|Statement||prepared by Farming Systems Support Project, International Programs, Institute of Food and Agricultural Sciences, University of Florida ; technical editor, John Caldwell ; coordinating editor, Lisette Walecka.|
|Series||FSR/E training units -- v. 2., FSR/E training units -- v. 2.|
|Contributions||Caldwell, John., Walecka, Lisette., Farming Systems Support Project.|
|The Physical Object|
|Pagination||ix, 356 p. :|
|Number of Pages||356|
A Practical Guide to On-Farm Research. Planning an OFR Trial. Well-designed trials follow a systematic approach. A meaningful question or hypothesis is developed. The research project is planned and conducted to objectively (without bias) test the question. Data are carefully measured and recorded. Results are statisticallyFile Size: 56KB. Analysis and interpretation of on-farm experimentation Series Title: FSR/E training units; Participcation manual volume 3 Creator: Caldwell, John S. Taylor, Dan. Walecks, Lisette Farming Systems Support Project Affiliation: University of Florida -- Farming Systems Support Project -- Institute of Food and Agricultural Sciences Place of Publication. Ganj, K., and C. Lightfoot, "Tools for Farmer Participation in On-farm Experiments." Paper given at Research Design Workshop Faizabad UP India February Gedeno, G., "Selecting Representative Farmers and Sites for On-Farm Experimentation." Farming Systems Support Project Newsletter 5(1): The Data-Intensive Farm Management Project was featured in the recent February edition of The Furrow. Precision ag technology is spurring a dramatic change in agricultural research. It’s replacing the time-consuming test plot techniques of the past – the marking flags, tape measures, weigh wagons, and grad students – with today’s.
This was the main text for a Graduate Experimental Design class. I found the book very good especially for agriculture. It is not strictly a recipe book on how to do statistics. If you want that get the Gomez and Gomez book or Little and Hills. This book covers many topics well and has problem sets/5(3). This book is intended for researchers who are insufficiently familiar with the techniques available to draw reliable conclusions from on-farm trials with their unavoidable variability. The emphasis is on experimental aspects of on-farm research to help researchers to arrive at solid conclusions, taking into account, rather than eliminating, variation among by: Strip-trial experimental design was implemented using precision agriculture techniques for the on-farm research (Bramley et al., ; Griffin et al., ). In strip trials, winter wheat was. STATISTICAL METHODOLOGY IN AGRICULTURE AND HORTICULTURE A. Mead Warwick HRI, University of Warwick, U.K Keywords: Variability, experimental design, analysis of variance (ANOVA), regression, generalized linear model (GLM), analysis of deviance, restricted maximum likelihood (REML), spatial data, precision agriculture, on-farm Size: KB.
ISBN: OCLC Number: Description: x, pages: illustrations ; 24 cm. Contents: Basic Principles * The Field Plot * Basic Experimental Designs * Agronomy Trials * Variety Trials * Combined Analysis of Several Experiments * Experiments with Perennial Crops * Pasture Trials * On-Farm Trials Farming Systems Research * Intercropping Research * Appendix * Table 1. A manual is presented on the techniques of on-farm experimentation. Common issues arising from the planning, design and implementation of such research is discussed. Although the emphasis is on the conditions and problems faced by scientists conducting bean research in Africa, the principles involved are generally applicable. The on-farm research process is described and its differences to Cited by: 7. Structuring on-farm experimentation and demonstrations on the basis of what research stations offer is putting the cart before the horse. A thorough assessment of the agronomic and social-economic situation of a certain area is what should drive the experimental agenda of agricultural by: The paper describes the agronomic and statistical principles that form the basis for measuring crop yields in on-farm agroforestry studies. Agroforestry systems differ from agricultural systems because of the presence of tree/crop interfaces and the need for large plots, large borders and long-term monitoring. These differences accentuate the variability of crop performance on by: