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International Journal of Current Microbiology and Applied Sciences (IJCMAS)
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National Academy of Agricultural Sciences (NAAS)
NAAS Score: *5.38 (2019)
[Effective from January 1, 2019]
For more details click here

ICV 2017: 100.00
Index Copernicus ICI Journals Master List 2017 - IJCMAS--ICV 2017: 100.00
For more details click here

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PRINT ISSN : 2319-7692
Online ISSN : 2319-7706
Issues : 12 per year
Publisher : Excellent Publishers
Email : editorijcmas@gmail.com / submit@ijcmas.com
Editor-in-chief: Dr.M.Prakash
Index Copernicus ICV 2017: 100.00
NAAS RATING 2018: 5.38

Int.J.Curr.Microbiol.App.Sci.2019.8(8): 2491-2500
DOI: https://doi.org/10.20546/ijcmas.2019.808.290


Yield Estimation of Rice Crop at Pre-Harvest Stage Using Regression Based Statistical Model for Arwal District, Bihar, India
Ravi Ranjan Kumar*, S.N. Singh, Kiran Kumari and Bhola Nath
Department of Statistics, Mathematics and Computer Application Bihar Agricultural University, Sabour, Bhagalpur, Bihar - 813210, India
*Corresponding author
Abstract:

The estimation of crop yield before harvest helps in different policy making in an order for storage, distribution, marketing, pricing, import-export etc. Crop productions depend on several factors such as weather factors, plant characters and agricultural inputs. The present study was carried out to develop the appropriate statistical model for estimation of rice yield before harvest in the year 2018-19. This research was done on plant biometrical characters along with farmer’s appraisal. Sample survey was done on farmer’s field through multistage stratified random sampling method and recorded fourteen parameters such as X1 (Number of irrigation), X2 (Average plant population), X3 (Average plant height), X4 (Average number of effective tillers), X5 (Average length of panicle), X6 (Average length of flag leaf), X7(Average width of flag leaf), X8 (Average number of filled grain), X9 (Damage due to pest and disease infestations), X10 (Applied nitrogen), X11 (Applied phosphorus), X12 (Applied potassium), X13 (Average plant condition) and Y (Yield). By the help of step-wise regression technique to select thirteen models on the basis of minimum BIC value and then after best models were selected on the basis of minimum AIC value. After regression analysis, one best fitted model was selected on the basis of some important statistics such as RMSE, R2, Adj.R2, C.V, Residual and Cook’s D statistic. However, 10 % observations were kept for model validation test purpose. Model -2(Ȳ= 27.07355-1.69966X1 + 0.25058X2 + 0.24110X4 + 1.28741X5-0.45193X6 + 1.17152X13) had minimum value of coefficient of variation, residual, and student residual which were 6.36430, 0.0000, and -0.0756 respectively. Value of Adj.R2 (0.8197) which indicated the better to fit of variables in the model. After model validation test, the lowest value of MAPE (1.18 – 5.48) were indicated the good precision for model-2. Thus the estimated rice yield in Arwal district is about 33.28 q/ ha for the year 2018-19.


Keywords: Yield estimation, Bio-metrical, Characters of rice, Farmer’s appraisal, Regression technique
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How to cite this article:

Ravi Ranjan Kumar, S.N. Singh, Kiran Kumari and Bhola Nath. 2019. Yield Estimation of Rice Crop at Pre-Harvest Stage Using Regression Based Statistical Model for Arwal District, Bihar, India.Int.J.Curr.Microbiol.App.Sci. 8(8): 2491-2500. doi: https://doi.org/10.20546/ijcmas.2019.808.290