Yield forecasting of sugarcane in Bihar based on biometrical characters

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dc.contributor.advisorKumar, Mahesh
dc.contributor.authorM, Muhammed Irshad
dc.date.accessioned2020-02-07T09:32:39Z
dc.date.available2020-02-07T09:32:39Z
dc.date.issued2019
dc.description.abstractThe present study deals with the development of yield forecast models for sugarcane (Saccharum officianarum) in Bihar based on Biometrical characters. For this research observations on plant biometrical characters such as number of millable canes per 100 m2 (X1), average plant height in cm (X2), average cane girth in cm (X3), average length of third leaves cm (X4), average width of third leaves in cm (X5), average cane perimeter in cm (X6), single cane weight in kg (X7), average plant population per 100 m2(X8), number of irrigations in entire crop season(X9), average number of tillers per 100 m2(X10), application of nitrogen (N) in kg/ha (X11), application of phosphorus (P2O5) in kg/ha (X12), application of potassium (K2O) in kg/ha (X13), disease infestation in percentage (X14) and average plant condition (X15) according to eye estimate, were recorded from 50 farmers fields in which 30 farmers were selected from Samastipur, 10 farmers were selected from West Champaran and 10 farmers were from East Champaran districts of Bihar. Simple random sampling was used for selecting farmer‟s field. All possible regression analyses were carried out to select the best combination of variables on the basis of some important statistics such as, RMSE, CV, R2 and adj- R2 . ̂ -596.51888+ 1. 35081X1-0.84646X2+ 1.08494X4 + 32.1379X5 + 423.25714X7- 6.40145X9 + 0.79303X13-13.20593X15 CV= 4.525, R2 = 0.9385, Adj R2=0.9248, RMSE = 32.269, Standard Error residuals=23.444 Further assessment regarding accuracy of model has been done on comparing the actual yield from 10 % of the observations not included in the model development with their predicted value and results shows close resemblance with the margin of error ranging from (5.91-8.36%). Forecasted yield of sugarcane has been worked out as 847.82 q/ha in Bihar with the help of proposed model. Forewarning models for wilt disease on sugarcane based on climate factors was mainly aimed at to study the behavior of climate factors on wilt of sugarcane, to establish association between climatic factors and wilt diseases of sugarcane in different years in sugarcane growing seasons, to generate forewarning statistical models for prediction of wilt diseases based on climatic factors. Data collection was done on the basis of major sugarcane grown area and also compatibility. The secondary data on wilt incidence (%) of sugarcane along with climate factors were collected for the period from 2008 to 2017 during crop seasons. The climatic factors from 2008 to 20117 in sugarcane growing seasons, the average rainfall distribution varied greatly within sugarcane growing seasons over years (19.5 mm – 78.5 mm). The average minimum temperatures (18.70C – 260C), maximum temperature (300C -310C), morning relative humidity (83.7-87.6%) and evening relative humidity (51.8-85.8%) were observed. Correlation studies revealed that there was positive association between the wilt infestation and weather factors morning relative humidity (0.23) while significant positive correlation with minimum temperature (0.89) and negative association with evening relative humidity (-0.03) while significant positive correlation was showed with maximum rainfall (0.97), maximum temperature (0.629). The Multiple Linear Regression (MLR) model was developed with respect to these factors with R2= 0.969. The MLR models for between years found to be useful in the prediction of wilt incidence of sugarcane. (Ŷ) = -99.498+0.142X1+0.345X2+0.601X3-0.05X4+0.46X5+6.252X6 Data was collected using structured schedule and procedure for quantifying Socio-economic status of sugarcane farmers. The data revealed that more than half of the respondents (52%) were small landholders, respondents had high school and above (86%) education, Majority (78%) of the respondents were belonged to UR category, majority (66%) of the farmers had joint family (less than five Members) and Cent percent of the respondents were following agriculture as their main Occupation. There is a positive correlation between income of the farmer with land holding and education Validation of selected forecasting model (5th model) was done by using forecast error (FE), mean absolute error (MAE), Mean absolute percentage error (MAPE),and mean square error (MSE). All the parameters shows a minimum value for the model 5 Key Word: Pre harvest forecast of sugarcane yield, Biometrical Characters of sugarcane, Farmers appraisal, forewarning of disease, socioeconomic condition of the farmer.en_US
dc.identifier.urihttp://krishikosh.egranth.ac.in/handle/1/5810142700
dc.keywordsStatistics, Economics, Sugarcane, West Champaran, East Champaran, RMSE, CV, R2en_US
dc.language.isoenen_US
dc.pages88p. ; v (Bibliography)en_US
dc.publisherDr. Rajendra Prasad Central Agricultural University, Pusa, Samastipur (Bihar)en_US
dc.subStatisticsen_US
dc.subjectnullen_US
dc.themeYield forecasting of sugarcane in Bihar based on biometrical charactersen_US
dc.these.typeM.Scen_US
dc.titleYield forecasting of sugarcane in Bihar based on biometrical charactersen_US
dc.typeThesisen_US
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