This paper has provided insights on the returns to investment in groundnut research and sources of productivity in Gujarat state from 1990-91 to 2011-12. Two outputs and ten inputs have been used to construct total output, total input and total factor productivity index using Tornqvist Theil Index technique. Compound growth rates were worked out using semi-log trend equation. Although the area under groundnut decreased yet, the production and productivity increased significantly at the rate of 5.10 and 5.24 per cent per annum, respectively during the study period. The groundnut registered higher TFP growth of about 2.21 per cent per annum in last two and half decades resulting in annual decline of 0.27 per cent in real cost of production. The Investment on groundnut research generated 27.10 per cent IRR thus, found to be a highly paying proposition. The growth in TFP was remarkably increased in nineties largely contributed by the release of groundnut varieties viz., GG-2 in 1986, GG-20 and GG-12 in 1991, GG-13 in 1994. The government expenditure on research, extension education, irrigation infrastructure and rainfall generated significant returns. The steady growth in TFP needs to be maintained by enhancing the resources which have contributed to productivity. More public and private investments, in under developed regions of the state are needed to strengthen agricultural research and rural infrastructure. The sufficient procurement at MSP is essential to enhance farm income.

: Agriculture is one of the important activities in both the developed and developing countries which provide basic raw materials to human beings and various agro-based industries. It continues to be the mainstay of the Indian economy contributing for 14.50 per cent of GDP and is also an effective antidote to poverty and unemployment. This paper tests the extent of co-integration of wholesale prices of cotton among major markets (Amreli, Rajkot, Gondal, Jamnagar and Junagadh APMC) of Saurashtra region by using Johansen test, examined the causality by granger causality test and also captures the speed of adjustment to deviations in long run equilibrium by using vector error correction model. Monthly wholesale price data were used for the study. The results of the Augmented dickey-fuller (ADF) unit root test for cotton showed that the level data were non-stationary but their first differences were stationary. Hence, all market price series were integrated of the order 1 i.e. I(1). The Johansen's co-integration test revealed that all the markets were integrated in the long run. The Vector error correction model (VECM) revealed that there was long relationship between the prices of all the markets viz., Amreli, Rajkot, Gondal, Jamnagar and Junagadh. The results of Pairwise Granger Causality test revealed that there was a bidirectional influence on prices of

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Onion is one of the most important commercial vegetable crops grown in India. Among the bulb crops onion is the only member grown to a great extent in this country. The historical data on area, production and yield of onion from Gujarat were collected for 26 years from the year 1992-93 to 2017-2018 and analysis was carried out using compound growth rate, Cuddy- Della Vella index and Structural break analysis (Chow test). This study was conducted on onion cultivation in Gujarat for the study period of 1992-93 to 2017-18. To capture the impact of NHM (National Horticulture Mission), the study period was re-categorized into: Pre- NHM Period (1992-93 to 2004-05); Post- NHM Period (2005-06 to 2017-18) and Overall Period (1992-93 to 2017-18). Major onion producing districts of Gujarat were selected for analysis. In case of growth rate and instability the yield was showed negative during study period so, more emphasis should be given to enhance the yield level with the help of innovations and technology in onion cultivation. structural break points plays a vital role regarding the forecasting purpose. For, structural break chow test was carried out, the results revealed that occur of structural break in particular district due to area and yield components used in this study.