Statistical Design and Analysis for Intercropping by Walter T. Federer

By Walter T. Federer

Intercropping is a space of study for which there's a determined want, either in constructing international locations the place everyone is swiftly depleting scarce assets and nonetheless ravenous, and in constructed international locations, the place extra ecologically and economically sound methods of feeding ourselves needs to be developed.The in basic terms released directions for engaging in such study and studying the information were scattered approximately in numerous magazine articles, lots of that are difficult to discover. This publication condenses those equipment and may be immensely precious to agricultural researchers and to the statisticians who aid them layout their experiments and interpret their effects.

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Extra info for Statistical Design and Analysis for Intercropping Experiments: Three or More Crops

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Here, we note that five out of the 8/3, six are lower in yield than the barley sole crop. f. f. ). 4, means of pairs of cultivars are presented. 47 for the barley sole crop seed weight. 1, which is a expected value. f. ) 24 12. 3. 392 relatively large value for χ 2 . This is evidence that mixtures of barley with three of the six species produced higher yields of barley grain than did barley alone or with barley plus one of the six species. 3. Frequency distribution of eˆij . 51. 00. 5. The only significant contrast was in the mean of mixtures of three lines with barley versus √ the√mean of single lines with barley as given by the above t-statistic.

The benefit then would be the value of the supplementary crops, as no extra land is utilized. It is possible and not infrequent that the main crop yields may be increased by the presence of the supplementary crops. For example, in Nigeria, when cassava is intercropped with melons, its yield is actually increased. The reason is that the melons prevent erosion over and above that found in the sole crop cassava. The erosion-control aspects of melons more than offset any competition between melons and cassava for space, water, and nutrients.

U. 8 Scope of Volume II 9 important. s. s may be ineffective because of the intimacy, competition, and mixing ability characteristics required to evaluate a mixture to be used in practice. 4 are reminicent of canonical variates in multivariate analyses. The statistician unfamilar with intercropping might think that multivariate statistical techniques would satisfy the needs of statistical analysis. However, as Federer and Murty (1987) have pointed out, multivariate techniques have very limited usefulness in this area.

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