Applied Ecology and Environmental Sciences
ISSN (Print): 2328-3912 ISSN (Online): 2328-3920 Website: http://www.sciepub.com/journal/aees Editor-in-chief: Alejandro González Medina
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Applied Ecology and Environmental Sciences. 2017, 5(2), 49-59
DOI: 10.12691/aees-5-2-4
Open AccessArticle

Using Residual Analysis to Validate Watermelon Date of Planting and Plant Spacings Experiment Models

I.U. OBI1, OKEKE G.C.1, , OSELEBE H.O.1 and T. VANGE2

1Department of Crop Production and Landscape Management, Ebonyi State University, Abakaliki, Ebonyi State, Nigeria

2Department of Plant Breeding and Seed Science, University of Agriculture, Makurdi, Benue State, Nigeria

Pub. Date: November 01, 2017

Cite this paper:
I.U. OBI, OKEKE G.C., OSELEBE H.O. and T. VANGE. Using Residual Analysis to Validate Watermelon Date of Planting and Plant Spacings Experiment Models. Applied Ecology and Environmental Sciences. 2017; 5(2):49-59. doi: 10.12691/aees-5-2-4

Abstract

Picking a model for a problem is a strong task. If the model fits well then it can be used to increase the understanding and learning of the problem and/or for prediction. Several procedures and steps have been adopted by researchers for dates of planting and plant spacing studies to suit their objectives. The ever-proliferation of Statistical steps available to researchers has given room for use of different statistical design for research into finding optimum date of planting and plant spacing for crops. Considering the subtle differences, advantages and disadvantage that these statistical designs brings, the results of such analysis may lead to false conclusion or be less reliable at least for comparative purposes. There is need to look at plant spacing trials again to see the possibility of proffering a statistical model that could be commonly used by researchers. The main purpose of this work is to apply the residual analysis to check the suitability of the series of similar experimental model to describe the effects of date of planting and plant spacings on yield of watermelon with the view of predicting optimum date of planting and plant spacing. Results show that the series of similar experiment methodology is able to model the changes associated with different date of planting and plant spacings. The questions associated with model adequacy were discussed.

Keywords:
dates of planting time of planting planting dates plant spacings watermelon statistical model residual analysis

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