Agricultural Field Experiments

Author : Roger G. Petersen
ISBN : 084938477X
Genre : Technology & Engineering
File Size : 41.66 MB
Format : PDF, Kindle
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This text provides statistical and biometrical procedures for designing, conducting, analyzing and interpreting field experiments. It addresses the most important research topics in agriculture, including agronomy, breeding and pasture trials; farming systems research; and intercropping research.
Category: Technology & Engineering

Statistical Methods For Agricultural Field Experiments

Author : Vijay Katyal
ISBN : 9380235429
Genre : Technology & Engineering
File Size : 79.39 MB
Format : PDF, ePub
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The book consists of 12 chapter. The I is related to terminology in experimental design while the II devoted to completely randomized block design and randomized block design for agricultural experiments in the field. The III is devoted to factorial experiments in randomized block design involving two or more factoThe IV deals with partially confounded and fully confounded factorial experiments. The cheaper V deals with split plot design and strip plot design. The VI deals with repetition of experiments over years with sampling in agricultural trials at cultivator's fields, while VII is related to sustainability of crop sequences and treatments. The VIII deals with analysis of trials at cultivators' fields while the IX deals with sampling techniques. X deals with co-relation and regression studies. The XI spells out the agronomic considerations and synthesis of system based results. The last XII deals with methodology and procedure for farming systems research while the schedule for date collection for farming systems characterization and evaluation is given in appendix.
Category: Technology & Engineering

Application Of Spatial Mixed Model In Agricultural Field Experiment

Author : Dibaba Gemechu
ISBN : 3844393153
Genre :
File Size : 20.59 MB
Format : PDF, Kindle
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Field experiments in agronomy and related disciplines have traditionally been affected by soil heterogeneity. This is because the soil characteristics are typically non-random and show fertility trend, spatial autocorrelation or periodicity. In the same way that spatial modeling is getting popular, robust designs which utilize spatial information are now common. Spatial variation in fertility, moisture, intercepted light, and other environmental factors can bias variety contrasts and inflate residual variation. This book, therefore, is to evaluate the efficiency of spatial statistical analysis in field trials and, particularly, to demonstrate the benefits of the approach when experimental observations are spatially dependent. Three different data sets taken from Ethiopian Agricultural Research Organization were used for the analysis. The analysis should help agronomists and any one else who may be want to analyze spatially related data.