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Über dieses Buch

Intercropping is a method of sustaining or improving soil structure by growing two or more crops on the same field. It is a technique of wide application and of growing importance for both commercial and subsistence farmers. This textbook provides a comprehensive survey of the design and analysis of intercropping experiments. Its main themes are that techniques such as relative indices make it possible to cover a wide variety of conditions, and that statistical models for density-yield relations enable recommendations to be made to growers of crops. As a result, graduate students and researchers in statistics, biometry, and agriculture whose study involves intercropping will find this an invaluable text and reference.

Inhaltsverzeichnis

Frontmatter

Chapter 1. Introduction and Definitions

Abstract
Intercropping, as the term will be used in this text, is the growing of two or more cultivars, either simultaneously or sequentially on the same area of land. For the most part, we shall confine our attention to the part of intercropping that deals with crops grown on the same area of land at the same time. Many of the concepts and analyses developed and exemplified will be useful for a mixture of cultivars grown at different times on the same unit of land. Intercropping is a centuries-old farming system that has persisted throughout the ages down to the present time. It is used extensively in areas of survival and tropical agriculture and will no doubt become important in temperate zone agriculture. This type of farming is becoming increasingly important for a variety of reasons such as, for example, the increasing costs and ineffectiveness of fungicides, herbicides, fertilizers, and irrigation.
Walter T. Federer

Chapter 2. One Main Crop Grown with a Supplementary Crop

Abstract
In certain agricultural cropping systems, interest centers on growing a particular crop, the main crop; it may be that the yield of this crop is unaffected, or is affected to a small degree if another crop, a supplemental crop, is grown simultaneously, or previously, with the crop of main importance. In such cases, it is necessary to determine the effect of growing the supplemental crop on the main crop yields. In addition, the effects of intercropping need to be assessed over a period of five, ten, or twenty years in comparison with other cropping systems over the same period of time in order to evaluate fully a cropping system. Many responses, e.g., soil erosion, soil structure, insect control, nitrogen fixation, etc., in addition to yield may be needed to fully evaluate the system.
Walter T. Federer

Chapter 3. Both Crops Main Crops—Density Constant—Analyses for Each Crop Separately

Abstract
In the preceding chapter, one crop of the mixture of two crops was considered to be the main crop whose yield was of primary importance. The yield of the second, supplementary, crop was considered to be of secondary importance. The yield of the main crop was not to be reduced or only reduced by a given small percentage if the second crop was to be grown. In the present and following chapters, the two crops of the mixture are considered to be of equal (or specified) importance. That is, the farmer grows both crops as main crops. The two crops need to be evaluated relative to their response in monoculture and in a mixture. The responses of each crop are to be evaluated as is some measure of their joint response. The effect of each crop on the response of the other crop in the mixture needs to be assessed. Within this context, the purpose of the experiment could also include evaluating a number of genotypes of each of the two crops so that best combinations may be chosen for specified climatic conditions. The objectives of these experiments could be maximization of total yield, profit, land utilization, irrigation utilization, insect or disease control, etc., or they could be the study of changes in soil conditions over a period of years for monocultures and for the mixtures of various combinations of the two crops. The objectives might also include an overall evaluation for a combination of previously stated objectives. Different weights could be attached to the various objectives in a given combination.
Walter T. Federer

Chapter 4. Both Crops Main Crops—Density Constant—Combined Crop Responses

Abstract
Up to this point responses from both crops have not been combined. Each crop response has been treated independently. Although this might satisfy some experimenters, it is not useful in evaluating cropping systems and in studying results as a farmer would. He would be interested in some combination of yields, Y 1 and Y 2 , say, from both crops. It would appear that a linear combination of a factor times crop 1 yield plus a factor times crop 2 yield would be the type of combination of value to a farmer. In considering such a trait as value of a crop, the value of crop 1 plus the value of crop 2, say, p 1 Y 1 + p 2 Y 2, would be the response of interest. We could equally well consider Y 1 + p 2 Y 2/p 1 as the response variable since the ratio, p 2/p 1, of values might be more stable over time than the actual vaues.
Walter T. Federer

