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Experiment code
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16.6.3.21 |
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Experiment Title
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Estimation of Cotton Yield using Two-Phase Sampling approach |
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Research Type
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Departmental Research |
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Experiment Background
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Cotton is a multiple picking crop which is grown in eleven states in India. Cotton is an important fibre yielding crop of global importance. It is one of the most important cash crops and accounts for around 25% of the total global fibre production. It is also known as the “White Gold” or the “King of Fibres”. India also has the distinction of having the largest area under cotton cultivation in the world i.e. about 126.07 lakh hectares. In India, the states of Gujarat (103.84 lakh bales), Maharashtra (83.35 lakh bales) and Telangana (54.44 lakh bales) are the leading cotton producing states having the predominantly tropical wet and dry climate. Cotton crop is harvested in the form of a number of pickings. The total number of pickings may vary from state to state. It varies from 2-3 pickings to 10 pickings. In the raw material consumption basket of the Indian textile industry, the proportion of cotton is around 59%. It plays a major role in sustaining the livelihood of an estimated 5.8 million cotton farmers and 40-50 million people engaged in related activities such as cotton processing and trade.
The existing procedure of estimation of average yield of cotton is based on crop cutting experiment (CCE) conducted under General Crop Estimation Survey (GCES), which utilizes data on all pickings. But this existing procedure is cumbersome and cost prohibitive. The two-phase sampling (double sampling) approach can be gainfully employed in this case by collecting data on picking which has highest correlation with the total picking yield on a larger sample as auxiliary variable and the total picking yield data on smaller sample. Accordingly, a stratified two-stage two phase sampling design is a very effective for the selection of representative sample. An estimation procedure, based on double sampling regression estimator will be used for the estimation of average yield of cotton at district level. This methodology will save cost of the survey significantly and will also be operationally more convenient than GCES procedure. As the traditional system of estimation of crop yield is facing several problems like lack of timely information and reliability of records maintained by the Government agencies. Advent of remote sensing & GIS technology and its great potential in the field of agriculture have opened newer possibilities of improving agricultural statistic system. Remote sensing & GIS technology has been increasingly considered for evolving an objective, standardized and possibly cheaper and faster methodology for crop yield estimation and reducing the number of CCE. |
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Experiment Group
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Social Science |
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Unit Type
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(02)EDUCATION UNIT |
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Unit
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(24)COLLEGE OF AGRICULTURE (WAGHAI) |
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Department
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(342)Statistics and computer Applications |
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BudgetHead
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(338/12402/00)338/05/REG/02465 |
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Objective
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- To estimate the average yield of cotton at district level using double sampling approach.
- To compare the results with the traditional methods of estimation of average yield.
- Optimization of CCE of cotton on the basis of remote sensing and GIS.
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PI Name
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(NAU-EMP-2019-000537)NITIN RAMESH CHANDRA VARSHNEY |
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PI Email
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nitin.caw@nau.in |
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PI Mobile
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9157548912 |
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Year of Approval
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2020 |
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Commencement Year
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2020 |
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Completion Year
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2023 |
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Research Methodology
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