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Groundnut is grown throughout the tropics and extended to the subtropical countries. India is the second largest producer of groundnut in the world after China. The fact is that groundnut crops in India, particularly in Karnataka are mainly covered under rain fed situation, which in turn has to depend on the arrival of monsoon, climatic changes and drought. Hence, the productivity level of groundnut crop was erratic. It was in this backdrop, an attempt was made through the present study to examine the growth and instability of groundnut in India and Karnataka by way of analyzing the time series data of 48 years. The results revealed that the level of instability was marginally higher in groundnut area (8.7 %) during period II compared to period I (2.9%) and period III (7.3%). The variation in production and yield of groundnut was higher during the period III compared to period I and II. Change in the mean area is contributing more to change in average production of groundnut in India and in Karnataka followed by interaction between changes in mean area and mean yield. Change in area variance is the predominant component contributing to the change in variance of production of groundnut in India as well as in Karnataka. From the outcome of the result, it is concluded that the researchers and policy makers have to pay more attention to develop location specific cultural practice to increase and sustain groundnut production and yield in the nation.

The groundnut crops in India, particularly in Karnataka are mainly covered under rain fed situation, which in turn has to depend on the arrival of monsoon, climatic changes and drought. Hence, the productivity level of groundnut crop was erratic.

Instability is one of the important decision parameters in development dynamics and more so in the context of agriculture production.

Change in area variance is the predominant component contributing to the change in variance of production of groundnut in India as well as in Karnataka.

The study pertains to Karnataka state and the country as a whole. The time series data pertaining to area, production, productivity of groundnut crop in India and Karnataka were collected from India stat. In view of the limitation of the data, the present study is restricted for a period of 48 years from 1971-72 to 2018-19 for analytical purpose. However, for better understanding of growth performance of groundnut crops and for instability analysis the growth in area, production and productivity were compared before and after introduction of Technology Mission on Oilseeds for the period from 1971-72 to 2018-19 which was further bifurcated into three sub periods

Instability analysis represents the uncertainty, with the help of indicators like Coefficient of variation, Standard deviation and instability index, etc. The instability in area, production and productivity of groundnut was analyzed using the following method suggested by

Where,

_{t}_{t + 1} is for the next year.

This index is unit free and it measures deviations from the underlying trend.

The instability of groundnut in India as well as Karnataka was estimated using the Cuddy- Della Valle index and is commonly used to measure the extent of instability in exports and imports (

The formula is as follows:

Where,

_{x}

^{2} = Coefficient of multiple determination obtained from the time series.

The model of decomposition was developed by Peter, B.R. Hazell in 1982. This model was primarily developed to analyze the instability in Indian cereal production. This method is one among the most common methods of decomposition used till now. In this model, average production and variance of production are decomposed into several components. This model is mainly used for the time series data.

Let

Where,

Thus, it can be noted that, the co-variance between area and yield, as well as changes in the mean area and mean yield, have an effect on average output. The decomposition analysis’ aim is to partition the changes in average output between the first and second periods.

The average production in first period and second period is given by,

And in the second period it is,

Each variable in the second period is expressed as its counterpart in the first plus the change in the variable between the two. For example,

Where,

Thus equation

The change in average production, ∆ (

First period variables can be expressed as second period values less the change between two periods. For example,

This change in average production has four different components (sources of change). These sources include the changes in mean area (

The analysis of the components of change in mean production can be depicted biometrically, on the simple assumption that COV (A, Y) = 0. This method of analysis uses the first period as the base, but an alternative procedure can be developed, based on the second period (Hazell, 1982). Both methods are mathematically correct, but method II combines pure and interaction effects and was not considered for this analysis.

The variance of production, V (Q), can be expressed as,

Where R is a residual term, which is expected to be very small. From equation (

The change in the variance of production can also be decomposed in the analogous way. Taking the variance of production and applying the variance formula given above leads to the decomposition as shown in

Ten sources of change in variance in output can be identified. The components 1, 2, 5 and 6 represents the sources of change in mean output as shown in earlier case of decomposing the average production. But change can also occur through changes in variance of area, yield and the interaction between them.

Among the ten constituents of change in variance of production, the first four represents the pure effect and are of immense importance from variability point of view. The fifth component contributes towards the interaction effect, which is the outcome of simultaneous occurrence in change in mean area and yield. Sixth component represents the change in variability in area, yield and from changes in correlation between area and yield. The seventh and the eighth components refer to second and third degree interaction between changes in mean area, yield and also the variability in them. The last two sources of change are not significant in the present context.

Instability is one of the important decision parameters in development dynamics and more so in the context of agriculture production. Instability in area, production and yield of groundnut has been discussed for India and Karnataka. The instability in area, production and yield of ground in India and Karnataka are presented in

Components of change in average production

Components of change in variance of production

The study concludes that the fluctuation in area, production and yield was noticed in groundnut during the period II (1995-96 to 2015-16) compared to period–I (1975-76 to 1995-96) with respect to instability of groundnut production in Karnataka. The fact that the oil seed crops in Karnataka are mainly covered under rain fed conditions, which in turn has to depend on the arrival of monsoon, climatic changes and drought; the productivity level of groundnut crop was erratic. Availability of quality seeds of improved varieties is one of the major constraints limiting groundnut productivity.

Instability in area, production and productivity of groundnut in India and Karnataka

Components of change in the Average Production of Groundnut in India

The components of variance in the groundnut production in India are given in

It is revealed from

The results of components of change in variance of production of Groundnut in Karnataka are presented in

Components of change in variance of production of Groundnut in India

Components of change in the Average Production of Groundnut in Karnataka

Components of change in variance of production of Groundnut in Karnataka

Instability is one of the important decision parameters in development dynamics and more so in the context of agriculture production. Instability of area, production and yield of groundnut has been discussed in both India and Karnataka. The level of instability was marginally higher in groundnut area (8.7 %) during period II compared to period I (2.9%) and period III (7.3%). The variation in production and yield of groundnut was higher during the period III compared to period I and II. The change in mean area is contributing more to change in average production of groundnut in India and Karnataka followed by interaction between change in mean area and mean yield. Change in area variance is the predominant component contributing to the change in variance of production of groundnut in India as well as in Karnataka. The area under cultivation of groundnut cannot be increased overnight as it is grown in rainfed condition; there is unpredictability in the onset of monsoons, annual rainfall and its distribution over the growing season leading to very low yield. Since groundnut is cultivable throughout the year, the area can be increased with improved cultural practices and improved cultivars contribute radically towards stability and increase of yield in all the cultivating states. From the outcome of the result, it is concluded that the researches and policy makers have to take more attention to develop location specific cultural practice to increase and sustain groundnut production and yield in the nation. Policies and programmes should concentrate on increasing the area under cultivation to include non-traditional areas to increase groundnut production.