Wednesday, 1 June 2016

Availability of Sub-district Crop Yields

Reliable and timely information on crop area, crop production and land use is of great importance to planners and policy makers for efficient agricultural development and for taking decisions on procurement, storage, public distribution, export, import and many other related issues including risk assemment and crop insurnace support. With an increasingly evident trend of decentralised planning and administration, these statistics are needed with as much disaggregation as possible down to the level of village panchayats. India possesses an excellent infrastructure and it has a long-standing tradition of generating a comprehensive series of crop and land use statistics though, of late, there has been a disturbing deterioration in their quality. With most parts of the country having detailed cadastral survey maps, frequently updated land records and the institution of a permanent village reporting agency, the country has all the necessary means to produce reliable and timely statistics.  The performance of the system was quite satisfactory until 2 – 3 decades ago but it has since become dysfunctional essentially due to administrative apathy and inaction. 

Current status on crop area statistics
As the total production of crop is the product of the area under the crop and average yield per hectare, the Crop Production has two major components viz., area sown and average yield. The primary responsibility for collection of statistics on these two aspects rests with the State and Union Territory Governments.
From the point of view of crop area statistics, the States and Union Territories can be classified into three broad groups:
a)      The first category comprises what is called as temporary settled states. The temporary settled states include Andhra Pradesh, Assam (excluding hill districts), Bihar, Chatisgarh, Goa, Gujarat, Haryana, Himachal Pradesh, Jammu and Kashmir, Jharkhand, Karnataka, Madhya Pradesh, Maharashtra, Punjab, Rajasthan, Tamil Nadu, Telangana, Uttaranchal and Uttar Pradesh, and the five Union Territories of Chandigarh, Dadra and Nagar Haveli, Daman and Diu, Delhi and Pondicherry. These states are cadastrally surveyed and having a primary reporting agency for collecting the statistics of crop area. In these states, crop area statistics are being collected by complete enumuration method. The primary worker called Patwari is responsible for collection of Agriculture Statistics in the state. The Agriculture Statistics is coillected through field inspection during each of the agriculture aseason. This exercise is kown as “Girdawari”. The register in which area is recorded is known as “Khasra Register”.
b)      The second category includes states like West Bengal, Prissa and parts of Kerala. These three states are called permanantly settled states. These states are cadastrally surveyed but they do not have primary reporting agency. Area statistics in these states are compiled by sample survey approach through a scheme entitled “Establishment for an Agency for Reporting of Agriculture Statistics” (EARAS) by the regular reporting agency. Every year a sample of 20% villages is selected and the selected villages are completely enumerated for the purpose of reporting crop area statistics. Next year a fresh sample of 20% villages is selected and data collected. Thus, all te villages in the respective state are covered in five years.
c)      The area estimates in the remaining areas of the country i.e., NEH regiona (except Assam) are not based on any systematic approach. Here, the statistics of land records are collected on a sample basis. The revenue/agriculture officer collects the information on the basis of his personal belief and knowledge.
The crop yield estimation in the country is carried out on the basis of sample survey approach. The estimates of yield rates are obtained on the basis of scientifically designed Crop Cutting Experiments (CCE) conducted under a scheme of the Directorate of Economics and Statistics, Ministry of Agriculture (DESMOA) entitled “General Crop Estimation Surveys” (GCES).
Crop area statistics of the temporarily settled areas are comprehensive, being based on the complete enumeration method. They are considered fairly reliable because of the patwari's intimate knowledge of local agriculture and his ready availability in the village.  However, due to an increasing range of functions assigned to the patwari, the girdawari tended to receive low priority. Hence, it was observed that a high degree of negligence in carrying out the girdawari, thereby casting doubt on the reliability of crop area statistics. It is a matter of concern that this has continued on for many years evidently with the knowledge and indulgence of the higher-level officials of the State departments of revenue and land records.
Another deficiency of crop area statistics is that with the development and modernisation of agriculture, several new short duration crops are grown. Although the patwari is required to undertake intermediate crop inspection between the two major kharif and rabi seasons, this does not appear to be done regularly. Even if short duration crops like vegetables, flowers, mushroom, etc. are covered during the crop inspection, they are not listed separately in the final crop abstract but clubbed together under “other crops”.
Current status in crop production
Estimates of crop production are obtained by multiplying the area under crop and the yield rate. The yield rate estimates are based on scientifically designed crop cutting experiments conducted under the General Crop Estimation Survey  (GCES).  The GCES covers around 68 crops (52 food and 16 non-food) in 22 States and 4 Union Territories.  Around 5,00,000 experiments are conducted every year with the help of State revenue and agricultural staff of a rank higher than the primary field staff of the departments.  The survey design adopted is that of a stratified three stage random sampling with tehsil or taluka as the stratum, a village as the first stage unit, a field growing the specified crop as the second stage unit and a plot, usually 5m x 5m, as the ultimate unit. The experiment consists of marking the plot and harvesting and weighing the produce from the plot. These weights form the basic data for yield estimation. The number of experiments and their distribution over the strata are made in a manner to be able to obtain the yield rate estimates with a fair degree of precision at the level of the State and each major crop-growing district.

The method of crop cutting experiments is objective and unbiased and if properly followed provides reliable estimates of yield rates.  In practice, however, the field staff do not strictly adhere to the prescribed procedures and thereby the survey estimates are subject to a variety of non-sampling errors. GCES carries out around 5,00,000 experiments every year; but these are not still adequate to provide usable estimates below the district level.  With the introduction of National Agricultural Insurance Scheme (NAIS) in several States a need is felt for assessment of yields of insured crops at the level of tehsil or C.D. Block and even at the panchayat level. NAIS has, therefore, prescribed additional crop cutting experiments for this purpose at the rate of 16 per block or 8 per panchayat for each insured crop. This imposes an enormous burden on the field agency, increases considerably the non-sampling errors and results in further deterioration of the quality of work. Apart from non-feasibility of carrying out such a huge number of experiments, the recent decision of Government of India that the States should combine GCES and NAIS series of experiments and use them together for framing crop production estimates is fraught with serious consequences.  The objectives of the two series are different and the NAIS series is likely to underestimate yield rates because of local pressure from insured farmers whose interest lies in depressing the crop output. Yet another deficiency in the production statistics is the divergence between the production figures available from different sources especially in respect of cash crops like cotton, oilseeds and horticultural crops.
As yield data is very critical for insurance claim settlement, we tried to improve the deficiencies through use of technology and modeling techniques with the objective of generating sub-district crop yield surfaces for all major crops in the country. So that the insurance companies can calculate the risk involved in underwriting the business. The statistical model that is being used for creating surfaces is Linear Rubber Sheeting with the help of image processing software ERDAS and Global Mapper. Sept-wise procedure for creating paddy yield surfaces, as an example, for the year 2000 kharif is discussed here under following sub sections.


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