidance for selecting the best genotypes or agronomic treatments for planting in future years and at new sites.

Agronomists in particular use multilocation trials to compare combinations of agronomic factors, such as fertilizer levels and plant density, and

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on this basis make recommendations for farmers. Breeders compare different improved genotypes to identify the superior ones.

Variation in yield responses among certain agricultural production alternatives (genotypes, agronomic treatments, and cropping systems), when

evaluated in different environments, is known in the classical sense as

interaction. This interaction is part of the behavior of the genotype

or agronomic treatment and confounds its observed mean performance

with its true value. Assessing any genotype or agronomic treatment

without including its interaction with the environment is incomplete and

thus limits the accuracy of yield estimates. Therefore, a significant portion of the resources of crop breeding and agronomy programs is devoted to determining this interaction through replicated multilocation

trials.

Data collected in multilocation trials are intrinsically complex, having

three fundamental aspects: (a) structural patterns; (b) nonstructural noise;

and (c) relationships among genotypes, environments, and genotypes and

environments considered jointly. Pattern implies that a number of genotypes respond to certain environments in a systematic, significant, and

interpretable manner, whereas noise suggests that the responses are unpredictable and uninterpretable.

The function of the experimental design and statistical analyses of multilocation trials is to eliminate as much as possible of the unexplainable and

extraneous variability (noise) contained in the data. Gauch (1988) mentions that statistical analysis of multilocation trials may have two different

objectives. With the first, postdictiue criteria, a statistical model is constructed for a data set, and success is measured in terms of the model’s

ability to fit this data set, with consideration of parsimony (reduced model

with minimal degrees of freedom). With the second, predictive criteria, the

data from a yield trial are partitioned into (a) data used to construct a

model (modeling data) and (b) data used to validate the model (validation

data). Success is measured in terms of the model’s ability to fit the validation observations. Gauch points out that predictive assessment of a multilocation trial is expected to provide more accurate yield estimates than a

model chosen by postdictive criteria.

Although many countries conduct extensive trials, little attention

has been devoted to the most effective analyses of the data generated.

This chapter reviews some of the conventional statistical analyses

and stability methods for yield trials, Statistical and biological limitations are discussed. New methodologies for analyzing multilocation trials

as well as multivariate analyses for assessing yield stability are presented.



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