Chapter 5. Both Crops of Major Interest with Varying Densities

Abstract
In Chapter 2, we considered the simplest possible situation for an intercropping experiment, i.e., one main crop and constant density. In Chapter 3, we considered the next simplest situation, both crops are main crops but the density remains constant whether in monoculture or in an intercrop. In Chapter 4, the yields of both crops were combined in the statistical analysis and results. In the present chapter, we consider intercrop experiments as discussed in the previous chapters with the cropping systems being allowed to vary over a range of densities for each of the two crops. The questions of interest would be similar to those discussed in Chapters 2, 3, and 4, but here additional information on the effect of changing densities on the observed variables would be available.
Walter T. Federer

Chapter 6. Monocultures and Their Pairwise Combinations when Responses Are Available for Each Member of the Combination

Abstract
In the previous chapters we were mainly concerned with comparative procedures for intercropping experiments. The intercropping system in this chapter could be handled by any one of a number of statistical procedures, such as, e.g., multiple comparisons. Since goals of mixture experiments vary, interest could center on biological modeling response equations as well as comparative procedures. In the diallel crossing genetic treatment design, interest centers upon how well a line performs on the average with all the other n - 1 lines (general combining ability), as well as how well a particular cross performs (specific combining ability). For example, a mixture of soybeans and maize has a higher yield than could be obtained from equal acreage of sole crop maize and soybeans. In this chapter, we concentrate on similar types of modeling considerations to assess quantitatively how well a line (or cultivar) mixes or competes with other lines in mixtures of two lines (general mixing or competing ability), and how well or poorly the line performs when in combination with a particular line (specific mixing or competing ability). The response model equations are formulated for the situation wherein responses are available for each member of the mixture. When only one combined response is available for a mixture, different response model equations are necessary; these are dealt with in Chapter 7.
Walter T. Federer

Chapter 7. Monocultures and Their Pairwise Combinations when Separate Crop Responses Are Not Available

Abstract
In Chapter 6, modeling considerations for intercropped experiments were discussed for the situation wherein separate responses are available for each of the two crops in a mixture. There are, however, many situations in agriculture and in other areas for which there is only one response for the mixture for each variable measured. This results from a physical or experimental inability to measure the response of each component of the mixture, but it is still desirable to model the responses as was done in Chapter 6. We do this in the present chapter.
Walter T. Federer

Chapter 8. Spatial and Density Arrangements

Abstract
Research efforts on and use of spatial arrangements, spatial and density arrangements, and variation of intercropped experiments are many and varied. The information that is available is scattered and fragmented throughout published literature. The reader is referred to Mead (1980), Mead and Riley (1981), Mead and Stern (1980), and Veevers and Zafar-Yab (1980, 1982) for spatial arrangements and to Neider (1962), Huxley and Maingu (1978), Wahua and Miller (1978), Willey (1979), and Mead (1979) for density and/or spatial arrangements of intercropping experiments.
Walter T. Federer

Chapter 9. Some Analytical Variations for Intercropping Studies

Abstract
A number of variations of statistical design and analyses have been found in the published literature and are discussed in this chapter. The first topic discussed is a replacement series wherein the ratio of one crop to a second varies from zero to one. In this set-up, a land equivalent ratio (LER) approaches one as the proportion of a crop approaches unity. Some statistical analyses are presented for a set of data involving two wheat varieties where their proportions vary from zero to one.
Walter T. Federer

Chapter 10. Experiment Designs for Intercropping Experiments

Abstract
The following discussion pertains to intercropping experiments such as those described in the preceding chapters, as well as to the design for all comparative experiments. It should be realized that the entire subject of experiment design (the arrangement of treatments in an experiment) cannot be covered in a single chapter or even a single book. We can, however, give some guidelines for the selection and use of experiment designs for some of the simpler intercropping experiments. Some of the experiment designs with less complicated statistical analyses will be illustrated. The ideas in this chapter have been presented and discussed in more detail by Federer (1984).
Walter T. Federer

Backmatter

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