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Please use this identifier to cite or link to this item: http://www.erepo.iihr.ernet.in/handle/123456789/67

Title: Statistical model for evolving crop-logging technique in banana
Authors: R, Venugopalan
K S, Shamasundaran
Keywords: Co-efficient of determination
Robusta
Statistical models
Issue Date: 2005
Abstract: Efforts were made in this article to develop robust statistical models to evolve crop-logging technique for identifying best yield indicators of banana (cv robusta), across its different growth stages. Optimum values of the identified variables were also worked out based on various biometrical characters of 200 plants observed at farmer’s field. Statistical models developed and validated showed that at 70 days after planting (DAP), Number of leaves and Plant girth (Co-efficient of determination (R2 ) 88 %) with optimum values as 8 leaves and 15.07 cm were the best yield indicators. While at 126 DAP Plant girth and Number of leaves (R2 89 %) with optimum values as 34.5 cm and 12 leaves and at 185 DAP Plant height and Leaf length (R2 92%) with optimum values as 138.9 cm and 127.3 cm were significant crop-logging parameters. Further, results showed that at 250 DAP Plant height and Plant girth (R2 90%) with optimum values as 159.21 cm and 67.8 cm and at 315 DAP Leaf breadth & Leaf length (R2 81%) with optimum values as 67.2 cm and 164.1 cm were the significant yield predictors. Finally, during harvest stage, i.e. at 375 DAP Number of fingers /bunch and Number of hands/ bunch (R2 99%) with optimum values as 26 fingers /hand and 13 hands/ bunch were the best indicators of crop yield. Identified models were also made robust by removing the effect of multi-collinearity among biometrical characters. Before making a final decision about the model adequacy, randomness assumption about the error term was statistically tested.
URI: http://hdl.handle.net/123456789/67
Appears in Collections:Economics & Statistics

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